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56
Studies of Air Pollutants and their Impact on Respiratory and Cardiovascular Diseases in the El Paso North Region with Emphasis on Mobile Emissions. Juan Gustavo Arias Ugarte Master in Environmental Science PhD. In Environmental Science & Engineering

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Page 1: Studies of Air Pollutants and their Impact on Respiratory and ...€¦ · Ascarate Park C37 Monitoring Station: The National Ambient Air Quality Standard (NAAQS) for PM 10 and 2.5

Studies of Air Pollutants and their Impact on Respiratory and

Cardiovascular Diseases in the El Paso North Region with Emphasis on

Mobile Emissions

Juan Gustavo Arias Ugarte

Master in Environmental Science

PhD In Environmental Science amp Engineering

OUTLINE

bull ABSTRACT

bull STUDY PROPOSE

bull SIGNIFICANCE OF THE RESEARCH

bull PROBLEM STATEMENT

bull METHODOLOGY

bull RESULT

bull CONCLUSION

bull BIBLIOGRAPHY

ABSTRACTThe focus of this research is the study of mobile emissions in the Paso del Norte (PdN) region with the

objective of establishing an association between mobile emissions and health

This association will allow a comparison of different exposure and risk situations relative to the emission

source (Exhaust and Non-Exhaust Emission) and to the particle size PM 10 (coarse) and PM25

(inhalable) with the adverse effects on respiratory (RD) and cardiovascular diseases (CVD)

The times selected for this study are periods in 2006 and 2010 Two areas associated with high traffic

density were selected highway I-10 in the Chamizal urban area zip code 79905 and Dona Ana

county urban areas zip codes 88021880278807288048 The mobile simulations were performed using

the Motor Vehicle Emission (MOVES model version 2014a) simulating weekly monthly and annual

data of mobile emissions

Estimates of the Health and Economic Effects of Air Pollution in the El PdN region were performed

using the Environmental Benefits Mapping and Analysis Program and GIS Software was used for

visualization purposes

In addition NOx is a major component of mobile emissions and is an ozone precursor Therefore we

have studied its concentrations during high episodes and analyzed the meteorological factors that

also contribute to high NOx and Ozone concentrations and performed corresponding air quality

simulations for the PdN region

Purpose

The purpose of this research was establishing an association between mobile emissions

and health This association will allow a comparison of different exposure and risk

situations relative to the location emission source (Exhaust and Non-Exhaust Emission)

and to the particle size PM 10 (coarse) and PM25 (inhalable) with the adverse effects

on respiratory (RD) and cardiovascular diseases (CVD)

Introduction

The Paso del Norte (PdN) region is

one of the largest metropolitan areas

along the US-Mexico border This

includes El Paso Ciudad Juarez

Mexico Each year over 18 million

vehicles cross the three international

ports of entry between El Paso and

Cuidad Juaacuterez

Approximately one-quarter of the

population in The Paso del Norte

(PdN) region lives close to major

roadways exposing the people to

risks of severe respiratory infections

and cardiovascular diseases (Trainer

M Parrish DD and Goldan PD 2000)

Significance of the Work

Traffic is a major source of mobile emissions causing air pollution

Mobile emissions such as

Exhaust Emissions (Carbon Monoxide Nitrogen Oxides and

Hydrocarbons) and Non-exhaust (Brake and Tire) Particulate

emissions can also be very damaging to health because their tiny

diameter can enter the respiratory system easily and possibly cause

adverse health impacts (pulmonary carcinogen inflammatory and

toxic effect on the lung (IARC 1989 Et al 2013) (Kelly and Fussell

2012) (iron(Fe) copper(Cu) Manganese(Mn) antimony(Sb)

barium(Ba) zinc(Zn)

Therefore the relevance of this research provides a key

knowledge to understand the impacts of traffic emissions on air

quality and the magnitude of public health risks associated with

exposure to mobile emissions

Problem Statement

0

100

200

300

400

500

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31

PM

10 (

μg

m3)

Days

Chamizal C 41

Montly 24 Hours Average

PM-10 measured in micrograms per cubic meter (μgm3)

2006 January

February

March

April

May

June

July

August

September

October

November

The National Ambient Air Quality Standard (NAAQS) for PM was Exceeded in The PdN Region during

2006 2010 Analysis of Chamizal Area Zip Code 79905

These chart illustrates two high spikes that occurred which exceeds the 24 hour average

0

20

40

60

80

100

120

140

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31

PM

25

( μ

gm

3)

Days

Chamizal C 41

Montly 24 Hours Average

PM-25 measured in micrograms per cubic meter (μgm3)

2006 january

February

March

April

May

June

July

August

September

October

November

December

Chamizal C41Monitoring Station The National Ambient Air Quality Standard (NAAQS) for PM 10 and 25 was

exceeded but in 24 hour average The NAAQS for PM 25 for 24-hour average is PM2535 microgmsup3 and PM10 50-

100 microgmsup3 The highest concentration occurred several times PM10(150200300450 microgmsup3)

PM25(4050607080120 microgmsup3 )

Problem Statement

0

100

200

300

400

500

600

700

800

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31

PM

10 (

μg

m3)

Days

Ascarate Park SE C37

Montly 24 Hours Avg PM 10 Exceedences and Maximum

Concentrations 2010 January

February

March

April

May

June

July

August

September

October

November

December

Graph 1 Source TCEQ ( Texas Commission on Environmental Quality) Ascarate Park monitoring station Data 2010

0

20

40

60

80

100

120

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31

PM

25

UG

M3

DAYS

Ascarate Park SE C37

Montly 24 Hours Average

PM-25 measured in micrograms per cubic meter

(μgm3)

2010 JanuaryFebruaryMarchAprilMayJuneJulyAugustSeptemberOctoberNovemberDecember

Graph 2 Source TCEQ ( Texas Commission on Environmental Quality) Ascarate Park monitoring station Data 2010

Ascarate Park C37 Monitoring Station The National Ambient Air Quality Standard (NAAQS) for PM

10 and 25 was exceeded but in 24 hour average The NAAQS for PM 25 for 24-hour average is

PM2535 microgmsup3 and PM10 50-100 microgmsup3 The highest concentration occurred several times

PM10(200250300400600720 microgmsup3) PM25(4090120microgmsup3)

The National Ambient Air Quality Standard (NAAQS) for PM was Exceeded in The PdN Region 2006 2010

Analysis of Ascarate Area Zip Code 79905

These chart is to illustrate there are two high spikes that occurred which exceeds the 24 hour average

Fig Number of registered automobiles in Texas The Statistics show the

number of registered automobiles truck motorcycle in Texas Source

Texas department motor vehicles

Fig More than 61 percent of

US transportation emissionscome from cars and lighttrucks

Fig in US On-roadmobile sourcesconstitute the largestsingle source categoryof air pollution with(327)

Problem Statement

13000000140000001500000016000000170000001800000019000000

Millio

ns

of

Ve

hic

les

Years

Total Growth of Texas Registrations

2001-2012

Total

Vehicles

Registratio

ns

Problem Statement

El Paso Texas and ciudad Juarez currently has commercialmovements through El PasondashCiudad Juarez gateways peaked at715000 trucks in the year 2010 and Approximately 40000 vehicles passthese roads each laborable day

Source US Department of Transportation Bureau of Transportation Statistics 2010

Bridge Number of US-bound

Truck Crossings year 2010

World Trade Bridge 1327479

Pharr ndash Reynosa International Bridge

452821

Ysleta ndash Zaragoza Bridge 379508

Laredo ndash Colombia Solidarity

Bridge

374781

Bridge of the Americas 337609

Veterans International Bridge 177986

Camino Real International Bridge 106423

Del Rio ndash Ciudad Acuna

International Bridge

62966

Progreso International Bridge 42605

Free Trade Bridge 30773

Source CBP

Fig Bridge of the Americas (Puente Cordova)

Publications Review to examine the relationship between exposure to motor vehicle emissions and respiratory and cardiovascular disease

We have analyzed the current literature which have served as the basis for this project

Some studies determined that traffic-related emissions have been recognized as a major contributor to urban air pollution in particular major cities proximity to major roadways and exposure to motor vehicle exhaust and Non-exhaust emissions are associated with increased risks of cardiovascular respiratory and other diseases (Brugge et al 2007 Gan et al 2010 Gauderman et al 2007 Jerrett et al 2009 Laden et al 2007 McConnell et al 2006)

Effect of traffic pollution on respiratory and allergic disease in adults cross-sectional and longitudinal analyses Mar Pujades-Rodriacuteguez Tricia McKeever Sarah Lewis Duncan Whyatt John Britton and Andrea Venn

httpwwwsciencedailycomreleases200811081114081003htm April 2011

Traffic Pollution Increases Asthma in Adults Several research results revealed adults who suffer asthma and were exposed to heavy traffic pollution experienced an 80 per cent increase University of Melbourne Rev Public Health 15 (1994) pp 107ndash132 August 2010

Traffic Pollution Aggravates Symptoms In Asthmatic Children Traffic pollution especially in cities adversely affects respiratory health in children with asthma studies suggest that traffic pollution and diesel particles in particular may have a greater effect on respiratory health than other pollutants httpwwwsciencedailycomreleases200811081114081003htm September 2010

Traffic-related air pollution associated with prevalence of asthma and COPDchronic bronchitis A cross-sectional study in Southern Sweden Anna Lindgren Emilie Stroh Peter Montneacutemery September 2009

Acute respiratory health effects of air pollution on children with asthma in US inner cities Benjamin Vaughn MS Meyer Kattan MD Herman Mitchell PhD May 2008

Comparison of Air QualityndashRelated Mortality Impacts of two Different source of emission Transportation in the United States httpwwwtrborgMainBlurbs166402aspx January 2008

Long-term exposure to traffic-related air pollution and cardiovascular mortality Chen H Goldberg MS Burnett RT Jerrett M Wheeler AJ Villeneuve PJ Source Department of Epidemiology and Biostatistics McGill University Montreal Quebec Canada January 2011

heavy-duty vehicles chemical composition impact of exhaust after treatment and fuel parameters Environ Health Perspect102(suppl 4)13ndash23 (1994)

Particulate Matter

PM is a mixture of solid and liquid particles suspended in the atmosphere

as atmospheric aerosols Mobile Pollutants are formed by chemical

reactions of gaseous components from burning of fossil fuel in vehicles

(Gasoline amp diesel motor vehicles)

Source EPA (2012) United States Environmental Protection Agency

Particulate matter basic information Cited October 30th 2012 Available

online at httpwwwepa govairqualityparticlepollutionbasichtml

Source EPA (2012) United States Environmental Protection Agency Particulate matter basic

information Cited October 30th 2012 Available online at httpwwwepa

govairqualityparticlepollutionbasichtml

PM10 25 Long Term Exposure ndashChronic Health Consequences

These particles are associated with a

variety of problems including

Aggravated asthma Chronic

bronchitis

Decreased lung function

Increased respiratory symptoms

coughing or difficulty breathing

Increased Cardiopulmonary Mortality

Increased Risk of Lung Cancer

Sources of Particulate Matter Emissions from traffic

Diesel exhaust particulate matter

This particulate toxic potential has been associated with serious adverse Health

effects including respiratory symptoms Pulmonary function and cardiovascular

diseases (Geller et al 2006 Bernstein et al 2004)

Brake wear particulate matter

Brake wear particulate matter Chemical content (iron(Fe) copper(Cu) Antimony(Sb) barium(Ba) this type of particulate can cause severe respiratory and cardiovascular damages and it is also known that Sb has been classified as a possible human pulmonary carcinogen by the International Agency for Research on Cancer (IARC 1989 Et al 2013)

Fig images of brake wear particles generated at a road simulation study ( centre lt25 μm right lt10

μm) Source [Kukutschovaacute et al 2011]

Tire wear particulate matter

The tire wear particles of the tires are generated either by frictional forces between the treadand the road pavement The chemical content Fe Cr Pb Ti Cr Cu Zn Sr Y Zr Sn Sb Ba LaCe and Pb)

Fig Examples of near spherical particles PM 10 and 25 which are originate from interaction of tires and pavements Source [Dahl et al 2006]

Study Area

The Paso del Norte (PdN) region Selected two strategic areas of study El Paso County zip code 79905 Urban area and Dona Ana County Zip Code 880218802788072 Rural Restricted urban access (freeways and interstates)

Map of the area of the simulation by the MOVES model in the study area

Geographic Domain Zip Code 79905 Urban Area (El Paso County)

Zip Codes 88021880278807288048 (Dona Ana County)

Urban road Delta Dr St 31o 45rsquo 5637- 106o 27rsquo 1212 10 miles

Cordova Bridge of the Americas 31o 45rsquo 4367- 106o 27rsquo 0506 15 miles

478 Highway interstate 31o 46rsquo 1326- 106o 27rsquo 0327 05 miles

110 Highway interstate 31o 46rsquo 1210- 106o 27rsquo 0066 10 miles

10 Interstate Gateway Blvd 31o 46rsquo 397- 106o 26rsquo 4769 05 miles

Chamizal Loop 478 31o 46rsquo 668- 106o 26rsquo 5456 05 miles

Alameda Loop 20 31o 46rsquo 1323- 106o 27rsquo 0328 10 miles

Paisano Dr St Patriot freeway

route 62

31o 46rsquo 0669- 106o 27rsquo 212 15 miles

St Piedras 31o 46rsquo 1326- 106o 27rsquo 0327 10 miles

Dona Ana County Miles

Interstate 25 32o 23rsquo 0561 -106 48

1054 32o 23rsquo 3434- -

106 48 1054 32o 23rsquo

5660 106 48 4314

50

Geographic domain To obtain the simulation mobile data from modelMOVES2010a was configurated the coordinates selected in the study areas

El Paso County

PM25 Estimation from Aerosol Optical Depth (AOD) using

satellites

We examined the relationship

between Aerosol Optical Depth

(AOD) estimated from satellite data

at 5 km spatial resolution and the

mass of fine particles le25 μm in

aerodynamic diameter (PM25)

monitored on the ground in El PdN

area PM25 data was recorded from

air quality monitoring Chamizal

station (TCEQ) on different periods

Our analysis shows a significant

positive association between AOD

and PM25

Time-series and scatter plots of AOD estimated PM25 and surface PM25

Analysis of the meteorological factors and synoptic conditions leading to a local high

ozone event episode June 12-21 2006

Meteorology plays a critical role in determining atmospheric ozone concentrations A good synoptic scale weather forecast is essential to accurately forecast tropospheric and surface ozone concentrations

Figure 1 The domain configuration and Landuse categories

resolution 25 km domainFigure 2 The Geopotential height at 500 mb Figure 3 depicts the 850 mb at a lower altitude The

white regions observed in the graph correspond to

mountainous areas

Figure 4 Temperature at 2m height

above surface at 22 UTC June 18 2006

36 km resolution

Performance Evaluation

01020304050

Ju

ne

137

130

0

190

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0

Ju

ne

157

130

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190

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0

Ju

ne

187

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10

0

Tem

pe

ratu

re (⁰C

)

Local time (Hrs)

C41 June 13-19 2006

WRF_temperature

(⁰C)

TCEQ_temperature

(⁰C)

01020304050

June1

37

100

0

130

0

160

0

190

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220

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June1

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Rel

ativ

e h

um

idit

y (

)

Local time (Hrs)

C41 June 13-19 2006

WRF_rh () TCEQ_relative humidity ()

0

5

10

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20

June

137 10

13

16

19

22 1 4

June

157 10

13

16

19

22 1 4

June

187 10

13

16

19

22 1 4

Win

d s

pee

d (

ms

Local time(Hrs)

C12 June 13-192006

WRF_wind speed (ms) TCEQ_ wind speed (ms)

We evaluate the WRF modelrsquos performance

by comparing against corresponding

experimental TCEQ data and performing the

required statistical analysis

HYSPLIT Model

HYSPLIT was simulated and showed that the ozone is mostly transported to El Paso from north western and south western US and Mexican regions during the 72 hours duration of the simulation

0

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Ho

url

y o

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pp

b]

0102030405060708090

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b]

June 18th June 19th

Performance Evaluation

01020304050

Ju

ne

137

130

0

190

0

10

0

Ju

ne

157

130

0

190

0

10

0

Ju

ne

187

130

0

190

0

10

0

Tem

pe

ratu

re (⁰C

)

Local time (Hrs)

C41 June 13-19 2006

WRF_temperature

(⁰C)

TCEQ_temperature

(⁰C)

0

50

100

150

June1

37

100

0

130

0

160

0

190

0

220

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10

0

40

0

June1

57

100

0

130

0

160

0

190

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220

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0

40

0

June1

87

100

0

130

0

160

0

190

0

220

0

10

0

40

0Ozo

ne

(pp

b)

Local time (Hrs)

C41 June 13-19 2006

CAMx_ozone (ppbV) TCEQ_ozone (ppb)

0

10

20

30

40

50

June1

37

100

0

130

0

160

0

190

0

220

0

10

0

40

0

June1

57

100

0

130

0

160

0

190

0

220

0

10

0

40

0

June1

87

100

0

130

0

160

0

190

0

220

0

10

0

40

0

Rel

ativ

e h

um

idit

y (

)

Local time (Hrs)

C41 June 13-19 2006

WRF_rh () TCEQ_relative humidity ()

0

5

10

15

20

June

137 10

13

16

19

22 1 4

June

157 10

13

16

19

22 1 4

June

187 10

13

16

19

22 1 4W

ind

sp

eed

(m

sLocal time(Hrs)

C12 June 13-192006

WRF_wind speed (ms) TCEQ_ wind speed (ms)

Methodology

Medical Data The data by weekly monthly and year for daily emergency room and hospital admission for the respiratory

infections (RD) and cardiovascular diseases (CVD) was extracted from hospitals records located in the El PdN

the system includes data on type of admission primary and secondary causes of admissionRESPIRATORY DISEASE

Bronquitis amp Chronic Bronchitis 466 - 4661 491 - 4919

Asthma 463 - 4939

Emphysema 492

Respiratory failure 51881

HEART DISEASE

Accute Myocardial Infarction 410

Coronary Athersclerosis 4140

Other Ischemic Heart Disease 411-4139 4141-4149

Cardiac Dyshythmias 427

Essential hypertension 401

Acute myocardial infarction 410

Congestive Heart Failure 4280 4282-4284

Hypertensive heart disease 402

Table 1 ICD -9 Codes for Respiratory and Cardiovascular Diseases

0

50

100

150

200

250

300

Wee

k 1

Wee

k 2

Wee

k 3

Wee

k 4

Wee

k 5

Wee

k 6

Wee

k 7

Wee

k 8

Wee

k 9

Wee

k 1

0

Wee

k 1

1

Wee

k 1

2

Wee

k 1

3

Wee

k 1

4

Wee

k 1

5

Wee

k 1

6

Wee

k 1

7

Wee

k 1

8

Wee

k 1

9

Wee

k 2

0

Wee

k 2

1

Mo

rb

idit

y D

isch

arg

e fo

r a

ll R

esp

ira

tory

Dis

ease

IC

D-9

(

Ast

hm

aB

ro

nch

itis

)

Weekly Morbidity Discharges of all the Listed Diagnoses for All

Respiratory Disease During WinterSpring 2010

Asthma-Bronchitis

EPA MOVES Model for Estimating Emission

Inventories

Motor Vehicle Emission Simulator (MOVES 2010b) will be configuredin The El Paso North Region for Calculate five categories of PM10

PM25 total Emission inventories from all on-road traffic over a

variety of scales within periods of time selected weeks months

and years

Moves (Motor Vehicle Emission

Simulator)

The emission model is develop using the current equation to calculate direct traffic emissions from

vehicles in the form of PM is

Eext annual emissions are measured in grams of miles traveled by the vehicle (gVMT )

SL is the road surface loading in (gm2)

W is the average weight in tons of the vehicles on the road

K is the particle size multiplier for particle size range (eg gVMT for PM10 when using grams and miles)

P is the 7 number of wet days with at least 0254 mm of precipitation during the averaging period

N is the number of years considered in the averaging period

C is the particle size specific emissions factor in units of interest vehicle direct exhaust brake wear and tirewear

Modeling Simulation Domain and Emissions Scenarios

For simulations of mobile air quality emission inventories a motor vehicle emission simulator EPA (MOVES 2014a) was used

The modeling use input factors divided into seven section

parameters

On-Road Inventory local data

input

Scale

Geographic Bounds

Traffic intensity

Vehicle Type

Pollutants

Road Type

Fuel Types

Figure Source EPA US Environmental Protection Agency 2012- Moves 2010b Model

EPA Moves 2014a The modeling used input factors divided into six section

parameters On-Road Inventory local data input

Geographic Domains CountyNonattainment Area

Vehicle-Miles Traveled (VMT) is the total number of miles driven by all vehicles withina given time period and geographic area

Average speed range from 25 miles per

hour to 65 miles per hour

Vehicle Classes Motorcycle PassengerCarTruks light-duty Commercial Truck(6001-8500 lbs) Buses heave-duty trucksRefuse trucks School Bus Single UnitShort Haul-truck Single Unit Long Haul-truck Long Haul Truck Heavy-DutyVehicles (26001-33000 lbs)

Pollutants

Road TypeRural restricted Acces(Freeways and interstates) Rural and Restricted Acces Urban Restricted Acces Off-Network

Fuel Types Gasoline Diesel Fuel

Specific Road Types

Two road types for running emission from the MOVES can be

selected

(freeways and interstates)

Interior urban Urban

Figure Source EPA US Environmental Protection Agency 2012- Moves 2010b Model

VehiclesEquipment

This panel show which on-road vehicles will be modeled

Figure Source EPA US Environmental Protection Agency 2012- Moves 2010b Model

Long haul truck Short haul truck Inercity bus Ligth comercial truck

Passenger car Passenger truck Refuse truck

School bus Single unit long haul-truck

Single unit short haul-truck

Transit bus

Motor home

Motorcycle

Based on Department of Transportation Highway MOVES will Estimates Traffic

Emissions from Cars Trucks amp Motorcycles

Output Data Moves 2014a

Inventories of PM 10 25 Mobile Emission from all

on-Road Traffic

Exhaust Emission PM 10 25 gramsmile

Brake Wear Emission PM 10 25 gramsmile

Tire wear Emission PM 10 25 gramsmile

Date of Vehicle miles traveled (VMT) for

Day Week Month Year

Total Vehicle population

Vehicle age distribution

Simulation of Mobile Emission in the El PdN Region Zip Code 79905

Figure Total Emissions from road traffic in El Paso TX Area were estimated for PM10

Exhaust and Non exhaust emission in kilogramsmonth (Source EPA MOVES 2014a)

0

10000

20000

30000

40000

50000

PM

10 k

gM

on

th

Months

Monthly PM 10 Exhaust and Non-Exhaust Mobile Emissions 2010

On-Road Urban Restricted Area Zip Code 79905

Primary Exhaust PM 10 (kg) Primary PM 10 Brakewear (kg)

Primary PM 10 Tirewear (kg)

05000

100001500020000250003000035000400004500050000

PM

25

kg

Mo

nth

Months

Monthly PM 25 Exhaust and Non-Exhaust Mobile Emission 2010

On-Road Urban Restricted Area Zip Code 79905

Primary Exhaust PM 25 (kg) Primary PM 25 Brakewear (kg) Primary PM 25Tirewear (kg)

Figure Total Emissions from road traffic in El Paso TX Area were estimated for PM25

Exhaust and Non exhaust emission in kilogramsmonth (Source EPA MOVES 2014a)

Total Emissions from Road Traffic in El Paso County PM1025 Exhaust and Non exhaust Emission in kilogramsmonth

Taking the interests to the health risks related to PM 1025 mobile emission were simulated

Exhaust and Non-exhaust emissions contribute almost equally to total traffic-related PM1025 Emissions (Querol et al 2004 Bukowiecki et al 2009a Amato et al 2011)

Monthly PM 10 25 Exhaust and Non-Exhaust (BrakewearTirewear) Mobile

Emission 2010 On-Road Urban Restricted Area Zip Code 79905

Figure Total Emissions from road traffic in El Paso TX Area were estimated for PM10 25 Exhaust and Non Exhaust mobile

emission in kilograms per month (Source EPA MOVES)

0

10000

20000

30000

40000

50000

January February March April May June July August September October November December

PM

10

25

(K

ilog

ram

s)

Months

Summary- Monthly PM 10 25 Exhaust and Non-Exhaust Mobile

Emission 2010 On-Road Urban Restricted Area Zip Code 79905

Primary Exhaust PM 10 Primary PM 10 Brakewear Primary PM 10 Tirewear

Primary Exhaust PM 25 Primary PM 25 Brakewear Primary PM 25Tirewear

Exhaust Emissions PM1025 is reaching maximum emission 48000-42000 thousand of Kgmonth followedby Brake wear 29000-5000 thousand kgmonth and Tire wear with 9000-2000 kgmonth The results showthat the emissions of PM derived mainly from Exhaust and Brake are significantly higher in Urban Area

Annual Contribution of Mobile Emission PM 1025 (Kg) Zip Code 79905 El

Paso County 2010

Total Primary

Exhaust _PM10

39

Total Primary

Exhaust _PM25

36

Brakewear

particulate_PM10

18

Tirewear

particulate_PM10

4

Brakewear

particulate_PM25

2

Tirewear

particulate_PM25

1

0

5

10

15

20

25

30

35

40

45

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53

Fig Annual Average PM10 Concentrations at the

Chamizal C41 Station and PM1025 mobile

Concentration Zip code 79905

PM10 TCEQ (μgm3) Total Mobile Emission PM10 (Ugm3)

Fig Exhaust Emission is Contributing Approximately 74 of total

PM1025 Mobile Emissions following of Brake wear with 20 and Tire

wear with 5

Annual Average PM1025 ugm3 Mobile Emissions (Moves) 26 Chamizal C41

Monitoring Station (TCEQ Chamizal Station )

Predicting Mobile Emission and VTM

Estimation The PdN Region 2010

44E+09

46E+09

48E+09

5E+09

52E+09

54E+09

56E+09

58E+09

6E+09

62E+09

0

50000

100000

150000

200000

250000

300000

350000

20

10

20

11

20

12

20

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20

14

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25

20

26

20

27

20

28

20

29

20

30

EX

HA

US

T

EM

ISS

ION

MO

BIL

E (

KG

YE

AR

)

YEARS

Predict ing Mobile Exhaust Emission and VTM

Estimation

2010 - 2030 e l PdN Area

Total_ Exhaust PM10 Total_ Exhaust PM25 Distance (Miles)

Fig Predicting Mobile Exhaust PM1025 (kgMonth) Emission and VTM Estimation 2010

- 2030 el PdN Area

44E+09

46E+09

48E+09

5E+09

52E+09

54E+09

56E+09

58E+09

6E+09

62E+09

0

5000000

10000000

15000000

20000000

25000000

30000000

20

10

20

11

20

12

20

13

20

14

20

15

20

16

20

17

20

18

20

21

20

22

20

23

20

24

20

25

20

26

20

27

20

28

20

29

20

30

EX

HA

US

T

EM

ISS

ION

MO

BIL

E (

KG

YE

AR

)

YEARS

Predict ing Mobile Exhaust Emission and

VTM Estimation

2010 - 2030 e l PdN Area

CO NO2 NO NOx Distance

Fig Predicting Mobile Exhaust Emission and VTM Estimation

2010 - 2030 el PdN Area in El Paso TX Area were estimated for

Total CO NOx NO2 NO emission in kilograms per year

(Source EPA MOVES 2014a model)

The simulated Exhaust emissions in the future years shows a trend of reduction of this type of emissions in the

future years one factor should be the new hybrid technology is increasing by 476 since 2010 to 2015 and

use of catalytic converters diesel particulate filters and improved fuels and engines Non-exhaustive sources

will increase in the coming years because there is no control in the material of manufacture composed by Fe

Cu and Mn also not to be able to reduce the number of events of braking (Accelerations and decelerations)

45E+09

5E+09

55E+09

6E+09

65E+09

0

50000

100000

150000

200000

250000

201

0

201

1

201

2

201

3

201

4

201

5

201

6

201

7

201

8

202

1

202

2

202

3

202

4

202

5

202

6

202

7

202

8

202

9

203

0

NO

N-

EX

HA

US

T

EM

ISS

ION

MO

BIL

E

(KG

YE

AR

)

YEARS

Predicting Non Exhaust Mobile

Emission and VTM Estimation

2010 - 2030 el PdN Area

Brake_PM10 Tire_PM10 Distance (Miles)

Fig Predicting Mobile Exhaust PM1025 (kgMonth) Emission and VTM

Estimation 2010 - 2030 el PdN Area

Daily Avg PM1025

Levels of PM Mobile Emission Non-Exhaust -Rush Hour Periods Fall 2010 Zip Code

79905

00

100

200

300

400

500

600

Mo

bil

e P

M1

0 (k

g)

Rush Hours

Daily Avg PM10

Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush Hours

Periods 2010 Zip Code 79905

Total Primary Exhaust

_PM10 WinterSpring

Brakewear

particulate_PM10

WinterSpringTirewear particulate_PM10

WinterSpring

Total Primary Exhaust

_PM10 Summer

Brakewear

particulate_PM10 Summer

Tirewear Particulate_PM10

Summer

Total Primary Exhaust

_PM10 Fall

Brakewear

particulate_PM10 Fall

Tirewear particulate_PM10

Fall

00

50

100

150

200

250

300

350

Mo

bil

e P

M2

5 (k

g)

Rush hours

Daily Avg PM25

Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush

Hours Periods 2010 Zip Code 79905

Total Primary Exhaust _PM25

WinterSpring

Brakewear Particulate_PM25

WinterSpring

Tirewear particulate_PM25

WinterSpring

Total Primary Exhaust _PM25

Summer

Brakewear particulate_PM25

Summer

Tirewear particulate_PM25

Summer

Total Primary Exhaust _PM25

Fall

Brakewear particulate_PM25

Fall

Tirewear particulate_PM25

Fall

Figure Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush Hours Figure Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush Hours

GIS EMISSIONS INVENTORY SYSTEM A geographic information system (GIS) was used to established geographic scenarios with processed images of seasonal mobile

emissions in the PdN region Seasonal mapping is visualized for different types of pollutants Brakewear Exhaust and Tyrewear

Fg Graphics of GIS and Seasonal mobile Emission of particulate matter emission inventory Seasonal emission simulations were performed in kilograms and five contributing inputs factors were identified for

modeling 1) On the composition of the particulate material from different sources such as Exhaust and Non exhaust (Brake wear Tirewear) 2) The Vehicles Equipment clasification were selected according to

the use of gasoline and diesel fuel (motorcycle passenger car Light Duty Vehicles Trucks refuse truck Light Duty Vehicles Light Commercial Truck Light Duty Vehicles School Bus)

Winter Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

120354 67860 19065

Spring Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

139767 86702 24463

Summer Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

94747 62481 17630

Fall Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

75510 45542 12596

251 Descriptive Statistics Data Analysis

Weekly Correlation Analysis of Mobile Emission PM10 (Exhaust-Non-Exhaust) and Respiratory

Diagnoses WinterSpring Summer and Fall 2010

0

2

4

6

8

10

0

50

100

150

200

250

300

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21

Mo

rbid

ity

Dis

ch

arg

e

for

all R

esp

ira

tory

Dis

ea

se

ICD

-9

(A

sth

ma

-Bro

nc

hitis

)

WinterSpring Week

Weekly Avg Mobile PM10 Concentrations during

WinterSpring 2010 and its Influence on Respiratory

Diagnoses

Zip Code 79905

Total Medical data ZIP Code 79902

Total Mobile Emission PM10 (Ugm3)

0

1

2

3

4

5

6

7

0

20

40

60

80

100

Mo

rbid

ity

Dis

ch

arg

e

for

all R

esp

ira

tory

Dis

ea

se

ICD

-9

(Ast

hm

aB

ron

ch

itis

)

Weekly Avg Mobile PM10 Concentrations during

Summer 2010 and its Influence on Respiratory

Diagnoses

Summer 2010 Zip Code 79905

Total Mobile Emission PM10

Hospital Admission (Asthma-Bronchitis)

0

2

4

6

8

10

12

0

20

40

60

80

100

120

140

160

180

200

Mo

rbid

ity

dis

ch

arg

es

for

all r

esp

ira

tory

dis

ea

se

Weekly Avg Mobile PM10 Concentrations

during Fall 2010 and its Influence on Respiratory

Diagnoses

Zip Code 79905

Total Medical data ZIP Code 79902

Total Mobile Emission PM10 (Ugm3)

Mobile(Exhaust-Non-

Exhaust) PM10 and

Asthma-Bronchitis)

Linear R

Square

WinterSpring 734 ndash 39

Summer 614 ndash 32

Fall 548 -29

PM10 Mobile emission (Exhaust-Non-Exhaust)contributed significantly

association to the incidence of RD

Weekly Correlation Analysis of PM 25 Mobile Emission (Exhaust-Non-Exhaust)

and Cardiovascular Diagnoses WinterSpring Summer and Fall 2010

0010203040

00500

100015002000

Wee

k 1

Wee

k 2

Wee

k 3

Wee

k 4

Wee

k 5

Wee

k 6

Wee

k 7

Wee

k 8

Wee

k 9

Wee

k 1

0

Wee

k 1

1

Wee

k 1

2

Wee

k 1

3

Wee

k 1

4

Wee

k 1

5

Wee

k 1

6

Wee

k 1

7

Wee

k 1

8

Wee

k 1

9

Wee

k 2

0

Wee

k 2

1

Morb

idit

y d

isch

arg

es f

or

all

card

iovasc

ula

r d

isea

se

Weekly Avg PM25 Mobile Concentrations during

WinterSpring 2010 and its Influence on all Heart

Diagnoses

Zip Code 79905

Total All Heart Disease PM 25 mobile (μgm3)

0010203040

00

500

1000

1500

Mo

rbid

ity

dis

ch

arg

es

for

all

ca

rdio

va

scu

lar

dis

ea

se

Weeks

CORRELATION BETWEEN MOBILE PM25 ugm3

EXPOSURE TO HEART DISEASES SYMPTOMS

SUMMER SEASON 2010

Total All Heart Disease PM 25 mobile (μgm3)

Figure Statistical Analyses of the Relationship Between PM25 Caused by Traffic Emission( 26 of total Emission) with Heart diseases Source Hospital Admissions for Asthma Acute Bronchitis and Heart diseases in El Paso County zip code 79905 from Texas Health Care

Information Council in Austin Texas (Texas Health Care Information Council 2000)

00

10

20

30

40

0

50

100

150

We

ek 3

6

We

ek 3

7

We

ek 3

8

We

ek 3

9

We

ek 4

0

We

ek 4

1

We

ek 4

2

We

ek 4

3

We

ek 4

4

We

ek 4

5

We

ek 4

6

We

ek 4

7

We

ek 4

8

We

ek 4

9

We

ek 5

0

We

ek 5

1

We

ek 5

2

We

ek 5

3

Mo

rbid

ity

dis

ch

arg

es

for

all

ca

rdio

va

scu

lar

dis

ea

se

CORRELATION BETWEEN MOBILE PM25 ugm3

EXPOSURE TO HEART DISEASES SYMPTOMS FALL

SEASON 2010

Total All Heart Disease PM 25 mobile (μgm3)

Mobile(Exhaust-

Non-Exhaust)

PM10 and

Asthma-

Bronchitis)

Linear R

Square

WinterSpring 833 -42

Summer 620 -32

Fall 501-26

PM10 Mobile

emission (Exhaust-

Non-

Exhaust)contribut

ed significantly

association to the

incidence of CVD

Diseases

Monthly Brake Mobile Emission PM1025 kg During year 2010 and its Influence on

Respiratory Diagnoses Zip Code 79905

00200040006000800010000

010000200003000040000

PM

10

Mo

bile

(K

g)

Months

Monthly Brake Mobile Emission PM10 kg during year

2010 and its Influence on Respiratory Diagnoses

Zip Code 79905

Primary PM 10

Brakewear 00100020003000400050006000

0

1000

2000

3000

4000

PM

25

Mo

bil

e(K

g)

Months

Monthly Brake Mobile Emission PM25 during

year 2010 and its Influence on Heart Diagnoses

Zip Code 79905

Primary PM 25

Brakewear

Heart Diseases

Hospital

Admission

Brake Mobile Emission

PM10 kg Asthma-

Bronchitis)

Brake Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=969 Linear Square R=856

Monthly Mobile Exhaust Emission PM1025 During year 2010 and its Influence on

Respiratory Diagnoses Zip Code 79905

0

200

400

600

800

1000

0

10000

20000

30000

40000

50000

1 3 5 7 9 11

PM

10

(K

g m

on

th)

Months

Monthly Mobile Exhaust Emission PM10 during

year 2010 and its Influence on Respiratory

Diagnoses

Zip Code 79905

Primary Exhaust

PM 10

Respiratory Disease

(Asthma

Bronchitis) Hospital

Admission

0

100

200

300

400

500

600

0

10000

20000

30000

40000

50000

1 2 3 4 5 6 7 8 9 101112

PM

25

(K

g m

on

th)

Months

Monthly Exhaust Mobile Emission PM25 during

year 2010 and its Influence on Heart Diagnoses

Zip Code 79905

Primary Exhaust PM

25

Heart Diseases

Hospital Admission

Exhaust Mobile Emission

PM10 kg Asthma-

Bronchitis)

Exhaust Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=929 Linear Square R=831

Monthly Tire wear Mobile Emission PM1025 During year 2010 and its Influence on Heart

Diagnoses Zip Code 79905

0

100

200

300

400

500

600

700

800

900

0

1000

2000

3000

4000

5000

6000

7000

8000

9000

1 2 3 4 5 6 7 8 9 10 11 12

PM

10

(K

g m

on

th)

Months

Monthly Tirewear Mobile Emission PM10 during year 2010

and its Influence on Heart Diagnoses

Zip Code 79905

Primary PM 10 Tirewear

Mobile Emission

Respiratory Disease

(Asthma Bronchitis)

Hospital Admission

0

100

200

300

400

500

600

0

200

400

600

800

1000

1200

1400

1 2 3 4 5 6 7 8 9 10 11 12

PM

25

(K

g m

on

th)

Months

Monthly Tirewear Mobile Emission PM25 during year 2010

and its Influence on Respiratory Diagnoses

Zip Code 79905

Primary PM 25Tirewear

Mobile Emission

Heart Diseases Hospital

Admission

Exhaust Mobile Emission

PM10 kg Asthma-

Bronchitis)

Exhaust Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=769 Linear Square R=715

Dona Ana County Zip Codes

88021880278807288048

Primary

Exhaust

PM 10 Zip

code

79905

Total

Primary

Exhaust

PM10

Dona Ana

Primary

Exhaust

PM 25 Zip

Code

79905

Total

Primary

Exhaust

PM25

Dona Ana

Series1 430378 111773 391915 102123

0

100000

200000

300000

400000

500000

AX

IS T

ITLE

Annual Comparison of the Mobile

Exhaust Emissions El Paso County

and Dona Ana 2010

Primary

PM 10

Brakewea

r Zip code

79905

Brakewea

r

particulat

e_PM10

Dona Ana

Primary

PM 10

Tirewear

Zip code

79905

Tirewear

particulat

e_PM10

Dona Ana

Series1 262585 48573 73754 11864

050000

100000150000200000250000300000

AX

IS T

ITLE

Annual Comparison of the Mobile

Brakewear Emissions El Paso County

and Dona Ana 2010

Figure Comparison of the Annual Mobile Emissions

of Primary PM10 Non-Exhauts (Brake ) from Dona

Ana County New Mexico and El Paso Texas Units

in KgMonth

Figure Comparison of the Annual Mobile Emissions

of Primary PM10-Exhauts Emission from Dona Ana

County New Mexico and El Paso Texas Units in

KgMonth

Primary

PM 25

Brakewe

ar Ziphellip

Brakewe

ar

particula

te_PMhellip

Primary

PM

25Tirewe

ar Ziphellip

Tirewear

particula

te_PM25

Donahellip

Series1 32645 6071 10919 1779

0

10000

20000

30000

40000

AX

IS T

ITLE

Annual Comparison of the

Mobile Exhaust Emissions El Paso

County and Dona Ana 2010

Figure Comparison of the Annual Mobile Emissions

of Primary PM10-Exhauts Emission from Dona Ana

County New Mexico and El Paso Texas Units in

KgMonth

Monthly Mobile Emission PM1025 kg During year 2006

and its Influence on Respiratory Diagnoses Dona Ana

County Zip Code 880218802788072

0

100

200

300

0

5000

10000

15000

Axi

s Ti

tle

Axis Title

Monthly Mobile Exhaust Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Total PrimaryMobile Exhaust_PM10

All Respiratory ICD-9 (AsthmaBronchitis)

050100150200250300

010002000300040005000

Axi

s Ti

tle

Axis Title

Monthly Mobile Brake Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Brakewearparticulate_PM10

All RespiratoryICD -9 (AsthmaBronchitis)

050100150200250300

0200400600800

10001200

Axi

s Ti

tle

Axis Title

Monthly Mobile Tirewear Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Tirewearparticulate_PM10

All Respiratory ICD -9 (AsthmaBronchitis)

Mobile Exhauts

Emission PM10

kg Asthma-

Bronchitis)

Brake Mobile

Emission PM10

kg and Heart

Diagnoses

Tirewear Mobile

Emission PM10

kg and Heart

Diagnoses

Linear Square

R= 951

Linear Square

R=625

Linear Square

R=525

Mobile Exhauts

Emission PM25

kg Asthma-

Bronchitis)

Brake Mobile

Emission PM25

kg and Heart

Diagnoses

Tirewear Mobile

Emission PM25

kg and Heart

Diagnoses

Linear Square

R= 986

Linear Square

R=691

Linear Square

R=601

Results

The results showed that mobile PM emissions in the urban areas close to urban Road and highways is putting at risk public health

and the proportion of diseases attributable to this exposure is potentially large

Brake wear emissions is much lower in freeways due to significantly reduced number of braking events while tire wear is much

higher in areas where studded tires are used The emission of exhaust gases are much higher in areas where there is a high

vehicular traffic

Brake Mobile

Emission PM10 kg

Asthma-Bronchitis)

Brake Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square

R=969

Linear Square

R=856

Exhaust Mobile

Emission PM10 kg

Asthma-Bronchitis)

Exhaust Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square

R=929

Linear Square

R=831

Tirewear Mobile

Emission PM10 kg

Asthma-Bronchitis)

Tirewear Mobile

Emission PM25 kg

and Heart Diagnoses

Linear Square R=769 Linear Square R=715

Brake Mobile

Emission PM10 kg

and Heart

Diagnoses

Brake Mobile

Emission PM25 kg

and Heart

Diagnoses

Exhaust Mobile

Emission PM10 kg

Asthma-Bronchitis)

Linear Square

R=625

Linear Square

R=691

Linear Square R=

951

Exhaust Mobile

Emission PM25 kg

Asthma-

Bronchitis)

Tire wear Mobile

Emission PM10 kg and

Heart Diagnoses

Tirewear Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square R=

986

Linear Square R=525 Linear Square

R=601

El Paso County

Dona Ana

County

BenMAP-CE

In this analysis the Program of Mapping and Analysis of Environmental Benefits-Community Edition

(BenMAP-CE) was used to Estimate the number and economic value of health impacts resulting from changes

in air pollution PM 25 Ugm3 in The El Paso Area

Health and Economic Benefits associated with the Response of PM25 Emission between

Base Year 2010

Number of Mortalities in 2010 Base Year Based on El Paso County Texas Department of State Health Services

Number of Mortalities in 2010 Base Year Based on El Paso County Texas

Department of State Health Services

cause of death

year

2010

Populatio

n

Affected

Backgro

und

Concentr

ation Pollutant

Rollback

Type

Avoided

Deaths

(

Populatio

n)

alzheimers disease 2010 40716 125 PM25

25

microgmAcircsup3

Rollback 9

diseases of the

heart 2010 15834 125 PM25

25

microgmAcircsup3

Rollback 35

influenza and

neumonia 2010 81432 125 PM25

25

microgmAcircsup3

Rollback 18

acute bronchitis

and bronchiolitis 2010 117624 125 PM25

25

microgmAcircsup3

Rollback 26

chronic lower

respiratory diseases 2010 54288 125 PM25

25

microgmAcircsup3

Rollback 12

The Basin-wide decrease in 4 ugm3 PM25 concentration after this

reduction control

Cause of death year 2010

Populatio

n

Affected

Background

Concentrati

on

Reduc

cion

scena

rio Polluta

nt

Rollback

Type

Avoi

ded

Deat

hs

(

Pop

ulati

on)

economic

benefits

analysis $

Alzheimers

disease 2010 121 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 9 12000

Diseases of the

heart 2010 470 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 35 35000

Influenza and

neumonia 2010 242 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 18 42500

Acute bronchitis

and bronchiolitis 2010 349 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 26 95000

Chronic lower

respiratory

diseases 2010 161 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 12 4500

$1 295000

PM25-related Mortalities Based on BenMAP-CE Estimate in 2010 Base Year with change in the concentrations levels

Health and Economic Benefits associated with the Response of PM25 Emission between

Base Year 2010 Increasing 7 Ugm3

Cause of death year 2010

Population

Affected

Deaths

avoided by

attaining 195

μgm3

standard

Background

Concentrati

on

Pollut

ant

Rollback

Type

Avoided

Deaths (

Populatio

n)

econo

mic

Unben

efits

analysi

s

Alzheimers

disease 2010 4524 195 PM25

25

microgmAcircsup3

Rollback 19 150000

Diseases of the

heart 2010 20358 195 PM25

25

microgmAcircsup3

Rollback 135 450000

Influenza and

neumonia 2010 126672 195 PM25

25

microgmAcircsup3

Rollback 38 525000

Acute bronchitis

and bronchiolitis 2010 162864 195 PM25

25

microgmAcircsup3

Rollback 36 122000

Chronic lower

respiratory

diseases 2010 99528 195 PM25

25

microgmAcircsup3

Rollback 12 650000

Conclusions

An excellent Pearson Correlation was established to analyze the relationship in the relative risks of hospitalization of Respiratory(RD) and cardiovascular (CVD) associated with ambient exposure caused by traffic emission in relation to their size andspecific sources of emission on different scenarios interior a border Urban Rural Urban restricted access (freeways andinterstates)

A significant correlation of PM1025 exposure from mobile emission and hospital admissions for selected Respiratory (RD) andcardiovascular (CVD) diagnoses was established The results showed that PM emissions in urban restricted access (freeways andinterstates) is mainly caused by traffic Therefore people living close to highways are more exposed higher vehicular emissions

Conclusions

We found statistically significant associations between mobile PM25 caused by traffic emission with Respiratory and Cardiovascular Diseases in the study areaSubsequently a correlation between cardio-respiratory mortality is established

A significant correlation of PM1025 exposure from mobile emission and hospital admissions for selected Respiratory (RD) and cardiovascular (CVD) diagnoses isestablished The results showed that PM emissions in urban restricted access (freeways and interstates) is mainly caused by traffic Therefore people living close tohighways receive higher vehicular emissions

The table shows the percentage of PM mobile exposure in the analyzed areas contributing to increase the risk of Respiratory and Cardiovascular Diseases

An examination was conducted of the synoptic and local meteorology for the June 2006 ozone episode using the WRF model to determine how meteorological parametersinfluence the formation transport and dispersion of ozone in the PdN The predominant synoptic feature of the ozone event day was the expansion intensification and slowprogression of an upper-level ridge of high pressure The high ozone episodes are associated with highly stable atmospheres strong temperature inversions with low mixingheights and therefore low mixing volumes Under these conditions emissions such as NOx lead to highly polluted conditions that favor ozone formation

BenMAP Conclusions

We have estimated the number and economic value of health impacts resulting

from changes in air pollution concentrations of PM 25 in the PdN region

Reduction of Pm 25 4 UGm3= Avoided 213 cases respiratory cardiovascular

diseses and Economic Benefits associated with the Response of PM25 Emission + $

1295000

Increase of PM25 7 ugm3 = increasing Dies= 326 economic Unbenefits= 2345000$

Bibliography

1 Dockery DW Pope CAI Xu X Spengler JD Ware JH Fay ME Ferris BG Speizer FE An association between air pollution and mortality in six US cities N Engl J Med 3291753ndash1759 (1993)

2 Samet JM Dominici F Curriero FC Coursac I Zeger SL Fine particulate air pollution and mortality in 20 US cities 1987ndash1994 N Engl J Med 3431742ndash1749 (2000)

3 Nel AE Diaz-Sanchez D Li N The role of particulate pollutants in pulmonary inflammation and asthma evidence for the involvement of organic chemicals and oxidative stress Curr Opin Pulm Med 20017 20ndash26

4 Westerholm R Karl-Erik E Exhaust emissions from lightand heavy-duty vehicles chemical composition impact of exhaust after treatment and fuel parameters Environ Health Perspect 102(suppl 4)13ndash23 (1994)

5 Bascom R Bromberg P Costa D Delvin R Dockery D Frampton M Lambert W Samet J Speizer F Utell

6 Health effects of outdoor air pollution Am J Respir Crit Care Med 1533ndash50 (1996)

7 Chow JC Watson JG Frazier CA Egami RT Goodrich A Ralph C Spatial and temporal source contributions to

8 PM10 and PM25 in Reno NV In PM-10 Implementation of Standards Transactions An APCAEPA International Speciality Conference San Francisco CA (Mathal CV Stonefield DH eds) PittsburghAPCA 1988439ndash457

9 overview In Particulate Matter Health and Regulatory Issues VIP-49 Proceedings of an International Specialty Conference 4ndash6 April 1995 Pittsburgh PA PittsburghAir and Waste Management Association 1995577ndash598

10 Kunzli N Kaiser R Medina S Studnicka M Chanel O

11 Filliger P Herry M Horak F Jr Puybonnieux-Texier V Quenel P et al Public-health impact of outdoor and traffic- related air pollution a European assessment Lancet 356795ndash801 (2000)

Bibliography

1 Sioutas C Delfino RJ Singh M Exposure assessment for atmospheric ultrafine particles (UFP) and implications in epidemiological research Environ Health Perspect 2005113947ndash955

2 Mosleh M Blau PJ Dumitrescu D (2004) Characteristics and morphology of wear particles from laboratory testing of disc brake materials Wear 2561128ndash1134

3 Kuumlnzli N et al (2000) Public-health impact of outdoor and traffi c-related air pollution a European assessment Lancet 356(9232)795ndash801

4 Dora C Phillips M eds (2000) Transport environment and health Copenhagen WHO Regional Office for Europe (WHO Regional Publications European Series No 89 httpwwweurowhointdocumente72015pdf accessed 26 November 2004)

5 Westerholm R Karl-Erik E Exhaust emissions from lightand

6 heavy-duty vehicles chemical composition impact of exhaust after treatment and fuel parameters Environ Health Perspect 102(suppl 4)13ndash23 (1994)

7 Fauser Tjell Mosbaek pigegaard Quantification of tire-Tread particles using extractable Organic Zinc as a Tracer Rubber Chemistry and Technology 1999 969Table shows some literature estimates of the contribution of tire wear to PM10 in air (Panko et al 2013) Gustafsson M Blomqvist G Gudmundsson A Dahl A Swietlicki E Bohgard M Lindbom J Ljungman A

8 Chen Y Shah N Huggins FE and Huffman GP (2006) Microanalysis of Ambient Particles from Lexington Ky by Electron Microscopy Atmos Environ 40 651ndash663

9 Donaldson K Tran CL Jimenez LA Duffin R Newby DE and Mills N (2005) Combustion-derived Nanoparticles A Review of Their Toxicology Following Inhalation Exposure Part Fibre Toxicol 2 10ndash23

10 Su D Serafino A Muller JO Jentoft RE Schlogl R and Fiorito S (2008) Cytotoxicity and Inflammatory Potential of Soot Particles of Low-emission Diesel Engines Environ Sci Technol 42 1761ndash1765

11 Maier KL Alessandrini F Beck-Speier I Hofer TPJ Diabatґe S Bitterle E Stoger T and Jakob T (2008) Health Effects of Ambient Particulate Matter-Biological Mechanisms and Inflammatory Responses to in Vitroand in Vivo Particle Exposures Inhalation Toxicol 20 319ndash337

Page 2: Studies of Air Pollutants and their Impact on Respiratory and ...€¦ · Ascarate Park C37 Monitoring Station: The National Ambient Air Quality Standard (NAAQS) for PM 10 and 2.5

OUTLINE

bull ABSTRACT

bull STUDY PROPOSE

bull SIGNIFICANCE OF THE RESEARCH

bull PROBLEM STATEMENT

bull METHODOLOGY

bull RESULT

bull CONCLUSION

bull BIBLIOGRAPHY

ABSTRACTThe focus of this research is the study of mobile emissions in the Paso del Norte (PdN) region with the

objective of establishing an association between mobile emissions and health

This association will allow a comparison of different exposure and risk situations relative to the emission

source (Exhaust and Non-Exhaust Emission) and to the particle size PM 10 (coarse) and PM25

(inhalable) with the adverse effects on respiratory (RD) and cardiovascular diseases (CVD)

The times selected for this study are periods in 2006 and 2010 Two areas associated with high traffic

density were selected highway I-10 in the Chamizal urban area zip code 79905 and Dona Ana

county urban areas zip codes 88021880278807288048 The mobile simulations were performed using

the Motor Vehicle Emission (MOVES model version 2014a) simulating weekly monthly and annual

data of mobile emissions

Estimates of the Health and Economic Effects of Air Pollution in the El PdN region were performed

using the Environmental Benefits Mapping and Analysis Program and GIS Software was used for

visualization purposes

In addition NOx is a major component of mobile emissions and is an ozone precursor Therefore we

have studied its concentrations during high episodes and analyzed the meteorological factors that

also contribute to high NOx and Ozone concentrations and performed corresponding air quality

simulations for the PdN region

Purpose

The purpose of this research was establishing an association between mobile emissions

and health This association will allow a comparison of different exposure and risk

situations relative to the location emission source (Exhaust and Non-Exhaust Emission)

and to the particle size PM 10 (coarse) and PM25 (inhalable) with the adverse effects

on respiratory (RD) and cardiovascular diseases (CVD)

Introduction

The Paso del Norte (PdN) region is

one of the largest metropolitan areas

along the US-Mexico border This

includes El Paso Ciudad Juarez

Mexico Each year over 18 million

vehicles cross the three international

ports of entry between El Paso and

Cuidad Juaacuterez

Approximately one-quarter of the

population in The Paso del Norte

(PdN) region lives close to major

roadways exposing the people to

risks of severe respiratory infections

and cardiovascular diseases (Trainer

M Parrish DD and Goldan PD 2000)

Significance of the Work

Traffic is a major source of mobile emissions causing air pollution

Mobile emissions such as

Exhaust Emissions (Carbon Monoxide Nitrogen Oxides and

Hydrocarbons) and Non-exhaust (Brake and Tire) Particulate

emissions can also be very damaging to health because their tiny

diameter can enter the respiratory system easily and possibly cause

adverse health impacts (pulmonary carcinogen inflammatory and

toxic effect on the lung (IARC 1989 Et al 2013) (Kelly and Fussell

2012) (iron(Fe) copper(Cu) Manganese(Mn) antimony(Sb)

barium(Ba) zinc(Zn)

Therefore the relevance of this research provides a key

knowledge to understand the impacts of traffic emissions on air

quality and the magnitude of public health risks associated with

exposure to mobile emissions

Problem Statement

0

100

200

300

400

500

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31

PM

10 (

μg

m3)

Days

Chamizal C 41

Montly 24 Hours Average

PM-10 measured in micrograms per cubic meter (μgm3)

2006 January

February

March

April

May

June

July

August

September

October

November

The National Ambient Air Quality Standard (NAAQS) for PM was Exceeded in The PdN Region during

2006 2010 Analysis of Chamizal Area Zip Code 79905

These chart illustrates two high spikes that occurred which exceeds the 24 hour average

0

20

40

60

80

100

120

140

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31

PM

25

( μ

gm

3)

Days

Chamizal C 41

Montly 24 Hours Average

PM-25 measured in micrograms per cubic meter (μgm3)

2006 january

February

March

April

May

June

July

August

September

October

November

December

Chamizal C41Monitoring Station The National Ambient Air Quality Standard (NAAQS) for PM 10 and 25 was

exceeded but in 24 hour average The NAAQS for PM 25 for 24-hour average is PM2535 microgmsup3 and PM10 50-

100 microgmsup3 The highest concentration occurred several times PM10(150200300450 microgmsup3)

PM25(4050607080120 microgmsup3 )

Problem Statement

0

100

200

300

400

500

600

700

800

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31

PM

10 (

μg

m3)

Days

Ascarate Park SE C37

Montly 24 Hours Avg PM 10 Exceedences and Maximum

Concentrations 2010 January

February

March

April

May

June

July

August

September

October

November

December

Graph 1 Source TCEQ ( Texas Commission on Environmental Quality) Ascarate Park monitoring station Data 2010

0

20

40

60

80

100

120

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31

PM

25

UG

M3

DAYS

Ascarate Park SE C37

Montly 24 Hours Average

PM-25 measured in micrograms per cubic meter

(μgm3)

2010 JanuaryFebruaryMarchAprilMayJuneJulyAugustSeptemberOctoberNovemberDecember

Graph 2 Source TCEQ ( Texas Commission on Environmental Quality) Ascarate Park monitoring station Data 2010

Ascarate Park C37 Monitoring Station The National Ambient Air Quality Standard (NAAQS) for PM

10 and 25 was exceeded but in 24 hour average The NAAQS for PM 25 for 24-hour average is

PM2535 microgmsup3 and PM10 50-100 microgmsup3 The highest concentration occurred several times

PM10(200250300400600720 microgmsup3) PM25(4090120microgmsup3)

The National Ambient Air Quality Standard (NAAQS) for PM was Exceeded in The PdN Region 2006 2010

Analysis of Ascarate Area Zip Code 79905

These chart is to illustrate there are two high spikes that occurred which exceeds the 24 hour average

Fig Number of registered automobiles in Texas The Statistics show the

number of registered automobiles truck motorcycle in Texas Source

Texas department motor vehicles

Fig More than 61 percent of

US transportation emissionscome from cars and lighttrucks

Fig in US On-roadmobile sourcesconstitute the largestsingle source categoryof air pollution with(327)

Problem Statement

13000000140000001500000016000000170000001800000019000000

Millio

ns

of

Ve

hic

les

Years

Total Growth of Texas Registrations

2001-2012

Total

Vehicles

Registratio

ns

Problem Statement

El Paso Texas and ciudad Juarez currently has commercialmovements through El PasondashCiudad Juarez gateways peaked at715000 trucks in the year 2010 and Approximately 40000 vehicles passthese roads each laborable day

Source US Department of Transportation Bureau of Transportation Statistics 2010

Bridge Number of US-bound

Truck Crossings year 2010

World Trade Bridge 1327479

Pharr ndash Reynosa International Bridge

452821

Ysleta ndash Zaragoza Bridge 379508

Laredo ndash Colombia Solidarity

Bridge

374781

Bridge of the Americas 337609

Veterans International Bridge 177986

Camino Real International Bridge 106423

Del Rio ndash Ciudad Acuna

International Bridge

62966

Progreso International Bridge 42605

Free Trade Bridge 30773

Source CBP

Fig Bridge of the Americas (Puente Cordova)

Publications Review to examine the relationship between exposure to motor vehicle emissions and respiratory and cardiovascular disease

We have analyzed the current literature which have served as the basis for this project

Some studies determined that traffic-related emissions have been recognized as a major contributor to urban air pollution in particular major cities proximity to major roadways and exposure to motor vehicle exhaust and Non-exhaust emissions are associated with increased risks of cardiovascular respiratory and other diseases (Brugge et al 2007 Gan et al 2010 Gauderman et al 2007 Jerrett et al 2009 Laden et al 2007 McConnell et al 2006)

Effect of traffic pollution on respiratory and allergic disease in adults cross-sectional and longitudinal analyses Mar Pujades-Rodriacuteguez Tricia McKeever Sarah Lewis Duncan Whyatt John Britton and Andrea Venn

httpwwwsciencedailycomreleases200811081114081003htm April 2011

Traffic Pollution Increases Asthma in Adults Several research results revealed adults who suffer asthma and were exposed to heavy traffic pollution experienced an 80 per cent increase University of Melbourne Rev Public Health 15 (1994) pp 107ndash132 August 2010

Traffic Pollution Aggravates Symptoms In Asthmatic Children Traffic pollution especially in cities adversely affects respiratory health in children with asthma studies suggest that traffic pollution and diesel particles in particular may have a greater effect on respiratory health than other pollutants httpwwwsciencedailycomreleases200811081114081003htm September 2010

Traffic-related air pollution associated with prevalence of asthma and COPDchronic bronchitis A cross-sectional study in Southern Sweden Anna Lindgren Emilie Stroh Peter Montneacutemery September 2009

Acute respiratory health effects of air pollution on children with asthma in US inner cities Benjamin Vaughn MS Meyer Kattan MD Herman Mitchell PhD May 2008

Comparison of Air QualityndashRelated Mortality Impacts of two Different source of emission Transportation in the United States httpwwwtrborgMainBlurbs166402aspx January 2008

Long-term exposure to traffic-related air pollution and cardiovascular mortality Chen H Goldberg MS Burnett RT Jerrett M Wheeler AJ Villeneuve PJ Source Department of Epidemiology and Biostatistics McGill University Montreal Quebec Canada January 2011

heavy-duty vehicles chemical composition impact of exhaust after treatment and fuel parameters Environ Health Perspect102(suppl 4)13ndash23 (1994)

Particulate Matter

PM is a mixture of solid and liquid particles suspended in the atmosphere

as atmospheric aerosols Mobile Pollutants are formed by chemical

reactions of gaseous components from burning of fossil fuel in vehicles

(Gasoline amp diesel motor vehicles)

Source EPA (2012) United States Environmental Protection Agency

Particulate matter basic information Cited October 30th 2012 Available

online at httpwwwepa govairqualityparticlepollutionbasichtml

Source EPA (2012) United States Environmental Protection Agency Particulate matter basic

information Cited October 30th 2012 Available online at httpwwwepa

govairqualityparticlepollutionbasichtml

PM10 25 Long Term Exposure ndashChronic Health Consequences

These particles are associated with a

variety of problems including

Aggravated asthma Chronic

bronchitis

Decreased lung function

Increased respiratory symptoms

coughing or difficulty breathing

Increased Cardiopulmonary Mortality

Increased Risk of Lung Cancer

Sources of Particulate Matter Emissions from traffic

Diesel exhaust particulate matter

This particulate toxic potential has been associated with serious adverse Health

effects including respiratory symptoms Pulmonary function and cardiovascular

diseases (Geller et al 2006 Bernstein et al 2004)

Brake wear particulate matter

Brake wear particulate matter Chemical content (iron(Fe) copper(Cu) Antimony(Sb) barium(Ba) this type of particulate can cause severe respiratory and cardiovascular damages and it is also known that Sb has been classified as a possible human pulmonary carcinogen by the International Agency for Research on Cancer (IARC 1989 Et al 2013)

Fig images of brake wear particles generated at a road simulation study ( centre lt25 μm right lt10

μm) Source [Kukutschovaacute et al 2011]

Tire wear particulate matter

The tire wear particles of the tires are generated either by frictional forces between the treadand the road pavement The chemical content Fe Cr Pb Ti Cr Cu Zn Sr Y Zr Sn Sb Ba LaCe and Pb)

Fig Examples of near spherical particles PM 10 and 25 which are originate from interaction of tires and pavements Source [Dahl et al 2006]

Study Area

The Paso del Norte (PdN) region Selected two strategic areas of study El Paso County zip code 79905 Urban area and Dona Ana County Zip Code 880218802788072 Rural Restricted urban access (freeways and interstates)

Map of the area of the simulation by the MOVES model in the study area

Geographic Domain Zip Code 79905 Urban Area (El Paso County)

Zip Codes 88021880278807288048 (Dona Ana County)

Urban road Delta Dr St 31o 45rsquo 5637- 106o 27rsquo 1212 10 miles

Cordova Bridge of the Americas 31o 45rsquo 4367- 106o 27rsquo 0506 15 miles

478 Highway interstate 31o 46rsquo 1326- 106o 27rsquo 0327 05 miles

110 Highway interstate 31o 46rsquo 1210- 106o 27rsquo 0066 10 miles

10 Interstate Gateway Blvd 31o 46rsquo 397- 106o 26rsquo 4769 05 miles

Chamizal Loop 478 31o 46rsquo 668- 106o 26rsquo 5456 05 miles

Alameda Loop 20 31o 46rsquo 1323- 106o 27rsquo 0328 10 miles

Paisano Dr St Patriot freeway

route 62

31o 46rsquo 0669- 106o 27rsquo 212 15 miles

St Piedras 31o 46rsquo 1326- 106o 27rsquo 0327 10 miles

Dona Ana County Miles

Interstate 25 32o 23rsquo 0561 -106 48

1054 32o 23rsquo 3434- -

106 48 1054 32o 23rsquo

5660 106 48 4314

50

Geographic domain To obtain the simulation mobile data from modelMOVES2010a was configurated the coordinates selected in the study areas

El Paso County

PM25 Estimation from Aerosol Optical Depth (AOD) using

satellites

We examined the relationship

between Aerosol Optical Depth

(AOD) estimated from satellite data

at 5 km spatial resolution and the

mass of fine particles le25 μm in

aerodynamic diameter (PM25)

monitored on the ground in El PdN

area PM25 data was recorded from

air quality monitoring Chamizal

station (TCEQ) on different periods

Our analysis shows a significant

positive association between AOD

and PM25

Time-series and scatter plots of AOD estimated PM25 and surface PM25

Analysis of the meteorological factors and synoptic conditions leading to a local high

ozone event episode June 12-21 2006

Meteorology plays a critical role in determining atmospheric ozone concentrations A good synoptic scale weather forecast is essential to accurately forecast tropospheric and surface ozone concentrations

Figure 1 The domain configuration and Landuse categories

resolution 25 km domainFigure 2 The Geopotential height at 500 mb Figure 3 depicts the 850 mb at a lower altitude The

white regions observed in the graph correspond to

mountainous areas

Figure 4 Temperature at 2m height

above surface at 22 UTC June 18 2006

36 km resolution

Performance Evaluation

01020304050

Ju

ne

137

130

0

190

0

10

0

Ju

ne

157

130

0

190

0

10

0

Ju

ne

187

130

0

190

0

10

0

Tem

pe

ratu

re (⁰C

)

Local time (Hrs)

C41 June 13-19 2006

WRF_temperature

(⁰C)

TCEQ_temperature

(⁰C)

01020304050

June1

37

100

0

130

0

160

0

190

0

220

0

10

0

40

0

June1

57

100

0

130

0

160

0

190

0

220

0

10

0

40

0

June1

87

100

0

130

0

160

0

190

0

220

0

10

0

40

0

Rel

ativ

e h

um

idit

y (

)

Local time (Hrs)

C41 June 13-19 2006

WRF_rh () TCEQ_relative humidity ()

0

5

10

15

20

June

137 10

13

16

19

22 1 4

June

157 10

13

16

19

22 1 4

June

187 10

13

16

19

22 1 4

Win

d s

pee

d (

ms

Local time(Hrs)

C12 June 13-192006

WRF_wind speed (ms) TCEQ_ wind speed (ms)

We evaluate the WRF modelrsquos performance

by comparing against corresponding

experimental TCEQ data and performing the

required statistical analysis

HYSPLIT Model

HYSPLIT was simulated and showed that the ozone is mostly transported to El Paso from north western and south western US and Mexican regions during the 72 hours duration of the simulation

0

20

40

60

80

100

1200

00

10

02

00

30

04

00

50

06

00

70

08

00

90

01

00

01

10

01

20

01

30

01

40

01

50

01

60

01

70

01

80

01

90

02

00

02

10

02

20

02

30

0

Ho

url

y o

zon

e [

pp

b]

0102030405060708090

00

01

00

20

03

00

40

05

00

60

07

00

80

09

00

10

00

11

00

12

00

13

00

14

00

15

00

16

00

17

00

18

00

19

00

20

00

21

00

22

00

23

00

Ho

url

y o

zon

e [

pp

b]

June 18th June 19th

Performance Evaluation

01020304050

Ju

ne

137

130

0

190

0

10

0

Ju

ne

157

130

0

190

0

10

0

Ju

ne

187

130

0

190

0

10

0

Tem

pe

ratu

re (⁰C

)

Local time (Hrs)

C41 June 13-19 2006

WRF_temperature

(⁰C)

TCEQ_temperature

(⁰C)

0

50

100

150

June1

37

100

0

130

0

160

0

190

0

220

0

10

0

40

0

June1

57

100

0

130

0

160

0

190

0

220

0

10

0

40

0

June1

87

100

0

130

0

160

0

190

0

220

0

10

0

40

0Ozo

ne

(pp

b)

Local time (Hrs)

C41 June 13-19 2006

CAMx_ozone (ppbV) TCEQ_ozone (ppb)

0

10

20

30

40

50

June1

37

100

0

130

0

160

0

190

0

220

0

10

0

40

0

June1

57

100

0

130

0

160

0

190

0

220

0

10

0

40

0

June1

87

100

0

130

0

160

0

190

0

220

0

10

0

40

0

Rel

ativ

e h

um

idit

y (

)

Local time (Hrs)

C41 June 13-19 2006

WRF_rh () TCEQ_relative humidity ()

0

5

10

15

20

June

137 10

13

16

19

22 1 4

June

157 10

13

16

19

22 1 4

June

187 10

13

16

19

22 1 4W

ind

sp

eed

(m

sLocal time(Hrs)

C12 June 13-192006

WRF_wind speed (ms) TCEQ_ wind speed (ms)

Methodology

Medical Data The data by weekly monthly and year for daily emergency room and hospital admission for the respiratory

infections (RD) and cardiovascular diseases (CVD) was extracted from hospitals records located in the El PdN

the system includes data on type of admission primary and secondary causes of admissionRESPIRATORY DISEASE

Bronquitis amp Chronic Bronchitis 466 - 4661 491 - 4919

Asthma 463 - 4939

Emphysema 492

Respiratory failure 51881

HEART DISEASE

Accute Myocardial Infarction 410

Coronary Athersclerosis 4140

Other Ischemic Heart Disease 411-4139 4141-4149

Cardiac Dyshythmias 427

Essential hypertension 401

Acute myocardial infarction 410

Congestive Heart Failure 4280 4282-4284

Hypertensive heart disease 402

Table 1 ICD -9 Codes for Respiratory and Cardiovascular Diseases

0

50

100

150

200

250

300

Wee

k 1

Wee

k 2

Wee

k 3

Wee

k 4

Wee

k 5

Wee

k 6

Wee

k 7

Wee

k 8

Wee

k 9

Wee

k 1

0

Wee

k 1

1

Wee

k 1

2

Wee

k 1

3

Wee

k 1

4

Wee

k 1

5

Wee

k 1

6

Wee

k 1

7

Wee

k 1

8

Wee

k 1

9

Wee

k 2

0

Wee

k 2

1

Mo

rb

idit

y D

isch

arg

e fo

r a

ll R

esp

ira

tory

Dis

ease

IC

D-9

(

Ast

hm

aB

ro

nch

itis

)

Weekly Morbidity Discharges of all the Listed Diagnoses for All

Respiratory Disease During WinterSpring 2010

Asthma-Bronchitis

EPA MOVES Model for Estimating Emission

Inventories

Motor Vehicle Emission Simulator (MOVES 2010b) will be configuredin The El Paso North Region for Calculate five categories of PM10

PM25 total Emission inventories from all on-road traffic over a

variety of scales within periods of time selected weeks months

and years

Moves (Motor Vehicle Emission

Simulator)

The emission model is develop using the current equation to calculate direct traffic emissions from

vehicles in the form of PM is

Eext annual emissions are measured in grams of miles traveled by the vehicle (gVMT )

SL is the road surface loading in (gm2)

W is the average weight in tons of the vehicles on the road

K is the particle size multiplier for particle size range (eg gVMT for PM10 when using grams and miles)

P is the 7 number of wet days with at least 0254 mm of precipitation during the averaging period

N is the number of years considered in the averaging period

C is the particle size specific emissions factor in units of interest vehicle direct exhaust brake wear and tirewear

Modeling Simulation Domain and Emissions Scenarios

For simulations of mobile air quality emission inventories a motor vehicle emission simulator EPA (MOVES 2014a) was used

The modeling use input factors divided into seven section

parameters

On-Road Inventory local data

input

Scale

Geographic Bounds

Traffic intensity

Vehicle Type

Pollutants

Road Type

Fuel Types

Figure Source EPA US Environmental Protection Agency 2012- Moves 2010b Model

EPA Moves 2014a The modeling used input factors divided into six section

parameters On-Road Inventory local data input

Geographic Domains CountyNonattainment Area

Vehicle-Miles Traveled (VMT) is the total number of miles driven by all vehicles withina given time period and geographic area

Average speed range from 25 miles per

hour to 65 miles per hour

Vehicle Classes Motorcycle PassengerCarTruks light-duty Commercial Truck(6001-8500 lbs) Buses heave-duty trucksRefuse trucks School Bus Single UnitShort Haul-truck Single Unit Long Haul-truck Long Haul Truck Heavy-DutyVehicles (26001-33000 lbs)

Pollutants

Road TypeRural restricted Acces(Freeways and interstates) Rural and Restricted Acces Urban Restricted Acces Off-Network

Fuel Types Gasoline Diesel Fuel

Specific Road Types

Two road types for running emission from the MOVES can be

selected

(freeways and interstates)

Interior urban Urban

Figure Source EPA US Environmental Protection Agency 2012- Moves 2010b Model

VehiclesEquipment

This panel show which on-road vehicles will be modeled

Figure Source EPA US Environmental Protection Agency 2012- Moves 2010b Model

Long haul truck Short haul truck Inercity bus Ligth comercial truck

Passenger car Passenger truck Refuse truck

School bus Single unit long haul-truck

Single unit short haul-truck

Transit bus

Motor home

Motorcycle

Based on Department of Transportation Highway MOVES will Estimates Traffic

Emissions from Cars Trucks amp Motorcycles

Output Data Moves 2014a

Inventories of PM 10 25 Mobile Emission from all

on-Road Traffic

Exhaust Emission PM 10 25 gramsmile

Brake Wear Emission PM 10 25 gramsmile

Tire wear Emission PM 10 25 gramsmile

Date of Vehicle miles traveled (VMT) for

Day Week Month Year

Total Vehicle population

Vehicle age distribution

Simulation of Mobile Emission in the El PdN Region Zip Code 79905

Figure Total Emissions from road traffic in El Paso TX Area were estimated for PM10

Exhaust and Non exhaust emission in kilogramsmonth (Source EPA MOVES 2014a)

0

10000

20000

30000

40000

50000

PM

10 k

gM

on

th

Months

Monthly PM 10 Exhaust and Non-Exhaust Mobile Emissions 2010

On-Road Urban Restricted Area Zip Code 79905

Primary Exhaust PM 10 (kg) Primary PM 10 Brakewear (kg)

Primary PM 10 Tirewear (kg)

05000

100001500020000250003000035000400004500050000

PM

25

kg

Mo

nth

Months

Monthly PM 25 Exhaust and Non-Exhaust Mobile Emission 2010

On-Road Urban Restricted Area Zip Code 79905

Primary Exhaust PM 25 (kg) Primary PM 25 Brakewear (kg) Primary PM 25Tirewear (kg)

Figure Total Emissions from road traffic in El Paso TX Area were estimated for PM25

Exhaust and Non exhaust emission in kilogramsmonth (Source EPA MOVES 2014a)

Total Emissions from Road Traffic in El Paso County PM1025 Exhaust and Non exhaust Emission in kilogramsmonth

Taking the interests to the health risks related to PM 1025 mobile emission were simulated

Exhaust and Non-exhaust emissions contribute almost equally to total traffic-related PM1025 Emissions (Querol et al 2004 Bukowiecki et al 2009a Amato et al 2011)

Monthly PM 10 25 Exhaust and Non-Exhaust (BrakewearTirewear) Mobile

Emission 2010 On-Road Urban Restricted Area Zip Code 79905

Figure Total Emissions from road traffic in El Paso TX Area were estimated for PM10 25 Exhaust and Non Exhaust mobile

emission in kilograms per month (Source EPA MOVES)

0

10000

20000

30000

40000

50000

January February March April May June July August September October November December

PM

10

25

(K

ilog

ram

s)

Months

Summary- Monthly PM 10 25 Exhaust and Non-Exhaust Mobile

Emission 2010 On-Road Urban Restricted Area Zip Code 79905

Primary Exhaust PM 10 Primary PM 10 Brakewear Primary PM 10 Tirewear

Primary Exhaust PM 25 Primary PM 25 Brakewear Primary PM 25Tirewear

Exhaust Emissions PM1025 is reaching maximum emission 48000-42000 thousand of Kgmonth followedby Brake wear 29000-5000 thousand kgmonth and Tire wear with 9000-2000 kgmonth The results showthat the emissions of PM derived mainly from Exhaust and Brake are significantly higher in Urban Area

Annual Contribution of Mobile Emission PM 1025 (Kg) Zip Code 79905 El

Paso County 2010

Total Primary

Exhaust _PM10

39

Total Primary

Exhaust _PM25

36

Brakewear

particulate_PM10

18

Tirewear

particulate_PM10

4

Brakewear

particulate_PM25

2

Tirewear

particulate_PM25

1

0

5

10

15

20

25

30

35

40

45

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53

Fig Annual Average PM10 Concentrations at the

Chamizal C41 Station and PM1025 mobile

Concentration Zip code 79905

PM10 TCEQ (μgm3) Total Mobile Emission PM10 (Ugm3)

Fig Exhaust Emission is Contributing Approximately 74 of total

PM1025 Mobile Emissions following of Brake wear with 20 and Tire

wear with 5

Annual Average PM1025 ugm3 Mobile Emissions (Moves) 26 Chamizal C41

Monitoring Station (TCEQ Chamizal Station )

Predicting Mobile Emission and VTM

Estimation The PdN Region 2010

44E+09

46E+09

48E+09

5E+09

52E+09

54E+09

56E+09

58E+09

6E+09

62E+09

0

50000

100000

150000

200000

250000

300000

350000

20

10

20

11

20

12

20

13

20

14

20

15

20

16

20

17

20

18

20

21

20

22

20

23

20

24

20

25

20

26

20

27

20

28

20

29

20

30

EX

HA

US

T

EM

ISS

ION

MO

BIL

E (

KG

YE

AR

)

YEARS

Predict ing Mobile Exhaust Emission and VTM

Estimation

2010 - 2030 e l PdN Area

Total_ Exhaust PM10 Total_ Exhaust PM25 Distance (Miles)

Fig Predicting Mobile Exhaust PM1025 (kgMonth) Emission and VTM Estimation 2010

- 2030 el PdN Area

44E+09

46E+09

48E+09

5E+09

52E+09

54E+09

56E+09

58E+09

6E+09

62E+09

0

5000000

10000000

15000000

20000000

25000000

30000000

20

10

20

11

20

12

20

13

20

14

20

15

20

16

20

17

20

18

20

21

20

22

20

23

20

24

20

25

20

26

20

27

20

28

20

29

20

30

EX

HA

US

T

EM

ISS

ION

MO

BIL

E (

KG

YE

AR

)

YEARS

Predict ing Mobile Exhaust Emission and

VTM Estimation

2010 - 2030 e l PdN Area

CO NO2 NO NOx Distance

Fig Predicting Mobile Exhaust Emission and VTM Estimation

2010 - 2030 el PdN Area in El Paso TX Area were estimated for

Total CO NOx NO2 NO emission in kilograms per year

(Source EPA MOVES 2014a model)

The simulated Exhaust emissions in the future years shows a trend of reduction of this type of emissions in the

future years one factor should be the new hybrid technology is increasing by 476 since 2010 to 2015 and

use of catalytic converters diesel particulate filters and improved fuels and engines Non-exhaustive sources

will increase in the coming years because there is no control in the material of manufacture composed by Fe

Cu and Mn also not to be able to reduce the number of events of braking (Accelerations and decelerations)

45E+09

5E+09

55E+09

6E+09

65E+09

0

50000

100000

150000

200000

250000

201

0

201

1

201

2

201

3

201

4

201

5

201

6

201

7

201

8

202

1

202

2

202

3

202

4

202

5

202

6

202

7

202

8

202

9

203

0

NO

N-

EX

HA

US

T

EM

ISS

ION

MO

BIL

E

(KG

YE

AR

)

YEARS

Predicting Non Exhaust Mobile

Emission and VTM Estimation

2010 - 2030 el PdN Area

Brake_PM10 Tire_PM10 Distance (Miles)

Fig Predicting Mobile Exhaust PM1025 (kgMonth) Emission and VTM

Estimation 2010 - 2030 el PdN Area

Daily Avg PM1025

Levels of PM Mobile Emission Non-Exhaust -Rush Hour Periods Fall 2010 Zip Code

79905

00

100

200

300

400

500

600

Mo

bil

e P

M1

0 (k

g)

Rush Hours

Daily Avg PM10

Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush Hours

Periods 2010 Zip Code 79905

Total Primary Exhaust

_PM10 WinterSpring

Brakewear

particulate_PM10

WinterSpringTirewear particulate_PM10

WinterSpring

Total Primary Exhaust

_PM10 Summer

Brakewear

particulate_PM10 Summer

Tirewear Particulate_PM10

Summer

Total Primary Exhaust

_PM10 Fall

Brakewear

particulate_PM10 Fall

Tirewear particulate_PM10

Fall

00

50

100

150

200

250

300

350

Mo

bil

e P

M2

5 (k

g)

Rush hours

Daily Avg PM25

Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush

Hours Periods 2010 Zip Code 79905

Total Primary Exhaust _PM25

WinterSpring

Brakewear Particulate_PM25

WinterSpring

Tirewear particulate_PM25

WinterSpring

Total Primary Exhaust _PM25

Summer

Brakewear particulate_PM25

Summer

Tirewear particulate_PM25

Summer

Total Primary Exhaust _PM25

Fall

Brakewear particulate_PM25

Fall

Tirewear particulate_PM25

Fall

Figure Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush Hours Figure Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush Hours

GIS EMISSIONS INVENTORY SYSTEM A geographic information system (GIS) was used to established geographic scenarios with processed images of seasonal mobile

emissions in the PdN region Seasonal mapping is visualized for different types of pollutants Brakewear Exhaust and Tyrewear

Fg Graphics of GIS and Seasonal mobile Emission of particulate matter emission inventory Seasonal emission simulations were performed in kilograms and five contributing inputs factors were identified for

modeling 1) On the composition of the particulate material from different sources such as Exhaust and Non exhaust (Brake wear Tirewear) 2) The Vehicles Equipment clasification were selected according to

the use of gasoline and diesel fuel (motorcycle passenger car Light Duty Vehicles Trucks refuse truck Light Duty Vehicles Light Commercial Truck Light Duty Vehicles School Bus)

Winter Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

120354 67860 19065

Spring Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

139767 86702 24463

Summer Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

94747 62481 17630

Fall Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

75510 45542 12596

251 Descriptive Statistics Data Analysis

Weekly Correlation Analysis of Mobile Emission PM10 (Exhaust-Non-Exhaust) and Respiratory

Diagnoses WinterSpring Summer and Fall 2010

0

2

4

6

8

10

0

50

100

150

200

250

300

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21

Mo

rbid

ity

Dis

ch

arg

e

for

all R

esp

ira

tory

Dis

ea

se

ICD

-9

(A

sth

ma

-Bro

nc

hitis

)

WinterSpring Week

Weekly Avg Mobile PM10 Concentrations during

WinterSpring 2010 and its Influence on Respiratory

Diagnoses

Zip Code 79905

Total Medical data ZIP Code 79902

Total Mobile Emission PM10 (Ugm3)

0

1

2

3

4

5

6

7

0

20

40

60

80

100

Mo

rbid

ity

Dis

ch

arg

e

for

all R

esp

ira

tory

Dis

ea

se

ICD

-9

(Ast

hm

aB

ron

ch

itis

)

Weekly Avg Mobile PM10 Concentrations during

Summer 2010 and its Influence on Respiratory

Diagnoses

Summer 2010 Zip Code 79905

Total Mobile Emission PM10

Hospital Admission (Asthma-Bronchitis)

0

2

4

6

8

10

12

0

20

40

60

80

100

120

140

160

180

200

Mo

rbid

ity

dis

ch

arg

es

for

all r

esp

ira

tory

dis

ea

se

Weekly Avg Mobile PM10 Concentrations

during Fall 2010 and its Influence on Respiratory

Diagnoses

Zip Code 79905

Total Medical data ZIP Code 79902

Total Mobile Emission PM10 (Ugm3)

Mobile(Exhaust-Non-

Exhaust) PM10 and

Asthma-Bronchitis)

Linear R

Square

WinterSpring 734 ndash 39

Summer 614 ndash 32

Fall 548 -29

PM10 Mobile emission (Exhaust-Non-Exhaust)contributed significantly

association to the incidence of RD

Weekly Correlation Analysis of PM 25 Mobile Emission (Exhaust-Non-Exhaust)

and Cardiovascular Diagnoses WinterSpring Summer and Fall 2010

0010203040

00500

100015002000

Wee

k 1

Wee

k 2

Wee

k 3

Wee

k 4

Wee

k 5

Wee

k 6

Wee

k 7

Wee

k 8

Wee

k 9

Wee

k 1

0

Wee

k 1

1

Wee

k 1

2

Wee

k 1

3

Wee

k 1

4

Wee

k 1

5

Wee

k 1

6

Wee

k 1

7

Wee

k 1

8

Wee

k 1

9

Wee

k 2

0

Wee

k 2

1

Morb

idit

y d

isch

arg

es f

or

all

card

iovasc

ula

r d

isea

se

Weekly Avg PM25 Mobile Concentrations during

WinterSpring 2010 and its Influence on all Heart

Diagnoses

Zip Code 79905

Total All Heart Disease PM 25 mobile (μgm3)

0010203040

00

500

1000

1500

Mo

rbid

ity

dis

ch

arg

es

for

all

ca

rdio

va

scu

lar

dis

ea

se

Weeks

CORRELATION BETWEEN MOBILE PM25 ugm3

EXPOSURE TO HEART DISEASES SYMPTOMS

SUMMER SEASON 2010

Total All Heart Disease PM 25 mobile (μgm3)

Figure Statistical Analyses of the Relationship Between PM25 Caused by Traffic Emission( 26 of total Emission) with Heart diseases Source Hospital Admissions for Asthma Acute Bronchitis and Heart diseases in El Paso County zip code 79905 from Texas Health Care

Information Council in Austin Texas (Texas Health Care Information Council 2000)

00

10

20

30

40

0

50

100

150

We

ek 3

6

We

ek 3

7

We

ek 3

8

We

ek 3

9

We

ek 4

0

We

ek 4

1

We

ek 4

2

We

ek 4

3

We

ek 4

4

We

ek 4

5

We

ek 4

6

We

ek 4

7

We

ek 4

8

We

ek 4

9

We

ek 5

0

We

ek 5

1

We

ek 5

2

We

ek 5

3

Mo

rbid

ity

dis

ch

arg

es

for

all

ca

rdio

va

scu

lar

dis

ea

se

CORRELATION BETWEEN MOBILE PM25 ugm3

EXPOSURE TO HEART DISEASES SYMPTOMS FALL

SEASON 2010

Total All Heart Disease PM 25 mobile (μgm3)

Mobile(Exhaust-

Non-Exhaust)

PM10 and

Asthma-

Bronchitis)

Linear R

Square

WinterSpring 833 -42

Summer 620 -32

Fall 501-26

PM10 Mobile

emission (Exhaust-

Non-

Exhaust)contribut

ed significantly

association to the

incidence of CVD

Diseases

Monthly Brake Mobile Emission PM1025 kg During year 2010 and its Influence on

Respiratory Diagnoses Zip Code 79905

00200040006000800010000

010000200003000040000

PM

10

Mo

bile

(K

g)

Months

Monthly Brake Mobile Emission PM10 kg during year

2010 and its Influence on Respiratory Diagnoses

Zip Code 79905

Primary PM 10

Brakewear 00100020003000400050006000

0

1000

2000

3000

4000

PM

25

Mo

bil

e(K

g)

Months

Monthly Brake Mobile Emission PM25 during

year 2010 and its Influence on Heart Diagnoses

Zip Code 79905

Primary PM 25

Brakewear

Heart Diseases

Hospital

Admission

Brake Mobile Emission

PM10 kg Asthma-

Bronchitis)

Brake Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=969 Linear Square R=856

Monthly Mobile Exhaust Emission PM1025 During year 2010 and its Influence on

Respiratory Diagnoses Zip Code 79905

0

200

400

600

800

1000

0

10000

20000

30000

40000

50000

1 3 5 7 9 11

PM

10

(K

g m

on

th)

Months

Monthly Mobile Exhaust Emission PM10 during

year 2010 and its Influence on Respiratory

Diagnoses

Zip Code 79905

Primary Exhaust

PM 10

Respiratory Disease

(Asthma

Bronchitis) Hospital

Admission

0

100

200

300

400

500

600

0

10000

20000

30000

40000

50000

1 2 3 4 5 6 7 8 9 101112

PM

25

(K

g m

on

th)

Months

Monthly Exhaust Mobile Emission PM25 during

year 2010 and its Influence on Heart Diagnoses

Zip Code 79905

Primary Exhaust PM

25

Heart Diseases

Hospital Admission

Exhaust Mobile Emission

PM10 kg Asthma-

Bronchitis)

Exhaust Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=929 Linear Square R=831

Monthly Tire wear Mobile Emission PM1025 During year 2010 and its Influence on Heart

Diagnoses Zip Code 79905

0

100

200

300

400

500

600

700

800

900

0

1000

2000

3000

4000

5000

6000

7000

8000

9000

1 2 3 4 5 6 7 8 9 10 11 12

PM

10

(K

g m

on

th)

Months

Monthly Tirewear Mobile Emission PM10 during year 2010

and its Influence on Heart Diagnoses

Zip Code 79905

Primary PM 10 Tirewear

Mobile Emission

Respiratory Disease

(Asthma Bronchitis)

Hospital Admission

0

100

200

300

400

500

600

0

200

400

600

800

1000

1200

1400

1 2 3 4 5 6 7 8 9 10 11 12

PM

25

(K

g m

on

th)

Months

Monthly Tirewear Mobile Emission PM25 during year 2010

and its Influence on Respiratory Diagnoses

Zip Code 79905

Primary PM 25Tirewear

Mobile Emission

Heart Diseases Hospital

Admission

Exhaust Mobile Emission

PM10 kg Asthma-

Bronchitis)

Exhaust Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=769 Linear Square R=715

Dona Ana County Zip Codes

88021880278807288048

Primary

Exhaust

PM 10 Zip

code

79905

Total

Primary

Exhaust

PM10

Dona Ana

Primary

Exhaust

PM 25 Zip

Code

79905

Total

Primary

Exhaust

PM25

Dona Ana

Series1 430378 111773 391915 102123

0

100000

200000

300000

400000

500000

AX

IS T

ITLE

Annual Comparison of the Mobile

Exhaust Emissions El Paso County

and Dona Ana 2010

Primary

PM 10

Brakewea

r Zip code

79905

Brakewea

r

particulat

e_PM10

Dona Ana

Primary

PM 10

Tirewear

Zip code

79905

Tirewear

particulat

e_PM10

Dona Ana

Series1 262585 48573 73754 11864

050000

100000150000200000250000300000

AX

IS T

ITLE

Annual Comparison of the Mobile

Brakewear Emissions El Paso County

and Dona Ana 2010

Figure Comparison of the Annual Mobile Emissions

of Primary PM10 Non-Exhauts (Brake ) from Dona

Ana County New Mexico and El Paso Texas Units

in KgMonth

Figure Comparison of the Annual Mobile Emissions

of Primary PM10-Exhauts Emission from Dona Ana

County New Mexico and El Paso Texas Units in

KgMonth

Primary

PM 25

Brakewe

ar Ziphellip

Brakewe

ar

particula

te_PMhellip

Primary

PM

25Tirewe

ar Ziphellip

Tirewear

particula

te_PM25

Donahellip

Series1 32645 6071 10919 1779

0

10000

20000

30000

40000

AX

IS T

ITLE

Annual Comparison of the

Mobile Exhaust Emissions El Paso

County and Dona Ana 2010

Figure Comparison of the Annual Mobile Emissions

of Primary PM10-Exhauts Emission from Dona Ana

County New Mexico and El Paso Texas Units in

KgMonth

Monthly Mobile Emission PM1025 kg During year 2006

and its Influence on Respiratory Diagnoses Dona Ana

County Zip Code 880218802788072

0

100

200

300

0

5000

10000

15000

Axi

s Ti

tle

Axis Title

Monthly Mobile Exhaust Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Total PrimaryMobile Exhaust_PM10

All Respiratory ICD-9 (AsthmaBronchitis)

050100150200250300

010002000300040005000

Axi

s Ti

tle

Axis Title

Monthly Mobile Brake Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Brakewearparticulate_PM10

All RespiratoryICD -9 (AsthmaBronchitis)

050100150200250300

0200400600800

10001200

Axi

s Ti

tle

Axis Title

Monthly Mobile Tirewear Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Tirewearparticulate_PM10

All Respiratory ICD -9 (AsthmaBronchitis)

Mobile Exhauts

Emission PM10

kg Asthma-

Bronchitis)

Brake Mobile

Emission PM10

kg and Heart

Diagnoses

Tirewear Mobile

Emission PM10

kg and Heart

Diagnoses

Linear Square

R= 951

Linear Square

R=625

Linear Square

R=525

Mobile Exhauts

Emission PM25

kg Asthma-

Bronchitis)

Brake Mobile

Emission PM25

kg and Heart

Diagnoses

Tirewear Mobile

Emission PM25

kg and Heart

Diagnoses

Linear Square

R= 986

Linear Square

R=691

Linear Square

R=601

Results

The results showed that mobile PM emissions in the urban areas close to urban Road and highways is putting at risk public health

and the proportion of diseases attributable to this exposure is potentially large

Brake wear emissions is much lower in freeways due to significantly reduced number of braking events while tire wear is much

higher in areas where studded tires are used The emission of exhaust gases are much higher in areas where there is a high

vehicular traffic

Brake Mobile

Emission PM10 kg

Asthma-Bronchitis)

Brake Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square

R=969

Linear Square

R=856

Exhaust Mobile

Emission PM10 kg

Asthma-Bronchitis)

Exhaust Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square

R=929

Linear Square

R=831

Tirewear Mobile

Emission PM10 kg

Asthma-Bronchitis)

Tirewear Mobile

Emission PM25 kg

and Heart Diagnoses

Linear Square R=769 Linear Square R=715

Brake Mobile

Emission PM10 kg

and Heart

Diagnoses

Brake Mobile

Emission PM25 kg

and Heart

Diagnoses

Exhaust Mobile

Emission PM10 kg

Asthma-Bronchitis)

Linear Square

R=625

Linear Square

R=691

Linear Square R=

951

Exhaust Mobile

Emission PM25 kg

Asthma-

Bronchitis)

Tire wear Mobile

Emission PM10 kg and

Heart Diagnoses

Tirewear Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square R=

986

Linear Square R=525 Linear Square

R=601

El Paso County

Dona Ana

County

BenMAP-CE

In this analysis the Program of Mapping and Analysis of Environmental Benefits-Community Edition

(BenMAP-CE) was used to Estimate the number and economic value of health impacts resulting from changes

in air pollution PM 25 Ugm3 in The El Paso Area

Health and Economic Benefits associated with the Response of PM25 Emission between

Base Year 2010

Number of Mortalities in 2010 Base Year Based on El Paso County Texas Department of State Health Services

Number of Mortalities in 2010 Base Year Based on El Paso County Texas

Department of State Health Services

cause of death

year

2010

Populatio

n

Affected

Backgro

und

Concentr

ation Pollutant

Rollback

Type

Avoided

Deaths

(

Populatio

n)

alzheimers disease 2010 40716 125 PM25

25

microgmAcircsup3

Rollback 9

diseases of the

heart 2010 15834 125 PM25

25

microgmAcircsup3

Rollback 35

influenza and

neumonia 2010 81432 125 PM25

25

microgmAcircsup3

Rollback 18

acute bronchitis

and bronchiolitis 2010 117624 125 PM25

25

microgmAcircsup3

Rollback 26

chronic lower

respiratory diseases 2010 54288 125 PM25

25

microgmAcircsup3

Rollback 12

The Basin-wide decrease in 4 ugm3 PM25 concentration after this

reduction control

Cause of death year 2010

Populatio

n

Affected

Background

Concentrati

on

Reduc

cion

scena

rio Polluta

nt

Rollback

Type

Avoi

ded

Deat

hs

(

Pop

ulati

on)

economic

benefits

analysis $

Alzheimers

disease 2010 121 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 9 12000

Diseases of the

heart 2010 470 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 35 35000

Influenza and

neumonia 2010 242 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 18 42500

Acute bronchitis

and bronchiolitis 2010 349 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 26 95000

Chronic lower

respiratory

diseases 2010 161 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 12 4500

$1 295000

PM25-related Mortalities Based on BenMAP-CE Estimate in 2010 Base Year with change in the concentrations levels

Health and Economic Benefits associated with the Response of PM25 Emission between

Base Year 2010 Increasing 7 Ugm3

Cause of death year 2010

Population

Affected

Deaths

avoided by

attaining 195

μgm3

standard

Background

Concentrati

on

Pollut

ant

Rollback

Type

Avoided

Deaths (

Populatio

n)

econo

mic

Unben

efits

analysi

s

Alzheimers

disease 2010 4524 195 PM25

25

microgmAcircsup3

Rollback 19 150000

Diseases of the

heart 2010 20358 195 PM25

25

microgmAcircsup3

Rollback 135 450000

Influenza and

neumonia 2010 126672 195 PM25

25

microgmAcircsup3

Rollback 38 525000

Acute bronchitis

and bronchiolitis 2010 162864 195 PM25

25

microgmAcircsup3

Rollback 36 122000

Chronic lower

respiratory

diseases 2010 99528 195 PM25

25

microgmAcircsup3

Rollback 12 650000

Conclusions

An excellent Pearson Correlation was established to analyze the relationship in the relative risks of hospitalization of Respiratory(RD) and cardiovascular (CVD) associated with ambient exposure caused by traffic emission in relation to their size andspecific sources of emission on different scenarios interior a border Urban Rural Urban restricted access (freeways andinterstates)

A significant correlation of PM1025 exposure from mobile emission and hospital admissions for selected Respiratory (RD) andcardiovascular (CVD) diagnoses was established The results showed that PM emissions in urban restricted access (freeways andinterstates) is mainly caused by traffic Therefore people living close to highways are more exposed higher vehicular emissions

Conclusions

We found statistically significant associations between mobile PM25 caused by traffic emission with Respiratory and Cardiovascular Diseases in the study areaSubsequently a correlation between cardio-respiratory mortality is established

A significant correlation of PM1025 exposure from mobile emission and hospital admissions for selected Respiratory (RD) and cardiovascular (CVD) diagnoses isestablished The results showed that PM emissions in urban restricted access (freeways and interstates) is mainly caused by traffic Therefore people living close tohighways receive higher vehicular emissions

The table shows the percentage of PM mobile exposure in the analyzed areas contributing to increase the risk of Respiratory and Cardiovascular Diseases

An examination was conducted of the synoptic and local meteorology for the June 2006 ozone episode using the WRF model to determine how meteorological parametersinfluence the formation transport and dispersion of ozone in the PdN The predominant synoptic feature of the ozone event day was the expansion intensification and slowprogression of an upper-level ridge of high pressure The high ozone episodes are associated with highly stable atmospheres strong temperature inversions with low mixingheights and therefore low mixing volumes Under these conditions emissions such as NOx lead to highly polluted conditions that favor ozone formation

BenMAP Conclusions

We have estimated the number and economic value of health impacts resulting

from changes in air pollution concentrations of PM 25 in the PdN region

Reduction of Pm 25 4 UGm3= Avoided 213 cases respiratory cardiovascular

diseses and Economic Benefits associated with the Response of PM25 Emission + $

1295000

Increase of PM25 7 ugm3 = increasing Dies= 326 economic Unbenefits= 2345000$

Bibliography

1 Dockery DW Pope CAI Xu X Spengler JD Ware JH Fay ME Ferris BG Speizer FE An association between air pollution and mortality in six US cities N Engl J Med 3291753ndash1759 (1993)

2 Samet JM Dominici F Curriero FC Coursac I Zeger SL Fine particulate air pollution and mortality in 20 US cities 1987ndash1994 N Engl J Med 3431742ndash1749 (2000)

3 Nel AE Diaz-Sanchez D Li N The role of particulate pollutants in pulmonary inflammation and asthma evidence for the involvement of organic chemicals and oxidative stress Curr Opin Pulm Med 20017 20ndash26

4 Westerholm R Karl-Erik E Exhaust emissions from lightand heavy-duty vehicles chemical composition impact of exhaust after treatment and fuel parameters Environ Health Perspect 102(suppl 4)13ndash23 (1994)

5 Bascom R Bromberg P Costa D Delvin R Dockery D Frampton M Lambert W Samet J Speizer F Utell

6 Health effects of outdoor air pollution Am J Respir Crit Care Med 1533ndash50 (1996)

7 Chow JC Watson JG Frazier CA Egami RT Goodrich A Ralph C Spatial and temporal source contributions to

8 PM10 and PM25 in Reno NV In PM-10 Implementation of Standards Transactions An APCAEPA International Speciality Conference San Francisco CA (Mathal CV Stonefield DH eds) PittsburghAPCA 1988439ndash457

9 overview In Particulate Matter Health and Regulatory Issues VIP-49 Proceedings of an International Specialty Conference 4ndash6 April 1995 Pittsburgh PA PittsburghAir and Waste Management Association 1995577ndash598

10 Kunzli N Kaiser R Medina S Studnicka M Chanel O

11 Filliger P Herry M Horak F Jr Puybonnieux-Texier V Quenel P et al Public-health impact of outdoor and traffic- related air pollution a European assessment Lancet 356795ndash801 (2000)

Bibliography

1 Sioutas C Delfino RJ Singh M Exposure assessment for atmospheric ultrafine particles (UFP) and implications in epidemiological research Environ Health Perspect 2005113947ndash955

2 Mosleh M Blau PJ Dumitrescu D (2004) Characteristics and morphology of wear particles from laboratory testing of disc brake materials Wear 2561128ndash1134

3 Kuumlnzli N et al (2000) Public-health impact of outdoor and traffi c-related air pollution a European assessment Lancet 356(9232)795ndash801

4 Dora C Phillips M eds (2000) Transport environment and health Copenhagen WHO Regional Office for Europe (WHO Regional Publications European Series No 89 httpwwweurowhointdocumente72015pdf accessed 26 November 2004)

5 Westerholm R Karl-Erik E Exhaust emissions from lightand

6 heavy-duty vehicles chemical composition impact of exhaust after treatment and fuel parameters Environ Health Perspect 102(suppl 4)13ndash23 (1994)

7 Fauser Tjell Mosbaek pigegaard Quantification of tire-Tread particles using extractable Organic Zinc as a Tracer Rubber Chemistry and Technology 1999 969Table shows some literature estimates of the contribution of tire wear to PM10 in air (Panko et al 2013) Gustafsson M Blomqvist G Gudmundsson A Dahl A Swietlicki E Bohgard M Lindbom J Ljungman A

8 Chen Y Shah N Huggins FE and Huffman GP (2006) Microanalysis of Ambient Particles from Lexington Ky by Electron Microscopy Atmos Environ 40 651ndash663

9 Donaldson K Tran CL Jimenez LA Duffin R Newby DE and Mills N (2005) Combustion-derived Nanoparticles A Review of Their Toxicology Following Inhalation Exposure Part Fibre Toxicol 2 10ndash23

10 Su D Serafino A Muller JO Jentoft RE Schlogl R and Fiorito S (2008) Cytotoxicity and Inflammatory Potential of Soot Particles of Low-emission Diesel Engines Environ Sci Technol 42 1761ndash1765

11 Maier KL Alessandrini F Beck-Speier I Hofer TPJ Diabatґe S Bitterle E Stoger T and Jakob T (2008) Health Effects of Ambient Particulate Matter-Biological Mechanisms and Inflammatory Responses to in Vitroand in Vivo Particle Exposures Inhalation Toxicol 20 319ndash337

Page 3: Studies of Air Pollutants and their Impact on Respiratory and ...€¦ · Ascarate Park C37 Monitoring Station: The National Ambient Air Quality Standard (NAAQS) for PM 10 and 2.5

ABSTRACTThe focus of this research is the study of mobile emissions in the Paso del Norte (PdN) region with the

objective of establishing an association between mobile emissions and health

This association will allow a comparison of different exposure and risk situations relative to the emission

source (Exhaust and Non-Exhaust Emission) and to the particle size PM 10 (coarse) and PM25

(inhalable) with the adverse effects on respiratory (RD) and cardiovascular diseases (CVD)

The times selected for this study are periods in 2006 and 2010 Two areas associated with high traffic

density were selected highway I-10 in the Chamizal urban area zip code 79905 and Dona Ana

county urban areas zip codes 88021880278807288048 The mobile simulations were performed using

the Motor Vehicle Emission (MOVES model version 2014a) simulating weekly monthly and annual

data of mobile emissions

Estimates of the Health and Economic Effects of Air Pollution in the El PdN region were performed

using the Environmental Benefits Mapping and Analysis Program and GIS Software was used for

visualization purposes

In addition NOx is a major component of mobile emissions and is an ozone precursor Therefore we

have studied its concentrations during high episodes and analyzed the meteorological factors that

also contribute to high NOx and Ozone concentrations and performed corresponding air quality

simulations for the PdN region

Purpose

The purpose of this research was establishing an association between mobile emissions

and health This association will allow a comparison of different exposure and risk

situations relative to the location emission source (Exhaust and Non-Exhaust Emission)

and to the particle size PM 10 (coarse) and PM25 (inhalable) with the adverse effects

on respiratory (RD) and cardiovascular diseases (CVD)

Introduction

The Paso del Norte (PdN) region is

one of the largest metropolitan areas

along the US-Mexico border This

includes El Paso Ciudad Juarez

Mexico Each year over 18 million

vehicles cross the three international

ports of entry between El Paso and

Cuidad Juaacuterez

Approximately one-quarter of the

population in The Paso del Norte

(PdN) region lives close to major

roadways exposing the people to

risks of severe respiratory infections

and cardiovascular diseases (Trainer

M Parrish DD and Goldan PD 2000)

Significance of the Work

Traffic is a major source of mobile emissions causing air pollution

Mobile emissions such as

Exhaust Emissions (Carbon Monoxide Nitrogen Oxides and

Hydrocarbons) and Non-exhaust (Brake and Tire) Particulate

emissions can also be very damaging to health because their tiny

diameter can enter the respiratory system easily and possibly cause

adverse health impacts (pulmonary carcinogen inflammatory and

toxic effect on the lung (IARC 1989 Et al 2013) (Kelly and Fussell

2012) (iron(Fe) copper(Cu) Manganese(Mn) antimony(Sb)

barium(Ba) zinc(Zn)

Therefore the relevance of this research provides a key

knowledge to understand the impacts of traffic emissions on air

quality and the magnitude of public health risks associated with

exposure to mobile emissions

Problem Statement

0

100

200

300

400

500

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31

PM

10 (

μg

m3)

Days

Chamizal C 41

Montly 24 Hours Average

PM-10 measured in micrograms per cubic meter (μgm3)

2006 January

February

March

April

May

June

July

August

September

October

November

The National Ambient Air Quality Standard (NAAQS) for PM was Exceeded in The PdN Region during

2006 2010 Analysis of Chamizal Area Zip Code 79905

These chart illustrates two high spikes that occurred which exceeds the 24 hour average

0

20

40

60

80

100

120

140

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31

PM

25

( μ

gm

3)

Days

Chamizal C 41

Montly 24 Hours Average

PM-25 measured in micrograms per cubic meter (μgm3)

2006 january

February

March

April

May

June

July

August

September

October

November

December

Chamizal C41Monitoring Station The National Ambient Air Quality Standard (NAAQS) for PM 10 and 25 was

exceeded but in 24 hour average The NAAQS for PM 25 for 24-hour average is PM2535 microgmsup3 and PM10 50-

100 microgmsup3 The highest concentration occurred several times PM10(150200300450 microgmsup3)

PM25(4050607080120 microgmsup3 )

Problem Statement

0

100

200

300

400

500

600

700

800

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31

PM

10 (

μg

m3)

Days

Ascarate Park SE C37

Montly 24 Hours Avg PM 10 Exceedences and Maximum

Concentrations 2010 January

February

March

April

May

June

July

August

September

October

November

December

Graph 1 Source TCEQ ( Texas Commission on Environmental Quality) Ascarate Park monitoring station Data 2010

0

20

40

60

80

100

120

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31

PM

25

UG

M3

DAYS

Ascarate Park SE C37

Montly 24 Hours Average

PM-25 measured in micrograms per cubic meter

(μgm3)

2010 JanuaryFebruaryMarchAprilMayJuneJulyAugustSeptemberOctoberNovemberDecember

Graph 2 Source TCEQ ( Texas Commission on Environmental Quality) Ascarate Park monitoring station Data 2010

Ascarate Park C37 Monitoring Station The National Ambient Air Quality Standard (NAAQS) for PM

10 and 25 was exceeded but in 24 hour average The NAAQS for PM 25 for 24-hour average is

PM2535 microgmsup3 and PM10 50-100 microgmsup3 The highest concentration occurred several times

PM10(200250300400600720 microgmsup3) PM25(4090120microgmsup3)

The National Ambient Air Quality Standard (NAAQS) for PM was Exceeded in The PdN Region 2006 2010

Analysis of Ascarate Area Zip Code 79905

These chart is to illustrate there are two high spikes that occurred which exceeds the 24 hour average

Fig Number of registered automobiles in Texas The Statistics show the

number of registered automobiles truck motorcycle in Texas Source

Texas department motor vehicles

Fig More than 61 percent of

US transportation emissionscome from cars and lighttrucks

Fig in US On-roadmobile sourcesconstitute the largestsingle source categoryof air pollution with(327)

Problem Statement

13000000140000001500000016000000170000001800000019000000

Millio

ns

of

Ve

hic

les

Years

Total Growth of Texas Registrations

2001-2012

Total

Vehicles

Registratio

ns

Problem Statement

El Paso Texas and ciudad Juarez currently has commercialmovements through El PasondashCiudad Juarez gateways peaked at715000 trucks in the year 2010 and Approximately 40000 vehicles passthese roads each laborable day

Source US Department of Transportation Bureau of Transportation Statistics 2010

Bridge Number of US-bound

Truck Crossings year 2010

World Trade Bridge 1327479

Pharr ndash Reynosa International Bridge

452821

Ysleta ndash Zaragoza Bridge 379508

Laredo ndash Colombia Solidarity

Bridge

374781

Bridge of the Americas 337609

Veterans International Bridge 177986

Camino Real International Bridge 106423

Del Rio ndash Ciudad Acuna

International Bridge

62966

Progreso International Bridge 42605

Free Trade Bridge 30773

Source CBP

Fig Bridge of the Americas (Puente Cordova)

Publications Review to examine the relationship between exposure to motor vehicle emissions and respiratory and cardiovascular disease

We have analyzed the current literature which have served as the basis for this project

Some studies determined that traffic-related emissions have been recognized as a major contributor to urban air pollution in particular major cities proximity to major roadways and exposure to motor vehicle exhaust and Non-exhaust emissions are associated with increased risks of cardiovascular respiratory and other diseases (Brugge et al 2007 Gan et al 2010 Gauderman et al 2007 Jerrett et al 2009 Laden et al 2007 McConnell et al 2006)

Effect of traffic pollution on respiratory and allergic disease in adults cross-sectional and longitudinal analyses Mar Pujades-Rodriacuteguez Tricia McKeever Sarah Lewis Duncan Whyatt John Britton and Andrea Venn

httpwwwsciencedailycomreleases200811081114081003htm April 2011

Traffic Pollution Increases Asthma in Adults Several research results revealed adults who suffer asthma and were exposed to heavy traffic pollution experienced an 80 per cent increase University of Melbourne Rev Public Health 15 (1994) pp 107ndash132 August 2010

Traffic Pollution Aggravates Symptoms In Asthmatic Children Traffic pollution especially in cities adversely affects respiratory health in children with asthma studies suggest that traffic pollution and diesel particles in particular may have a greater effect on respiratory health than other pollutants httpwwwsciencedailycomreleases200811081114081003htm September 2010

Traffic-related air pollution associated with prevalence of asthma and COPDchronic bronchitis A cross-sectional study in Southern Sweden Anna Lindgren Emilie Stroh Peter Montneacutemery September 2009

Acute respiratory health effects of air pollution on children with asthma in US inner cities Benjamin Vaughn MS Meyer Kattan MD Herman Mitchell PhD May 2008

Comparison of Air QualityndashRelated Mortality Impacts of two Different source of emission Transportation in the United States httpwwwtrborgMainBlurbs166402aspx January 2008

Long-term exposure to traffic-related air pollution and cardiovascular mortality Chen H Goldberg MS Burnett RT Jerrett M Wheeler AJ Villeneuve PJ Source Department of Epidemiology and Biostatistics McGill University Montreal Quebec Canada January 2011

heavy-duty vehicles chemical composition impact of exhaust after treatment and fuel parameters Environ Health Perspect102(suppl 4)13ndash23 (1994)

Particulate Matter

PM is a mixture of solid and liquid particles suspended in the atmosphere

as atmospheric aerosols Mobile Pollutants are formed by chemical

reactions of gaseous components from burning of fossil fuel in vehicles

(Gasoline amp diesel motor vehicles)

Source EPA (2012) United States Environmental Protection Agency

Particulate matter basic information Cited October 30th 2012 Available

online at httpwwwepa govairqualityparticlepollutionbasichtml

Source EPA (2012) United States Environmental Protection Agency Particulate matter basic

information Cited October 30th 2012 Available online at httpwwwepa

govairqualityparticlepollutionbasichtml

PM10 25 Long Term Exposure ndashChronic Health Consequences

These particles are associated with a

variety of problems including

Aggravated asthma Chronic

bronchitis

Decreased lung function

Increased respiratory symptoms

coughing or difficulty breathing

Increased Cardiopulmonary Mortality

Increased Risk of Lung Cancer

Sources of Particulate Matter Emissions from traffic

Diesel exhaust particulate matter

This particulate toxic potential has been associated with serious adverse Health

effects including respiratory symptoms Pulmonary function and cardiovascular

diseases (Geller et al 2006 Bernstein et al 2004)

Brake wear particulate matter

Brake wear particulate matter Chemical content (iron(Fe) copper(Cu) Antimony(Sb) barium(Ba) this type of particulate can cause severe respiratory and cardiovascular damages and it is also known that Sb has been classified as a possible human pulmonary carcinogen by the International Agency for Research on Cancer (IARC 1989 Et al 2013)

Fig images of brake wear particles generated at a road simulation study ( centre lt25 μm right lt10

μm) Source [Kukutschovaacute et al 2011]

Tire wear particulate matter

The tire wear particles of the tires are generated either by frictional forces between the treadand the road pavement The chemical content Fe Cr Pb Ti Cr Cu Zn Sr Y Zr Sn Sb Ba LaCe and Pb)

Fig Examples of near spherical particles PM 10 and 25 which are originate from interaction of tires and pavements Source [Dahl et al 2006]

Study Area

The Paso del Norte (PdN) region Selected two strategic areas of study El Paso County zip code 79905 Urban area and Dona Ana County Zip Code 880218802788072 Rural Restricted urban access (freeways and interstates)

Map of the area of the simulation by the MOVES model in the study area

Geographic Domain Zip Code 79905 Urban Area (El Paso County)

Zip Codes 88021880278807288048 (Dona Ana County)

Urban road Delta Dr St 31o 45rsquo 5637- 106o 27rsquo 1212 10 miles

Cordova Bridge of the Americas 31o 45rsquo 4367- 106o 27rsquo 0506 15 miles

478 Highway interstate 31o 46rsquo 1326- 106o 27rsquo 0327 05 miles

110 Highway interstate 31o 46rsquo 1210- 106o 27rsquo 0066 10 miles

10 Interstate Gateway Blvd 31o 46rsquo 397- 106o 26rsquo 4769 05 miles

Chamizal Loop 478 31o 46rsquo 668- 106o 26rsquo 5456 05 miles

Alameda Loop 20 31o 46rsquo 1323- 106o 27rsquo 0328 10 miles

Paisano Dr St Patriot freeway

route 62

31o 46rsquo 0669- 106o 27rsquo 212 15 miles

St Piedras 31o 46rsquo 1326- 106o 27rsquo 0327 10 miles

Dona Ana County Miles

Interstate 25 32o 23rsquo 0561 -106 48

1054 32o 23rsquo 3434- -

106 48 1054 32o 23rsquo

5660 106 48 4314

50

Geographic domain To obtain the simulation mobile data from modelMOVES2010a was configurated the coordinates selected in the study areas

El Paso County

PM25 Estimation from Aerosol Optical Depth (AOD) using

satellites

We examined the relationship

between Aerosol Optical Depth

(AOD) estimated from satellite data

at 5 km spatial resolution and the

mass of fine particles le25 μm in

aerodynamic diameter (PM25)

monitored on the ground in El PdN

area PM25 data was recorded from

air quality monitoring Chamizal

station (TCEQ) on different periods

Our analysis shows a significant

positive association between AOD

and PM25

Time-series and scatter plots of AOD estimated PM25 and surface PM25

Analysis of the meteorological factors and synoptic conditions leading to a local high

ozone event episode June 12-21 2006

Meteorology plays a critical role in determining atmospheric ozone concentrations A good synoptic scale weather forecast is essential to accurately forecast tropospheric and surface ozone concentrations

Figure 1 The domain configuration and Landuse categories

resolution 25 km domainFigure 2 The Geopotential height at 500 mb Figure 3 depicts the 850 mb at a lower altitude The

white regions observed in the graph correspond to

mountainous areas

Figure 4 Temperature at 2m height

above surface at 22 UTC June 18 2006

36 km resolution

Performance Evaluation

01020304050

Ju

ne

137

130

0

190

0

10

0

Ju

ne

157

130

0

190

0

10

0

Ju

ne

187

130

0

190

0

10

0

Tem

pe

ratu

re (⁰C

)

Local time (Hrs)

C41 June 13-19 2006

WRF_temperature

(⁰C)

TCEQ_temperature

(⁰C)

01020304050

June1

37

100

0

130

0

160

0

190

0

220

0

10

0

40

0

June1

57

100

0

130

0

160

0

190

0

220

0

10

0

40

0

June1

87

100

0

130

0

160

0

190

0

220

0

10

0

40

0

Rel

ativ

e h

um

idit

y (

)

Local time (Hrs)

C41 June 13-19 2006

WRF_rh () TCEQ_relative humidity ()

0

5

10

15

20

June

137 10

13

16

19

22 1 4

June

157 10

13

16

19

22 1 4

June

187 10

13

16

19

22 1 4

Win

d s

pee

d (

ms

Local time(Hrs)

C12 June 13-192006

WRF_wind speed (ms) TCEQ_ wind speed (ms)

We evaluate the WRF modelrsquos performance

by comparing against corresponding

experimental TCEQ data and performing the

required statistical analysis

HYSPLIT Model

HYSPLIT was simulated and showed that the ozone is mostly transported to El Paso from north western and south western US and Mexican regions during the 72 hours duration of the simulation

0

20

40

60

80

100

1200

00

10

02

00

30

04

00

50

06

00

70

08

00

90

01

00

01

10

01

20

01

30

01

40

01

50

01

60

01

70

01

80

01

90

02

00

02

10

02

20

02

30

0

Ho

url

y o

zon

e [

pp

b]

0102030405060708090

00

01

00

20

03

00

40

05

00

60

07

00

80

09

00

10

00

11

00

12

00

13

00

14

00

15

00

16

00

17

00

18

00

19

00

20

00

21

00

22

00

23

00

Ho

url

y o

zon

e [

pp

b]

June 18th June 19th

Performance Evaluation

01020304050

Ju

ne

137

130

0

190

0

10

0

Ju

ne

157

130

0

190

0

10

0

Ju

ne

187

130

0

190

0

10

0

Tem

pe

ratu

re (⁰C

)

Local time (Hrs)

C41 June 13-19 2006

WRF_temperature

(⁰C)

TCEQ_temperature

(⁰C)

0

50

100

150

June1

37

100

0

130

0

160

0

190

0

220

0

10

0

40

0

June1

57

100

0

130

0

160

0

190

0

220

0

10

0

40

0

June1

87

100

0

130

0

160

0

190

0

220

0

10

0

40

0Ozo

ne

(pp

b)

Local time (Hrs)

C41 June 13-19 2006

CAMx_ozone (ppbV) TCEQ_ozone (ppb)

0

10

20

30

40

50

June1

37

100

0

130

0

160

0

190

0

220

0

10

0

40

0

June1

57

100

0

130

0

160

0

190

0

220

0

10

0

40

0

June1

87

100

0

130

0

160

0

190

0

220

0

10

0

40

0

Rel

ativ

e h

um

idit

y (

)

Local time (Hrs)

C41 June 13-19 2006

WRF_rh () TCEQ_relative humidity ()

0

5

10

15

20

June

137 10

13

16

19

22 1 4

June

157 10

13

16

19

22 1 4

June

187 10

13

16

19

22 1 4W

ind

sp

eed

(m

sLocal time(Hrs)

C12 June 13-192006

WRF_wind speed (ms) TCEQ_ wind speed (ms)

Methodology

Medical Data The data by weekly monthly and year for daily emergency room and hospital admission for the respiratory

infections (RD) and cardiovascular diseases (CVD) was extracted from hospitals records located in the El PdN

the system includes data on type of admission primary and secondary causes of admissionRESPIRATORY DISEASE

Bronquitis amp Chronic Bronchitis 466 - 4661 491 - 4919

Asthma 463 - 4939

Emphysema 492

Respiratory failure 51881

HEART DISEASE

Accute Myocardial Infarction 410

Coronary Athersclerosis 4140

Other Ischemic Heart Disease 411-4139 4141-4149

Cardiac Dyshythmias 427

Essential hypertension 401

Acute myocardial infarction 410

Congestive Heart Failure 4280 4282-4284

Hypertensive heart disease 402

Table 1 ICD -9 Codes for Respiratory and Cardiovascular Diseases

0

50

100

150

200

250

300

Wee

k 1

Wee

k 2

Wee

k 3

Wee

k 4

Wee

k 5

Wee

k 6

Wee

k 7

Wee

k 8

Wee

k 9

Wee

k 1

0

Wee

k 1

1

Wee

k 1

2

Wee

k 1

3

Wee

k 1

4

Wee

k 1

5

Wee

k 1

6

Wee

k 1

7

Wee

k 1

8

Wee

k 1

9

Wee

k 2

0

Wee

k 2

1

Mo

rb

idit

y D

isch

arg

e fo

r a

ll R

esp

ira

tory

Dis

ease

IC

D-9

(

Ast

hm

aB

ro

nch

itis

)

Weekly Morbidity Discharges of all the Listed Diagnoses for All

Respiratory Disease During WinterSpring 2010

Asthma-Bronchitis

EPA MOVES Model for Estimating Emission

Inventories

Motor Vehicle Emission Simulator (MOVES 2010b) will be configuredin The El Paso North Region for Calculate five categories of PM10

PM25 total Emission inventories from all on-road traffic over a

variety of scales within periods of time selected weeks months

and years

Moves (Motor Vehicle Emission

Simulator)

The emission model is develop using the current equation to calculate direct traffic emissions from

vehicles in the form of PM is

Eext annual emissions are measured in grams of miles traveled by the vehicle (gVMT )

SL is the road surface loading in (gm2)

W is the average weight in tons of the vehicles on the road

K is the particle size multiplier for particle size range (eg gVMT for PM10 when using grams and miles)

P is the 7 number of wet days with at least 0254 mm of precipitation during the averaging period

N is the number of years considered in the averaging period

C is the particle size specific emissions factor in units of interest vehicle direct exhaust brake wear and tirewear

Modeling Simulation Domain and Emissions Scenarios

For simulations of mobile air quality emission inventories a motor vehicle emission simulator EPA (MOVES 2014a) was used

The modeling use input factors divided into seven section

parameters

On-Road Inventory local data

input

Scale

Geographic Bounds

Traffic intensity

Vehicle Type

Pollutants

Road Type

Fuel Types

Figure Source EPA US Environmental Protection Agency 2012- Moves 2010b Model

EPA Moves 2014a The modeling used input factors divided into six section

parameters On-Road Inventory local data input

Geographic Domains CountyNonattainment Area

Vehicle-Miles Traveled (VMT) is the total number of miles driven by all vehicles withina given time period and geographic area

Average speed range from 25 miles per

hour to 65 miles per hour

Vehicle Classes Motorcycle PassengerCarTruks light-duty Commercial Truck(6001-8500 lbs) Buses heave-duty trucksRefuse trucks School Bus Single UnitShort Haul-truck Single Unit Long Haul-truck Long Haul Truck Heavy-DutyVehicles (26001-33000 lbs)

Pollutants

Road TypeRural restricted Acces(Freeways and interstates) Rural and Restricted Acces Urban Restricted Acces Off-Network

Fuel Types Gasoline Diesel Fuel

Specific Road Types

Two road types for running emission from the MOVES can be

selected

(freeways and interstates)

Interior urban Urban

Figure Source EPA US Environmental Protection Agency 2012- Moves 2010b Model

VehiclesEquipment

This panel show which on-road vehicles will be modeled

Figure Source EPA US Environmental Protection Agency 2012- Moves 2010b Model

Long haul truck Short haul truck Inercity bus Ligth comercial truck

Passenger car Passenger truck Refuse truck

School bus Single unit long haul-truck

Single unit short haul-truck

Transit bus

Motor home

Motorcycle

Based on Department of Transportation Highway MOVES will Estimates Traffic

Emissions from Cars Trucks amp Motorcycles

Output Data Moves 2014a

Inventories of PM 10 25 Mobile Emission from all

on-Road Traffic

Exhaust Emission PM 10 25 gramsmile

Brake Wear Emission PM 10 25 gramsmile

Tire wear Emission PM 10 25 gramsmile

Date of Vehicle miles traveled (VMT) for

Day Week Month Year

Total Vehicle population

Vehicle age distribution

Simulation of Mobile Emission in the El PdN Region Zip Code 79905

Figure Total Emissions from road traffic in El Paso TX Area were estimated for PM10

Exhaust and Non exhaust emission in kilogramsmonth (Source EPA MOVES 2014a)

0

10000

20000

30000

40000

50000

PM

10 k

gM

on

th

Months

Monthly PM 10 Exhaust and Non-Exhaust Mobile Emissions 2010

On-Road Urban Restricted Area Zip Code 79905

Primary Exhaust PM 10 (kg) Primary PM 10 Brakewear (kg)

Primary PM 10 Tirewear (kg)

05000

100001500020000250003000035000400004500050000

PM

25

kg

Mo

nth

Months

Monthly PM 25 Exhaust and Non-Exhaust Mobile Emission 2010

On-Road Urban Restricted Area Zip Code 79905

Primary Exhaust PM 25 (kg) Primary PM 25 Brakewear (kg) Primary PM 25Tirewear (kg)

Figure Total Emissions from road traffic in El Paso TX Area were estimated for PM25

Exhaust and Non exhaust emission in kilogramsmonth (Source EPA MOVES 2014a)

Total Emissions from Road Traffic in El Paso County PM1025 Exhaust and Non exhaust Emission in kilogramsmonth

Taking the interests to the health risks related to PM 1025 mobile emission were simulated

Exhaust and Non-exhaust emissions contribute almost equally to total traffic-related PM1025 Emissions (Querol et al 2004 Bukowiecki et al 2009a Amato et al 2011)

Monthly PM 10 25 Exhaust and Non-Exhaust (BrakewearTirewear) Mobile

Emission 2010 On-Road Urban Restricted Area Zip Code 79905

Figure Total Emissions from road traffic in El Paso TX Area were estimated for PM10 25 Exhaust and Non Exhaust mobile

emission in kilograms per month (Source EPA MOVES)

0

10000

20000

30000

40000

50000

January February March April May June July August September October November December

PM

10

25

(K

ilog

ram

s)

Months

Summary- Monthly PM 10 25 Exhaust and Non-Exhaust Mobile

Emission 2010 On-Road Urban Restricted Area Zip Code 79905

Primary Exhaust PM 10 Primary PM 10 Brakewear Primary PM 10 Tirewear

Primary Exhaust PM 25 Primary PM 25 Brakewear Primary PM 25Tirewear

Exhaust Emissions PM1025 is reaching maximum emission 48000-42000 thousand of Kgmonth followedby Brake wear 29000-5000 thousand kgmonth and Tire wear with 9000-2000 kgmonth The results showthat the emissions of PM derived mainly from Exhaust and Brake are significantly higher in Urban Area

Annual Contribution of Mobile Emission PM 1025 (Kg) Zip Code 79905 El

Paso County 2010

Total Primary

Exhaust _PM10

39

Total Primary

Exhaust _PM25

36

Brakewear

particulate_PM10

18

Tirewear

particulate_PM10

4

Brakewear

particulate_PM25

2

Tirewear

particulate_PM25

1

0

5

10

15

20

25

30

35

40

45

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53

Fig Annual Average PM10 Concentrations at the

Chamizal C41 Station and PM1025 mobile

Concentration Zip code 79905

PM10 TCEQ (μgm3) Total Mobile Emission PM10 (Ugm3)

Fig Exhaust Emission is Contributing Approximately 74 of total

PM1025 Mobile Emissions following of Brake wear with 20 and Tire

wear with 5

Annual Average PM1025 ugm3 Mobile Emissions (Moves) 26 Chamizal C41

Monitoring Station (TCEQ Chamizal Station )

Predicting Mobile Emission and VTM

Estimation The PdN Region 2010

44E+09

46E+09

48E+09

5E+09

52E+09

54E+09

56E+09

58E+09

6E+09

62E+09

0

50000

100000

150000

200000

250000

300000

350000

20

10

20

11

20

12

20

13

20

14

20

15

20

16

20

17

20

18

20

21

20

22

20

23

20

24

20

25

20

26

20

27

20

28

20

29

20

30

EX

HA

US

T

EM

ISS

ION

MO

BIL

E (

KG

YE

AR

)

YEARS

Predict ing Mobile Exhaust Emission and VTM

Estimation

2010 - 2030 e l PdN Area

Total_ Exhaust PM10 Total_ Exhaust PM25 Distance (Miles)

Fig Predicting Mobile Exhaust PM1025 (kgMonth) Emission and VTM Estimation 2010

- 2030 el PdN Area

44E+09

46E+09

48E+09

5E+09

52E+09

54E+09

56E+09

58E+09

6E+09

62E+09

0

5000000

10000000

15000000

20000000

25000000

30000000

20

10

20

11

20

12

20

13

20

14

20

15

20

16

20

17

20

18

20

21

20

22

20

23

20

24

20

25

20

26

20

27

20

28

20

29

20

30

EX

HA

US

T

EM

ISS

ION

MO

BIL

E (

KG

YE

AR

)

YEARS

Predict ing Mobile Exhaust Emission and

VTM Estimation

2010 - 2030 e l PdN Area

CO NO2 NO NOx Distance

Fig Predicting Mobile Exhaust Emission and VTM Estimation

2010 - 2030 el PdN Area in El Paso TX Area were estimated for

Total CO NOx NO2 NO emission in kilograms per year

(Source EPA MOVES 2014a model)

The simulated Exhaust emissions in the future years shows a trend of reduction of this type of emissions in the

future years one factor should be the new hybrid technology is increasing by 476 since 2010 to 2015 and

use of catalytic converters diesel particulate filters and improved fuels and engines Non-exhaustive sources

will increase in the coming years because there is no control in the material of manufacture composed by Fe

Cu and Mn also not to be able to reduce the number of events of braking (Accelerations and decelerations)

45E+09

5E+09

55E+09

6E+09

65E+09

0

50000

100000

150000

200000

250000

201

0

201

1

201

2

201

3

201

4

201

5

201

6

201

7

201

8

202

1

202

2

202

3

202

4

202

5

202

6

202

7

202

8

202

9

203

0

NO

N-

EX

HA

US

T

EM

ISS

ION

MO

BIL

E

(KG

YE

AR

)

YEARS

Predicting Non Exhaust Mobile

Emission and VTM Estimation

2010 - 2030 el PdN Area

Brake_PM10 Tire_PM10 Distance (Miles)

Fig Predicting Mobile Exhaust PM1025 (kgMonth) Emission and VTM

Estimation 2010 - 2030 el PdN Area

Daily Avg PM1025

Levels of PM Mobile Emission Non-Exhaust -Rush Hour Periods Fall 2010 Zip Code

79905

00

100

200

300

400

500

600

Mo

bil

e P

M1

0 (k

g)

Rush Hours

Daily Avg PM10

Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush Hours

Periods 2010 Zip Code 79905

Total Primary Exhaust

_PM10 WinterSpring

Brakewear

particulate_PM10

WinterSpringTirewear particulate_PM10

WinterSpring

Total Primary Exhaust

_PM10 Summer

Brakewear

particulate_PM10 Summer

Tirewear Particulate_PM10

Summer

Total Primary Exhaust

_PM10 Fall

Brakewear

particulate_PM10 Fall

Tirewear particulate_PM10

Fall

00

50

100

150

200

250

300

350

Mo

bil

e P

M2

5 (k

g)

Rush hours

Daily Avg PM25

Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush

Hours Periods 2010 Zip Code 79905

Total Primary Exhaust _PM25

WinterSpring

Brakewear Particulate_PM25

WinterSpring

Tirewear particulate_PM25

WinterSpring

Total Primary Exhaust _PM25

Summer

Brakewear particulate_PM25

Summer

Tirewear particulate_PM25

Summer

Total Primary Exhaust _PM25

Fall

Brakewear particulate_PM25

Fall

Tirewear particulate_PM25

Fall

Figure Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush Hours Figure Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush Hours

GIS EMISSIONS INVENTORY SYSTEM A geographic information system (GIS) was used to established geographic scenarios with processed images of seasonal mobile

emissions in the PdN region Seasonal mapping is visualized for different types of pollutants Brakewear Exhaust and Tyrewear

Fg Graphics of GIS and Seasonal mobile Emission of particulate matter emission inventory Seasonal emission simulations were performed in kilograms and five contributing inputs factors were identified for

modeling 1) On the composition of the particulate material from different sources such as Exhaust and Non exhaust (Brake wear Tirewear) 2) The Vehicles Equipment clasification were selected according to

the use of gasoline and diesel fuel (motorcycle passenger car Light Duty Vehicles Trucks refuse truck Light Duty Vehicles Light Commercial Truck Light Duty Vehicles School Bus)

Winter Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

120354 67860 19065

Spring Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

139767 86702 24463

Summer Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

94747 62481 17630

Fall Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

75510 45542 12596

251 Descriptive Statistics Data Analysis

Weekly Correlation Analysis of Mobile Emission PM10 (Exhaust-Non-Exhaust) and Respiratory

Diagnoses WinterSpring Summer and Fall 2010

0

2

4

6

8

10

0

50

100

150

200

250

300

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21

Mo

rbid

ity

Dis

ch

arg

e

for

all R

esp

ira

tory

Dis

ea

se

ICD

-9

(A

sth

ma

-Bro

nc

hitis

)

WinterSpring Week

Weekly Avg Mobile PM10 Concentrations during

WinterSpring 2010 and its Influence on Respiratory

Diagnoses

Zip Code 79905

Total Medical data ZIP Code 79902

Total Mobile Emission PM10 (Ugm3)

0

1

2

3

4

5

6

7

0

20

40

60

80

100

Mo

rbid

ity

Dis

ch

arg

e

for

all R

esp

ira

tory

Dis

ea

se

ICD

-9

(Ast

hm

aB

ron

ch

itis

)

Weekly Avg Mobile PM10 Concentrations during

Summer 2010 and its Influence on Respiratory

Diagnoses

Summer 2010 Zip Code 79905

Total Mobile Emission PM10

Hospital Admission (Asthma-Bronchitis)

0

2

4

6

8

10

12

0

20

40

60

80

100

120

140

160

180

200

Mo

rbid

ity

dis

ch

arg

es

for

all r

esp

ira

tory

dis

ea

se

Weekly Avg Mobile PM10 Concentrations

during Fall 2010 and its Influence on Respiratory

Diagnoses

Zip Code 79905

Total Medical data ZIP Code 79902

Total Mobile Emission PM10 (Ugm3)

Mobile(Exhaust-Non-

Exhaust) PM10 and

Asthma-Bronchitis)

Linear R

Square

WinterSpring 734 ndash 39

Summer 614 ndash 32

Fall 548 -29

PM10 Mobile emission (Exhaust-Non-Exhaust)contributed significantly

association to the incidence of RD

Weekly Correlation Analysis of PM 25 Mobile Emission (Exhaust-Non-Exhaust)

and Cardiovascular Diagnoses WinterSpring Summer and Fall 2010

0010203040

00500

100015002000

Wee

k 1

Wee

k 2

Wee

k 3

Wee

k 4

Wee

k 5

Wee

k 6

Wee

k 7

Wee

k 8

Wee

k 9

Wee

k 1

0

Wee

k 1

1

Wee

k 1

2

Wee

k 1

3

Wee

k 1

4

Wee

k 1

5

Wee

k 1

6

Wee

k 1

7

Wee

k 1

8

Wee

k 1

9

Wee

k 2

0

Wee

k 2

1

Morb

idit

y d

isch

arg

es f

or

all

card

iovasc

ula

r d

isea

se

Weekly Avg PM25 Mobile Concentrations during

WinterSpring 2010 and its Influence on all Heart

Diagnoses

Zip Code 79905

Total All Heart Disease PM 25 mobile (μgm3)

0010203040

00

500

1000

1500

Mo

rbid

ity

dis

ch

arg

es

for

all

ca

rdio

va

scu

lar

dis

ea

se

Weeks

CORRELATION BETWEEN MOBILE PM25 ugm3

EXPOSURE TO HEART DISEASES SYMPTOMS

SUMMER SEASON 2010

Total All Heart Disease PM 25 mobile (μgm3)

Figure Statistical Analyses of the Relationship Between PM25 Caused by Traffic Emission( 26 of total Emission) with Heart diseases Source Hospital Admissions for Asthma Acute Bronchitis and Heart diseases in El Paso County zip code 79905 from Texas Health Care

Information Council in Austin Texas (Texas Health Care Information Council 2000)

00

10

20

30

40

0

50

100

150

We

ek 3

6

We

ek 3

7

We

ek 3

8

We

ek 3

9

We

ek 4

0

We

ek 4

1

We

ek 4

2

We

ek 4

3

We

ek 4

4

We

ek 4

5

We

ek 4

6

We

ek 4

7

We

ek 4

8

We

ek 4

9

We

ek 5

0

We

ek 5

1

We

ek 5

2

We

ek 5

3

Mo

rbid

ity

dis

ch

arg

es

for

all

ca

rdio

va

scu

lar

dis

ea

se

CORRELATION BETWEEN MOBILE PM25 ugm3

EXPOSURE TO HEART DISEASES SYMPTOMS FALL

SEASON 2010

Total All Heart Disease PM 25 mobile (μgm3)

Mobile(Exhaust-

Non-Exhaust)

PM10 and

Asthma-

Bronchitis)

Linear R

Square

WinterSpring 833 -42

Summer 620 -32

Fall 501-26

PM10 Mobile

emission (Exhaust-

Non-

Exhaust)contribut

ed significantly

association to the

incidence of CVD

Diseases

Monthly Brake Mobile Emission PM1025 kg During year 2010 and its Influence on

Respiratory Diagnoses Zip Code 79905

00200040006000800010000

010000200003000040000

PM

10

Mo

bile

(K

g)

Months

Monthly Brake Mobile Emission PM10 kg during year

2010 and its Influence on Respiratory Diagnoses

Zip Code 79905

Primary PM 10

Brakewear 00100020003000400050006000

0

1000

2000

3000

4000

PM

25

Mo

bil

e(K

g)

Months

Monthly Brake Mobile Emission PM25 during

year 2010 and its Influence on Heart Diagnoses

Zip Code 79905

Primary PM 25

Brakewear

Heart Diseases

Hospital

Admission

Brake Mobile Emission

PM10 kg Asthma-

Bronchitis)

Brake Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=969 Linear Square R=856

Monthly Mobile Exhaust Emission PM1025 During year 2010 and its Influence on

Respiratory Diagnoses Zip Code 79905

0

200

400

600

800

1000

0

10000

20000

30000

40000

50000

1 3 5 7 9 11

PM

10

(K

g m

on

th)

Months

Monthly Mobile Exhaust Emission PM10 during

year 2010 and its Influence on Respiratory

Diagnoses

Zip Code 79905

Primary Exhaust

PM 10

Respiratory Disease

(Asthma

Bronchitis) Hospital

Admission

0

100

200

300

400

500

600

0

10000

20000

30000

40000

50000

1 2 3 4 5 6 7 8 9 101112

PM

25

(K

g m

on

th)

Months

Monthly Exhaust Mobile Emission PM25 during

year 2010 and its Influence on Heart Diagnoses

Zip Code 79905

Primary Exhaust PM

25

Heart Diseases

Hospital Admission

Exhaust Mobile Emission

PM10 kg Asthma-

Bronchitis)

Exhaust Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=929 Linear Square R=831

Monthly Tire wear Mobile Emission PM1025 During year 2010 and its Influence on Heart

Diagnoses Zip Code 79905

0

100

200

300

400

500

600

700

800

900

0

1000

2000

3000

4000

5000

6000

7000

8000

9000

1 2 3 4 5 6 7 8 9 10 11 12

PM

10

(K

g m

on

th)

Months

Monthly Tirewear Mobile Emission PM10 during year 2010

and its Influence on Heart Diagnoses

Zip Code 79905

Primary PM 10 Tirewear

Mobile Emission

Respiratory Disease

(Asthma Bronchitis)

Hospital Admission

0

100

200

300

400

500

600

0

200

400

600

800

1000

1200

1400

1 2 3 4 5 6 7 8 9 10 11 12

PM

25

(K

g m

on

th)

Months

Monthly Tirewear Mobile Emission PM25 during year 2010

and its Influence on Respiratory Diagnoses

Zip Code 79905

Primary PM 25Tirewear

Mobile Emission

Heart Diseases Hospital

Admission

Exhaust Mobile Emission

PM10 kg Asthma-

Bronchitis)

Exhaust Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=769 Linear Square R=715

Dona Ana County Zip Codes

88021880278807288048

Primary

Exhaust

PM 10 Zip

code

79905

Total

Primary

Exhaust

PM10

Dona Ana

Primary

Exhaust

PM 25 Zip

Code

79905

Total

Primary

Exhaust

PM25

Dona Ana

Series1 430378 111773 391915 102123

0

100000

200000

300000

400000

500000

AX

IS T

ITLE

Annual Comparison of the Mobile

Exhaust Emissions El Paso County

and Dona Ana 2010

Primary

PM 10

Brakewea

r Zip code

79905

Brakewea

r

particulat

e_PM10

Dona Ana

Primary

PM 10

Tirewear

Zip code

79905

Tirewear

particulat

e_PM10

Dona Ana

Series1 262585 48573 73754 11864

050000

100000150000200000250000300000

AX

IS T

ITLE

Annual Comparison of the Mobile

Brakewear Emissions El Paso County

and Dona Ana 2010

Figure Comparison of the Annual Mobile Emissions

of Primary PM10 Non-Exhauts (Brake ) from Dona

Ana County New Mexico and El Paso Texas Units

in KgMonth

Figure Comparison of the Annual Mobile Emissions

of Primary PM10-Exhauts Emission from Dona Ana

County New Mexico and El Paso Texas Units in

KgMonth

Primary

PM 25

Brakewe

ar Ziphellip

Brakewe

ar

particula

te_PMhellip

Primary

PM

25Tirewe

ar Ziphellip

Tirewear

particula

te_PM25

Donahellip

Series1 32645 6071 10919 1779

0

10000

20000

30000

40000

AX

IS T

ITLE

Annual Comparison of the

Mobile Exhaust Emissions El Paso

County and Dona Ana 2010

Figure Comparison of the Annual Mobile Emissions

of Primary PM10-Exhauts Emission from Dona Ana

County New Mexico and El Paso Texas Units in

KgMonth

Monthly Mobile Emission PM1025 kg During year 2006

and its Influence on Respiratory Diagnoses Dona Ana

County Zip Code 880218802788072

0

100

200

300

0

5000

10000

15000

Axi

s Ti

tle

Axis Title

Monthly Mobile Exhaust Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Total PrimaryMobile Exhaust_PM10

All Respiratory ICD-9 (AsthmaBronchitis)

050100150200250300

010002000300040005000

Axi

s Ti

tle

Axis Title

Monthly Mobile Brake Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Brakewearparticulate_PM10

All RespiratoryICD -9 (AsthmaBronchitis)

050100150200250300

0200400600800

10001200

Axi

s Ti

tle

Axis Title

Monthly Mobile Tirewear Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Tirewearparticulate_PM10

All Respiratory ICD -9 (AsthmaBronchitis)

Mobile Exhauts

Emission PM10

kg Asthma-

Bronchitis)

Brake Mobile

Emission PM10

kg and Heart

Diagnoses

Tirewear Mobile

Emission PM10

kg and Heart

Diagnoses

Linear Square

R= 951

Linear Square

R=625

Linear Square

R=525

Mobile Exhauts

Emission PM25

kg Asthma-

Bronchitis)

Brake Mobile

Emission PM25

kg and Heart

Diagnoses

Tirewear Mobile

Emission PM25

kg and Heart

Diagnoses

Linear Square

R= 986

Linear Square

R=691

Linear Square

R=601

Results

The results showed that mobile PM emissions in the urban areas close to urban Road and highways is putting at risk public health

and the proportion of diseases attributable to this exposure is potentially large

Brake wear emissions is much lower in freeways due to significantly reduced number of braking events while tire wear is much

higher in areas where studded tires are used The emission of exhaust gases are much higher in areas where there is a high

vehicular traffic

Brake Mobile

Emission PM10 kg

Asthma-Bronchitis)

Brake Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square

R=969

Linear Square

R=856

Exhaust Mobile

Emission PM10 kg

Asthma-Bronchitis)

Exhaust Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square

R=929

Linear Square

R=831

Tirewear Mobile

Emission PM10 kg

Asthma-Bronchitis)

Tirewear Mobile

Emission PM25 kg

and Heart Diagnoses

Linear Square R=769 Linear Square R=715

Brake Mobile

Emission PM10 kg

and Heart

Diagnoses

Brake Mobile

Emission PM25 kg

and Heart

Diagnoses

Exhaust Mobile

Emission PM10 kg

Asthma-Bronchitis)

Linear Square

R=625

Linear Square

R=691

Linear Square R=

951

Exhaust Mobile

Emission PM25 kg

Asthma-

Bronchitis)

Tire wear Mobile

Emission PM10 kg and

Heart Diagnoses

Tirewear Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square R=

986

Linear Square R=525 Linear Square

R=601

El Paso County

Dona Ana

County

BenMAP-CE

In this analysis the Program of Mapping and Analysis of Environmental Benefits-Community Edition

(BenMAP-CE) was used to Estimate the number and economic value of health impacts resulting from changes

in air pollution PM 25 Ugm3 in The El Paso Area

Health and Economic Benefits associated with the Response of PM25 Emission between

Base Year 2010

Number of Mortalities in 2010 Base Year Based on El Paso County Texas Department of State Health Services

Number of Mortalities in 2010 Base Year Based on El Paso County Texas

Department of State Health Services

cause of death

year

2010

Populatio

n

Affected

Backgro

und

Concentr

ation Pollutant

Rollback

Type

Avoided

Deaths

(

Populatio

n)

alzheimers disease 2010 40716 125 PM25

25

microgmAcircsup3

Rollback 9

diseases of the

heart 2010 15834 125 PM25

25

microgmAcircsup3

Rollback 35

influenza and

neumonia 2010 81432 125 PM25

25

microgmAcircsup3

Rollback 18

acute bronchitis

and bronchiolitis 2010 117624 125 PM25

25

microgmAcircsup3

Rollback 26

chronic lower

respiratory diseases 2010 54288 125 PM25

25

microgmAcircsup3

Rollback 12

The Basin-wide decrease in 4 ugm3 PM25 concentration after this

reduction control

Cause of death year 2010

Populatio

n

Affected

Background

Concentrati

on

Reduc

cion

scena

rio Polluta

nt

Rollback

Type

Avoi

ded

Deat

hs

(

Pop

ulati

on)

economic

benefits

analysis $

Alzheimers

disease 2010 121 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 9 12000

Diseases of the

heart 2010 470 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 35 35000

Influenza and

neumonia 2010 242 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 18 42500

Acute bronchitis

and bronchiolitis 2010 349 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 26 95000

Chronic lower

respiratory

diseases 2010 161 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 12 4500

$1 295000

PM25-related Mortalities Based on BenMAP-CE Estimate in 2010 Base Year with change in the concentrations levels

Health and Economic Benefits associated with the Response of PM25 Emission between

Base Year 2010 Increasing 7 Ugm3

Cause of death year 2010

Population

Affected

Deaths

avoided by

attaining 195

μgm3

standard

Background

Concentrati

on

Pollut

ant

Rollback

Type

Avoided

Deaths (

Populatio

n)

econo

mic

Unben

efits

analysi

s

Alzheimers

disease 2010 4524 195 PM25

25

microgmAcircsup3

Rollback 19 150000

Diseases of the

heart 2010 20358 195 PM25

25

microgmAcircsup3

Rollback 135 450000

Influenza and

neumonia 2010 126672 195 PM25

25

microgmAcircsup3

Rollback 38 525000

Acute bronchitis

and bronchiolitis 2010 162864 195 PM25

25

microgmAcircsup3

Rollback 36 122000

Chronic lower

respiratory

diseases 2010 99528 195 PM25

25

microgmAcircsup3

Rollback 12 650000

Conclusions

An excellent Pearson Correlation was established to analyze the relationship in the relative risks of hospitalization of Respiratory(RD) and cardiovascular (CVD) associated with ambient exposure caused by traffic emission in relation to their size andspecific sources of emission on different scenarios interior a border Urban Rural Urban restricted access (freeways andinterstates)

A significant correlation of PM1025 exposure from mobile emission and hospital admissions for selected Respiratory (RD) andcardiovascular (CVD) diagnoses was established The results showed that PM emissions in urban restricted access (freeways andinterstates) is mainly caused by traffic Therefore people living close to highways are more exposed higher vehicular emissions

Conclusions

We found statistically significant associations between mobile PM25 caused by traffic emission with Respiratory and Cardiovascular Diseases in the study areaSubsequently a correlation between cardio-respiratory mortality is established

A significant correlation of PM1025 exposure from mobile emission and hospital admissions for selected Respiratory (RD) and cardiovascular (CVD) diagnoses isestablished The results showed that PM emissions in urban restricted access (freeways and interstates) is mainly caused by traffic Therefore people living close tohighways receive higher vehicular emissions

The table shows the percentage of PM mobile exposure in the analyzed areas contributing to increase the risk of Respiratory and Cardiovascular Diseases

An examination was conducted of the synoptic and local meteorology for the June 2006 ozone episode using the WRF model to determine how meteorological parametersinfluence the formation transport and dispersion of ozone in the PdN The predominant synoptic feature of the ozone event day was the expansion intensification and slowprogression of an upper-level ridge of high pressure The high ozone episodes are associated with highly stable atmospheres strong temperature inversions with low mixingheights and therefore low mixing volumes Under these conditions emissions such as NOx lead to highly polluted conditions that favor ozone formation

BenMAP Conclusions

We have estimated the number and economic value of health impacts resulting

from changes in air pollution concentrations of PM 25 in the PdN region

Reduction of Pm 25 4 UGm3= Avoided 213 cases respiratory cardiovascular

diseses and Economic Benefits associated with the Response of PM25 Emission + $

1295000

Increase of PM25 7 ugm3 = increasing Dies= 326 economic Unbenefits= 2345000$

Bibliography

1 Dockery DW Pope CAI Xu X Spengler JD Ware JH Fay ME Ferris BG Speizer FE An association between air pollution and mortality in six US cities N Engl J Med 3291753ndash1759 (1993)

2 Samet JM Dominici F Curriero FC Coursac I Zeger SL Fine particulate air pollution and mortality in 20 US cities 1987ndash1994 N Engl J Med 3431742ndash1749 (2000)

3 Nel AE Diaz-Sanchez D Li N The role of particulate pollutants in pulmonary inflammation and asthma evidence for the involvement of organic chemicals and oxidative stress Curr Opin Pulm Med 20017 20ndash26

4 Westerholm R Karl-Erik E Exhaust emissions from lightand heavy-duty vehicles chemical composition impact of exhaust after treatment and fuel parameters Environ Health Perspect 102(suppl 4)13ndash23 (1994)

5 Bascom R Bromberg P Costa D Delvin R Dockery D Frampton M Lambert W Samet J Speizer F Utell

6 Health effects of outdoor air pollution Am J Respir Crit Care Med 1533ndash50 (1996)

7 Chow JC Watson JG Frazier CA Egami RT Goodrich A Ralph C Spatial and temporal source contributions to

8 PM10 and PM25 in Reno NV In PM-10 Implementation of Standards Transactions An APCAEPA International Speciality Conference San Francisco CA (Mathal CV Stonefield DH eds) PittsburghAPCA 1988439ndash457

9 overview In Particulate Matter Health and Regulatory Issues VIP-49 Proceedings of an International Specialty Conference 4ndash6 April 1995 Pittsburgh PA PittsburghAir and Waste Management Association 1995577ndash598

10 Kunzli N Kaiser R Medina S Studnicka M Chanel O

11 Filliger P Herry M Horak F Jr Puybonnieux-Texier V Quenel P et al Public-health impact of outdoor and traffic- related air pollution a European assessment Lancet 356795ndash801 (2000)

Bibliography

1 Sioutas C Delfino RJ Singh M Exposure assessment for atmospheric ultrafine particles (UFP) and implications in epidemiological research Environ Health Perspect 2005113947ndash955

2 Mosleh M Blau PJ Dumitrescu D (2004) Characteristics and morphology of wear particles from laboratory testing of disc brake materials Wear 2561128ndash1134

3 Kuumlnzli N et al (2000) Public-health impact of outdoor and traffi c-related air pollution a European assessment Lancet 356(9232)795ndash801

4 Dora C Phillips M eds (2000) Transport environment and health Copenhagen WHO Regional Office for Europe (WHO Regional Publications European Series No 89 httpwwweurowhointdocumente72015pdf accessed 26 November 2004)

5 Westerholm R Karl-Erik E Exhaust emissions from lightand

6 heavy-duty vehicles chemical composition impact of exhaust after treatment and fuel parameters Environ Health Perspect 102(suppl 4)13ndash23 (1994)

7 Fauser Tjell Mosbaek pigegaard Quantification of tire-Tread particles using extractable Organic Zinc as a Tracer Rubber Chemistry and Technology 1999 969Table shows some literature estimates of the contribution of tire wear to PM10 in air (Panko et al 2013) Gustafsson M Blomqvist G Gudmundsson A Dahl A Swietlicki E Bohgard M Lindbom J Ljungman A

8 Chen Y Shah N Huggins FE and Huffman GP (2006) Microanalysis of Ambient Particles from Lexington Ky by Electron Microscopy Atmos Environ 40 651ndash663

9 Donaldson K Tran CL Jimenez LA Duffin R Newby DE and Mills N (2005) Combustion-derived Nanoparticles A Review of Their Toxicology Following Inhalation Exposure Part Fibre Toxicol 2 10ndash23

10 Su D Serafino A Muller JO Jentoft RE Schlogl R and Fiorito S (2008) Cytotoxicity and Inflammatory Potential of Soot Particles of Low-emission Diesel Engines Environ Sci Technol 42 1761ndash1765

11 Maier KL Alessandrini F Beck-Speier I Hofer TPJ Diabatґe S Bitterle E Stoger T and Jakob T (2008) Health Effects of Ambient Particulate Matter-Biological Mechanisms and Inflammatory Responses to in Vitroand in Vivo Particle Exposures Inhalation Toxicol 20 319ndash337

Page 4: Studies of Air Pollutants and their Impact on Respiratory and ...€¦ · Ascarate Park C37 Monitoring Station: The National Ambient Air Quality Standard (NAAQS) for PM 10 and 2.5

Purpose

The purpose of this research was establishing an association between mobile emissions

and health This association will allow a comparison of different exposure and risk

situations relative to the location emission source (Exhaust and Non-Exhaust Emission)

and to the particle size PM 10 (coarse) and PM25 (inhalable) with the adverse effects

on respiratory (RD) and cardiovascular diseases (CVD)

Introduction

The Paso del Norte (PdN) region is

one of the largest metropolitan areas

along the US-Mexico border This

includes El Paso Ciudad Juarez

Mexico Each year over 18 million

vehicles cross the three international

ports of entry between El Paso and

Cuidad Juaacuterez

Approximately one-quarter of the

population in The Paso del Norte

(PdN) region lives close to major

roadways exposing the people to

risks of severe respiratory infections

and cardiovascular diseases (Trainer

M Parrish DD and Goldan PD 2000)

Significance of the Work

Traffic is a major source of mobile emissions causing air pollution

Mobile emissions such as

Exhaust Emissions (Carbon Monoxide Nitrogen Oxides and

Hydrocarbons) and Non-exhaust (Brake and Tire) Particulate

emissions can also be very damaging to health because their tiny

diameter can enter the respiratory system easily and possibly cause

adverse health impacts (pulmonary carcinogen inflammatory and

toxic effect on the lung (IARC 1989 Et al 2013) (Kelly and Fussell

2012) (iron(Fe) copper(Cu) Manganese(Mn) antimony(Sb)

barium(Ba) zinc(Zn)

Therefore the relevance of this research provides a key

knowledge to understand the impacts of traffic emissions on air

quality and the magnitude of public health risks associated with

exposure to mobile emissions

Problem Statement

0

100

200

300

400

500

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31

PM

10 (

μg

m3)

Days

Chamizal C 41

Montly 24 Hours Average

PM-10 measured in micrograms per cubic meter (μgm3)

2006 January

February

March

April

May

June

July

August

September

October

November

The National Ambient Air Quality Standard (NAAQS) for PM was Exceeded in The PdN Region during

2006 2010 Analysis of Chamizal Area Zip Code 79905

These chart illustrates two high spikes that occurred which exceeds the 24 hour average

0

20

40

60

80

100

120

140

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31

PM

25

( μ

gm

3)

Days

Chamizal C 41

Montly 24 Hours Average

PM-25 measured in micrograms per cubic meter (μgm3)

2006 january

February

March

April

May

June

July

August

September

October

November

December

Chamizal C41Monitoring Station The National Ambient Air Quality Standard (NAAQS) for PM 10 and 25 was

exceeded but in 24 hour average The NAAQS for PM 25 for 24-hour average is PM2535 microgmsup3 and PM10 50-

100 microgmsup3 The highest concentration occurred several times PM10(150200300450 microgmsup3)

PM25(4050607080120 microgmsup3 )

Problem Statement

0

100

200

300

400

500

600

700

800

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31

PM

10 (

μg

m3)

Days

Ascarate Park SE C37

Montly 24 Hours Avg PM 10 Exceedences and Maximum

Concentrations 2010 January

February

March

April

May

June

July

August

September

October

November

December

Graph 1 Source TCEQ ( Texas Commission on Environmental Quality) Ascarate Park monitoring station Data 2010

0

20

40

60

80

100

120

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31

PM

25

UG

M3

DAYS

Ascarate Park SE C37

Montly 24 Hours Average

PM-25 measured in micrograms per cubic meter

(μgm3)

2010 JanuaryFebruaryMarchAprilMayJuneJulyAugustSeptemberOctoberNovemberDecember

Graph 2 Source TCEQ ( Texas Commission on Environmental Quality) Ascarate Park monitoring station Data 2010

Ascarate Park C37 Monitoring Station The National Ambient Air Quality Standard (NAAQS) for PM

10 and 25 was exceeded but in 24 hour average The NAAQS for PM 25 for 24-hour average is

PM2535 microgmsup3 and PM10 50-100 microgmsup3 The highest concentration occurred several times

PM10(200250300400600720 microgmsup3) PM25(4090120microgmsup3)

The National Ambient Air Quality Standard (NAAQS) for PM was Exceeded in The PdN Region 2006 2010

Analysis of Ascarate Area Zip Code 79905

These chart is to illustrate there are two high spikes that occurred which exceeds the 24 hour average

Fig Number of registered automobiles in Texas The Statistics show the

number of registered automobiles truck motorcycle in Texas Source

Texas department motor vehicles

Fig More than 61 percent of

US transportation emissionscome from cars and lighttrucks

Fig in US On-roadmobile sourcesconstitute the largestsingle source categoryof air pollution with(327)

Problem Statement

13000000140000001500000016000000170000001800000019000000

Millio

ns

of

Ve

hic

les

Years

Total Growth of Texas Registrations

2001-2012

Total

Vehicles

Registratio

ns

Problem Statement

El Paso Texas and ciudad Juarez currently has commercialmovements through El PasondashCiudad Juarez gateways peaked at715000 trucks in the year 2010 and Approximately 40000 vehicles passthese roads each laborable day

Source US Department of Transportation Bureau of Transportation Statistics 2010

Bridge Number of US-bound

Truck Crossings year 2010

World Trade Bridge 1327479

Pharr ndash Reynosa International Bridge

452821

Ysleta ndash Zaragoza Bridge 379508

Laredo ndash Colombia Solidarity

Bridge

374781

Bridge of the Americas 337609

Veterans International Bridge 177986

Camino Real International Bridge 106423

Del Rio ndash Ciudad Acuna

International Bridge

62966

Progreso International Bridge 42605

Free Trade Bridge 30773

Source CBP

Fig Bridge of the Americas (Puente Cordova)

Publications Review to examine the relationship between exposure to motor vehicle emissions and respiratory and cardiovascular disease

We have analyzed the current literature which have served as the basis for this project

Some studies determined that traffic-related emissions have been recognized as a major contributor to urban air pollution in particular major cities proximity to major roadways and exposure to motor vehicle exhaust and Non-exhaust emissions are associated with increased risks of cardiovascular respiratory and other diseases (Brugge et al 2007 Gan et al 2010 Gauderman et al 2007 Jerrett et al 2009 Laden et al 2007 McConnell et al 2006)

Effect of traffic pollution on respiratory and allergic disease in adults cross-sectional and longitudinal analyses Mar Pujades-Rodriacuteguez Tricia McKeever Sarah Lewis Duncan Whyatt John Britton and Andrea Venn

httpwwwsciencedailycomreleases200811081114081003htm April 2011

Traffic Pollution Increases Asthma in Adults Several research results revealed adults who suffer asthma and were exposed to heavy traffic pollution experienced an 80 per cent increase University of Melbourne Rev Public Health 15 (1994) pp 107ndash132 August 2010

Traffic Pollution Aggravates Symptoms In Asthmatic Children Traffic pollution especially in cities adversely affects respiratory health in children with asthma studies suggest that traffic pollution and diesel particles in particular may have a greater effect on respiratory health than other pollutants httpwwwsciencedailycomreleases200811081114081003htm September 2010

Traffic-related air pollution associated with prevalence of asthma and COPDchronic bronchitis A cross-sectional study in Southern Sweden Anna Lindgren Emilie Stroh Peter Montneacutemery September 2009

Acute respiratory health effects of air pollution on children with asthma in US inner cities Benjamin Vaughn MS Meyer Kattan MD Herman Mitchell PhD May 2008

Comparison of Air QualityndashRelated Mortality Impacts of two Different source of emission Transportation in the United States httpwwwtrborgMainBlurbs166402aspx January 2008

Long-term exposure to traffic-related air pollution and cardiovascular mortality Chen H Goldberg MS Burnett RT Jerrett M Wheeler AJ Villeneuve PJ Source Department of Epidemiology and Biostatistics McGill University Montreal Quebec Canada January 2011

heavy-duty vehicles chemical composition impact of exhaust after treatment and fuel parameters Environ Health Perspect102(suppl 4)13ndash23 (1994)

Particulate Matter

PM is a mixture of solid and liquid particles suspended in the atmosphere

as atmospheric aerosols Mobile Pollutants are formed by chemical

reactions of gaseous components from burning of fossil fuel in vehicles

(Gasoline amp diesel motor vehicles)

Source EPA (2012) United States Environmental Protection Agency

Particulate matter basic information Cited October 30th 2012 Available

online at httpwwwepa govairqualityparticlepollutionbasichtml

Source EPA (2012) United States Environmental Protection Agency Particulate matter basic

information Cited October 30th 2012 Available online at httpwwwepa

govairqualityparticlepollutionbasichtml

PM10 25 Long Term Exposure ndashChronic Health Consequences

These particles are associated with a

variety of problems including

Aggravated asthma Chronic

bronchitis

Decreased lung function

Increased respiratory symptoms

coughing or difficulty breathing

Increased Cardiopulmonary Mortality

Increased Risk of Lung Cancer

Sources of Particulate Matter Emissions from traffic

Diesel exhaust particulate matter

This particulate toxic potential has been associated with serious adverse Health

effects including respiratory symptoms Pulmonary function and cardiovascular

diseases (Geller et al 2006 Bernstein et al 2004)

Brake wear particulate matter

Brake wear particulate matter Chemical content (iron(Fe) copper(Cu) Antimony(Sb) barium(Ba) this type of particulate can cause severe respiratory and cardiovascular damages and it is also known that Sb has been classified as a possible human pulmonary carcinogen by the International Agency for Research on Cancer (IARC 1989 Et al 2013)

Fig images of brake wear particles generated at a road simulation study ( centre lt25 μm right lt10

μm) Source [Kukutschovaacute et al 2011]

Tire wear particulate matter

The tire wear particles of the tires are generated either by frictional forces between the treadand the road pavement The chemical content Fe Cr Pb Ti Cr Cu Zn Sr Y Zr Sn Sb Ba LaCe and Pb)

Fig Examples of near spherical particles PM 10 and 25 which are originate from interaction of tires and pavements Source [Dahl et al 2006]

Study Area

The Paso del Norte (PdN) region Selected two strategic areas of study El Paso County zip code 79905 Urban area and Dona Ana County Zip Code 880218802788072 Rural Restricted urban access (freeways and interstates)

Map of the area of the simulation by the MOVES model in the study area

Geographic Domain Zip Code 79905 Urban Area (El Paso County)

Zip Codes 88021880278807288048 (Dona Ana County)

Urban road Delta Dr St 31o 45rsquo 5637- 106o 27rsquo 1212 10 miles

Cordova Bridge of the Americas 31o 45rsquo 4367- 106o 27rsquo 0506 15 miles

478 Highway interstate 31o 46rsquo 1326- 106o 27rsquo 0327 05 miles

110 Highway interstate 31o 46rsquo 1210- 106o 27rsquo 0066 10 miles

10 Interstate Gateway Blvd 31o 46rsquo 397- 106o 26rsquo 4769 05 miles

Chamizal Loop 478 31o 46rsquo 668- 106o 26rsquo 5456 05 miles

Alameda Loop 20 31o 46rsquo 1323- 106o 27rsquo 0328 10 miles

Paisano Dr St Patriot freeway

route 62

31o 46rsquo 0669- 106o 27rsquo 212 15 miles

St Piedras 31o 46rsquo 1326- 106o 27rsquo 0327 10 miles

Dona Ana County Miles

Interstate 25 32o 23rsquo 0561 -106 48

1054 32o 23rsquo 3434- -

106 48 1054 32o 23rsquo

5660 106 48 4314

50

Geographic domain To obtain the simulation mobile data from modelMOVES2010a was configurated the coordinates selected in the study areas

El Paso County

PM25 Estimation from Aerosol Optical Depth (AOD) using

satellites

We examined the relationship

between Aerosol Optical Depth

(AOD) estimated from satellite data

at 5 km spatial resolution and the

mass of fine particles le25 μm in

aerodynamic diameter (PM25)

monitored on the ground in El PdN

area PM25 data was recorded from

air quality monitoring Chamizal

station (TCEQ) on different periods

Our analysis shows a significant

positive association between AOD

and PM25

Time-series and scatter plots of AOD estimated PM25 and surface PM25

Analysis of the meteorological factors and synoptic conditions leading to a local high

ozone event episode June 12-21 2006

Meteorology plays a critical role in determining atmospheric ozone concentrations A good synoptic scale weather forecast is essential to accurately forecast tropospheric and surface ozone concentrations

Figure 1 The domain configuration and Landuse categories

resolution 25 km domainFigure 2 The Geopotential height at 500 mb Figure 3 depicts the 850 mb at a lower altitude The

white regions observed in the graph correspond to

mountainous areas

Figure 4 Temperature at 2m height

above surface at 22 UTC June 18 2006

36 km resolution

Performance Evaluation

01020304050

Ju

ne

137

130

0

190

0

10

0

Ju

ne

157

130

0

190

0

10

0

Ju

ne

187

130

0

190

0

10

0

Tem

pe

ratu

re (⁰C

)

Local time (Hrs)

C41 June 13-19 2006

WRF_temperature

(⁰C)

TCEQ_temperature

(⁰C)

01020304050

June1

37

100

0

130

0

160

0

190

0

220

0

10

0

40

0

June1

57

100

0

130

0

160

0

190

0

220

0

10

0

40

0

June1

87

100

0

130

0

160

0

190

0

220

0

10

0

40

0

Rel

ativ

e h

um

idit

y (

)

Local time (Hrs)

C41 June 13-19 2006

WRF_rh () TCEQ_relative humidity ()

0

5

10

15

20

June

137 10

13

16

19

22 1 4

June

157 10

13

16

19

22 1 4

June

187 10

13

16

19

22 1 4

Win

d s

pee

d (

ms

Local time(Hrs)

C12 June 13-192006

WRF_wind speed (ms) TCEQ_ wind speed (ms)

We evaluate the WRF modelrsquos performance

by comparing against corresponding

experimental TCEQ data and performing the

required statistical analysis

HYSPLIT Model

HYSPLIT was simulated and showed that the ozone is mostly transported to El Paso from north western and south western US and Mexican regions during the 72 hours duration of the simulation

0

20

40

60

80

100

1200

00

10

02

00

30

04

00

50

06

00

70

08

00

90

01

00

01

10

01

20

01

30

01

40

01

50

01

60

01

70

01

80

01

90

02

00

02

10

02

20

02

30

0

Ho

url

y o

zon

e [

pp

b]

0102030405060708090

00

01

00

20

03

00

40

05

00

60

07

00

80

09

00

10

00

11

00

12

00

13

00

14

00

15

00

16

00

17

00

18

00

19

00

20

00

21

00

22

00

23

00

Ho

url

y o

zon

e [

pp

b]

June 18th June 19th

Performance Evaluation

01020304050

Ju

ne

137

130

0

190

0

10

0

Ju

ne

157

130

0

190

0

10

0

Ju

ne

187

130

0

190

0

10

0

Tem

pe

ratu

re (⁰C

)

Local time (Hrs)

C41 June 13-19 2006

WRF_temperature

(⁰C)

TCEQ_temperature

(⁰C)

0

50

100

150

June1

37

100

0

130

0

160

0

190

0

220

0

10

0

40

0

June1

57

100

0

130

0

160

0

190

0

220

0

10

0

40

0

June1

87

100

0

130

0

160

0

190

0

220

0

10

0

40

0Ozo

ne

(pp

b)

Local time (Hrs)

C41 June 13-19 2006

CAMx_ozone (ppbV) TCEQ_ozone (ppb)

0

10

20

30

40

50

June1

37

100

0

130

0

160

0

190

0

220

0

10

0

40

0

June1

57

100

0

130

0

160

0

190

0

220

0

10

0

40

0

June1

87

100

0

130

0

160

0

190

0

220

0

10

0

40

0

Rel

ativ

e h

um

idit

y (

)

Local time (Hrs)

C41 June 13-19 2006

WRF_rh () TCEQ_relative humidity ()

0

5

10

15

20

June

137 10

13

16

19

22 1 4

June

157 10

13

16

19

22 1 4

June

187 10

13

16

19

22 1 4W

ind

sp

eed

(m

sLocal time(Hrs)

C12 June 13-192006

WRF_wind speed (ms) TCEQ_ wind speed (ms)

Methodology

Medical Data The data by weekly monthly and year for daily emergency room and hospital admission for the respiratory

infections (RD) and cardiovascular diseases (CVD) was extracted from hospitals records located in the El PdN

the system includes data on type of admission primary and secondary causes of admissionRESPIRATORY DISEASE

Bronquitis amp Chronic Bronchitis 466 - 4661 491 - 4919

Asthma 463 - 4939

Emphysema 492

Respiratory failure 51881

HEART DISEASE

Accute Myocardial Infarction 410

Coronary Athersclerosis 4140

Other Ischemic Heart Disease 411-4139 4141-4149

Cardiac Dyshythmias 427

Essential hypertension 401

Acute myocardial infarction 410

Congestive Heart Failure 4280 4282-4284

Hypertensive heart disease 402

Table 1 ICD -9 Codes for Respiratory and Cardiovascular Diseases

0

50

100

150

200

250

300

Wee

k 1

Wee

k 2

Wee

k 3

Wee

k 4

Wee

k 5

Wee

k 6

Wee

k 7

Wee

k 8

Wee

k 9

Wee

k 1

0

Wee

k 1

1

Wee

k 1

2

Wee

k 1

3

Wee

k 1

4

Wee

k 1

5

Wee

k 1

6

Wee

k 1

7

Wee

k 1

8

Wee

k 1

9

Wee

k 2

0

Wee

k 2

1

Mo

rb

idit

y D

isch

arg

e fo

r a

ll R

esp

ira

tory

Dis

ease

IC

D-9

(

Ast

hm

aB

ro

nch

itis

)

Weekly Morbidity Discharges of all the Listed Diagnoses for All

Respiratory Disease During WinterSpring 2010

Asthma-Bronchitis

EPA MOVES Model for Estimating Emission

Inventories

Motor Vehicle Emission Simulator (MOVES 2010b) will be configuredin The El Paso North Region for Calculate five categories of PM10

PM25 total Emission inventories from all on-road traffic over a

variety of scales within periods of time selected weeks months

and years

Moves (Motor Vehicle Emission

Simulator)

The emission model is develop using the current equation to calculate direct traffic emissions from

vehicles in the form of PM is

Eext annual emissions are measured in grams of miles traveled by the vehicle (gVMT )

SL is the road surface loading in (gm2)

W is the average weight in tons of the vehicles on the road

K is the particle size multiplier for particle size range (eg gVMT for PM10 when using grams and miles)

P is the 7 number of wet days with at least 0254 mm of precipitation during the averaging period

N is the number of years considered in the averaging period

C is the particle size specific emissions factor in units of interest vehicle direct exhaust brake wear and tirewear

Modeling Simulation Domain and Emissions Scenarios

For simulations of mobile air quality emission inventories a motor vehicle emission simulator EPA (MOVES 2014a) was used

The modeling use input factors divided into seven section

parameters

On-Road Inventory local data

input

Scale

Geographic Bounds

Traffic intensity

Vehicle Type

Pollutants

Road Type

Fuel Types

Figure Source EPA US Environmental Protection Agency 2012- Moves 2010b Model

EPA Moves 2014a The modeling used input factors divided into six section

parameters On-Road Inventory local data input

Geographic Domains CountyNonattainment Area

Vehicle-Miles Traveled (VMT) is the total number of miles driven by all vehicles withina given time period and geographic area

Average speed range from 25 miles per

hour to 65 miles per hour

Vehicle Classes Motorcycle PassengerCarTruks light-duty Commercial Truck(6001-8500 lbs) Buses heave-duty trucksRefuse trucks School Bus Single UnitShort Haul-truck Single Unit Long Haul-truck Long Haul Truck Heavy-DutyVehicles (26001-33000 lbs)

Pollutants

Road TypeRural restricted Acces(Freeways and interstates) Rural and Restricted Acces Urban Restricted Acces Off-Network

Fuel Types Gasoline Diesel Fuel

Specific Road Types

Two road types for running emission from the MOVES can be

selected

(freeways and interstates)

Interior urban Urban

Figure Source EPA US Environmental Protection Agency 2012- Moves 2010b Model

VehiclesEquipment

This panel show which on-road vehicles will be modeled

Figure Source EPA US Environmental Protection Agency 2012- Moves 2010b Model

Long haul truck Short haul truck Inercity bus Ligth comercial truck

Passenger car Passenger truck Refuse truck

School bus Single unit long haul-truck

Single unit short haul-truck

Transit bus

Motor home

Motorcycle

Based on Department of Transportation Highway MOVES will Estimates Traffic

Emissions from Cars Trucks amp Motorcycles

Output Data Moves 2014a

Inventories of PM 10 25 Mobile Emission from all

on-Road Traffic

Exhaust Emission PM 10 25 gramsmile

Brake Wear Emission PM 10 25 gramsmile

Tire wear Emission PM 10 25 gramsmile

Date of Vehicle miles traveled (VMT) for

Day Week Month Year

Total Vehicle population

Vehicle age distribution

Simulation of Mobile Emission in the El PdN Region Zip Code 79905

Figure Total Emissions from road traffic in El Paso TX Area were estimated for PM10

Exhaust and Non exhaust emission in kilogramsmonth (Source EPA MOVES 2014a)

0

10000

20000

30000

40000

50000

PM

10 k

gM

on

th

Months

Monthly PM 10 Exhaust and Non-Exhaust Mobile Emissions 2010

On-Road Urban Restricted Area Zip Code 79905

Primary Exhaust PM 10 (kg) Primary PM 10 Brakewear (kg)

Primary PM 10 Tirewear (kg)

05000

100001500020000250003000035000400004500050000

PM

25

kg

Mo

nth

Months

Monthly PM 25 Exhaust and Non-Exhaust Mobile Emission 2010

On-Road Urban Restricted Area Zip Code 79905

Primary Exhaust PM 25 (kg) Primary PM 25 Brakewear (kg) Primary PM 25Tirewear (kg)

Figure Total Emissions from road traffic in El Paso TX Area were estimated for PM25

Exhaust and Non exhaust emission in kilogramsmonth (Source EPA MOVES 2014a)

Total Emissions from Road Traffic in El Paso County PM1025 Exhaust and Non exhaust Emission in kilogramsmonth

Taking the interests to the health risks related to PM 1025 mobile emission were simulated

Exhaust and Non-exhaust emissions contribute almost equally to total traffic-related PM1025 Emissions (Querol et al 2004 Bukowiecki et al 2009a Amato et al 2011)

Monthly PM 10 25 Exhaust and Non-Exhaust (BrakewearTirewear) Mobile

Emission 2010 On-Road Urban Restricted Area Zip Code 79905

Figure Total Emissions from road traffic in El Paso TX Area were estimated for PM10 25 Exhaust and Non Exhaust mobile

emission in kilograms per month (Source EPA MOVES)

0

10000

20000

30000

40000

50000

January February March April May June July August September October November December

PM

10

25

(K

ilog

ram

s)

Months

Summary- Monthly PM 10 25 Exhaust and Non-Exhaust Mobile

Emission 2010 On-Road Urban Restricted Area Zip Code 79905

Primary Exhaust PM 10 Primary PM 10 Brakewear Primary PM 10 Tirewear

Primary Exhaust PM 25 Primary PM 25 Brakewear Primary PM 25Tirewear

Exhaust Emissions PM1025 is reaching maximum emission 48000-42000 thousand of Kgmonth followedby Brake wear 29000-5000 thousand kgmonth and Tire wear with 9000-2000 kgmonth The results showthat the emissions of PM derived mainly from Exhaust and Brake are significantly higher in Urban Area

Annual Contribution of Mobile Emission PM 1025 (Kg) Zip Code 79905 El

Paso County 2010

Total Primary

Exhaust _PM10

39

Total Primary

Exhaust _PM25

36

Brakewear

particulate_PM10

18

Tirewear

particulate_PM10

4

Brakewear

particulate_PM25

2

Tirewear

particulate_PM25

1

0

5

10

15

20

25

30

35

40

45

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53

Fig Annual Average PM10 Concentrations at the

Chamizal C41 Station and PM1025 mobile

Concentration Zip code 79905

PM10 TCEQ (μgm3) Total Mobile Emission PM10 (Ugm3)

Fig Exhaust Emission is Contributing Approximately 74 of total

PM1025 Mobile Emissions following of Brake wear with 20 and Tire

wear with 5

Annual Average PM1025 ugm3 Mobile Emissions (Moves) 26 Chamizal C41

Monitoring Station (TCEQ Chamizal Station )

Predicting Mobile Emission and VTM

Estimation The PdN Region 2010

44E+09

46E+09

48E+09

5E+09

52E+09

54E+09

56E+09

58E+09

6E+09

62E+09

0

50000

100000

150000

200000

250000

300000

350000

20

10

20

11

20

12

20

13

20

14

20

15

20

16

20

17

20

18

20

21

20

22

20

23

20

24

20

25

20

26

20

27

20

28

20

29

20

30

EX

HA

US

T

EM

ISS

ION

MO

BIL

E (

KG

YE

AR

)

YEARS

Predict ing Mobile Exhaust Emission and VTM

Estimation

2010 - 2030 e l PdN Area

Total_ Exhaust PM10 Total_ Exhaust PM25 Distance (Miles)

Fig Predicting Mobile Exhaust PM1025 (kgMonth) Emission and VTM Estimation 2010

- 2030 el PdN Area

44E+09

46E+09

48E+09

5E+09

52E+09

54E+09

56E+09

58E+09

6E+09

62E+09

0

5000000

10000000

15000000

20000000

25000000

30000000

20

10

20

11

20

12

20

13

20

14

20

15

20

16

20

17

20

18

20

21

20

22

20

23

20

24

20

25

20

26

20

27

20

28

20

29

20

30

EX

HA

US

T

EM

ISS

ION

MO

BIL

E (

KG

YE

AR

)

YEARS

Predict ing Mobile Exhaust Emission and

VTM Estimation

2010 - 2030 e l PdN Area

CO NO2 NO NOx Distance

Fig Predicting Mobile Exhaust Emission and VTM Estimation

2010 - 2030 el PdN Area in El Paso TX Area were estimated for

Total CO NOx NO2 NO emission in kilograms per year

(Source EPA MOVES 2014a model)

The simulated Exhaust emissions in the future years shows a trend of reduction of this type of emissions in the

future years one factor should be the new hybrid technology is increasing by 476 since 2010 to 2015 and

use of catalytic converters diesel particulate filters and improved fuels and engines Non-exhaustive sources

will increase in the coming years because there is no control in the material of manufacture composed by Fe

Cu and Mn also not to be able to reduce the number of events of braking (Accelerations and decelerations)

45E+09

5E+09

55E+09

6E+09

65E+09

0

50000

100000

150000

200000

250000

201

0

201

1

201

2

201

3

201

4

201

5

201

6

201

7

201

8

202

1

202

2

202

3

202

4

202

5

202

6

202

7

202

8

202

9

203

0

NO

N-

EX

HA

US

T

EM

ISS

ION

MO

BIL

E

(KG

YE

AR

)

YEARS

Predicting Non Exhaust Mobile

Emission and VTM Estimation

2010 - 2030 el PdN Area

Brake_PM10 Tire_PM10 Distance (Miles)

Fig Predicting Mobile Exhaust PM1025 (kgMonth) Emission and VTM

Estimation 2010 - 2030 el PdN Area

Daily Avg PM1025

Levels of PM Mobile Emission Non-Exhaust -Rush Hour Periods Fall 2010 Zip Code

79905

00

100

200

300

400

500

600

Mo

bil

e P

M1

0 (k

g)

Rush Hours

Daily Avg PM10

Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush Hours

Periods 2010 Zip Code 79905

Total Primary Exhaust

_PM10 WinterSpring

Brakewear

particulate_PM10

WinterSpringTirewear particulate_PM10

WinterSpring

Total Primary Exhaust

_PM10 Summer

Brakewear

particulate_PM10 Summer

Tirewear Particulate_PM10

Summer

Total Primary Exhaust

_PM10 Fall

Brakewear

particulate_PM10 Fall

Tirewear particulate_PM10

Fall

00

50

100

150

200

250

300

350

Mo

bil

e P

M2

5 (k

g)

Rush hours

Daily Avg PM25

Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush

Hours Periods 2010 Zip Code 79905

Total Primary Exhaust _PM25

WinterSpring

Brakewear Particulate_PM25

WinterSpring

Tirewear particulate_PM25

WinterSpring

Total Primary Exhaust _PM25

Summer

Brakewear particulate_PM25

Summer

Tirewear particulate_PM25

Summer

Total Primary Exhaust _PM25

Fall

Brakewear particulate_PM25

Fall

Tirewear particulate_PM25

Fall

Figure Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush Hours Figure Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush Hours

GIS EMISSIONS INVENTORY SYSTEM A geographic information system (GIS) was used to established geographic scenarios with processed images of seasonal mobile

emissions in the PdN region Seasonal mapping is visualized for different types of pollutants Brakewear Exhaust and Tyrewear

Fg Graphics of GIS and Seasonal mobile Emission of particulate matter emission inventory Seasonal emission simulations were performed in kilograms and five contributing inputs factors were identified for

modeling 1) On the composition of the particulate material from different sources such as Exhaust and Non exhaust (Brake wear Tirewear) 2) The Vehicles Equipment clasification were selected according to

the use of gasoline and diesel fuel (motorcycle passenger car Light Duty Vehicles Trucks refuse truck Light Duty Vehicles Light Commercial Truck Light Duty Vehicles School Bus)

Winter Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

120354 67860 19065

Spring Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

139767 86702 24463

Summer Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

94747 62481 17630

Fall Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

75510 45542 12596

251 Descriptive Statistics Data Analysis

Weekly Correlation Analysis of Mobile Emission PM10 (Exhaust-Non-Exhaust) and Respiratory

Diagnoses WinterSpring Summer and Fall 2010

0

2

4

6

8

10

0

50

100

150

200

250

300

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21

Mo

rbid

ity

Dis

ch

arg

e

for

all R

esp

ira

tory

Dis

ea

se

ICD

-9

(A

sth

ma

-Bro

nc

hitis

)

WinterSpring Week

Weekly Avg Mobile PM10 Concentrations during

WinterSpring 2010 and its Influence on Respiratory

Diagnoses

Zip Code 79905

Total Medical data ZIP Code 79902

Total Mobile Emission PM10 (Ugm3)

0

1

2

3

4

5

6

7

0

20

40

60

80

100

Mo

rbid

ity

Dis

ch

arg

e

for

all R

esp

ira

tory

Dis

ea

se

ICD

-9

(Ast

hm

aB

ron

ch

itis

)

Weekly Avg Mobile PM10 Concentrations during

Summer 2010 and its Influence on Respiratory

Diagnoses

Summer 2010 Zip Code 79905

Total Mobile Emission PM10

Hospital Admission (Asthma-Bronchitis)

0

2

4

6

8

10

12

0

20

40

60

80

100

120

140

160

180

200

Mo

rbid

ity

dis

ch

arg

es

for

all r

esp

ira

tory

dis

ea

se

Weekly Avg Mobile PM10 Concentrations

during Fall 2010 and its Influence on Respiratory

Diagnoses

Zip Code 79905

Total Medical data ZIP Code 79902

Total Mobile Emission PM10 (Ugm3)

Mobile(Exhaust-Non-

Exhaust) PM10 and

Asthma-Bronchitis)

Linear R

Square

WinterSpring 734 ndash 39

Summer 614 ndash 32

Fall 548 -29

PM10 Mobile emission (Exhaust-Non-Exhaust)contributed significantly

association to the incidence of RD

Weekly Correlation Analysis of PM 25 Mobile Emission (Exhaust-Non-Exhaust)

and Cardiovascular Diagnoses WinterSpring Summer and Fall 2010

0010203040

00500

100015002000

Wee

k 1

Wee

k 2

Wee

k 3

Wee

k 4

Wee

k 5

Wee

k 6

Wee

k 7

Wee

k 8

Wee

k 9

Wee

k 1

0

Wee

k 1

1

Wee

k 1

2

Wee

k 1

3

Wee

k 1

4

Wee

k 1

5

Wee

k 1

6

Wee

k 1

7

Wee

k 1

8

Wee

k 1

9

Wee

k 2

0

Wee

k 2

1

Morb

idit

y d

isch

arg

es f

or

all

card

iovasc

ula

r d

isea

se

Weekly Avg PM25 Mobile Concentrations during

WinterSpring 2010 and its Influence on all Heart

Diagnoses

Zip Code 79905

Total All Heart Disease PM 25 mobile (μgm3)

0010203040

00

500

1000

1500

Mo

rbid

ity

dis

ch

arg

es

for

all

ca

rdio

va

scu

lar

dis

ea

se

Weeks

CORRELATION BETWEEN MOBILE PM25 ugm3

EXPOSURE TO HEART DISEASES SYMPTOMS

SUMMER SEASON 2010

Total All Heart Disease PM 25 mobile (μgm3)

Figure Statistical Analyses of the Relationship Between PM25 Caused by Traffic Emission( 26 of total Emission) with Heart diseases Source Hospital Admissions for Asthma Acute Bronchitis and Heart diseases in El Paso County zip code 79905 from Texas Health Care

Information Council in Austin Texas (Texas Health Care Information Council 2000)

00

10

20

30

40

0

50

100

150

We

ek 3

6

We

ek 3

7

We

ek 3

8

We

ek 3

9

We

ek 4

0

We

ek 4

1

We

ek 4

2

We

ek 4

3

We

ek 4

4

We

ek 4

5

We

ek 4

6

We

ek 4

7

We

ek 4

8

We

ek 4

9

We

ek 5

0

We

ek 5

1

We

ek 5

2

We

ek 5

3

Mo

rbid

ity

dis

ch

arg

es

for

all

ca

rdio

va

scu

lar

dis

ea

se

CORRELATION BETWEEN MOBILE PM25 ugm3

EXPOSURE TO HEART DISEASES SYMPTOMS FALL

SEASON 2010

Total All Heart Disease PM 25 mobile (μgm3)

Mobile(Exhaust-

Non-Exhaust)

PM10 and

Asthma-

Bronchitis)

Linear R

Square

WinterSpring 833 -42

Summer 620 -32

Fall 501-26

PM10 Mobile

emission (Exhaust-

Non-

Exhaust)contribut

ed significantly

association to the

incidence of CVD

Diseases

Monthly Brake Mobile Emission PM1025 kg During year 2010 and its Influence on

Respiratory Diagnoses Zip Code 79905

00200040006000800010000

010000200003000040000

PM

10

Mo

bile

(K

g)

Months

Monthly Brake Mobile Emission PM10 kg during year

2010 and its Influence on Respiratory Diagnoses

Zip Code 79905

Primary PM 10

Brakewear 00100020003000400050006000

0

1000

2000

3000

4000

PM

25

Mo

bil

e(K

g)

Months

Monthly Brake Mobile Emission PM25 during

year 2010 and its Influence on Heart Diagnoses

Zip Code 79905

Primary PM 25

Brakewear

Heart Diseases

Hospital

Admission

Brake Mobile Emission

PM10 kg Asthma-

Bronchitis)

Brake Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=969 Linear Square R=856

Monthly Mobile Exhaust Emission PM1025 During year 2010 and its Influence on

Respiratory Diagnoses Zip Code 79905

0

200

400

600

800

1000

0

10000

20000

30000

40000

50000

1 3 5 7 9 11

PM

10

(K

g m

on

th)

Months

Monthly Mobile Exhaust Emission PM10 during

year 2010 and its Influence on Respiratory

Diagnoses

Zip Code 79905

Primary Exhaust

PM 10

Respiratory Disease

(Asthma

Bronchitis) Hospital

Admission

0

100

200

300

400

500

600

0

10000

20000

30000

40000

50000

1 2 3 4 5 6 7 8 9 101112

PM

25

(K

g m

on

th)

Months

Monthly Exhaust Mobile Emission PM25 during

year 2010 and its Influence on Heart Diagnoses

Zip Code 79905

Primary Exhaust PM

25

Heart Diseases

Hospital Admission

Exhaust Mobile Emission

PM10 kg Asthma-

Bronchitis)

Exhaust Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=929 Linear Square R=831

Monthly Tire wear Mobile Emission PM1025 During year 2010 and its Influence on Heart

Diagnoses Zip Code 79905

0

100

200

300

400

500

600

700

800

900

0

1000

2000

3000

4000

5000

6000

7000

8000

9000

1 2 3 4 5 6 7 8 9 10 11 12

PM

10

(K

g m

on

th)

Months

Monthly Tirewear Mobile Emission PM10 during year 2010

and its Influence on Heart Diagnoses

Zip Code 79905

Primary PM 10 Tirewear

Mobile Emission

Respiratory Disease

(Asthma Bronchitis)

Hospital Admission

0

100

200

300

400

500

600

0

200

400

600

800

1000

1200

1400

1 2 3 4 5 6 7 8 9 10 11 12

PM

25

(K

g m

on

th)

Months

Monthly Tirewear Mobile Emission PM25 during year 2010

and its Influence on Respiratory Diagnoses

Zip Code 79905

Primary PM 25Tirewear

Mobile Emission

Heart Diseases Hospital

Admission

Exhaust Mobile Emission

PM10 kg Asthma-

Bronchitis)

Exhaust Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=769 Linear Square R=715

Dona Ana County Zip Codes

88021880278807288048

Primary

Exhaust

PM 10 Zip

code

79905

Total

Primary

Exhaust

PM10

Dona Ana

Primary

Exhaust

PM 25 Zip

Code

79905

Total

Primary

Exhaust

PM25

Dona Ana

Series1 430378 111773 391915 102123

0

100000

200000

300000

400000

500000

AX

IS T

ITLE

Annual Comparison of the Mobile

Exhaust Emissions El Paso County

and Dona Ana 2010

Primary

PM 10

Brakewea

r Zip code

79905

Brakewea

r

particulat

e_PM10

Dona Ana

Primary

PM 10

Tirewear

Zip code

79905

Tirewear

particulat

e_PM10

Dona Ana

Series1 262585 48573 73754 11864

050000

100000150000200000250000300000

AX

IS T

ITLE

Annual Comparison of the Mobile

Brakewear Emissions El Paso County

and Dona Ana 2010

Figure Comparison of the Annual Mobile Emissions

of Primary PM10 Non-Exhauts (Brake ) from Dona

Ana County New Mexico and El Paso Texas Units

in KgMonth

Figure Comparison of the Annual Mobile Emissions

of Primary PM10-Exhauts Emission from Dona Ana

County New Mexico and El Paso Texas Units in

KgMonth

Primary

PM 25

Brakewe

ar Ziphellip

Brakewe

ar

particula

te_PMhellip

Primary

PM

25Tirewe

ar Ziphellip

Tirewear

particula

te_PM25

Donahellip

Series1 32645 6071 10919 1779

0

10000

20000

30000

40000

AX

IS T

ITLE

Annual Comparison of the

Mobile Exhaust Emissions El Paso

County and Dona Ana 2010

Figure Comparison of the Annual Mobile Emissions

of Primary PM10-Exhauts Emission from Dona Ana

County New Mexico and El Paso Texas Units in

KgMonth

Monthly Mobile Emission PM1025 kg During year 2006

and its Influence on Respiratory Diagnoses Dona Ana

County Zip Code 880218802788072

0

100

200

300

0

5000

10000

15000

Axi

s Ti

tle

Axis Title

Monthly Mobile Exhaust Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Total PrimaryMobile Exhaust_PM10

All Respiratory ICD-9 (AsthmaBronchitis)

050100150200250300

010002000300040005000

Axi

s Ti

tle

Axis Title

Monthly Mobile Brake Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Brakewearparticulate_PM10

All RespiratoryICD -9 (AsthmaBronchitis)

050100150200250300

0200400600800

10001200

Axi

s Ti

tle

Axis Title

Monthly Mobile Tirewear Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Tirewearparticulate_PM10

All Respiratory ICD -9 (AsthmaBronchitis)

Mobile Exhauts

Emission PM10

kg Asthma-

Bronchitis)

Brake Mobile

Emission PM10

kg and Heart

Diagnoses

Tirewear Mobile

Emission PM10

kg and Heart

Diagnoses

Linear Square

R= 951

Linear Square

R=625

Linear Square

R=525

Mobile Exhauts

Emission PM25

kg Asthma-

Bronchitis)

Brake Mobile

Emission PM25

kg and Heart

Diagnoses

Tirewear Mobile

Emission PM25

kg and Heart

Diagnoses

Linear Square

R= 986

Linear Square

R=691

Linear Square

R=601

Results

The results showed that mobile PM emissions in the urban areas close to urban Road and highways is putting at risk public health

and the proportion of diseases attributable to this exposure is potentially large

Brake wear emissions is much lower in freeways due to significantly reduced number of braking events while tire wear is much

higher in areas where studded tires are used The emission of exhaust gases are much higher in areas where there is a high

vehicular traffic

Brake Mobile

Emission PM10 kg

Asthma-Bronchitis)

Brake Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square

R=969

Linear Square

R=856

Exhaust Mobile

Emission PM10 kg

Asthma-Bronchitis)

Exhaust Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square

R=929

Linear Square

R=831

Tirewear Mobile

Emission PM10 kg

Asthma-Bronchitis)

Tirewear Mobile

Emission PM25 kg

and Heart Diagnoses

Linear Square R=769 Linear Square R=715

Brake Mobile

Emission PM10 kg

and Heart

Diagnoses

Brake Mobile

Emission PM25 kg

and Heart

Diagnoses

Exhaust Mobile

Emission PM10 kg

Asthma-Bronchitis)

Linear Square

R=625

Linear Square

R=691

Linear Square R=

951

Exhaust Mobile

Emission PM25 kg

Asthma-

Bronchitis)

Tire wear Mobile

Emission PM10 kg and

Heart Diagnoses

Tirewear Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square R=

986

Linear Square R=525 Linear Square

R=601

El Paso County

Dona Ana

County

BenMAP-CE

In this analysis the Program of Mapping and Analysis of Environmental Benefits-Community Edition

(BenMAP-CE) was used to Estimate the number and economic value of health impacts resulting from changes

in air pollution PM 25 Ugm3 in The El Paso Area

Health and Economic Benefits associated with the Response of PM25 Emission between

Base Year 2010

Number of Mortalities in 2010 Base Year Based on El Paso County Texas Department of State Health Services

Number of Mortalities in 2010 Base Year Based on El Paso County Texas

Department of State Health Services

cause of death

year

2010

Populatio

n

Affected

Backgro

und

Concentr

ation Pollutant

Rollback

Type

Avoided

Deaths

(

Populatio

n)

alzheimers disease 2010 40716 125 PM25

25

microgmAcircsup3

Rollback 9

diseases of the

heart 2010 15834 125 PM25

25

microgmAcircsup3

Rollback 35

influenza and

neumonia 2010 81432 125 PM25

25

microgmAcircsup3

Rollback 18

acute bronchitis

and bronchiolitis 2010 117624 125 PM25

25

microgmAcircsup3

Rollback 26

chronic lower

respiratory diseases 2010 54288 125 PM25

25

microgmAcircsup3

Rollback 12

The Basin-wide decrease in 4 ugm3 PM25 concentration after this

reduction control

Cause of death year 2010

Populatio

n

Affected

Background

Concentrati

on

Reduc

cion

scena

rio Polluta

nt

Rollback

Type

Avoi

ded

Deat

hs

(

Pop

ulati

on)

economic

benefits

analysis $

Alzheimers

disease 2010 121 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 9 12000

Diseases of the

heart 2010 470 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 35 35000

Influenza and

neumonia 2010 242 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 18 42500

Acute bronchitis

and bronchiolitis 2010 349 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 26 95000

Chronic lower

respiratory

diseases 2010 161 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 12 4500

$1 295000

PM25-related Mortalities Based on BenMAP-CE Estimate in 2010 Base Year with change in the concentrations levels

Health and Economic Benefits associated with the Response of PM25 Emission between

Base Year 2010 Increasing 7 Ugm3

Cause of death year 2010

Population

Affected

Deaths

avoided by

attaining 195

μgm3

standard

Background

Concentrati

on

Pollut

ant

Rollback

Type

Avoided

Deaths (

Populatio

n)

econo

mic

Unben

efits

analysi

s

Alzheimers

disease 2010 4524 195 PM25

25

microgmAcircsup3

Rollback 19 150000

Diseases of the

heart 2010 20358 195 PM25

25

microgmAcircsup3

Rollback 135 450000

Influenza and

neumonia 2010 126672 195 PM25

25

microgmAcircsup3

Rollback 38 525000

Acute bronchitis

and bronchiolitis 2010 162864 195 PM25

25

microgmAcircsup3

Rollback 36 122000

Chronic lower

respiratory

diseases 2010 99528 195 PM25

25

microgmAcircsup3

Rollback 12 650000

Conclusions

An excellent Pearson Correlation was established to analyze the relationship in the relative risks of hospitalization of Respiratory(RD) and cardiovascular (CVD) associated with ambient exposure caused by traffic emission in relation to their size andspecific sources of emission on different scenarios interior a border Urban Rural Urban restricted access (freeways andinterstates)

A significant correlation of PM1025 exposure from mobile emission and hospital admissions for selected Respiratory (RD) andcardiovascular (CVD) diagnoses was established The results showed that PM emissions in urban restricted access (freeways andinterstates) is mainly caused by traffic Therefore people living close to highways are more exposed higher vehicular emissions

Conclusions

We found statistically significant associations between mobile PM25 caused by traffic emission with Respiratory and Cardiovascular Diseases in the study areaSubsequently a correlation between cardio-respiratory mortality is established

A significant correlation of PM1025 exposure from mobile emission and hospital admissions for selected Respiratory (RD) and cardiovascular (CVD) diagnoses isestablished The results showed that PM emissions in urban restricted access (freeways and interstates) is mainly caused by traffic Therefore people living close tohighways receive higher vehicular emissions

The table shows the percentage of PM mobile exposure in the analyzed areas contributing to increase the risk of Respiratory and Cardiovascular Diseases

An examination was conducted of the synoptic and local meteorology for the June 2006 ozone episode using the WRF model to determine how meteorological parametersinfluence the formation transport and dispersion of ozone in the PdN The predominant synoptic feature of the ozone event day was the expansion intensification and slowprogression of an upper-level ridge of high pressure The high ozone episodes are associated with highly stable atmospheres strong temperature inversions with low mixingheights and therefore low mixing volumes Under these conditions emissions such as NOx lead to highly polluted conditions that favor ozone formation

BenMAP Conclusions

We have estimated the number and economic value of health impacts resulting

from changes in air pollution concentrations of PM 25 in the PdN region

Reduction of Pm 25 4 UGm3= Avoided 213 cases respiratory cardiovascular

diseses and Economic Benefits associated with the Response of PM25 Emission + $

1295000

Increase of PM25 7 ugm3 = increasing Dies= 326 economic Unbenefits= 2345000$

Bibliography

1 Dockery DW Pope CAI Xu X Spengler JD Ware JH Fay ME Ferris BG Speizer FE An association between air pollution and mortality in six US cities N Engl J Med 3291753ndash1759 (1993)

2 Samet JM Dominici F Curriero FC Coursac I Zeger SL Fine particulate air pollution and mortality in 20 US cities 1987ndash1994 N Engl J Med 3431742ndash1749 (2000)

3 Nel AE Diaz-Sanchez D Li N The role of particulate pollutants in pulmonary inflammation and asthma evidence for the involvement of organic chemicals and oxidative stress Curr Opin Pulm Med 20017 20ndash26

4 Westerholm R Karl-Erik E Exhaust emissions from lightand heavy-duty vehicles chemical composition impact of exhaust after treatment and fuel parameters Environ Health Perspect 102(suppl 4)13ndash23 (1994)

5 Bascom R Bromberg P Costa D Delvin R Dockery D Frampton M Lambert W Samet J Speizer F Utell

6 Health effects of outdoor air pollution Am J Respir Crit Care Med 1533ndash50 (1996)

7 Chow JC Watson JG Frazier CA Egami RT Goodrich A Ralph C Spatial and temporal source contributions to

8 PM10 and PM25 in Reno NV In PM-10 Implementation of Standards Transactions An APCAEPA International Speciality Conference San Francisco CA (Mathal CV Stonefield DH eds) PittsburghAPCA 1988439ndash457

9 overview In Particulate Matter Health and Regulatory Issues VIP-49 Proceedings of an International Specialty Conference 4ndash6 April 1995 Pittsburgh PA PittsburghAir and Waste Management Association 1995577ndash598

10 Kunzli N Kaiser R Medina S Studnicka M Chanel O

11 Filliger P Herry M Horak F Jr Puybonnieux-Texier V Quenel P et al Public-health impact of outdoor and traffic- related air pollution a European assessment Lancet 356795ndash801 (2000)

Bibliography

1 Sioutas C Delfino RJ Singh M Exposure assessment for atmospheric ultrafine particles (UFP) and implications in epidemiological research Environ Health Perspect 2005113947ndash955

2 Mosleh M Blau PJ Dumitrescu D (2004) Characteristics and morphology of wear particles from laboratory testing of disc brake materials Wear 2561128ndash1134

3 Kuumlnzli N et al (2000) Public-health impact of outdoor and traffi c-related air pollution a European assessment Lancet 356(9232)795ndash801

4 Dora C Phillips M eds (2000) Transport environment and health Copenhagen WHO Regional Office for Europe (WHO Regional Publications European Series No 89 httpwwweurowhointdocumente72015pdf accessed 26 November 2004)

5 Westerholm R Karl-Erik E Exhaust emissions from lightand

6 heavy-duty vehicles chemical composition impact of exhaust after treatment and fuel parameters Environ Health Perspect 102(suppl 4)13ndash23 (1994)

7 Fauser Tjell Mosbaek pigegaard Quantification of tire-Tread particles using extractable Organic Zinc as a Tracer Rubber Chemistry and Technology 1999 969Table shows some literature estimates of the contribution of tire wear to PM10 in air (Panko et al 2013) Gustafsson M Blomqvist G Gudmundsson A Dahl A Swietlicki E Bohgard M Lindbom J Ljungman A

8 Chen Y Shah N Huggins FE and Huffman GP (2006) Microanalysis of Ambient Particles from Lexington Ky by Electron Microscopy Atmos Environ 40 651ndash663

9 Donaldson K Tran CL Jimenez LA Duffin R Newby DE and Mills N (2005) Combustion-derived Nanoparticles A Review of Their Toxicology Following Inhalation Exposure Part Fibre Toxicol 2 10ndash23

10 Su D Serafino A Muller JO Jentoft RE Schlogl R and Fiorito S (2008) Cytotoxicity and Inflammatory Potential of Soot Particles of Low-emission Diesel Engines Environ Sci Technol 42 1761ndash1765

11 Maier KL Alessandrini F Beck-Speier I Hofer TPJ Diabatґe S Bitterle E Stoger T and Jakob T (2008) Health Effects of Ambient Particulate Matter-Biological Mechanisms and Inflammatory Responses to in Vitroand in Vivo Particle Exposures Inhalation Toxicol 20 319ndash337

Page 5: Studies of Air Pollutants and their Impact on Respiratory and ...€¦ · Ascarate Park C37 Monitoring Station: The National Ambient Air Quality Standard (NAAQS) for PM 10 and 2.5

Introduction

The Paso del Norte (PdN) region is

one of the largest metropolitan areas

along the US-Mexico border This

includes El Paso Ciudad Juarez

Mexico Each year over 18 million

vehicles cross the three international

ports of entry between El Paso and

Cuidad Juaacuterez

Approximately one-quarter of the

population in The Paso del Norte

(PdN) region lives close to major

roadways exposing the people to

risks of severe respiratory infections

and cardiovascular diseases (Trainer

M Parrish DD and Goldan PD 2000)

Significance of the Work

Traffic is a major source of mobile emissions causing air pollution

Mobile emissions such as

Exhaust Emissions (Carbon Monoxide Nitrogen Oxides and

Hydrocarbons) and Non-exhaust (Brake and Tire) Particulate

emissions can also be very damaging to health because their tiny

diameter can enter the respiratory system easily and possibly cause

adverse health impacts (pulmonary carcinogen inflammatory and

toxic effect on the lung (IARC 1989 Et al 2013) (Kelly and Fussell

2012) (iron(Fe) copper(Cu) Manganese(Mn) antimony(Sb)

barium(Ba) zinc(Zn)

Therefore the relevance of this research provides a key

knowledge to understand the impacts of traffic emissions on air

quality and the magnitude of public health risks associated with

exposure to mobile emissions

Problem Statement

0

100

200

300

400

500

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31

PM

10 (

μg

m3)

Days

Chamizal C 41

Montly 24 Hours Average

PM-10 measured in micrograms per cubic meter (μgm3)

2006 January

February

March

April

May

June

July

August

September

October

November

The National Ambient Air Quality Standard (NAAQS) for PM was Exceeded in The PdN Region during

2006 2010 Analysis of Chamizal Area Zip Code 79905

These chart illustrates two high spikes that occurred which exceeds the 24 hour average

0

20

40

60

80

100

120

140

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31

PM

25

( μ

gm

3)

Days

Chamizal C 41

Montly 24 Hours Average

PM-25 measured in micrograms per cubic meter (μgm3)

2006 january

February

March

April

May

June

July

August

September

October

November

December

Chamizal C41Monitoring Station The National Ambient Air Quality Standard (NAAQS) for PM 10 and 25 was

exceeded but in 24 hour average The NAAQS for PM 25 for 24-hour average is PM2535 microgmsup3 and PM10 50-

100 microgmsup3 The highest concentration occurred several times PM10(150200300450 microgmsup3)

PM25(4050607080120 microgmsup3 )

Problem Statement

0

100

200

300

400

500

600

700

800

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31

PM

10 (

μg

m3)

Days

Ascarate Park SE C37

Montly 24 Hours Avg PM 10 Exceedences and Maximum

Concentrations 2010 January

February

March

April

May

June

July

August

September

October

November

December

Graph 1 Source TCEQ ( Texas Commission on Environmental Quality) Ascarate Park monitoring station Data 2010

0

20

40

60

80

100

120

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31

PM

25

UG

M3

DAYS

Ascarate Park SE C37

Montly 24 Hours Average

PM-25 measured in micrograms per cubic meter

(μgm3)

2010 JanuaryFebruaryMarchAprilMayJuneJulyAugustSeptemberOctoberNovemberDecember

Graph 2 Source TCEQ ( Texas Commission on Environmental Quality) Ascarate Park monitoring station Data 2010

Ascarate Park C37 Monitoring Station The National Ambient Air Quality Standard (NAAQS) for PM

10 and 25 was exceeded but in 24 hour average The NAAQS for PM 25 for 24-hour average is

PM2535 microgmsup3 and PM10 50-100 microgmsup3 The highest concentration occurred several times

PM10(200250300400600720 microgmsup3) PM25(4090120microgmsup3)

The National Ambient Air Quality Standard (NAAQS) for PM was Exceeded in The PdN Region 2006 2010

Analysis of Ascarate Area Zip Code 79905

These chart is to illustrate there are two high spikes that occurred which exceeds the 24 hour average

Fig Number of registered automobiles in Texas The Statistics show the

number of registered automobiles truck motorcycle in Texas Source

Texas department motor vehicles

Fig More than 61 percent of

US transportation emissionscome from cars and lighttrucks

Fig in US On-roadmobile sourcesconstitute the largestsingle source categoryof air pollution with(327)

Problem Statement

13000000140000001500000016000000170000001800000019000000

Millio

ns

of

Ve

hic

les

Years

Total Growth of Texas Registrations

2001-2012

Total

Vehicles

Registratio

ns

Problem Statement

El Paso Texas and ciudad Juarez currently has commercialmovements through El PasondashCiudad Juarez gateways peaked at715000 trucks in the year 2010 and Approximately 40000 vehicles passthese roads each laborable day

Source US Department of Transportation Bureau of Transportation Statistics 2010

Bridge Number of US-bound

Truck Crossings year 2010

World Trade Bridge 1327479

Pharr ndash Reynosa International Bridge

452821

Ysleta ndash Zaragoza Bridge 379508

Laredo ndash Colombia Solidarity

Bridge

374781

Bridge of the Americas 337609

Veterans International Bridge 177986

Camino Real International Bridge 106423

Del Rio ndash Ciudad Acuna

International Bridge

62966

Progreso International Bridge 42605

Free Trade Bridge 30773

Source CBP

Fig Bridge of the Americas (Puente Cordova)

Publications Review to examine the relationship between exposure to motor vehicle emissions and respiratory and cardiovascular disease

We have analyzed the current literature which have served as the basis for this project

Some studies determined that traffic-related emissions have been recognized as a major contributor to urban air pollution in particular major cities proximity to major roadways and exposure to motor vehicle exhaust and Non-exhaust emissions are associated with increased risks of cardiovascular respiratory and other diseases (Brugge et al 2007 Gan et al 2010 Gauderman et al 2007 Jerrett et al 2009 Laden et al 2007 McConnell et al 2006)

Effect of traffic pollution on respiratory and allergic disease in adults cross-sectional and longitudinal analyses Mar Pujades-Rodriacuteguez Tricia McKeever Sarah Lewis Duncan Whyatt John Britton and Andrea Venn

httpwwwsciencedailycomreleases200811081114081003htm April 2011

Traffic Pollution Increases Asthma in Adults Several research results revealed adults who suffer asthma and were exposed to heavy traffic pollution experienced an 80 per cent increase University of Melbourne Rev Public Health 15 (1994) pp 107ndash132 August 2010

Traffic Pollution Aggravates Symptoms In Asthmatic Children Traffic pollution especially in cities adversely affects respiratory health in children with asthma studies suggest that traffic pollution and diesel particles in particular may have a greater effect on respiratory health than other pollutants httpwwwsciencedailycomreleases200811081114081003htm September 2010

Traffic-related air pollution associated with prevalence of asthma and COPDchronic bronchitis A cross-sectional study in Southern Sweden Anna Lindgren Emilie Stroh Peter Montneacutemery September 2009

Acute respiratory health effects of air pollution on children with asthma in US inner cities Benjamin Vaughn MS Meyer Kattan MD Herman Mitchell PhD May 2008

Comparison of Air QualityndashRelated Mortality Impacts of two Different source of emission Transportation in the United States httpwwwtrborgMainBlurbs166402aspx January 2008

Long-term exposure to traffic-related air pollution and cardiovascular mortality Chen H Goldberg MS Burnett RT Jerrett M Wheeler AJ Villeneuve PJ Source Department of Epidemiology and Biostatistics McGill University Montreal Quebec Canada January 2011

heavy-duty vehicles chemical composition impact of exhaust after treatment and fuel parameters Environ Health Perspect102(suppl 4)13ndash23 (1994)

Particulate Matter

PM is a mixture of solid and liquid particles suspended in the atmosphere

as atmospheric aerosols Mobile Pollutants are formed by chemical

reactions of gaseous components from burning of fossil fuel in vehicles

(Gasoline amp diesel motor vehicles)

Source EPA (2012) United States Environmental Protection Agency

Particulate matter basic information Cited October 30th 2012 Available

online at httpwwwepa govairqualityparticlepollutionbasichtml

Source EPA (2012) United States Environmental Protection Agency Particulate matter basic

information Cited October 30th 2012 Available online at httpwwwepa

govairqualityparticlepollutionbasichtml

PM10 25 Long Term Exposure ndashChronic Health Consequences

These particles are associated with a

variety of problems including

Aggravated asthma Chronic

bronchitis

Decreased lung function

Increased respiratory symptoms

coughing or difficulty breathing

Increased Cardiopulmonary Mortality

Increased Risk of Lung Cancer

Sources of Particulate Matter Emissions from traffic

Diesel exhaust particulate matter

This particulate toxic potential has been associated with serious adverse Health

effects including respiratory symptoms Pulmonary function and cardiovascular

diseases (Geller et al 2006 Bernstein et al 2004)

Brake wear particulate matter

Brake wear particulate matter Chemical content (iron(Fe) copper(Cu) Antimony(Sb) barium(Ba) this type of particulate can cause severe respiratory and cardiovascular damages and it is also known that Sb has been classified as a possible human pulmonary carcinogen by the International Agency for Research on Cancer (IARC 1989 Et al 2013)

Fig images of brake wear particles generated at a road simulation study ( centre lt25 μm right lt10

μm) Source [Kukutschovaacute et al 2011]

Tire wear particulate matter

The tire wear particles of the tires are generated either by frictional forces between the treadand the road pavement The chemical content Fe Cr Pb Ti Cr Cu Zn Sr Y Zr Sn Sb Ba LaCe and Pb)

Fig Examples of near spherical particles PM 10 and 25 which are originate from interaction of tires and pavements Source [Dahl et al 2006]

Study Area

The Paso del Norte (PdN) region Selected two strategic areas of study El Paso County zip code 79905 Urban area and Dona Ana County Zip Code 880218802788072 Rural Restricted urban access (freeways and interstates)

Map of the area of the simulation by the MOVES model in the study area

Geographic Domain Zip Code 79905 Urban Area (El Paso County)

Zip Codes 88021880278807288048 (Dona Ana County)

Urban road Delta Dr St 31o 45rsquo 5637- 106o 27rsquo 1212 10 miles

Cordova Bridge of the Americas 31o 45rsquo 4367- 106o 27rsquo 0506 15 miles

478 Highway interstate 31o 46rsquo 1326- 106o 27rsquo 0327 05 miles

110 Highway interstate 31o 46rsquo 1210- 106o 27rsquo 0066 10 miles

10 Interstate Gateway Blvd 31o 46rsquo 397- 106o 26rsquo 4769 05 miles

Chamizal Loop 478 31o 46rsquo 668- 106o 26rsquo 5456 05 miles

Alameda Loop 20 31o 46rsquo 1323- 106o 27rsquo 0328 10 miles

Paisano Dr St Patriot freeway

route 62

31o 46rsquo 0669- 106o 27rsquo 212 15 miles

St Piedras 31o 46rsquo 1326- 106o 27rsquo 0327 10 miles

Dona Ana County Miles

Interstate 25 32o 23rsquo 0561 -106 48

1054 32o 23rsquo 3434- -

106 48 1054 32o 23rsquo

5660 106 48 4314

50

Geographic domain To obtain the simulation mobile data from modelMOVES2010a was configurated the coordinates selected in the study areas

El Paso County

PM25 Estimation from Aerosol Optical Depth (AOD) using

satellites

We examined the relationship

between Aerosol Optical Depth

(AOD) estimated from satellite data

at 5 km spatial resolution and the

mass of fine particles le25 μm in

aerodynamic diameter (PM25)

monitored on the ground in El PdN

area PM25 data was recorded from

air quality monitoring Chamizal

station (TCEQ) on different periods

Our analysis shows a significant

positive association between AOD

and PM25

Time-series and scatter plots of AOD estimated PM25 and surface PM25

Analysis of the meteorological factors and synoptic conditions leading to a local high

ozone event episode June 12-21 2006

Meteorology plays a critical role in determining atmospheric ozone concentrations A good synoptic scale weather forecast is essential to accurately forecast tropospheric and surface ozone concentrations

Figure 1 The domain configuration and Landuse categories

resolution 25 km domainFigure 2 The Geopotential height at 500 mb Figure 3 depicts the 850 mb at a lower altitude The

white regions observed in the graph correspond to

mountainous areas

Figure 4 Temperature at 2m height

above surface at 22 UTC June 18 2006

36 km resolution

Performance Evaluation

01020304050

Ju

ne

137

130

0

190

0

10

0

Ju

ne

157

130

0

190

0

10

0

Ju

ne

187

130

0

190

0

10

0

Tem

pe

ratu

re (⁰C

)

Local time (Hrs)

C41 June 13-19 2006

WRF_temperature

(⁰C)

TCEQ_temperature

(⁰C)

01020304050

June1

37

100

0

130

0

160

0

190

0

220

0

10

0

40

0

June1

57

100

0

130

0

160

0

190

0

220

0

10

0

40

0

June1

87

100

0

130

0

160

0

190

0

220

0

10

0

40

0

Rel

ativ

e h

um

idit

y (

)

Local time (Hrs)

C41 June 13-19 2006

WRF_rh () TCEQ_relative humidity ()

0

5

10

15

20

June

137 10

13

16

19

22 1 4

June

157 10

13

16

19

22 1 4

June

187 10

13

16

19

22 1 4

Win

d s

pee

d (

ms

Local time(Hrs)

C12 June 13-192006

WRF_wind speed (ms) TCEQ_ wind speed (ms)

We evaluate the WRF modelrsquos performance

by comparing against corresponding

experimental TCEQ data and performing the

required statistical analysis

HYSPLIT Model

HYSPLIT was simulated and showed that the ozone is mostly transported to El Paso from north western and south western US and Mexican regions during the 72 hours duration of the simulation

0

20

40

60

80

100

1200

00

10

02

00

30

04

00

50

06

00

70

08

00

90

01

00

01

10

01

20

01

30

01

40

01

50

01

60

01

70

01

80

01

90

02

00

02

10

02

20

02

30

0

Ho

url

y o

zon

e [

pp

b]

0102030405060708090

00

01

00

20

03

00

40

05

00

60

07

00

80

09

00

10

00

11

00

12

00

13

00

14

00

15

00

16

00

17

00

18

00

19

00

20

00

21

00

22

00

23

00

Ho

url

y o

zon

e [

pp

b]

June 18th June 19th

Performance Evaluation

01020304050

Ju

ne

137

130

0

190

0

10

0

Ju

ne

157

130

0

190

0

10

0

Ju

ne

187

130

0

190

0

10

0

Tem

pe

ratu

re (⁰C

)

Local time (Hrs)

C41 June 13-19 2006

WRF_temperature

(⁰C)

TCEQ_temperature

(⁰C)

0

50

100

150

June1

37

100

0

130

0

160

0

190

0

220

0

10

0

40

0

June1

57

100

0

130

0

160

0

190

0

220

0

10

0

40

0

June1

87

100

0

130

0

160

0

190

0

220

0

10

0

40

0Ozo

ne

(pp

b)

Local time (Hrs)

C41 June 13-19 2006

CAMx_ozone (ppbV) TCEQ_ozone (ppb)

0

10

20

30

40

50

June1

37

100

0

130

0

160

0

190

0

220

0

10

0

40

0

June1

57

100

0

130

0

160

0

190

0

220

0

10

0

40

0

June1

87

100

0

130

0

160

0

190

0

220

0

10

0

40

0

Rel

ativ

e h

um

idit

y (

)

Local time (Hrs)

C41 June 13-19 2006

WRF_rh () TCEQ_relative humidity ()

0

5

10

15

20

June

137 10

13

16

19

22 1 4

June

157 10

13

16

19

22 1 4

June

187 10

13

16

19

22 1 4W

ind

sp

eed

(m

sLocal time(Hrs)

C12 June 13-192006

WRF_wind speed (ms) TCEQ_ wind speed (ms)

Methodology

Medical Data The data by weekly monthly and year for daily emergency room and hospital admission for the respiratory

infections (RD) and cardiovascular diseases (CVD) was extracted from hospitals records located in the El PdN

the system includes data on type of admission primary and secondary causes of admissionRESPIRATORY DISEASE

Bronquitis amp Chronic Bronchitis 466 - 4661 491 - 4919

Asthma 463 - 4939

Emphysema 492

Respiratory failure 51881

HEART DISEASE

Accute Myocardial Infarction 410

Coronary Athersclerosis 4140

Other Ischemic Heart Disease 411-4139 4141-4149

Cardiac Dyshythmias 427

Essential hypertension 401

Acute myocardial infarction 410

Congestive Heart Failure 4280 4282-4284

Hypertensive heart disease 402

Table 1 ICD -9 Codes for Respiratory and Cardiovascular Diseases

0

50

100

150

200

250

300

Wee

k 1

Wee

k 2

Wee

k 3

Wee

k 4

Wee

k 5

Wee

k 6

Wee

k 7

Wee

k 8

Wee

k 9

Wee

k 1

0

Wee

k 1

1

Wee

k 1

2

Wee

k 1

3

Wee

k 1

4

Wee

k 1

5

Wee

k 1

6

Wee

k 1

7

Wee

k 1

8

Wee

k 1

9

Wee

k 2

0

Wee

k 2

1

Mo

rb

idit

y D

isch

arg

e fo

r a

ll R

esp

ira

tory

Dis

ease

IC

D-9

(

Ast

hm

aB

ro

nch

itis

)

Weekly Morbidity Discharges of all the Listed Diagnoses for All

Respiratory Disease During WinterSpring 2010

Asthma-Bronchitis

EPA MOVES Model for Estimating Emission

Inventories

Motor Vehicle Emission Simulator (MOVES 2010b) will be configuredin The El Paso North Region for Calculate five categories of PM10

PM25 total Emission inventories from all on-road traffic over a

variety of scales within periods of time selected weeks months

and years

Moves (Motor Vehicle Emission

Simulator)

The emission model is develop using the current equation to calculate direct traffic emissions from

vehicles in the form of PM is

Eext annual emissions are measured in grams of miles traveled by the vehicle (gVMT )

SL is the road surface loading in (gm2)

W is the average weight in tons of the vehicles on the road

K is the particle size multiplier for particle size range (eg gVMT for PM10 when using grams and miles)

P is the 7 number of wet days with at least 0254 mm of precipitation during the averaging period

N is the number of years considered in the averaging period

C is the particle size specific emissions factor in units of interest vehicle direct exhaust brake wear and tirewear

Modeling Simulation Domain and Emissions Scenarios

For simulations of mobile air quality emission inventories a motor vehicle emission simulator EPA (MOVES 2014a) was used

The modeling use input factors divided into seven section

parameters

On-Road Inventory local data

input

Scale

Geographic Bounds

Traffic intensity

Vehicle Type

Pollutants

Road Type

Fuel Types

Figure Source EPA US Environmental Protection Agency 2012- Moves 2010b Model

EPA Moves 2014a The modeling used input factors divided into six section

parameters On-Road Inventory local data input

Geographic Domains CountyNonattainment Area

Vehicle-Miles Traveled (VMT) is the total number of miles driven by all vehicles withina given time period and geographic area

Average speed range from 25 miles per

hour to 65 miles per hour

Vehicle Classes Motorcycle PassengerCarTruks light-duty Commercial Truck(6001-8500 lbs) Buses heave-duty trucksRefuse trucks School Bus Single UnitShort Haul-truck Single Unit Long Haul-truck Long Haul Truck Heavy-DutyVehicles (26001-33000 lbs)

Pollutants

Road TypeRural restricted Acces(Freeways and interstates) Rural and Restricted Acces Urban Restricted Acces Off-Network

Fuel Types Gasoline Diesel Fuel

Specific Road Types

Two road types for running emission from the MOVES can be

selected

(freeways and interstates)

Interior urban Urban

Figure Source EPA US Environmental Protection Agency 2012- Moves 2010b Model

VehiclesEquipment

This panel show which on-road vehicles will be modeled

Figure Source EPA US Environmental Protection Agency 2012- Moves 2010b Model

Long haul truck Short haul truck Inercity bus Ligth comercial truck

Passenger car Passenger truck Refuse truck

School bus Single unit long haul-truck

Single unit short haul-truck

Transit bus

Motor home

Motorcycle

Based on Department of Transportation Highway MOVES will Estimates Traffic

Emissions from Cars Trucks amp Motorcycles

Output Data Moves 2014a

Inventories of PM 10 25 Mobile Emission from all

on-Road Traffic

Exhaust Emission PM 10 25 gramsmile

Brake Wear Emission PM 10 25 gramsmile

Tire wear Emission PM 10 25 gramsmile

Date of Vehicle miles traveled (VMT) for

Day Week Month Year

Total Vehicle population

Vehicle age distribution

Simulation of Mobile Emission in the El PdN Region Zip Code 79905

Figure Total Emissions from road traffic in El Paso TX Area were estimated for PM10

Exhaust and Non exhaust emission in kilogramsmonth (Source EPA MOVES 2014a)

0

10000

20000

30000

40000

50000

PM

10 k

gM

on

th

Months

Monthly PM 10 Exhaust and Non-Exhaust Mobile Emissions 2010

On-Road Urban Restricted Area Zip Code 79905

Primary Exhaust PM 10 (kg) Primary PM 10 Brakewear (kg)

Primary PM 10 Tirewear (kg)

05000

100001500020000250003000035000400004500050000

PM

25

kg

Mo

nth

Months

Monthly PM 25 Exhaust and Non-Exhaust Mobile Emission 2010

On-Road Urban Restricted Area Zip Code 79905

Primary Exhaust PM 25 (kg) Primary PM 25 Brakewear (kg) Primary PM 25Tirewear (kg)

Figure Total Emissions from road traffic in El Paso TX Area were estimated for PM25

Exhaust and Non exhaust emission in kilogramsmonth (Source EPA MOVES 2014a)

Total Emissions from Road Traffic in El Paso County PM1025 Exhaust and Non exhaust Emission in kilogramsmonth

Taking the interests to the health risks related to PM 1025 mobile emission were simulated

Exhaust and Non-exhaust emissions contribute almost equally to total traffic-related PM1025 Emissions (Querol et al 2004 Bukowiecki et al 2009a Amato et al 2011)

Monthly PM 10 25 Exhaust and Non-Exhaust (BrakewearTirewear) Mobile

Emission 2010 On-Road Urban Restricted Area Zip Code 79905

Figure Total Emissions from road traffic in El Paso TX Area were estimated for PM10 25 Exhaust and Non Exhaust mobile

emission in kilograms per month (Source EPA MOVES)

0

10000

20000

30000

40000

50000

January February March April May June July August September October November December

PM

10

25

(K

ilog

ram

s)

Months

Summary- Monthly PM 10 25 Exhaust and Non-Exhaust Mobile

Emission 2010 On-Road Urban Restricted Area Zip Code 79905

Primary Exhaust PM 10 Primary PM 10 Brakewear Primary PM 10 Tirewear

Primary Exhaust PM 25 Primary PM 25 Brakewear Primary PM 25Tirewear

Exhaust Emissions PM1025 is reaching maximum emission 48000-42000 thousand of Kgmonth followedby Brake wear 29000-5000 thousand kgmonth and Tire wear with 9000-2000 kgmonth The results showthat the emissions of PM derived mainly from Exhaust and Brake are significantly higher in Urban Area

Annual Contribution of Mobile Emission PM 1025 (Kg) Zip Code 79905 El

Paso County 2010

Total Primary

Exhaust _PM10

39

Total Primary

Exhaust _PM25

36

Brakewear

particulate_PM10

18

Tirewear

particulate_PM10

4

Brakewear

particulate_PM25

2

Tirewear

particulate_PM25

1

0

5

10

15

20

25

30

35

40

45

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53

Fig Annual Average PM10 Concentrations at the

Chamizal C41 Station and PM1025 mobile

Concentration Zip code 79905

PM10 TCEQ (μgm3) Total Mobile Emission PM10 (Ugm3)

Fig Exhaust Emission is Contributing Approximately 74 of total

PM1025 Mobile Emissions following of Brake wear with 20 and Tire

wear with 5

Annual Average PM1025 ugm3 Mobile Emissions (Moves) 26 Chamizal C41

Monitoring Station (TCEQ Chamizal Station )

Predicting Mobile Emission and VTM

Estimation The PdN Region 2010

44E+09

46E+09

48E+09

5E+09

52E+09

54E+09

56E+09

58E+09

6E+09

62E+09

0

50000

100000

150000

200000

250000

300000

350000

20

10

20

11

20

12

20

13

20

14

20

15

20

16

20

17

20

18

20

21

20

22

20

23

20

24

20

25

20

26

20

27

20

28

20

29

20

30

EX

HA

US

T

EM

ISS

ION

MO

BIL

E (

KG

YE

AR

)

YEARS

Predict ing Mobile Exhaust Emission and VTM

Estimation

2010 - 2030 e l PdN Area

Total_ Exhaust PM10 Total_ Exhaust PM25 Distance (Miles)

Fig Predicting Mobile Exhaust PM1025 (kgMonth) Emission and VTM Estimation 2010

- 2030 el PdN Area

44E+09

46E+09

48E+09

5E+09

52E+09

54E+09

56E+09

58E+09

6E+09

62E+09

0

5000000

10000000

15000000

20000000

25000000

30000000

20

10

20

11

20

12

20

13

20

14

20

15

20

16

20

17

20

18

20

21

20

22

20

23

20

24

20

25

20

26

20

27

20

28

20

29

20

30

EX

HA

US

T

EM

ISS

ION

MO

BIL

E (

KG

YE

AR

)

YEARS

Predict ing Mobile Exhaust Emission and

VTM Estimation

2010 - 2030 e l PdN Area

CO NO2 NO NOx Distance

Fig Predicting Mobile Exhaust Emission and VTM Estimation

2010 - 2030 el PdN Area in El Paso TX Area were estimated for

Total CO NOx NO2 NO emission in kilograms per year

(Source EPA MOVES 2014a model)

The simulated Exhaust emissions in the future years shows a trend of reduction of this type of emissions in the

future years one factor should be the new hybrid technology is increasing by 476 since 2010 to 2015 and

use of catalytic converters diesel particulate filters and improved fuels and engines Non-exhaustive sources

will increase in the coming years because there is no control in the material of manufacture composed by Fe

Cu and Mn also not to be able to reduce the number of events of braking (Accelerations and decelerations)

45E+09

5E+09

55E+09

6E+09

65E+09

0

50000

100000

150000

200000

250000

201

0

201

1

201

2

201

3

201

4

201

5

201

6

201

7

201

8

202

1

202

2

202

3

202

4

202

5

202

6

202

7

202

8

202

9

203

0

NO

N-

EX

HA

US

T

EM

ISS

ION

MO

BIL

E

(KG

YE

AR

)

YEARS

Predicting Non Exhaust Mobile

Emission and VTM Estimation

2010 - 2030 el PdN Area

Brake_PM10 Tire_PM10 Distance (Miles)

Fig Predicting Mobile Exhaust PM1025 (kgMonth) Emission and VTM

Estimation 2010 - 2030 el PdN Area

Daily Avg PM1025

Levels of PM Mobile Emission Non-Exhaust -Rush Hour Periods Fall 2010 Zip Code

79905

00

100

200

300

400

500

600

Mo

bil

e P

M1

0 (k

g)

Rush Hours

Daily Avg PM10

Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush Hours

Periods 2010 Zip Code 79905

Total Primary Exhaust

_PM10 WinterSpring

Brakewear

particulate_PM10

WinterSpringTirewear particulate_PM10

WinterSpring

Total Primary Exhaust

_PM10 Summer

Brakewear

particulate_PM10 Summer

Tirewear Particulate_PM10

Summer

Total Primary Exhaust

_PM10 Fall

Brakewear

particulate_PM10 Fall

Tirewear particulate_PM10

Fall

00

50

100

150

200

250

300

350

Mo

bil

e P

M2

5 (k

g)

Rush hours

Daily Avg PM25

Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush

Hours Periods 2010 Zip Code 79905

Total Primary Exhaust _PM25

WinterSpring

Brakewear Particulate_PM25

WinterSpring

Tirewear particulate_PM25

WinterSpring

Total Primary Exhaust _PM25

Summer

Brakewear particulate_PM25

Summer

Tirewear particulate_PM25

Summer

Total Primary Exhaust _PM25

Fall

Brakewear particulate_PM25

Fall

Tirewear particulate_PM25

Fall

Figure Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush Hours Figure Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush Hours

GIS EMISSIONS INVENTORY SYSTEM A geographic information system (GIS) was used to established geographic scenarios with processed images of seasonal mobile

emissions in the PdN region Seasonal mapping is visualized for different types of pollutants Brakewear Exhaust and Tyrewear

Fg Graphics of GIS and Seasonal mobile Emission of particulate matter emission inventory Seasonal emission simulations were performed in kilograms and five contributing inputs factors were identified for

modeling 1) On the composition of the particulate material from different sources such as Exhaust and Non exhaust (Brake wear Tirewear) 2) The Vehicles Equipment clasification were selected according to

the use of gasoline and diesel fuel (motorcycle passenger car Light Duty Vehicles Trucks refuse truck Light Duty Vehicles Light Commercial Truck Light Duty Vehicles School Bus)

Winter Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

120354 67860 19065

Spring Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

139767 86702 24463

Summer Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

94747 62481 17630

Fall Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

75510 45542 12596

251 Descriptive Statistics Data Analysis

Weekly Correlation Analysis of Mobile Emission PM10 (Exhaust-Non-Exhaust) and Respiratory

Diagnoses WinterSpring Summer and Fall 2010

0

2

4

6

8

10

0

50

100

150

200

250

300

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21

Mo

rbid

ity

Dis

ch

arg

e

for

all R

esp

ira

tory

Dis

ea

se

ICD

-9

(A

sth

ma

-Bro

nc

hitis

)

WinterSpring Week

Weekly Avg Mobile PM10 Concentrations during

WinterSpring 2010 and its Influence on Respiratory

Diagnoses

Zip Code 79905

Total Medical data ZIP Code 79902

Total Mobile Emission PM10 (Ugm3)

0

1

2

3

4

5

6

7

0

20

40

60

80

100

Mo

rbid

ity

Dis

ch

arg

e

for

all R

esp

ira

tory

Dis

ea

se

ICD

-9

(Ast

hm

aB

ron

ch

itis

)

Weekly Avg Mobile PM10 Concentrations during

Summer 2010 and its Influence on Respiratory

Diagnoses

Summer 2010 Zip Code 79905

Total Mobile Emission PM10

Hospital Admission (Asthma-Bronchitis)

0

2

4

6

8

10

12

0

20

40

60

80

100

120

140

160

180

200

Mo

rbid

ity

dis

ch

arg

es

for

all r

esp

ira

tory

dis

ea

se

Weekly Avg Mobile PM10 Concentrations

during Fall 2010 and its Influence on Respiratory

Diagnoses

Zip Code 79905

Total Medical data ZIP Code 79902

Total Mobile Emission PM10 (Ugm3)

Mobile(Exhaust-Non-

Exhaust) PM10 and

Asthma-Bronchitis)

Linear R

Square

WinterSpring 734 ndash 39

Summer 614 ndash 32

Fall 548 -29

PM10 Mobile emission (Exhaust-Non-Exhaust)contributed significantly

association to the incidence of RD

Weekly Correlation Analysis of PM 25 Mobile Emission (Exhaust-Non-Exhaust)

and Cardiovascular Diagnoses WinterSpring Summer and Fall 2010

0010203040

00500

100015002000

Wee

k 1

Wee

k 2

Wee

k 3

Wee

k 4

Wee

k 5

Wee

k 6

Wee

k 7

Wee

k 8

Wee

k 9

Wee

k 1

0

Wee

k 1

1

Wee

k 1

2

Wee

k 1

3

Wee

k 1

4

Wee

k 1

5

Wee

k 1

6

Wee

k 1

7

Wee

k 1

8

Wee

k 1

9

Wee

k 2

0

Wee

k 2

1

Morb

idit

y d

isch

arg

es f

or

all

card

iovasc

ula

r d

isea

se

Weekly Avg PM25 Mobile Concentrations during

WinterSpring 2010 and its Influence on all Heart

Diagnoses

Zip Code 79905

Total All Heart Disease PM 25 mobile (μgm3)

0010203040

00

500

1000

1500

Mo

rbid

ity

dis

ch

arg

es

for

all

ca

rdio

va

scu

lar

dis

ea

se

Weeks

CORRELATION BETWEEN MOBILE PM25 ugm3

EXPOSURE TO HEART DISEASES SYMPTOMS

SUMMER SEASON 2010

Total All Heart Disease PM 25 mobile (μgm3)

Figure Statistical Analyses of the Relationship Between PM25 Caused by Traffic Emission( 26 of total Emission) with Heart diseases Source Hospital Admissions for Asthma Acute Bronchitis and Heart diseases in El Paso County zip code 79905 from Texas Health Care

Information Council in Austin Texas (Texas Health Care Information Council 2000)

00

10

20

30

40

0

50

100

150

We

ek 3

6

We

ek 3

7

We

ek 3

8

We

ek 3

9

We

ek 4

0

We

ek 4

1

We

ek 4

2

We

ek 4

3

We

ek 4

4

We

ek 4

5

We

ek 4

6

We

ek 4

7

We

ek 4

8

We

ek 4

9

We

ek 5

0

We

ek 5

1

We

ek 5

2

We

ek 5

3

Mo

rbid

ity

dis

ch

arg

es

for

all

ca

rdio

va

scu

lar

dis

ea

se

CORRELATION BETWEEN MOBILE PM25 ugm3

EXPOSURE TO HEART DISEASES SYMPTOMS FALL

SEASON 2010

Total All Heart Disease PM 25 mobile (μgm3)

Mobile(Exhaust-

Non-Exhaust)

PM10 and

Asthma-

Bronchitis)

Linear R

Square

WinterSpring 833 -42

Summer 620 -32

Fall 501-26

PM10 Mobile

emission (Exhaust-

Non-

Exhaust)contribut

ed significantly

association to the

incidence of CVD

Diseases

Monthly Brake Mobile Emission PM1025 kg During year 2010 and its Influence on

Respiratory Diagnoses Zip Code 79905

00200040006000800010000

010000200003000040000

PM

10

Mo

bile

(K

g)

Months

Monthly Brake Mobile Emission PM10 kg during year

2010 and its Influence on Respiratory Diagnoses

Zip Code 79905

Primary PM 10

Brakewear 00100020003000400050006000

0

1000

2000

3000

4000

PM

25

Mo

bil

e(K

g)

Months

Monthly Brake Mobile Emission PM25 during

year 2010 and its Influence on Heart Diagnoses

Zip Code 79905

Primary PM 25

Brakewear

Heart Diseases

Hospital

Admission

Brake Mobile Emission

PM10 kg Asthma-

Bronchitis)

Brake Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=969 Linear Square R=856

Monthly Mobile Exhaust Emission PM1025 During year 2010 and its Influence on

Respiratory Diagnoses Zip Code 79905

0

200

400

600

800

1000

0

10000

20000

30000

40000

50000

1 3 5 7 9 11

PM

10

(K

g m

on

th)

Months

Monthly Mobile Exhaust Emission PM10 during

year 2010 and its Influence on Respiratory

Diagnoses

Zip Code 79905

Primary Exhaust

PM 10

Respiratory Disease

(Asthma

Bronchitis) Hospital

Admission

0

100

200

300

400

500

600

0

10000

20000

30000

40000

50000

1 2 3 4 5 6 7 8 9 101112

PM

25

(K

g m

on

th)

Months

Monthly Exhaust Mobile Emission PM25 during

year 2010 and its Influence on Heart Diagnoses

Zip Code 79905

Primary Exhaust PM

25

Heart Diseases

Hospital Admission

Exhaust Mobile Emission

PM10 kg Asthma-

Bronchitis)

Exhaust Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=929 Linear Square R=831

Monthly Tire wear Mobile Emission PM1025 During year 2010 and its Influence on Heart

Diagnoses Zip Code 79905

0

100

200

300

400

500

600

700

800

900

0

1000

2000

3000

4000

5000

6000

7000

8000

9000

1 2 3 4 5 6 7 8 9 10 11 12

PM

10

(K

g m

on

th)

Months

Monthly Tirewear Mobile Emission PM10 during year 2010

and its Influence on Heart Diagnoses

Zip Code 79905

Primary PM 10 Tirewear

Mobile Emission

Respiratory Disease

(Asthma Bronchitis)

Hospital Admission

0

100

200

300

400

500

600

0

200

400

600

800

1000

1200

1400

1 2 3 4 5 6 7 8 9 10 11 12

PM

25

(K

g m

on

th)

Months

Monthly Tirewear Mobile Emission PM25 during year 2010

and its Influence on Respiratory Diagnoses

Zip Code 79905

Primary PM 25Tirewear

Mobile Emission

Heart Diseases Hospital

Admission

Exhaust Mobile Emission

PM10 kg Asthma-

Bronchitis)

Exhaust Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=769 Linear Square R=715

Dona Ana County Zip Codes

88021880278807288048

Primary

Exhaust

PM 10 Zip

code

79905

Total

Primary

Exhaust

PM10

Dona Ana

Primary

Exhaust

PM 25 Zip

Code

79905

Total

Primary

Exhaust

PM25

Dona Ana

Series1 430378 111773 391915 102123

0

100000

200000

300000

400000

500000

AX

IS T

ITLE

Annual Comparison of the Mobile

Exhaust Emissions El Paso County

and Dona Ana 2010

Primary

PM 10

Brakewea

r Zip code

79905

Brakewea

r

particulat

e_PM10

Dona Ana

Primary

PM 10

Tirewear

Zip code

79905

Tirewear

particulat

e_PM10

Dona Ana

Series1 262585 48573 73754 11864

050000

100000150000200000250000300000

AX

IS T

ITLE

Annual Comparison of the Mobile

Brakewear Emissions El Paso County

and Dona Ana 2010

Figure Comparison of the Annual Mobile Emissions

of Primary PM10 Non-Exhauts (Brake ) from Dona

Ana County New Mexico and El Paso Texas Units

in KgMonth

Figure Comparison of the Annual Mobile Emissions

of Primary PM10-Exhauts Emission from Dona Ana

County New Mexico and El Paso Texas Units in

KgMonth

Primary

PM 25

Brakewe

ar Ziphellip

Brakewe

ar

particula

te_PMhellip

Primary

PM

25Tirewe

ar Ziphellip

Tirewear

particula

te_PM25

Donahellip

Series1 32645 6071 10919 1779

0

10000

20000

30000

40000

AX

IS T

ITLE

Annual Comparison of the

Mobile Exhaust Emissions El Paso

County and Dona Ana 2010

Figure Comparison of the Annual Mobile Emissions

of Primary PM10-Exhauts Emission from Dona Ana

County New Mexico and El Paso Texas Units in

KgMonth

Monthly Mobile Emission PM1025 kg During year 2006

and its Influence on Respiratory Diagnoses Dona Ana

County Zip Code 880218802788072

0

100

200

300

0

5000

10000

15000

Axi

s Ti

tle

Axis Title

Monthly Mobile Exhaust Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Total PrimaryMobile Exhaust_PM10

All Respiratory ICD-9 (AsthmaBronchitis)

050100150200250300

010002000300040005000

Axi

s Ti

tle

Axis Title

Monthly Mobile Brake Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Brakewearparticulate_PM10

All RespiratoryICD -9 (AsthmaBronchitis)

050100150200250300

0200400600800

10001200

Axi

s Ti

tle

Axis Title

Monthly Mobile Tirewear Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Tirewearparticulate_PM10

All Respiratory ICD -9 (AsthmaBronchitis)

Mobile Exhauts

Emission PM10

kg Asthma-

Bronchitis)

Brake Mobile

Emission PM10

kg and Heart

Diagnoses

Tirewear Mobile

Emission PM10

kg and Heart

Diagnoses

Linear Square

R= 951

Linear Square

R=625

Linear Square

R=525

Mobile Exhauts

Emission PM25

kg Asthma-

Bronchitis)

Brake Mobile

Emission PM25

kg and Heart

Diagnoses

Tirewear Mobile

Emission PM25

kg and Heart

Diagnoses

Linear Square

R= 986

Linear Square

R=691

Linear Square

R=601

Results

The results showed that mobile PM emissions in the urban areas close to urban Road and highways is putting at risk public health

and the proportion of diseases attributable to this exposure is potentially large

Brake wear emissions is much lower in freeways due to significantly reduced number of braking events while tire wear is much

higher in areas where studded tires are used The emission of exhaust gases are much higher in areas where there is a high

vehicular traffic

Brake Mobile

Emission PM10 kg

Asthma-Bronchitis)

Brake Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square

R=969

Linear Square

R=856

Exhaust Mobile

Emission PM10 kg

Asthma-Bronchitis)

Exhaust Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square

R=929

Linear Square

R=831

Tirewear Mobile

Emission PM10 kg

Asthma-Bronchitis)

Tirewear Mobile

Emission PM25 kg

and Heart Diagnoses

Linear Square R=769 Linear Square R=715

Brake Mobile

Emission PM10 kg

and Heart

Diagnoses

Brake Mobile

Emission PM25 kg

and Heart

Diagnoses

Exhaust Mobile

Emission PM10 kg

Asthma-Bronchitis)

Linear Square

R=625

Linear Square

R=691

Linear Square R=

951

Exhaust Mobile

Emission PM25 kg

Asthma-

Bronchitis)

Tire wear Mobile

Emission PM10 kg and

Heart Diagnoses

Tirewear Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square R=

986

Linear Square R=525 Linear Square

R=601

El Paso County

Dona Ana

County

BenMAP-CE

In this analysis the Program of Mapping and Analysis of Environmental Benefits-Community Edition

(BenMAP-CE) was used to Estimate the number and economic value of health impacts resulting from changes

in air pollution PM 25 Ugm3 in The El Paso Area

Health and Economic Benefits associated with the Response of PM25 Emission between

Base Year 2010

Number of Mortalities in 2010 Base Year Based on El Paso County Texas Department of State Health Services

Number of Mortalities in 2010 Base Year Based on El Paso County Texas

Department of State Health Services

cause of death

year

2010

Populatio

n

Affected

Backgro

und

Concentr

ation Pollutant

Rollback

Type

Avoided

Deaths

(

Populatio

n)

alzheimers disease 2010 40716 125 PM25

25

microgmAcircsup3

Rollback 9

diseases of the

heart 2010 15834 125 PM25

25

microgmAcircsup3

Rollback 35

influenza and

neumonia 2010 81432 125 PM25

25

microgmAcircsup3

Rollback 18

acute bronchitis

and bronchiolitis 2010 117624 125 PM25

25

microgmAcircsup3

Rollback 26

chronic lower

respiratory diseases 2010 54288 125 PM25

25

microgmAcircsup3

Rollback 12

The Basin-wide decrease in 4 ugm3 PM25 concentration after this

reduction control

Cause of death year 2010

Populatio

n

Affected

Background

Concentrati

on

Reduc

cion

scena

rio Polluta

nt

Rollback

Type

Avoi

ded

Deat

hs

(

Pop

ulati

on)

economic

benefits

analysis $

Alzheimers

disease 2010 121 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 9 12000

Diseases of the

heart 2010 470 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 35 35000

Influenza and

neumonia 2010 242 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 18 42500

Acute bronchitis

and bronchiolitis 2010 349 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 26 95000

Chronic lower

respiratory

diseases 2010 161 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 12 4500

$1 295000

PM25-related Mortalities Based on BenMAP-CE Estimate in 2010 Base Year with change in the concentrations levels

Health and Economic Benefits associated with the Response of PM25 Emission between

Base Year 2010 Increasing 7 Ugm3

Cause of death year 2010

Population

Affected

Deaths

avoided by

attaining 195

μgm3

standard

Background

Concentrati

on

Pollut

ant

Rollback

Type

Avoided

Deaths (

Populatio

n)

econo

mic

Unben

efits

analysi

s

Alzheimers

disease 2010 4524 195 PM25

25

microgmAcircsup3

Rollback 19 150000

Diseases of the

heart 2010 20358 195 PM25

25

microgmAcircsup3

Rollback 135 450000

Influenza and

neumonia 2010 126672 195 PM25

25

microgmAcircsup3

Rollback 38 525000

Acute bronchitis

and bronchiolitis 2010 162864 195 PM25

25

microgmAcircsup3

Rollback 36 122000

Chronic lower

respiratory

diseases 2010 99528 195 PM25

25

microgmAcircsup3

Rollback 12 650000

Conclusions

An excellent Pearson Correlation was established to analyze the relationship in the relative risks of hospitalization of Respiratory(RD) and cardiovascular (CVD) associated with ambient exposure caused by traffic emission in relation to their size andspecific sources of emission on different scenarios interior a border Urban Rural Urban restricted access (freeways andinterstates)

A significant correlation of PM1025 exposure from mobile emission and hospital admissions for selected Respiratory (RD) andcardiovascular (CVD) diagnoses was established The results showed that PM emissions in urban restricted access (freeways andinterstates) is mainly caused by traffic Therefore people living close to highways are more exposed higher vehicular emissions

Conclusions

We found statistically significant associations between mobile PM25 caused by traffic emission with Respiratory and Cardiovascular Diseases in the study areaSubsequently a correlation between cardio-respiratory mortality is established

A significant correlation of PM1025 exposure from mobile emission and hospital admissions for selected Respiratory (RD) and cardiovascular (CVD) diagnoses isestablished The results showed that PM emissions in urban restricted access (freeways and interstates) is mainly caused by traffic Therefore people living close tohighways receive higher vehicular emissions

The table shows the percentage of PM mobile exposure in the analyzed areas contributing to increase the risk of Respiratory and Cardiovascular Diseases

An examination was conducted of the synoptic and local meteorology for the June 2006 ozone episode using the WRF model to determine how meteorological parametersinfluence the formation transport and dispersion of ozone in the PdN The predominant synoptic feature of the ozone event day was the expansion intensification and slowprogression of an upper-level ridge of high pressure The high ozone episodes are associated with highly stable atmospheres strong temperature inversions with low mixingheights and therefore low mixing volumes Under these conditions emissions such as NOx lead to highly polluted conditions that favor ozone formation

BenMAP Conclusions

We have estimated the number and economic value of health impacts resulting

from changes in air pollution concentrations of PM 25 in the PdN region

Reduction of Pm 25 4 UGm3= Avoided 213 cases respiratory cardiovascular

diseses and Economic Benefits associated with the Response of PM25 Emission + $

1295000

Increase of PM25 7 ugm3 = increasing Dies= 326 economic Unbenefits= 2345000$

Bibliography

1 Dockery DW Pope CAI Xu X Spengler JD Ware JH Fay ME Ferris BG Speizer FE An association between air pollution and mortality in six US cities N Engl J Med 3291753ndash1759 (1993)

2 Samet JM Dominici F Curriero FC Coursac I Zeger SL Fine particulate air pollution and mortality in 20 US cities 1987ndash1994 N Engl J Med 3431742ndash1749 (2000)

3 Nel AE Diaz-Sanchez D Li N The role of particulate pollutants in pulmonary inflammation and asthma evidence for the involvement of organic chemicals and oxidative stress Curr Opin Pulm Med 20017 20ndash26

4 Westerholm R Karl-Erik E Exhaust emissions from lightand heavy-duty vehicles chemical composition impact of exhaust after treatment and fuel parameters Environ Health Perspect 102(suppl 4)13ndash23 (1994)

5 Bascom R Bromberg P Costa D Delvin R Dockery D Frampton M Lambert W Samet J Speizer F Utell

6 Health effects of outdoor air pollution Am J Respir Crit Care Med 1533ndash50 (1996)

7 Chow JC Watson JG Frazier CA Egami RT Goodrich A Ralph C Spatial and temporal source contributions to

8 PM10 and PM25 in Reno NV In PM-10 Implementation of Standards Transactions An APCAEPA International Speciality Conference San Francisco CA (Mathal CV Stonefield DH eds) PittsburghAPCA 1988439ndash457

9 overview In Particulate Matter Health and Regulatory Issues VIP-49 Proceedings of an International Specialty Conference 4ndash6 April 1995 Pittsburgh PA PittsburghAir and Waste Management Association 1995577ndash598

10 Kunzli N Kaiser R Medina S Studnicka M Chanel O

11 Filliger P Herry M Horak F Jr Puybonnieux-Texier V Quenel P et al Public-health impact of outdoor and traffic- related air pollution a European assessment Lancet 356795ndash801 (2000)

Bibliography

1 Sioutas C Delfino RJ Singh M Exposure assessment for atmospheric ultrafine particles (UFP) and implications in epidemiological research Environ Health Perspect 2005113947ndash955

2 Mosleh M Blau PJ Dumitrescu D (2004) Characteristics and morphology of wear particles from laboratory testing of disc brake materials Wear 2561128ndash1134

3 Kuumlnzli N et al (2000) Public-health impact of outdoor and traffi c-related air pollution a European assessment Lancet 356(9232)795ndash801

4 Dora C Phillips M eds (2000) Transport environment and health Copenhagen WHO Regional Office for Europe (WHO Regional Publications European Series No 89 httpwwweurowhointdocumente72015pdf accessed 26 November 2004)

5 Westerholm R Karl-Erik E Exhaust emissions from lightand

6 heavy-duty vehicles chemical composition impact of exhaust after treatment and fuel parameters Environ Health Perspect 102(suppl 4)13ndash23 (1994)

7 Fauser Tjell Mosbaek pigegaard Quantification of tire-Tread particles using extractable Organic Zinc as a Tracer Rubber Chemistry and Technology 1999 969Table shows some literature estimates of the contribution of tire wear to PM10 in air (Panko et al 2013) Gustafsson M Blomqvist G Gudmundsson A Dahl A Swietlicki E Bohgard M Lindbom J Ljungman A

8 Chen Y Shah N Huggins FE and Huffman GP (2006) Microanalysis of Ambient Particles from Lexington Ky by Electron Microscopy Atmos Environ 40 651ndash663

9 Donaldson K Tran CL Jimenez LA Duffin R Newby DE and Mills N (2005) Combustion-derived Nanoparticles A Review of Their Toxicology Following Inhalation Exposure Part Fibre Toxicol 2 10ndash23

10 Su D Serafino A Muller JO Jentoft RE Schlogl R and Fiorito S (2008) Cytotoxicity and Inflammatory Potential of Soot Particles of Low-emission Diesel Engines Environ Sci Technol 42 1761ndash1765

11 Maier KL Alessandrini F Beck-Speier I Hofer TPJ Diabatґe S Bitterle E Stoger T and Jakob T (2008) Health Effects of Ambient Particulate Matter-Biological Mechanisms and Inflammatory Responses to in Vitroand in Vivo Particle Exposures Inhalation Toxicol 20 319ndash337

Page 6: Studies of Air Pollutants and their Impact on Respiratory and ...€¦ · Ascarate Park C37 Monitoring Station: The National Ambient Air Quality Standard (NAAQS) for PM 10 and 2.5

Significance of the Work

Traffic is a major source of mobile emissions causing air pollution

Mobile emissions such as

Exhaust Emissions (Carbon Monoxide Nitrogen Oxides and

Hydrocarbons) and Non-exhaust (Brake and Tire) Particulate

emissions can also be very damaging to health because their tiny

diameter can enter the respiratory system easily and possibly cause

adverse health impacts (pulmonary carcinogen inflammatory and

toxic effect on the lung (IARC 1989 Et al 2013) (Kelly and Fussell

2012) (iron(Fe) copper(Cu) Manganese(Mn) antimony(Sb)

barium(Ba) zinc(Zn)

Therefore the relevance of this research provides a key

knowledge to understand the impacts of traffic emissions on air

quality and the magnitude of public health risks associated with

exposure to mobile emissions

Problem Statement

0

100

200

300

400

500

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31

PM

10 (

μg

m3)

Days

Chamizal C 41

Montly 24 Hours Average

PM-10 measured in micrograms per cubic meter (μgm3)

2006 January

February

March

April

May

June

July

August

September

October

November

The National Ambient Air Quality Standard (NAAQS) for PM was Exceeded in The PdN Region during

2006 2010 Analysis of Chamizal Area Zip Code 79905

These chart illustrates two high spikes that occurred which exceeds the 24 hour average

0

20

40

60

80

100

120

140

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31

PM

25

( μ

gm

3)

Days

Chamizal C 41

Montly 24 Hours Average

PM-25 measured in micrograms per cubic meter (μgm3)

2006 january

February

March

April

May

June

July

August

September

October

November

December

Chamizal C41Monitoring Station The National Ambient Air Quality Standard (NAAQS) for PM 10 and 25 was

exceeded but in 24 hour average The NAAQS for PM 25 for 24-hour average is PM2535 microgmsup3 and PM10 50-

100 microgmsup3 The highest concentration occurred several times PM10(150200300450 microgmsup3)

PM25(4050607080120 microgmsup3 )

Problem Statement

0

100

200

300

400

500

600

700

800

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31

PM

10 (

μg

m3)

Days

Ascarate Park SE C37

Montly 24 Hours Avg PM 10 Exceedences and Maximum

Concentrations 2010 January

February

March

April

May

June

July

August

September

October

November

December

Graph 1 Source TCEQ ( Texas Commission on Environmental Quality) Ascarate Park monitoring station Data 2010

0

20

40

60

80

100

120

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31

PM

25

UG

M3

DAYS

Ascarate Park SE C37

Montly 24 Hours Average

PM-25 measured in micrograms per cubic meter

(μgm3)

2010 JanuaryFebruaryMarchAprilMayJuneJulyAugustSeptemberOctoberNovemberDecember

Graph 2 Source TCEQ ( Texas Commission on Environmental Quality) Ascarate Park monitoring station Data 2010

Ascarate Park C37 Monitoring Station The National Ambient Air Quality Standard (NAAQS) for PM

10 and 25 was exceeded but in 24 hour average The NAAQS for PM 25 for 24-hour average is

PM2535 microgmsup3 and PM10 50-100 microgmsup3 The highest concentration occurred several times

PM10(200250300400600720 microgmsup3) PM25(4090120microgmsup3)

The National Ambient Air Quality Standard (NAAQS) for PM was Exceeded in The PdN Region 2006 2010

Analysis of Ascarate Area Zip Code 79905

These chart is to illustrate there are two high spikes that occurred which exceeds the 24 hour average

Fig Number of registered automobiles in Texas The Statistics show the

number of registered automobiles truck motorcycle in Texas Source

Texas department motor vehicles

Fig More than 61 percent of

US transportation emissionscome from cars and lighttrucks

Fig in US On-roadmobile sourcesconstitute the largestsingle source categoryof air pollution with(327)

Problem Statement

13000000140000001500000016000000170000001800000019000000

Millio

ns

of

Ve

hic

les

Years

Total Growth of Texas Registrations

2001-2012

Total

Vehicles

Registratio

ns

Problem Statement

El Paso Texas and ciudad Juarez currently has commercialmovements through El PasondashCiudad Juarez gateways peaked at715000 trucks in the year 2010 and Approximately 40000 vehicles passthese roads each laborable day

Source US Department of Transportation Bureau of Transportation Statistics 2010

Bridge Number of US-bound

Truck Crossings year 2010

World Trade Bridge 1327479

Pharr ndash Reynosa International Bridge

452821

Ysleta ndash Zaragoza Bridge 379508

Laredo ndash Colombia Solidarity

Bridge

374781

Bridge of the Americas 337609

Veterans International Bridge 177986

Camino Real International Bridge 106423

Del Rio ndash Ciudad Acuna

International Bridge

62966

Progreso International Bridge 42605

Free Trade Bridge 30773

Source CBP

Fig Bridge of the Americas (Puente Cordova)

Publications Review to examine the relationship between exposure to motor vehicle emissions and respiratory and cardiovascular disease

We have analyzed the current literature which have served as the basis for this project

Some studies determined that traffic-related emissions have been recognized as a major contributor to urban air pollution in particular major cities proximity to major roadways and exposure to motor vehicle exhaust and Non-exhaust emissions are associated with increased risks of cardiovascular respiratory and other diseases (Brugge et al 2007 Gan et al 2010 Gauderman et al 2007 Jerrett et al 2009 Laden et al 2007 McConnell et al 2006)

Effect of traffic pollution on respiratory and allergic disease in adults cross-sectional and longitudinal analyses Mar Pujades-Rodriacuteguez Tricia McKeever Sarah Lewis Duncan Whyatt John Britton and Andrea Venn

httpwwwsciencedailycomreleases200811081114081003htm April 2011

Traffic Pollution Increases Asthma in Adults Several research results revealed adults who suffer asthma and were exposed to heavy traffic pollution experienced an 80 per cent increase University of Melbourne Rev Public Health 15 (1994) pp 107ndash132 August 2010

Traffic Pollution Aggravates Symptoms In Asthmatic Children Traffic pollution especially in cities adversely affects respiratory health in children with asthma studies suggest that traffic pollution and diesel particles in particular may have a greater effect on respiratory health than other pollutants httpwwwsciencedailycomreleases200811081114081003htm September 2010

Traffic-related air pollution associated with prevalence of asthma and COPDchronic bronchitis A cross-sectional study in Southern Sweden Anna Lindgren Emilie Stroh Peter Montneacutemery September 2009

Acute respiratory health effects of air pollution on children with asthma in US inner cities Benjamin Vaughn MS Meyer Kattan MD Herman Mitchell PhD May 2008

Comparison of Air QualityndashRelated Mortality Impacts of two Different source of emission Transportation in the United States httpwwwtrborgMainBlurbs166402aspx January 2008

Long-term exposure to traffic-related air pollution and cardiovascular mortality Chen H Goldberg MS Burnett RT Jerrett M Wheeler AJ Villeneuve PJ Source Department of Epidemiology and Biostatistics McGill University Montreal Quebec Canada January 2011

heavy-duty vehicles chemical composition impact of exhaust after treatment and fuel parameters Environ Health Perspect102(suppl 4)13ndash23 (1994)

Particulate Matter

PM is a mixture of solid and liquid particles suspended in the atmosphere

as atmospheric aerosols Mobile Pollutants are formed by chemical

reactions of gaseous components from burning of fossil fuel in vehicles

(Gasoline amp diesel motor vehicles)

Source EPA (2012) United States Environmental Protection Agency

Particulate matter basic information Cited October 30th 2012 Available

online at httpwwwepa govairqualityparticlepollutionbasichtml

Source EPA (2012) United States Environmental Protection Agency Particulate matter basic

information Cited October 30th 2012 Available online at httpwwwepa

govairqualityparticlepollutionbasichtml

PM10 25 Long Term Exposure ndashChronic Health Consequences

These particles are associated with a

variety of problems including

Aggravated asthma Chronic

bronchitis

Decreased lung function

Increased respiratory symptoms

coughing or difficulty breathing

Increased Cardiopulmonary Mortality

Increased Risk of Lung Cancer

Sources of Particulate Matter Emissions from traffic

Diesel exhaust particulate matter

This particulate toxic potential has been associated with serious adverse Health

effects including respiratory symptoms Pulmonary function and cardiovascular

diseases (Geller et al 2006 Bernstein et al 2004)

Brake wear particulate matter

Brake wear particulate matter Chemical content (iron(Fe) copper(Cu) Antimony(Sb) barium(Ba) this type of particulate can cause severe respiratory and cardiovascular damages and it is also known that Sb has been classified as a possible human pulmonary carcinogen by the International Agency for Research on Cancer (IARC 1989 Et al 2013)

Fig images of brake wear particles generated at a road simulation study ( centre lt25 μm right lt10

μm) Source [Kukutschovaacute et al 2011]

Tire wear particulate matter

The tire wear particles of the tires are generated either by frictional forces between the treadand the road pavement The chemical content Fe Cr Pb Ti Cr Cu Zn Sr Y Zr Sn Sb Ba LaCe and Pb)

Fig Examples of near spherical particles PM 10 and 25 which are originate from interaction of tires and pavements Source [Dahl et al 2006]

Study Area

The Paso del Norte (PdN) region Selected two strategic areas of study El Paso County zip code 79905 Urban area and Dona Ana County Zip Code 880218802788072 Rural Restricted urban access (freeways and interstates)

Map of the area of the simulation by the MOVES model in the study area

Geographic Domain Zip Code 79905 Urban Area (El Paso County)

Zip Codes 88021880278807288048 (Dona Ana County)

Urban road Delta Dr St 31o 45rsquo 5637- 106o 27rsquo 1212 10 miles

Cordova Bridge of the Americas 31o 45rsquo 4367- 106o 27rsquo 0506 15 miles

478 Highway interstate 31o 46rsquo 1326- 106o 27rsquo 0327 05 miles

110 Highway interstate 31o 46rsquo 1210- 106o 27rsquo 0066 10 miles

10 Interstate Gateway Blvd 31o 46rsquo 397- 106o 26rsquo 4769 05 miles

Chamizal Loop 478 31o 46rsquo 668- 106o 26rsquo 5456 05 miles

Alameda Loop 20 31o 46rsquo 1323- 106o 27rsquo 0328 10 miles

Paisano Dr St Patriot freeway

route 62

31o 46rsquo 0669- 106o 27rsquo 212 15 miles

St Piedras 31o 46rsquo 1326- 106o 27rsquo 0327 10 miles

Dona Ana County Miles

Interstate 25 32o 23rsquo 0561 -106 48

1054 32o 23rsquo 3434- -

106 48 1054 32o 23rsquo

5660 106 48 4314

50

Geographic domain To obtain the simulation mobile data from modelMOVES2010a was configurated the coordinates selected in the study areas

El Paso County

PM25 Estimation from Aerosol Optical Depth (AOD) using

satellites

We examined the relationship

between Aerosol Optical Depth

(AOD) estimated from satellite data

at 5 km spatial resolution and the

mass of fine particles le25 μm in

aerodynamic diameter (PM25)

monitored on the ground in El PdN

area PM25 data was recorded from

air quality monitoring Chamizal

station (TCEQ) on different periods

Our analysis shows a significant

positive association between AOD

and PM25

Time-series and scatter plots of AOD estimated PM25 and surface PM25

Analysis of the meteorological factors and synoptic conditions leading to a local high

ozone event episode June 12-21 2006

Meteorology plays a critical role in determining atmospheric ozone concentrations A good synoptic scale weather forecast is essential to accurately forecast tropospheric and surface ozone concentrations

Figure 1 The domain configuration and Landuse categories

resolution 25 km domainFigure 2 The Geopotential height at 500 mb Figure 3 depicts the 850 mb at a lower altitude The

white regions observed in the graph correspond to

mountainous areas

Figure 4 Temperature at 2m height

above surface at 22 UTC June 18 2006

36 km resolution

Performance Evaluation

01020304050

Ju

ne

137

130

0

190

0

10

0

Ju

ne

157

130

0

190

0

10

0

Ju

ne

187

130

0

190

0

10

0

Tem

pe

ratu

re (⁰C

)

Local time (Hrs)

C41 June 13-19 2006

WRF_temperature

(⁰C)

TCEQ_temperature

(⁰C)

01020304050

June1

37

100

0

130

0

160

0

190

0

220

0

10

0

40

0

June1

57

100

0

130

0

160

0

190

0

220

0

10

0

40

0

June1

87

100

0

130

0

160

0

190

0

220

0

10

0

40

0

Rel

ativ

e h

um

idit

y (

)

Local time (Hrs)

C41 June 13-19 2006

WRF_rh () TCEQ_relative humidity ()

0

5

10

15

20

June

137 10

13

16

19

22 1 4

June

157 10

13

16

19

22 1 4

June

187 10

13

16

19

22 1 4

Win

d s

pee

d (

ms

Local time(Hrs)

C12 June 13-192006

WRF_wind speed (ms) TCEQ_ wind speed (ms)

We evaluate the WRF modelrsquos performance

by comparing against corresponding

experimental TCEQ data and performing the

required statistical analysis

HYSPLIT Model

HYSPLIT was simulated and showed that the ozone is mostly transported to El Paso from north western and south western US and Mexican regions during the 72 hours duration of the simulation

0

20

40

60

80

100

1200

00

10

02

00

30

04

00

50

06

00

70

08

00

90

01

00

01

10

01

20

01

30

01

40

01

50

01

60

01

70

01

80

01

90

02

00

02

10

02

20

02

30

0

Ho

url

y o

zon

e [

pp

b]

0102030405060708090

00

01

00

20

03

00

40

05

00

60

07

00

80

09

00

10

00

11

00

12

00

13

00

14

00

15

00

16

00

17

00

18

00

19

00

20

00

21

00

22

00

23

00

Ho

url

y o

zon

e [

pp

b]

June 18th June 19th

Performance Evaluation

01020304050

Ju

ne

137

130

0

190

0

10

0

Ju

ne

157

130

0

190

0

10

0

Ju

ne

187

130

0

190

0

10

0

Tem

pe

ratu

re (⁰C

)

Local time (Hrs)

C41 June 13-19 2006

WRF_temperature

(⁰C)

TCEQ_temperature

(⁰C)

0

50

100

150

June1

37

100

0

130

0

160

0

190

0

220

0

10

0

40

0

June1

57

100

0

130

0

160

0

190

0

220

0

10

0

40

0

June1

87

100

0

130

0

160

0

190

0

220

0

10

0

40

0Ozo

ne

(pp

b)

Local time (Hrs)

C41 June 13-19 2006

CAMx_ozone (ppbV) TCEQ_ozone (ppb)

0

10

20

30

40

50

June1

37

100

0

130

0

160

0

190

0

220

0

10

0

40

0

June1

57

100

0

130

0

160

0

190

0

220

0

10

0

40

0

June1

87

100

0

130

0

160

0

190

0

220

0

10

0

40

0

Rel

ativ

e h

um

idit

y (

)

Local time (Hrs)

C41 June 13-19 2006

WRF_rh () TCEQ_relative humidity ()

0

5

10

15

20

June

137 10

13

16

19

22 1 4

June

157 10

13

16

19

22 1 4

June

187 10

13

16

19

22 1 4W

ind

sp

eed

(m

sLocal time(Hrs)

C12 June 13-192006

WRF_wind speed (ms) TCEQ_ wind speed (ms)

Methodology

Medical Data The data by weekly monthly and year for daily emergency room and hospital admission for the respiratory

infections (RD) and cardiovascular diseases (CVD) was extracted from hospitals records located in the El PdN

the system includes data on type of admission primary and secondary causes of admissionRESPIRATORY DISEASE

Bronquitis amp Chronic Bronchitis 466 - 4661 491 - 4919

Asthma 463 - 4939

Emphysema 492

Respiratory failure 51881

HEART DISEASE

Accute Myocardial Infarction 410

Coronary Athersclerosis 4140

Other Ischemic Heart Disease 411-4139 4141-4149

Cardiac Dyshythmias 427

Essential hypertension 401

Acute myocardial infarction 410

Congestive Heart Failure 4280 4282-4284

Hypertensive heart disease 402

Table 1 ICD -9 Codes for Respiratory and Cardiovascular Diseases

0

50

100

150

200

250

300

Wee

k 1

Wee

k 2

Wee

k 3

Wee

k 4

Wee

k 5

Wee

k 6

Wee

k 7

Wee

k 8

Wee

k 9

Wee

k 1

0

Wee

k 1

1

Wee

k 1

2

Wee

k 1

3

Wee

k 1

4

Wee

k 1

5

Wee

k 1

6

Wee

k 1

7

Wee

k 1

8

Wee

k 1

9

Wee

k 2

0

Wee

k 2

1

Mo

rb

idit

y D

isch

arg

e fo

r a

ll R

esp

ira

tory

Dis

ease

IC

D-9

(

Ast

hm

aB

ro

nch

itis

)

Weekly Morbidity Discharges of all the Listed Diagnoses for All

Respiratory Disease During WinterSpring 2010

Asthma-Bronchitis

EPA MOVES Model for Estimating Emission

Inventories

Motor Vehicle Emission Simulator (MOVES 2010b) will be configuredin The El Paso North Region for Calculate five categories of PM10

PM25 total Emission inventories from all on-road traffic over a

variety of scales within periods of time selected weeks months

and years

Moves (Motor Vehicle Emission

Simulator)

The emission model is develop using the current equation to calculate direct traffic emissions from

vehicles in the form of PM is

Eext annual emissions are measured in grams of miles traveled by the vehicle (gVMT )

SL is the road surface loading in (gm2)

W is the average weight in tons of the vehicles on the road

K is the particle size multiplier for particle size range (eg gVMT for PM10 when using grams and miles)

P is the 7 number of wet days with at least 0254 mm of precipitation during the averaging period

N is the number of years considered in the averaging period

C is the particle size specific emissions factor in units of interest vehicle direct exhaust brake wear and tirewear

Modeling Simulation Domain and Emissions Scenarios

For simulations of mobile air quality emission inventories a motor vehicle emission simulator EPA (MOVES 2014a) was used

The modeling use input factors divided into seven section

parameters

On-Road Inventory local data

input

Scale

Geographic Bounds

Traffic intensity

Vehicle Type

Pollutants

Road Type

Fuel Types

Figure Source EPA US Environmental Protection Agency 2012- Moves 2010b Model

EPA Moves 2014a The modeling used input factors divided into six section

parameters On-Road Inventory local data input

Geographic Domains CountyNonattainment Area

Vehicle-Miles Traveled (VMT) is the total number of miles driven by all vehicles withina given time period and geographic area

Average speed range from 25 miles per

hour to 65 miles per hour

Vehicle Classes Motorcycle PassengerCarTruks light-duty Commercial Truck(6001-8500 lbs) Buses heave-duty trucksRefuse trucks School Bus Single UnitShort Haul-truck Single Unit Long Haul-truck Long Haul Truck Heavy-DutyVehicles (26001-33000 lbs)

Pollutants

Road TypeRural restricted Acces(Freeways and interstates) Rural and Restricted Acces Urban Restricted Acces Off-Network

Fuel Types Gasoline Diesel Fuel

Specific Road Types

Two road types for running emission from the MOVES can be

selected

(freeways and interstates)

Interior urban Urban

Figure Source EPA US Environmental Protection Agency 2012- Moves 2010b Model

VehiclesEquipment

This panel show which on-road vehicles will be modeled

Figure Source EPA US Environmental Protection Agency 2012- Moves 2010b Model

Long haul truck Short haul truck Inercity bus Ligth comercial truck

Passenger car Passenger truck Refuse truck

School bus Single unit long haul-truck

Single unit short haul-truck

Transit bus

Motor home

Motorcycle

Based on Department of Transportation Highway MOVES will Estimates Traffic

Emissions from Cars Trucks amp Motorcycles

Output Data Moves 2014a

Inventories of PM 10 25 Mobile Emission from all

on-Road Traffic

Exhaust Emission PM 10 25 gramsmile

Brake Wear Emission PM 10 25 gramsmile

Tire wear Emission PM 10 25 gramsmile

Date of Vehicle miles traveled (VMT) for

Day Week Month Year

Total Vehicle population

Vehicle age distribution

Simulation of Mobile Emission in the El PdN Region Zip Code 79905

Figure Total Emissions from road traffic in El Paso TX Area were estimated for PM10

Exhaust and Non exhaust emission in kilogramsmonth (Source EPA MOVES 2014a)

0

10000

20000

30000

40000

50000

PM

10 k

gM

on

th

Months

Monthly PM 10 Exhaust and Non-Exhaust Mobile Emissions 2010

On-Road Urban Restricted Area Zip Code 79905

Primary Exhaust PM 10 (kg) Primary PM 10 Brakewear (kg)

Primary PM 10 Tirewear (kg)

05000

100001500020000250003000035000400004500050000

PM

25

kg

Mo

nth

Months

Monthly PM 25 Exhaust and Non-Exhaust Mobile Emission 2010

On-Road Urban Restricted Area Zip Code 79905

Primary Exhaust PM 25 (kg) Primary PM 25 Brakewear (kg) Primary PM 25Tirewear (kg)

Figure Total Emissions from road traffic in El Paso TX Area were estimated for PM25

Exhaust and Non exhaust emission in kilogramsmonth (Source EPA MOVES 2014a)

Total Emissions from Road Traffic in El Paso County PM1025 Exhaust and Non exhaust Emission in kilogramsmonth

Taking the interests to the health risks related to PM 1025 mobile emission were simulated

Exhaust and Non-exhaust emissions contribute almost equally to total traffic-related PM1025 Emissions (Querol et al 2004 Bukowiecki et al 2009a Amato et al 2011)

Monthly PM 10 25 Exhaust and Non-Exhaust (BrakewearTirewear) Mobile

Emission 2010 On-Road Urban Restricted Area Zip Code 79905

Figure Total Emissions from road traffic in El Paso TX Area were estimated for PM10 25 Exhaust and Non Exhaust mobile

emission in kilograms per month (Source EPA MOVES)

0

10000

20000

30000

40000

50000

January February March April May June July August September October November December

PM

10

25

(K

ilog

ram

s)

Months

Summary- Monthly PM 10 25 Exhaust and Non-Exhaust Mobile

Emission 2010 On-Road Urban Restricted Area Zip Code 79905

Primary Exhaust PM 10 Primary PM 10 Brakewear Primary PM 10 Tirewear

Primary Exhaust PM 25 Primary PM 25 Brakewear Primary PM 25Tirewear

Exhaust Emissions PM1025 is reaching maximum emission 48000-42000 thousand of Kgmonth followedby Brake wear 29000-5000 thousand kgmonth and Tire wear with 9000-2000 kgmonth The results showthat the emissions of PM derived mainly from Exhaust and Brake are significantly higher in Urban Area

Annual Contribution of Mobile Emission PM 1025 (Kg) Zip Code 79905 El

Paso County 2010

Total Primary

Exhaust _PM10

39

Total Primary

Exhaust _PM25

36

Brakewear

particulate_PM10

18

Tirewear

particulate_PM10

4

Brakewear

particulate_PM25

2

Tirewear

particulate_PM25

1

0

5

10

15

20

25

30

35

40

45

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53

Fig Annual Average PM10 Concentrations at the

Chamizal C41 Station and PM1025 mobile

Concentration Zip code 79905

PM10 TCEQ (μgm3) Total Mobile Emission PM10 (Ugm3)

Fig Exhaust Emission is Contributing Approximately 74 of total

PM1025 Mobile Emissions following of Brake wear with 20 and Tire

wear with 5

Annual Average PM1025 ugm3 Mobile Emissions (Moves) 26 Chamizal C41

Monitoring Station (TCEQ Chamizal Station )

Predicting Mobile Emission and VTM

Estimation The PdN Region 2010

44E+09

46E+09

48E+09

5E+09

52E+09

54E+09

56E+09

58E+09

6E+09

62E+09

0

50000

100000

150000

200000

250000

300000

350000

20

10

20

11

20

12

20

13

20

14

20

15

20

16

20

17

20

18

20

21

20

22

20

23

20

24

20

25

20

26

20

27

20

28

20

29

20

30

EX

HA

US

T

EM

ISS

ION

MO

BIL

E (

KG

YE

AR

)

YEARS

Predict ing Mobile Exhaust Emission and VTM

Estimation

2010 - 2030 e l PdN Area

Total_ Exhaust PM10 Total_ Exhaust PM25 Distance (Miles)

Fig Predicting Mobile Exhaust PM1025 (kgMonth) Emission and VTM Estimation 2010

- 2030 el PdN Area

44E+09

46E+09

48E+09

5E+09

52E+09

54E+09

56E+09

58E+09

6E+09

62E+09

0

5000000

10000000

15000000

20000000

25000000

30000000

20

10

20

11

20

12

20

13

20

14

20

15

20

16

20

17

20

18

20

21

20

22

20

23

20

24

20

25

20

26

20

27

20

28

20

29

20

30

EX

HA

US

T

EM

ISS

ION

MO

BIL

E (

KG

YE

AR

)

YEARS

Predict ing Mobile Exhaust Emission and

VTM Estimation

2010 - 2030 e l PdN Area

CO NO2 NO NOx Distance

Fig Predicting Mobile Exhaust Emission and VTM Estimation

2010 - 2030 el PdN Area in El Paso TX Area were estimated for

Total CO NOx NO2 NO emission in kilograms per year

(Source EPA MOVES 2014a model)

The simulated Exhaust emissions in the future years shows a trend of reduction of this type of emissions in the

future years one factor should be the new hybrid technology is increasing by 476 since 2010 to 2015 and

use of catalytic converters diesel particulate filters and improved fuels and engines Non-exhaustive sources

will increase in the coming years because there is no control in the material of manufacture composed by Fe

Cu and Mn also not to be able to reduce the number of events of braking (Accelerations and decelerations)

45E+09

5E+09

55E+09

6E+09

65E+09

0

50000

100000

150000

200000

250000

201

0

201

1

201

2

201

3

201

4

201

5

201

6

201

7

201

8

202

1

202

2

202

3

202

4

202

5

202

6

202

7

202

8

202

9

203

0

NO

N-

EX

HA

US

T

EM

ISS

ION

MO

BIL

E

(KG

YE

AR

)

YEARS

Predicting Non Exhaust Mobile

Emission and VTM Estimation

2010 - 2030 el PdN Area

Brake_PM10 Tire_PM10 Distance (Miles)

Fig Predicting Mobile Exhaust PM1025 (kgMonth) Emission and VTM

Estimation 2010 - 2030 el PdN Area

Daily Avg PM1025

Levels of PM Mobile Emission Non-Exhaust -Rush Hour Periods Fall 2010 Zip Code

79905

00

100

200

300

400

500

600

Mo

bil

e P

M1

0 (k

g)

Rush Hours

Daily Avg PM10

Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush Hours

Periods 2010 Zip Code 79905

Total Primary Exhaust

_PM10 WinterSpring

Brakewear

particulate_PM10

WinterSpringTirewear particulate_PM10

WinterSpring

Total Primary Exhaust

_PM10 Summer

Brakewear

particulate_PM10 Summer

Tirewear Particulate_PM10

Summer

Total Primary Exhaust

_PM10 Fall

Brakewear

particulate_PM10 Fall

Tirewear particulate_PM10

Fall

00

50

100

150

200

250

300

350

Mo

bil

e P

M2

5 (k

g)

Rush hours

Daily Avg PM25

Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush

Hours Periods 2010 Zip Code 79905

Total Primary Exhaust _PM25

WinterSpring

Brakewear Particulate_PM25

WinterSpring

Tirewear particulate_PM25

WinterSpring

Total Primary Exhaust _PM25

Summer

Brakewear particulate_PM25

Summer

Tirewear particulate_PM25

Summer

Total Primary Exhaust _PM25

Fall

Brakewear particulate_PM25

Fall

Tirewear particulate_PM25

Fall

Figure Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush Hours Figure Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush Hours

GIS EMISSIONS INVENTORY SYSTEM A geographic information system (GIS) was used to established geographic scenarios with processed images of seasonal mobile

emissions in the PdN region Seasonal mapping is visualized for different types of pollutants Brakewear Exhaust and Tyrewear

Fg Graphics of GIS and Seasonal mobile Emission of particulate matter emission inventory Seasonal emission simulations were performed in kilograms and five contributing inputs factors were identified for

modeling 1) On the composition of the particulate material from different sources such as Exhaust and Non exhaust (Brake wear Tirewear) 2) The Vehicles Equipment clasification were selected according to

the use of gasoline and diesel fuel (motorcycle passenger car Light Duty Vehicles Trucks refuse truck Light Duty Vehicles Light Commercial Truck Light Duty Vehicles School Bus)

Winter Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

120354 67860 19065

Spring Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

139767 86702 24463

Summer Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

94747 62481 17630

Fall Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

75510 45542 12596

251 Descriptive Statistics Data Analysis

Weekly Correlation Analysis of Mobile Emission PM10 (Exhaust-Non-Exhaust) and Respiratory

Diagnoses WinterSpring Summer and Fall 2010

0

2

4

6

8

10

0

50

100

150

200

250

300

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21

Mo

rbid

ity

Dis

ch

arg

e

for

all R

esp

ira

tory

Dis

ea

se

ICD

-9

(A

sth

ma

-Bro

nc

hitis

)

WinterSpring Week

Weekly Avg Mobile PM10 Concentrations during

WinterSpring 2010 and its Influence on Respiratory

Diagnoses

Zip Code 79905

Total Medical data ZIP Code 79902

Total Mobile Emission PM10 (Ugm3)

0

1

2

3

4

5

6

7

0

20

40

60

80

100

Mo

rbid

ity

Dis

ch

arg

e

for

all R

esp

ira

tory

Dis

ea

se

ICD

-9

(Ast

hm

aB

ron

ch

itis

)

Weekly Avg Mobile PM10 Concentrations during

Summer 2010 and its Influence on Respiratory

Diagnoses

Summer 2010 Zip Code 79905

Total Mobile Emission PM10

Hospital Admission (Asthma-Bronchitis)

0

2

4

6

8

10

12

0

20

40

60

80

100

120

140

160

180

200

Mo

rbid

ity

dis

ch

arg

es

for

all r

esp

ira

tory

dis

ea

se

Weekly Avg Mobile PM10 Concentrations

during Fall 2010 and its Influence on Respiratory

Diagnoses

Zip Code 79905

Total Medical data ZIP Code 79902

Total Mobile Emission PM10 (Ugm3)

Mobile(Exhaust-Non-

Exhaust) PM10 and

Asthma-Bronchitis)

Linear R

Square

WinterSpring 734 ndash 39

Summer 614 ndash 32

Fall 548 -29

PM10 Mobile emission (Exhaust-Non-Exhaust)contributed significantly

association to the incidence of RD

Weekly Correlation Analysis of PM 25 Mobile Emission (Exhaust-Non-Exhaust)

and Cardiovascular Diagnoses WinterSpring Summer and Fall 2010

0010203040

00500

100015002000

Wee

k 1

Wee

k 2

Wee

k 3

Wee

k 4

Wee

k 5

Wee

k 6

Wee

k 7

Wee

k 8

Wee

k 9

Wee

k 1

0

Wee

k 1

1

Wee

k 1

2

Wee

k 1

3

Wee

k 1

4

Wee

k 1

5

Wee

k 1

6

Wee

k 1

7

Wee

k 1

8

Wee

k 1

9

Wee

k 2

0

Wee

k 2

1

Morb

idit

y d

isch

arg

es f

or

all

card

iovasc

ula

r d

isea

se

Weekly Avg PM25 Mobile Concentrations during

WinterSpring 2010 and its Influence on all Heart

Diagnoses

Zip Code 79905

Total All Heart Disease PM 25 mobile (μgm3)

0010203040

00

500

1000

1500

Mo

rbid

ity

dis

ch

arg

es

for

all

ca

rdio

va

scu

lar

dis

ea

se

Weeks

CORRELATION BETWEEN MOBILE PM25 ugm3

EXPOSURE TO HEART DISEASES SYMPTOMS

SUMMER SEASON 2010

Total All Heart Disease PM 25 mobile (μgm3)

Figure Statistical Analyses of the Relationship Between PM25 Caused by Traffic Emission( 26 of total Emission) with Heart diseases Source Hospital Admissions for Asthma Acute Bronchitis and Heart diseases in El Paso County zip code 79905 from Texas Health Care

Information Council in Austin Texas (Texas Health Care Information Council 2000)

00

10

20

30

40

0

50

100

150

We

ek 3

6

We

ek 3

7

We

ek 3

8

We

ek 3

9

We

ek 4

0

We

ek 4

1

We

ek 4

2

We

ek 4

3

We

ek 4

4

We

ek 4

5

We

ek 4

6

We

ek 4

7

We

ek 4

8

We

ek 4

9

We

ek 5

0

We

ek 5

1

We

ek 5

2

We

ek 5

3

Mo

rbid

ity

dis

ch

arg

es

for

all

ca

rdio

va

scu

lar

dis

ea

se

CORRELATION BETWEEN MOBILE PM25 ugm3

EXPOSURE TO HEART DISEASES SYMPTOMS FALL

SEASON 2010

Total All Heart Disease PM 25 mobile (μgm3)

Mobile(Exhaust-

Non-Exhaust)

PM10 and

Asthma-

Bronchitis)

Linear R

Square

WinterSpring 833 -42

Summer 620 -32

Fall 501-26

PM10 Mobile

emission (Exhaust-

Non-

Exhaust)contribut

ed significantly

association to the

incidence of CVD

Diseases

Monthly Brake Mobile Emission PM1025 kg During year 2010 and its Influence on

Respiratory Diagnoses Zip Code 79905

00200040006000800010000

010000200003000040000

PM

10

Mo

bile

(K

g)

Months

Monthly Brake Mobile Emission PM10 kg during year

2010 and its Influence on Respiratory Diagnoses

Zip Code 79905

Primary PM 10

Brakewear 00100020003000400050006000

0

1000

2000

3000

4000

PM

25

Mo

bil

e(K

g)

Months

Monthly Brake Mobile Emission PM25 during

year 2010 and its Influence on Heart Diagnoses

Zip Code 79905

Primary PM 25

Brakewear

Heart Diseases

Hospital

Admission

Brake Mobile Emission

PM10 kg Asthma-

Bronchitis)

Brake Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=969 Linear Square R=856

Monthly Mobile Exhaust Emission PM1025 During year 2010 and its Influence on

Respiratory Diagnoses Zip Code 79905

0

200

400

600

800

1000

0

10000

20000

30000

40000

50000

1 3 5 7 9 11

PM

10

(K

g m

on

th)

Months

Monthly Mobile Exhaust Emission PM10 during

year 2010 and its Influence on Respiratory

Diagnoses

Zip Code 79905

Primary Exhaust

PM 10

Respiratory Disease

(Asthma

Bronchitis) Hospital

Admission

0

100

200

300

400

500

600

0

10000

20000

30000

40000

50000

1 2 3 4 5 6 7 8 9 101112

PM

25

(K

g m

on

th)

Months

Monthly Exhaust Mobile Emission PM25 during

year 2010 and its Influence on Heart Diagnoses

Zip Code 79905

Primary Exhaust PM

25

Heart Diseases

Hospital Admission

Exhaust Mobile Emission

PM10 kg Asthma-

Bronchitis)

Exhaust Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=929 Linear Square R=831

Monthly Tire wear Mobile Emission PM1025 During year 2010 and its Influence on Heart

Diagnoses Zip Code 79905

0

100

200

300

400

500

600

700

800

900

0

1000

2000

3000

4000

5000

6000

7000

8000

9000

1 2 3 4 5 6 7 8 9 10 11 12

PM

10

(K

g m

on

th)

Months

Monthly Tirewear Mobile Emission PM10 during year 2010

and its Influence on Heart Diagnoses

Zip Code 79905

Primary PM 10 Tirewear

Mobile Emission

Respiratory Disease

(Asthma Bronchitis)

Hospital Admission

0

100

200

300

400

500

600

0

200

400

600

800

1000

1200

1400

1 2 3 4 5 6 7 8 9 10 11 12

PM

25

(K

g m

on

th)

Months

Monthly Tirewear Mobile Emission PM25 during year 2010

and its Influence on Respiratory Diagnoses

Zip Code 79905

Primary PM 25Tirewear

Mobile Emission

Heart Diseases Hospital

Admission

Exhaust Mobile Emission

PM10 kg Asthma-

Bronchitis)

Exhaust Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=769 Linear Square R=715

Dona Ana County Zip Codes

88021880278807288048

Primary

Exhaust

PM 10 Zip

code

79905

Total

Primary

Exhaust

PM10

Dona Ana

Primary

Exhaust

PM 25 Zip

Code

79905

Total

Primary

Exhaust

PM25

Dona Ana

Series1 430378 111773 391915 102123

0

100000

200000

300000

400000

500000

AX

IS T

ITLE

Annual Comparison of the Mobile

Exhaust Emissions El Paso County

and Dona Ana 2010

Primary

PM 10

Brakewea

r Zip code

79905

Brakewea

r

particulat

e_PM10

Dona Ana

Primary

PM 10

Tirewear

Zip code

79905

Tirewear

particulat

e_PM10

Dona Ana

Series1 262585 48573 73754 11864

050000

100000150000200000250000300000

AX

IS T

ITLE

Annual Comparison of the Mobile

Brakewear Emissions El Paso County

and Dona Ana 2010

Figure Comparison of the Annual Mobile Emissions

of Primary PM10 Non-Exhauts (Brake ) from Dona

Ana County New Mexico and El Paso Texas Units

in KgMonth

Figure Comparison of the Annual Mobile Emissions

of Primary PM10-Exhauts Emission from Dona Ana

County New Mexico and El Paso Texas Units in

KgMonth

Primary

PM 25

Brakewe

ar Ziphellip

Brakewe

ar

particula

te_PMhellip

Primary

PM

25Tirewe

ar Ziphellip

Tirewear

particula

te_PM25

Donahellip

Series1 32645 6071 10919 1779

0

10000

20000

30000

40000

AX

IS T

ITLE

Annual Comparison of the

Mobile Exhaust Emissions El Paso

County and Dona Ana 2010

Figure Comparison of the Annual Mobile Emissions

of Primary PM10-Exhauts Emission from Dona Ana

County New Mexico and El Paso Texas Units in

KgMonth

Monthly Mobile Emission PM1025 kg During year 2006

and its Influence on Respiratory Diagnoses Dona Ana

County Zip Code 880218802788072

0

100

200

300

0

5000

10000

15000

Axi

s Ti

tle

Axis Title

Monthly Mobile Exhaust Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Total PrimaryMobile Exhaust_PM10

All Respiratory ICD-9 (AsthmaBronchitis)

050100150200250300

010002000300040005000

Axi

s Ti

tle

Axis Title

Monthly Mobile Brake Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Brakewearparticulate_PM10

All RespiratoryICD -9 (AsthmaBronchitis)

050100150200250300

0200400600800

10001200

Axi

s Ti

tle

Axis Title

Monthly Mobile Tirewear Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Tirewearparticulate_PM10

All Respiratory ICD -9 (AsthmaBronchitis)

Mobile Exhauts

Emission PM10

kg Asthma-

Bronchitis)

Brake Mobile

Emission PM10

kg and Heart

Diagnoses

Tirewear Mobile

Emission PM10

kg and Heart

Diagnoses

Linear Square

R= 951

Linear Square

R=625

Linear Square

R=525

Mobile Exhauts

Emission PM25

kg Asthma-

Bronchitis)

Brake Mobile

Emission PM25

kg and Heart

Diagnoses

Tirewear Mobile

Emission PM25

kg and Heart

Diagnoses

Linear Square

R= 986

Linear Square

R=691

Linear Square

R=601

Results

The results showed that mobile PM emissions in the urban areas close to urban Road and highways is putting at risk public health

and the proportion of diseases attributable to this exposure is potentially large

Brake wear emissions is much lower in freeways due to significantly reduced number of braking events while tire wear is much

higher in areas where studded tires are used The emission of exhaust gases are much higher in areas where there is a high

vehicular traffic

Brake Mobile

Emission PM10 kg

Asthma-Bronchitis)

Brake Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square

R=969

Linear Square

R=856

Exhaust Mobile

Emission PM10 kg

Asthma-Bronchitis)

Exhaust Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square

R=929

Linear Square

R=831

Tirewear Mobile

Emission PM10 kg

Asthma-Bronchitis)

Tirewear Mobile

Emission PM25 kg

and Heart Diagnoses

Linear Square R=769 Linear Square R=715

Brake Mobile

Emission PM10 kg

and Heart

Diagnoses

Brake Mobile

Emission PM25 kg

and Heart

Diagnoses

Exhaust Mobile

Emission PM10 kg

Asthma-Bronchitis)

Linear Square

R=625

Linear Square

R=691

Linear Square R=

951

Exhaust Mobile

Emission PM25 kg

Asthma-

Bronchitis)

Tire wear Mobile

Emission PM10 kg and

Heart Diagnoses

Tirewear Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square R=

986

Linear Square R=525 Linear Square

R=601

El Paso County

Dona Ana

County

BenMAP-CE

In this analysis the Program of Mapping and Analysis of Environmental Benefits-Community Edition

(BenMAP-CE) was used to Estimate the number and economic value of health impacts resulting from changes

in air pollution PM 25 Ugm3 in The El Paso Area

Health and Economic Benefits associated with the Response of PM25 Emission between

Base Year 2010

Number of Mortalities in 2010 Base Year Based on El Paso County Texas Department of State Health Services

Number of Mortalities in 2010 Base Year Based on El Paso County Texas

Department of State Health Services

cause of death

year

2010

Populatio

n

Affected

Backgro

und

Concentr

ation Pollutant

Rollback

Type

Avoided

Deaths

(

Populatio

n)

alzheimers disease 2010 40716 125 PM25

25

microgmAcircsup3

Rollback 9

diseases of the

heart 2010 15834 125 PM25

25

microgmAcircsup3

Rollback 35

influenza and

neumonia 2010 81432 125 PM25

25

microgmAcircsup3

Rollback 18

acute bronchitis

and bronchiolitis 2010 117624 125 PM25

25

microgmAcircsup3

Rollback 26

chronic lower

respiratory diseases 2010 54288 125 PM25

25

microgmAcircsup3

Rollback 12

The Basin-wide decrease in 4 ugm3 PM25 concentration after this

reduction control

Cause of death year 2010

Populatio

n

Affected

Background

Concentrati

on

Reduc

cion

scena

rio Polluta

nt

Rollback

Type

Avoi

ded

Deat

hs

(

Pop

ulati

on)

economic

benefits

analysis $

Alzheimers

disease 2010 121 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 9 12000

Diseases of the

heart 2010 470 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 35 35000

Influenza and

neumonia 2010 242 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 18 42500

Acute bronchitis

and bronchiolitis 2010 349 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 26 95000

Chronic lower

respiratory

diseases 2010 161 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 12 4500

$1 295000

PM25-related Mortalities Based on BenMAP-CE Estimate in 2010 Base Year with change in the concentrations levels

Health and Economic Benefits associated with the Response of PM25 Emission between

Base Year 2010 Increasing 7 Ugm3

Cause of death year 2010

Population

Affected

Deaths

avoided by

attaining 195

μgm3

standard

Background

Concentrati

on

Pollut

ant

Rollback

Type

Avoided

Deaths (

Populatio

n)

econo

mic

Unben

efits

analysi

s

Alzheimers

disease 2010 4524 195 PM25

25

microgmAcircsup3

Rollback 19 150000

Diseases of the

heart 2010 20358 195 PM25

25

microgmAcircsup3

Rollback 135 450000

Influenza and

neumonia 2010 126672 195 PM25

25

microgmAcircsup3

Rollback 38 525000

Acute bronchitis

and bronchiolitis 2010 162864 195 PM25

25

microgmAcircsup3

Rollback 36 122000

Chronic lower

respiratory

diseases 2010 99528 195 PM25

25

microgmAcircsup3

Rollback 12 650000

Conclusions

An excellent Pearson Correlation was established to analyze the relationship in the relative risks of hospitalization of Respiratory(RD) and cardiovascular (CVD) associated with ambient exposure caused by traffic emission in relation to their size andspecific sources of emission on different scenarios interior a border Urban Rural Urban restricted access (freeways andinterstates)

A significant correlation of PM1025 exposure from mobile emission and hospital admissions for selected Respiratory (RD) andcardiovascular (CVD) diagnoses was established The results showed that PM emissions in urban restricted access (freeways andinterstates) is mainly caused by traffic Therefore people living close to highways are more exposed higher vehicular emissions

Conclusions

We found statistically significant associations between mobile PM25 caused by traffic emission with Respiratory and Cardiovascular Diseases in the study areaSubsequently a correlation between cardio-respiratory mortality is established

A significant correlation of PM1025 exposure from mobile emission and hospital admissions for selected Respiratory (RD) and cardiovascular (CVD) diagnoses isestablished The results showed that PM emissions in urban restricted access (freeways and interstates) is mainly caused by traffic Therefore people living close tohighways receive higher vehicular emissions

The table shows the percentage of PM mobile exposure in the analyzed areas contributing to increase the risk of Respiratory and Cardiovascular Diseases

An examination was conducted of the synoptic and local meteorology for the June 2006 ozone episode using the WRF model to determine how meteorological parametersinfluence the formation transport and dispersion of ozone in the PdN The predominant synoptic feature of the ozone event day was the expansion intensification and slowprogression of an upper-level ridge of high pressure The high ozone episodes are associated with highly stable atmospheres strong temperature inversions with low mixingheights and therefore low mixing volumes Under these conditions emissions such as NOx lead to highly polluted conditions that favor ozone formation

BenMAP Conclusions

We have estimated the number and economic value of health impacts resulting

from changes in air pollution concentrations of PM 25 in the PdN region

Reduction of Pm 25 4 UGm3= Avoided 213 cases respiratory cardiovascular

diseses and Economic Benefits associated with the Response of PM25 Emission + $

1295000

Increase of PM25 7 ugm3 = increasing Dies= 326 economic Unbenefits= 2345000$

Bibliography

1 Dockery DW Pope CAI Xu X Spengler JD Ware JH Fay ME Ferris BG Speizer FE An association between air pollution and mortality in six US cities N Engl J Med 3291753ndash1759 (1993)

2 Samet JM Dominici F Curriero FC Coursac I Zeger SL Fine particulate air pollution and mortality in 20 US cities 1987ndash1994 N Engl J Med 3431742ndash1749 (2000)

3 Nel AE Diaz-Sanchez D Li N The role of particulate pollutants in pulmonary inflammation and asthma evidence for the involvement of organic chemicals and oxidative stress Curr Opin Pulm Med 20017 20ndash26

4 Westerholm R Karl-Erik E Exhaust emissions from lightand heavy-duty vehicles chemical composition impact of exhaust after treatment and fuel parameters Environ Health Perspect 102(suppl 4)13ndash23 (1994)

5 Bascom R Bromberg P Costa D Delvin R Dockery D Frampton M Lambert W Samet J Speizer F Utell

6 Health effects of outdoor air pollution Am J Respir Crit Care Med 1533ndash50 (1996)

7 Chow JC Watson JG Frazier CA Egami RT Goodrich A Ralph C Spatial and temporal source contributions to

8 PM10 and PM25 in Reno NV In PM-10 Implementation of Standards Transactions An APCAEPA International Speciality Conference San Francisco CA (Mathal CV Stonefield DH eds) PittsburghAPCA 1988439ndash457

9 overview In Particulate Matter Health and Regulatory Issues VIP-49 Proceedings of an International Specialty Conference 4ndash6 April 1995 Pittsburgh PA PittsburghAir and Waste Management Association 1995577ndash598

10 Kunzli N Kaiser R Medina S Studnicka M Chanel O

11 Filliger P Herry M Horak F Jr Puybonnieux-Texier V Quenel P et al Public-health impact of outdoor and traffic- related air pollution a European assessment Lancet 356795ndash801 (2000)

Bibliography

1 Sioutas C Delfino RJ Singh M Exposure assessment for atmospheric ultrafine particles (UFP) and implications in epidemiological research Environ Health Perspect 2005113947ndash955

2 Mosleh M Blau PJ Dumitrescu D (2004) Characteristics and morphology of wear particles from laboratory testing of disc brake materials Wear 2561128ndash1134

3 Kuumlnzli N et al (2000) Public-health impact of outdoor and traffi c-related air pollution a European assessment Lancet 356(9232)795ndash801

4 Dora C Phillips M eds (2000) Transport environment and health Copenhagen WHO Regional Office for Europe (WHO Regional Publications European Series No 89 httpwwweurowhointdocumente72015pdf accessed 26 November 2004)

5 Westerholm R Karl-Erik E Exhaust emissions from lightand

6 heavy-duty vehicles chemical composition impact of exhaust after treatment and fuel parameters Environ Health Perspect 102(suppl 4)13ndash23 (1994)

7 Fauser Tjell Mosbaek pigegaard Quantification of tire-Tread particles using extractable Organic Zinc as a Tracer Rubber Chemistry and Technology 1999 969Table shows some literature estimates of the contribution of tire wear to PM10 in air (Panko et al 2013) Gustafsson M Blomqvist G Gudmundsson A Dahl A Swietlicki E Bohgard M Lindbom J Ljungman A

8 Chen Y Shah N Huggins FE and Huffman GP (2006) Microanalysis of Ambient Particles from Lexington Ky by Electron Microscopy Atmos Environ 40 651ndash663

9 Donaldson K Tran CL Jimenez LA Duffin R Newby DE and Mills N (2005) Combustion-derived Nanoparticles A Review of Their Toxicology Following Inhalation Exposure Part Fibre Toxicol 2 10ndash23

10 Su D Serafino A Muller JO Jentoft RE Schlogl R and Fiorito S (2008) Cytotoxicity and Inflammatory Potential of Soot Particles of Low-emission Diesel Engines Environ Sci Technol 42 1761ndash1765

11 Maier KL Alessandrini F Beck-Speier I Hofer TPJ Diabatґe S Bitterle E Stoger T and Jakob T (2008) Health Effects of Ambient Particulate Matter-Biological Mechanisms and Inflammatory Responses to in Vitroand in Vivo Particle Exposures Inhalation Toxicol 20 319ndash337

Page 7: Studies of Air Pollutants and their Impact on Respiratory and ...€¦ · Ascarate Park C37 Monitoring Station: The National Ambient Air Quality Standard (NAAQS) for PM 10 and 2.5

Problem Statement

0

100

200

300

400

500

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31

PM

10 (

μg

m3)

Days

Chamizal C 41

Montly 24 Hours Average

PM-10 measured in micrograms per cubic meter (μgm3)

2006 January

February

March

April

May

June

July

August

September

October

November

The National Ambient Air Quality Standard (NAAQS) for PM was Exceeded in The PdN Region during

2006 2010 Analysis of Chamizal Area Zip Code 79905

These chart illustrates two high spikes that occurred which exceeds the 24 hour average

0

20

40

60

80

100

120

140

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31

PM

25

( μ

gm

3)

Days

Chamizal C 41

Montly 24 Hours Average

PM-25 measured in micrograms per cubic meter (μgm3)

2006 january

February

March

April

May

June

July

August

September

October

November

December

Chamizal C41Monitoring Station The National Ambient Air Quality Standard (NAAQS) for PM 10 and 25 was

exceeded but in 24 hour average The NAAQS for PM 25 for 24-hour average is PM2535 microgmsup3 and PM10 50-

100 microgmsup3 The highest concentration occurred several times PM10(150200300450 microgmsup3)

PM25(4050607080120 microgmsup3 )

Problem Statement

0

100

200

300

400

500

600

700

800

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31

PM

10 (

μg

m3)

Days

Ascarate Park SE C37

Montly 24 Hours Avg PM 10 Exceedences and Maximum

Concentrations 2010 January

February

March

April

May

June

July

August

September

October

November

December

Graph 1 Source TCEQ ( Texas Commission on Environmental Quality) Ascarate Park monitoring station Data 2010

0

20

40

60

80

100

120

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31

PM

25

UG

M3

DAYS

Ascarate Park SE C37

Montly 24 Hours Average

PM-25 measured in micrograms per cubic meter

(μgm3)

2010 JanuaryFebruaryMarchAprilMayJuneJulyAugustSeptemberOctoberNovemberDecember

Graph 2 Source TCEQ ( Texas Commission on Environmental Quality) Ascarate Park monitoring station Data 2010

Ascarate Park C37 Monitoring Station The National Ambient Air Quality Standard (NAAQS) for PM

10 and 25 was exceeded but in 24 hour average The NAAQS for PM 25 for 24-hour average is

PM2535 microgmsup3 and PM10 50-100 microgmsup3 The highest concentration occurred several times

PM10(200250300400600720 microgmsup3) PM25(4090120microgmsup3)

The National Ambient Air Quality Standard (NAAQS) for PM was Exceeded in The PdN Region 2006 2010

Analysis of Ascarate Area Zip Code 79905

These chart is to illustrate there are two high spikes that occurred which exceeds the 24 hour average

Fig Number of registered automobiles in Texas The Statistics show the

number of registered automobiles truck motorcycle in Texas Source

Texas department motor vehicles

Fig More than 61 percent of

US transportation emissionscome from cars and lighttrucks

Fig in US On-roadmobile sourcesconstitute the largestsingle source categoryof air pollution with(327)

Problem Statement

13000000140000001500000016000000170000001800000019000000

Millio

ns

of

Ve

hic

les

Years

Total Growth of Texas Registrations

2001-2012

Total

Vehicles

Registratio

ns

Problem Statement

El Paso Texas and ciudad Juarez currently has commercialmovements through El PasondashCiudad Juarez gateways peaked at715000 trucks in the year 2010 and Approximately 40000 vehicles passthese roads each laborable day

Source US Department of Transportation Bureau of Transportation Statistics 2010

Bridge Number of US-bound

Truck Crossings year 2010

World Trade Bridge 1327479

Pharr ndash Reynosa International Bridge

452821

Ysleta ndash Zaragoza Bridge 379508

Laredo ndash Colombia Solidarity

Bridge

374781

Bridge of the Americas 337609

Veterans International Bridge 177986

Camino Real International Bridge 106423

Del Rio ndash Ciudad Acuna

International Bridge

62966

Progreso International Bridge 42605

Free Trade Bridge 30773

Source CBP

Fig Bridge of the Americas (Puente Cordova)

Publications Review to examine the relationship between exposure to motor vehicle emissions and respiratory and cardiovascular disease

We have analyzed the current literature which have served as the basis for this project

Some studies determined that traffic-related emissions have been recognized as a major contributor to urban air pollution in particular major cities proximity to major roadways and exposure to motor vehicle exhaust and Non-exhaust emissions are associated with increased risks of cardiovascular respiratory and other diseases (Brugge et al 2007 Gan et al 2010 Gauderman et al 2007 Jerrett et al 2009 Laden et al 2007 McConnell et al 2006)

Effect of traffic pollution on respiratory and allergic disease in adults cross-sectional and longitudinal analyses Mar Pujades-Rodriacuteguez Tricia McKeever Sarah Lewis Duncan Whyatt John Britton and Andrea Venn

httpwwwsciencedailycomreleases200811081114081003htm April 2011

Traffic Pollution Increases Asthma in Adults Several research results revealed adults who suffer asthma and were exposed to heavy traffic pollution experienced an 80 per cent increase University of Melbourne Rev Public Health 15 (1994) pp 107ndash132 August 2010

Traffic Pollution Aggravates Symptoms In Asthmatic Children Traffic pollution especially in cities adversely affects respiratory health in children with asthma studies suggest that traffic pollution and diesel particles in particular may have a greater effect on respiratory health than other pollutants httpwwwsciencedailycomreleases200811081114081003htm September 2010

Traffic-related air pollution associated with prevalence of asthma and COPDchronic bronchitis A cross-sectional study in Southern Sweden Anna Lindgren Emilie Stroh Peter Montneacutemery September 2009

Acute respiratory health effects of air pollution on children with asthma in US inner cities Benjamin Vaughn MS Meyer Kattan MD Herman Mitchell PhD May 2008

Comparison of Air QualityndashRelated Mortality Impacts of two Different source of emission Transportation in the United States httpwwwtrborgMainBlurbs166402aspx January 2008

Long-term exposure to traffic-related air pollution and cardiovascular mortality Chen H Goldberg MS Burnett RT Jerrett M Wheeler AJ Villeneuve PJ Source Department of Epidemiology and Biostatistics McGill University Montreal Quebec Canada January 2011

heavy-duty vehicles chemical composition impact of exhaust after treatment and fuel parameters Environ Health Perspect102(suppl 4)13ndash23 (1994)

Particulate Matter

PM is a mixture of solid and liquid particles suspended in the atmosphere

as atmospheric aerosols Mobile Pollutants are formed by chemical

reactions of gaseous components from burning of fossil fuel in vehicles

(Gasoline amp diesel motor vehicles)

Source EPA (2012) United States Environmental Protection Agency

Particulate matter basic information Cited October 30th 2012 Available

online at httpwwwepa govairqualityparticlepollutionbasichtml

Source EPA (2012) United States Environmental Protection Agency Particulate matter basic

information Cited October 30th 2012 Available online at httpwwwepa

govairqualityparticlepollutionbasichtml

PM10 25 Long Term Exposure ndashChronic Health Consequences

These particles are associated with a

variety of problems including

Aggravated asthma Chronic

bronchitis

Decreased lung function

Increased respiratory symptoms

coughing or difficulty breathing

Increased Cardiopulmonary Mortality

Increased Risk of Lung Cancer

Sources of Particulate Matter Emissions from traffic

Diesel exhaust particulate matter

This particulate toxic potential has been associated with serious adverse Health

effects including respiratory symptoms Pulmonary function and cardiovascular

diseases (Geller et al 2006 Bernstein et al 2004)

Brake wear particulate matter

Brake wear particulate matter Chemical content (iron(Fe) copper(Cu) Antimony(Sb) barium(Ba) this type of particulate can cause severe respiratory and cardiovascular damages and it is also known that Sb has been classified as a possible human pulmonary carcinogen by the International Agency for Research on Cancer (IARC 1989 Et al 2013)

Fig images of brake wear particles generated at a road simulation study ( centre lt25 μm right lt10

μm) Source [Kukutschovaacute et al 2011]

Tire wear particulate matter

The tire wear particles of the tires are generated either by frictional forces between the treadand the road pavement The chemical content Fe Cr Pb Ti Cr Cu Zn Sr Y Zr Sn Sb Ba LaCe and Pb)

Fig Examples of near spherical particles PM 10 and 25 which are originate from interaction of tires and pavements Source [Dahl et al 2006]

Study Area

The Paso del Norte (PdN) region Selected two strategic areas of study El Paso County zip code 79905 Urban area and Dona Ana County Zip Code 880218802788072 Rural Restricted urban access (freeways and interstates)

Map of the area of the simulation by the MOVES model in the study area

Geographic Domain Zip Code 79905 Urban Area (El Paso County)

Zip Codes 88021880278807288048 (Dona Ana County)

Urban road Delta Dr St 31o 45rsquo 5637- 106o 27rsquo 1212 10 miles

Cordova Bridge of the Americas 31o 45rsquo 4367- 106o 27rsquo 0506 15 miles

478 Highway interstate 31o 46rsquo 1326- 106o 27rsquo 0327 05 miles

110 Highway interstate 31o 46rsquo 1210- 106o 27rsquo 0066 10 miles

10 Interstate Gateway Blvd 31o 46rsquo 397- 106o 26rsquo 4769 05 miles

Chamizal Loop 478 31o 46rsquo 668- 106o 26rsquo 5456 05 miles

Alameda Loop 20 31o 46rsquo 1323- 106o 27rsquo 0328 10 miles

Paisano Dr St Patriot freeway

route 62

31o 46rsquo 0669- 106o 27rsquo 212 15 miles

St Piedras 31o 46rsquo 1326- 106o 27rsquo 0327 10 miles

Dona Ana County Miles

Interstate 25 32o 23rsquo 0561 -106 48

1054 32o 23rsquo 3434- -

106 48 1054 32o 23rsquo

5660 106 48 4314

50

Geographic domain To obtain the simulation mobile data from modelMOVES2010a was configurated the coordinates selected in the study areas

El Paso County

PM25 Estimation from Aerosol Optical Depth (AOD) using

satellites

We examined the relationship

between Aerosol Optical Depth

(AOD) estimated from satellite data

at 5 km spatial resolution and the

mass of fine particles le25 μm in

aerodynamic diameter (PM25)

monitored on the ground in El PdN

area PM25 data was recorded from

air quality monitoring Chamizal

station (TCEQ) on different periods

Our analysis shows a significant

positive association between AOD

and PM25

Time-series and scatter plots of AOD estimated PM25 and surface PM25

Analysis of the meteorological factors and synoptic conditions leading to a local high

ozone event episode June 12-21 2006

Meteorology plays a critical role in determining atmospheric ozone concentrations A good synoptic scale weather forecast is essential to accurately forecast tropospheric and surface ozone concentrations

Figure 1 The domain configuration and Landuse categories

resolution 25 km domainFigure 2 The Geopotential height at 500 mb Figure 3 depicts the 850 mb at a lower altitude The

white regions observed in the graph correspond to

mountainous areas

Figure 4 Temperature at 2m height

above surface at 22 UTC June 18 2006

36 km resolution

Performance Evaluation

01020304050

Ju

ne

137

130

0

190

0

10

0

Ju

ne

157

130

0

190

0

10

0

Ju

ne

187

130

0

190

0

10

0

Tem

pe

ratu

re (⁰C

)

Local time (Hrs)

C41 June 13-19 2006

WRF_temperature

(⁰C)

TCEQ_temperature

(⁰C)

01020304050

June1

37

100

0

130

0

160

0

190

0

220

0

10

0

40

0

June1

57

100

0

130

0

160

0

190

0

220

0

10

0

40

0

June1

87

100

0

130

0

160

0

190

0

220

0

10

0

40

0

Rel

ativ

e h

um

idit

y (

)

Local time (Hrs)

C41 June 13-19 2006

WRF_rh () TCEQ_relative humidity ()

0

5

10

15

20

June

137 10

13

16

19

22 1 4

June

157 10

13

16

19

22 1 4

June

187 10

13

16

19

22 1 4

Win

d s

pee

d (

ms

Local time(Hrs)

C12 June 13-192006

WRF_wind speed (ms) TCEQ_ wind speed (ms)

We evaluate the WRF modelrsquos performance

by comparing against corresponding

experimental TCEQ data and performing the

required statistical analysis

HYSPLIT Model

HYSPLIT was simulated and showed that the ozone is mostly transported to El Paso from north western and south western US and Mexican regions during the 72 hours duration of the simulation

0

20

40

60

80

100

1200

00

10

02

00

30

04

00

50

06

00

70

08

00

90

01

00

01

10

01

20

01

30

01

40

01

50

01

60

01

70

01

80

01

90

02

00

02

10

02

20

02

30

0

Ho

url

y o

zon

e [

pp

b]

0102030405060708090

00

01

00

20

03

00

40

05

00

60

07

00

80

09

00

10

00

11

00

12

00

13

00

14

00

15

00

16

00

17

00

18

00

19

00

20

00

21

00

22

00

23

00

Ho

url

y o

zon

e [

pp

b]

June 18th June 19th

Performance Evaluation

01020304050

Ju

ne

137

130

0

190

0

10

0

Ju

ne

157

130

0

190

0

10

0

Ju

ne

187

130

0

190

0

10

0

Tem

pe

ratu

re (⁰C

)

Local time (Hrs)

C41 June 13-19 2006

WRF_temperature

(⁰C)

TCEQ_temperature

(⁰C)

0

50

100

150

June1

37

100

0

130

0

160

0

190

0

220

0

10

0

40

0

June1

57

100

0

130

0

160

0

190

0

220

0

10

0

40

0

June1

87

100

0

130

0

160

0

190

0

220

0

10

0

40

0Ozo

ne

(pp

b)

Local time (Hrs)

C41 June 13-19 2006

CAMx_ozone (ppbV) TCEQ_ozone (ppb)

0

10

20

30

40

50

June1

37

100

0

130

0

160

0

190

0

220

0

10

0

40

0

June1

57

100

0

130

0

160

0

190

0

220

0

10

0

40

0

June1

87

100

0

130

0

160

0

190

0

220

0

10

0

40

0

Rel

ativ

e h

um

idit

y (

)

Local time (Hrs)

C41 June 13-19 2006

WRF_rh () TCEQ_relative humidity ()

0

5

10

15

20

June

137 10

13

16

19

22 1 4

June

157 10

13

16

19

22 1 4

June

187 10

13

16

19

22 1 4W

ind

sp

eed

(m

sLocal time(Hrs)

C12 June 13-192006

WRF_wind speed (ms) TCEQ_ wind speed (ms)

Methodology

Medical Data The data by weekly monthly and year for daily emergency room and hospital admission for the respiratory

infections (RD) and cardiovascular diseases (CVD) was extracted from hospitals records located in the El PdN

the system includes data on type of admission primary and secondary causes of admissionRESPIRATORY DISEASE

Bronquitis amp Chronic Bronchitis 466 - 4661 491 - 4919

Asthma 463 - 4939

Emphysema 492

Respiratory failure 51881

HEART DISEASE

Accute Myocardial Infarction 410

Coronary Athersclerosis 4140

Other Ischemic Heart Disease 411-4139 4141-4149

Cardiac Dyshythmias 427

Essential hypertension 401

Acute myocardial infarction 410

Congestive Heart Failure 4280 4282-4284

Hypertensive heart disease 402

Table 1 ICD -9 Codes for Respiratory and Cardiovascular Diseases

0

50

100

150

200

250

300

Wee

k 1

Wee

k 2

Wee

k 3

Wee

k 4

Wee

k 5

Wee

k 6

Wee

k 7

Wee

k 8

Wee

k 9

Wee

k 1

0

Wee

k 1

1

Wee

k 1

2

Wee

k 1

3

Wee

k 1

4

Wee

k 1

5

Wee

k 1

6

Wee

k 1

7

Wee

k 1

8

Wee

k 1

9

Wee

k 2

0

Wee

k 2

1

Mo

rb

idit

y D

isch

arg

e fo

r a

ll R

esp

ira

tory

Dis

ease

IC

D-9

(

Ast

hm

aB

ro

nch

itis

)

Weekly Morbidity Discharges of all the Listed Diagnoses for All

Respiratory Disease During WinterSpring 2010

Asthma-Bronchitis

EPA MOVES Model for Estimating Emission

Inventories

Motor Vehicle Emission Simulator (MOVES 2010b) will be configuredin The El Paso North Region for Calculate five categories of PM10

PM25 total Emission inventories from all on-road traffic over a

variety of scales within periods of time selected weeks months

and years

Moves (Motor Vehicle Emission

Simulator)

The emission model is develop using the current equation to calculate direct traffic emissions from

vehicles in the form of PM is

Eext annual emissions are measured in grams of miles traveled by the vehicle (gVMT )

SL is the road surface loading in (gm2)

W is the average weight in tons of the vehicles on the road

K is the particle size multiplier for particle size range (eg gVMT for PM10 when using grams and miles)

P is the 7 number of wet days with at least 0254 mm of precipitation during the averaging period

N is the number of years considered in the averaging period

C is the particle size specific emissions factor in units of interest vehicle direct exhaust brake wear and tirewear

Modeling Simulation Domain and Emissions Scenarios

For simulations of mobile air quality emission inventories a motor vehicle emission simulator EPA (MOVES 2014a) was used

The modeling use input factors divided into seven section

parameters

On-Road Inventory local data

input

Scale

Geographic Bounds

Traffic intensity

Vehicle Type

Pollutants

Road Type

Fuel Types

Figure Source EPA US Environmental Protection Agency 2012- Moves 2010b Model

EPA Moves 2014a The modeling used input factors divided into six section

parameters On-Road Inventory local data input

Geographic Domains CountyNonattainment Area

Vehicle-Miles Traveled (VMT) is the total number of miles driven by all vehicles withina given time period and geographic area

Average speed range from 25 miles per

hour to 65 miles per hour

Vehicle Classes Motorcycle PassengerCarTruks light-duty Commercial Truck(6001-8500 lbs) Buses heave-duty trucksRefuse trucks School Bus Single UnitShort Haul-truck Single Unit Long Haul-truck Long Haul Truck Heavy-DutyVehicles (26001-33000 lbs)

Pollutants

Road TypeRural restricted Acces(Freeways and interstates) Rural and Restricted Acces Urban Restricted Acces Off-Network

Fuel Types Gasoline Diesel Fuel

Specific Road Types

Two road types for running emission from the MOVES can be

selected

(freeways and interstates)

Interior urban Urban

Figure Source EPA US Environmental Protection Agency 2012- Moves 2010b Model

VehiclesEquipment

This panel show which on-road vehicles will be modeled

Figure Source EPA US Environmental Protection Agency 2012- Moves 2010b Model

Long haul truck Short haul truck Inercity bus Ligth comercial truck

Passenger car Passenger truck Refuse truck

School bus Single unit long haul-truck

Single unit short haul-truck

Transit bus

Motor home

Motorcycle

Based on Department of Transportation Highway MOVES will Estimates Traffic

Emissions from Cars Trucks amp Motorcycles

Output Data Moves 2014a

Inventories of PM 10 25 Mobile Emission from all

on-Road Traffic

Exhaust Emission PM 10 25 gramsmile

Brake Wear Emission PM 10 25 gramsmile

Tire wear Emission PM 10 25 gramsmile

Date of Vehicle miles traveled (VMT) for

Day Week Month Year

Total Vehicle population

Vehicle age distribution

Simulation of Mobile Emission in the El PdN Region Zip Code 79905

Figure Total Emissions from road traffic in El Paso TX Area were estimated for PM10

Exhaust and Non exhaust emission in kilogramsmonth (Source EPA MOVES 2014a)

0

10000

20000

30000

40000

50000

PM

10 k

gM

on

th

Months

Monthly PM 10 Exhaust and Non-Exhaust Mobile Emissions 2010

On-Road Urban Restricted Area Zip Code 79905

Primary Exhaust PM 10 (kg) Primary PM 10 Brakewear (kg)

Primary PM 10 Tirewear (kg)

05000

100001500020000250003000035000400004500050000

PM

25

kg

Mo

nth

Months

Monthly PM 25 Exhaust and Non-Exhaust Mobile Emission 2010

On-Road Urban Restricted Area Zip Code 79905

Primary Exhaust PM 25 (kg) Primary PM 25 Brakewear (kg) Primary PM 25Tirewear (kg)

Figure Total Emissions from road traffic in El Paso TX Area were estimated for PM25

Exhaust and Non exhaust emission in kilogramsmonth (Source EPA MOVES 2014a)

Total Emissions from Road Traffic in El Paso County PM1025 Exhaust and Non exhaust Emission in kilogramsmonth

Taking the interests to the health risks related to PM 1025 mobile emission were simulated

Exhaust and Non-exhaust emissions contribute almost equally to total traffic-related PM1025 Emissions (Querol et al 2004 Bukowiecki et al 2009a Amato et al 2011)

Monthly PM 10 25 Exhaust and Non-Exhaust (BrakewearTirewear) Mobile

Emission 2010 On-Road Urban Restricted Area Zip Code 79905

Figure Total Emissions from road traffic in El Paso TX Area were estimated for PM10 25 Exhaust and Non Exhaust mobile

emission in kilograms per month (Source EPA MOVES)

0

10000

20000

30000

40000

50000

January February March April May June July August September October November December

PM

10

25

(K

ilog

ram

s)

Months

Summary- Monthly PM 10 25 Exhaust and Non-Exhaust Mobile

Emission 2010 On-Road Urban Restricted Area Zip Code 79905

Primary Exhaust PM 10 Primary PM 10 Brakewear Primary PM 10 Tirewear

Primary Exhaust PM 25 Primary PM 25 Brakewear Primary PM 25Tirewear

Exhaust Emissions PM1025 is reaching maximum emission 48000-42000 thousand of Kgmonth followedby Brake wear 29000-5000 thousand kgmonth and Tire wear with 9000-2000 kgmonth The results showthat the emissions of PM derived mainly from Exhaust and Brake are significantly higher in Urban Area

Annual Contribution of Mobile Emission PM 1025 (Kg) Zip Code 79905 El

Paso County 2010

Total Primary

Exhaust _PM10

39

Total Primary

Exhaust _PM25

36

Brakewear

particulate_PM10

18

Tirewear

particulate_PM10

4

Brakewear

particulate_PM25

2

Tirewear

particulate_PM25

1

0

5

10

15

20

25

30

35

40

45

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53

Fig Annual Average PM10 Concentrations at the

Chamizal C41 Station and PM1025 mobile

Concentration Zip code 79905

PM10 TCEQ (μgm3) Total Mobile Emission PM10 (Ugm3)

Fig Exhaust Emission is Contributing Approximately 74 of total

PM1025 Mobile Emissions following of Brake wear with 20 and Tire

wear with 5

Annual Average PM1025 ugm3 Mobile Emissions (Moves) 26 Chamizal C41

Monitoring Station (TCEQ Chamizal Station )

Predicting Mobile Emission and VTM

Estimation The PdN Region 2010

44E+09

46E+09

48E+09

5E+09

52E+09

54E+09

56E+09

58E+09

6E+09

62E+09

0

50000

100000

150000

200000

250000

300000

350000

20

10

20

11

20

12

20

13

20

14

20

15

20

16

20

17

20

18

20

21

20

22

20

23

20

24

20

25

20

26

20

27

20

28

20

29

20

30

EX

HA

US

T

EM

ISS

ION

MO

BIL

E (

KG

YE

AR

)

YEARS

Predict ing Mobile Exhaust Emission and VTM

Estimation

2010 - 2030 e l PdN Area

Total_ Exhaust PM10 Total_ Exhaust PM25 Distance (Miles)

Fig Predicting Mobile Exhaust PM1025 (kgMonth) Emission and VTM Estimation 2010

- 2030 el PdN Area

44E+09

46E+09

48E+09

5E+09

52E+09

54E+09

56E+09

58E+09

6E+09

62E+09

0

5000000

10000000

15000000

20000000

25000000

30000000

20

10

20

11

20

12

20

13

20

14

20

15

20

16

20

17

20

18

20

21

20

22

20

23

20

24

20

25

20

26

20

27

20

28

20

29

20

30

EX

HA

US

T

EM

ISS

ION

MO

BIL

E (

KG

YE

AR

)

YEARS

Predict ing Mobile Exhaust Emission and

VTM Estimation

2010 - 2030 e l PdN Area

CO NO2 NO NOx Distance

Fig Predicting Mobile Exhaust Emission and VTM Estimation

2010 - 2030 el PdN Area in El Paso TX Area were estimated for

Total CO NOx NO2 NO emission in kilograms per year

(Source EPA MOVES 2014a model)

The simulated Exhaust emissions in the future years shows a trend of reduction of this type of emissions in the

future years one factor should be the new hybrid technology is increasing by 476 since 2010 to 2015 and

use of catalytic converters diesel particulate filters and improved fuels and engines Non-exhaustive sources

will increase in the coming years because there is no control in the material of manufacture composed by Fe

Cu and Mn also not to be able to reduce the number of events of braking (Accelerations and decelerations)

45E+09

5E+09

55E+09

6E+09

65E+09

0

50000

100000

150000

200000

250000

201

0

201

1

201

2

201

3

201

4

201

5

201

6

201

7

201

8

202

1

202

2

202

3

202

4

202

5

202

6

202

7

202

8

202

9

203

0

NO

N-

EX

HA

US

T

EM

ISS

ION

MO

BIL

E

(KG

YE

AR

)

YEARS

Predicting Non Exhaust Mobile

Emission and VTM Estimation

2010 - 2030 el PdN Area

Brake_PM10 Tire_PM10 Distance (Miles)

Fig Predicting Mobile Exhaust PM1025 (kgMonth) Emission and VTM

Estimation 2010 - 2030 el PdN Area

Daily Avg PM1025

Levels of PM Mobile Emission Non-Exhaust -Rush Hour Periods Fall 2010 Zip Code

79905

00

100

200

300

400

500

600

Mo

bil

e P

M1

0 (k

g)

Rush Hours

Daily Avg PM10

Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush Hours

Periods 2010 Zip Code 79905

Total Primary Exhaust

_PM10 WinterSpring

Brakewear

particulate_PM10

WinterSpringTirewear particulate_PM10

WinterSpring

Total Primary Exhaust

_PM10 Summer

Brakewear

particulate_PM10 Summer

Tirewear Particulate_PM10

Summer

Total Primary Exhaust

_PM10 Fall

Brakewear

particulate_PM10 Fall

Tirewear particulate_PM10

Fall

00

50

100

150

200

250

300

350

Mo

bil

e P

M2

5 (k

g)

Rush hours

Daily Avg PM25

Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush

Hours Periods 2010 Zip Code 79905

Total Primary Exhaust _PM25

WinterSpring

Brakewear Particulate_PM25

WinterSpring

Tirewear particulate_PM25

WinterSpring

Total Primary Exhaust _PM25

Summer

Brakewear particulate_PM25

Summer

Tirewear particulate_PM25

Summer

Total Primary Exhaust _PM25

Fall

Brakewear particulate_PM25

Fall

Tirewear particulate_PM25

Fall

Figure Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush Hours Figure Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush Hours

GIS EMISSIONS INVENTORY SYSTEM A geographic information system (GIS) was used to established geographic scenarios with processed images of seasonal mobile

emissions in the PdN region Seasonal mapping is visualized for different types of pollutants Brakewear Exhaust and Tyrewear

Fg Graphics of GIS and Seasonal mobile Emission of particulate matter emission inventory Seasonal emission simulations were performed in kilograms and five contributing inputs factors were identified for

modeling 1) On the composition of the particulate material from different sources such as Exhaust and Non exhaust (Brake wear Tirewear) 2) The Vehicles Equipment clasification were selected according to

the use of gasoline and diesel fuel (motorcycle passenger car Light Duty Vehicles Trucks refuse truck Light Duty Vehicles Light Commercial Truck Light Duty Vehicles School Bus)

Winter Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

120354 67860 19065

Spring Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

139767 86702 24463

Summer Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

94747 62481 17630

Fall Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

75510 45542 12596

251 Descriptive Statistics Data Analysis

Weekly Correlation Analysis of Mobile Emission PM10 (Exhaust-Non-Exhaust) and Respiratory

Diagnoses WinterSpring Summer and Fall 2010

0

2

4

6

8

10

0

50

100

150

200

250

300

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21

Mo

rbid

ity

Dis

ch

arg

e

for

all R

esp

ira

tory

Dis

ea

se

ICD

-9

(A

sth

ma

-Bro

nc

hitis

)

WinterSpring Week

Weekly Avg Mobile PM10 Concentrations during

WinterSpring 2010 and its Influence on Respiratory

Diagnoses

Zip Code 79905

Total Medical data ZIP Code 79902

Total Mobile Emission PM10 (Ugm3)

0

1

2

3

4

5

6

7

0

20

40

60

80

100

Mo

rbid

ity

Dis

ch

arg

e

for

all R

esp

ira

tory

Dis

ea

se

ICD

-9

(Ast

hm

aB

ron

ch

itis

)

Weekly Avg Mobile PM10 Concentrations during

Summer 2010 and its Influence on Respiratory

Diagnoses

Summer 2010 Zip Code 79905

Total Mobile Emission PM10

Hospital Admission (Asthma-Bronchitis)

0

2

4

6

8

10

12

0

20

40

60

80

100

120

140

160

180

200

Mo

rbid

ity

dis

ch

arg

es

for

all r

esp

ira

tory

dis

ea

se

Weekly Avg Mobile PM10 Concentrations

during Fall 2010 and its Influence on Respiratory

Diagnoses

Zip Code 79905

Total Medical data ZIP Code 79902

Total Mobile Emission PM10 (Ugm3)

Mobile(Exhaust-Non-

Exhaust) PM10 and

Asthma-Bronchitis)

Linear R

Square

WinterSpring 734 ndash 39

Summer 614 ndash 32

Fall 548 -29

PM10 Mobile emission (Exhaust-Non-Exhaust)contributed significantly

association to the incidence of RD

Weekly Correlation Analysis of PM 25 Mobile Emission (Exhaust-Non-Exhaust)

and Cardiovascular Diagnoses WinterSpring Summer and Fall 2010

0010203040

00500

100015002000

Wee

k 1

Wee

k 2

Wee

k 3

Wee

k 4

Wee

k 5

Wee

k 6

Wee

k 7

Wee

k 8

Wee

k 9

Wee

k 1

0

Wee

k 1

1

Wee

k 1

2

Wee

k 1

3

Wee

k 1

4

Wee

k 1

5

Wee

k 1

6

Wee

k 1

7

Wee

k 1

8

Wee

k 1

9

Wee

k 2

0

Wee

k 2

1

Morb

idit

y d

isch

arg

es f

or

all

card

iovasc

ula

r d

isea

se

Weekly Avg PM25 Mobile Concentrations during

WinterSpring 2010 and its Influence on all Heart

Diagnoses

Zip Code 79905

Total All Heart Disease PM 25 mobile (μgm3)

0010203040

00

500

1000

1500

Mo

rbid

ity

dis

ch

arg

es

for

all

ca

rdio

va

scu

lar

dis

ea

se

Weeks

CORRELATION BETWEEN MOBILE PM25 ugm3

EXPOSURE TO HEART DISEASES SYMPTOMS

SUMMER SEASON 2010

Total All Heart Disease PM 25 mobile (μgm3)

Figure Statistical Analyses of the Relationship Between PM25 Caused by Traffic Emission( 26 of total Emission) with Heart diseases Source Hospital Admissions for Asthma Acute Bronchitis and Heart diseases in El Paso County zip code 79905 from Texas Health Care

Information Council in Austin Texas (Texas Health Care Information Council 2000)

00

10

20

30

40

0

50

100

150

We

ek 3

6

We

ek 3

7

We

ek 3

8

We

ek 3

9

We

ek 4

0

We

ek 4

1

We

ek 4

2

We

ek 4

3

We

ek 4

4

We

ek 4

5

We

ek 4

6

We

ek 4

7

We

ek 4

8

We

ek 4

9

We

ek 5

0

We

ek 5

1

We

ek 5

2

We

ek 5

3

Mo

rbid

ity

dis

ch

arg

es

for

all

ca

rdio

va

scu

lar

dis

ea

se

CORRELATION BETWEEN MOBILE PM25 ugm3

EXPOSURE TO HEART DISEASES SYMPTOMS FALL

SEASON 2010

Total All Heart Disease PM 25 mobile (μgm3)

Mobile(Exhaust-

Non-Exhaust)

PM10 and

Asthma-

Bronchitis)

Linear R

Square

WinterSpring 833 -42

Summer 620 -32

Fall 501-26

PM10 Mobile

emission (Exhaust-

Non-

Exhaust)contribut

ed significantly

association to the

incidence of CVD

Diseases

Monthly Brake Mobile Emission PM1025 kg During year 2010 and its Influence on

Respiratory Diagnoses Zip Code 79905

00200040006000800010000

010000200003000040000

PM

10

Mo

bile

(K

g)

Months

Monthly Brake Mobile Emission PM10 kg during year

2010 and its Influence on Respiratory Diagnoses

Zip Code 79905

Primary PM 10

Brakewear 00100020003000400050006000

0

1000

2000

3000

4000

PM

25

Mo

bil

e(K

g)

Months

Monthly Brake Mobile Emission PM25 during

year 2010 and its Influence on Heart Diagnoses

Zip Code 79905

Primary PM 25

Brakewear

Heart Diseases

Hospital

Admission

Brake Mobile Emission

PM10 kg Asthma-

Bronchitis)

Brake Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=969 Linear Square R=856

Monthly Mobile Exhaust Emission PM1025 During year 2010 and its Influence on

Respiratory Diagnoses Zip Code 79905

0

200

400

600

800

1000

0

10000

20000

30000

40000

50000

1 3 5 7 9 11

PM

10

(K

g m

on

th)

Months

Monthly Mobile Exhaust Emission PM10 during

year 2010 and its Influence on Respiratory

Diagnoses

Zip Code 79905

Primary Exhaust

PM 10

Respiratory Disease

(Asthma

Bronchitis) Hospital

Admission

0

100

200

300

400

500

600

0

10000

20000

30000

40000

50000

1 2 3 4 5 6 7 8 9 101112

PM

25

(K

g m

on

th)

Months

Monthly Exhaust Mobile Emission PM25 during

year 2010 and its Influence on Heart Diagnoses

Zip Code 79905

Primary Exhaust PM

25

Heart Diseases

Hospital Admission

Exhaust Mobile Emission

PM10 kg Asthma-

Bronchitis)

Exhaust Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=929 Linear Square R=831

Monthly Tire wear Mobile Emission PM1025 During year 2010 and its Influence on Heart

Diagnoses Zip Code 79905

0

100

200

300

400

500

600

700

800

900

0

1000

2000

3000

4000

5000

6000

7000

8000

9000

1 2 3 4 5 6 7 8 9 10 11 12

PM

10

(K

g m

on

th)

Months

Monthly Tirewear Mobile Emission PM10 during year 2010

and its Influence on Heart Diagnoses

Zip Code 79905

Primary PM 10 Tirewear

Mobile Emission

Respiratory Disease

(Asthma Bronchitis)

Hospital Admission

0

100

200

300

400

500

600

0

200

400

600

800

1000

1200

1400

1 2 3 4 5 6 7 8 9 10 11 12

PM

25

(K

g m

on

th)

Months

Monthly Tirewear Mobile Emission PM25 during year 2010

and its Influence on Respiratory Diagnoses

Zip Code 79905

Primary PM 25Tirewear

Mobile Emission

Heart Diseases Hospital

Admission

Exhaust Mobile Emission

PM10 kg Asthma-

Bronchitis)

Exhaust Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=769 Linear Square R=715

Dona Ana County Zip Codes

88021880278807288048

Primary

Exhaust

PM 10 Zip

code

79905

Total

Primary

Exhaust

PM10

Dona Ana

Primary

Exhaust

PM 25 Zip

Code

79905

Total

Primary

Exhaust

PM25

Dona Ana

Series1 430378 111773 391915 102123

0

100000

200000

300000

400000

500000

AX

IS T

ITLE

Annual Comparison of the Mobile

Exhaust Emissions El Paso County

and Dona Ana 2010

Primary

PM 10

Brakewea

r Zip code

79905

Brakewea

r

particulat

e_PM10

Dona Ana

Primary

PM 10

Tirewear

Zip code

79905

Tirewear

particulat

e_PM10

Dona Ana

Series1 262585 48573 73754 11864

050000

100000150000200000250000300000

AX

IS T

ITLE

Annual Comparison of the Mobile

Brakewear Emissions El Paso County

and Dona Ana 2010

Figure Comparison of the Annual Mobile Emissions

of Primary PM10 Non-Exhauts (Brake ) from Dona

Ana County New Mexico and El Paso Texas Units

in KgMonth

Figure Comparison of the Annual Mobile Emissions

of Primary PM10-Exhauts Emission from Dona Ana

County New Mexico and El Paso Texas Units in

KgMonth

Primary

PM 25

Brakewe

ar Ziphellip

Brakewe

ar

particula

te_PMhellip

Primary

PM

25Tirewe

ar Ziphellip

Tirewear

particula

te_PM25

Donahellip

Series1 32645 6071 10919 1779

0

10000

20000

30000

40000

AX

IS T

ITLE

Annual Comparison of the

Mobile Exhaust Emissions El Paso

County and Dona Ana 2010

Figure Comparison of the Annual Mobile Emissions

of Primary PM10-Exhauts Emission from Dona Ana

County New Mexico and El Paso Texas Units in

KgMonth

Monthly Mobile Emission PM1025 kg During year 2006

and its Influence on Respiratory Diagnoses Dona Ana

County Zip Code 880218802788072

0

100

200

300

0

5000

10000

15000

Axi

s Ti

tle

Axis Title

Monthly Mobile Exhaust Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Total PrimaryMobile Exhaust_PM10

All Respiratory ICD-9 (AsthmaBronchitis)

050100150200250300

010002000300040005000

Axi

s Ti

tle

Axis Title

Monthly Mobile Brake Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Brakewearparticulate_PM10

All RespiratoryICD -9 (AsthmaBronchitis)

050100150200250300

0200400600800

10001200

Axi

s Ti

tle

Axis Title

Monthly Mobile Tirewear Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Tirewearparticulate_PM10

All Respiratory ICD -9 (AsthmaBronchitis)

Mobile Exhauts

Emission PM10

kg Asthma-

Bronchitis)

Brake Mobile

Emission PM10

kg and Heart

Diagnoses

Tirewear Mobile

Emission PM10

kg and Heart

Diagnoses

Linear Square

R= 951

Linear Square

R=625

Linear Square

R=525

Mobile Exhauts

Emission PM25

kg Asthma-

Bronchitis)

Brake Mobile

Emission PM25

kg and Heart

Diagnoses

Tirewear Mobile

Emission PM25

kg and Heart

Diagnoses

Linear Square

R= 986

Linear Square

R=691

Linear Square

R=601

Results

The results showed that mobile PM emissions in the urban areas close to urban Road and highways is putting at risk public health

and the proportion of diseases attributable to this exposure is potentially large

Brake wear emissions is much lower in freeways due to significantly reduced number of braking events while tire wear is much

higher in areas where studded tires are used The emission of exhaust gases are much higher in areas where there is a high

vehicular traffic

Brake Mobile

Emission PM10 kg

Asthma-Bronchitis)

Brake Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square

R=969

Linear Square

R=856

Exhaust Mobile

Emission PM10 kg

Asthma-Bronchitis)

Exhaust Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square

R=929

Linear Square

R=831

Tirewear Mobile

Emission PM10 kg

Asthma-Bronchitis)

Tirewear Mobile

Emission PM25 kg

and Heart Diagnoses

Linear Square R=769 Linear Square R=715

Brake Mobile

Emission PM10 kg

and Heart

Diagnoses

Brake Mobile

Emission PM25 kg

and Heart

Diagnoses

Exhaust Mobile

Emission PM10 kg

Asthma-Bronchitis)

Linear Square

R=625

Linear Square

R=691

Linear Square R=

951

Exhaust Mobile

Emission PM25 kg

Asthma-

Bronchitis)

Tire wear Mobile

Emission PM10 kg and

Heart Diagnoses

Tirewear Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square R=

986

Linear Square R=525 Linear Square

R=601

El Paso County

Dona Ana

County

BenMAP-CE

In this analysis the Program of Mapping and Analysis of Environmental Benefits-Community Edition

(BenMAP-CE) was used to Estimate the number and economic value of health impacts resulting from changes

in air pollution PM 25 Ugm3 in The El Paso Area

Health and Economic Benefits associated with the Response of PM25 Emission between

Base Year 2010

Number of Mortalities in 2010 Base Year Based on El Paso County Texas Department of State Health Services

Number of Mortalities in 2010 Base Year Based on El Paso County Texas

Department of State Health Services

cause of death

year

2010

Populatio

n

Affected

Backgro

und

Concentr

ation Pollutant

Rollback

Type

Avoided

Deaths

(

Populatio

n)

alzheimers disease 2010 40716 125 PM25

25

microgmAcircsup3

Rollback 9

diseases of the

heart 2010 15834 125 PM25

25

microgmAcircsup3

Rollback 35

influenza and

neumonia 2010 81432 125 PM25

25

microgmAcircsup3

Rollback 18

acute bronchitis

and bronchiolitis 2010 117624 125 PM25

25

microgmAcircsup3

Rollback 26

chronic lower

respiratory diseases 2010 54288 125 PM25

25

microgmAcircsup3

Rollback 12

The Basin-wide decrease in 4 ugm3 PM25 concentration after this

reduction control

Cause of death year 2010

Populatio

n

Affected

Background

Concentrati

on

Reduc

cion

scena

rio Polluta

nt

Rollback

Type

Avoi

ded

Deat

hs

(

Pop

ulati

on)

economic

benefits

analysis $

Alzheimers

disease 2010 121 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 9 12000

Diseases of the

heart 2010 470 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 35 35000

Influenza and

neumonia 2010 242 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 18 42500

Acute bronchitis

and bronchiolitis 2010 349 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 26 95000

Chronic lower

respiratory

diseases 2010 161 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 12 4500

$1 295000

PM25-related Mortalities Based on BenMAP-CE Estimate in 2010 Base Year with change in the concentrations levels

Health and Economic Benefits associated with the Response of PM25 Emission between

Base Year 2010 Increasing 7 Ugm3

Cause of death year 2010

Population

Affected

Deaths

avoided by

attaining 195

μgm3

standard

Background

Concentrati

on

Pollut

ant

Rollback

Type

Avoided

Deaths (

Populatio

n)

econo

mic

Unben

efits

analysi

s

Alzheimers

disease 2010 4524 195 PM25

25

microgmAcircsup3

Rollback 19 150000

Diseases of the

heart 2010 20358 195 PM25

25

microgmAcircsup3

Rollback 135 450000

Influenza and

neumonia 2010 126672 195 PM25

25

microgmAcircsup3

Rollback 38 525000

Acute bronchitis

and bronchiolitis 2010 162864 195 PM25

25

microgmAcircsup3

Rollback 36 122000

Chronic lower

respiratory

diseases 2010 99528 195 PM25

25

microgmAcircsup3

Rollback 12 650000

Conclusions

An excellent Pearson Correlation was established to analyze the relationship in the relative risks of hospitalization of Respiratory(RD) and cardiovascular (CVD) associated with ambient exposure caused by traffic emission in relation to their size andspecific sources of emission on different scenarios interior a border Urban Rural Urban restricted access (freeways andinterstates)

A significant correlation of PM1025 exposure from mobile emission and hospital admissions for selected Respiratory (RD) andcardiovascular (CVD) diagnoses was established The results showed that PM emissions in urban restricted access (freeways andinterstates) is mainly caused by traffic Therefore people living close to highways are more exposed higher vehicular emissions

Conclusions

We found statistically significant associations between mobile PM25 caused by traffic emission with Respiratory and Cardiovascular Diseases in the study areaSubsequently a correlation between cardio-respiratory mortality is established

A significant correlation of PM1025 exposure from mobile emission and hospital admissions for selected Respiratory (RD) and cardiovascular (CVD) diagnoses isestablished The results showed that PM emissions in urban restricted access (freeways and interstates) is mainly caused by traffic Therefore people living close tohighways receive higher vehicular emissions

The table shows the percentage of PM mobile exposure in the analyzed areas contributing to increase the risk of Respiratory and Cardiovascular Diseases

An examination was conducted of the synoptic and local meteorology for the June 2006 ozone episode using the WRF model to determine how meteorological parametersinfluence the formation transport and dispersion of ozone in the PdN The predominant synoptic feature of the ozone event day was the expansion intensification and slowprogression of an upper-level ridge of high pressure The high ozone episodes are associated with highly stable atmospheres strong temperature inversions with low mixingheights and therefore low mixing volumes Under these conditions emissions such as NOx lead to highly polluted conditions that favor ozone formation

BenMAP Conclusions

We have estimated the number and economic value of health impacts resulting

from changes in air pollution concentrations of PM 25 in the PdN region

Reduction of Pm 25 4 UGm3= Avoided 213 cases respiratory cardiovascular

diseses and Economic Benefits associated with the Response of PM25 Emission + $

1295000

Increase of PM25 7 ugm3 = increasing Dies= 326 economic Unbenefits= 2345000$

Bibliography

1 Dockery DW Pope CAI Xu X Spengler JD Ware JH Fay ME Ferris BG Speizer FE An association between air pollution and mortality in six US cities N Engl J Med 3291753ndash1759 (1993)

2 Samet JM Dominici F Curriero FC Coursac I Zeger SL Fine particulate air pollution and mortality in 20 US cities 1987ndash1994 N Engl J Med 3431742ndash1749 (2000)

3 Nel AE Diaz-Sanchez D Li N The role of particulate pollutants in pulmonary inflammation and asthma evidence for the involvement of organic chemicals and oxidative stress Curr Opin Pulm Med 20017 20ndash26

4 Westerholm R Karl-Erik E Exhaust emissions from lightand heavy-duty vehicles chemical composition impact of exhaust after treatment and fuel parameters Environ Health Perspect 102(suppl 4)13ndash23 (1994)

5 Bascom R Bromberg P Costa D Delvin R Dockery D Frampton M Lambert W Samet J Speizer F Utell

6 Health effects of outdoor air pollution Am J Respir Crit Care Med 1533ndash50 (1996)

7 Chow JC Watson JG Frazier CA Egami RT Goodrich A Ralph C Spatial and temporal source contributions to

8 PM10 and PM25 in Reno NV In PM-10 Implementation of Standards Transactions An APCAEPA International Speciality Conference San Francisco CA (Mathal CV Stonefield DH eds) PittsburghAPCA 1988439ndash457

9 overview In Particulate Matter Health and Regulatory Issues VIP-49 Proceedings of an International Specialty Conference 4ndash6 April 1995 Pittsburgh PA PittsburghAir and Waste Management Association 1995577ndash598

10 Kunzli N Kaiser R Medina S Studnicka M Chanel O

11 Filliger P Herry M Horak F Jr Puybonnieux-Texier V Quenel P et al Public-health impact of outdoor and traffic- related air pollution a European assessment Lancet 356795ndash801 (2000)

Bibliography

1 Sioutas C Delfino RJ Singh M Exposure assessment for atmospheric ultrafine particles (UFP) and implications in epidemiological research Environ Health Perspect 2005113947ndash955

2 Mosleh M Blau PJ Dumitrescu D (2004) Characteristics and morphology of wear particles from laboratory testing of disc brake materials Wear 2561128ndash1134

3 Kuumlnzli N et al (2000) Public-health impact of outdoor and traffi c-related air pollution a European assessment Lancet 356(9232)795ndash801

4 Dora C Phillips M eds (2000) Transport environment and health Copenhagen WHO Regional Office for Europe (WHO Regional Publications European Series No 89 httpwwweurowhointdocumente72015pdf accessed 26 November 2004)

5 Westerholm R Karl-Erik E Exhaust emissions from lightand

6 heavy-duty vehicles chemical composition impact of exhaust after treatment and fuel parameters Environ Health Perspect 102(suppl 4)13ndash23 (1994)

7 Fauser Tjell Mosbaek pigegaard Quantification of tire-Tread particles using extractable Organic Zinc as a Tracer Rubber Chemistry and Technology 1999 969Table shows some literature estimates of the contribution of tire wear to PM10 in air (Panko et al 2013) Gustafsson M Blomqvist G Gudmundsson A Dahl A Swietlicki E Bohgard M Lindbom J Ljungman A

8 Chen Y Shah N Huggins FE and Huffman GP (2006) Microanalysis of Ambient Particles from Lexington Ky by Electron Microscopy Atmos Environ 40 651ndash663

9 Donaldson K Tran CL Jimenez LA Duffin R Newby DE and Mills N (2005) Combustion-derived Nanoparticles A Review of Their Toxicology Following Inhalation Exposure Part Fibre Toxicol 2 10ndash23

10 Su D Serafino A Muller JO Jentoft RE Schlogl R and Fiorito S (2008) Cytotoxicity and Inflammatory Potential of Soot Particles of Low-emission Diesel Engines Environ Sci Technol 42 1761ndash1765

11 Maier KL Alessandrini F Beck-Speier I Hofer TPJ Diabatґe S Bitterle E Stoger T and Jakob T (2008) Health Effects of Ambient Particulate Matter-Biological Mechanisms and Inflammatory Responses to in Vitroand in Vivo Particle Exposures Inhalation Toxicol 20 319ndash337

Page 8: Studies of Air Pollutants and their Impact on Respiratory and ...€¦ · Ascarate Park C37 Monitoring Station: The National Ambient Air Quality Standard (NAAQS) for PM 10 and 2.5

Problem Statement

0

100

200

300

400

500

600

700

800

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31

PM

10 (

μg

m3)

Days

Ascarate Park SE C37

Montly 24 Hours Avg PM 10 Exceedences and Maximum

Concentrations 2010 January

February

March

April

May

June

July

August

September

October

November

December

Graph 1 Source TCEQ ( Texas Commission on Environmental Quality) Ascarate Park monitoring station Data 2010

0

20

40

60

80

100

120

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31

PM

25

UG

M3

DAYS

Ascarate Park SE C37

Montly 24 Hours Average

PM-25 measured in micrograms per cubic meter

(μgm3)

2010 JanuaryFebruaryMarchAprilMayJuneJulyAugustSeptemberOctoberNovemberDecember

Graph 2 Source TCEQ ( Texas Commission on Environmental Quality) Ascarate Park monitoring station Data 2010

Ascarate Park C37 Monitoring Station The National Ambient Air Quality Standard (NAAQS) for PM

10 and 25 was exceeded but in 24 hour average The NAAQS for PM 25 for 24-hour average is

PM2535 microgmsup3 and PM10 50-100 microgmsup3 The highest concentration occurred several times

PM10(200250300400600720 microgmsup3) PM25(4090120microgmsup3)

The National Ambient Air Quality Standard (NAAQS) for PM was Exceeded in The PdN Region 2006 2010

Analysis of Ascarate Area Zip Code 79905

These chart is to illustrate there are two high spikes that occurred which exceeds the 24 hour average

Fig Number of registered automobiles in Texas The Statistics show the

number of registered automobiles truck motorcycle in Texas Source

Texas department motor vehicles

Fig More than 61 percent of

US transportation emissionscome from cars and lighttrucks

Fig in US On-roadmobile sourcesconstitute the largestsingle source categoryof air pollution with(327)

Problem Statement

13000000140000001500000016000000170000001800000019000000

Millio

ns

of

Ve

hic

les

Years

Total Growth of Texas Registrations

2001-2012

Total

Vehicles

Registratio

ns

Problem Statement

El Paso Texas and ciudad Juarez currently has commercialmovements through El PasondashCiudad Juarez gateways peaked at715000 trucks in the year 2010 and Approximately 40000 vehicles passthese roads each laborable day

Source US Department of Transportation Bureau of Transportation Statistics 2010

Bridge Number of US-bound

Truck Crossings year 2010

World Trade Bridge 1327479

Pharr ndash Reynosa International Bridge

452821

Ysleta ndash Zaragoza Bridge 379508

Laredo ndash Colombia Solidarity

Bridge

374781

Bridge of the Americas 337609

Veterans International Bridge 177986

Camino Real International Bridge 106423

Del Rio ndash Ciudad Acuna

International Bridge

62966

Progreso International Bridge 42605

Free Trade Bridge 30773

Source CBP

Fig Bridge of the Americas (Puente Cordova)

Publications Review to examine the relationship between exposure to motor vehicle emissions and respiratory and cardiovascular disease

We have analyzed the current literature which have served as the basis for this project

Some studies determined that traffic-related emissions have been recognized as a major contributor to urban air pollution in particular major cities proximity to major roadways and exposure to motor vehicle exhaust and Non-exhaust emissions are associated with increased risks of cardiovascular respiratory and other diseases (Brugge et al 2007 Gan et al 2010 Gauderman et al 2007 Jerrett et al 2009 Laden et al 2007 McConnell et al 2006)

Effect of traffic pollution on respiratory and allergic disease in adults cross-sectional and longitudinal analyses Mar Pujades-Rodriacuteguez Tricia McKeever Sarah Lewis Duncan Whyatt John Britton and Andrea Venn

httpwwwsciencedailycomreleases200811081114081003htm April 2011

Traffic Pollution Increases Asthma in Adults Several research results revealed adults who suffer asthma and were exposed to heavy traffic pollution experienced an 80 per cent increase University of Melbourne Rev Public Health 15 (1994) pp 107ndash132 August 2010

Traffic Pollution Aggravates Symptoms In Asthmatic Children Traffic pollution especially in cities adversely affects respiratory health in children with asthma studies suggest that traffic pollution and diesel particles in particular may have a greater effect on respiratory health than other pollutants httpwwwsciencedailycomreleases200811081114081003htm September 2010

Traffic-related air pollution associated with prevalence of asthma and COPDchronic bronchitis A cross-sectional study in Southern Sweden Anna Lindgren Emilie Stroh Peter Montneacutemery September 2009

Acute respiratory health effects of air pollution on children with asthma in US inner cities Benjamin Vaughn MS Meyer Kattan MD Herman Mitchell PhD May 2008

Comparison of Air QualityndashRelated Mortality Impacts of two Different source of emission Transportation in the United States httpwwwtrborgMainBlurbs166402aspx January 2008

Long-term exposure to traffic-related air pollution and cardiovascular mortality Chen H Goldberg MS Burnett RT Jerrett M Wheeler AJ Villeneuve PJ Source Department of Epidemiology and Biostatistics McGill University Montreal Quebec Canada January 2011

heavy-duty vehicles chemical composition impact of exhaust after treatment and fuel parameters Environ Health Perspect102(suppl 4)13ndash23 (1994)

Particulate Matter

PM is a mixture of solid and liquid particles suspended in the atmosphere

as atmospheric aerosols Mobile Pollutants are formed by chemical

reactions of gaseous components from burning of fossil fuel in vehicles

(Gasoline amp diesel motor vehicles)

Source EPA (2012) United States Environmental Protection Agency

Particulate matter basic information Cited October 30th 2012 Available

online at httpwwwepa govairqualityparticlepollutionbasichtml

Source EPA (2012) United States Environmental Protection Agency Particulate matter basic

information Cited October 30th 2012 Available online at httpwwwepa

govairqualityparticlepollutionbasichtml

PM10 25 Long Term Exposure ndashChronic Health Consequences

These particles are associated with a

variety of problems including

Aggravated asthma Chronic

bronchitis

Decreased lung function

Increased respiratory symptoms

coughing or difficulty breathing

Increased Cardiopulmonary Mortality

Increased Risk of Lung Cancer

Sources of Particulate Matter Emissions from traffic

Diesel exhaust particulate matter

This particulate toxic potential has been associated with serious adverse Health

effects including respiratory symptoms Pulmonary function and cardiovascular

diseases (Geller et al 2006 Bernstein et al 2004)

Brake wear particulate matter

Brake wear particulate matter Chemical content (iron(Fe) copper(Cu) Antimony(Sb) barium(Ba) this type of particulate can cause severe respiratory and cardiovascular damages and it is also known that Sb has been classified as a possible human pulmonary carcinogen by the International Agency for Research on Cancer (IARC 1989 Et al 2013)

Fig images of brake wear particles generated at a road simulation study ( centre lt25 μm right lt10

μm) Source [Kukutschovaacute et al 2011]

Tire wear particulate matter

The tire wear particles of the tires are generated either by frictional forces between the treadand the road pavement The chemical content Fe Cr Pb Ti Cr Cu Zn Sr Y Zr Sn Sb Ba LaCe and Pb)

Fig Examples of near spherical particles PM 10 and 25 which are originate from interaction of tires and pavements Source [Dahl et al 2006]

Study Area

The Paso del Norte (PdN) region Selected two strategic areas of study El Paso County zip code 79905 Urban area and Dona Ana County Zip Code 880218802788072 Rural Restricted urban access (freeways and interstates)

Map of the area of the simulation by the MOVES model in the study area

Geographic Domain Zip Code 79905 Urban Area (El Paso County)

Zip Codes 88021880278807288048 (Dona Ana County)

Urban road Delta Dr St 31o 45rsquo 5637- 106o 27rsquo 1212 10 miles

Cordova Bridge of the Americas 31o 45rsquo 4367- 106o 27rsquo 0506 15 miles

478 Highway interstate 31o 46rsquo 1326- 106o 27rsquo 0327 05 miles

110 Highway interstate 31o 46rsquo 1210- 106o 27rsquo 0066 10 miles

10 Interstate Gateway Blvd 31o 46rsquo 397- 106o 26rsquo 4769 05 miles

Chamizal Loop 478 31o 46rsquo 668- 106o 26rsquo 5456 05 miles

Alameda Loop 20 31o 46rsquo 1323- 106o 27rsquo 0328 10 miles

Paisano Dr St Patriot freeway

route 62

31o 46rsquo 0669- 106o 27rsquo 212 15 miles

St Piedras 31o 46rsquo 1326- 106o 27rsquo 0327 10 miles

Dona Ana County Miles

Interstate 25 32o 23rsquo 0561 -106 48

1054 32o 23rsquo 3434- -

106 48 1054 32o 23rsquo

5660 106 48 4314

50

Geographic domain To obtain the simulation mobile data from modelMOVES2010a was configurated the coordinates selected in the study areas

El Paso County

PM25 Estimation from Aerosol Optical Depth (AOD) using

satellites

We examined the relationship

between Aerosol Optical Depth

(AOD) estimated from satellite data

at 5 km spatial resolution and the

mass of fine particles le25 μm in

aerodynamic diameter (PM25)

monitored on the ground in El PdN

area PM25 data was recorded from

air quality monitoring Chamizal

station (TCEQ) on different periods

Our analysis shows a significant

positive association between AOD

and PM25

Time-series and scatter plots of AOD estimated PM25 and surface PM25

Analysis of the meteorological factors and synoptic conditions leading to a local high

ozone event episode June 12-21 2006

Meteorology plays a critical role in determining atmospheric ozone concentrations A good synoptic scale weather forecast is essential to accurately forecast tropospheric and surface ozone concentrations

Figure 1 The domain configuration and Landuse categories

resolution 25 km domainFigure 2 The Geopotential height at 500 mb Figure 3 depicts the 850 mb at a lower altitude The

white regions observed in the graph correspond to

mountainous areas

Figure 4 Temperature at 2m height

above surface at 22 UTC June 18 2006

36 km resolution

Performance Evaluation

01020304050

Ju

ne

137

130

0

190

0

10

0

Ju

ne

157

130

0

190

0

10

0

Ju

ne

187

130

0

190

0

10

0

Tem

pe

ratu

re (⁰C

)

Local time (Hrs)

C41 June 13-19 2006

WRF_temperature

(⁰C)

TCEQ_temperature

(⁰C)

01020304050

June1

37

100

0

130

0

160

0

190

0

220

0

10

0

40

0

June1

57

100

0

130

0

160

0

190

0

220

0

10

0

40

0

June1

87

100

0

130

0

160

0

190

0

220

0

10

0

40

0

Rel

ativ

e h

um

idit

y (

)

Local time (Hrs)

C41 June 13-19 2006

WRF_rh () TCEQ_relative humidity ()

0

5

10

15

20

June

137 10

13

16

19

22 1 4

June

157 10

13

16

19

22 1 4

June

187 10

13

16

19

22 1 4

Win

d s

pee

d (

ms

Local time(Hrs)

C12 June 13-192006

WRF_wind speed (ms) TCEQ_ wind speed (ms)

We evaluate the WRF modelrsquos performance

by comparing against corresponding

experimental TCEQ data and performing the

required statistical analysis

HYSPLIT Model

HYSPLIT was simulated and showed that the ozone is mostly transported to El Paso from north western and south western US and Mexican regions during the 72 hours duration of the simulation

0

20

40

60

80

100

1200

00

10

02

00

30

04

00

50

06

00

70

08

00

90

01

00

01

10

01

20

01

30

01

40

01

50

01

60

01

70

01

80

01

90

02

00

02

10

02

20

02

30

0

Ho

url

y o

zon

e [

pp

b]

0102030405060708090

00

01

00

20

03

00

40

05

00

60

07

00

80

09

00

10

00

11

00

12

00

13

00

14

00

15

00

16

00

17

00

18

00

19

00

20

00

21

00

22

00

23

00

Ho

url

y o

zon

e [

pp

b]

June 18th June 19th

Performance Evaluation

01020304050

Ju

ne

137

130

0

190

0

10

0

Ju

ne

157

130

0

190

0

10

0

Ju

ne

187

130

0

190

0

10

0

Tem

pe

ratu

re (⁰C

)

Local time (Hrs)

C41 June 13-19 2006

WRF_temperature

(⁰C)

TCEQ_temperature

(⁰C)

0

50

100

150

June1

37

100

0

130

0

160

0

190

0

220

0

10

0

40

0

June1

57

100

0

130

0

160

0

190

0

220

0

10

0

40

0

June1

87

100

0

130

0

160

0

190

0

220

0

10

0

40

0Ozo

ne

(pp

b)

Local time (Hrs)

C41 June 13-19 2006

CAMx_ozone (ppbV) TCEQ_ozone (ppb)

0

10

20

30

40

50

June1

37

100

0

130

0

160

0

190

0

220

0

10

0

40

0

June1

57

100

0

130

0

160

0

190

0

220

0

10

0

40

0

June1

87

100

0

130

0

160

0

190

0

220

0

10

0

40

0

Rel

ativ

e h

um

idit

y (

)

Local time (Hrs)

C41 June 13-19 2006

WRF_rh () TCEQ_relative humidity ()

0

5

10

15

20

June

137 10

13

16

19

22 1 4

June

157 10

13

16

19

22 1 4

June

187 10

13

16

19

22 1 4W

ind

sp

eed

(m

sLocal time(Hrs)

C12 June 13-192006

WRF_wind speed (ms) TCEQ_ wind speed (ms)

Methodology

Medical Data The data by weekly monthly and year for daily emergency room and hospital admission for the respiratory

infections (RD) and cardiovascular diseases (CVD) was extracted from hospitals records located in the El PdN

the system includes data on type of admission primary and secondary causes of admissionRESPIRATORY DISEASE

Bronquitis amp Chronic Bronchitis 466 - 4661 491 - 4919

Asthma 463 - 4939

Emphysema 492

Respiratory failure 51881

HEART DISEASE

Accute Myocardial Infarction 410

Coronary Athersclerosis 4140

Other Ischemic Heart Disease 411-4139 4141-4149

Cardiac Dyshythmias 427

Essential hypertension 401

Acute myocardial infarction 410

Congestive Heart Failure 4280 4282-4284

Hypertensive heart disease 402

Table 1 ICD -9 Codes for Respiratory and Cardiovascular Diseases

0

50

100

150

200

250

300

Wee

k 1

Wee

k 2

Wee

k 3

Wee

k 4

Wee

k 5

Wee

k 6

Wee

k 7

Wee

k 8

Wee

k 9

Wee

k 1

0

Wee

k 1

1

Wee

k 1

2

Wee

k 1

3

Wee

k 1

4

Wee

k 1

5

Wee

k 1

6

Wee

k 1

7

Wee

k 1

8

Wee

k 1

9

Wee

k 2

0

Wee

k 2

1

Mo

rb

idit

y D

isch

arg

e fo

r a

ll R

esp

ira

tory

Dis

ease

IC

D-9

(

Ast

hm

aB

ro

nch

itis

)

Weekly Morbidity Discharges of all the Listed Diagnoses for All

Respiratory Disease During WinterSpring 2010

Asthma-Bronchitis

EPA MOVES Model for Estimating Emission

Inventories

Motor Vehicle Emission Simulator (MOVES 2010b) will be configuredin The El Paso North Region for Calculate five categories of PM10

PM25 total Emission inventories from all on-road traffic over a

variety of scales within periods of time selected weeks months

and years

Moves (Motor Vehicle Emission

Simulator)

The emission model is develop using the current equation to calculate direct traffic emissions from

vehicles in the form of PM is

Eext annual emissions are measured in grams of miles traveled by the vehicle (gVMT )

SL is the road surface loading in (gm2)

W is the average weight in tons of the vehicles on the road

K is the particle size multiplier for particle size range (eg gVMT for PM10 when using grams and miles)

P is the 7 number of wet days with at least 0254 mm of precipitation during the averaging period

N is the number of years considered in the averaging period

C is the particle size specific emissions factor in units of interest vehicle direct exhaust brake wear and tirewear

Modeling Simulation Domain and Emissions Scenarios

For simulations of mobile air quality emission inventories a motor vehicle emission simulator EPA (MOVES 2014a) was used

The modeling use input factors divided into seven section

parameters

On-Road Inventory local data

input

Scale

Geographic Bounds

Traffic intensity

Vehicle Type

Pollutants

Road Type

Fuel Types

Figure Source EPA US Environmental Protection Agency 2012- Moves 2010b Model

EPA Moves 2014a The modeling used input factors divided into six section

parameters On-Road Inventory local data input

Geographic Domains CountyNonattainment Area

Vehicle-Miles Traveled (VMT) is the total number of miles driven by all vehicles withina given time period and geographic area

Average speed range from 25 miles per

hour to 65 miles per hour

Vehicle Classes Motorcycle PassengerCarTruks light-duty Commercial Truck(6001-8500 lbs) Buses heave-duty trucksRefuse trucks School Bus Single UnitShort Haul-truck Single Unit Long Haul-truck Long Haul Truck Heavy-DutyVehicles (26001-33000 lbs)

Pollutants

Road TypeRural restricted Acces(Freeways and interstates) Rural and Restricted Acces Urban Restricted Acces Off-Network

Fuel Types Gasoline Diesel Fuel

Specific Road Types

Two road types for running emission from the MOVES can be

selected

(freeways and interstates)

Interior urban Urban

Figure Source EPA US Environmental Protection Agency 2012- Moves 2010b Model

VehiclesEquipment

This panel show which on-road vehicles will be modeled

Figure Source EPA US Environmental Protection Agency 2012- Moves 2010b Model

Long haul truck Short haul truck Inercity bus Ligth comercial truck

Passenger car Passenger truck Refuse truck

School bus Single unit long haul-truck

Single unit short haul-truck

Transit bus

Motor home

Motorcycle

Based on Department of Transportation Highway MOVES will Estimates Traffic

Emissions from Cars Trucks amp Motorcycles

Output Data Moves 2014a

Inventories of PM 10 25 Mobile Emission from all

on-Road Traffic

Exhaust Emission PM 10 25 gramsmile

Brake Wear Emission PM 10 25 gramsmile

Tire wear Emission PM 10 25 gramsmile

Date of Vehicle miles traveled (VMT) for

Day Week Month Year

Total Vehicle population

Vehicle age distribution

Simulation of Mobile Emission in the El PdN Region Zip Code 79905

Figure Total Emissions from road traffic in El Paso TX Area were estimated for PM10

Exhaust and Non exhaust emission in kilogramsmonth (Source EPA MOVES 2014a)

0

10000

20000

30000

40000

50000

PM

10 k

gM

on

th

Months

Monthly PM 10 Exhaust and Non-Exhaust Mobile Emissions 2010

On-Road Urban Restricted Area Zip Code 79905

Primary Exhaust PM 10 (kg) Primary PM 10 Brakewear (kg)

Primary PM 10 Tirewear (kg)

05000

100001500020000250003000035000400004500050000

PM

25

kg

Mo

nth

Months

Monthly PM 25 Exhaust and Non-Exhaust Mobile Emission 2010

On-Road Urban Restricted Area Zip Code 79905

Primary Exhaust PM 25 (kg) Primary PM 25 Brakewear (kg) Primary PM 25Tirewear (kg)

Figure Total Emissions from road traffic in El Paso TX Area were estimated for PM25

Exhaust and Non exhaust emission in kilogramsmonth (Source EPA MOVES 2014a)

Total Emissions from Road Traffic in El Paso County PM1025 Exhaust and Non exhaust Emission in kilogramsmonth

Taking the interests to the health risks related to PM 1025 mobile emission were simulated

Exhaust and Non-exhaust emissions contribute almost equally to total traffic-related PM1025 Emissions (Querol et al 2004 Bukowiecki et al 2009a Amato et al 2011)

Monthly PM 10 25 Exhaust and Non-Exhaust (BrakewearTirewear) Mobile

Emission 2010 On-Road Urban Restricted Area Zip Code 79905

Figure Total Emissions from road traffic in El Paso TX Area were estimated for PM10 25 Exhaust and Non Exhaust mobile

emission in kilograms per month (Source EPA MOVES)

0

10000

20000

30000

40000

50000

January February March April May June July August September October November December

PM

10

25

(K

ilog

ram

s)

Months

Summary- Monthly PM 10 25 Exhaust and Non-Exhaust Mobile

Emission 2010 On-Road Urban Restricted Area Zip Code 79905

Primary Exhaust PM 10 Primary PM 10 Brakewear Primary PM 10 Tirewear

Primary Exhaust PM 25 Primary PM 25 Brakewear Primary PM 25Tirewear

Exhaust Emissions PM1025 is reaching maximum emission 48000-42000 thousand of Kgmonth followedby Brake wear 29000-5000 thousand kgmonth and Tire wear with 9000-2000 kgmonth The results showthat the emissions of PM derived mainly from Exhaust and Brake are significantly higher in Urban Area

Annual Contribution of Mobile Emission PM 1025 (Kg) Zip Code 79905 El

Paso County 2010

Total Primary

Exhaust _PM10

39

Total Primary

Exhaust _PM25

36

Brakewear

particulate_PM10

18

Tirewear

particulate_PM10

4

Brakewear

particulate_PM25

2

Tirewear

particulate_PM25

1

0

5

10

15

20

25

30

35

40

45

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53

Fig Annual Average PM10 Concentrations at the

Chamizal C41 Station and PM1025 mobile

Concentration Zip code 79905

PM10 TCEQ (μgm3) Total Mobile Emission PM10 (Ugm3)

Fig Exhaust Emission is Contributing Approximately 74 of total

PM1025 Mobile Emissions following of Brake wear with 20 and Tire

wear with 5

Annual Average PM1025 ugm3 Mobile Emissions (Moves) 26 Chamizal C41

Monitoring Station (TCEQ Chamizal Station )

Predicting Mobile Emission and VTM

Estimation The PdN Region 2010

44E+09

46E+09

48E+09

5E+09

52E+09

54E+09

56E+09

58E+09

6E+09

62E+09

0

50000

100000

150000

200000

250000

300000

350000

20

10

20

11

20

12

20

13

20

14

20

15

20

16

20

17

20

18

20

21

20

22

20

23

20

24

20

25

20

26

20

27

20

28

20

29

20

30

EX

HA

US

T

EM

ISS

ION

MO

BIL

E (

KG

YE

AR

)

YEARS

Predict ing Mobile Exhaust Emission and VTM

Estimation

2010 - 2030 e l PdN Area

Total_ Exhaust PM10 Total_ Exhaust PM25 Distance (Miles)

Fig Predicting Mobile Exhaust PM1025 (kgMonth) Emission and VTM Estimation 2010

- 2030 el PdN Area

44E+09

46E+09

48E+09

5E+09

52E+09

54E+09

56E+09

58E+09

6E+09

62E+09

0

5000000

10000000

15000000

20000000

25000000

30000000

20

10

20

11

20

12

20

13

20

14

20

15

20

16

20

17

20

18

20

21

20

22

20

23

20

24

20

25

20

26

20

27

20

28

20

29

20

30

EX

HA

US

T

EM

ISS

ION

MO

BIL

E (

KG

YE

AR

)

YEARS

Predict ing Mobile Exhaust Emission and

VTM Estimation

2010 - 2030 e l PdN Area

CO NO2 NO NOx Distance

Fig Predicting Mobile Exhaust Emission and VTM Estimation

2010 - 2030 el PdN Area in El Paso TX Area were estimated for

Total CO NOx NO2 NO emission in kilograms per year

(Source EPA MOVES 2014a model)

The simulated Exhaust emissions in the future years shows a trend of reduction of this type of emissions in the

future years one factor should be the new hybrid technology is increasing by 476 since 2010 to 2015 and

use of catalytic converters diesel particulate filters and improved fuels and engines Non-exhaustive sources

will increase in the coming years because there is no control in the material of manufacture composed by Fe

Cu and Mn also not to be able to reduce the number of events of braking (Accelerations and decelerations)

45E+09

5E+09

55E+09

6E+09

65E+09

0

50000

100000

150000

200000

250000

201

0

201

1

201

2

201

3

201

4

201

5

201

6

201

7

201

8

202

1

202

2

202

3

202

4

202

5

202

6

202

7

202

8

202

9

203

0

NO

N-

EX

HA

US

T

EM

ISS

ION

MO

BIL

E

(KG

YE

AR

)

YEARS

Predicting Non Exhaust Mobile

Emission and VTM Estimation

2010 - 2030 el PdN Area

Brake_PM10 Tire_PM10 Distance (Miles)

Fig Predicting Mobile Exhaust PM1025 (kgMonth) Emission and VTM

Estimation 2010 - 2030 el PdN Area

Daily Avg PM1025

Levels of PM Mobile Emission Non-Exhaust -Rush Hour Periods Fall 2010 Zip Code

79905

00

100

200

300

400

500

600

Mo

bil

e P

M1

0 (k

g)

Rush Hours

Daily Avg PM10

Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush Hours

Periods 2010 Zip Code 79905

Total Primary Exhaust

_PM10 WinterSpring

Brakewear

particulate_PM10

WinterSpringTirewear particulate_PM10

WinterSpring

Total Primary Exhaust

_PM10 Summer

Brakewear

particulate_PM10 Summer

Tirewear Particulate_PM10

Summer

Total Primary Exhaust

_PM10 Fall

Brakewear

particulate_PM10 Fall

Tirewear particulate_PM10

Fall

00

50

100

150

200

250

300

350

Mo

bil

e P

M2

5 (k

g)

Rush hours

Daily Avg PM25

Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush

Hours Periods 2010 Zip Code 79905

Total Primary Exhaust _PM25

WinterSpring

Brakewear Particulate_PM25

WinterSpring

Tirewear particulate_PM25

WinterSpring

Total Primary Exhaust _PM25

Summer

Brakewear particulate_PM25

Summer

Tirewear particulate_PM25

Summer

Total Primary Exhaust _PM25

Fall

Brakewear particulate_PM25

Fall

Tirewear particulate_PM25

Fall

Figure Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush Hours Figure Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush Hours

GIS EMISSIONS INVENTORY SYSTEM A geographic information system (GIS) was used to established geographic scenarios with processed images of seasonal mobile

emissions in the PdN region Seasonal mapping is visualized for different types of pollutants Brakewear Exhaust and Tyrewear

Fg Graphics of GIS and Seasonal mobile Emission of particulate matter emission inventory Seasonal emission simulations were performed in kilograms and five contributing inputs factors were identified for

modeling 1) On the composition of the particulate material from different sources such as Exhaust and Non exhaust (Brake wear Tirewear) 2) The Vehicles Equipment clasification were selected according to

the use of gasoline and diesel fuel (motorcycle passenger car Light Duty Vehicles Trucks refuse truck Light Duty Vehicles Light Commercial Truck Light Duty Vehicles School Bus)

Winter Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

120354 67860 19065

Spring Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

139767 86702 24463

Summer Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

94747 62481 17630

Fall Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

75510 45542 12596

251 Descriptive Statistics Data Analysis

Weekly Correlation Analysis of Mobile Emission PM10 (Exhaust-Non-Exhaust) and Respiratory

Diagnoses WinterSpring Summer and Fall 2010

0

2

4

6

8

10

0

50

100

150

200

250

300

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21

Mo

rbid

ity

Dis

ch

arg

e

for

all R

esp

ira

tory

Dis

ea

se

ICD

-9

(A

sth

ma

-Bro

nc

hitis

)

WinterSpring Week

Weekly Avg Mobile PM10 Concentrations during

WinterSpring 2010 and its Influence on Respiratory

Diagnoses

Zip Code 79905

Total Medical data ZIP Code 79902

Total Mobile Emission PM10 (Ugm3)

0

1

2

3

4

5

6

7

0

20

40

60

80

100

Mo

rbid

ity

Dis

ch

arg

e

for

all R

esp

ira

tory

Dis

ea

se

ICD

-9

(Ast

hm

aB

ron

ch

itis

)

Weekly Avg Mobile PM10 Concentrations during

Summer 2010 and its Influence on Respiratory

Diagnoses

Summer 2010 Zip Code 79905

Total Mobile Emission PM10

Hospital Admission (Asthma-Bronchitis)

0

2

4

6

8

10

12

0

20

40

60

80

100

120

140

160

180

200

Mo

rbid

ity

dis

ch

arg

es

for

all r

esp

ira

tory

dis

ea

se

Weekly Avg Mobile PM10 Concentrations

during Fall 2010 and its Influence on Respiratory

Diagnoses

Zip Code 79905

Total Medical data ZIP Code 79902

Total Mobile Emission PM10 (Ugm3)

Mobile(Exhaust-Non-

Exhaust) PM10 and

Asthma-Bronchitis)

Linear R

Square

WinterSpring 734 ndash 39

Summer 614 ndash 32

Fall 548 -29

PM10 Mobile emission (Exhaust-Non-Exhaust)contributed significantly

association to the incidence of RD

Weekly Correlation Analysis of PM 25 Mobile Emission (Exhaust-Non-Exhaust)

and Cardiovascular Diagnoses WinterSpring Summer and Fall 2010

0010203040

00500

100015002000

Wee

k 1

Wee

k 2

Wee

k 3

Wee

k 4

Wee

k 5

Wee

k 6

Wee

k 7

Wee

k 8

Wee

k 9

Wee

k 1

0

Wee

k 1

1

Wee

k 1

2

Wee

k 1

3

Wee

k 1

4

Wee

k 1

5

Wee

k 1

6

Wee

k 1

7

Wee

k 1

8

Wee

k 1

9

Wee

k 2

0

Wee

k 2

1

Morb

idit

y d

isch

arg

es f

or

all

card

iovasc

ula

r d

isea

se

Weekly Avg PM25 Mobile Concentrations during

WinterSpring 2010 and its Influence on all Heart

Diagnoses

Zip Code 79905

Total All Heart Disease PM 25 mobile (μgm3)

0010203040

00

500

1000

1500

Mo

rbid

ity

dis

ch

arg

es

for

all

ca

rdio

va

scu

lar

dis

ea

se

Weeks

CORRELATION BETWEEN MOBILE PM25 ugm3

EXPOSURE TO HEART DISEASES SYMPTOMS

SUMMER SEASON 2010

Total All Heart Disease PM 25 mobile (μgm3)

Figure Statistical Analyses of the Relationship Between PM25 Caused by Traffic Emission( 26 of total Emission) with Heart diseases Source Hospital Admissions for Asthma Acute Bronchitis and Heart diseases in El Paso County zip code 79905 from Texas Health Care

Information Council in Austin Texas (Texas Health Care Information Council 2000)

00

10

20

30

40

0

50

100

150

We

ek 3

6

We

ek 3

7

We

ek 3

8

We

ek 3

9

We

ek 4

0

We

ek 4

1

We

ek 4

2

We

ek 4

3

We

ek 4

4

We

ek 4

5

We

ek 4

6

We

ek 4

7

We

ek 4

8

We

ek 4

9

We

ek 5

0

We

ek 5

1

We

ek 5

2

We

ek 5

3

Mo

rbid

ity

dis

ch

arg

es

for

all

ca

rdio

va

scu

lar

dis

ea

se

CORRELATION BETWEEN MOBILE PM25 ugm3

EXPOSURE TO HEART DISEASES SYMPTOMS FALL

SEASON 2010

Total All Heart Disease PM 25 mobile (μgm3)

Mobile(Exhaust-

Non-Exhaust)

PM10 and

Asthma-

Bronchitis)

Linear R

Square

WinterSpring 833 -42

Summer 620 -32

Fall 501-26

PM10 Mobile

emission (Exhaust-

Non-

Exhaust)contribut

ed significantly

association to the

incidence of CVD

Diseases

Monthly Brake Mobile Emission PM1025 kg During year 2010 and its Influence on

Respiratory Diagnoses Zip Code 79905

00200040006000800010000

010000200003000040000

PM

10

Mo

bile

(K

g)

Months

Monthly Brake Mobile Emission PM10 kg during year

2010 and its Influence on Respiratory Diagnoses

Zip Code 79905

Primary PM 10

Brakewear 00100020003000400050006000

0

1000

2000

3000

4000

PM

25

Mo

bil

e(K

g)

Months

Monthly Brake Mobile Emission PM25 during

year 2010 and its Influence on Heart Diagnoses

Zip Code 79905

Primary PM 25

Brakewear

Heart Diseases

Hospital

Admission

Brake Mobile Emission

PM10 kg Asthma-

Bronchitis)

Brake Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=969 Linear Square R=856

Monthly Mobile Exhaust Emission PM1025 During year 2010 and its Influence on

Respiratory Diagnoses Zip Code 79905

0

200

400

600

800

1000

0

10000

20000

30000

40000

50000

1 3 5 7 9 11

PM

10

(K

g m

on

th)

Months

Monthly Mobile Exhaust Emission PM10 during

year 2010 and its Influence on Respiratory

Diagnoses

Zip Code 79905

Primary Exhaust

PM 10

Respiratory Disease

(Asthma

Bronchitis) Hospital

Admission

0

100

200

300

400

500

600

0

10000

20000

30000

40000

50000

1 2 3 4 5 6 7 8 9 101112

PM

25

(K

g m

on

th)

Months

Monthly Exhaust Mobile Emission PM25 during

year 2010 and its Influence on Heart Diagnoses

Zip Code 79905

Primary Exhaust PM

25

Heart Diseases

Hospital Admission

Exhaust Mobile Emission

PM10 kg Asthma-

Bronchitis)

Exhaust Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=929 Linear Square R=831

Monthly Tire wear Mobile Emission PM1025 During year 2010 and its Influence on Heart

Diagnoses Zip Code 79905

0

100

200

300

400

500

600

700

800

900

0

1000

2000

3000

4000

5000

6000

7000

8000

9000

1 2 3 4 5 6 7 8 9 10 11 12

PM

10

(K

g m

on

th)

Months

Monthly Tirewear Mobile Emission PM10 during year 2010

and its Influence on Heart Diagnoses

Zip Code 79905

Primary PM 10 Tirewear

Mobile Emission

Respiratory Disease

(Asthma Bronchitis)

Hospital Admission

0

100

200

300

400

500

600

0

200

400

600

800

1000

1200

1400

1 2 3 4 5 6 7 8 9 10 11 12

PM

25

(K

g m

on

th)

Months

Monthly Tirewear Mobile Emission PM25 during year 2010

and its Influence on Respiratory Diagnoses

Zip Code 79905

Primary PM 25Tirewear

Mobile Emission

Heart Diseases Hospital

Admission

Exhaust Mobile Emission

PM10 kg Asthma-

Bronchitis)

Exhaust Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=769 Linear Square R=715

Dona Ana County Zip Codes

88021880278807288048

Primary

Exhaust

PM 10 Zip

code

79905

Total

Primary

Exhaust

PM10

Dona Ana

Primary

Exhaust

PM 25 Zip

Code

79905

Total

Primary

Exhaust

PM25

Dona Ana

Series1 430378 111773 391915 102123

0

100000

200000

300000

400000

500000

AX

IS T

ITLE

Annual Comparison of the Mobile

Exhaust Emissions El Paso County

and Dona Ana 2010

Primary

PM 10

Brakewea

r Zip code

79905

Brakewea

r

particulat

e_PM10

Dona Ana

Primary

PM 10

Tirewear

Zip code

79905

Tirewear

particulat

e_PM10

Dona Ana

Series1 262585 48573 73754 11864

050000

100000150000200000250000300000

AX

IS T

ITLE

Annual Comparison of the Mobile

Brakewear Emissions El Paso County

and Dona Ana 2010

Figure Comparison of the Annual Mobile Emissions

of Primary PM10 Non-Exhauts (Brake ) from Dona

Ana County New Mexico and El Paso Texas Units

in KgMonth

Figure Comparison of the Annual Mobile Emissions

of Primary PM10-Exhauts Emission from Dona Ana

County New Mexico and El Paso Texas Units in

KgMonth

Primary

PM 25

Brakewe

ar Ziphellip

Brakewe

ar

particula

te_PMhellip

Primary

PM

25Tirewe

ar Ziphellip

Tirewear

particula

te_PM25

Donahellip

Series1 32645 6071 10919 1779

0

10000

20000

30000

40000

AX

IS T

ITLE

Annual Comparison of the

Mobile Exhaust Emissions El Paso

County and Dona Ana 2010

Figure Comparison of the Annual Mobile Emissions

of Primary PM10-Exhauts Emission from Dona Ana

County New Mexico and El Paso Texas Units in

KgMonth

Monthly Mobile Emission PM1025 kg During year 2006

and its Influence on Respiratory Diagnoses Dona Ana

County Zip Code 880218802788072

0

100

200

300

0

5000

10000

15000

Axi

s Ti

tle

Axis Title

Monthly Mobile Exhaust Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Total PrimaryMobile Exhaust_PM10

All Respiratory ICD-9 (AsthmaBronchitis)

050100150200250300

010002000300040005000

Axi

s Ti

tle

Axis Title

Monthly Mobile Brake Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Brakewearparticulate_PM10

All RespiratoryICD -9 (AsthmaBronchitis)

050100150200250300

0200400600800

10001200

Axi

s Ti

tle

Axis Title

Monthly Mobile Tirewear Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Tirewearparticulate_PM10

All Respiratory ICD -9 (AsthmaBronchitis)

Mobile Exhauts

Emission PM10

kg Asthma-

Bronchitis)

Brake Mobile

Emission PM10

kg and Heart

Diagnoses

Tirewear Mobile

Emission PM10

kg and Heart

Diagnoses

Linear Square

R= 951

Linear Square

R=625

Linear Square

R=525

Mobile Exhauts

Emission PM25

kg Asthma-

Bronchitis)

Brake Mobile

Emission PM25

kg and Heart

Diagnoses

Tirewear Mobile

Emission PM25

kg and Heart

Diagnoses

Linear Square

R= 986

Linear Square

R=691

Linear Square

R=601

Results

The results showed that mobile PM emissions in the urban areas close to urban Road and highways is putting at risk public health

and the proportion of diseases attributable to this exposure is potentially large

Brake wear emissions is much lower in freeways due to significantly reduced number of braking events while tire wear is much

higher in areas where studded tires are used The emission of exhaust gases are much higher in areas where there is a high

vehicular traffic

Brake Mobile

Emission PM10 kg

Asthma-Bronchitis)

Brake Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square

R=969

Linear Square

R=856

Exhaust Mobile

Emission PM10 kg

Asthma-Bronchitis)

Exhaust Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square

R=929

Linear Square

R=831

Tirewear Mobile

Emission PM10 kg

Asthma-Bronchitis)

Tirewear Mobile

Emission PM25 kg

and Heart Diagnoses

Linear Square R=769 Linear Square R=715

Brake Mobile

Emission PM10 kg

and Heart

Diagnoses

Brake Mobile

Emission PM25 kg

and Heart

Diagnoses

Exhaust Mobile

Emission PM10 kg

Asthma-Bronchitis)

Linear Square

R=625

Linear Square

R=691

Linear Square R=

951

Exhaust Mobile

Emission PM25 kg

Asthma-

Bronchitis)

Tire wear Mobile

Emission PM10 kg and

Heart Diagnoses

Tirewear Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square R=

986

Linear Square R=525 Linear Square

R=601

El Paso County

Dona Ana

County

BenMAP-CE

In this analysis the Program of Mapping and Analysis of Environmental Benefits-Community Edition

(BenMAP-CE) was used to Estimate the number and economic value of health impacts resulting from changes

in air pollution PM 25 Ugm3 in The El Paso Area

Health and Economic Benefits associated with the Response of PM25 Emission between

Base Year 2010

Number of Mortalities in 2010 Base Year Based on El Paso County Texas Department of State Health Services

Number of Mortalities in 2010 Base Year Based on El Paso County Texas

Department of State Health Services

cause of death

year

2010

Populatio

n

Affected

Backgro

und

Concentr

ation Pollutant

Rollback

Type

Avoided

Deaths

(

Populatio

n)

alzheimers disease 2010 40716 125 PM25

25

microgmAcircsup3

Rollback 9

diseases of the

heart 2010 15834 125 PM25

25

microgmAcircsup3

Rollback 35

influenza and

neumonia 2010 81432 125 PM25

25

microgmAcircsup3

Rollback 18

acute bronchitis

and bronchiolitis 2010 117624 125 PM25

25

microgmAcircsup3

Rollback 26

chronic lower

respiratory diseases 2010 54288 125 PM25

25

microgmAcircsup3

Rollback 12

The Basin-wide decrease in 4 ugm3 PM25 concentration after this

reduction control

Cause of death year 2010

Populatio

n

Affected

Background

Concentrati

on

Reduc

cion

scena

rio Polluta

nt

Rollback

Type

Avoi

ded

Deat

hs

(

Pop

ulati

on)

economic

benefits

analysis $

Alzheimers

disease 2010 121 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 9 12000

Diseases of the

heart 2010 470 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 35 35000

Influenza and

neumonia 2010 242 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 18 42500

Acute bronchitis

and bronchiolitis 2010 349 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 26 95000

Chronic lower

respiratory

diseases 2010 161 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 12 4500

$1 295000

PM25-related Mortalities Based on BenMAP-CE Estimate in 2010 Base Year with change in the concentrations levels

Health and Economic Benefits associated with the Response of PM25 Emission between

Base Year 2010 Increasing 7 Ugm3

Cause of death year 2010

Population

Affected

Deaths

avoided by

attaining 195

μgm3

standard

Background

Concentrati

on

Pollut

ant

Rollback

Type

Avoided

Deaths (

Populatio

n)

econo

mic

Unben

efits

analysi

s

Alzheimers

disease 2010 4524 195 PM25

25

microgmAcircsup3

Rollback 19 150000

Diseases of the

heart 2010 20358 195 PM25

25

microgmAcircsup3

Rollback 135 450000

Influenza and

neumonia 2010 126672 195 PM25

25

microgmAcircsup3

Rollback 38 525000

Acute bronchitis

and bronchiolitis 2010 162864 195 PM25

25

microgmAcircsup3

Rollback 36 122000

Chronic lower

respiratory

diseases 2010 99528 195 PM25

25

microgmAcircsup3

Rollback 12 650000

Conclusions

An excellent Pearson Correlation was established to analyze the relationship in the relative risks of hospitalization of Respiratory(RD) and cardiovascular (CVD) associated with ambient exposure caused by traffic emission in relation to their size andspecific sources of emission on different scenarios interior a border Urban Rural Urban restricted access (freeways andinterstates)

A significant correlation of PM1025 exposure from mobile emission and hospital admissions for selected Respiratory (RD) andcardiovascular (CVD) diagnoses was established The results showed that PM emissions in urban restricted access (freeways andinterstates) is mainly caused by traffic Therefore people living close to highways are more exposed higher vehicular emissions

Conclusions

We found statistically significant associations between mobile PM25 caused by traffic emission with Respiratory and Cardiovascular Diseases in the study areaSubsequently a correlation between cardio-respiratory mortality is established

A significant correlation of PM1025 exposure from mobile emission and hospital admissions for selected Respiratory (RD) and cardiovascular (CVD) diagnoses isestablished The results showed that PM emissions in urban restricted access (freeways and interstates) is mainly caused by traffic Therefore people living close tohighways receive higher vehicular emissions

The table shows the percentage of PM mobile exposure in the analyzed areas contributing to increase the risk of Respiratory and Cardiovascular Diseases

An examination was conducted of the synoptic and local meteorology for the June 2006 ozone episode using the WRF model to determine how meteorological parametersinfluence the formation transport and dispersion of ozone in the PdN The predominant synoptic feature of the ozone event day was the expansion intensification and slowprogression of an upper-level ridge of high pressure The high ozone episodes are associated with highly stable atmospheres strong temperature inversions with low mixingheights and therefore low mixing volumes Under these conditions emissions such as NOx lead to highly polluted conditions that favor ozone formation

BenMAP Conclusions

We have estimated the number and economic value of health impacts resulting

from changes in air pollution concentrations of PM 25 in the PdN region

Reduction of Pm 25 4 UGm3= Avoided 213 cases respiratory cardiovascular

diseses and Economic Benefits associated with the Response of PM25 Emission + $

1295000

Increase of PM25 7 ugm3 = increasing Dies= 326 economic Unbenefits= 2345000$

Bibliography

1 Dockery DW Pope CAI Xu X Spengler JD Ware JH Fay ME Ferris BG Speizer FE An association between air pollution and mortality in six US cities N Engl J Med 3291753ndash1759 (1993)

2 Samet JM Dominici F Curriero FC Coursac I Zeger SL Fine particulate air pollution and mortality in 20 US cities 1987ndash1994 N Engl J Med 3431742ndash1749 (2000)

3 Nel AE Diaz-Sanchez D Li N The role of particulate pollutants in pulmonary inflammation and asthma evidence for the involvement of organic chemicals and oxidative stress Curr Opin Pulm Med 20017 20ndash26

4 Westerholm R Karl-Erik E Exhaust emissions from lightand heavy-duty vehicles chemical composition impact of exhaust after treatment and fuel parameters Environ Health Perspect 102(suppl 4)13ndash23 (1994)

5 Bascom R Bromberg P Costa D Delvin R Dockery D Frampton M Lambert W Samet J Speizer F Utell

6 Health effects of outdoor air pollution Am J Respir Crit Care Med 1533ndash50 (1996)

7 Chow JC Watson JG Frazier CA Egami RT Goodrich A Ralph C Spatial and temporal source contributions to

8 PM10 and PM25 in Reno NV In PM-10 Implementation of Standards Transactions An APCAEPA International Speciality Conference San Francisco CA (Mathal CV Stonefield DH eds) PittsburghAPCA 1988439ndash457

9 overview In Particulate Matter Health and Regulatory Issues VIP-49 Proceedings of an International Specialty Conference 4ndash6 April 1995 Pittsburgh PA PittsburghAir and Waste Management Association 1995577ndash598

10 Kunzli N Kaiser R Medina S Studnicka M Chanel O

11 Filliger P Herry M Horak F Jr Puybonnieux-Texier V Quenel P et al Public-health impact of outdoor and traffic- related air pollution a European assessment Lancet 356795ndash801 (2000)

Bibliography

1 Sioutas C Delfino RJ Singh M Exposure assessment for atmospheric ultrafine particles (UFP) and implications in epidemiological research Environ Health Perspect 2005113947ndash955

2 Mosleh M Blau PJ Dumitrescu D (2004) Characteristics and morphology of wear particles from laboratory testing of disc brake materials Wear 2561128ndash1134

3 Kuumlnzli N et al (2000) Public-health impact of outdoor and traffi c-related air pollution a European assessment Lancet 356(9232)795ndash801

4 Dora C Phillips M eds (2000) Transport environment and health Copenhagen WHO Regional Office for Europe (WHO Regional Publications European Series No 89 httpwwweurowhointdocumente72015pdf accessed 26 November 2004)

5 Westerholm R Karl-Erik E Exhaust emissions from lightand

6 heavy-duty vehicles chemical composition impact of exhaust after treatment and fuel parameters Environ Health Perspect 102(suppl 4)13ndash23 (1994)

7 Fauser Tjell Mosbaek pigegaard Quantification of tire-Tread particles using extractable Organic Zinc as a Tracer Rubber Chemistry and Technology 1999 969Table shows some literature estimates of the contribution of tire wear to PM10 in air (Panko et al 2013) Gustafsson M Blomqvist G Gudmundsson A Dahl A Swietlicki E Bohgard M Lindbom J Ljungman A

8 Chen Y Shah N Huggins FE and Huffman GP (2006) Microanalysis of Ambient Particles from Lexington Ky by Electron Microscopy Atmos Environ 40 651ndash663

9 Donaldson K Tran CL Jimenez LA Duffin R Newby DE and Mills N (2005) Combustion-derived Nanoparticles A Review of Their Toxicology Following Inhalation Exposure Part Fibre Toxicol 2 10ndash23

10 Su D Serafino A Muller JO Jentoft RE Schlogl R and Fiorito S (2008) Cytotoxicity and Inflammatory Potential of Soot Particles of Low-emission Diesel Engines Environ Sci Technol 42 1761ndash1765

11 Maier KL Alessandrini F Beck-Speier I Hofer TPJ Diabatґe S Bitterle E Stoger T and Jakob T (2008) Health Effects of Ambient Particulate Matter-Biological Mechanisms and Inflammatory Responses to in Vitroand in Vivo Particle Exposures Inhalation Toxicol 20 319ndash337

Page 9: Studies of Air Pollutants and their Impact on Respiratory and ...€¦ · Ascarate Park C37 Monitoring Station: The National Ambient Air Quality Standard (NAAQS) for PM 10 and 2.5

Fig Number of registered automobiles in Texas The Statistics show the

number of registered automobiles truck motorcycle in Texas Source

Texas department motor vehicles

Fig More than 61 percent of

US transportation emissionscome from cars and lighttrucks

Fig in US On-roadmobile sourcesconstitute the largestsingle source categoryof air pollution with(327)

Problem Statement

13000000140000001500000016000000170000001800000019000000

Millio

ns

of

Ve

hic

les

Years

Total Growth of Texas Registrations

2001-2012

Total

Vehicles

Registratio

ns

Problem Statement

El Paso Texas and ciudad Juarez currently has commercialmovements through El PasondashCiudad Juarez gateways peaked at715000 trucks in the year 2010 and Approximately 40000 vehicles passthese roads each laborable day

Source US Department of Transportation Bureau of Transportation Statistics 2010

Bridge Number of US-bound

Truck Crossings year 2010

World Trade Bridge 1327479

Pharr ndash Reynosa International Bridge

452821

Ysleta ndash Zaragoza Bridge 379508

Laredo ndash Colombia Solidarity

Bridge

374781

Bridge of the Americas 337609

Veterans International Bridge 177986

Camino Real International Bridge 106423

Del Rio ndash Ciudad Acuna

International Bridge

62966

Progreso International Bridge 42605

Free Trade Bridge 30773

Source CBP

Fig Bridge of the Americas (Puente Cordova)

Publications Review to examine the relationship between exposure to motor vehicle emissions and respiratory and cardiovascular disease

We have analyzed the current literature which have served as the basis for this project

Some studies determined that traffic-related emissions have been recognized as a major contributor to urban air pollution in particular major cities proximity to major roadways and exposure to motor vehicle exhaust and Non-exhaust emissions are associated with increased risks of cardiovascular respiratory and other diseases (Brugge et al 2007 Gan et al 2010 Gauderman et al 2007 Jerrett et al 2009 Laden et al 2007 McConnell et al 2006)

Effect of traffic pollution on respiratory and allergic disease in adults cross-sectional and longitudinal analyses Mar Pujades-Rodriacuteguez Tricia McKeever Sarah Lewis Duncan Whyatt John Britton and Andrea Venn

httpwwwsciencedailycomreleases200811081114081003htm April 2011

Traffic Pollution Increases Asthma in Adults Several research results revealed adults who suffer asthma and were exposed to heavy traffic pollution experienced an 80 per cent increase University of Melbourne Rev Public Health 15 (1994) pp 107ndash132 August 2010

Traffic Pollution Aggravates Symptoms In Asthmatic Children Traffic pollution especially in cities adversely affects respiratory health in children with asthma studies suggest that traffic pollution and diesel particles in particular may have a greater effect on respiratory health than other pollutants httpwwwsciencedailycomreleases200811081114081003htm September 2010

Traffic-related air pollution associated with prevalence of asthma and COPDchronic bronchitis A cross-sectional study in Southern Sweden Anna Lindgren Emilie Stroh Peter Montneacutemery September 2009

Acute respiratory health effects of air pollution on children with asthma in US inner cities Benjamin Vaughn MS Meyer Kattan MD Herman Mitchell PhD May 2008

Comparison of Air QualityndashRelated Mortality Impacts of two Different source of emission Transportation in the United States httpwwwtrborgMainBlurbs166402aspx January 2008

Long-term exposure to traffic-related air pollution and cardiovascular mortality Chen H Goldberg MS Burnett RT Jerrett M Wheeler AJ Villeneuve PJ Source Department of Epidemiology and Biostatistics McGill University Montreal Quebec Canada January 2011

heavy-duty vehicles chemical composition impact of exhaust after treatment and fuel parameters Environ Health Perspect102(suppl 4)13ndash23 (1994)

Particulate Matter

PM is a mixture of solid and liquid particles suspended in the atmosphere

as atmospheric aerosols Mobile Pollutants are formed by chemical

reactions of gaseous components from burning of fossil fuel in vehicles

(Gasoline amp diesel motor vehicles)

Source EPA (2012) United States Environmental Protection Agency

Particulate matter basic information Cited October 30th 2012 Available

online at httpwwwepa govairqualityparticlepollutionbasichtml

Source EPA (2012) United States Environmental Protection Agency Particulate matter basic

information Cited October 30th 2012 Available online at httpwwwepa

govairqualityparticlepollutionbasichtml

PM10 25 Long Term Exposure ndashChronic Health Consequences

These particles are associated with a

variety of problems including

Aggravated asthma Chronic

bronchitis

Decreased lung function

Increased respiratory symptoms

coughing or difficulty breathing

Increased Cardiopulmonary Mortality

Increased Risk of Lung Cancer

Sources of Particulate Matter Emissions from traffic

Diesel exhaust particulate matter

This particulate toxic potential has been associated with serious adverse Health

effects including respiratory symptoms Pulmonary function and cardiovascular

diseases (Geller et al 2006 Bernstein et al 2004)

Brake wear particulate matter

Brake wear particulate matter Chemical content (iron(Fe) copper(Cu) Antimony(Sb) barium(Ba) this type of particulate can cause severe respiratory and cardiovascular damages and it is also known that Sb has been classified as a possible human pulmonary carcinogen by the International Agency for Research on Cancer (IARC 1989 Et al 2013)

Fig images of brake wear particles generated at a road simulation study ( centre lt25 μm right lt10

μm) Source [Kukutschovaacute et al 2011]

Tire wear particulate matter

The tire wear particles of the tires are generated either by frictional forces between the treadand the road pavement The chemical content Fe Cr Pb Ti Cr Cu Zn Sr Y Zr Sn Sb Ba LaCe and Pb)

Fig Examples of near spherical particles PM 10 and 25 which are originate from interaction of tires and pavements Source [Dahl et al 2006]

Study Area

The Paso del Norte (PdN) region Selected two strategic areas of study El Paso County zip code 79905 Urban area and Dona Ana County Zip Code 880218802788072 Rural Restricted urban access (freeways and interstates)

Map of the area of the simulation by the MOVES model in the study area

Geographic Domain Zip Code 79905 Urban Area (El Paso County)

Zip Codes 88021880278807288048 (Dona Ana County)

Urban road Delta Dr St 31o 45rsquo 5637- 106o 27rsquo 1212 10 miles

Cordova Bridge of the Americas 31o 45rsquo 4367- 106o 27rsquo 0506 15 miles

478 Highway interstate 31o 46rsquo 1326- 106o 27rsquo 0327 05 miles

110 Highway interstate 31o 46rsquo 1210- 106o 27rsquo 0066 10 miles

10 Interstate Gateway Blvd 31o 46rsquo 397- 106o 26rsquo 4769 05 miles

Chamizal Loop 478 31o 46rsquo 668- 106o 26rsquo 5456 05 miles

Alameda Loop 20 31o 46rsquo 1323- 106o 27rsquo 0328 10 miles

Paisano Dr St Patriot freeway

route 62

31o 46rsquo 0669- 106o 27rsquo 212 15 miles

St Piedras 31o 46rsquo 1326- 106o 27rsquo 0327 10 miles

Dona Ana County Miles

Interstate 25 32o 23rsquo 0561 -106 48

1054 32o 23rsquo 3434- -

106 48 1054 32o 23rsquo

5660 106 48 4314

50

Geographic domain To obtain the simulation mobile data from modelMOVES2010a was configurated the coordinates selected in the study areas

El Paso County

PM25 Estimation from Aerosol Optical Depth (AOD) using

satellites

We examined the relationship

between Aerosol Optical Depth

(AOD) estimated from satellite data

at 5 km spatial resolution and the

mass of fine particles le25 μm in

aerodynamic diameter (PM25)

monitored on the ground in El PdN

area PM25 data was recorded from

air quality monitoring Chamizal

station (TCEQ) on different periods

Our analysis shows a significant

positive association between AOD

and PM25

Time-series and scatter plots of AOD estimated PM25 and surface PM25

Analysis of the meteorological factors and synoptic conditions leading to a local high

ozone event episode June 12-21 2006

Meteorology plays a critical role in determining atmospheric ozone concentrations A good synoptic scale weather forecast is essential to accurately forecast tropospheric and surface ozone concentrations

Figure 1 The domain configuration and Landuse categories

resolution 25 km domainFigure 2 The Geopotential height at 500 mb Figure 3 depicts the 850 mb at a lower altitude The

white regions observed in the graph correspond to

mountainous areas

Figure 4 Temperature at 2m height

above surface at 22 UTC June 18 2006

36 km resolution

Performance Evaluation

01020304050

Ju

ne

137

130

0

190

0

10

0

Ju

ne

157

130

0

190

0

10

0

Ju

ne

187

130

0

190

0

10

0

Tem

pe

ratu

re (⁰C

)

Local time (Hrs)

C41 June 13-19 2006

WRF_temperature

(⁰C)

TCEQ_temperature

(⁰C)

01020304050

June1

37

100

0

130

0

160

0

190

0

220

0

10

0

40

0

June1

57

100

0

130

0

160

0

190

0

220

0

10

0

40

0

June1

87

100

0

130

0

160

0

190

0

220

0

10

0

40

0

Rel

ativ

e h

um

idit

y (

)

Local time (Hrs)

C41 June 13-19 2006

WRF_rh () TCEQ_relative humidity ()

0

5

10

15

20

June

137 10

13

16

19

22 1 4

June

157 10

13

16

19

22 1 4

June

187 10

13

16

19

22 1 4

Win

d s

pee

d (

ms

Local time(Hrs)

C12 June 13-192006

WRF_wind speed (ms) TCEQ_ wind speed (ms)

We evaluate the WRF modelrsquos performance

by comparing against corresponding

experimental TCEQ data and performing the

required statistical analysis

HYSPLIT Model

HYSPLIT was simulated and showed that the ozone is mostly transported to El Paso from north western and south western US and Mexican regions during the 72 hours duration of the simulation

0

20

40

60

80

100

1200

00

10

02

00

30

04

00

50

06

00

70

08

00

90

01

00

01

10

01

20

01

30

01

40

01

50

01

60

01

70

01

80

01

90

02

00

02

10

02

20

02

30

0

Ho

url

y o

zon

e [

pp

b]

0102030405060708090

00

01

00

20

03

00

40

05

00

60

07

00

80

09

00

10

00

11

00

12

00

13

00

14

00

15

00

16

00

17

00

18

00

19

00

20

00

21

00

22

00

23

00

Ho

url

y o

zon

e [

pp

b]

June 18th June 19th

Performance Evaluation

01020304050

Ju

ne

137

130

0

190

0

10

0

Ju

ne

157

130

0

190

0

10

0

Ju

ne

187

130

0

190

0

10

0

Tem

pe

ratu

re (⁰C

)

Local time (Hrs)

C41 June 13-19 2006

WRF_temperature

(⁰C)

TCEQ_temperature

(⁰C)

0

50

100

150

June1

37

100

0

130

0

160

0

190

0

220

0

10

0

40

0

June1

57

100

0

130

0

160

0

190

0

220

0

10

0

40

0

June1

87

100

0

130

0

160

0

190

0

220

0

10

0

40

0Ozo

ne

(pp

b)

Local time (Hrs)

C41 June 13-19 2006

CAMx_ozone (ppbV) TCEQ_ozone (ppb)

0

10

20

30

40

50

June1

37

100

0

130

0

160

0

190

0

220

0

10

0

40

0

June1

57

100

0

130

0

160

0

190

0

220

0

10

0

40

0

June1

87

100

0

130

0

160

0

190

0

220

0

10

0

40

0

Rel

ativ

e h

um

idit

y (

)

Local time (Hrs)

C41 June 13-19 2006

WRF_rh () TCEQ_relative humidity ()

0

5

10

15

20

June

137 10

13

16

19

22 1 4

June

157 10

13

16

19

22 1 4

June

187 10

13

16

19

22 1 4W

ind

sp

eed

(m

sLocal time(Hrs)

C12 June 13-192006

WRF_wind speed (ms) TCEQ_ wind speed (ms)

Methodology

Medical Data The data by weekly monthly and year for daily emergency room and hospital admission for the respiratory

infections (RD) and cardiovascular diseases (CVD) was extracted from hospitals records located in the El PdN

the system includes data on type of admission primary and secondary causes of admissionRESPIRATORY DISEASE

Bronquitis amp Chronic Bronchitis 466 - 4661 491 - 4919

Asthma 463 - 4939

Emphysema 492

Respiratory failure 51881

HEART DISEASE

Accute Myocardial Infarction 410

Coronary Athersclerosis 4140

Other Ischemic Heart Disease 411-4139 4141-4149

Cardiac Dyshythmias 427

Essential hypertension 401

Acute myocardial infarction 410

Congestive Heart Failure 4280 4282-4284

Hypertensive heart disease 402

Table 1 ICD -9 Codes for Respiratory and Cardiovascular Diseases

0

50

100

150

200

250

300

Wee

k 1

Wee

k 2

Wee

k 3

Wee

k 4

Wee

k 5

Wee

k 6

Wee

k 7

Wee

k 8

Wee

k 9

Wee

k 1

0

Wee

k 1

1

Wee

k 1

2

Wee

k 1

3

Wee

k 1

4

Wee

k 1

5

Wee

k 1

6

Wee

k 1

7

Wee

k 1

8

Wee

k 1

9

Wee

k 2

0

Wee

k 2

1

Mo

rb

idit

y D

isch

arg

e fo

r a

ll R

esp

ira

tory

Dis

ease

IC

D-9

(

Ast

hm

aB

ro

nch

itis

)

Weekly Morbidity Discharges of all the Listed Diagnoses for All

Respiratory Disease During WinterSpring 2010

Asthma-Bronchitis

EPA MOVES Model for Estimating Emission

Inventories

Motor Vehicle Emission Simulator (MOVES 2010b) will be configuredin The El Paso North Region for Calculate five categories of PM10

PM25 total Emission inventories from all on-road traffic over a

variety of scales within periods of time selected weeks months

and years

Moves (Motor Vehicle Emission

Simulator)

The emission model is develop using the current equation to calculate direct traffic emissions from

vehicles in the form of PM is

Eext annual emissions are measured in grams of miles traveled by the vehicle (gVMT )

SL is the road surface loading in (gm2)

W is the average weight in tons of the vehicles on the road

K is the particle size multiplier for particle size range (eg gVMT for PM10 when using grams and miles)

P is the 7 number of wet days with at least 0254 mm of precipitation during the averaging period

N is the number of years considered in the averaging period

C is the particle size specific emissions factor in units of interest vehicle direct exhaust brake wear and tirewear

Modeling Simulation Domain and Emissions Scenarios

For simulations of mobile air quality emission inventories a motor vehicle emission simulator EPA (MOVES 2014a) was used

The modeling use input factors divided into seven section

parameters

On-Road Inventory local data

input

Scale

Geographic Bounds

Traffic intensity

Vehicle Type

Pollutants

Road Type

Fuel Types

Figure Source EPA US Environmental Protection Agency 2012- Moves 2010b Model

EPA Moves 2014a The modeling used input factors divided into six section

parameters On-Road Inventory local data input

Geographic Domains CountyNonattainment Area

Vehicle-Miles Traveled (VMT) is the total number of miles driven by all vehicles withina given time period and geographic area

Average speed range from 25 miles per

hour to 65 miles per hour

Vehicle Classes Motorcycle PassengerCarTruks light-duty Commercial Truck(6001-8500 lbs) Buses heave-duty trucksRefuse trucks School Bus Single UnitShort Haul-truck Single Unit Long Haul-truck Long Haul Truck Heavy-DutyVehicles (26001-33000 lbs)

Pollutants

Road TypeRural restricted Acces(Freeways and interstates) Rural and Restricted Acces Urban Restricted Acces Off-Network

Fuel Types Gasoline Diesel Fuel

Specific Road Types

Two road types for running emission from the MOVES can be

selected

(freeways and interstates)

Interior urban Urban

Figure Source EPA US Environmental Protection Agency 2012- Moves 2010b Model

VehiclesEquipment

This panel show which on-road vehicles will be modeled

Figure Source EPA US Environmental Protection Agency 2012- Moves 2010b Model

Long haul truck Short haul truck Inercity bus Ligth comercial truck

Passenger car Passenger truck Refuse truck

School bus Single unit long haul-truck

Single unit short haul-truck

Transit bus

Motor home

Motorcycle

Based on Department of Transportation Highway MOVES will Estimates Traffic

Emissions from Cars Trucks amp Motorcycles

Output Data Moves 2014a

Inventories of PM 10 25 Mobile Emission from all

on-Road Traffic

Exhaust Emission PM 10 25 gramsmile

Brake Wear Emission PM 10 25 gramsmile

Tire wear Emission PM 10 25 gramsmile

Date of Vehicle miles traveled (VMT) for

Day Week Month Year

Total Vehicle population

Vehicle age distribution

Simulation of Mobile Emission in the El PdN Region Zip Code 79905

Figure Total Emissions from road traffic in El Paso TX Area were estimated for PM10

Exhaust and Non exhaust emission in kilogramsmonth (Source EPA MOVES 2014a)

0

10000

20000

30000

40000

50000

PM

10 k

gM

on

th

Months

Monthly PM 10 Exhaust and Non-Exhaust Mobile Emissions 2010

On-Road Urban Restricted Area Zip Code 79905

Primary Exhaust PM 10 (kg) Primary PM 10 Brakewear (kg)

Primary PM 10 Tirewear (kg)

05000

100001500020000250003000035000400004500050000

PM

25

kg

Mo

nth

Months

Monthly PM 25 Exhaust and Non-Exhaust Mobile Emission 2010

On-Road Urban Restricted Area Zip Code 79905

Primary Exhaust PM 25 (kg) Primary PM 25 Brakewear (kg) Primary PM 25Tirewear (kg)

Figure Total Emissions from road traffic in El Paso TX Area were estimated for PM25

Exhaust and Non exhaust emission in kilogramsmonth (Source EPA MOVES 2014a)

Total Emissions from Road Traffic in El Paso County PM1025 Exhaust and Non exhaust Emission in kilogramsmonth

Taking the interests to the health risks related to PM 1025 mobile emission were simulated

Exhaust and Non-exhaust emissions contribute almost equally to total traffic-related PM1025 Emissions (Querol et al 2004 Bukowiecki et al 2009a Amato et al 2011)

Monthly PM 10 25 Exhaust and Non-Exhaust (BrakewearTirewear) Mobile

Emission 2010 On-Road Urban Restricted Area Zip Code 79905

Figure Total Emissions from road traffic in El Paso TX Area were estimated for PM10 25 Exhaust and Non Exhaust mobile

emission in kilograms per month (Source EPA MOVES)

0

10000

20000

30000

40000

50000

January February March April May June July August September October November December

PM

10

25

(K

ilog

ram

s)

Months

Summary- Monthly PM 10 25 Exhaust and Non-Exhaust Mobile

Emission 2010 On-Road Urban Restricted Area Zip Code 79905

Primary Exhaust PM 10 Primary PM 10 Brakewear Primary PM 10 Tirewear

Primary Exhaust PM 25 Primary PM 25 Brakewear Primary PM 25Tirewear

Exhaust Emissions PM1025 is reaching maximum emission 48000-42000 thousand of Kgmonth followedby Brake wear 29000-5000 thousand kgmonth and Tire wear with 9000-2000 kgmonth The results showthat the emissions of PM derived mainly from Exhaust and Brake are significantly higher in Urban Area

Annual Contribution of Mobile Emission PM 1025 (Kg) Zip Code 79905 El

Paso County 2010

Total Primary

Exhaust _PM10

39

Total Primary

Exhaust _PM25

36

Brakewear

particulate_PM10

18

Tirewear

particulate_PM10

4

Brakewear

particulate_PM25

2

Tirewear

particulate_PM25

1

0

5

10

15

20

25

30

35

40

45

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53

Fig Annual Average PM10 Concentrations at the

Chamizal C41 Station and PM1025 mobile

Concentration Zip code 79905

PM10 TCEQ (μgm3) Total Mobile Emission PM10 (Ugm3)

Fig Exhaust Emission is Contributing Approximately 74 of total

PM1025 Mobile Emissions following of Brake wear with 20 and Tire

wear with 5

Annual Average PM1025 ugm3 Mobile Emissions (Moves) 26 Chamizal C41

Monitoring Station (TCEQ Chamizal Station )

Predicting Mobile Emission and VTM

Estimation The PdN Region 2010

44E+09

46E+09

48E+09

5E+09

52E+09

54E+09

56E+09

58E+09

6E+09

62E+09

0

50000

100000

150000

200000

250000

300000

350000

20

10

20

11

20

12

20

13

20

14

20

15

20

16

20

17

20

18

20

21

20

22

20

23

20

24

20

25

20

26

20

27

20

28

20

29

20

30

EX

HA

US

T

EM

ISS

ION

MO

BIL

E (

KG

YE

AR

)

YEARS

Predict ing Mobile Exhaust Emission and VTM

Estimation

2010 - 2030 e l PdN Area

Total_ Exhaust PM10 Total_ Exhaust PM25 Distance (Miles)

Fig Predicting Mobile Exhaust PM1025 (kgMonth) Emission and VTM Estimation 2010

- 2030 el PdN Area

44E+09

46E+09

48E+09

5E+09

52E+09

54E+09

56E+09

58E+09

6E+09

62E+09

0

5000000

10000000

15000000

20000000

25000000

30000000

20

10

20

11

20

12

20

13

20

14

20

15

20

16

20

17

20

18

20

21

20

22

20

23

20

24

20

25

20

26

20

27

20

28

20

29

20

30

EX

HA

US

T

EM

ISS

ION

MO

BIL

E (

KG

YE

AR

)

YEARS

Predict ing Mobile Exhaust Emission and

VTM Estimation

2010 - 2030 e l PdN Area

CO NO2 NO NOx Distance

Fig Predicting Mobile Exhaust Emission and VTM Estimation

2010 - 2030 el PdN Area in El Paso TX Area were estimated for

Total CO NOx NO2 NO emission in kilograms per year

(Source EPA MOVES 2014a model)

The simulated Exhaust emissions in the future years shows a trend of reduction of this type of emissions in the

future years one factor should be the new hybrid technology is increasing by 476 since 2010 to 2015 and

use of catalytic converters diesel particulate filters and improved fuels and engines Non-exhaustive sources

will increase in the coming years because there is no control in the material of manufacture composed by Fe

Cu and Mn also not to be able to reduce the number of events of braking (Accelerations and decelerations)

45E+09

5E+09

55E+09

6E+09

65E+09

0

50000

100000

150000

200000

250000

201

0

201

1

201

2

201

3

201

4

201

5

201

6

201

7

201

8

202

1

202

2

202

3

202

4

202

5

202

6

202

7

202

8

202

9

203

0

NO

N-

EX

HA

US

T

EM

ISS

ION

MO

BIL

E

(KG

YE

AR

)

YEARS

Predicting Non Exhaust Mobile

Emission and VTM Estimation

2010 - 2030 el PdN Area

Brake_PM10 Tire_PM10 Distance (Miles)

Fig Predicting Mobile Exhaust PM1025 (kgMonth) Emission and VTM

Estimation 2010 - 2030 el PdN Area

Daily Avg PM1025

Levels of PM Mobile Emission Non-Exhaust -Rush Hour Periods Fall 2010 Zip Code

79905

00

100

200

300

400

500

600

Mo

bil

e P

M1

0 (k

g)

Rush Hours

Daily Avg PM10

Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush Hours

Periods 2010 Zip Code 79905

Total Primary Exhaust

_PM10 WinterSpring

Brakewear

particulate_PM10

WinterSpringTirewear particulate_PM10

WinterSpring

Total Primary Exhaust

_PM10 Summer

Brakewear

particulate_PM10 Summer

Tirewear Particulate_PM10

Summer

Total Primary Exhaust

_PM10 Fall

Brakewear

particulate_PM10 Fall

Tirewear particulate_PM10

Fall

00

50

100

150

200

250

300

350

Mo

bil

e P

M2

5 (k

g)

Rush hours

Daily Avg PM25

Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush

Hours Periods 2010 Zip Code 79905

Total Primary Exhaust _PM25

WinterSpring

Brakewear Particulate_PM25

WinterSpring

Tirewear particulate_PM25

WinterSpring

Total Primary Exhaust _PM25

Summer

Brakewear particulate_PM25

Summer

Tirewear particulate_PM25

Summer

Total Primary Exhaust _PM25

Fall

Brakewear particulate_PM25

Fall

Tirewear particulate_PM25

Fall

Figure Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush Hours Figure Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush Hours

GIS EMISSIONS INVENTORY SYSTEM A geographic information system (GIS) was used to established geographic scenarios with processed images of seasonal mobile

emissions in the PdN region Seasonal mapping is visualized for different types of pollutants Brakewear Exhaust and Tyrewear

Fg Graphics of GIS and Seasonal mobile Emission of particulate matter emission inventory Seasonal emission simulations were performed in kilograms and five contributing inputs factors were identified for

modeling 1) On the composition of the particulate material from different sources such as Exhaust and Non exhaust (Brake wear Tirewear) 2) The Vehicles Equipment clasification were selected according to

the use of gasoline and diesel fuel (motorcycle passenger car Light Duty Vehicles Trucks refuse truck Light Duty Vehicles Light Commercial Truck Light Duty Vehicles School Bus)

Winter Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

120354 67860 19065

Spring Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

139767 86702 24463

Summer Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

94747 62481 17630

Fall Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

75510 45542 12596

251 Descriptive Statistics Data Analysis

Weekly Correlation Analysis of Mobile Emission PM10 (Exhaust-Non-Exhaust) and Respiratory

Diagnoses WinterSpring Summer and Fall 2010

0

2

4

6

8

10

0

50

100

150

200

250

300

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21

Mo

rbid

ity

Dis

ch

arg

e

for

all R

esp

ira

tory

Dis

ea

se

ICD

-9

(A

sth

ma

-Bro

nc

hitis

)

WinterSpring Week

Weekly Avg Mobile PM10 Concentrations during

WinterSpring 2010 and its Influence on Respiratory

Diagnoses

Zip Code 79905

Total Medical data ZIP Code 79902

Total Mobile Emission PM10 (Ugm3)

0

1

2

3

4

5

6

7

0

20

40

60

80

100

Mo

rbid

ity

Dis

ch

arg

e

for

all R

esp

ira

tory

Dis

ea

se

ICD

-9

(Ast

hm

aB

ron

ch

itis

)

Weekly Avg Mobile PM10 Concentrations during

Summer 2010 and its Influence on Respiratory

Diagnoses

Summer 2010 Zip Code 79905

Total Mobile Emission PM10

Hospital Admission (Asthma-Bronchitis)

0

2

4

6

8

10

12

0

20

40

60

80

100

120

140

160

180

200

Mo

rbid

ity

dis

ch

arg

es

for

all r

esp

ira

tory

dis

ea

se

Weekly Avg Mobile PM10 Concentrations

during Fall 2010 and its Influence on Respiratory

Diagnoses

Zip Code 79905

Total Medical data ZIP Code 79902

Total Mobile Emission PM10 (Ugm3)

Mobile(Exhaust-Non-

Exhaust) PM10 and

Asthma-Bronchitis)

Linear R

Square

WinterSpring 734 ndash 39

Summer 614 ndash 32

Fall 548 -29

PM10 Mobile emission (Exhaust-Non-Exhaust)contributed significantly

association to the incidence of RD

Weekly Correlation Analysis of PM 25 Mobile Emission (Exhaust-Non-Exhaust)

and Cardiovascular Diagnoses WinterSpring Summer and Fall 2010

0010203040

00500

100015002000

Wee

k 1

Wee

k 2

Wee

k 3

Wee

k 4

Wee

k 5

Wee

k 6

Wee

k 7

Wee

k 8

Wee

k 9

Wee

k 1

0

Wee

k 1

1

Wee

k 1

2

Wee

k 1

3

Wee

k 1

4

Wee

k 1

5

Wee

k 1

6

Wee

k 1

7

Wee

k 1

8

Wee

k 1

9

Wee

k 2

0

Wee

k 2

1

Morb

idit

y d

isch

arg

es f

or

all

card

iovasc

ula

r d

isea

se

Weekly Avg PM25 Mobile Concentrations during

WinterSpring 2010 and its Influence on all Heart

Diagnoses

Zip Code 79905

Total All Heart Disease PM 25 mobile (μgm3)

0010203040

00

500

1000

1500

Mo

rbid

ity

dis

ch

arg

es

for

all

ca

rdio

va

scu

lar

dis

ea

se

Weeks

CORRELATION BETWEEN MOBILE PM25 ugm3

EXPOSURE TO HEART DISEASES SYMPTOMS

SUMMER SEASON 2010

Total All Heart Disease PM 25 mobile (μgm3)

Figure Statistical Analyses of the Relationship Between PM25 Caused by Traffic Emission( 26 of total Emission) with Heart diseases Source Hospital Admissions for Asthma Acute Bronchitis and Heart diseases in El Paso County zip code 79905 from Texas Health Care

Information Council in Austin Texas (Texas Health Care Information Council 2000)

00

10

20

30

40

0

50

100

150

We

ek 3

6

We

ek 3

7

We

ek 3

8

We

ek 3

9

We

ek 4

0

We

ek 4

1

We

ek 4

2

We

ek 4

3

We

ek 4

4

We

ek 4

5

We

ek 4

6

We

ek 4

7

We

ek 4

8

We

ek 4

9

We

ek 5

0

We

ek 5

1

We

ek 5

2

We

ek 5

3

Mo

rbid

ity

dis

ch

arg

es

for

all

ca

rdio

va

scu

lar

dis

ea

se

CORRELATION BETWEEN MOBILE PM25 ugm3

EXPOSURE TO HEART DISEASES SYMPTOMS FALL

SEASON 2010

Total All Heart Disease PM 25 mobile (μgm3)

Mobile(Exhaust-

Non-Exhaust)

PM10 and

Asthma-

Bronchitis)

Linear R

Square

WinterSpring 833 -42

Summer 620 -32

Fall 501-26

PM10 Mobile

emission (Exhaust-

Non-

Exhaust)contribut

ed significantly

association to the

incidence of CVD

Diseases

Monthly Brake Mobile Emission PM1025 kg During year 2010 and its Influence on

Respiratory Diagnoses Zip Code 79905

00200040006000800010000

010000200003000040000

PM

10

Mo

bile

(K

g)

Months

Monthly Brake Mobile Emission PM10 kg during year

2010 and its Influence on Respiratory Diagnoses

Zip Code 79905

Primary PM 10

Brakewear 00100020003000400050006000

0

1000

2000

3000

4000

PM

25

Mo

bil

e(K

g)

Months

Monthly Brake Mobile Emission PM25 during

year 2010 and its Influence on Heart Diagnoses

Zip Code 79905

Primary PM 25

Brakewear

Heart Diseases

Hospital

Admission

Brake Mobile Emission

PM10 kg Asthma-

Bronchitis)

Brake Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=969 Linear Square R=856

Monthly Mobile Exhaust Emission PM1025 During year 2010 and its Influence on

Respiratory Diagnoses Zip Code 79905

0

200

400

600

800

1000

0

10000

20000

30000

40000

50000

1 3 5 7 9 11

PM

10

(K

g m

on

th)

Months

Monthly Mobile Exhaust Emission PM10 during

year 2010 and its Influence on Respiratory

Diagnoses

Zip Code 79905

Primary Exhaust

PM 10

Respiratory Disease

(Asthma

Bronchitis) Hospital

Admission

0

100

200

300

400

500

600

0

10000

20000

30000

40000

50000

1 2 3 4 5 6 7 8 9 101112

PM

25

(K

g m

on

th)

Months

Monthly Exhaust Mobile Emission PM25 during

year 2010 and its Influence on Heart Diagnoses

Zip Code 79905

Primary Exhaust PM

25

Heart Diseases

Hospital Admission

Exhaust Mobile Emission

PM10 kg Asthma-

Bronchitis)

Exhaust Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=929 Linear Square R=831

Monthly Tire wear Mobile Emission PM1025 During year 2010 and its Influence on Heart

Diagnoses Zip Code 79905

0

100

200

300

400

500

600

700

800

900

0

1000

2000

3000

4000

5000

6000

7000

8000

9000

1 2 3 4 5 6 7 8 9 10 11 12

PM

10

(K

g m

on

th)

Months

Monthly Tirewear Mobile Emission PM10 during year 2010

and its Influence on Heart Diagnoses

Zip Code 79905

Primary PM 10 Tirewear

Mobile Emission

Respiratory Disease

(Asthma Bronchitis)

Hospital Admission

0

100

200

300

400

500

600

0

200

400

600

800

1000

1200

1400

1 2 3 4 5 6 7 8 9 10 11 12

PM

25

(K

g m

on

th)

Months

Monthly Tirewear Mobile Emission PM25 during year 2010

and its Influence on Respiratory Diagnoses

Zip Code 79905

Primary PM 25Tirewear

Mobile Emission

Heart Diseases Hospital

Admission

Exhaust Mobile Emission

PM10 kg Asthma-

Bronchitis)

Exhaust Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=769 Linear Square R=715

Dona Ana County Zip Codes

88021880278807288048

Primary

Exhaust

PM 10 Zip

code

79905

Total

Primary

Exhaust

PM10

Dona Ana

Primary

Exhaust

PM 25 Zip

Code

79905

Total

Primary

Exhaust

PM25

Dona Ana

Series1 430378 111773 391915 102123

0

100000

200000

300000

400000

500000

AX

IS T

ITLE

Annual Comparison of the Mobile

Exhaust Emissions El Paso County

and Dona Ana 2010

Primary

PM 10

Brakewea

r Zip code

79905

Brakewea

r

particulat

e_PM10

Dona Ana

Primary

PM 10

Tirewear

Zip code

79905

Tirewear

particulat

e_PM10

Dona Ana

Series1 262585 48573 73754 11864

050000

100000150000200000250000300000

AX

IS T

ITLE

Annual Comparison of the Mobile

Brakewear Emissions El Paso County

and Dona Ana 2010

Figure Comparison of the Annual Mobile Emissions

of Primary PM10 Non-Exhauts (Brake ) from Dona

Ana County New Mexico and El Paso Texas Units

in KgMonth

Figure Comparison of the Annual Mobile Emissions

of Primary PM10-Exhauts Emission from Dona Ana

County New Mexico and El Paso Texas Units in

KgMonth

Primary

PM 25

Brakewe

ar Ziphellip

Brakewe

ar

particula

te_PMhellip

Primary

PM

25Tirewe

ar Ziphellip

Tirewear

particula

te_PM25

Donahellip

Series1 32645 6071 10919 1779

0

10000

20000

30000

40000

AX

IS T

ITLE

Annual Comparison of the

Mobile Exhaust Emissions El Paso

County and Dona Ana 2010

Figure Comparison of the Annual Mobile Emissions

of Primary PM10-Exhauts Emission from Dona Ana

County New Mexico and El Paso Texas Units in

KgMonth

Monthly Mobile Emission PM1025 kg During year 2006

and its Influence on Respiratory Diagnoses Dona Ana

County Zip Code 880218802788072

0

100

200

300

0

5000

10000

15000

Axi

s Ti

tle

Axis Title

Monthly Mobile Exhaust Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Total PrimaryMobile Exhaust_PM10

All Respiratory ICD-9 (AsthmaBronchitis)

050100150200250300

010002000300040005000

Axi

s Ti

tle

Axis Title

Monthly Mobile Brake Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Brakewearparticulate_PM10

All RespiratoryICD -9 (AsthmaBronchitis)

050100150200250300

0200400600800

10001200

Axi

s Ti

tle

Axis Title

Monthly Mobile Tirewear Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Tirewearparticulate_PM10

All Respiratory ICD -9 (AsthmaBronchitis)

Mobile Exhauts

Emission PM10

kg Asthma-

Bronchitis)

Brake Mobile

Emission PM10

kg and Heart

Diagnoses

Tirewear Mobile

Emission PM10

kg and Heart

Diagnoses

Linear Square

R= 951

Linear Square

R=625

Linear Square

R=525

Mobile Exhauts

Emission PM25

kg Asthma-

Bronchitis)

Brake Mobile

Emission PM25

kg and Heart

Diagnoses

Tirewear Mobile

Emission PM25

kg and Heart

Diagnoses

Linear Square

R= 986

Linear Square

R=691

Linear Square

R=601

Results

The results showed that mobile PM emissions in the urban areas close to urban Road and highways is putting at risk public health

and the proportion of diseases attributable to this exposure is potentially large

Brake wear emissions is much lower in freeways due to significantly reduced number of braking events while tire wear is much

higher in areas where studded tires are used The emission of exhaust gases are much higher in areas where there is a high

vehicular traffic

Brake Mobile

Emission PM10 kg

Asthma-Bronchitis)

Brake Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square

R=969

Linear Square

R=856

Exhaust Mobile

Emission PM10 kg

Asthma-Bronchitis)

Exhaust Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square

R=929

Linear Square

R=831

Tirewear Mobile

Emission PM10 kg

Asthma-Bronchitis)

Tirewear Mobile

Emission PM25 kg

and Heart Diagnoses

Linear Square R=769 Linear Square R=715

Brake Mobile

Emission PM10 kg

and Heart

Diagnoses

Brake Mobile

Emission PM25 kg

and Heart

Diagnoses

Exhaust Mobile

Emission PM10 kg

Asthma-Bronchitis)

Linear Square

R=625

Linear Square

R=691

Linear Square R=

951

Exhaust Mobile

Emission PM25 kg

Asthma-

Bronchitis)

Tire wear Mobile

Emission PM10 kg and

Heart Diagnoses

Tirewear Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square R=

986

Linear Square R=525 Linear Square

R=601

El Paso County

Dona Ana

County

BenMAP-CE

In this analysis the Program of Mapping and Analysis of Environmental Benefits-Community Edition

(BenMAP-CE) was used to Estimate the number and economic value of health impacts resulting from changes

in air pollution PM 25 Ugm3 in The El Paso Area

Health and Economic Benefits associated with the Response of PM25 Emission between

Base Year 2010

Number of Mortalities in 2010 Base Year Based on El Paso County Texas Department of State Health Services

Number of Mortalities in 2010 Base Year Based on El Paso County Texas

Department of State Health Services

cause of death

year

2010

Populatio

n

Affected

Backgro

und

Concentr

ation Pollutant

Rollback

Type

Avoided

Deaths

(

Populatio

n)

alzheimers disease 2010 40716 125 PM25

25

microgmAcircsup3

Rollback 9

diseases of the

heart 2010 15834 125 PM25

25

microgmAcircsup3

Rollback 35

influenza and

neumonia 2010 81432 125 PM25

25

microgmAcircsup3

Rollback 18

acute bronchitis

and bronchiolitis 2010 117624 125 PM25

25

microgmAcircsup3

Rollback 26

chronic lower

respiratory diseases 2010 54288 125 PM25

25

microgmAcircsup3

Rollback 12

The Basin-wide decrease in 4 ugm3 PM25 concentration after this

reduction control

Cause of death year 2010

Populatio

n

Affected

Background

Concentrati

on

Reduc

cion

scena

rio Polluta

nt

Rollback

Type

Avoi

ded

Deat

hs

(

Pop

ulati

on)

economic

benefits

analysis $

Alzheimers

disease 2010 121 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 9 12000

Diseases of the

heart 2010 470 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 35 35000

Influenza and

neumonia 2010 242 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 18 42500

Acute bronchitis

and bronchiolitis 2010 349 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 26 95000

Chronic lower

respiratory

diseases 2010 161 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 12 4500

$1 295000

PM25-related Mortalities Based on BenMAP-CE Estimate in 2010 Base Year with change in the concentrations levels

Health and Economic Benefits associated with the Response of PM25 Emission between

Base Year 2010 Increasing 7 Ugm3

Cause of death year 2010

Population

Affected

Deaths

avoided by

attaining 195

μgm3

standard

Background

Concentrati

on

Pollut

ant

Rollback

Type

Avoided

Deaths (

Populatio

n)

econo

mic

Unben

efits

analysi

s

Alzheimers

disease 2010 4524 195 PM25

25

microgmAcircsup3

Rollback 19 150000

Diseases of the

heart 2010 20358 195 PM25

25

microgmAcircsup3

Rollback 135 450000

Influenza and

neumonia 2010 126672 195 PM25

25

microgmAcircsup3

Rollback 38 525000

Acute bronchitis

and bronchiolitis 2010 162864 195 PM25

25

microgmAcircsup3

Rollback 36 122000

Chronic lower

respiratory

diseases 2010 99528 195 PM25

25

microgmAcircsup3

Rollback 12 650000

Conclusions

An excellent Pearson Correlation was established to analyze the relationship in the relative risks of hospitalization of Respiratory(RD) and cardiovascular (CVD) associated with ambient exposure caused by traffic emission in relation to their size andspecific sources of emission on different scenarios interior a border Urban Rural Urban restricted access (freeways andinterstates)

A significant correlation of PM1025 exposure from mobile emission and hospital admissions for selected Respiratory (RD) andcardiovascular (CVD) diagnoses was established The results showed that PM emissions in urban restricted access (freeways andinterstates) is mainly caused by traffic Therefore people living close to highways are more exposed higher vehicular emissions

Conclusions

We found statistically significant associations between mobile PM25 caused by traffic emission with Respiratory and Cardiovascular Diseases in the study areaSubsequently a correlation between cardio-respiratory mortality is established

A significant correlation of PM1025 exposure from mobile emission and hospital admissions for selected Respiratory (RD) and cardiovascular (CVD) diagnoses isestablished The results showed that PM emissions in urban restricted access (freeways and interstates) is mainly caused by traffic Therefore people living close tohighways receive higher vehicular emissions

The table shows the percentage of PM mobile exposure in the analyzed areas contributing to increase the risk of Respiratory and Cardiovascular Diseases

An examination was conducted of the synoptic and local meteorology for the June 2006 ozone episode using the WRF model to determine how meteorological parametersinfluence the formation transport and dispersion of ozone in the PdN The predominant synoptic feature of the ozone event day was the expansion intensification and slowprogression of an upper-level ridge of high pressure The high ozone episodes are associated with highly stable atmospheres strong temperature inversions with low mixingheights and therefore low mixing volumes Under these conditions emissions such as NOx lead to highly polluted conditions that favor ozone formation

BenMAP Conclusions

We have estimated the number and economic value of health impacts resulting

from changes in air pollution concentrations of PM 25 in the PdN region

Reduction of Pm 25 4 UGm3= Avoided 213 cases respiratory cardiovascular

diseses and Economic Benefits associated with the Response of PM25 Emission + $

1295000

Increase of PM25 7 ugm3 = increasing Dies= 326 economic Unbenefits= 2345000$

Bibliography

1 Dockery DW Pope CAI Xu X Spengler JD Ware JH Fay ME Ferris BG Speizer FE An association between air pollution and mortality in six US cities N Engl J Med 3291753ndash1759 (1993)

2 Samet JM Dominici F Curriero FC Coursac I Zeger SL Fine particulate air pollution and mortality in 20 US cities 1987ndash1994 N Engl J Med 3431742ndash1749 (2000)

3 Nel AE Diaz-Sanchez D Li N The role of particulate pollutants in pulmonary inflammation and asthma evidence for the involvement of organic chemicals and oxidative stress Curr Opin Pulm Med 20017 20ndash26

4 Westerholm R Karl-Erik E Exhaust emissions from lightand heavy-duty vehicles chemical composition impact of exhaust after treatment and fuel parameters Environ Health Perspect 102(suppl 4)13ndash23 (1994)

5 Bascom R Bromberg P Costa D Delvin R Dockery D Frampton M Lambert W Samet J Speizer F Utell

6 Health effects of outdoor air pollution Am J Respir Crit Care Med 1533ndash50 (1996)

7 Chow JC Watson JG Frazier CA Egami RT Goodrich A Ralph C Spatial and temporal source contributions to

8 PM10 and PM25 in Reno NV In PM-10 Implementation of Standards Transactions An APCAEPA International Speciality Conference San Francisco CA (Mathal CV Stonefield DH eds) PittsburghAPCA 1988439ndash457

9 overview In Particulate Matter Health and Regulatory Issues VIP-49 Proceedings of an International Specialty Conference 4ndash6 April 1995 Pittsburgh PA PittsburghAir and Waste Management Association 1995577ndash598

10 Kunzli N Kaiser R Medina S Studnicka M Chanel O

11 Filliger P Herry M Horak F Jr Puybonnieux-Texier V Quenel P et al Public-health impact of outdoor and traffic- related air pollution a European assessment Lancet 356795ndash801 (2000)

Bibliography

1 Sioutas C Delfino RJ Singh M Exposure assessment for atmospheric ultrafine particles (UFP) and implications in epidemiological research Environ Health Perspect 2005113947ndash955

2 Mosleh M Blau PJ Dumitrescu D (2004) Characteristics and morphology of wear particles from laboratory testing of disc brake materials Wear 2561128ndash1134

3 Kuumlnzli N et al (2000) Public-health impact of outdoor and traffi c-related air pollution a European assessment Lancet 356(9232)795ndash801

4 Dora C Phillips M eds (2000) Transport environment and health Copenhagen WHO Regional Office for Europe (WHO Regional Publications European Series No 89 httpwwweurowhointdocumente72015pdf accessed 26 November 2004)

5 Westerholm R Karl-Erik E Exhaust emissions from lightand

6 heavy-duty vehicles chemical composition impact of exhaust after treatment and fuel parameters Environ Health Perspect 102(suppl 4)13ndash23 (1994)

7 Fauser Tjell Mosbaek pigegaard Quantification of tire-Tread particles using extractable Organic Zinc as a Tracer Rubber Chemistry and Technology 1999 969Table shows some literature estimates of the contribution of tire wear to PM10 in air (Panko et al 2013) Gustafsson M Blomqvist G Gudmundsson A Dahl A Swietlicki E Bohgard M Lindbom J Ljungman A

8 Chen Y Shah N Huggins FE and Huffman GP (2006) Microanalysis of Ambient Particles from Lexington Ky by Electron Microscopy Atmos Environ 40 651ndash663

9 Donaldson K Tran CL Jimenez LA Duffin R Newby DE and Mills N (2005) Combustion-derived Nanoparticles A Review of Their Toxicology Following Inhalation Exposure Part Fibre Toxicol 2 10ndash23

10 Su D Serafino A Muller JO Jentoft RE Schlogl R and Fiorito S (2008) Cytotoxicity and Inflammatory Potential of Soot Particles of Low-emission Diesel Engines Environ Sci Technol 42 1761ndash1765

11 Maier KL Alessandrini F Beck-Speier I Hofer TPJ Diabatґe S Bitterle E Stoger T and Jakob T (2008) Health Effects of Ambient Particulate Matter-Biological Mechanisms and Inflammatory Responses to in Vitroand in Vivo Particle Exposures Inhalation Toxicol 20 319ndash337

Page 10: Studies of Air Pollutants and their Impact on Respiratory and ...€¦ · Ascarate Park C37 Monitoring Station: The National Ambient Air Quality Standard (NAAQS) for PM 10 and 2.5

Problem Statement

El Paso Texas and ciudad Juarez currently has commercialmovements through El PasondashCiudad Juarez gateways peaked at715000 trucks in the year 2010 and Approximately 40000 vehicles passthese roads each laborable day

Source US Department of Transportation Bureau of Transportation Statistics 2010

Bridge Number of US-bound

Truck Crossings year 2010

World Trade Bridge 1327479

Pharr ndash Reynosa International Bridge

452821

Ysleta ndash Zaragoza Bridge 379508

Laredo ndash Colombia Solidarity

Bridge

374781

Bridge of the Americas 337609

Veterans International Bridge 177986

Camino Real International Bridge 106423

Del Rio ndash Ciudad Acuna

International Bridge

62966

Progreso International Bridge 42605

Free Trade Bridge 30773

Source CBP

Fig Bridge of the Americas (Puente Cordova)

Publications Review to examine the relationship between exposure to motor vehicle emissions and respiratory and cardiovascular disease

We have analyzed the current literature which have served as the basis for this project

Some studies determined that traffic-related emissions have been recognized as a major contributor to urban air pollution in particular major cities proximity to major roadways and exposure to motor vehicle exhaust and Non-exhaust emissions are associated with increased risks of cardiovascular respiratory and other diseases (Brugge et al 2007 Gan et al 2010 Gauderman et al 2007 Jerrett et al 2009 Laden et al 2007 McConnell et al 2006)

Effect of traffic pollution on respiratory and allergic disease in adults cross-sectional and longitudinal analyses Mar Pujades-Rodriacuteguez Tricia McKeever Sarah Lewis Duncan Whyatt John Britton and Andrea Venn

httpwwwsciencedailycomreleases200811081114081003htm April 2011

Traffic Pollution Increases Asthma in Adults Several research results revealed adults who suffer asthma and were exposed to heavy traffic pollution experienced an 80 per cent increase University of Melbourne Rev Public Health 15 (1994) pp 107ndash132 August 2010

Traffic Pollution Aggravates Symptoms In Asthmatic Children Traffic pollution especially in cities adversely affects respiratory health in children with asthma studies suggest that traffic pollution and diesel particles in particular may have a greater effect on respiratory health than other pollutants httpwwwsciencedailycomreleases200811081114081003htm September 2010

Traffic-related air pollution associated with prevalence of asthma and COPDchronic bronchitis A cross-sectional study in Southern Sweden Anna Lindgren Emilie Stroh Peter Montneacutemery September 2009

Acute respiratory health effects of air pollution on children with asthma in US inner cities Benjamin Vaughn MS Meyer Kattan MD Herman Mitchell PhD May 2008

Comparison of Air QualityndashRelated Mortality Impacts of two Different source of emission Transportation in the United States httpwwwtrborgMainBlurbs166402aspx January 2008

Long-term exposure to traffic-related air pollution and cardiovascular mortality Chen H Goldberg MS Burnett RT Jerrett M Wheeler AJ Villeneuve PJ Source Department of Epidemiology and Biostatistics McGill University Montreal Quebec Canada January 2011

heavy-duty vehicles chemical composition impact of exhaust after treatment and fuel parameters Environ Health Perspect102(suppl 4)13ndash23 (1994)

Particulate Matter

PM is a mixture of solid and liquid particles suspended in the atmosphere

as atmospheric aerosols Mobile Pollutants are formed by chemical

reactions of gaseous components from burning of fossil fuel in vehicles

(Gasoline amp diesel motor vehicles)

Source EPA (2012) United States Environmental Protection Agency

Particulate matter basic information Cited October 30th 2012 Available

online at httpwwwepa govairqualityparticlepollutionbasichtml

Source EPA (2012) United States Environmental Protection Agency Particulate matter basic

information Cited October 30th 2012 Available online at httpwwwepa

govairqualityparticlepollutionbasichtml

PM10 25 Long Term Exposure ndashChronic Health Consequences

These particles are associated with a

variety of problems including

Aggravated asthma Chronic

bronchitis

Decreased lung function

Increased respiratory symptoms

coughing or difficulty breathing

Increased Cardiopulmonary Mortality

Increased Risk of Lung Cancer

Sources of Particulate Matter Emissions from traffic

Diesel exhaust particulate matter

This particulate toxic potential has been associated with serious adverse Health

effects including respiratory symptoms Pulmonary function and cardiovascular

diseases (Geller et al 2006 Bernstein et al 2004)

Brake wear particulate matter

Brake wear particulate matter Chemical content (iron(Fe) copper(Cu) Antimony(Sb) barium(Ba) this type of particulate can cause severe respiratory and cardiovascular damages and it is also known that Sb has been classified as a possible human pulmonary carcinogen by the International Agency for Research on Cancer (IARC 1989 Et al 2013)

Fig images of brake wear particles generated at a road simulation study ( centre lt25 μm right lt10

μm) Source [Kukutschovaacute et al 2011]

Tire wear particulate matter

The tire wear particles of the tires are generated either by frictional forces between the treadand the road pavement The chemical content Fe Cr Pb Ti Cr Cu Zn Sr Y Zr Sn Sb Ba LaCe and Pb)

Fig Examples of near spherical particles PM 10 and 25 which are originate from interaction of tires and pavements Source [Dahl et al 2006]

Study Area

The Paso del Norte (PdN) region Selected two strategic areas of study El Paso County zip code 79905 Urban area and Dona Ana County Zip Code 880218802788072 Rural Restricted urban access (freeways and interstates)

Map of the area of the simulation by the MOVES model in the study area

Geographic Domain Zip Code 79905 Urban Area (El Paso County)

Zip Codes 88021880278807288048 (Dona Ana County)

Urban road Delta Dr St 31o 45rsquo 5637- 106o 27rsquo 1212 10 miles

Cordova Bridge of the Americas 31o 45rsquo 4367- 106o 27rsquo 0506 15 miles

478 Highway interstate 31o 46rsquo 1326- 106o 27rsquo 0327 05 miles

110 Highway interstate 31o 46rsquo 1210- 106o 27rsquo 0066 10 miles

10 Interstate Gateway Blvd 31o 46rsquo 397- 106o 26rsquo 4769 05 miles

Chamizal Loop 478 31o 46rsquo 668- 106o 26rsquo 5456 05 miles

Alameda Loop 20 31o 46rsquo 1323- 106o 27rsquo 0328 10 miles

Paisano Dr St Patriot freeway

route 62

31o 46rsquo 0669- 106o 27rsquo 212 15 miles

St Piedras 31o 46rsquo 1326- 106o 27rsquo 0327 10 miles

Dona Ana County Miles

Interstate 25 32o 23rsquo 0561 -106 48

1054 32o 23rsquo 3434- -

106 48 1054 32o 23rsquo

5660 106 48 4314

50

Geographic domain To obtain the simulation mobile data from modelMOVES2010a was configurated the coordinates selected in the study areas

El Paso County

PM25 Estimation from Aerosol Optical Depth (AOD) using

satellites

We examined the relationship

between Aerosol Optical Depth

(AOD) estimated from satellite data

at 5 km spatial resolution and the

mass of fine particles le25 μm in

aerodynamic diameter (PM25)

monitored on the ground in El PdN

area PM25 data was recorded from

air quality monitoring Chamizal

station (TCEQ) on different periods

Our analysis shows a significant

positive association between AOD

and PM25

Time-series and scatter plots of AOD estimated PM25 and surface PM25

Analysis of the meteorological factors and synoptic conditions leading to a local high

ozone event episode June 12-21 2006

Meteorology plays a critical role in determining atmospheric ozone concentrations A good synoptic scale weather forecast is essential to accurately forecast tropospheric and surface ozone concentrations

Figure 1 The domain configuration and Landuse categories

resolution 25 km domainFigure 2 The Geopotential height at 500 mb Figure 3 depicts the 850 mb at a lower altitude The

white regions observed in the graph correspond to

mountainous areas

Figure 4 Temperature at 2m height

above surface at 22 UTC June 18 2006

36 km resolution

Performance Evaluation

01020304050

Ju

ne

137

130

0

190

0

10

0

Ju

ne

157

130

0

190

0

10

0

Ju

ne

187

130

0

190

0

10

0

Tem

pe

ratu

re (⁰C

)

Local time (Hrs)

C41 June 13-19 2006

WRF_temperature

(⁰C)

TCEQ_temperature

(⁰C)

01020304050

June1

37

100

0

130

0

160

0

190

0

220

0

10

0

40

0

June1

57

100

0

130

0

160

0

190

0

220

0

10

0

40

0

June1

87

100

0

130

0

160

0

190

0

220

0

10

0

40

0

Rel

ativ

e h

um

idit

y (

)

Local time (Hrs)

C41 June 13-19 2006

WRF_rh () TCEQ_relative humidity ()

0

5

10

15

20

June

137 10

13

16

19

22 1 4

June

157 10

13

16

19

22 1 4

June

187 10

13

16

19

22 1 4

Win

d s

pee

d (

ms

Local time(Hrs)

C12 June 13-192006

WRF_wind speed (ms) TCEQ_ wind speed (ms)

We evaluate the WRF modelrsquos performance

by comparing against corresponding

experimental TCEQ data and performing the

required statistical analysis

HYSPLIT Model

HYSPLIT was simulated and showed that the ozone is mostly transported to El Paso from north western and south western US and Mexican regions during the 72 hours duration of the simulation

0

20

40

60

80

100

1200

00

10

02

00

30

04

00

50

06

00

70

08

00

90

01

00

01

10

01

20

01

30

01

40

01

50

01

60

01

70

01

80

01

90

02

00

02

10

02

20

02

30

0

Ho

url

y o

zon

e [

pp

b]

0102030405060708090

00

01

00

20

03

00

40

05

00

60

07

00

80

09

00

10

00

11

00

12

00

13

00

14

00

15

00

16

00

17

00

18

00

19

00

20

00

21

00

22

00

23

00

Ho

url

y o

zon

e [

pp

b]

June 18th June 19th

Performance Evaluation

01020304050

Ju

ne

137

130

0

190

0

10

0

Ju

ne

157

130

0

190

0

10

0

Ju

ne

187

130

0

190

0

10

0

Tem

pe

ratu

re (⁰C

)

Local time (Hrs)

C41 June 13-19 2006

WRF_temperature

(⁰C)

TCEQ_temperature

(⁰C)

0

50

100

150

June1

37

100

0

130

0

160

0

190

0

220

0

10

0

40

0

June1

57

100

0

130

0

160

0

190

0

220

0

10

0

40

0

June1

87

100

0

130

0

160

0

190

0

220

0

10

0

40

0Ozo

ne

(pp

b)

Local time (Hrs)

C41 June 13-19 2006

CAMx_ozone (ppbV) TCEQ_ozone (ppb)

0

10

20

30

40

50

June1

37

100

0

130

0

160

0

190

0

220

0

10

0

40

0

June1

57

100

0

130

0

160

0

190

0

220

0

10

0

40

0

June1

87

100

0

130

0

160

0

190

0

220

0

10

0

40

0

Rel

ativ

e h

um

idit

y (

)

Local time (Hrs)

C41 June 13-19 2006

WRF_rh () TCEQ_relative humidity ()

0

5

10

15

20

June

137 10

13

16

19

22 1 4

June

157 10

13

16

19

22 1 4

June

187 10

13

16

19

22 1 4W

ind

sp

eed

(m

sLocal time(Hrs)

C12 June 13-192006

WRF_wind speed (ms) TCEQ_ wind speed (ms)

Methodology

Medical Data The data by weekly monthly and year for daily emergency room and hospital admission for the respiratory

infections (RD) and cardiovascular diseases (CVD) was extracted from hospitals records located in the El PdN

the system includes data on type of admission primary and secondary causes of admissionRESPIRATORY DISEASE

Bronquitis amp Chronic Bronchitis 466 - 4661 491 - 4919

Asthma 463 - 4939

Emphysema 492

Respiratory failure 51881

HEART DISEASE

Accute Myocardial Infarction 410

Coronary Athersclerosis 4140

Other Ischemic Heart Disease 411-4139 4141-4149

Cardiac Dyshythmias 427

Essential hypertension 401

Acute myocardial infarction 410

Congestive Heart Failure 4280 4282-4284

Hypertensive heart disease 402

Table 1 ICD -9 Codes for Respiratory and Cardiovascular Diseases

0

50

100

150

200

250

300

Wee

k 1

Wee

k 2

Wee

k 3

Wee

k 4

Wee

k 5

Wee

k 6

Wee

k 7

Wee

k 8

Wee

k 9

Wee

k 1

0

Wee

k 1

1

Wee

k 1

2

Wee

k 1

3

Wee

k 1

4

Wee

k 1

5

Wee

k 1

6

Wee

k 1

7

Wee

k 1

8

Wee

k 1

9

Wee

k 2

0

Wee

k 2

1

Mo

rb

idit

y D

isch

arg

e fo

r a

ll R

esp

ira

tory

Dis

ease

IC

D-9

(

Ast

hm

aB

ro

nch

itis

)

Weekly Morbidity Discharges of all the Listed Diagnoses for All

Respiratory Disease During WinterSpring 2010

Asthma-Bronchitis

EPA MOVES Model for Estimating Emission

Inventories

Motor Vehicle Emission Simulator (MOVES 2010b) will be configuredin The El Paso North Region for Calculate five categories of PM10

PM25 total Emission inventories from all on-road traffic over a

variety of scales within periods of time selected weeks months

and years

Moves (Motor Vehicle Emission

Simulator)

The emission model is develop using the current equation to calculate direct traffic emissions from

vehicles in the form of PM is

Eext annual emissions are measured in grams of miles traveled by the vehicle (gVMT )

SL is the road surface loading in (gm2)

W is the average weight in tons of the vehicles on the road

K is the particle size multiplier for particle size range (eg gVMT for PM10 when using grams and miles)

P is the 7 number of wet days with at least 0254 mm of precipitation during the averaging period

N is the number of years considered in the averaging period

C is the particle size specific emissions factor in units of interest vehicle direct exhaust brake wear and tirewear

Modeling Simulation Domain and Emissions Scenarios

For simulations of mobile air quality emission inventories a motor vehicle emission simulator EPA (MOVES 2014a) was used

The modeling use input factors divided into seven section

parameters

On-Road Inventory local data

input

Scale

Geographic Bounds

Traffic intensity

Vehicle Type

Pollutants

Road Type

Fuel Types

Figure Source EPA US Environmental Protection Agency 2012- Moves 2010b Model

EPA Moves 2014a The modeling used input factors divided into six section

parameters On-Road Inventory local data input

Geographic Domains CountyNonattainment Area

Vehicle-Miles Traveled (VMT) is the total number of miles driven by all vehicles withina given time period and geographic area

Average speed range from 25 miles per

hour to 65 miles per hour

Vehicle Classes Motorcycle PassengerCarTruks light-duty Commercial Truck(6001-8500 lbs) Buses heave-duty trucksRefuse trucks School Bus Single UnitShort Haul-truck Single Unit Long Haul-truck Long Haul Truck Heavy-DutyVehicles (26001-33000 lbs)

Pollutants

Road TypeRural restricted Acces(Freeways and interstates) Rural and Restricted Acces Urban Restricted Acces Off-Network

Fuel Types Gasoline Diesel Fuel

Specific Road Types

Two road types for running emission from the MOVES can be

selected

(freeways and interstates)

Interior urban Urban

Figure Source EPA US Environmental Protection Agency 2012- Moves 2010b Model

VehiclesEquipment

This panel show which on-road vehicles will be modeled

Figure Source EPA US Environmental Protection Agency 2012- Moves 2010b Model

Long haul truck Short haul truck Inercity bus Ligth comercial truck

Passenger car Passenger truck Refuse truck

School bus Single unit long haul-truck

Single unit short haul-truck

Transit bus

Motor home

Motorcycle

Based on Department of Transportation Highway MOVES will Estimates Traffic

Emissions from Cars Trucks amp Motorcycles

Output Data Moves 2014a

Inventories of PM 10 25 Mobile Emission from all

on-Road Traffic

Exhaust Emission PM 10 25 gramsmile

Brake Wear Emission PM 10 25 gramsmile

Tire wear Emission PM 10 25 gramsmile

Date of Vehicle miles traveled (VMT) for

Day Week Month Year

Total Vehicle population

Vehicle age distribution

Simulation of Mobile Emission in the El PdN Region Zip Code 79905

Figure Total Emissions from road traffic in El Paso TX Area were estimated for PM10

Exhaust and Non exhaust emission in kilogramsmonth (Source EPA MOVES 2014a)

0

10000

20000

30000

40000

50000

PM

10 k

gM

on

th

Months

Monthly PM 10 Exhaust and Non-Exhaust Mobile Emissions 2010

On-Road Urban Restricted Area Zip Code 79905

Primary Exhaust PM 10 (kg) Primary PM 10 Brakewear (kg)

Primary PM 10 Tirewear (kg)

05000

100001500020000250003000035000400004500050000

PM

25

kg

Mo

nth

Months

Monthly PM 25 Exhaust and Non-Exhaust Mobile Emission 2010

On-Road Urban Restricted Area Zip Code 79905

Primary Exhaust PM 25 (kg) Primary PM 25 Brakewear (kg) Primary PM 25Tirewear (kg)

Figure Total Emissions from road traffic in El Paso TX Area were estimated for PM25

Exhaust and Non exhaust emission in kilogramsmonth (Source EPA MOVES 2014a)

Total Emissions from Road Traffic in El Paso County PM1025 Exhaust and Non exhaust Emission in kilogramsmonth

Taking the interests to the health risks related to PM 1025 mobile emission were simulated

Exhaust and Non-exhaust emissions contribute almost equally to total traffic-related PM1025 Emissions (Querol et al 2004 Bukowiecki et al 2009a Amato et al 2011)

Monthly PM 10 25 Exhaust and Non-Exhaust (BrakewearTirewear) Mobile

Emission 2010 On-Road Urban Restricted Area Zip Code 79905

Figure Total Emissions from road traffic in El Paso TX Area were estimated for PM10 25 Exhaust and Non Exhaust mobile

emission in kilograms per month (Source EPA MOVES)

0

10000

20000

30000

40000

50000

January February March April May June July August September October November December

PM

10

25

(K

ilog

ram

s)

Months

Summary- Monthly PM 10 25 Exhaust and Non-Exhaust Mobile

Emission 2010 On-Road Urban Restricted Area Zip Code 79905

Primary Exhaust PM 10 Primary PM 10 Brakewear Primary PM 10 Tirewear

Primary Exhaust PM 25 Primary PM 25 Brakewear Primary PM 25Tirewear

Exhaust Emissions PM1025 is reaching maximum emission 48000-42000 thousand of Kgmonth followedby Brake wear 29000-5000 thousand kgmonth and Tire wear with 9000-2000 kgmonth The results showthat the emissions of PM derived mainly from Exhaust and Brake are significantly higher in Urban Area

Annual Contribution of Mobile Emission PM 1025 (Kg) Zip Code 79905 El

Paso County 2010

Total Primary

Exhaust _PM10

39

Total Primary

Exhaust _PM25

36

Brakewear

particulate_PM10

18

Tirewear

particulate_PM10

4

Brakewear

particulate_PM25

2

Tirewear

particulate_PM25

1

0

5

10

15

20

25

30

35

40

45

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53

Fig Annual Average PM10 Concentrations at the

Chamizal C41 Station and PM1025 mobile

Concentration Zip code 79905

PM10 TCEQ (μgm3) Total Mobile Emission PM10 (Ugm3)

Fig Exhaust Emission is Contributing Approximately 74 of total

PM1025 Mobile Emissions following of Brake wear with 20 and Tire

wear with 5

Annual Average PM1025 ugm3 Mobile Emissions (Moves) 26 Chamizal C41

Monitoring Station (TCEQ Chamizal Station )

Predicting Mobile Emission and VTM

Estimation The PdN Region 2010

44E+09

46E+09

48E+09

5E+09

52E+09

54E+09

56E+09

58E+09

6E+09

62E+09

0

50000

100000

150000

200000

250000

300000

350000

20

10

20

11

20

12

20

13

20

14

20

15

20

16

20

17

20

18

20

21

20

22

20

23

20

24

20

25

20

26

20

27

20

28

20

29

20

30

EX

HA

US

T

EM

ISS

ION

MO

BIL

E (

KG

YE

AR

)

YEARS

Predict ing Mobile Exhaust Emission and VTM

Estimation

2010 - 2030 e l PdN Area

Total_ Exhaust PM10 Total_ Exhaust PM25 Distance (Miles)

Fig Predicting Mobile Exhaust PM1025 (kgMonth) Emission and VTM Estimation 2010

- 2030 el PdN Area

44E+09

46E+09

48E+09

5E+09

52E+09

54E+09

56E+09

58E+09

6E+09

62E+09

0

5000000

10000000

15000000

20000000

25000000

30000000

20

10

20

11

20

12

20

13

20

14

20

15

20

16

20

17

20

18

20

21

20

22

20

23

20

24

20

25

20

26

20

27

20

28

20

29

20

30

EX

HA

US

T

EM

ISS

ION

MO

BIL

E (

KG

YE

AR

)

YEARS

Predict ing Mobile Exhaust Emission and

VTM Estimation

2010 - 2030 e l PdN Area

CO NO2 NO NOx Distance

Fig Predicting Mobile Exhaust Emission and VTM Estimation

2010 - 2030 el PdN Area in El Paso TX Area were estimated for

Total CO NOx NO2 NO emission in kilograms per year

(Source EPA MOVES 2014a model)

The simulated Exhaust emissions in the future years shows a trend of reduction of this type of emissions in the

future years one factor should be the new hybrid technology is increasing by 476 since 2010 to 2015 and

use of catalytic converters diesel particulate filters and improved fuels and engines Non-exhaustive sources

will increase in the coming years because there is no control in the material of manufacture composed by Fe

Cu and Mn also not to be able to reduce the number of events of braking (Accelerations and decelerations)

45E+09

5E+09

55E+09

6E+09

65E+09

0

50000

100000

150000

200000

250000

201

0

201

1

201

2

201

3

201

4

201

5

201

6

201

7

201

8

202

1

202

2

202

3

202

4

202

5

202

6

202

7

202

8

202

9

203

0

NO

N-

EX

HA

US

T

EM

ISS

ION

MO

BIL

E

(KG

YE

AR

)

YEARS

Predicting Non Exhaust Mobile

Emission and VTM Estimation

2010 - 2030 el PdN Area

Brake_PM10 Tire_PM10 Distance (Miles)

Fig Predicting Mobile Exhaust PM1025 (kgMonth) Emission and VTM

Estimation 2010 - 2030 el PdN Area

Daily Avg PM1025

Levels of PM Mobile Emission Non-Exhaust -Rush Hour Periods Fall 2010 Zip Code

79905

00

100

200

300

400

500

600

Mo

bil

e P

M1

0 (k

g)

Rush Hours

Daily Avg PM10

Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush Hours

Periods 2010 Zip Code 79905

Total Primary Exhaust

_PM10 WinterSpring

Brakewear

particulate_PM10

WinterSpringTirewear particulate_PM10

WinterSpring

Total Primary Exhaust

_PM10 Summer

Brakewear

particulate_PM10 Summer

Tirewear Particulate_PM10

Summer

Total Primary Exhaust

_PM10 Fall

Brakewear

particulate_PM10 Fall

Tirewear particulate_PM10

Fall

00

50

100

150

200

250

300

350

Mo

bil

e P

M2

5 (k

g)

Rush hours

Daily Avg PM25

Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush

Hours Periods 2010 Zip Code 79905

Total Primary Exhaust _PM25

WinterSpring

Brakewear Particulate_PM25

WinterSpring

Tirewear particulate_PM25

WinterSpring

Total Primary Exhaust _PM25

Summer

Brakewear particulate_PM25

Summer

Tirewear particulate_PM25

Summer

Total Primary Exhaust _PM25

Fall

Brakewear particulate_PM25

Fall

Tirewear particulate_PM25

Fall

Figure Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush Hours Figure Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush Hours

GIS EMISSIONS INVENTORY SYSTEM A geographic information system (GIS) was used to established geographic scenarios with processed images of seasonal mobile

emissions in the PdN region Seasonal mapping is visualized for different types of pollutants Brakewear Exhaust and Tyrewear

Fg Graphics of GIS and Seasonal mobile Emission of particulate matter emission inventory Seasonal emission simulations were performed in kilograms and five contributing inputs factors were identified for

modeling 1) On the composition of the particulate material from different sources such as Exhaust and Non exhaust (Brake wear Tirewear) 2) The Vehicles Equipment clasification were selected according to

the use of gasoline and diesel fuel (motorcycle passenger car Light Duty Vehicles Trucks refuse truck Light Duty Vehicles Light Commercial Truck Light Duty Vehicles School Bus)

Winter Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

120354 67860 19065

Spring Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

139767 86702 24463

Summer Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

94747 62481 17630

Fall Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

75510 45542 12596

251 Descriptive Statistics Data Analysis

Weekly Correlation Analysis of Mobile Emission PM10 (Exhaust-Non-Exhaust) and Respiratory

Diagnoses WinterSpring Summer and Fall 2010

0

2

4

6

8

10

0

50

100

150

200

250

300

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21

Mo

rbid

ity

Dis

ch

arg

e

for

all R

esp

ira

tory

Dis

ea

se

ICD

-9

(A

sth

ma

-Bro

nc

hitis

)

WinterSpring Week

Weekly Avg Mobile PM10 Concentrations during

WinterSpring 2010 and its Influence on Respiratory

Diagnoses

Zip Code 79905

Total Medical data ZIP Code 79902

Total Mobile Emission PM10 (Ugm3)

0

1

2

3

4

5

6

7

0

20

40

60

80

100

Mo

rbid

ity

Dis

ch

arg

e

for

all R

esp

ira

tory

Dis

ea

se

ICD

-9

(Ast

hm

aB

ron

ch

itis

)

Weekly Avg Mobile PM10 Concentrations during

Summer 2010 and its Influence on Respiratory

Diagnoses

Summer 2010 Zip Code 79905

Total Mobile Emission PM10

Hospital Admission (Asthma-Bronchitis)

0

2

4

6

8

10

12

0

20

40

60

80

100

120

140

160

180

200

Mo

rbid

ity

dis

ch

arg

es

for

all r

esp

ira

tory

dis

ea

se

Weekly Avg Mobile PM10 Concentrations

during Fall 2010 and its Influence on Respiratory

Diagnoses

Zip Code 79905

Total Medical data ZIP Code 79902

Total Mobile Emission PM10 (Ugm3)

Mobile(Exhaust-Non-

Exhaust) PM10 and

Asthma-Bronchitis)

Linear R

Square

WinterSpring 734 ndash 39

Summer 614 ndash 32

Fall 548 -29

PM10 Mobile emission (Exhaust-Non-Exhaust)contributed significantly

association to the incidence of RD

Weekly Correlation Analysis of PM 25 Mobile Emission (Exhaust-Non-Exhaust)

and Cardiovascular Diagnoses WinterSpring Summer and Fall 2010

0010203040

00500

100015002000

Wee

k 1

Wee

k 2

Wee

k 3

Wee

k 4

Wee

k 5

Wee

k 6

Wee

k 7

Wee

k 8

Wee

k 9

Wee

k 1

0

Wee

k 1

1

Wee

k 1

2

Wee

k 1

3

Wee

k 1

4

Wee

k 1

5

Wee

k 1

6

Wee

k 1

7

Wee

k 1

8

Wee

k 1

9

Wee

k 2

0

Wee

k 2

1

Morb

idit

y d

isch

arg

es f

or

all

card

iovasc

ula

r d

isea

se

Weekly Avg PM25 Mobile Concentrations during

WinterSpring 2010 and its Influence on all Heart

Diagnoses

Zip Code 79905

Total All Heart Disease PM 25 mobile (μgm3)

0010203040

00

500

1000

1500

Mo

rbid

ity

dis

ch

arg

es

for

all

ca

rdio

va

scu

lar

dis

ea

se

Weeks

CORRELATION BETWEEN MOBILE PM25 ugm3

EXPOSURE TO HEART DISEASES SYMPTOMS

SUMMER SEASON 2010

Total All Heart Disease PM 25 mobile (μgm3)

Figure Statistical Analyses of the Relationship Between PM25 Caused by Traffic Emission( 26 of total Emission) with Heart diseases Source Hospital Admissions for Asthma Acute Bronchitis and Heart diseases in El Paso County zip code 79905 from Texas Health Care

Information Council in Austin Texas (Texas Health Care Information Council 2000)

00

10

20

30

40

0

50

100

150

We

ek 3

6

We

ek 3

7

We

ek 3

8

We

ek 3

9

We

ek 4

0

We

ek 4

1

We

ek 4

2

We

ek 4

3

We

ek 4

4

We

ek 4

5

We

ek 4

6

We

ek 4

7

We

ek 4

8

We

ek 4

9

We

ek 5

0

We

ek 5

1

We

ek 5

2

We

ek 5

3

Mo

rbid

ity

dis

ch

arg

es

for

all

ca

rdio

va

scu

lar

dis

ea

se

CORRELATION BETWEEN MOBILE PM25 ugm3

EXPOSURE TO HEART DISEASES SYMPTOMS FALL

SEASON 2010

Total All Heart Disease PM 25 mobile (μgm3)

Mobile(Exhaust-

Non-Exhaust)

PM10 and

Asthma-

Bronchitis)

Linear R

Square

WinterSpring 833 -42

Summer 620 -32

Fall 501-26

PM10 Mobile

emission (Exhaust-

Non-

Exhaust)contribut

ed significantly

association to the

incidence of CVD

Diseases

Monthly Brake Mobile Emission PM1025 kg During year 2010 and its Influence on

Respiratory Diagnoses Zip Code 79905

00200040006000800010000

010000200003000040000

PM

10

Mo

bile

(K

g)

Months

Monthly Brake Mobile Emission PM10 kg during year

2010 and its Influence on Respiratory Diagnoses

Zip Code 79905

Primary PM 10

Brakewear 00100020003000400050006000

0

1000

2000

3000

4000

PM

25

Mo

bil

e(K

g)

Months

Monthly Brake Mobile Emission PM25 during

year 2010 and its Influence on Heart Diagnoses

Zip Code 79905

Primary PM 25

Brakewear

Heart Diseases

Hospital

Admission

Brake Mobile Emission

PM10 kg Asthma-

Bronchitis)

Brake Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=969 Linear Square R=856

Monthly Mobile Exhaust Emission PM1025 During year 2010 and its Influence on

Respiratory Diagnoses Zip Code 79905

0

200

400

600

800

1000

0

10000

20000

30000

40000

50000

1 3 5 7 9 11

PM

10

(K

g m

on

th)

Months

Monthly Mobile Exhaust Emission PM10 during

year 2010 and its Influence on Respiratory

Diagnoses

Zip Code 79905

Primary Exhaust

PM 10

Respiratory Disease

(Asthma

Bronchitis) Hospital

Admission

0

100

200

300

400

500

600

0

10000

20000

30000

40000

50000

1 2 3 4 5 6 7 8 9 101112

PM

25

(K

g m

on

th)

Months

Monthly Exhaust Mobile Emission PM25 during

year 2010 and its Influence on Heart Diagnoses

Zip Code 79905

Primary Exhaust PM

25

Heart Diseases

Hospital Admission

Exhaust Mobile Emission

PM10 kg Asthma-

Bronchitis)

Exhaust Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=929 Linear Square R=831

Monthly Tire wear Mobile Emission PM1025 During year 2010 and its Influence on Heart

Diagnoses Zip Code 79905

0

100

200

300

400

500

600

700

800

900

0

1000

2000

3000

4000

5000

6000

7000

8000

9000

1 2 3 4 5 6 7 8 9 10 11 12

PM

10

(K

g m

on

th)

Months

Monthly Tirewear Mobile Emission PM10 during year 2010

and its Influence on Heart Diagnoses

Zip Code 79905

Primary PM 10 Tirewear

Mobile Emission

Respiratory Disease

(Asthma Bronchitis)

Hospital Admission

0

100

200

300

400

500

600

0

200

400

600

800

1000

1200

1400

1 2 3 4 5 6 7 8 9 10 11 12

PM

25

(K

g m

on

th)

Months

Monthly Tirewear Mobile Emission PM25 during year 2010

and its Influence on Respiratory Diagnoses

Zip Code 79905

Primary PM 25Tirewear

Mobile Emission

Heart Diseases Hospital

Admission

Exhaust Mobile Emission

PM10 kg Asthma-

Bronchitis)

Exhaust Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=769 Linear Square R=715

Dona Ana County Zip Codes

88021880278807288048

Primary

Exhaust

PM 10 Zip

code

79905

Total

Primary

Exhaust

PM10

Dona Ana

Primary

Exhaust

PM 25 Zip

Code

79905

Total

Primary

Exhaust

PM25

Dona Ana

Series1 430378 111773 391915 102123

0

100000

200000

300000

400000

500000

AX

IS T

ITLE

Annual Comparison of the Mobile

Exhaust Emissions El Paso County

and Dona Ana 2010

Primary

PM 10

Brakewea

r Zip code

79905

Brakewea

r

particulat

e_PM10

Dona Ana

Primary

PM 10

Tirewear

Zip code

79905

Tirewear

particulat

e_PM10

Dona Ana

Series1 262585 48573 73754 11864

050000

100000150000200000250000300000

AX

IS T

ITLE

Annual Comparison of the Mobile

Brakewear Emissions El Paso County

and Dona Ana 2010

Figure Comparison of the Annual Mobile Emissions

of Primary PM10 Non-Exhauts (Brake ) from Dona

Ana County New Mexico and El Paso Texas Units

in KgMonth

Figure Comparison of the Annual Mobile Emissions

of Primary PM10-Exhauts Emission from Dona Ana

County New Mexico and El Paso Texas Units in

KgMonth

Primary

PM 25

Brakewe

ar Ziphellip

Brakewe

ar

particula

te_PMhellip

Primary

PM

25Tirewe

ar Ziphellip

Tirewear

particula

te_PM25

Donahellip

Series1 32645 6071 10919 1779

0

10000

20000

30000

40000

AX

IS T

ITLE

Annual Comparison of the

Mobile Exhaust Emissions El Paso

County and Dona Ana 2010

Figure Comparison of the Annual Mobile Emissions

of Primary PM10-Exhauts Emission from Dona Ana

County New Mexico and El Paso Texas Units in

KgMonth

Monthly Mobile Emission PM1025 kg During year 2006

and its Influence on Respiratory Diagnoses Dona Ana

County Zip Code 880218802788072

0

100

200

300

0

5000

10000

15000

Axi

s Ti

tle

Axis Title

Monthly Mobile Exhaust Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Total PrimaryMobile Exhaust_PM10

All Respiratory ICD-9 (AsthmaBronchitis)

050100150200250300

010002000300040005000

Axi

s Ti

tle

Axis Title

Monthly Mobile Brake Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Brakewearparticulate_PM10

All RespiratoryICD -9 (AsthmaBronchitis)

050100150200250300

0200400600800

10001200

Axi

s Ti

tle

Axis Title

Monthly Mobile Tirewear Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Tirewearparticulate_PM10

All Respiratory ICD -9 (AsthmaBronchitis)

Mobile Exhauts

Emission PM10

kg Asthma-

Bronchitis)

Brake Mobile

Emission PM10

kg and Heart

Diagnoses

Tirewear Mobile

Emission PM10

kg and Heart

Diagnoses

Linear Square

R= 951

Linear Square

R=625

Linear Square

R=525

Mobile Exhauts

Emission PM25

kg Asthma-

Bronchitis)

Brake Mobile

Emission PM25

kg and Heart

Diagnoses

Tirewear Mobile

Emission PM25

kg and Heart

Diagnoses

Linear Square

R= 986

Linear Square

R=691

Linear Square

R=601

Results

The results showed that mobile PM emissions in the urban areas close to urban Road and highways is putting at risk public health

and the proportion of diseases attributable to this exposure is potentially large

Brake wear emissions is much lower in freeways due to significantly reduced number of braking events while tire wear is much

higher in areas where studded tires are used The emission of exhaust gases are much higher in areas where there is a high

vehicular traffic

Brake Mobile

Emission PM10 kg

Asthma-Bronchitis)

Brake Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square

R=969

Linear Square

R=856

Exhaust Mobile

Emission PM10 kg

Asthma-Bronchitis)

Exhaust Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square

R=929

Linear Square

R=831

Tirewear Mobile

Emission PM10 kg

Asthma-Bronchitis)

Tirewear Mobile

Emission PM25 kg

and Heart Diagnoses

Linear Square R=769 Linear Square R=715

Brake Mobile

Emission PM10 kg

and Heart

Diagnoses

Brake Mobile

Emission PM25 kg

and Heart

Diagnoses

Exhaust Mobile

Emission PM10 kg

Asthma-Bronchitis)

Linear Square

R=625

Linear Square

R=691

Linear Square R=

951

Exhaust Mobile

Emission PM25 kg

Asthma-

Bronchitis)

Tire wear Mobile

Emission PM10 kg and

Heart Diagnoses

Tirewear Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square R=

986

Linear Square R=525 Linear Square

R=601

El Paso County

Dona Ana

County

BenMAP-CE

In this analysis the Program of Mapping and Analysis of Environmental Benefits-Community Edition

(BenMAP-CE) was used to Estimate the number and economic value of health impacts resulting from changes

in air pollution PM 25 Ugm3 in The El Paso Area

Health and Economic Benefits associated with the Response of PM25 Emission between

Base Year 2010

Number of Mortalities in 2010 Base Year Based on El Paso County Texas Department of State Health Services

Number of Mortalities in 2010 Base Year Based on El Paso County Texas

Department of State Health Services

cause of death

year

2010

Populatio

n

Affected

Backgro

und

Concentr

ation Pollutant

Rollback

Type

Avoided

Deaths

(

Populatio

n)

alzheimers disease 2010 40716 125 PM25

25

microgmAcircsup3

Rollback 9

diseases of the

heart 2010 15834 125 PM25

25

microgmAcircsup3

Rollback 35

influenza and

neumonia 2010 81432 125 PM25

25

microgmAcircsup3

Rollback 18

acute bronchitis

and bronchiolitis 2010 117624 125 PM25

25

microgmAcircsup3

Rollback 26

chronic lower

respiratory diseases 2010 54288 125 PM25

25

microgmAcircsup3

Rollback 12

The Basin-wide decrease in 4 ugm3 PM25 concentration after this

reduction control

Cause of death year 2010

Populatio

n

Affected

Background

Concentrati

on

Reduc

cion

scena

rio Polluta

nt

Rollback

Type

Avoi

ded

Deat

hs

(

Pop

ulati

on)

economic

benefits

analysis $

Alzheimers

disease 2010 121 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 9 12000

Diseases of the

heart 2010 470 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 35 35000

Influenza and

neumonia 2010 242 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 18 42500

Acute bronchitis

and bronchiolitis 2010 349 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 26 95000

Chronic lower

respiratory

diseases 2010 161 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 12 4500

$1 295000

PM25-related Mortalities Based on BenMAP-CE Estimate in 2010 Base Year with change in the concentrations levels

Health and Economic Benefits associated with the Response of PM25 Emission between

Base Year 2010 Increasing 7 Ugm3

Cause of death year 2010

Population

Affected

Deaths

avoided by

attaining 195

μgm3

standard

Background

Concentrati

on

Pollut

ant

Rollback

Type

Avoided

Deaths (

Populatio

n)

econo

mic

Unben

efits

analysi

s

Alzheimers

disease 2010 4524 195 PM25

25

microgmAcircsup3

Rollback 19 150000

Diseases of the

heart 2010 20358 195 PM25

25

microgmAcircsup3

Rollback 135 450000

Influenza and

neumonia 2010 126672 195 PM25

25

microgmAcircsup3

Rollback 38 525000

Acute bronchitis

and bronchiolitis 2010 162864 195 PM25

25

microgmAcircsup3

Rollback 36 122000

Chronic lower

respiratory

diseases 2010 99528 195 PM25

25

microgmAcircsup3

Rollback 12 650000

Conclusions

An excellent Pearson Correlation was established to analyze the relationship in the relative risks of hospitalization of Respiratory(RD) and cardiovascular (CVD) associated with ambient exposure caused by traffic emission in relation to their size andspecific sources of emission on different scenarios interior a border Urban Rural Urban restricted access (freeways andinterstates)

A significant correlation of PM1025 exposure from mobile emission and hospital admissions for selected Respiratory (RD) andcardiovascular (CVD) diagnoses was established The results showed that PM emissions in urban restricted access (freeways andinterstates) is mainly caused by traffic Therefore people living close to highways are more exposed higher vehicular emissions

Conclusions

We found statistically significant associations between mobile PM25 caused by traffic emission with Respiratory and Cardiovascular Diseases in the study areaSubsequently a correlation between cardio-respiratory mortality is established

A significant correlation of PM1025 exposure from mobile emission and hospital admissions for selected Respiratory (RD) and cardiovascular (CVD) diagnoses isestablished The results showed that PM emissions in urban restricted access (freeways and interstates) is mainly caused by traffic Therefore people living close tohighways receive higher vehicular emissions

The table shows the percentage of PM mobile exposure in the analyzed areas contributing to increase the risk of Respiratory and Cardiovascular Diseases

An examination was conducted of the synoptic and local meteorology for the June 2006 ozone episode using the WRF model to determine how meteorological parametersinfluence the formation transport and dispersion of ozone in the PdN The predominant synoptic feature of the ozone event day was the expansion intensification and slowprogression of an upper-level ridge of high pressure The high ozone episodes are associated with highly stable atmospheres strong temperature inversions with low mixingheights and therefore low mixing volumes Under these conditions emissions such as NOx lead to highly polluted conditions that favor ozone formation

BenMAP Conclusions

We have estimated the number and economic value of health impacts resulting

from changes in air pollution concentrations of PM 25 in the PdN region

Reduction of Pm 25 4 UGm3= Avoided 213 cases respiratory cardiovascular

diseses and Economic Benefits associated with the Response of PM25 Emission + $

1295000

Increase of PM25 7 ugm3 = increasing Dies= 326 economic Unbenefits= 2345000$

Bibliography

1 Dockery DW Pope CAI Xu X Spengler JD Ware JH Fay ME Ferris BG Speizer FE An association between air pollution and mortality in six US cities N Engl J Med 3291753ndash1759 (1993)

2 Samet JM Dominici F Curriero FC Coursac I Zeger SL Fine particulate air pollution and mortality in 20 US cities 1987ndash1994 N Engl J Med 3431742ndash1749 (2000)

3 Nel AE Diaz-Sanchez D Li N The role of particulate pollutants in pulmonary inflammation and asthma evidence for the involvement of organic chemicals and oxidative stress Curr Opin Pulm Med 20017 20ndash26

4 Westerholm R Karl-Erik E Exhaust emissions from lightand heavy-duty vehicles chemical composition impact of exhaust after treatment and fuel parameters Environ Health Perspect 102(suppl 4)13ndash23 (1994)

5 Bascom R Bromberg P Costa D Delvin R Dockery D Frampton M Lambert W Samet J Speizer F Utell

6 Health effects of outdoor air pollution Am J Respir Crit Care Med 1533ndash50 (1996)

7 Chow JC Watson JG Frazier CA Egami RT Goodrich A Ralph C Spatial and temporal source contributions to

8 PM10 and PM25 in Reno NV In PM-10 Implementation of Standards Transactions An APCAEPA International Speciality Conference San Francisco CA (Mathal CV Stonefield DH eds) PittsburghAPCA 1988439ndash457

9 overview In Particulate Matter Health and Regulatory Issues VIP-49 Proceedings of an International Specialty Conference 4ndash6 April 1995 Pittsburgh PA PittsburghAir and Waste Management Association 1995577ndash598

10 Kunzli N Kaiser R Medina S Studnicka M Chanel O

11 Filliger P Herry M Horak F Jr Puybonnieux-Texier V Quenel P et al Public-health impact of outdoor and traffic- related air pollution a European assessment Lancet 356795ndash801 (2000)

Bibliography

1 Sioutas C Delfino RJ Singh M Exposure assessment for atmospheric ultrafine particles (UFP) and implications in epidemiological research Environ Health Perspect 2005113947ndash955

2 Mosleh M Blau PJ Dumitrescu D (2004) Characteristics and morphology of wear particles from laboratory testing of disc brake materials Wear 2561128ndash1134

3 Kuumlnzli N et al (2000) Public-health impact of outdoor and traffi c-related air pollution a European assessment Lancet 356(9232)795ndash801

4 Dora C Phillips M eds (2000) Transport environment and health Copenhagen WHO Regional Office for Europe (WHO Regional Publications European Series No 89 httpwwweurowhointdocumente72015pdf accessed 26 November 2004)

5 Westerholm R Karl-Erik E Exhaust emissions from lightand

6 heavy-duty vehicles chemical composition impact of exhaust after treatment and fuel parameters Environ Health Perspect 102(suppl 4)13ndash23 (1994)

7 Fauser Tjell Mosbaek pigegaard Quantification of tire-Tread particles using extractable Organic Zinc as a Tracer Rubber Chemistry and Technology 1999 969Table shows some literature estimates of the contribution of tire wear to PM10 in air (Panko et al 2013) Gustafsson M Blomqvist G Gudmundsson A Dahl A Swietlicki E Bohgard M Lindbom J Ljungman A

8 Chen Y Shah N Huggins FE and Huffman GP (2006) Microanalysis of Ambient Particles from Lexington Ky by Electron Microscopy Atmos Environ 40 651ndash663

9 Donaldson K Tran CL Jimenez LA Duffin R Newby DE and Mills N (2005) Combustion-derived Nanoparticles A Review of Their Toxicology Following Inhalation Exposure Part Fibre Toxicol 2 10ndash23

10 Su D Serafino A Muller JO Jentoft RE Schlogl R and Fiorito S (2008) Cytotoxicity and Inflammatory Potential of Soot Particles of Low-emission Diesel Engines Environ Sci Technol 42 1761ndash1765

11 Maier KL Alessandrini F Beck-Speier I Hofer TPJ Diabatґe S Bitterle E Stoger T and Jakob T (2008) Health Effects of Ambient Particulate Matter-Biological Mechanisms and Inflammatory Responses to in Vitroand in Vivo Particle Exposures Inhalation Toxicol 20 319ndash337

Page 11: Studies of Air Pollutants and their Impact on Respiratory and ...€¦ · Ascarate Park C37 Monitoring Station: The National Ambient Air Quality Standard (NAAQS) for PM 10 and 2.5

Publications Review to examine the relationship between exposure to motor vehicle emissions and respiratory and cardiovascular disease

We have analyzed the current literature which have served as the basis for this project

Some studies determined that traffic-related emissions have been recognized as a major contributor to urban air pollution in particular major cities proximity to major roadways and exposure to motor vehicle exhaust and Non-exhaust emissions are associated with increased risks of cardiovascular respiratory and other diseases (Brugge et al 2007 Gan et al 2010 Gauderman et al 2007 Jerrett et al 2009 Laden et al 2007 McConnell et al 2006)

Effect of traffic pollution on respiratory and allergic disease in adults cross-sectional and longitudinal analyses Mar Pujades-Rodriacuteguez Tricia McKeever Sarah Lewis Duncan Whyatt John Britton and Andrea Venn

httpwwwsciencedailycomreleases200811081114081003htm April 2011

Traffic Pollution Increases Asthma in Adults Several research results revealed adults who suffer asthma and were exposed to heavy traffic pollution experienced an 80 per cent increase University of Melbourne Rev Public Health 15 (1994) pp 107ndash132 August 2010

Traffic Pollution Aggravates Symptoms In Asthmatic Children Traffic pollution especially in cities adversely affects respiratory health in children with asthma studies suggest that traffic pollution and diesel particles in particular may have a greater effect on respiratory health than other pollutants httpwwwsciencedailycomreleases200811081114081003htm September 2010

Traffic-related air pollution associated with prevalence of asthma and COPDchronic bronchitis A cross-sectional study in Southern Sweden Anna Lindgren Emilie Stroh Peter Montneacutemery September 2009

Acute respiratory health effects of air pollution on children with asthma in US inner cities Benjamin Vaughn MS Meyer Kattan MD Herman Mitchell PhD May 2008

Comparison of Air QualityndashRelated Mortality Impacts of two Different source of emission Transportation in the United States httpwwwtrborgMainBlurbs166402aspx January 2008

Long-term exposure to traffic-related air pollution and cardiovascular mortality Chen H Goldberg MS Burnett RT Jerrett M Wheeler AJ Villeneuve PJ Source Department of Epidemiology and Biostatistics McGill University Montreal Quebec Canada January 2011

heavy-duty vehicles chemical composition impact of exhaust after treatment and fuel parameters Environ Health Perspect102(suppl 4)13ndash23 (1994)

Particulate Matter

PM is a mixture of solid and liquid particles suspended in the atmosphere

as atmospheric aerosols Mobile Pollutants are formed by chemical

reactions of gaseous components from burning of fossil fuel in vehicles

(Gasoline amp diesel motor vehicles)

Source EPA (2012) United States Environmental Protection Agency

Particulate matter basic information Cited October 30th 2012 Available

online at httpwwwepa govairqualityparticlepollutionbasichtml

Source EPA (2012) United States Environmental Protection Agency Particulate matter basic

information Cited October 30th 2012 Available online at httpwwwepa

govairqualityparticlepollutionbasichtml

PM10 25 Long Term Exposure ndashChronic Health Consequences

These particles are associated with a

variety of problems including

Aggravated asthma Chronic

bronchitis

Decreased lung function

Increased respiratory symptoms

coughing or difficulty breathing

Increased Cardiopulmonary Mortality

Increased Risk of Lung Cancer

Sources of Particulate Matter Emissions from traffic

Diesel exhaust particulate matter

This particulate toxic potential has been associated with serious adverse Health

effects including respiratory symptoms Pulmonary function and cardiovascular

diseases (Geller et al 2006 Bernstein et al 2004)

Brake wear particulate matter

Brake wear particulate matter Chemical content (iron(Fe) copper(Cu) Antimony(Sb) barium(Ba) this type of particulate can cause severe respiratory and cardiovascular damages and it is also known that Sb has been classified as a possible human pulmonary carcinogen by the International Agency for Research on Cancer (IARC 1989 Et al 2013)

Fig images of brake wear particles generated at a road simulation study ( centre lt25 μm right lt10

μm) Source [Kukutschovaacute et al 2011]

Tire wear particulate matter

The tire wear particles of the tires are generated either by frictional forces between the treadand the road pavement The chemical content Fe Cr Pb Ti Cr Cu Zn Sr Y Zr Sn Sb Ba LaCe and Pb)

Fig Examples of near spherical particles PM 10 and 25 which are originate from interaction of tires and pavements Source [Dahl et al 2006]

Study Area

The Paso del Norte (PdN) region Selected two strategic areas of study El Paso County zip code 79905 Urban area and Dona Ana County Zip Code 880218802788072 Rural Restricted urban access (freeways and interstates)

Map of the area of the simulation by the MOVES model in the study area

Geographic Domain Zip Code 79905 Urban Area (El Paso County)

Zip Codes 88021880278807288048 (Dona Ana County)

Urban road Delta Dr St 31o 45rsquo 5637- 106o 27rsquo 1212 10 miles

Cordova Bridge of the Americas 31o 45rsquo 4367- 106o 27rsquo 0506 15 miles

478 Highway interstate 31o 46rsquo 1326- 106o 27rsquo 0327 05 miles

110 Highway interstate 31o 46rsquo 1210- 106o 27rsquo 0066 10 miles

10 Interstate Gateway Blvd 31o 46rsquo 397- 106o 26rsquo 4769 05 miles

Chamizal Loop 478 31o 46rsquo 668- 106o 26rsquo 5456 05 miles

Alameda Loop 20 31o 46rsquo 1323- 106o 27rsquo 0328 10 miles

Paisano Dr St Patriot freeway

route 62

31o 46rsquo 0669- 106o 27rsquo 212 15 miles

St Piedras 31o 46rsquo 1326- 106o 27rsquo 0327 10 miles

Dona Ana County Miles

Interstate 25 32o 23rsquo 0561 -106 48

1054 32o 23rsquo 3434- -

106 48 1054 32o 23rsquo

5660 106 48 4314

50

Geographic domain To obtain the simulation mobile data from modelMOVES2010a was configurated the coordinates selected in the study areas

El Paso County

PM25 Estimation from Aerosol Optical Depth (AOD) using

satellites

We examined the relationship

between Aerosol Optical Depth

(AOD) estimated from satellite data

at 5 km spatial resolution and the

mass of fine particles le25 μm in

aerodynamic diameter (PM25)

monitored on the ground in El PdN

area PM25 data was recorded from

air quality monitoring Chamizal

station (TCEQ) on different periods

Our analysis shows a significant

positive association between AOD

and PM25

Time-series and scatter plots of AOD estimated PM25 and surface PM25

Analysis of the meteorological factors and synoptic conditions leading to a local high

ozone event episode June 12-21 2006

Meteorology plays a critical role in determining atmospheric ozone concentrations A good synoptic scale weather forecast is essential to accurately forecast tropospheric and surface ozone concentrations

Figure 1 The domain configuration and Landuse categories

resolution 25 km domainFigure 2 The Geopotential height at 500 mb Figure 3 depicts the 850 mb at a lower altitude The

white regions observed in the graph correspond to

mountainous areas

Figure 4 Temperature at 2m height

above surface at 22 UTC June 18 2006

36 km resolution

Performance Evaluation

01020304050

Ju

ne

137

130

0

190

0

10

0

Ju

ne

157

130

0

190

0

10

0

Ju

ne

187

130

0

190

0

10

0

Tem

pe

ratu

re (⁰C

)

Local time (Hrs)

C41 June 13-19 2006

WRF_temperature

(⁰C)

TCEQ_temperature

(⁰C)

01020304050

June1

37

100

0

130

0

160

0

190

0

220

0

10

0

40

0

June1

57

100

0

130

0

160

0

190

0

220

0

10

0

40

0

June1

87

100

0

130

0

160

0

190

0

220

0

10

0

40

0

Rel

ativ

e h

um

idit

y (

)

Local time (Hrs)

C41 June 13-19 2006

WRF_rh () TCEQ_relative humidity ()

0

5

10

15

20

June

137 10

13

16

19

22 1 4

June

157 10

13

16

19

22 1 4

June

187 10

13

16

19

22 1 4

Win

d s

pee

d (

ms

Local time(Hrs)

C12 June 13-192006

WRF_wind speed (ms) TCEQ_ wind speed (ms)

We evaluate the WRF modelrsquos performance

by comparing against corresponding

experimental TCEQ data and performing the

required statistical analysis

HYSPLIT Model

HYSPLIT was simulated and showed that the ozone is mostly transported to El Paso from north western and south western US and Mexican regions during the 72 hours duration of the simulation

0

20

40

60

80

100

1200

00

10

02

00

30

04

00

50

06

00

70

08

00

90

01

00

01

10

01

20

01

30

01

40

01

50

01

60

01

70

01

80

01

90

02

00

02

10

02

20

02

30

0

Ho

url

y o

zon

e [

pp

b]

0102030405060708090

00

01

00

20

03

00

40

05

00

60

07

00

80

09

00

10

00

11

00

12

00

13

00

14

00

15

00

16

00

17

00

18

00

19

00

20

00

21

00

22

00

23

00

Ho

url

y o

zon

e [

pp

b]

June 18th June 19th

Performance Evaluation

01020304050

Ju

ne

137

130

0

190

0

10

0

Ju

ne

157

130

0

190

0

10

0

Ju

ne

187

130

0

190

0

10

0

Tem

pe

ratu

re (⁰C

)

Local time (Hrs)

C41 June 13-19 2006

WRF_temperature

(⁰C)

TCEQ_temperature

(⁰C)

0

50

100

150

June1

37

100

0

130

0

160

0

190

0

220

0

10

0

40

0

June1

57

100

0

130

0

160

0

190

0

220

0

10

0

40

0

June1

87

100

0

130

0

160

0

190

0

220

0

10

0

40

0Ozo

ne

(pp

b)

Local time (Hrs)

C41 June 13-19 2006

CAMx_ozone (ppbV) TCEQ_ozone (ppb)

0

10

20

30

40

50

June1

37

100

0

130

0

160

0

190

0

220

0

10

0

40

0

June1

57

100

0

130

0

160

0

190

0

220

0

10

0

40

0

June1

87

100

0

130

0

160

0

190

0

220

0

10

0

40

0

Rel

ativ

e h

um

idit

y (

)

Local time (Hrs)

C41 June 13-19 2006

WRF_rh () TCEQ_relative humidity ()

0

5

10

15

20

June

137 10

13

16

19

22 1 4

June

157 10

13

16

19

22 1 4

June

187 10

13

16

19

22 1 4W

ind

sp

eed

(m

sLocal time(Hrs)

C12 June 13-192006

WRF_wind speed (ms) TCEQ_ wind speed (ms)

Methodology

Medical Data The data by weekly monthly and year for daily emergency room and hospital admission for the respiratory

infections (RD) and cardiovascular diseases (CVD) was extracted from hospitals records located in the El PdN

the system includes data on type of admission primary and secondary causes of admissionRESPIRATORY DISEASE

Bronquitis amp Chronic Bronchitis 466 - 4661 491 - 4919

Asthma 463 - 4939

Emphysema 492

Respiratory failure 51881

HEART DISEASE

Accute Myocardial Infarction 410

Coronary Athersclerosis 4140

Other Ischemic Heart Disease 411-4139 4141-4149

Cardiac Dyshythmias 427

Essential hypertension 401

Acute myocardial infarction 410

Congestive Heart Failure 4280 4282-4284

Hypertensive heart disease 402

Table 1 ICD -9 Codes for Respiratory and Cardiovascular Diseases

0

50

100

150

200

250

300

Wee

k 1

Wee

k 2

Wee

k 3

Wee

k 4

Wee

k 5

Wee

k 6

Wee

k 7

Wee

k 8

Wee

k 9

Wee

k 1

0

Wee

k 1

1

Wee

k 1

2

Wee

k 1

3

Wee

k 1

4

Wee

k 1

5

Wee

k 1

6

Wee

k 1

7

Wee

k 1

8

Wee

k 1

9

Wee

k 2

0

Wee

k 2

1

Mo

rb

idit

y D

isch

arg

e fo

r a

ll R

esp

ira

tory

Dis

ease

IC

D-9

(

Ast

hm

aB

ro

nch

itis

)

Weekly Morbidity Discharges of all the Listed Diagnoses for All

Respiratory Disease During WinterSpring 2010

Asthma-Bronchitis

EPA MOVES Model for Estimating Emission

Inventories

Motor Vehicle Emission Simulator (MOVES 2010b) will be configuredin The El Paso North Region for Calculate five categories of PM10

PM25 total Emission inventories from all on-road traffic over a

variety of scales within periods of time selected weeks months

and years

Moves (Motor Vehicle Emission

Simulator)

The emission model is develop using the current equation to calculate direct traffic emissions from

vehicles in the form of PM is

Eext annual emissions are measured in grams of miles traveled by the vehicle (gVMT )

SL is the road surface loading in (gm2)

W is the average weight in tons of the vehicles on the road

K is the particle size multiplier for particle size range (eg gVMT for PM10 when using grams and miles)

P is the 7 number of wet days with at least 0254 mm of precipitation during the averaging period

N is the number of years considered in the averaging period

C is the particle size specific emissions factor in units of interest vehicle direct exhaust brake wear and tirewear

Modeling Simulation Domain and Emissions Scenarios

For simulations of mobile air quality emission inventories a motor vehicle emission simulator EPA (MOVES 2014a) was used

The modeling use input factors divided into seven section

parameters

On-Road Inventory local data

input

Scale

Geographic Bounds

Traffic intensity

Vehicle Type

Pollutants

Road Type

Fuel Types

Figure Source EPA US Environmental Protection Agency 2012- Moves 2010b Model

EPA Moves 2014a The modeling used input factors divided into six section

parameters On-Road Inventory local data input

Geographic Domains CountyNonattainment Area

Vehicle-Miles Traveled (VMT) is the total number of miles driven by all vehicles withina given time period and geographic area

Average speed range from 25 miles per

hour to 65 miles per hour

Vehicle Classes Motorcycle PassengerCarTruks light-duty Commercial Truck(6001-8500 lbs) Buses heave-duty trucksRefuse trucks School Bus Single UnitShort Haul-truck Single Unit Long Haul-truck Long Haul Truck Heavy-DutyVehicles (26001-33000 lbs)

Pollutants

Road TypeRural restricted Acces(Freeways and interstates) Rural and Restricted Acces Urban Restricted Acces Off-Network

Fuel Types Gasoline Diesel Fuel

Specific Road Types

Two road types for running emission from the MOVES can be

selected

(freeways and interstates)

Interior urban Urban

Figure Source EPA US Environmental Protection Agency 2012- Moves 2010b Model

VehiclesEquipment

This panel show which on-road vehicles will be modeled

Figure Source EPA US Environmental Protection Agency 2012- Moves 2010b Model

Long haul truck Short haul truck Inercity bus Ligth comercial truck

Passenger car Passenger truck Refuse truck

School bus Single unit long haul-truck

Single unit short haul-truck

Transit bus

Motor home

Motorcycle

Based on Department of Transportation Highway MOVES will Estimates Traffic

Emissions from Cars Trucks amp Motorcycles

Output Data Moves 2014a

Inventories of PM 10 25 Mobile Emission from all

on-Road Traffic

Exhaust Emission PM 10 25 gramsmile

Brake Wear Emission PM 10 25 gramsmile

Tire wear Emission PM 10 25 gramsmile

Date of Vehicle miles traveled (VMT) for

Day Week Month Year

Total Vehicle population

Vehicle age distribution

Simulation of Mobile Emission in the El PdN Region Zip Code 79905

Figure Total Emissions from road traffic in El Paso TX Area were estimated for PM10

Exhaust and Non exhaust emission in kilogramsmonth (Source EPA MOVES 2014a)

0

10000

20000

30000

40000

50000

PM

10 k

gM

on

th

Months

Monthly PM 10 Exhaust and Non-Exhaust Mobile Emissions 2010

On-Road Urban Restricted Area Zip Code 79905

Primary Exhaust PM 10 (kg) Primary PM 10 Brakewear (kg)

Primary PM 10 Tirewear (kg)

05000

100001500020000250003000035000400004500050000

PM

25

kg

Mo

nth

Months

Monthly PM 25 Exhaust and Non-Exhaust Mobile Emission 2010

On-Road Urban Restricted Area Zip Code 79905

Primary Exhaust PM 25 (kg) Primary PM 25 Brakewear (kg) Primary PM 25Tirewear (kg)

Figure Total Emissions from road traffic in El Paso TX Area were estimated for PM25

Exhaust and Non exhaust emission in kilogramsmonth (Source EPA MOVES 2014a)

Total Emissions from Road Traffic in El Paso County PM1025 Exhaust and Non exhaust Emission in kilogramsmonth

Taking the interests to the health risks related to PM 1025 mobile emission were simulated

Exhaust and Non-exhaust emissions contribute almost equally to total traffic-related PM1025 Emissions (Querol et al 2004 Bukowiecki et al 2009a Amato et al 2011)

Monthly PM 10 25 Exhaust and Non-Exhaust (BrakewearTirewear) Mobile

Emission 2010 On-Road Urban Restricted Area Zip Code 79905

Figure Total Emissions from road traffic in El Paso TX Area were estimated for PM10 25 Exhaust and Non Exhaust mobile

emission in kilograms per month (Source EPA MOVES)

0

10000

20000

30000

40000

50000

January February March April May June July August September October November December

PM

10

25

(K

ilog

ram

s)

Months

Summary- Monthly PM 10 25 Exhaust and Non-Exhaust Mobile

Emission 2010 On-Road Urban Restricted Area Zip Code 79905

Primary Exhaust PM 10 Primary PM 10 Brakewear Primary PM 10 Tirewear

Primary Exhaust PM 25 Primary PM 25 Brakewear Primary PM 25Tirewear

Exhaust Emissions PM1025 is reaching maximum emission 48000-42000 thousand of Kgmonth followedby Brake wear 29000-5000 thousand kgmonth and Tire wear with 9000-2000 kgmonth The results showthat the emissions of PM derived mainly from Exhaust and Brake are significantly higher in Urban Area

Annual Contribution of Mobile Emission PM 1025 (Kg) Zip Code 79905 El

Paso County 2010

Total Primary

Exhaust _PM10

39

Total Primary

Exhaust _PM25

36

Brakewear

particulate_PM10

18

Tirewear

particulate_PM10

4

Brakewear

particulate_PM25

2

Tirewear

particulate_PM25

1

0

5

10

15

20

25

30

35

40

45

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53

Fig Annual Average PM10 Concentrations at the

Chamizal C41 Station and PM1025 mobile

Concentration Zip code 79905

PM10 TCEQ (μgm3) Total Mobile Emission PM10 (Ugm3)

Fig Exhaust Emission is Contributing Approximately 74 of total

PM1025 Mobile Emissions following of Brake wear with 20 and Tire

wear with 5

Annual Average PM1025 ugm3 Mobile Emissions (Moves) 26 Chamizal C41

Monitoring Station (TCEQ Chamizal Station )

Predicting Mobile Emission and VTM

Estimation The PdN Region 2010

44E+09

46E+09

48E+09

5E+09

52E+09

54E+09

56E+09

58E+09

6E+09

62E+09

0

50000

100000

150000

200000

250000

300000

350000

20

10

20

11

20

12

20

13

20

14

20

15

20

16

20

17

20

18

20

21

20

22

20

23

20

24

20

25

20

26

20

27

20

28

20

29

20

30

EX

HA

US

T

EM

ISS

ION

MO

BIL

E (

KG

YE

AR

)

YEARS

Predict ing Mobile Exhaust Emission and VTM

Estimation

2010 - 2030 e l PdN Area

Total_ Exhaust PM10 Total_ Exhaust PM25 Distance (Miles)

Fig Predicting Mobile Exhaust PM1025 (kgMonth) Emission and VTM Estimation 2010

- 2030 el PdN Area

44E+09

46E+09

48E+09

5E+09

52E+09

54E+09

56E+09

58E+09

6E+09

62E+09

0

5000000

10000000

15000000

20000000

25000000

30000000

20

10

20

11

20

12

20

13

20

14

20

15

20

16

20

17

20

18

20

21

20

22

20

23

20

24

20

25

20

26

20

27

20

28

20

29

20

30

EX

HA

US

T

EM

ISS

ION

MO

BIL

E (

KG

YE

AR

)

YEARS

Predict ing Mobile Exhaust Emission and

VTM Estimation

2010 - 2030 e l PdN Area

CO NO2 NO NOx Distance

Fig Predicting Mobile Exhaust Emission and VTM Estimation

2010 - 2030 el PdN Area in El Paso TX Area were estimated for

Total CO NOx NO2 NO emission in kilograms per year

(Source EPA MOVES 2014a model)

The simulated Exhaust emissions in the future years shows a trend of reduction of this type of emissions in the

future years one factor should be the new hybrid technology is increasing by 476 since 2010 to 2015 and

use of catalytic converters diesel particulate filters and improved fuels and engines Non-exhaustive sources

will increase in the coming years because there is no control in the material of manufacture composed by Fe

Cu and Mn also not to be able to reduce the number of events of braking (Accelerations and decelerations)

45E+09

5E+09

55E+09

6E+09

65E+09

0

50000

100000

150000

200000

250000

201

0

201

1

201

2

201

3

201

4

201

5

201

6

201

7

201

8

202

1

202

2

202

3

202

4

202

5

202

6

202

7

202

8

202

9

203

0

NO

N-

EX

HA

US

T

EM

ISS

ION

MO

BIL

E

(KG

YE

AR

)

YEARS

Predicting Non Exhaust Mobile

Emission and VTM Estimation

2010 - 2030 el PdN Area

Brake_PM10 Tire_PM10 Distance (Miles)

Fig Predicting Mobile Exhaust PM1025 (kgMonth) Emission and VTM

Estimation 2010 - 2030 el PdN Area

Daily Avg PM1025

Levels of PM Mobile Emission Non-Exhaust -Rush Hour Periods Fall 2010 Zip Code

79905

00

100

200

300

400

500

600

Mo

bil

e P

M1

0 (k

g)

Rush Hours

Daily Avg PM10

Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush Hours

Periods 2010 Zip Code 79905

Total Primary Exhaust

_PM10 WinterSpring

Brakewear

particulate_PM10

WinterSpringTirewear particulate_PM10

WinterSpring

Total Primary Exhaust

_PM10 Summer

Brakewear

particulate_PM10 Summer

Tirewear Particulate_PM10

Summer

Total Primary Exhaust

_PM10 Fall

Brakewear

particulate_PM10 Fall

Tirewear particulate_PM10

Fall

00

50

100

150

200

250

300

350

Mo

bil

e P

M2

5 (k

g)

Rush hours

Daily Avg PM25

Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush

Hours Periods 2010 Zip Code 79905

Total Primary Exhaust _PM25

WinterSpring

Brakewear Particulate_PM25

WinterSpring

Tirewear particulate_PM25

WinterSpring

Total Primary Exhaust _PM25

Summer

Brakewear particulate_PM25

Summer

Tirewear particulate_PM25

Summer

Total Primary Exhaust _PM25

Fall

Brakewear particulate_PM25

Fall

Tirewear particulate_PM25

Fall

Figure Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush Hours Figure Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush Hours

GIS EMISSIONS INVENTORY SYSTEM A geographic information system (GIS) was used to established geographic scenarios with processed images of seasonal mobile

emissions in the PdN region Seasonal mapping is visualized for different types of pollutants Brakewear Exhaust and Tyrewear

Fg Graphics of GIS and Seasonal mobile Emission of particulate matter emission inventory Seasonal emission simulations were performed in kilograms and five contributing inputs factors were identified for

modeling 1) On the composition of the particulate material from different sources such as Exhaust and Non exhaust (Brake wear Tirewear) 2) The Vehicles Equipment clasification were selected according to

the use of gasoline and diesel fuel (motorcycle passenger car Light Duty Vehicles Trucks refuse truck Light Duty Vehicles Light Commercial Truck Light Duty Vehicles School Bus)

Winter Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

120354 67860 19065

Spring Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

139767 86702 24463

Summer Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

94747 62481 17630

Fall Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

75510 45542 12596

251 Descriptive Statistics Data Analysis

Weekly Correlation Analysis of Mobile Emission PM10 (Exhaust-Non-Exhaust) and Respiratory

Diagnoses WinterSpring Summer and Fall 2010

0

2

4

6

8

10

0

50

100

150

200

250

300

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21

Mo

rbid

ity

Dis

ch

arg

e

for

all R

esp

ira

tory

Dis

ea

se

ICD

-9

(A

sth

ma

-Bro

nc

hitis

)

WinterSpring Week

Weekly Avg Mobile PM10 Concentrations during

WinterSpring 2010 and its Influence on Respiratory

Diagnoses

Zip Code 79905

Total Medical data ZIP Code 79902

Total Mobile Emission PM10 (Ugm3)

0

1

2

3

4

5

6

7

0

20

40

60

80

100

Mo

rbid

ity

Dis

ch

arg

e

for

all R

esp

ira

tory

Dis

ea

se

ICD

-9

(Ast

hm

aB

ron

ch

itis

)

Weekly Avg Mobile PM10 Concentrations during

Summer 2010 and its Influence on Respiratory

Diagnoses

Summer 2010 Zip Code 79905

Total Mobile Emission PM10

Hospital Admission (Asthma-Bronchitis)

0

2

4

6

8

10

12

0

20

40

60

80

100

120

140

160

180

200

Mo

rbid

ity

dis

ch

arg

es

for

all r

esp

ira

tory

dis

ea

se

Weekly Avg Mobile PM10 Concentrations

during Fall 2010 and its Influence on Respiratory

Diagnoses

Zip Code 79905

Total Medical data ZIP Code 79902

Total Mobile Emission PM10 (Ugm3)

Mobile(Exhaust-Non-

Exhaust) PM10 and

Asthma-Bronchitis)

Linear R

Square

WinterSpring 734 ndash 39

Summer 614 ndash 32

Fall 548 -29

PM10 Mobile emission (Exhaust-Non-Exhaust)contributed significantly

association to the incidence of RD

Weekly Correlation Analysis of PM 25 Mobile Emission (Exhaust-Non-Exhaust)

and Cardiovascular Diagnoses WinterSpring Summer and Fall 2010

0010203040

00500

100015002000

Wee

k 1

Wee

k 2

Wee

k 3

Wee

k 4

Wee

k 5

Wee

k 6

Wee

k 7

Wee

k 8

Wee

k 9

Wee

k 1

0

Wee

k 1

1

Wee

k 1

2

Wee

k 1

3

Wee

k 1

4

Wee

k 1

5

Wee

k 1

6

Wee

k 1

7

Wee

k 1

8

Wee

k 1

9

Wee

k 2

0

Wee

k 2

1

Morb

idit

y d

isch

arg

es f

or

all

card

iovasc

ula

r d

isea

se

Weekly Avg PM25 Mobile Concentrations during

WinterSpring 2010 and its Influence on all Heart

Diagnoses

Zip Code 79905

Total All Heart Disease PM 25 mobile (μgm3)

0010203040

00

500

1000

1500

Mo

rbid

ity

dis

ch

arg

es

for

all

ca

rdio

va

scu

lar

dis

ea

se

Weeks

CORRELATION BETWEEN MOBILE PM25 ugm3

EXPOSURE TO HEART DISEASES SYMPTOMS

SUMMER SEASON 2010

Total All Heart Disease PM 25 mobile (μgm3)

Figure Statistical Analyses of the Relationship Between PM25 Caused by Traffic Emission( 26 of total Emission) with Heart diseases Source Hospital Admissions for Asthma Acute Bronchitis and Heart diseases in El Paso County zip code 79905 from Texas Health Care

Information Council in Austin Texas (Texas Health Care Information Council 2000)

00

10

20

30

40

0

50

100

150

We

ek 3

6

We

ek 3

7

We

ek 3

8

We

ek 3

9

We

ek 4

0

We

ek 4

1

We

ek 4

2

We

ek 4

3

We

ek 4

4

We

ek 4

5

We

ek 4

6

We

ek 4

7

We

ek 4

8

We

ek 4

9

We

ek 5

0

We

ek 5

1

We

ek 5

2

We

ek 5

3

Mo

rbid

ity

dis

ch

arg

es

for

all

ca

rdio

va

scu

lar

dis

ea

se

CORRELATION BETWEEN MOBILE PM25 ugm3

EXPOSURE TO HEART DISEASES SYMPTOMS FALL

SEASON 2010

Total All Heart Disease PM 25 mobile (μgm3)

Mobile(Exhaust-

Non-Exhaust)

PM10 and

Asthma-

Bronchitis)

Linear R

Square

WinterSpring 833 -42

Summer 620 -32

Fall 501-26

PM10 Mobile

emission (Exhaust-

Non-

Exhaust)contribut

ed significantly

association to the

incidence of CVD

Diseases

Monthly Brake Mobile Emission PM1025 kg During year 2010 and its Influence on

Respiratory Diagnoses Zip Code 79905

00200040006000800010000

010000200003000040000

PM

10

Mo

bile

(K

g)

Months

Monthly Brake Mobile Emission PM10 kg during year

2010 and its Influence on Respiratory Diagnoses

Zip Code 79905

Primary PM 10

Brakewear 00100020003000400050006000

0

1000

2000

3000

4000

PM

25

Mo

bil

e(K

g)

Months

Monthly Brake Mobile Emission PM25 during

year 2010 and its Influence on Heart Diagnoses

Zip Code 79905

Primary PM 25

Brakewear

Heart Diseases

Hospital

Admission

Brake Mobile Emission

PM10 kg Asthma-

Bronchitis)

Brake Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=969 Linear Square R=856

Monthly Mobile Exhaust Emission PM1025 During year 2010 and its Influence on

Respiratory Diagnoses Zip Code 79905

0

200

400

600

800

1000

0

10000

20000

30000

40000

50000

1 3 5 7 9 11

PM

10

(K

g m

on

th)

Months

Monthly Mobile Exhaust Emission PM10 during

year 2010 and its Influence on Respiratory

Diagnoses

Zip Code 79905

Primary Exhaust

PM 10

Respiratory Disease

(Asthma

Bronchitis) Hospital

Admission

0

100

200

300

400

500

600

0

10000

20000

30000

40000

50000

1 2 3 4 5 6 7 8 9 101112

PM

25

(K

g m

on

th)

Months

Monthly Exhaust Mobile Emission PM25 during

year 2010 and its Influence on Heart Diagnoses

Zip Code 79905

Primary Exhaust PM

25

Heart Diseases

Hospital Admission

Exhaust Mobile Emission

PM10 kg Asthma-

Bronchitis)

Exhaust Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=929 Linear Square R=831

Monthly Tire wear Mobile Emission PM1025 During year 2010 and its Influence on Heart

Diagnoses Zip Code 79905

0

100

200

300

400

500

600

700

800

900

0

1000

2000

3000

4000

5000

6000

7000

8000

9000

1 2 3 4 5 6 7 8 9 10 11 12

PM

10

(K

g m

on

th)

Months

Monthly Tirewear Mobile Emission PM10 during year 2010

and its Influence on Heart Diagnoses

Zip Code 79905

Primary PM 10 Tirewear

Mobile Emission

Respiratory Disease

(Asthma Bronchitis)

Hospital Admission

0

100

200

300

400

500

600

0

200

400

600

800

1000

1200

1400

1 2 3 4 5 6 7 8 9 10 11 12

PM

25

(K

g m

on

th)

Months

Monthly Tirewear Mobile Emission PM25 during year 2010

and its Influence on Respiratory Diagnoses

Zip Code 79905

Primary PM 25Tirewear

Mobile Emission

Heart Diseases Hospital

Admission

Exhaust Mobile Emission

PM10 kg Asthma-

Bronchitis)

Exhaust Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=769 Linear Square R=715

Dona Ana County Zip Codes

88021880278807288048

Primary

Exhaust

PM 10 Zip

code

79905

Total

Primary

Exhaust

PM10

Dona Ana

Primary

Exhaust

PM 25 Zip

Code

79905

Total

Primary

Exhaust

PM25

Dona Ana

Series1 430378 111773 391915 102123

0

100000

200000

300000

400000

500000

AX

IS T

ITLE

Annual Comparison of the Mobile

Exhaust Emissions El Paso County

and Dona Ana 2010

Primary

PM 10

Brakewea

r Zip code

79905

Brakewea

r

particulat

e_PM10

Dona Ana

Primary

PM 10

Tirewear

Zip code

79905

Tirewear

particulat

e_PM10

Dona Ana

Series1 262585 48573 73754 11864

050000

100000150000200000250000300000

AX

IS T

ITLE

Annual Comparison of the Mobile

Brakewear Emissions El Paso County

and Dona Ana 2010

Figure Comparison of the Annual Mobile Emissions

of Primary PM10 Non-Exhauts (Brake ) from Dona

Ana County New Mexico and El Paso Texas Units

in KgMonth

Figure Comparison of the Annual Mobile Emissions

of Primary PM10-Exhauts Emission from Dona Ana

County New Mexico and El Paso Texas Units in

KgMonth

Primary

PM 25

Brakewe

ar Ziphellip

Brakewe

ar

particula

te_PMhellip

Primary

PM

25Tirewe

ar Ziphellip

Tirewear

particula

te_PM25

Donahellip

Series1 32645 6071 10919 1779

0

10000

20000

30000

40000

AX

IS T

ITLE

Annual Comparison of the

Mobile Exhaust Emissions El Paso

County and Dona Ana 2010

Figure Comparison of the Annual Mobile Emissions

of Primary PM10-Exhauts Emission from Dona Ana

County New Mexico and El Paso Texas Units in

KgMonth

Monthly Mobile Emission PM1025 kg During year 2006

and its Influence on Respiratory Diagnoses Dona Ana

County Zip Code 880218802788072

0

100

200

300

0

5000

10000

15000

Axi

s Ti

tle

Axis Title

Monthly Mobile Exhaust Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Total PrimaryMobile Exhaust_PM10

All Respiratory ICD-9 (AsthmaBronchitis)

050100150200250300

010002000300040005000

Axi

s Ti

tle

Axis Title

Monthly Mobile Brake Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Brakewearparticulate_PM10

All RespiratoryICD -9 (AsthmaBronchitis)

050100150200250300

0200400600800

10001200

Axi

s Ti

tle

Axis Title

Monthly Mobile Tirewear Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Tirewearparticulate_PM10

All Respiratory ICD -9 (AsthmaBronchitis)

Mobile Exhauts

Emission PM10

kg Asthma-

Bronchitis)

Brake Mobile

Emission PM10

kg and Heart

Diagnoses

Tirewear Mobile

Emission PM10

kg and Heart

Diagnoses

Linear Square

R= 951

Linear Square

R=625

Linear Square

R=525

Mobile Exhauts

Emission PM25

kg Asthma-

Bronchitis)

Brake Mobile

Emission PM25

kg and Heart

Diagnoses

Tirewear Mobile

Emission PM25

kg and Heart

Diagnoses

Linear Square

R= 986

Linear Square

R=691

Linear Square

R=601

Results

The results showed that mobile PM emissions in the urban areas close to urban Road and highways is putting at risk public health

and the proportion of diseases attributable to this exposure is potentially large

Brake wear emissions is much lower in freeways due to significantly reduced number of braking events while tire wear is much

higher in areas where studded tires are used The emission of exhaust gases are much higher in areas where there is a high

vehicular traffic

Brake Mobile

Emission PM10 kg

Asthma-Bronchitis)

Brake Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square

R=969

Linear Square

R=856

Exhaust Mobile

Emission PM10 kg

Asthma-Bronchitis)

Exhaust Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square

R=929

Linear Square

R=831

Tirewear Mobile

Emission PM10 kg

Asthma-Bronchitis)

Tirewear Mobile

Emission PM25 kg

and Heart Diagnoses

Linear Square R=769 Linear Square R=715

Brake Mobile

Emission PM10 kg

and Heart

Diagnoses

Brake Mobile

Emission PM25 kg

and Heart

Diagnoses

Exhaust Mobile

Emission PM10 kg

Asthma-Bronchitis)

Linear Square

R=625

Linear Square

R=691

Linear Square R=

951

Exhaust Mobile

Emission PM25 kg

Asthma-

Bronchitis)

Tire wear Mobile

Emission PM10 kg and

Heart Diagnoses

Tirewear Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square R=

986

Linear Square R=525 Linear Square

R=601

El Paso County

Dona Ana

County

BenMAP-CE

In this analysis the Program of Mapping and Analysis of Environmental Benefits-Community Edition

(BenMAP-CE) was used to Estimate the number and economic value of health impacts resulting from changes

in air pollution PM 25 Ugm3 in The El Paso Area

Health and Economic Benefits associated with the Response of PM25 Emission between

Base Year 2010

Number of Mortalities in 2010 Base Year Based on El Paso County Texas Department of State Health Services

Number of Mortalities in 2010 Base Year Based on El Paso County Texas

Department of State Health Services

cause of death

year

2010

Populatio

n

Affected

Backgro

und

Concentr

ation Pollutant

Rollback

Type

Avoided

Deaths

(

Populatio

n)

alzheimers disease 2010 40716 125 PM25

25

microgmAcircsup3

Rollback 9

diseases of the

heart 2010 15834 125 PM25

25

microgmAcircsup3

Rollback 35

influenza and

neumonia 2010 81432 125 PM25

25

microgmAcircsup3

Rollback 18

acute bronchitis

and bronchiolitis 2010 117624 125 PM25

25

microgmAcircsup3

Rollback 26

chronic lower

respiratory diseases 2010 54288 125 PM25

25

microgmAcircsup3

Rollback 12

The Basin-wide decrease in 4 ugm3 PM25 concentration after this

reduction control

Cause of death year 2010

Populatio

n

Affected

Background

Concentrati

on

Reduc

cion

scena

rio Polluta

nt

Rollback

Type

Avoi

ded

Deat

hs

(

Pop

ulati

on)

economic

benefits

analysis $

Alzheimers

disease 2010 121 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 9 12000

Diseases of the

heart 2010 470 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 35 35000

Influenza and

neumonia 2010 242 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 18 42500

Acute bronchitis

and bronchiolitis 2010 349 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 26 95000

Chronic lower

respiratory

diseases 2010 161 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 12 4500

$1 295000

PM25-related Mortalities Based on BenMAP-CE Estimate in 2010 Base Year with change in the concentrations levels

Health and Economic Benefits associated with the Response of PM25 Emission between

Base Year 2010 Increasing 7 Ugm3

Cause of death year 2010

Population

Affected

Deaths

avoided by

attaining 195

μgm3

standard

Background

Concentrati

on

Pollut

ant

Rollback

Type

Avoided

Deaths (

Populatio

n)

econo

mic

Unben

efits

analysi

s

Alzheimers

disease 2010 4524 195 PM25

25

microgmAcircsup3

Rollback 19 150000

Diseases of the

heart 2010 20358 195 PM25

25

microgmAcircsup3

Rollback 135 450000

Influenza and

neumonia 2010 126672 195 PM25

25

microgmAcircsup3

Rollback 38 525000

Acute bronchitis

and bronchiolitis 2010 162864 195 PM25

25

microgmAcircsup3

Rollback 36 122000

Chronic lower

respiratory

diseases 2010 99528 195 PM25

25

microgmAcircsup3

Rollback 12 650000

Conclusions

An excellent Pearson Correlation was established to analyze the relationship in the relative risks of hospitalization of Respiratory(RD) and cardiovascular (CVD) associated with ambient exposure caused by traffic emission in relation to their size andspecific sources of emission on different scenarios interior a border Urban Rural Urban restricted access (freeways andinterstates)

A significant correlation of PM1025 exposure from mobile emission and hospital admissions for selected Respiratory (RD) andcardiovascular (CVD) diagnoses was established The results showed that PM emissions in urban restricted access (freeways andinterstates) is mainly caused by traffic Therefore people living close to highways are more exposed higher vehicular emissions

Conclusions

We found statistically significant associations between mobile PM25 caused by traffic emission with Respiratory and Cardiovascular Diseases in the study areaSubsequently a correlation between cardio-respiratory mortality is established

A significant correlation of PM1025 exposure from mobile emission and hospital admissions for selected Respiratory (RD) and cardiovascular (CVD) diagnoses isestablished The results showed that PM emissions in urban restricted access (freeways and interstates) is mainly caused by traffic Therefore people living close tohighways receive higher vehicular emissions

The table shows the percentage of PM mobile exposure in the analyzed areas contributing to increase the risk of Respiratory and Cardiovascular Diseases

An examination was conducted of the synoptic and local meteorology for the June 2006 ozone episode using the WRF model to determine how meteorological parametersinfluence the formation transport and dispersion of ozone in the PdN The predominant synoptic feature of the ozone event day was the expansion intensification and slowprogression of an upper-level ridge of high pressure The high ozone episodes are associated with highly stable atmospheres strong temperature inversions with low mixingheights and therefore low mixing volumes Under these conditions emissions such as NOx lead to highly polluted conditions that favor ozone formation

BenMAP Conclusions

We have estimated the number and economic value of health impacts resulting

from changes in air pollution concentrations of PM 25 in the PdN region

Reduction of Pm 25 4 UGm3= Avoided 213 cases respiratory cardiovascular

diseses and Economic Benefits associated with the Response of PM25 Emission + $

1295000

Increase of PM25 7 ugm3 = increasing Dies= 326 economic Unbenefits= 2345000$

Bibliography

1 Dockery DW Pope CAI Xu X Spengler JD Ware JH Fay ME Ferris BG Speizer FE An association between air pollution and mortality in six US cities N Engl J Med 3291753ndash1759 (1993)

2 Samet JM Dominici F Curriero FC Coursac I Zeger SL Fine particulate air pollution and mortality in 20 US cities 1987ndash1994 N Engl J Med 3431742ndash1749 (2000)

3 Nel AE Diaz-Sanchez D Li N The role of particulate pollutants in pulmonary inflammation and asthma evidence for the involvement of organic chemicals and oxidative stress Curr Opin Pulm Med 20017 20ndash26

4 Westerholm R Karl-Erik E Exhaust emissions from lightand heavy-duty vehicles chemical composition impact of exhaust after treatment and fuel parameters Environ Health Perspect 102(suppl 4)13ndash23 (1994)

5 Bascom R Bromberg P Costa D Delvin R Dockery D Frampton M Lambert W Samet J Speizer F Utell

6 Health effects of outdoor air pollution Am J Respir Crit Care Med 1533ndash50 (1996)

7 Chow JC Watson JG Frazier CA Egami RT Goodrich A Ralph C Spatial and temporal source contributions to

8 PM10 and PM25 in Reno NV In PM-10 Implementation of Standards Transactions An APCAEPA International Speciality Conference San Francisco CA (Mathal CV Stonefield DH eds) PittsburghAPCA 1988439ndash457

9 overview In Particulate Matter Health and Regulatory Issues VIP-49 Proceedings of an International Specialty Conference 4ndash6 April 1995 Pittsburgh PA PittsburghAir and Waste Management Association 1995577ndash598

10 Kunzli N Kaiser R Medina S Studnicka M Chanel O

11 Filliger P Herry M Horak F Jr Puybonnieux-Texier V Quenel P et al Public-health impact of outdoor and traffic- related air pollution a European assessment Lancet 356795ndash801 (2000)

Bibliography

1 Sioutas C Delfino RJ Singh M Exposure assessment for atmospheric ultrafine particles (UFP) and implications in epidemiological research Environ Health Perspect 2005113947ndash955

2 Mosleh M Blau PJ Dumitrescu D (2004) Characteristics and morphology of wear particles from laboratory testing of disc brake materials Wear 2561128ndash1134

3 Kuumlnzli N et al (2000) Public-health impact of outdoor and traffi c-related air pollution a European assessment Lancet 356(9232)795ndash801

4 Dora C Phillips M eds (2000) Transport environment and health Copenhagen WHO Regional Office for Europe (WHO Regional Publications European Series No 89 httpwwweurowhointdocumente72015pdf accessed 26 November 2004)

5 Westerholm R Karl-Erik E Exhaust emissions from lightand

6 heavy-duty vehicles chemical composition impact of exhaust after treatment and fuel parameters Environ Health Perspect 102(suppl 4)13ndash23 (1994)

7 Fauser Tjell Mosbaek pigegaard Quantification of tire-Tread particles using extractable Organic Zinc as a Tracer Rubber Chemistry and Technology 1999 969Table shows some literature estimates of the contribution of tire wear to PM10 in air (Panko et al 2013) Gustafsson M Blomqvist G Gudmundsson A Dahl A Swietlicki E Bohgard M Lindbom J Ljungman A

8 Chen Y Shah N Huggins FE and Huffman GP (2006) Microanalysis of Ambient Particles from Lexington Ky by Electron Microscopy Atmos Environ 40 651ndash663

9 Donaldson K Tran CL Jimenez LA Duffin R Newby DE and Mills N (2005) Combustion-derived Nanoparticles A Review of Their Toxicology Following Inhalation Exposure Part Fibre Toxicol 2 10ndash23

10 Su D Serafino A Muller JO Jentoft RE Schlogl R and Fiorito S (2008) Cytotoxicity and Inflammatory Potential of Soot Particles of Low-emission Diesel Engines Environ Sci Technol 42 1761ndash1765

11 Maier KL Alessandrini F Beck-Speier I Hofer TPJ Diabatґe S Bitterle E Stoger T and Jakob T (2008) Health Effects of Ambient Particulate Matter-Biological Mechanisms and Inflammatory Responses to in Vitroand in Vivo Particle Exposures Inhalation Toxicol 20 319ndash337

Page 12: Studies of Air Pollutants and their Impact on Respiratory and ...€¦ · Ascarate Park C37 Monitoring Station: The National Ambient Air Quality Standard (NAAQS) for PM 10 and 2.5

Particulate Matter

PM is a mixture of solid and liquid particles suspended in the atmosphere

as atmospheric aerosols Mobile Pollutants are formed by chemical

reactions of gaseous components from burning of fossil fuel in vehicles

(Gasoline amp diesel motor vehicles)

Source EPA (2012) United States Environmental Protection Agency

Particulate matter basic information Cited October 30th 2012 Available

online at httpwwwepa govairqualityparticlepollutionbasichtml

Source EPA (2012) United States Environmental Protection Agency Particulate matter basic

information Cited October 30th 2012 Available online at httpwwwepa

govairqualityparticlepollutionbasichtml

PM10 25 Long Term Exposure ndashChronic Health Consequences

These particles are associated with a

variety of problems including

Aggravated asthma Chronic

bronchitis

Decreased lung function

Increased respiratory symptoms

coughing or difficulty breathing

Increased Cardiopulmonary Mortality

Increased Risk of Lung Cancer

Sources of Particulate Matter Emissions from traffic

Diesel exhaust particulate matter

This particulate toxic potential has been associated with serious adverse Health

effects including respiratory symptoms Pulmonary function and cardiovascular

diseases (Geller et al 2006 Bernstein et al 2004)

Brake wear particulate matter

Brake wear particulate matter Chemical content (iron(Fe) copper(Cu) Antimony(Sb) barium(Ba) this type of particulate can cause severe respiratory and cardiovascular damages and it is also known that Sb has been classified as a possible human pulmonary carcinogen by the International Agency for Research on Cancer (IARC 1989 Et al 2013)

Fig images of brake wear particles generated at a road simulation study ( centre lt25 μm right lt10

μm) Source [Kukutschovaacute et al 2011]

Tire wear particulate matter

The tire wear particles of the tires are generated either by frictional forces between the treadand the road pavement The chemical content Fe Cr Pb Ti Cr Cu Zn Sr Y Zr Sn Sb Ba LaCe and Pb)

Fig Examples of near spherical particles PM 10 and 25 which are originate from interaction of tires and pavements Source [Dahl et al 2006]

Study Area

The Paso del Norte (PdN) region Selected two strategic areas of study El Paso County zip code 79905 Urban area and Dona Ana County Zip Code 880218802788072 Rural Restricted urban access (freeways and interstates)

Map of the area of the simulation by the MOVES model in the study area

Geographic Domain Zip Code 79905 Urban Area (El Paso County)

Zip Codes 88021880278807288048 (Dona Ana County)

Urban road Delta Dr St 31o 45rsquo 5637- 106o 27rsquo 1212 10 miles

Cordova Bridge of the Americas 31o 45rsquo 4367- 106o 27rsquo 0506 15 miles

478 Highway interstate 31o 46rsquo 1326- 106o 27rsquo 0327 05 miles

110 Highway interstate 31o 46rsquo 1210- 106o 27rsquo 0066 10 miles

10 Interstate Gateway Blvd 31o 46rsquo 397- 106o 26rsquo 4769 05 miles

Chamizal Loop 478 31o 46rsquo 668- 106o 26rsquo 5456 05 miles

Alameda Loop 20 31o 46rsquo 1323- 106o 27rsquo 0328 10 miles

Paisano Dr St Patriot freeway

route 62

31o 46rsquo 0669- 106o 27rsquo 212 15 miles

St Piedras 31o 46rsquo 1326- 106o 27rsquo 0327 10 miles

Dona Ana County Miles

Interstate 25 32o 23rsquo 0561 -106 48

1054 32o 23rsquo 3434- -

106 48 1054 32o 23rsquo

5660 106 48 4314

50

Geographic domain To obtain the simulation mobile data from modelMOVES2010a was configurated the coordinates selected in the study areas

El Paso County

PM25 Estimation from Aerosol Optical Depth (AOD) using

satellites

We examined the relationship

between Aerosol Optical Depth

(AOD) estimated from satellite data

at 5 km spatial resolution and the

mass of fine particles le25 μm in

aerodynamic diameter (PM25)

monitored on the ground in El PdN

area PM25 data was recorded from

air quality monitoring Chamizal

station (TCEQ) on different periods

Our analysis shows a significant

positive association between AOD

and PM25

Time-series and scatter plots of AOD estimated PM25 and surface PM25

Analysis of the meteorological factors and synoptic conditions leading to a local high

ozone event episode June 12-21 2006

Meteorology plays a critical role in determining atmospheric ozone concentrations A good synoptic scale weather forecast is essential to accurately forecast tropospheric and surface ozone concentrations

Figure 1 The domain configuration and Landuse categories

resolution 25 km domainFigure 2 The Geopotential height at 500 mb Figure 3 depicts the 850 mb at a lower altitude The

white regions observed in the graph correspond to

mountainous areas

Figure 4 Temperature at 2m height

above surface at 22 UTC June 18 2006

36 km resolution

Performance Evaluation

01020304050

Ju

ne

137

130

0

190

0

10

0

Ju

ne

157

130

0

190

0

10

0

Ju

ne

187

130

0

190

0

10

0

Tem

pe

ratu

re (⁰C

)

Local time (Hrs)

C41 June 13-19 2006

WRF_temperature

(⁰C)

TCEQ_temperature

(⁰C)

01020304050

June1

37

100

0

130

0

160

0

190

0

220

0

10

0

40

0

June1

57

100

0

130

0

160

0

190

0

220

0

10

0

40

0

June1

87

100

0

130

0

160

0

190

0

220

0

10

0

40

0

Rel

ativ

e h

um

idit

y (

)

Local time (Hrs)

C41 June 13-19 2006

WRF_rh () TCEQ_relative humidity ()

0

5

10

15

20

June

137 10

13

16

19

22 1 4

June

157 10

13

16

19

22 1 4

June

187 10

13

16

19

22 1 4

Win

d s

pee

d (

ms

Local time(Hrs)

C12 June 13-192006

WRF_wind speed (ms) TCEQ_ wind speed (ms)

We evaluate the WRF modelrsquos performance

by comparing against corresponding

experimental TCEQ data and performing the

required statistical analysis

HYSPLIT Model

HYSPLIT was simulated and showed that the ozone is mostly transported to El Paso from north western and south western US and Mexican regions during the 72 hours duration of the simulation

0

20

40

60

80

100

1200

00

10

02

00

30

04

00

50

06

00

70

08

00

90

01

00

01

10

01

20

01

30

01

40

01

50

01

60

01

70

01

80

01

90

02

00

02

10

02

20

02

30

0

Ho

url

y o

zon

e [

pp

b]

0102030405060708090

00

01

00

20

03

00

40

05

00

60

07

00

80

09

00

10

00

11

00

12

00

13

00

14

00

15

00

16

00

17

00

18

00

19

00

20

00

21

00

22

00

23

00

Ho

url

y o

zon

e [

pp

b]

June 18th June 19th

Performance Evaluation

01020304050

Ju

ne

137

130

0

190

0

10

0

Ju

ne

157

130

0

190

0

10

0

Ju

ne

187

130

0

190

0

10

0

Tem

pe

ratu

re (⁰C

)

Local time (Hrs)

C41 June 13-19 2006

WRF_temperature

(⁰C)

TCEQ_temperature

(⁰C)

0

50

100

150

June1

37

100

0

130

0

160

0

190

0

220

0

10

0

40

0

June1

57

100

0

130

0

160

0

190

0

220

0

10

0

40

0

June1

87

100

0

130

0

160

0

190

0

220

0

10

0

40

0Ozo

ne

(pp

b)

Local time (Hrs)

C41 June 13-19 2006

CAMx_ozone (ppbV) TCEQ_ozone (ppb)

0

10

20

30

40

50

June1

37

100

0

130

0

160

0

190

0

220

0

10

0

40

0

June1

57

100

0

130

0

160

0

190

0

220

0

10

0

40

0

June1

87

100

0

130

0

160

0

190

0

220

0

10

0

40

0

Rel

ativ

e h

um

idit

y (

)

Local time (Hrs)

C41 June 13-19 2006

WRF_rh () TCEQ_relative humidity ()

0

5

10

15

20

June

137 10

13

16

19

22 1 4

June

157 10

13

16

19

22 1 4

June

187 10

13

16

19

22 1 4W

ind

sp

eed

(m

sLocal time(Hrs)

C12 June 13-192006

WRF_wind speed (ms) TCEQ_ wind speed (ms)

Methodology

Medical Data The data by weekly monthly and year for daily emergency room and hospital admission for the respiratory

infections (RD) and cardiovascular diseases (CVD) was extracted from hospitals records located in the El PdN

the system includes data on type of admission primary and secondary causes of admissionRESPIRATORY DISEASE

Bronquitis amp Chronic Bronchitis 466 - 4661 491 - 4919

Asthma 463 - 4939

Emphysema 492

Respiratory failure 51881

HEART DISEASE

Accute Myocardial Infarction 410

Coronary Athersclerosis 4140

Other Ischemic Heart Disease 411-4139 4141-4149

Cardiac Dyshythmias 427

Essential hypertension 401

Acute myocardial infarction 410

Congestive Heart Failure 4280 4282-4284

Hypertensive heart disease 402

Table 1 ICD -9 Codes for Respiratory and Cardiovascular Diseases

0

50

100

150

200

250

300

Wee

k 1

Wee

k 2

Wee

k 3

Wee

k 4

Wee

k 5

Wee

k 6

Wee

k 7

Wee

k 8

Wee

k 9

Wee

k 1

0

Wee

k 1

1

Wee

k 1

2

Wee

k 1

3

Wee

k 1

4

Wee

k 1

5

Wee

k 1

6

Wee

k 1

7

Wee

k 1

8

Wee

k 1

9

Wee

k 2

0

Wee

k 2

1

Mo

rb

idit

y D

isch

arg

e fo

r a

ll R

esp

ira

tory

Dis

ease

IC

D-9

(

Ast

hm

aB

ro

nch

itis

)

Weekly Morbidity Discharges of all the Listed Diagnoses for All

Respiratory Disease During WinterSpring 2010

Asthma-Bronchitis

EPA MOVES Model for Estimating Emission

Inventories

Motor Vehicle Emission Simulator (MOVES 2010b) will be configuredin The El Paso North Region for Calculate five categories of PM10

PM25 total Emission inventories from all on-road traffic over a

variety of scales within periods of time selected weeks months

and years

Moves (Motor Vehicle Emission

Simulator)

The emission model is develop using the current equation to calculate direct traffic emissions from

vehicles in the form of PM is

Eext annual emissions are measured in grams of miles traveled by the vehicle (gVMT )

SL is the road surface loading in (gm2)

W is the average weight in tons of the vehicles on the road

K is the particle size multiplier for particle size range (eg gVMT for PM10 when using grams and miles)

P is the 7 number of wet days with at least 0254 mm of precipitation during the averaging period

N is the number of years considered in the averaging period

C is the particle size specific emissions factor in units of interest vehicle direct exhaust brake wear and tirewear

Modeling Simulation Domain and Emissions Scenarios

For simulations of mobile air quality emission inventories a motor vehicle emission simulator EPA (MOVES 2014a) was used

The modeling use input factors divided into seven section

parameters

On-Road Inventory local data

input

Scale

Geographic Bounds

Traffic intensity

Vehicle Type

Pollutants

Road Type

Fuel Types

Figure Source EPA US Environmental Protection Agency 2012- Moves 2010b Model

EPA Moves 2014a The modeling used input factors divided into six section

parameters On-Road Inventory local data input

Geographic Domains CountyNonattainment Area

Vehicle-Miles Traveled (VMT) is the total number of miles driven by all vehicles withina given time period and geographic area

Average speed range from 25 miles per

hour to 65 miles per hour

Vehicle Classes Motorcycle PassengerCarTruks light-duty Commercial Truck(6001-8500 lbs) Buses heave-duty trucksRefuse trucks School Bus Single UnitShort Haul-truck Single Unit Long Haul-truck Long Haul Truck Heavy-DutyVehicles (26001-33000 lbs)

Pollutants

Road TypeRural restricted Acces(Freeways and interstates) Rural and Restricted Acces Urban Restricted Acces Off-Network

Fuel Types Gasoline Diesel Fuel

Specific Road Types

Two road types for running emission from the MOVES can be

selected

(freeways and interstates)

Interior urban Urban

Figure Source EPA US Environmental Protection Agency 2012- Moves 2010b Model

VehiclesEquipment

This panel show which on-road vehicles will be modeled

Figure Source EPA US Environmental Protection Agency 2012- Moves 2010b Model

Long haul truck Short haul truck Inercity bus Ligth comercial truck

Passenger car Passenger truck Refuse truck

School bus Single unit long haul-truck

Single unit short haul-truck

Transit bus

Motor home

Motorcycle

Based on Department of Transportation Highway MOVES will Estimates Traffic

Emissions from Cars Trucks amp Motorcycles

Output Data Moves 2014a

Inventories of PM 10 25 Mobile Emission from all

on-Road Traffic

Exhaust Emission PM 10 25 gramsmile

Brake Wear Emission PM 10 25 gramsmile

Tire wear Emission PM 10 25 gramsmile

Date of Vehicle miles traveled (VMT) for

Day Week Month Year

Total Vehicle population

Vehicle age distribution

Simulation of Mobile Emission in the El PdN Region Zip Code 79905

Figure Total Emissions from road traffic in El Paso TX Area were estimated for PM10

Exhaust and Non exhaust emission in kilogramsmonth (Source EPA MOVES 2014a)

0

10000

20000

30000

40000

50000

PM

10 k

gM

on

th

Months

Monthly PM 10 Exhaust and Non-Exhaust Mobile Emissions 2010

On-Road Urban Restricted Area Zip Code 79905

Primary Exhaust PM 10 (kg) Primary PM 10 Brakewear (kg)

Primary PM 10 Tirewear (kg)

05000

100001500020000250003000035000400004500050000

PM

25

kg

Mo

nth

Months

Monthly PM 25 Exhaust and Non-Exhaust Mobile Emission 2010

On-Road Urban Restricted Area Zip Code 79905

Primary Exhaust PM 25 (kg) Primary PM 25 Brakewear (kg) Primary PM 25Tirewear (kg)

Figure Total Emissions from road traffic in El Paso TX Area were estimated for PM25

Exhaust and Non exhaust emission in kilogramsmonth (Source EPA MOVES 2014a)

Total Emissions from Road Traffic in El Paso County PM1025 Exhaust and Non exhaust Emission in kilogramsmonth

Taking the interests to the health risks related to PM 1025 mobile emission were simulated

Exhaust and Non-exhaust emissions contribute almost equally to total traffic-related PM1025 Emissions (Querol et al 2004 Bukowiecki et al 2009a Amato et al 2011)

Monthly PM 10 25 Exhaust and Non-Exhaust (BrakewearTirewear) Mobile

Emission 2010 On-Road Urban Restricted Area Zip Code 79905

Figure Total Emissions from road traffic in El Paso TX Area were estimated for PM10 25 Exhaust and Non Exhaust mobile

emission in kilograms per month (Source EPA MOVES)

0

10000

20000

30000

40000

50000

January February March April May June July August September October November December

PM

10

25

(K

ilog

ram

s)

Months

Summary- Monthly PM 10 25 Exhaust and Non-Exhaust Mobile

Emission 2010 On-Road Urban Restricted Area Zip Code 79905

Primary Exhaust PM 10 Primary PM 10 Brakewear Primary PM 10 Tirewear

Primary Exhaust PM 25 Primary PM 25 Brakewear Primary PM 25Tirewear

Exhaust Emissions PM1025 is reaching maximum emission 48000-42000 thousand of Kgmonth followedby Brake wear 29000-5000 thousand kgmonth and Tire wear with 9000-2000 kgmonth The results showthat the emissions of PM derived mainly from Exhaust and Brake are significantly higher in Urban Area

Annual Contribution of Mobile Emission PM 1025 (Kg) Zip Code 79905 El

Paso County 2010

Total Primary

Exhaust _PM10

39

Total Primary

Exhaust _PM25

36

Brakewear

particulate_PM10

18

Tirewear

particulate_PM10

4

Brakewear

particulate_PM25

2

Tirewear

particulate_PM25

1

0

5

10

15

20

25

30

35

40

45

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53

Fig Annual Average PM10 Concentrations at the

Chamizal C41 Station and PM1025 mobile

Concentration Zip code 79905

PM10 TCEQ (μgm3) Total Mobile Emission PM10 (Ugm3)

Fig Exhaust Emission is Contributing Approximately 74 of total

PM1025 Mobile Emissions following of Brake wear with 20 and Tire

wear with 5

Annual Average PM1025 ugm3 Mobile Emissions (Moves) 26 Chamizal C41

Monitoring Station (TCEQ Chamizal Station )

Predicting Mobile Emission and VTM

Estimation The PdN Region 2010

44E+09

46E+09

48E+09

5E+09

52E+09

54E+09

56E+09

58E+09

6E+09

62E+09

0

50000

100000

150000

200000

250000

300000

350000

20

10

20

11

20

12

20

13

20

14

20

15

20

16

20

17

20

18

20

21

20

22

20

23

20

24

20

25

20

26

20

27

20

28

20

29

20

30

EX

HA

US

T

EM

ISS

ION

MO

BIL

E (

KG

YE

AR

)

YEARS

Predict ing Mobile Exhaust Emission and VTM

Estimation

2010 - 2030 e l PdN Area

Total_ Exhaust PM10 Total_ Exhaust PM25 Distance (Miles)

Fig Predicting Mobile Exhaust PM1025 (kgMonth) Emission and VTM Estimation 2010

- 2030 el PdN Area

44E+09

46E+09

48E+09

5E+09

52E+09

54E+09

56E+09

58E+09

6E+09

62E+09

0

5000000

10000000

15000000

20000000

25000000

30000000

20

10

20

11

20

12

20

13

20

14

20

15

20

16

20

17

20

18

20

21

20

22

20

23

20

24

20

25

20

26

20

27

20

28

20

29

20

30

EX

HA

US

T

EM

ISS

ION

MO

BIL

E (

KG

YE

AR

)

YEARS

Predict ing Mobile Exhaust Emission and

VTM Estimation

2010 - 2030 e l PdN Area

CO NO2 NO NOx Distance

Fig Predicting Mobile Exhaust Emission and VTM Estimation

2010 - 2030 el PdN Area in El Paso TX Area were estimated for

Total CO NOx NO2 NO emission in kilograms per year

(Source EPA MOVES 2014a model)

The simulated Exhaust emissions in the future years shows a trend of reduction of this type of emissions in the

future years one factor should be the new hybrid technology is increasing by 476 since 2010 to 2015 and

use of catalytic converters diesel particulate filters and improved fuels and engines Non-exhaustive sources

will increase in the coming years because there is no control in the material of manufacture composed by Fe

Cu and Mn also not to be able to reduce the number of events of braking (Accelerations and decelerations)

45E+09

5E+09

55E+09

6E+09

65E+09

0

50000

100000

150000

200000

250000

201

0

201

1

201

2

201

3

201

4

201

5

201

6

201

7

201

8

202

1

202

2

202

3

202

4

202

5

202

6

202

7

202

8

202

9

203

0

NO

N-

EX

HA

US

T

EM

ISS

ION

MO

BIL

E

(KG

YE

AR

)

YEARS

Predicting Non Exhaust Mobile

Emission and VTM Estimation

2010 - 2030 el PdN Area

Brake_PM10 Tire_PM10 Distance (Miles)

Fig Predicting Mobile Exhaust PM1025 (kgMonth) Emission and VTM

Estimation 2010 - 2030 el PdN Area

Daily Avg PM1025

Levels of PM Mobile Emission Non-Exhaust -Rush Hour Periods Fall 2010 Zip Code

79905

00

100

200

300

400

500

600

Mo

bil

e P

M1

0 (k

g)

Rush Hours

Daily Avg PM10

Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush Hours

Periods 2010 Zip Code 79905

Total Primary Exhaust

_PM10 WinterSpring

Brakewear

particulate_PM10

WinterSpringTirewear particulate_PM10

WinterSpring

Total Primary Exhaust

_PM10 Summer

Brakewear

particulate_PM10 Summer

Tirewear Particulate_PM10

Summer

Total Primary Exhaust

_PM10 Fall

Brakewear

particulate_PM10 Fall

Tirewear particulate_PM10

Fall

00

50

100

150

200

250

300

350

Mo

bil

e P

M2

5 (k

g)

Rush hours

Daily Avg PM25

Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush

Hours Periods 2010 Zip Code 79905

Total Primary Exhaust _PM25

WinterSpring

Brakewear Particulate_PM25

WinterSpring

Tirewear particulate_PM25

WinterSpring

Total Primary Exhaust _PM25

Summer

Brakewear particulate_PM25

Summer

Tirewear particulate_PM25

Summer

Total Primary Exhaust _PM25

Fall

Brakewear particulate_PM25

Fall

Tirewear particulate_PM25

Fall

Figure Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush Hours Figure Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush Hours

GIS EMISSIONS INVENTORY SYSTEM A geographic information system (GIS) was used to established geographic scenarios with processed images of seasonal mobile

emissions in the PdN region Seasonal mapping is visualized for different types of pollutants Brakewear Exhaust and Tyrewear

Fg Graphics of GIS and Seasonal mobile Emission of particulate matter emission inventory Seasonal emission simulations were performed in kilograms and five contributing inputs factors were identified for

modeling 1) On the composition of the particulate material from different sources such as Exhaust and Non exhaust (Brake wear Tirewear) 2) The Vehicles Equipment clasification were selected according to

the use of gasoline and diesel fuel (motorcycle passenger car Light Duty Vehicles Trucks refuse truck Light Duty Vehicles Light Commercial Truck Light Duty Vehicles School Bus)

Winter Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

120354 67860 19065

Spring Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

139767 86702 24463

Summer Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

94747 62481 17630

Fall Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

75510 45542 12596

251 Descriptive Statistics Data Analysis

Weekly Correlation Analysis of Mobile Emission PM10 (Exhaust-Non-Exhaust) and Respiratory

Diagnoses WinterSpring Summer and Fall 2010

0

2

4

6

8

10

0

50

100

150

200

250

300

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21

Mo

rbid

ity

Dis

ch

arg

e

for

all R

esp

ira

tory

Dis

ea

se

ICD

-9

(A

sth

ma

-Bro

nc

hitis

)

WinterSpring Week

Weekly Avg Mobile PM10 Concentrations during

WinterSpring 2010 and its Influence on Respiratory

Diagnoses

Zip Code 79905

Total Medical data ZIP Code 79902

Total Mobile Emission PM10 (Ugm3)

0

1

2

3

4

5

6

7

0

20

40

60

80

100

Mo

rbid

ity

Dis

ch

arg

e

for

all R

esp

ira

tory

Dis

ea

se

ICD

-9

(Ast

hm

aB

ron

ch

itis

)

Weekly Avg Mobile PM10 Concentrations during

Summer 2010 and its Influence on Respiratory

Diagnoses

Summer 2010 Zip Code 79905

Total Mobile Emission PM10

Hospital Admission (Asthma-Bronchitis)

0

2

4

6

8

10

12

0

20

40

60

80

100

120

140

160

180

200

Mo

rbid

ity

dis

ch

arg

es

for

all r

esp

ira

tory

dis

ea

se

Weekly Avg Mobile PM10 Concentrations

during Fall 2010 and its Influence on Respiratory

Diagnoses

Zip Code 79905

Total Medical data ZIP Code 79902

Total Mobile Emission PM10 (Ugm3)

Mobile(Exhaust-Non-

Exhaust) PM10 and

Asthma-Bronchitis)

Linear R

Square

WinterSpring 734 ndash 39

Summer 614 ndash 32

Fall 548 -29

PM10 Mobile emission (Exhaust-Non-Exhaust)contributed significantly

association to the incidence of RD

Weekly Correlation Analysis of PM 25 Mobile Emission (Exhaust-Non-Exhaust)

and Cardiovascular Diagnoses WinterSpring Summer and Fall 2010

0010203040

00500

100015002000

Wee

k 1

Wee

k 2

Wee

k 3

Wee

k 4

Wee

k 5

Wee

k 6

Wee

k 7

Wee

k 8

Wee

k 9

Wee

k 1

0

Wee

k 1

1

Wee

k 1

2

Wee

k 1

3

Wee

k 1

4

Wee

k 1

5

Wee

k 1

6

Wee

k 1

7

Wee

k 1

8

Wee

k 1

9

Wee

k 2

0

Wee

k 2

1

Morb

idit

y d

isch

arg

es f

or

all

card

iovasc

ula

r d

isea

se

Weekly Avg PM25 Mobile Concentrations during

WinterSpring 2010 and its Influence on all Heart

Diagnoses

Zip Code 79905

Total All Heart Disease PM 25 mobile (μgm3)

0010203040

00

500

1000

1500

Mo

rbid

ity

dis

ch

arg

es

for

all

ca

rdio

va

scu

lar

dis

ea

se

Weeks

CORRELATION BETWEEN MOBILE PM25 ugm3

EXPOSURE TO HEART DISEASES SYMPTOMS

SUMMER SEASON 2010

Total All Heart Disease PM 25 mobile (μgm3)

Figure Statistical Analyses of the Relationship Between PM25 Caused by Traffic Emission( 26 of total Emission) with Heart diseases Source Hospital Admissions for Asthma Acute Bronchitis and Heart diseases in El Paso County zip code 79905 from Texas Health Care

Information Council in Austin Texas (Texas Health Care Information Council 2000)

00

10

20

30

40

0

50

100

150

We

ek 3

6

We

ek 3

7

We

ek 3

8

We

ek 3

9

We

ek 4

0

We

ek 4

1

We

ek 4

2

We

ek 4

3

We

ek 4

4

We

ek 4

5

We

ek 4

6

We

ek 4

7

We

ek 4

8

We

ek 4

9

We

ek 5

0

We

ek 5

1

We

ek 5

2

We

ek 5

3

Mo

rbid

ity

dis

ch

arg

es

for

all

ca

rdio

va

scu

lar

dis

ea

se

CORRELATION BETWEEN MOBILE PM25 ugm3

EXPOSURE TO HEART DISEASES SYMPTOMS FALL

SEASON 2010

Total All Heart Disease PM 25 mobile (μgm3)

Mobile(Exhaust-

Non-Exhaust)

PM10 and

Asthma-

Bronchitis)

Linear R

Square

WinterSpring 833 -42

Summer 620 -32

Fall 501-26

PM10 Mobile

emission (Exhaust-

Non-

Exhaust)contribut

ed significantly

association to the

incidence of CVD

Diseases

Monthly Brake Mobile Emission PM1025 kg During year 2010 and its Influence on

Respiratory Diagnoses Zip Code 79905

00200040006000800010000

010000200003000040000

PM

10

Mo

bile

(K

g)

Months

Monthly Brake Mobile Emission PM10 kg during year

2010 and its Influence on Respiratory Diagnoses

Zip Code 79905

Primary PM 10

Brakewear 00100020003000400050006000

0

1000

2000

3000

4000

PM

25

Mo

bil

e(K

g)

Months

Monthly Brake Mobile Emission PM25 during

year 2010 and its Influence on Heart Diagnoses

Zip Code 79905

Primary PM 25

Brakewear

Heart Diseases

Hospital

Admission

Brake Mobile Emission

PM10 kg Asthma-

Bronchitis)

Brake Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=969 Linear Square R=856

Monthly Mobile Exhaust Emission PM1025 During year 2010 and its Influence on

Respiratory Diagnoses Zip Code 79905

0

200

400

600

800

1000

0

10000

20000

30000

40000

50000

1 3 5 7 9 11

PM

10

(K

g m

on

th)

Months

Monthly Mobile Exhaust Emission PM10 during

year 2010 and its Influence on Respiratory

Diagnoses

Zip Code 79905

Primary Exhaust

PM 10

Respiratory Disease

(Asthma

Bronchitis) Hospital

Admission

0

100

200

300

400

500

600

0

10000

20000

30000

40000

50000

1 2 3 4 5 6 7 8 9 101112

PM

25

(K

g m

on

th)

Months

Monthly Exhaust Mobile Emission PM25 during

year 2010 and its Influence on Heart Diagnoses

Zip Code 79905

Primary Exhaust PM

25

Heart Diseases

Hospital Admission

Exhaust Mobile Emission

PM10 kg Asthma-

Bronchitis)

Exhaust Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=929 Linear Square R=831

Monthly Tire wear Mobile Emission PM1025 During year 2010 and its Influence on Heart

Diagnoses Zip Code 79905

0

100

200

300

400

500

600

700

800

900

0

1000

2000

3000

4000

5000

6000

7000

8000

9000

1 2 3 4 5 6 7 8 9 10 11 12

PM

10

(K

g m

on

th)

Months

Monthly Tirewear Mobile Emission PM10 during year 2010

and its Influence on Heart Diagnoses

Zip Code 79905

Primary PM 10 Tirewear

Mobile Emission

Respiratory Disease

(Asthma Bronchitis)

Hospital Admission

0

100

200

300

400

500

600

0

200

400

600

800

1000

1200

1400

1 2 3 4 5 6 7 8 9 10 11 12

PM

25

(K

g m

on

th)

Months

Monthly Tirewear Mobile Emission PM25 during year 2010

and its Influence on Respiratory Diagnoses

Zip Code 79905

Primary PM 25Tirewear

Mobile Emission

Heart Diseases Hospital

Admission

Exhaust Mobile Emission

PM10 kg Asthma-

Bronchitis)

Exhaust Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=769 Linear Square R=715

Dona Ana County Zip Codes

88021880278807288048

Primary

Exhaust

PM 10 Zip

code

79905

Total

Primary

Exhaust

PM10

Dona Ana

Primary

Exhaust

PM 25 Zip

Code

79905

Total

Primary

Exhaust

PM25

Dona Ana

Series1 430378 111773 391915 102123

0

100000

200000

300000

400000

500000

AX

IS T

ITLE

Annual Comparison of the Mobile

Exhaust Emissions El Paso County

and Dona Ana 2010

Primary

PM 10

Brakewea

r Zip code

79905

Brakewea

r

particulat

e_PM10

Dona Ana

Primary

PM 10

Tirewear

Zip code

79905

Tirewear

particulat

e_PM10

Dona Ana

Series1 262585 48573 73754 11864

050000

100000150000200000250000300000

AX

IS T

ITLE

Annual Comparison of the Mobile

Brakewear Emissions El Paso County

and Dona Ana 2010

Figure Comparison of the Annual Mobile Emissions

of Primary PM10 Non-Exhauts (Brake ) from Dona

Ana County New Mexico and El Paso Texas Units

in KgMonth

Figure Comparison of the Annual Mobile Emissions

of Primary PM10-Exhauts Emission from Dona Ana

County New Mexico and El Paso Texas Units in

KgMonth

Primary

PM 25

Brakewe

ar Ziphellip

Brakewe

ar

particula

te_PMhellip

Primary

PM

25Tirewe

ar Ziphellip

Tirewear

particula

te_PM25

Donahellip

Series1 32645 6071 10919 1779

0

10000

20000

30000

40000

AX

IS T

ITLE

Annual Comparison of the

Mobile Exhaust Emissions El Paso

County and Dona Ana 2010

Figure Comparison of the Annual Mobile Emissions

of Primary PM10-Exhauts Emission from Dona Ana

County New Mexico and El Paso Texas Units in

KgMonth

Monthly Mobile Emission PM1025 kg During year 2006

and its Influence on Respiratory Diagnoses Dona Ana

County Zip Code 880218802788072

0

100

200

300

0

5000

10000

15000

Axi

s Ti

tle

Axis Title

Monthly Mobile Exhaust Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Total PrimaryMobile Exhaust_PM10

All Respiratory ICD-9 (AsthmaBronchitis)

050100150200250300

010002000300040005000

Axi

s Ti

tle

Axis Title

Monthly Mobile Brake Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Brakewearparticulate_PM10

All RespiratoryICD -9 (AsthmaBronchitis)

050100150200250300

0200400600800

10001200

Axi

s Ti

tle

Axis Title

Monthly Mobile Tirewear Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Tirewearparticulate_PM10

All Respiratory ICD -9 (AsthmaBronchitis)

Mobile Exhauts

Emission PM10

kg Asthma-

Bronchitis)

Brake Mobile

Emission PM10

kg and Heart

Diagnoses

Tirewear Mobile

Emission PM10

kg and Heart

Diagnoses

Linear Square

R= 951

Linear Square

R=625

Linear Square

R=525

Mobile Exhauts

Emission PM25

kg Asthma-

Bronchitis)

Brake Mobile

Emission PM25

kg and Heart

Diagnoses

Tirewear Mobile

Emission PM25

kg and Heart

Diagnoses

Linear Square

R= 986

Linear Square

R=691

Linear Square

R=601

Results

The results showed that mobile PM emissions in the urban areas close to urban Road and highways is putting at risk public health

and the proportion of diseases attributable to this exposure is potentially large

Brake wear emissions is much lower in freeways due to significantly reduced number of braking events while tire wear is much

higher in areas where studded tires are used The emission of exhaust gases are much higher in areas where there is a high

vehicular traffic

Brake Mobile

Emission PM10 kg

Asthma-Bronchitis)

Brake Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square

R=969

Linear Square

R=856

Exhaust Mobile

Emission PM10 kg

Asthma-Bronchitis)

Exhaust Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square

R=929

Linear Square

R=831

Tirewear Mobile

Emission PM10 kg

Asthma-Bronchitis)

Tirewear Mobile

Emission PM25 kg

and Heart Diagnoses

Linear Square R=769 Linear Square R=715

Brake Mobile

Emission PM10 kg

and Heart

Diagnoses

Brake Mobile

Emission PM25 kg

and Heart

Diagnoses

Exhaust Mobile

Emission PM10 kg

Asthma-Bronchitis)

Linear Square

R=625

Linear Square

R=691

Linear Square R=

951

Exhaust Mobile

Emission PM25 kg

Asthma-

Bronchitis)

Tire wear Mobile

Emission PM10 kg and

Heart Diagnoses

Tirewear Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square R=

986

Linear Square R=525 Linear Square

R=601

El Paso County

Dona Ana

County

BenMAP-CE

In this analysis the Program of Mapping and Analysis of Environmental Benefits-Community Edition

(BenMAP-CE) was used to Estimate the number and economic value of health impacts resulting from changes

in air pollution PM 25 Ugm3 in The El Paso Area

Health and Economic Benefits associated with the Response of PM25 Emission between

Base Year 2010

Number of Mortalities in 2010 Base Year Based on El Paso County Texas Department of State Health Services

Number of Mortalities in 2010 Base Year Based on El Paso County Texas

Department of State Health Services

cause of death

year

2010

Populatio

n

Affected

Backgro

und

Concentr

ation Pollutant

Rollback

Type

Avoided

Deaths

(

Populatio

n)

alzheimers disease 2010 40716 125 PM25

25

microgmAcircsup3

Rollback 9

diseases of the

heart 2010 15834 125 PM25

25

microgmAcircsup3

Rollback 35

influenza and

neumonia 2010 81432 125 PM25

25

microgmAcircsup3

Rollback 18

acute bronchitis

and bronchiolitis 2010 117624 125 PM25

25

microgmAcircsup3

Rollback 26

chronic lower

respiratory diseases 2010 54288 125 PM25

25

microgmAcircsup3

Rollback 12

The Basin-wide decrease in 4 ugm3 PM25 concentration after this

reduction control

Cause of death year 2010

Populatio

n

Affected

Background

Concentrati

on

Reduc

cion

scena

rio Polluta

nt

Rollback

Type

Avoi

ded

Deat

hs

(

Pop

ulati

on)

economic

benefits

analysis $

Alzheimers

disease 2010 121 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 9 12000

Diseases of the

heart 2010 470 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 35 35000

Influenza and

neumonia 2010 242 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 18 42500

Acute bronchitis

and bronchiolitis 2010 349 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 26 95000

Chronic lower

respiratory

diseases 2010 161 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 12 4500

$1 295000

PM25-related Mortalities Based on BenMAP-CE Estimate in 2010 Base Year with change in the concentrations levels

Health and Economic Benefits associated with the Response of PM25 Emission between

Base Year 2010 Increasing 7 Ugm3

Cause of death year 2010

Population

Affected

Deaths

avoided by

attaining 195

μgm3

standard

Background

Concentrati

on

Pollut

ant

Rollback

Type

Avoided

Deaths (

Populatio

n)

econo

mic

Unben

efits

analysi

s

Alzheimers

disease 2010 4524 195 PM25

25

microgmAcircsup3

Rollback 19 150000

Diseases of the

heart 2010 20358 195 PM25

25

microgmAcircsup3

Rollback 135 450000

Influenza and

neumonia 2010 126672 195 PM25

25

microgmAcircsup3

Rollback 38 525000

Acute bronchitis

and bronchiolitis 2010 162864 195 PM25

25

microgmAcircsup3

Rollback 36 122000

Chronic lower

respiratory

diseases 2010 99528 195 PM25

25

microgmAcircsup3

Rollback 12 650000

Conclusions

An excellent Pearson Correlation was established to analyze the relationship in the relative risks of hospitalization of Respiratory(RD) and cardiovascular (CVD) associated with ambient exposure caused by traffic emission in relation to their size andspecific sources of emission on different scenarios interior a border Urban Rural Urban restricted access (freeways andinterstates)

A significant correlation of PM1025 exposure from mobile emission and hospital admissions for selected Respiratory (RD) andcardiovascular (CVD) diagnoses was established The results showed that PM emissions in urban restricted access (freeways andinterstates) is mainly caused by traffic Therefore people living close to highways are more exposed higher vehicular emissions

Conclusions

We found statistically significant associations between mobile PM25 caused by traffic emission with Respiratory and Cardiovascular Diseases in the study areaSubsequently a correlation between cardio-respiratory mortality is established

A significant correlation of PM1025 exposure from mobile emission and hospital admissions for selected Respiratory (RD) and cardiovascular (CVD) diagnoses isestablished The results showed that PM emissions in urban restricted access (freeways and interstates) is mainly caused by traffic Therefore people living close tohighways receive higher vehicular emissions

The table shows the percentage of PM mobile exposure in the analyzed areas contributing to increase the risk of Respiratory and Cardiovascular Diseases

An examination was conducted of the synoptic and local meteorology for the June 2006 ozone episode using the WRF model to determine how meteorological parametersinfluence the formation transport and dispersion of ozone in the PdN The predominant synoptic feature of the ozone event day was the expansion intensification and slowprogression of an upper-level ridge of high pressure The high ozone episodes are associated with highly stable atmospheres strong temperature inversions with low mixingheights and therefore low mixing volumes Under these conditions emissions such as NOx lead to highly polluted conditions that favor ozone formation

BenMAP Conclusions

We have estimated the number and economic value of health impacts resulting

from changes in air pollution concentrations of PM 25 in the PdN region

Reduction of Pm 25 4 UGm3= Avoided 213 cases respiratory cardiovascular

diseses and Economic Benefits associated with the Response of PM25 Emission + $

1295000

Increase of PM25 7 ugm3 = increasing Dies= 326 economic Unbenefits= 2345000$

Bibliography

1 Dockery DW Pope CAI Xu X Spengler JD Ware JH Fay ME Ferris BG Speizer FE An association between air pollution and mortality in six US cities N Engl J Med 3291753ndash1759 (1993)

2 Samet JM Dominici F Curriero FC Coursac I Zeger SL Fine particulate air pollution and mortality in 20 US cities 1987ndash1994 N Engl J Med 3431742ndash1749 (2000)

3 Nel AE Diaz-Sanchez D Li N The role of particulate pollutants in pulmonary inflammation and asthma evidence for the involvement of organic chemicals and oxidative stress Curr Opin Pulm Med 20017 20ndash26

4 Westerholm R Karl-Erik E Exhaust emissions from lightand heavy-duty vehicles chemical composition impact of exhaust after treatment and fuel parameters Environ Health Perspect 102(suppl 4)13ndash23 (1994)

5 Bascom R Bromberg P Costa D Delvin R Dockery D Frampton M Lambert W Samet J Speizer F Utell

6 Health effects of outdoor air pollution Am J Respir Crit Care Med 1533ndash50 (1996)

7 Chow JC Watson JG Frazier CA Egami RT Goodrich A Ralph C Spatial and temporal source contributions to

8 PM10 and PM25 in Reno NV In PM-10 Implementation of Standards Transactions An APCAEPA International Speciality Conference San Francisco CA (Mathal CV Stonefield DH eds) PittsburghAPCA 1988439ndash457

9 overview In Particulate Matter Health and Regulatory Issues VIP-49 Proceedings of an International Specialty Conference 4ndash6 April 1995 Pittsburgh PA PittsburghAir and Waste Management Association 1995577ndash598

10 Kunzli N Kaiser R Medina S Studnicka M Chanel O

11 Filliger P Herry M Horak F Jr Puybonnieux-Texier V Quenel P et al Public-health impact of outdoor and traffic- related air pollution a European assessment Lancet 356795ndash801 (2000)

Bibliography

1 Sioutas C Delfino RJ Singh M Exposure assessment for atmospheric ultrafine particles (UFP) and implications in epidemiological research Environ Health Perspect 2005113947ndash955

2 Mosleh M Blau PJ Dumitrescu D (2004) Characteristics and morphology of wear particles from laboratory testing of disc brake materials Wear 2561128ndash1134

3 Kuumlnzli N et al (2000) Public-health impact of outdoor and traffi c-related air pollution a European assessment Lancet 356(9232)795ndash801

4 Dora C Phillips M eds (2000) Transport environment and health Copenhagen WHO Regional Office for Europe (WHO Regional Publications European Series No 89 httpwwweurowhointdocumente72015pdf accessed 26 November 2004)

5 Westerholm R Karl-Erik E Exhaust emissions from lightand

6 heavy-duty vehicles chemical composition impact of exhaust after treatment and fuel parameters Environ Health Perspect 102(suppl 4)13ndash23 (1994)

7 Fauser Tjell Mosbaek pigegaard Quantification of tire-Tread particles using extractable Organic Zinc as a Tracer Rubber Chemistry and Technology 1999 969Table shows some literature estimates of the contribution of tire wear to PM10 in air (Panko et al 2013) Gustafsson M Blomqvist G Gudmundsson A Dahl A Swietlicki E Bohgard M Lindbom J Ljungman A

8 Chen Y Shah N Huggins FE and Huffman GP (2006) Microanalysis of Ambient Particles from Lexington Ky by Electron Microscopy Atmos Environ 40 651ndash663

9 Donaldson K Tran CL Jimenez LA Duffin R Newby DE and Mills N (2005) Combustion-derived Nanoparticles A Review of Their Toxicology Following Inhalation Exposure Part Fibre Toxicol 2 10ndash23

10 Su D Serafino A Muller JO Jentoft RE Schlogl R and Fiorito S (2008) Cytotoxicity and Inflammatory Potential of Soot Particles of Low-emission Diesel Engines Environ Sci Technol 42 1761ndash1765

11 Maier KL Alessandrini F Beck-Speier I Hofer TPJ Diabatґe S Bitterle E Stoger T and Jakob T (2008) Health Effects of Ambient Particulate Matter-Biological Mechanisms and Inflammatory Responses to in Vitroand in Vivo Particle Exposures Inhalation Toxicol 20 319ndash337

Page 13: Studies of Air Pollutants and their Impact on Respiratory and ...€¦ · Ascarate Park C37 Monitoring Station: The National Ambient Air Quality Standard (NAAQS) for PM 10 and 2.5

PM10 25 Long Term Exposure ndashChronic Health Consequences

These particles are associated with a

variety of problems including

Aggravated asthma Chronic

bronchitis

Decreased lung function

Increased respiratory symptoms

coughing or difficulty breathing

Increased Cardiopulmonary Mortality

Increased Risk of Lung Cancer

Sources of Particulate Matter Emissions from traffic

Diesel exhaust particulate matter

This particulate toxic potential has been associated with serious adverse Health

effects including respiratory symptoms Pulmonary function and cardiovascular

diseases (Geller et al 2006 Bernstein et al 2004)

Brake wear particulate matter

Brake wear particulate matter Chemical content (iron(Fe) copper(Cu) Antimony(Sb) barium(Ba) this type of particulate can cause severe respiratory and cardiovascular damages and it is also known that Sb has been classified as a possible human pulmonary carcinogen by the International Agency for Research on Cancer (IARC 1989 Et al 2013)

Fig images of brake wear particles generated at a road simulation study ( centre lt25 μm right lt10

μm) Source [Kukutschovaacute et al 2011]

Tire wear particulate matter

The tire wear particles of the tires are generated either by frictional forces between the treadand the road pavement The chemical content Fe Cr Pb Ti Cr Cu Zn Sr Y Zr Sn Sb Ba LaCe and Pb)

Fig Examples of near spherical particles PM 10 and 25 which are originate from interaction of tires and pavements Source [Dahl et al 2006]

Study Area

The Paso del Norte (PdN) region Selected two strategic areas of study El Paso County zip code 79905 Urban area and Dona Ana County Zip Code 880218802788072 Rural Restricted urban access (freeways and interstates)

Map of the area of the simulation by the MOVES model in the study area

Geographic Domain Zip Code 79905 Urban Area (El Paso County)

Zip Codes 88021880278807288048 (Dona Ana County)

Urban road Delta Dr St 31o 45rsquo 5637- 106o 27rsquo 1212 10 miles

Cordova Bridge of the Americas 31o 45rsquo 4367- 106o 27rsquo 0506 15 miles

478 Highway interstate 31o 46rsquo 1326- 106o 27rsquo 0327 05 miles

110 Highway interstate 31o 46rsquo 1210- 106o 27rsquo 0066 10 miles

10 Interstate Gateway Blvd 31o 46rsquo 397- 106o 26rsquo 4769 05 miles

Chamizal Loop 478 31o 46rsquo 668- 106o 26rsquo 5456 05 miles

Alameda Loop 20 31o 46rsquo 1323- 106o 27rsquo 0328 10 miles

Paisano Dr St Patriot freeway

route 62

31o 46rsquo 0669- 106o 27rsquo 212 15 miles

St Piedras 31o 46rsquo 1326- 106o 27rsquo 0327 10 miles

Dona Ana County Miles

Interstate 25 32o 23rsquo 0561 -106 48

1054 32o 23rsquo 3434- -

106 48 1054 32o 23rsquo

5660 106 48 4314

50

Geographic domain To obtain the simulation mobile data from modelMOVES2010a was configurated the coordinates selected in the study areas

El Paso County

PM25 Estimation from Aerosol Optical Depth (AOD) using

satellites

We examined the relationship

between Aerosol Optical Depth

(AOD) estimated from satellite data

at 5 km spatial resolution and the

mass of fine particles le25 μm in

aerodynamic diameter (PM25)

monitored on the ground in El PdN

area PM25 data was recorded from

air quality monitoring Chamizal

station (TCEQ) on different periods

Our analysis shows a significant

positive association between AOD

and PM25

Time-series and scatter plots of AOD estimated PM25 and surface PM25

Analysis of the meteorological factors and synoptic conditions leading to a local high

ozone event episode June 12-21 2006

Meteorology plays a critical role in determining atmospheric ozone concentrations A good synoptic scale weather forecast is essential to accurately forecast tropospheric and surface ozone concentrations

Figure 1 The domain configuration and Landuse categories

resolution 25 km domainFigure 2 The Geopotential height at 500 mb Figure 3 depicts the 850 mb at a lower altitude The

white regions observed in the graph correspond to

mountainous areas

Figure 4 Temperature at 2m height

above surface at 22 UTC June 18 2006

36 km resolution

Performance Evaluation

01020304050

Ju

ne

137

130

0

190

0

10

0

Ju

ne

157

130

0

190

0

10

0

Ju

ne

187

130

0

190

0

10

0

Tem

pe

ratu

re (⁰C

)

Local time (Hrs)

C41 June 13-19 2006

WRF_temperature

(⁰C)

TCEQ_temperature

(⁰C)

01020304050

June1

37

100

0

130

0

160

0

190

0

220

0

10

0

40

0

June1

57

100

0

130

0

160

0

190

0

220

0

10

0

40

0

June1

87

100

0

130

0

160

0

190

0

220

0

10

0

40

0

Rel

ativ

e h

um

idit

y (

)

Local time (Hrs)

C41 June 13-19 2006

WRF_rh () TCEQ_relative humidity ()

0

5

10

15

20

June

137 10

13

16

19

22 1 4

June

157 10

13

16

19

22 1 4

June

187 10

13

16

19

22 1 4

Win

d s

pee

d (

ms

Local time(Hrs)

C12 June 13-192006

WRF_wind speed (ms) TCEQ_ wind speed (ms)

We evaluate the WRF modelrsquos performance

by comparing against corresponding

experimental TCEQ data and performing the

required statistical analysis

HYSPLIT Model

HYSPLIT was simulated and showed that the ozone is mostly transported to El Paso from north western and south western US and Mexican regions during the 72 hours duration of the simulation

0

20

40

60

80

100

1200

00

10

02

00

30

04

00

50

06

00

70

08

00

90

01

00

01

10

01

20

01

30

01

40

01

50

01

60

01

70

01

80

01

90

02

00

02

10

02

20

02

30

0

Ho

url

y o

zon

e [

pp

b]

0102030405060708090

00

01

00

20

03

00

40

05

00

60

07

00

80

09

00

10

00

11

00

12

00

13

00

14

00

15

00

16

00

17

00

18

00

19

00

20

00

21

00

22

00

23

00

Ho

url

y o

zon

e [

pp

b]

June 18th June 19th

Performance Evaluation

01020304050

Ju

ne

137

130

0

190

0

10

0

Ju

ne

157

130

0

190

0

10

0

Ju

ne

187

130

0

190

0

10

0

Tem

pe

ratu

re (⁰C

)

Local time (Hrs)

C41 June 13-19 2006

WRF_temperature

(⁰C)

TCEQ_temperature

(⁰C)

0

50

100

150

June1

37

100

0

130

0

160

0

190

0

220

0

10

0

40

0

June1

57

100

0

130

0

160

0

190

0

220

0

10

0

40

0

June1

87

100

0

130

0

160

0

190

0

220

0

10

0

40

0Ozo

ne

(pp

b)

Local time (Hrs)

C41 June 13-19 2006

CAMx_ozone (ppbV) TCEQ_ozone (ppb)

0

10

20

30

40

50

June1

37

100

0

130

0

160

0

190

0

220

0

10

0

40

0

June1

57

100

0

130

0

160

0

190

0

220

0

10

0

40

0

June1

87

100

0

130

0

160

0

190

0

220

0

10

0

40

0

Rel

ativ

e h

um

idit

y (

)

Local time (Hrs)

C41 June 13-19 2006

WRF_rh () TCEQ_relative humidity ()

0

5

10

15

20

June

137 10

13

16

19

22 1 4

June

157 10

13

16

19

22 1 4

June

187 10

13

16

19

22 1 4W

ind

sp

eed

(m

sLocal time(Hrs)

C12 June 13-192006

WRF_wind speed (ms) TCEQ_ wind speed (ms)

Methodology

Medical Data The data by weekly monthly and year for daily emergency room and hospital admission for the respiratory

infections (RD) and cardiovascular diseases (CVD) was extracted from hospitals records located in the El PdN

the system includes data on type of admission primary and secondary causes of admissionRESPIRATORY DISEASE

Bronquitis amp Chronic Bronchitis 466 - 4661 491 - 4919

Asthma 463 - 4939

Emphysema 492

Respiratory failure 51881

HEART DISEASE

Accute Myocardial Infarction 410

Coronary Athersclerosis 4140

Other Ischemic Heart Disease 411-4139 4141-4149

Cardiac Dyshythmias 427

Essential hypertension 401

Acute myocardial infarction 410

Congestive Heart Failure 4280 4282-4284

Hypertensive heart disease 402

Table 1 ICD -9 Codes for Respiratory and Cardiovascular Diseases

0

50

100

150

200

250

300

Wee

k 1

Wee

k 2

Wee

k 3

Wee

k 4

Wee

k 5

Wee

k 6

Wee

k 7

Wee

k 8

Wee

k 9

Wee

k 1

0

Wee

k 1

1

Wee

k 1

2

Wee

k 1

3

Wee

k 1

4

Wee

k 1

5

Wee

k 1

6

Wee

k 1

7

Wee

k 1

8

Wee

k 1

9

Wee

k 2

0

Wee

k 2

1

Mo

rb

idit

y D

isch

arg

e fo

r a

ll R

esp

ira

tory

Dis

ease

IC

D-9

(

Ast

hm

aB

ro

nch

itis

)

Weekly Morbidity Discharges of all the Listed Diagnoses for All

Respiratory Disease During WinterSpring 2010

Asthma-Bronchitis

EPA MOVES Model for Estimating Emission

Inventories

Motor Vehicle Emission Simulator (MOVES 2010b) will be configuredin The El Paso North Region for Calculate five categories of PM10

PM25 total Emission inventories from all on-road traffic over a

variety of scales within periods of time selected weeks months

and years

Moves (Motor Vehicle Emission

Simulator)

The emission model is develop using the current equation to calculate direct traffic emissions from

vehicles in the form of PM is

Eext annual emissions are measured in grams of miles traveled by the vehicle (gVMT )

SL is the road surface loading in (gm2)

W is the average weight in tons of the vehicles on the road

K is the particle size multiplier for particle size range (eg gVMT for PM10 when using grams and miles)

P is the 7 number of wet days with at least 0254 mm of precipitation during the averaging period

N is the number of years considered in the averaging period

C is the particle size specific emissions factor in units of interest vehicle direct exhaust brake wear and tirewear

Modeling Simulation Domain and Emissions Scenarios

For simulations of mobile air quality emission inventories a motor vehicle emission simulator EPA (MOVES 2014a) was used

The modeling use input factors divided into seven section

parameters

On-Road Inventory local data

input

Scale

Geographic Bounds

Traffic intensity

Vehicle Type

Pollutants

Road Type

Fuel Types

Figure Source EPA US Environmental Protection Agency 2012- Moves 2010b Model

EPA Moves 2014a The modeling used input factors divided into six section

parameters On-Road Inventory local data input

Geographic Domains CountyNonattainment Area

Vehicle-Miles Traveled (VMT) is the total number of miles driven by all vehicles withina given time period and geographic area

Average speed range from 25 miles per

hour to 65 miles per hour

Vehicle Classes Motorcycle PassengerCarTruks light-duty Commercial Truck(6001-8500 lbs) Buses heave-duty trucksRefuse trucks School Bus Single UnitShort Haul-truck Single Unit Long Haul-truck Long Haul Truck Heavy-DutyVehicles (26001-33000 lbs)

Pollutants

Road TypeRural restricted Acces(Freeways and interstates) Rural and Restricted Acces Urban Restricted Acces Off-Network

Fuel Types Gasoline Diesel Fuel

Specific Road Types

Two road types for running emission from the MOVES can be

selected

(freeways and interstates)

Interior urban Urban

Figure Source EPA US Environmental Protection Agency 2012- Moves 2010b Model

VehiclesEquipment

This panel show which on-road vehicles will be modeled

Figure Source EPA US Environmental Protection Agency 2012- Moves 2010b Model

Long haul truck Short haul truck Inercity bus Ligth comercial truck

Passenger car Passenger truck Refuse truck

School bus Single unit long haul-truck

Single unit short haul-truck

Transit bus

Motor home

Motorcycle

Based on Department of Transportation Highway MOVES will Estimates Traffic

Emissions from Cars Trucks amp Motorcycles

Output Data Moves 2014a

Inventories of PM 10 25 Mobile Emission from all

on-Road Traffic

Exhaust Emission PM 10 25 gramsmile

Brake Wear Emission PM 10 25 gramsmile

Tire wear Emission PM 10 25 gramsmile

Date of Vehicle miles traveled (VMT) for

Day Week Month Year

Total Vehicle population

Vehicle age distribution

Simulation of Mobile Emission in the El PdN Region Zip Code 79905

Figure Total Emissions from road traffic in El Paso TX Area were estimated for PM10

Exhaust and Non exhaust emission in kilogramsmonth (Source EPA MOVES 2014a)

0

10000

20000

30000

40000

50000

PM

10 k

gM

on

th

Months

Monthly PM 10 Exhaust and Non-Exhaust Mobile Emissions 2010

On-Road Urban Restricted Area Zip Code 79905

Primary Exhaust PM 10 (kg) Primary PM 10 Brakewear (kg)

Primary PM 10 Tirewear (kg)

05000

100001500020000250003000035000400004500050000

PM

25

kg

Mo

nth

Months

Monthly PM 25 Exhaust and Non-Exhaust Mobile Emission 2010

On-Road Urban Restricted Area Zip Code 79905

Primary Exhaust PM 25 (kg) Primary PM 25 Brakewear (kg) Primary PM 25Tirewear (kg)

Figure Total Emissions from road traffic in El Paso TX Area were estimated for PM25

Exhaust and Non exhaust emission in kilogramsmonth (Source EPA MOVES 2014a)

Total Emissions from Road Traffic in El Paso County PM1025 Exhaust and Non exhaust Emission in kilogramsmonth

Taking the interests to the health risks related to PM 1025 mobile emission were simulated

Exhaust and Non-exhaust emissions contribute almost equally to total traffic-related PM1025 Emissions (Querol et al 2004 Bukowiecki et al 2009a Amato et al 2011)

Monthly PM 10 25 Exhaust and Non-Exhaust (BrakewearTirewear) Mobile

Emission 2010 On-Road Urban Restricted Area Zip Code 79905

Figure Total Emissions from road traffic in El Paso TX Area were estimated for PM10 25 Exhaust and Non Exhaust mobile

emission in kilograms per month (Source EPA MOVES)

0

10000

20000

30000

40000

50000

January February March April May June July August September October November December

PM

10

25

(K

ilog

ram

s)

Months

Summary- Monthly PM 10 25 Exhaust and Non-Exhaust Mobile

Emission 2010 On-Road Urban Restricted Area Zip Code 79905

Primary Exhaust PM 10 Primary PM 10 Brakewear Primary PM 10 Tirewear

Primary Exhaust PM 25 Primary PM 25 Brakewear Primary PM 25Tirewear

Exhaust Emissions PM1025 is reaching maximum emission 48000-42000 thousand of Kgmonth followedby Brake wear 29000-5000 thousand kgmonth and Tire wear with 9000-2000 kgmonth The results showthat the emissions of PM derived mainly from Exhaust and Brake are significantly higher in Urban Area

Annual Contribution of Mobile Emission PM 1025 (Kg) Zip Code 79905 El

Paso County 2010

Total Primary

Exhaust _PM10

39

Total Primary

Exhaust _PM25

36

Brakewear

particulate_PM10

18

Tirewear

particulate_PM10

4

Brakewear

particulate_PM25

2

Tirewear

particulate_PM25

1

0

5

10

15

20

25

30

35

40

45

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53

Fig Annual Average PM10 Concentrations at the

Chamizal C41 Station and PM1025 mobile

Concentration Zip code 79905

PM10 TCEQ (μgm3) Total Mobile Emission PM10 (Ugm3)

Fig Exhaust Emission is Contributing Approximately 74 of total

PM1025 Mobile Emissions following of Brake wear with 20 and Tire

wear with 5

Annual Average PM1025 ugm3 Mobile Emissions (Moves) 26 Chamizal C41

Monitoring Station (TCEQ Chamizal Station )

Predicting Mobile Emission and VTM

Estimation The PdN Region 2010

44E+09

46E+09

48E+09

5E+09

52E+09

54E+09

56E+09

58E+09

6E+09

62E+09

0

50000

100000

150000

200000

250000

300000

350000

20

10

20

11

20

12

20

13

20

14

20

15

20

16

20

17

20

18

20

21

20

22

20

23

20

24

20

25

20

26

20

27

20

28

20

29

20

30

EX

HA

US

T

EM

ISS

ION

MO

BIL

E (

KG

YE

AR

)

YEARS

Predict ing Mobile Exhaust Emission and VTM

Estimation

2010 - 2030 e l PdN Area

Total_ Exhaust PM10 Total_ Exhaust PM25 Distance (Miles)

Fig Predicting Mobile Exhaust PM1025 (kgMonth) Emission and VTM Estimation 2010

- 2030 el PdN Area

44E+09

46E+09

48E+09

5E+09

52E+09

54E+09

56E+09

58E+09

6E+09

62E+09

0

5000000

10000000

15000000

20000000

25000000

30000000

20

10

20

11

20

12

20

13

20

14

20

15

20

16

20

17

20

18

20

21

20

22

20

23

20

24

20

25

20

26

20

27

20

28

20

29

20

30

EX

HA

US

T

EM

ISS

ION

MO

BIL

E (

KG

YE

AR

)

YEARS

Predict ing Mobile Exhaust Emission and

VTM Estimation

2010 - 2030 e l PdN Area

CO NO2 NO NOx Distance

Fig Predicting Mobile Exhaust Emission and VTM Estimation

2010 - 2030 el PdN Area in El Paso TX Area were estimated for

Total CO NOx NO2 NO emission in kilograms per year

(Source EPA MOVES 2014a model)

The simulated Exhaust emissions in the future years shows a trend of reduction of this type of emissions in the

future years one factor should be the new hybrid technology is increasing by 476 since 2010 to 2015 and

use of catalytic converters diesel particulate filters and improved fuels and engines Non-exhaustive sources

will increase in the coming years because there is no control in the material of manufacture composed by Fe

Cu and Mn also not to be able to reduce the number of events of braking (Accelerations and decelerations)

45E+09

5E+09

55E+09

6E+09

65E+09

0

50000

100000

150000

200000

250000

201

0

201

1

201

2

201

3

201

4

201

5

201

6

201

7

201

8

202

1

202

2

202

3

202

4

202

5

202

6

202

7

202

8

202

9

203

0

NO

N-

EX

HA

US

T

EM

ISS

ION

MO

BIL

E

(KG

YE

AR

)

YEARS

Predicting Non Exhaust Mobile

Emission and VTM Estimation

2010 - 2030 el PdN Area

Brake_PM10 Tire_PM10 Distance (Miles)

Fig Predicting Mobile Exhaust PM1025 (kgMonth) Emission and VTM

Estimation 2010 - 2030 el PdN Area

Daily Avg PM1025

Levels of PM Mobile Emission Non-Exhaust -Rush Hour Periods Fall 2010 Zip Code

79905

00

100

200

300

400

500

600

Mo

bil

e P

M1

0 (k

g)

Rush Hours

Daily Avg PM10

Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush Hours

Periods 2010 Zip Code 79905

Total Primary Exhaust

_PM10 WinterSpring

Brakewear

particulate_PM10

WinterSpringTirewear particulate_PM10

WinterSpring

Total Primary Exhaust

_PM10 Summer

Brakewear

particulate_PM10 Summer

Tirewear Particulate_PM10

Summer

Total Primary Exhaust

_PM10 Fall

Brakewear

particulate_PM10 Fall

Tirewear particulate_PM10

Fall

00

50

100

150

200

250

300

350

Mo

bil

e P

M2

5 (k

g)

Rush hours

Daily Avg PM25

Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush

Hours Periods 2010 Zip Code 79905

Total Primary Exhaust _PM25

WinterSpring

Brakewear Particulate_PM25

WinterSpring

Tirewear particulate_PM25

WinterSpring

Total Primary Exhaust _PM25

Summer

Brakewear particulate_PM25

Summer

Tirewear particulate_PM25

Summer

Total Primary Exhaust _PM25

Fall

Brakewear particulate_PM25

Fall

Tirewear particulate_PM25

Fall

Figure Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush Hours Figure Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush Hours

GIS EMISSIONS INVENTORY SYSTEM A geographic information system (GIS) was used to established geographic scenarios with processed images of seasonal mobile

emissions in the PdN region Seasonal mapping is visualized for different types of pollutants Brakewear Exhaust and Tyrewear

Fg Graphics of GIS and Seasonal mobile Emission of particulate matter emission inventory Seasonal emission simulations were performed in kilograms and five contributing inputs factors were identified for

modeling 1) On the composition of the particulate material from different sources such as Exhaust and Non exhaust (Brake wear Tirewear) 2) The Vehicles Equipment clasification were selected according to

the use of gasoline and diesel fuel (motorcycle passenger car Light Duty Vehicles Trucks refuse truck Light Duty Vehicles Light Commercial Truck Light Duty Vehicles School Bus)

Winter Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

120354 67860 19065

Spring Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

139767 86702 24463

Summer Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

94747 62481 17630

Fall Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

75510 45542 12596

251 Descriptive Statistics Data Analysis

Weekly Correlation Analysis of Mobile Emission PM10 (Exhaust-Non-Exhaust) and Respiratory

Diagnoses WinterSpring Summer and Fall 2010

0

2

4

6

8

10

0

50

100

150

200

250

300

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21

Mo

rbid

ity

Dis

ch

arg

e

for

all R

esp

ira

tory

Dis

ea

se

ICD

-9

(A

sth

ma

-Bro

nc

hitis

)

WinterSpring Week

Weekly Avg Mobile PM10 Concentrations during

WinterSpring 2010 and its Influence on Respiratory

Diagnoses

Zip Code 79905

Total Medical data ZIP Code 79902

Total Mobile Emission PM10 (Ugm3)

0

1

2

3

4

5

6

7

0

20

40

60

80

100

Mo

rbid

ity

Dis

ch

arg

e

for

all R

esp

ira

tory

Dis

ea

se

ICD

-9

(Ast

hm

aB

ron

ch

itis

)

Weekly Avg Mobile PM10 Concentrations during

Summer 2010 and its Influence on Respiratory

Diagnoses

Summer 2010 Zip Code 79905

Total Mobile Emission PM10

Hospital Admission (Asthma-Bronchitis)

0

2

4

6

8

10

12

0

20

40

60

80

100

120

140

160

180

200

Mo

rbid

ity

dis

ch

arg

es

for

all r

esp

ira

tory

dis

ea

se

Weekly Avg Mobile PM10 Concentrations

during Fall 2010 and its Influence on Respiratory

Diagnoses

Zip Code 79905

Total Medical data ZIP Code 79902

Total Mobile Emission PM10 (Ugm3)

Mobile(Exhaust-Non-

Exhaust) PM10 and

Asthma-Bronchitis)

Linear R

Square

WinterSpring 734 ndash 39

Summer 614 ndash 32

Fall 548 -29

PM10 Mobile emission (Exhaust-Non-Exhaust)contributed significantly

association to the incidence of RD

Weekly Correlation Analysis of PM 25 Mobile Emission (Exhaust-Non-Exhaust)

and Cardiovascular Diagnoses WinterSpring Summer and Fall 2010

0010203040

00500

100015002000

Wee

k 1

Wee

k 2

Wee

k 3

Wee

k 4

Wee

k 5

Wee

k 6

Wee

k 7

Wee

k 8

Wee

k 9

Wee

k 1

0

Wee

k 1

1

Wee

k 1

2

Wee

k 1

3

Wee

k 1

4

Wee

k 1

5

Wee

k 1

6

Wee

k 1

7

Wee

k 1

8

Wee

k 1

9

Wee

k 2

0

Wee

k 2

1

Morb

idit

y d

isch

arg

es f

or

all

card

iovasc

ula

r d

isea

se

Weekly Avg PM25 Mobile Concentrations during

WinterSpring 2010 and its Influence on all Heart

Diagnoses

Zip Code 79905

Total All Heart Disease PM 25 mobile (μgm3)

0010203040

00

500

1000

1500

Mo

rbid

ity

dis

ch

arg

es

for

all

ca

rdio

va

scu

lar

dis

ea

se

Weeks

CORRELATION BETWEEN MOBILE PM25 ugm3

EXPOSURE TO HEART DISEASES SYMPTOMS

SUMMER SEASON 2010

Total All Heart Disease PM 25 mobile (μgm3)

Figure Statistical Analyses of the Relationship Between PM25 Caused by Traffic Emission( 26 of total Emission) with Heart diseases Source Hospital Admissions for Asthma Acute Bronchitis and Heart diseases in El Paso County zip code 79905 from Texas Health Care

Information Council in Austin Texas (Texas Health Care Information Council 2000)

00

10

20

30

40

0

50

100

150

We

ek 3

6

We

ek 3

7

We

ek 3

8

We

ek 3

9

We

ek 4

0

We

ek 4

1

We

ek 4

2

We

ek 4

3

We

ek 4

4

We

ek 4

5

We

ek 4

6

We

ek 4

7

We

ek 4

8

We

ek 4

9

We

ek 5

0

We

ek 5

1

We

ek 5

2

We

ek 5

3

Mo

rbid

ity

dis

ch

arg

es

for

all

ca

rdio

va

scu

lar

dis

ea

se

CORRELATION BETWEEN MOBILE PM25 ugm3

EXPOSURE TO HEART DISEASES SYMPTOMS FALL

SEASON 2010

Total All Heart Disease PM 25 mobile (μgm3)

Mobile(Exhaust-

Non-Exhaust)

PM10 and

Asthma-

Bronchitis)

Linear R

Square

WinterSpring 833 -42

Summer 620 -32

Fall 501-26

PM10 Mobile

emission (Exhaust-

Non-

Exhaust)contribut

ed significantly

association to the

incidence of CVD

Diseases

Monthly Brake Mobile Emission PM1025 kg During year 2010 and its Influence on

Respiratory Diagnoses Zip Code 79905

00200040006000800010000

010000200003000040000

PM

10

Mo

bile

(K

g)

Months

Monthly Brake Mobile Emission PM10 kg during year

2010 and its Influence on Respiratory Diagnoses

Zip Code 79905

Primary PM 10

Brakewear 00100020003000400050006000

0

1000

2000

3000

4000

PM

25

Mo

bil

e(K

g)

Months

Monthly Brake Mobile Emission PM25 during

year 2010 and its Influence on Heart Diagnoses

Zip Code 79905

Primary PM 25

Brakewear

Heart Diseases

Hospital

Admission

Brake Mobile Emission

PM10 kg Asthma-

Bronchitis)

Brake Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=969 Linear Square R=856

Monthly Mobile Exhaust Emission PM1025 During year 2010 and its Influence on

Respiratory Diagnoses Zip Code 79905

0

200

400

600

800

1000

0

10000

20000

30000

40000

50000

1 3 5 7 9 11

PM

10

(K

g m

on

th)

Months

Monthly Mobile Exhaust Emission PM10 during

year 2010 and its Influence on Respiratory

Diagnoses

Zip Code 79905

Primary Exhaust

PM 10

Respiratory Disease

(Asthma

Bronchitis) Hospital

Admission

0

100

200

300

400

500

600

0

10000

20000

30000

40000

50000

1 2 3 4 5 6 7 8 9 101112

PM

25

(K

g m

on

th)

Months

Monthly Exhaust Mobile Emission PM25 during

year 2010 and its Influence on Heart Diagnoses

Zip Code 79905

Primary Exhaust PM

25

Heart Diseases

Hospital Admission

Exhaust Mobile Emission

PM10 kg Asthma-

Bronchitis)

Exhaust Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=929 Linear Square R=831

Monthly Tire wear Mobile Emission PM1025 During year 2010 and its Influence on Heart

Diagnoses Zip Code 79905

0

100

200

300

400

500

600

700

800

900

0

1000

2000

3000

4000

5000

6000

7000

8000

9000

1 2 3 4 5 6 7 8 9 10 11 12

PM

10

(K

g m

on

th)

Months

Monthly Tirewear Mobile Emission PM10 during year 2010

and its Influence on Heart Diagnoses

Zip Code 79905

Primary PM 10 Tirewear

Mobile Emission

Respiratory Disease

(Asthma Bronchitis)

Hospital Admission

0

100

200

300

400

500

600

0

200

400

600

800

1000

1200

1400

1 2 3 4 5 6 7 8 9 10 11 12

PM

25

(K

g m

on

th)

Months

Monthly Tirewear Mobile Emission PM25 during year 2010

and its Influence on Respiratory Diagnoses

Zip Code 79905

Primary PM 25Tirewear

Mobile Emission

Heart Diseases Hospital

Admission

Exhaust Mobile Emission

PM10 kg Asthma-

Bronchitis)

Exhaust Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=769 Linear Square R=715

Dona Ana County Zip Codes

88021880278807288048

Primary

Exhaust

PM 10 Zip

code

79905

Total

Primary

Exhaust

PM10

Dona Ana

Primary

Exhaust

PM 25 Zip

Code

79905

Total

Primary

Exhaust

PM25

Dona Ana

Series1 430378 111773 391915 102123

0

100000

200000

300000

400000

500000

AX

IS T

ITLE

Annual Comparison of the Mobile

Exhaust Emissions El Paso County

and Dona Ana 2010

Primary

PM 10

Brakewea

r Zip code

79905

Brakewea

r

particulat

e_PM10

Dona Ana

Primary

PM 10

Tirewear

Zip code

79905

Tirewear

particulat

e_PM10

Dona Ana

Series1 262585 48573 73754 11864

050000

100000150000200000250000300000

AX

IS T

ITLE

Annual Comparison of the Mobile

Brakewear Emissions El Paso County

and Dona Ana 2010

Figure Comparison of the Annual Mobile Emissions

of Primary PM10 Non-Exhauts (Brake ) from Dona

Ana County New Mexico and El Paso Texas Units

in KgMonth

Figure Comparison of the Annual Mobile Emissions

of Primary PM10-Exhauts Emission from Dona Ana

County New Mexico and El Paso Texas Units in

KgMonth

Primary

PM 25

Brakewe

ar Ziphellip

Brakewe

ar

particula

te_PMhellip

Primary

PM

25Tirewe

ar Ziphellip

Tirewear

particula

te_PM25

Donahellip

Series1 32645 6071 10919 1779

0

10000

20000

30000

40000

AX

IS T

ITLE

Annual Comparison of the

Mobile Exhaust Emissions El Paso

County and Dona Ana 2010

Figure Comparison of the Annual Mobile Emissions

of Primary PM10-Exhauts Emission from Dona Ana

County New Mexico and El Paso Texas Units in

KgMonth

Monthly Mobile Emission PM1025 kg During year 2006

and its Influence on Respiratory Diagnoses Dona Ana

County Zip Code 880218802788072

0

100

200

300

0

5000

10000

15000

Axi

s Ti

tle

Axis Title

Monthly Mobile Exhaust Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Total PrimaryMobile Exhaust_PM10

All Respiratory ICD-9 (AsthmaBronchitis)

050100150200250300

010002000300040005000

Axi

s Ti

tle

Axis Title

Monthly Mobile Brake Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Brakewearparticulate_PM10

All RespiratoryICD -9 (AsthmaBronchitis)

050100150200250300

0200400600800

10001200

Axi

s Ti

tle

Axis Title

Monthly Mobile Tirewear Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Tirewearparticulate_PM10

All Respiratory ICD -9 (AsthmaBronchitis)

Mobile Exhauts

Emission PM10

kg Asthma-

Bronchitis)

Brake Mobile

Emission PM10

kg and Heart

Diagnoses

Tirewear Mobile

Emission PM10

kg and Heart

Diagnoses

Linear Square

R= 951

Linear Square

R=625

Linear Square

R=525

Mobile Exhauts

Emission PM25

kg Asthma-

Bronchitis)

Brake Mobile

Emission PM25

kg and Heart

Diagnoses

Tirewear Mobile

Emission PM25

kg and Heart

Diagnoses

Linear Square

R= 986

Linear Square

R=691

Linear Square

R=601

Results

The results showed that mobile PM emissions in the urban areas close to urban Road and highways is putting at risk public health

and the proportion of diseases attributable to this exposure is potentially large

Brake wear emissions is much lower in freeways due to significantly reduced number of braking events while tire wear is much

higher in areas where studded tires are used The emission of exhaust gases are much higher in areas where there is a high

vehicular traffic

Brake Mobile

Emission PM10 kg

Asthma-Bronchitis)

Brake Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square

R=969

Linear Square

R=856

Exhaust Mobile

Emission PM10 kg

Asthma-Bronchitis)

Exhaust Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square

R=929

Linear Square

R=831

Tirewear Mobile

Emission PM10 kg

Asthma-Bronchitis)

Tirewear Mobile

Emission PM25 kg

and Heart Diagnoses

Linear Square R=769 Linear Square R=715

Brake Mobile

Emission PM10 kg

and Heart

Diagnoses

Brake Mobile

Emission PM25 kg

and Heart

Diagnoses

Exhaust Mobile

Emission PM10 kg

Asthma-Bronchitis)

Linear Square

R=625

Linear Square

R=691

Linear Square R=

951

Exhaust Mobile

Emission PM25 kg

Asthma-

Bronchitis)

Tire wear Mobile

Emission PM10 kg and

Heart Diagnoses

Tirewear Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square R=

986

Linear Square R=525 Linear Square

R=601

El Paso County

Dona Ana

County

BenMAP-CE

In this analysis the Program of Mapping and Analysis of Environmental Benefits-Community Edition

(BenMAP-CE) was used to Estimate the number and economic value of health impacts resulting from changes

in air pollution PM 25 Ugm3 in The El Paso Area

Health and Economic Benefits associated with the Response of PM25 Emission between

Base Year 2010

Number of Mortalities in 2010 Base Year Based on El Paso County Texas Department of State Health Services

Number of Mortalities in 2010 Base Year Based on El Paso County Texas

Department of State Health Services

cause of death

year

2010

Populatio

n

Affected

Backgro

und

Concentr

ation Pollutant

Rollback

Type

Avoided

Deaths

(

Populatio

n)

alzheimers disease 2010 40716 125 PM25

25

microgmAcircsup3

Rollback 9

diseases of the

heart 2010 15834 125 PM25

25

microgmAcircsup3

Rollback 35

influenza and

neumonia 2010 81432 125 PM25

25

microgmAcircsup3

Rollback 18

acute bronchitis

and bronchiolitis 2010 117624 125 PM25

25

microgmAcircsup3

Rollback 26

chronic lower

respiratory diseases 2010 54288 125 PM25

25

microgmAcircsup3

Rollback 12

The Basin-wide decrease in 4 ugm3 PM25 concentration after this

reduction control

Cause of death year 2010

Populatio

n

Affected

Background

Concentrati

on

Reduc

cion

scena

rio Polluta

nt

Rollback

Type

Avoi

ded

Deat

hs

(

Pop

ulati

on)

economic

benefits

analysis $

Alzheimers

disease 2010 121 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 9 12000

Diseases of the

heart 2010 470 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 35 35000

Influenza and

neumonia 2010 242 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 18 42500

Acute bronchitis

and bronchiolitis 2010 349 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 26 95000

Chronic lower

respiratory

diseases 2010 161 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 12 4500

$1 295000

PM25-related Mortalities Based on BenMAP-CE Estimate in 2010 Base Year with change in the concentrations levels

Health and Economic Benefits associated with the Response of PM25 Emission between

Base Year 2010 Increasing 7 Ugm3

Cause of death year 2010

Population

Affected

Deaths

avoided by

attaining 195

μgm3

standard

Background

Concentrati

on

Pollut

ant

Rollback

Type

Avoided

Deaths (

Populatio

n)

econo

mic

Unben

efits

analysi

s

Alzheimers

disease 2010 4524 195 PM25

25

microgmAcircsup3

Rollback 19 150000

Diseases of the

heart 2010 20358 195 PM25

25

microgmAcircsup3

Rollback 135 450000

Influenza and

neumonia 2010 126672 195 PM25

25

microgmAcircsup3

Rollback 38 525000

Acute bronchitis

and bronchiolitis 2010 162864 195 PM25

25

microgmAcircsup3

Rollback 36 122000

Chronic lower

respiratory

diseases 2010 99528 195 PM25

25

microgmAcircsup3

Rollback 12 650000

Conclusions

An excellent Pearson Correlation was established to analyze the relationship in the relative risks of hospitalization of Respiratory(RD) and cardiovascular (CVD) associated with ambient exposure caused by traffic emission in relation to their size andspecific sources of emission on different scenarios interior a border Urban Rural Urban restricted access (freeways andinterstates)

A significant correlation of PM1025 exposure from mobile emission and hospital admissions for selected Respiratory (RD) andcardiovascular (CVD) diagnoses was established The results showed that PM emissions in urban restricted access (freeways andinterstates) is mainly caused by traffic Therefore people living close to highways are more exposed higher vehicular emissions

Conclusions

We found statistically significant associations between mobile PM25 caused by traffic emission with Respiratory and Cardiovascular Diseases in the study areaSubsequently a correlation between cardio-respiratory mortality is established

A significant correlation of PM1025 exposure from mobile emission and hospital admissions for selected Respiratory (RD) and cardiovascular (CVD) diagnoses isestablished The results showed that PM emissions in urban restricted access (freeways and interstates) is mainly caused by traffic Therefore people living close tohighways receive higher vehicular emissions

The table shows the percentage of PM mobile exposure in the analyzed areas contributing to increase the risk of Respiratory and Cardiovascular Diseases

An examination was conducted of the synoptic and local meteorology for the June 2006 ozone episode using the WRF model to determine how meteorological parametersinfluence the formation transport and dispersion of ozone in the PdN The predominant synoptic feature of the ozone event day was the expansion intensification and slowprogression of an upper-level ridge of high pressure The high ozone episodes are associated with highly stable atmospheres strong temperature inversions with low mixingheights and therefore low mixing volumes Under these conditions emissions such as NOx lead to highly polluted conditions that favor ozone formation

BenMAP Conclusions

We have estimated the number and economic value of health impacts resulting

from changes in air pollution concentrations of PM 25 in the PdN region

Reduction of Pm 25 4 UGm3= Avoided 213 cases respiratory cardiovascular

diseses and Economic Benefits associated with the Response of PM25 Emission + $

1295000

Increase of PM25 7 ugm3 = increasing Dies= 326 economic Unbenefits= 2345000$

Bibliography

1 Dockery DW Pope CAI Xu X Spengler JD Ware JH Fay ME Ferris BG Speizer FE An association between air pollution and mortality in six US cities N Engl J Med 3291753ndash1759 (1993)

2 Samet JM Dominici F Curriero FC Coursac I Zeger SL Fine particulate air pollution and mortality in 20 US cities 1987ndash1994 N Engl J Med 3431742ndash1749 (2000)

3 Nel AE Diaz-Sanchez D Li N The role of particulate pollutants in pulmonary inflammation and asthma evidence for the involvement of organic chemicals and oxidative stress Curr Opin Pulm Med 20017 20ndash26

4 Westerholm R Karl-Erik E Exhaust emissions from lightand heavy-duty vehicles chemical composition impact of exhaust after treatment and fuel parameters Environ Health Perspect 102(suppl 4)13ndash23 (1994)

5 Bascom R Bromberg P Costa D Delvin R Dockery D Frampton M Lambert W Samet J Speizer F Utell

6 Health effects of outdoor air pollution Am J Respir Crit Care Med 1533ndash50 (1996)

7 Chow JC Watson JG Frazier CA Egami RT Goodrich A Ralph C Spatial and temporal source contributions to

8 PM10 and PM25 in Reno NV In PM-10 Implementation of Standards Transactions An APCAEPA International Speciality Conference San Francisco CA (Mathal CV Stonefield DH eds) PittsburghAPCA 1988439ndash457

9 overview In Particulate Matter Health and Regulatory Issues VIP-49 Proceedings of an International Specialty Conference 4ndash6 April 1995 Pittsburgh PA PittsburghAir and Waste Management Association 1995577ndash598

10 Kunzli N Kaiser R Medina S Studnicka M Chanel O

11 Filliger P Herry M Horak F Jr Puybonnieux-Texier V Quenel P et al Public-health impact of outdoor and traffic- related air pollution a European assessment Lancet 356795ndash801 (2000)

Bibliography

1 Sioutas C Delfino RJ Singh M Exposure assessment for atmospheric ultrafine particles (UFP) and implications in epidemiological research Environ Health Perspect 2005113947ndash955

2 Mosleh M Blau PJ Dumitrescu D (2004) Characteristics and morphology of wear particles from laboratory testing of disc brake materials Wear 2561128ndash1134

3 Kuumlnzli N et al (2000) Public-health impact of outdoor and traffi c-related air pollution a European assessment Lancet 356(9232)795ndash801

4 Dora C Phillips M eds (2000) Transport environment and health Copenhagen WHO Regional Office for Europe (WHO Regional Publications European Series No 89 httpwwweurowhointdocumente72015pdf accessed 26 November 2004)

5 Westerholm R Karl-Erik E Exhaust emissions from lightand

6 heavy-duty vehicles chemical composition impact of exhaust after treatment and fuel parameters Environ Health Perspect 102(suppl 4)13ndash23 (1994)

7 Fauser Tjell Mosbaek pigegaard Quantification of tire-Tread particles using extractable Organic Zinc as a Tracer Rubber Chemistry and Technology 1999 969Table shows some literature estimates of the contribution of tire wear to PM10 in air (Panko et al 2013) Gustafsson M Blomqvist G Gudmundsson A Dahl A Swietlicki E Bohgard M Lindbom J Ljungman A

8 Chen Y Shah N Huggins FE and Huffman GP (2006) Microanalysis of Ambient Particles from Lexington Ky by Electron Microscopy Atmos Environ 40 651ndash663

9 Donaldson K Tran CL Jimenez LA Duffin R Newby DE and Mills N (2005) Combustion-derived Nanoparticles A Review of Their Toxicology Following Inhalation Exposure Part Fibre Toxicol 2 10ndash23

10 Su D Serafino A Muller JO Jentoft RE Schlogl R and Fiorito S (2008) Cytotoxicity and Inflammatory Potential of Soot Particles of Low-emission Diesel Engines Environ Sci Technol 42 1761ndash1765

11 Maier KL Alessandrini F Beck-Speier I Hofer TPJ Diabatґe S Bitterle E Stoger T and Jakob T (2008) Health Effects of Ambient Particulate Matter-Biological Mechanisms and Inflammatory Responses to in Vitroand in Vivo Particle Exposures Inhalation Toxicol 20 319ndash337

Page 14: Studies of Air Pollutants and their Impact on Respiratory and ...€¦ · Ascarate Park C37 Monitoring Station: The National Ambient Air Quality Standard (NAAQS) for PM 10 and 2.5

Sources of Particulate Matter Emissions from traffic

Diesel exhaust particulate matter

This particulate toxic potential has been associated with serious adverse Health

effects including respiratory symptoms Pulmonary function and cardiovascular

diseases (Geller et al 2006 Bernstein et al 2004)

Brake wear particulate matter

Brake wear particulate matter Chemical content (iron(Fe) copper(Cu) Antimony(Sb) barium(Ba) this type of particulate can cause severe respiratory and cardiovascular damages and it is also known that Sb has been classified as a possible human pulmonary carcinogen by the International Agency for Research on Cancer (IARC 1989 Et al 2013)

Fig images of brake wear particles generated at a road simulation study ( centre lt25 μm right lt10

μm) Source [Kukutschovaacute et al 2011]

Tire wear particulate matter

The tire wear particles of the tires are generated either by frictional forces between the treadand the road pavement The chemical content Fe Cr Pb Ti Cr Cu Zn Sr Y Zr Sn Sb Ba LaCe and Pb)

Fig Examples of near spherical particles PM 10 and 25 which are originate from interaction of tires and pavements Source [Dahl et al 2006]

Study Area

The Paso del Norte (PdN) region Selected two strategic areas of study El Paso County zip code 79905 Urban area and Dona Ana County Zip Code 880218802788072 Rural Restricted urban access (freeways and interstates)

Map of the area of the simulation by the MOVES model in the study area

Geographic Domain Zip Code 79905 Urban Area (El Paso County)

Zip Codes 88021880278807288048 (Dona Ana County)

Urban road Delta Dr St 31o 45rsquo 5637- 106o 27rsquo 1212 10 miles

Cordova Bridge of the Americas 31o 45rsquo 4367- 106o 27rsquo 0506 15 miles

478 Highway interstate 31o 46rsquo 1326- 106o 27rsquo 0327 05 miles

110 Highway interstate 31o 46rsquo 1210- 106o 27rsquo 0066 10 miles

10 Interstate Gateway Blvd 31o 46rsquo 397- 106o 26rsquo 4769 05 miles

Chamizal Loop 478 31o 46rsquo 668- 106o 26rsquo 5456 05 miles

Alameda Loop 20 31o 46rsquo 1323- 106o 27rsquo 0328 10 miles

Paisano Dr St Patriot freeway

route 62

31o 46rsquo 0669- 106o 27rsquo 212 15 miles

St Piedras 31o 46rsquo 1326- 106o 27rsquo 0327 10 miles

Dona Ana County Miles

Interstate 25 32o 23rsquo 0561 -106 48

1054 32o 23rsquo 3434- -

106 48 1054 32o 23rsquo

5660 106 48 4314

50

Geographic domain To obtain the simulation mobile data from modelMOVES2010a was configurated the coordinates selected in the study areas

El Paso County

PM25 Estimation from Aerosol Optical Depth (AOD) using

satellites

We examined the relationship

between Aerosol Optical Depth

(AOD) estimated from satellite data

at 5 km spatial resolution and the

mass of fine particles le25 μm in

aerodynamic diameter (PM25)

monitored on the ground in El PdN

area PM25 data was recorded from

air quality monitoring Chamizal

station (TCEQ) on different periods

Our analysis shows a significant

positive association between AOD

and PM25

Time-series and scatter plots of AOD estimated PM25 and surface PM25

Analysis of the meteorological factors and synoptic conditions leading to a local high

ozone event episode June 12-21 2006

Meteorology plays a critical role in determining atmospheric ozone concentrations A good synoptic scale weather forecast is essential to accurately forecast tropospheric and surface ozone concentrations

Figure 1 The domain configuration and Landuse categories

resolution 25 km domainFigure 2 The Geopotential height at 500 mb Figure 3 depicts the 850 mb at a lower altitude The

white regions observed in the graph correspond to

mountainous areas

Figure 4 Temperature at 2m height

above surface at 22 UTC June 18 2006

36 km resolution

Performance Evaluation

01020304050

Ju

ne

137

130

0

190

0

10

0

Ju

ne

157

130

0

190

0

10

0

Ju

ne

187

130

0

190

0

10

0

Tem

pe

ratu

re (⁰C

)

Local time (Hrs)

C41 June 13-19 2006

WRF_temperature

(⁰C)

TCEQ_temperature

(⁰C)

01020304050

June1

37

100

0

130

0

160

0

190

0

220

0

10

0

40

0

June1

57

100

0

130

0

160

0

190

0

220

0

10

0

40

0

June1

87

100

0

130

0

160

0

190

0

220

0

10

0

40

0

Rel

ativ

e h

um

idit

y (

)

Local time (Hrs)

C41 June 13-19 2006

WRF_rh () TCEQ_relative humidity ()

0

5

10

15

20

June

137 10

13

16

19

22 1 4

June

157 10

13

16

19

22 1 4

June

187 10

13

16

19

22 1 4

Win

d s

pee

d (

ms

Local time(Hrs)

C12 June 13-192006

WRF_wind speed (ms) TCEQ_ wind speed (ms)

We evaluate the WRF modelrsquos performance

by comparing against corresponding

experimental TCEQ data and performing the

required statistical analysis

HYSPLIT Model

HYSPLIT was simulated and showed that the ozone is mostly transported to El Paso from north western and south western US and Mexican regions during the 72 hours duration of the simulation

0

20

40

60

80

100

1200

00

10

02

00

30

04

00

50

06

00

70

08

00

90

01

00

01

10

01

20

01

30

01

40

01

50

01

60

01

70

01

80

01

90

02

00

02

10

02

20

02

30

0

Ho

url

y o

zon

e [

pp

b]

0102030405060708090

00

01

00

20

03

00

40

05

00

60

07

00

80

09

00

10

00

11

00

12

00

13

00

14

00

15

00

16

00

17

00

18

00

19

00

20

00

21

00

22

00

23

00

Ho

url

y o

zon

e [

pp

b]

June 18th June 19th

Performance Evaluation

01020304050

Ju

ne

137

130

0

190

0

10

0

Ju

ne

157

130

0

190

0

10

0

Ju

ne

187

130

0

190

0

10

0

Tem

pe

ratu

re (⁰C

)

Local time (Hrs)

C41 June 13-19 2006

WRF_temperature

(⁰C)

TCEQ_temperature

(⁰C)

0

50

100

150

June1

37

100

0

130

0

160

0

190

0

220

0

10

0

40

0

June1

57

100

0

130

0

160

0

190

0

220

0

10

0

40

0

June1

87

100

0

130

0

160

0

190

0

220

0

10

0

40

0Ozo

ne

(pp

b)

Local time (Hrs)

C41 June 13-19 2006

CAMx_ozone (ppbV) TCEQ_ozone (ppb)

0

10

20

30

40

50

June1

37

100

0

130

0

160

0

190

0

220

0

10

0

40

0

June1

57

100

0

130

0

160

0

190

0

220

0

10

0

40

0

June1

87

100

0

130

0

160

0

190

0

220

0

10

0

40

0

Rel

ativ

e h

um

idit

y (

)

Local time (Hrs)

C41 June 13-19 2006

WRF_rh () TCEQ_relative humidity ()

0

5

10

15

20

June

137 10

13

16

19

22 1 4

June

157 10

13

16

19

22 1 4

June

187 10

13

16

19

22 1 4W

ind

sp

eed

(m

sLocal time(Hrs)

C12 June 13-192006

WRF_wind speed (ms) TCEQ_ wind speed (ms)

Methodology

Medical Data The data by weekly monthly and year for daily emergency room and hospital admission for the respiratory

infections (RD) and cardiovascular diseases (CVD) was extracted from hospitals records located in the El PdN

the system includes data on type of admission primary and secondary causes of admissionRESPIRATORY DISEASE

Bronquitis amp Chronic Bronchitis 466 - 4661 491 - 4919

Asthma 463 - 4939

Emphysema 492

Respiratory failure 51881

HEART DISEASE

Accute Myocardial Infarction 410

Coronary Athersclerosis 4140

Other Ischemic Heart Disease 411-4139 4141-4149

Cardiac Dyshythmias 427

Essential hypertension 401

Acute myocardial infarction 410

Congestive Heart Failure 4280 4282-4284

Hypertensive heart disease 402

Table 1 ICD -9 Codes for Respiratory and Cardiovascular Diseases

0

50

100

150

200

250

300

Wee

k 1

Wee

k 2

Wee

k 3

Wee

k 4

Wee

k 5

Wee

k 6

Wee

k 7

Wee

k 8

Wee

k 9

Wee

k 1

0

Wee

k 1

1

Wee

k 1

2

Wee

k 1

3

Wee

k 1

4

Wee

k 1

5

Wee

k 1

6

Wee

k 1

7

Wee

k 1

8

Wee

k 1

9

Wee

k 2

0

Wee

k 2

1

Mo

rb

idit

y D

isch

arg

e fo

r a

ll R

esp

ira

tory

Dis

ease

IC

D-9

(

Ast

hm

aB

ro

nch

itis

)

Weekly Morbidity Discharges of all the Listed Diagnoses for All

Respiratory Disease During WinterSpring 2010

Asthma-Bronchitis

EPA MOVES Model for Estimating Emission

Inventories

Motor Vehicle Emission Simulator (MOVES 2010b) will be configuredin The El Paso North Region for Calculate five categories of PM10

PM25 total Emission inventories from all on-road traffic over a

variety of scales within periods of time selected weeks months

and years

Moves (Motor Vehicle Emission

Simulator)

The emission model is develop using the current equation to calculate direct traffic emissions from

vehicles in the form of PM is

Eext annual emissions are measured in grams of miles traveled by the vehicle (gVMT )

SL is the road surface loading in (gm2)

W is the average weight in tons of the vehicles on the road

K is the particle size multiplier for particle size range (eg gVMT for PM10 when using grams and miles)

P is the 7 number of wet days with at least 0254 mm of precipitation during the averaging period

N is the number of years considered in the averaging period

C is the particle size specific emissions factor in units of interest vehicle direct exhaust brake wear and tirewear

Modeling Simulation Domain and Emissions Scenarios

For simulations of mobile air quality emission inventories a motor vehicle emission simulator EPA (MOVES 2014a) was used

The modeling use input factors divided into seven section

parameters

On-Road Inventory local data

input

Scale

Geographic Bounds

Traffic intensity

Vehicle Type

Pollutants

Road Type

Fuel Types

Figure Source EPA US Environmental Protection Agency 2012- Moves 2010b Model

EPA Moves 2014a The modeling used input factors divided into six section

parameters On-Road Inventory local data input

Geographic Domains CountyNonattainment Area

Vehicle-Miles Traveled (VMT) is the total number of miles driven by all vehicles withina given time period and geographic area

Average speed range from 25 miles per

hour to 65 miles per hour

Vehicle Classes Motorcycle PassengerCarTruks light-duty Commercial Truck(6001-8500 lbs) Buses heave-duty trucksRefuse trucks School Bus Single UnitShort Haul-truck Single Unit Long Haul-truck Long Haul Truck Heavy-DutyVehicles (26001-33000 lbs)

Pollutants

Road TypeRural restricted Acces(Freeways and interstates) Rural and Restricted Acces Urban Restricted Acces Off-Network

Fuel Types Gasoline Diesel Fuel

Specific Road Types

Two road types for running emission from the MOVES can be

selected

(freeways and interstates)

Interior urban Urban

Figure Source EPA US Environmental Protection Agency 2012- Moves 2010b Model

VehiclesEquipment

This panel show which on-road vehicles will be modeled

Figure Source EPA US Environmental Protection Agency 2012- Moves 2010b Model

Long haul truck Short haul truck Inercity bus Ligth comercial truck

Passenger car Passenger truck Refuse truck

School bus Single unit long haul-truck

Single unit short haul-truck

Transit bus

Motor home

Motorcycle

Based on Department of Transportation Highway MOVES will Estimates Traffic

Emissions from Cars Trucks amp Motorcycles

Output Data Moves 2014a

Inventories of PM 10 25 Mobile Emission from all

on-Road Traffic

Exhaust Emission PM 10 25 gramsmile

Brake Wear Emission PM 10 25 gramsmile

Tire wear Emission PM 10 25 gramsmile

Date of Vehicle miles traveled (VMT) for

Day Week Month Year

Total Vehicle population

Vehicle age distribution

Simulation of Mobile Emission in the El PdN Region Zip Code 79905

Figure Total Emissions from road traffic in El Paso TX Area were estimated for PM10

Exhaust and Non exhaust emission in kilogramsmonth (Source EPA MOVES 2014a)

0

10000

20000

30000

40000

50000

PM

10 k

gM

on

th

Months

Monthly PM 10 Exhaust and Non-Exhaust Mobile Emissions 2010

On-Road Urban Restricted Area Zip Code 79905

Primary Exhaust PM 10 (kg) Primary PM 10 Brakewear (kg)

Primary PM 10 Tirewear (kg)

05000

100001500020000250003000035000400004500050000

PM

25

kg

Mo

nth

Months

Monthly PM 25 Exhaust and Non-Exhaust Mobile Emission 2010

On-Road Urban Restricted Area Zip Code 79905

Primary Exhaust PM 25 (kg) Primary PM 25 Brakewear (kg) Primary PM 25Tirewear (kg)

Figure Total Emissions from road traffic in El Paso TX Area were estimated for PM25

Exhaust and Non exhaust emission in kilogramsmonth (Source EPA MOVES 2014a)

Total Emissions from Road Traffic in El Paso County PM1025 Exhaust and Non exhaust Emission in kilogramsmonth

Taking the interests to the health risks related to PM 1025 mobile emission were simulated

Exhaust and Non-exhaust emissions contribute almost equally to total traffic-related PM1025 Emissions (Querol et al 2004 Bukowiecki et al 2009a Amato et al 2011)

Monthly PM 10 25 Exhaust and Non-Exhaust (BrakewearTirewear) Mobile

Emission 2010 On-Road Urban Restricted Area Zip Code 79905

Figure Total Emissions from road traffic in El Paso TX Area were estimated for PM10 25 Exhaust and Non Exhaust mobile

emission in kilograms per month (Source EPA MOVES)

0

10000

20000

30000

40000

50000

January February March April May June July August September October November December

PM

10

25

(K

ilog

ram

s)

Months

Summary- Monthly PM 10 25 Exhaust and Non-Exhaust Mobile

Emission 2010 On-Road Urban Restricted Area Zip Code 79905

Primary Exhaust PM 10 Primary PM 10 Brakewear Primary PM 10 Tirewear

Primary Exhaust PM 25 Primary PM 25 Brakewear Primary PM 25Tirewear

Exhaust Emissions PM1025 is reaching maximum emission 48000-42000 thousand of Kgmonth followedby Brake wear 29000-5000 thousand kgmonth and Tire wear with 9000-2000 kgmonth The results showthat the emissions of PM derived mainly from Exhaust and Brake are significantly higher in Urban Area

Annual Contribution of Mobile Emission PM 1025 (Kg) Zip Code 79905 El

Paso County 2010

Total Primary

Exhaust _PM10

39

Total Primary

Exhaust _PM25

36

Brakewear

particulate_PM10

18

Tirewear

particulate_PM10

4

Brakewear

particulate_PM25

2

Tirewear

particulate_PM25

1

0

5

10

15

20

25

30

35

40

45

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53

Fig Annual Average PM10 Concentrations at the

Chamizal C41 Station and PM1025 mobile

Concentration Zip code 79905

PM10 TCEQ (μgm3) Total Mobile Emission PM10 (Ugm3)

Fig Exhaust Emission is Contributing Approximately 74 of total

PM1025 Mobile Emissions following of Brake wear with 20 and Tire

wear with 5

Annual Average PM1025 ugm3 Mobile Emissions (Moves) 26 Chamizal C41

Monitoring Station (TCEQ Chamizal Station )

Predicting Mobile Emission and VTM

Estimation The PdN Region 2010

44E+09

46E+09

48E+09

5E+09

52E+09

54E+09

56E+09

58E+09

6E+09

62E+09

0

50000

100000

150000

200000

250000

300000

350000

20

10

20

11

20

12

20

13

20

14

20

15

20

16

20

17

20

18

20

21

20

22

20

23

20

24

20

25

20

26

20

27

20

28

20

29

20

30

EX

HA

US

T

EM

ISS

ION

MO

BIL

E (

KG

YE

AR

)

YEARS

Predict ing Mobile Exhaust Emission and VTM

Estimation

2010 - 2030 e l PdN Area

Total_ Exhaust PM10 Total_ Exhaust PM25 Distance (Miles)

Fig Predicting Mobile Exhaust PM1025 (kgMonth) Emission and VTM Estimation 2010

- 2030 el PdN Area

44E+09

46E+09

48E+09

5E+09

52E+09

54E+09

56E+09

58E+09

6E+09

62E+09

0

5000000

10000000

15000000

20000000

25000000

30000000

20

10

20

11

20

12

20

13

20

14

20

15

20

16

20

17

20

18

20

21

20

22

20

23

20

24

20

25

20

26

20

27

20

28

20

29

20

30

EX

HA

US

T

EM

ISS

ION

MO

BIL

E (

KG

YE

AR

)

YEARS

Predict ing Mobile Exhaust Emission and

VTM Estimation

2010 - 2030 e l PdN Area

CO NO2 NO NOx Distance

Fig Predicting Mobile Exhaust Emission and VTM Estimation

2010 - 2030 el PdN Area in El Paso TX Area were estimated for

Total CO NOx NO2 NO emission in kilograms per year

(Source EPA MOVES 2014a model)

The simulated Exhaust emissions in the future years shows a trend of reduction of this type of emissions in the

future years one factor should be the new hybrid technology is increasing by 476 since 2010 to 2015 and

use of catalytic converters diesel particulate filters and improved fuels and engines Non-exhaustive sources

will increase in the coming years because there is no control in the material of manufacture composed by Fe

Cu and Mn also not to be able to reduce the number of events of braking (Accelerations and decelerations)

45E+09

5E+09

55E+09

6E+09

65E+09

0

50000

100000

150000

200000

250000

201

0

201

1

201

2

201

3

201

4

201

5

201

6

201

7

201

8

202

1

202

2

202

3

202

4

202

5

202

6

202

7

202

8

202

9

203

0

NO

N-

EX

HA

US

T

EM

ISS

ION

MO

BIL

E

(KG

YE

AR

)

YEARS

Predicting Non Exhaust Mobile

Emission and VTM Estimation

2010 - 2030 el PdN Area

Brake_PM10 Tire_PM10 Distance (Miles)

Fig Predicting Mobile Exhaust PM1025 (kgMonth) Emission and VTM

Estimation 2010 - 2030 el PdN Area

Daily Avg PM1025

Levels of PM Mobile Emission Non-Exhaust -Rush Hour Periods Fall 2010 Zip Code

79905

00

100

200

300

400

500

600

Mo

bil

e P

M1

0 (k

g)

Rush Hours

Daily Avg PM10

Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush Hours

Periods 2010 Zip Code 79905

Total Primary Exhaust

_PM10 WinterSpring

Brakewear

particulate_PM10

WinterSpringTirewear particulate_PM10

WinterSpring

Total Primary Exhaust

_PM10 Summer

Brakewear

particulate_PM10 Summer

Tirewear Particulate_PM10

Summer

Total Primary Exhaust

_PM10 Fall

Brakewear

particulate_PM10 Fall

Tirewear particulate_PM10

Fall

00

50

100

150

200

250

300

350

Mo

bil

e P

M2

5 (k

g)

Rush hours

Daily Avg PM25

Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush

Hours Periods 2010 Zip Code 79905

Total Primary Exhaust _PM25

WinterSpring

Brakewear Particulate_PM25

WinterSpring

Tirewear particulate_PM25

WinterSpring

Total Primary Exhaust _PM25

Summer

Brakewear particulate_PM25

Summer

Tirewear particulate_PM25

Summer

Total Primary Exhaust _PM25

Fall

Brakewear particulate_PM25

Fall

Tirewear particulate_PM25

Fall

Figure Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush Hours Figure Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush Hours

GIS EMISSIONS INVENTORY SYSTEM A geographic information system (GIS) was used to established geographic scenarios with processed images of seasonal mobile

emissions in the PdN region Seasonal mapping is visualized for different types of pollutants Brakewear Exhaust and Tyrewear

Fg Graphics of GIS and Seasonal mobile Emission of particulate matter emission inventory Seasonal emission simulations were performed in kilograms and five contributing inputs factors were identified for

modeling 1) On the composition of the particulate material from different sources such as Exhaust and Non exhaust (Brake wear Tirewear) 2) The Vehicles Equipment clasification were selected according to

the use of gasoline and diesel fuel (motorcycle passenger car Light Duty Vehicles Trucks refuse truck Light Duty Vehicles Light Commercial Truck Light Duty Vehicles School Bus)

Winter Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

120354 67860 19065

Spring Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

139767 86702 24463

Summer Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

94747 62481 17630

Fall Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

75510 45542 12596

251 Descriptive Statistics Data Analysis

Weekly Correlation Analysis of Mobile Emission PM10 (Exhaust-Non-Exhaust) and Respiratory

Diagnoses WinterSpring Summer and Fall 2010

0

2

4

6

8

10

0

50

100

150

200

250

300

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21

Mo

rbid

ity

Dis

ch

arg

e

for

all R

esp

ira

tory

Dis

ea

se

ICD

-9

(A

sth

ma

-Bro

nc

hitis

)

WinterSpring Week

Weekly Avg Mobile PM10 Concentrations during

WinterSpring 2010 and its Influence on Respiratory

Diagnoses

Zip Code 79905

Total Medical data ZIP Code 79902

Total Mobile Emission PM10 (Ugm3)

0

1

2

3

4

5

6

7

0

20

40

60

80

100

Mo

rbid

ity

Dis

ch

arg

e

for

all R

esp

ira

tory

Dis

ea

se

ICD

-9

(Ast

hm

aB

ron

ch

itis

)

Weekly Avg Mobile PM10 Concentrations during

Summer 2010 and its Influence on Respiratory

Diagnoses

Summer 2010 Zip Code 79905

Total Mobile Emission PM10

Hospital Admission (Asthma-Bronchitis)

0

2

4

6

8

10

12

0

20

40

60

80

100

120

140

160

180

200

Mo

rbid

ity

dis

ch

arg

es

for

all r

esp

ira

tory

dis

ea

se

Weekly Avg Mobile PM10 Concentrations

during Fall 2010 and its Influence on Respiratory

Diagnoses

Zip Code 79905

Total Medical data ZIP Code 79902

Total Mobile Emission PM10 (Ugm3)

Mobile(Exhaust-Non-

Exhaust) PM10 and

Asthma-Bronchitis)

Linear R

Square

WinterSpring 734 ndash 39

Summer 614 ndash 32

Fall 548 -29

PM10 Mobile emission (Exhaust-Non-Exhaust)contributed significantly

association to the incidence of RD

Weekly Correlation Analysis of PM 25 Mobile Emission (Exhaust-Non-Exhaust)

and Cardiovascular Diagnoses WinterSpring Summer and Fall 2010

0010203040

00500

100015002000

Wee

k 1

Wee

k 2

Wee

k 3

Wee

k 4

Wee

k 5

Wee

k 6

Wee

k 7

Wee

k 8

Wee

k 9

Wee

k 1

0

Wee

k 1

1

Wee

k 1

2

Wee

k 1

3

Wee

k 1

4

Wee

k 1

5

Wee

k 1

6

Wee

k 1

7

Wee

k 1

8

Wee

k 1

9

Wee

k 2

0

Wee

k 2

1

Morb

idit

y d

isch

arg

es f

or

all

card

iovasc

ula

r d

isea

se

Weekly Avg PM25 Mobile Concentrations during

WinterSpring 2010 and its Influence on all Heart

Diagnoses

Zip Code 79905

Total All Heart Disease PM 25 mobile (μgm3)

0010203040

00

500

1000

1500

Mo

rbid

ity

dis

ch

arg

es

for

all

ca

rdio

va

scu

lar

dis

ea

se

Weeks

CORRELATION BETWEEN MOBILE PM25 ugm3

EXPOSURE TO HEART DISEASES SYMPTOMS

SUMMER SEASON 2010

Total All Heart Disease PM 25 mobile (μgm3)

Figure Statistical Analyses of the Relationship Between PM25 Caused by Traffic Emission( 26 of total Emission) with Heart diseases Source Hospital Admissions for Asthma Acute Bronchitis and Heart diseases in El Paso County zip code 79905 from Texas Health Care

Information Council in Austin Texas (Texas Health Care Information Council 2000)

00

10

20

30

40

0

50

100

150

We

ek 3

6

We

ek 3

7

We

ek 3

8

We

ek 3

9

We

ek 4

0

We

ek 4

1

We

ek 4

2

We

ek 4

3

We

ek 4

4

We

ek 4

5

We

ek 4

6

We

ek 4

7

We

ek 4

8

We

ek 4

9

We

ek 5

0

We

ek 5

1

We

ek 5

2

We

ek 5

3

Mo

rbid

ity

dis

ch

arg

es

for

all

ca

rdio

va

scu

lar

dis

ea

se

CORRELATION BETWEEN MOBILE PM25 ugm3

EXPOSURE TO HEART DISEASES SYMPTOMS FALL

SEASON 2010

Total All Heart Disease PM 25 mobile (μgm3)

Mobile(Exhaust-

Non-Exhaust)

PM10 and

Asthma-

Bronchitis)

Linear R

Square

WinterSpring 833 -42

Summer 620 -32

Fall 501-26

PM10 Mobile

emission (Exhaust-

Non-

Exhaust)contribut

ed significantly

association to the

incidence of CVD

Diseases

Monthly Brake Mobile Emission PM1025 kg During year 2010 and its Influence on

Respiratory Diagnoses Zip Code 79905

00200040006000800010000

010000200003000040000

PM

10

Mo

bile

(K

g)

Months

Monthly Brake Mobile Emission PM10 kg during year

2010 and its Influence on Respiratory Diagnoses

Zip Code 79905

Primary PM 10

Brakewear 00100020003000400050006000

0

1000

2000

3000

4000

PM

25

Mo

bil

e(K

g)

Months

Monthly Brake Mobile Emission PM25 during

year 2010 and its Influence on Heart Diagnoses

Zip Code 79905

Primary PM 25

Brakewear

Heart Diseases

Hospital

Admission

Brake Mobile Emission

PM10 kg Asthma-

Bronchitis)

Brake Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=969 Linear Square R=856

Monthly Mobile Exhaust Emission PM1025 During year 2010 and its Influence on

Respiratory Diagnoses Zip Code 79905

0

200

400

600

800

1000

0

10000

20000

30000

40000

50000

1 3 5 7 9 11

PM

10

(K

g m

on

th)

Months

Monthly Mobile Exhaust Emission PM10 during

year 2010 and its Influence on Respiratory

Diagnoses

Zip Code 79905

Primary Exhaust

PM 10

Respiratory Disease

(Asthma

Bronchitis) Hospital

Admission

0

100

200

300

400

500

600

0

10000

20000

30000

40000

50000

1 2 3 4 5 6 7 8 9 101112

PM

25

(K

g m

on

th)

Months

Monthly Exhaust Mobile Emission PM25 during

year 2010 and its Influence on Heart Diagnoses

Zip Code 79905

Primary Exhaust PM

25

Heart Diseases

Hospital Admission

Exhaust Mobile Emission

PM10 kg Asthma-

Bronchitis)

Exhaust Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=929 Linear Square R=831

Monthly Tire wear Mobile Emission PM1025 During year 2010 and its Influence on Heart

Diagnoses Zip Code 79905

0

100

200

300

400

500

600

700

800

900

0

1000

2000

3000

4000

5000

6000

7000

8000

9000

1 2 3 4 5 6 7 8 9 10 11 12

PM

10

(K

g m

on

th)

Months

Monthly Tirewear Mobile Emission PM10 during year 2010

and its Influence on Heart Diagnoses

Zip Code 79905

Primary PM 10 Tirewear

Mobile Emission

Respiratory Disease

(Asthma Bronchitis)

Hospital Admission

0

100

200

300

400

500

600

0

200

400

600

800

1000

1200

1400

1 2 3 4 5 6 7 8 9 10 11 12

PM

25

(K

g m

on

th)

Months

Monthly Tirewear Mobile Emission PM25 during year 2010

and its Influence on Respiratory Diagnoses

Zip Code 79905

Primary PM 25Tirewear

Mobile Emission

Heart Diseases Hospital

Admission

Exhaust Mobile Emission

PM10 kg Asthma-

Bronchitis)

Exhaust Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=769 Linear Square R=715

Dona Ana County Zip Codes

88021880278807288048

Primary

Exhaust

PM 10 Zip

code

79905

Total

Primary

Exhaust

PM10

Dona Ana

Primary

Exhaust

PM 25 Zip

Code

79905

Total

Primary

Exhaust

PM25

Dona Ana

Series1 430378 111773 391915 102123

0

100000

200000

300000

400000

500000

AX

IS T

ITLE

Annual Comparison of the Mobile

Exhaust Emissions El Paso County

and Dona Ana 2010

Primary

PM 10

Brakewea

r Zip code

79905

Brakewea

r

particulat

e_PM10

Dona Ana

Primary

PM 10

Tirewear

Zip code

79905

Tirewear

particulat

e_PM10

Dona Ana

Series1 262585 48573 73754 11864

050000

100000150000200000250000300000

AX

IS T

ITLE

Annual Comparison of the Mobile

Brakewear Emissions El Paso County

and Dona Ana 2010

Figure Comparison of the Annual Mobile Emissions

of Primary PM10 Non-Exhauts (Brake ) from Dona

Ana County New Mexico and El Paso Texas Units

in KgMonth

Figure Comparison of the Annual Mobile Emissions

of Primary PM10-Exhauts Emission from Dona Ana

County New Mexico and El Paso Texas Units in

KgMonth

Primary

PM 25

Brakewe

ar Ziphellip

Brakewe

ar

particula

te_PMhellip

Primary

PM

25Tirewe

ar Ziphellip

Tirewear

particula

te_PM25

Donahellip

Series1 32645 6071 10919 1779

0

10000

20000

30000

40000

AX

IS T

ITLE

Annual Comparison of the

Mobile Exhaust Emissions El Paso

County and Dona Ana 2010

Figure Comparison of the Annual Mobile Emissions

of Primary PM10-Exhauts Emission from Dona Ana

County New Mexico and El Paso Texas Units in

KgMonth

Monthly Mobile Emission PM1025 kg During year 2006

and its Influence on Respiratory Diagnoses Dona Ana

County Zip Code 880218802788072

0

100

200

300

0

5000

10000

15000

Axi

s Ti

tle

Axis Title

Monthly Mobile Exhaust Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Total PrimaryMobile Exhaust_PM10

All Respiratory ICD-9 (AsthmaBronchitis)

050100150200250300

010002000300040005000

Axi

s Ti

tle

Axis Title

Monthly Mobile Brake Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Brakewearparticulate_PM10

All RespiratoryICD -9 (AsthmaBronchitis)

050100150200250300

0200400600800

10001200

Axi

s Ti

tle

Axis Title

Monthly Mobile Tirewear Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Tirewearparticulate_PM10

All Respiratory ICD -9 (AsthmaBronchitis)

Mobile Exhauts

Emission PM10

kg Asthma-

Bronchitis)

Brake Mobile

Emission PM10

kg and Heart

Diagnoses

Tirewear Mobile

Emission PM10

kg and Heart

Diagnoses

Linear Square

R= 951

Linear Square

R=625

Linear Square

R=525

Mobile Exhauts

Emission PM25

kg Asthma-

Bronchitis)

Brake Mobile

Emission PM25

kg and Heart

Diagnoses

Tirewear Mobile

Emission PM25

kg and Heart

Diagnoses

Linear Square

R= 986

Linear Square

R=691

Linear Square

R=601

Results

The results showed that mobile PM emissions in the urban areas close to urban Road and highways is putting at risk public health

and the proportion of diseases attributable to this exposure is potentially large

Brake wear emissions is much lower in freeways due to significantly reduced number of braking events while tire wear is much

higher in areas where studded tires are used The emission of exhaust gases are much higher in areas where there is a high

vehicular traffic

Brake Mobile

Emission PM10 kg

Asthma-Bronchitis)

Brake Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square

R=969

Linear Square

R=856

Exhaust Mobile

Emission PM10 kg

Asthma-Bronchitis)

Exhaust Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square

R=929

Linear Square

R=831

Tirewear Mobile

Emission PM10 kg

Asthma-Bronchitis)

Tirewear Mobile

Emission PM25 kg

and Heart Diagnoses

Linear Square R=769 Linear Square R=715

Brake Mobile

Emission PM10 kg

and Heart

Diagnoses

Brake Mobile

Emission PM25 kg

and Heart

Diagnoses

Exhaust Mobile

Emission PM10 kg

Asthma-Bronchitis)

Linear Square

R=625

Linear Square

R=691

Linear Square R=

951

Exhaust Mobile

Emission PM25 kg

Asthma-

Bronchitis)

Tire wear Mobile

Emission PM10 kg and

Heart Diagnoses

Tirewear Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square R=

986

Linear Square R=525 Linear Square

R=601

El Paso County

Dona Ana

County

BenMAP-CE

In this analysis the Program of Mapping and Analysis of Environmental Benefits-Community Edition

(BenMAP-CE) was used to Estimate the number and economic value of health impacts resulting from changes

in air pollution PM 25 Ugm3 in The El Paso Area

Health and Economic Benefits associated with the Response of PM25 Emission between

Base Year 2010

Number of Mortalities in 2010 Base Year Based on El Paso County Texas Department of State Health Services

Number of Mortalities in 2010 Base Year Based on El Paso County Texas

Department of State Health Services

cause of death

year

2010

Populatio

n

Affected

Backgro

und

Concentr

ation Pollutant

Rollback

Type

Avoided

Deaths

(

Populatio

n)

alzheimers disease 2010 40716 125 PM25

25

microgmAcircsup3

Rollback 9

diseases of the

heart 2010 15834 125 PM25

25

microgmAcircsup3

Rollback 35

influenza and

neumonia 2010 81432 125 PM25

25

microgmAcircsup3

Rollback 18

acute bronchitis

and bronchiolitis 2010 117624 125 PM25

25

microgmAcircsup3

Rollback 26

chronic lower

respiratory diseases 2010 54288 125 PM25

25

microgmAcircsup3

Rollback 12

The Basin-wide decrease in 4 ugm3 PM25 concentration after this

reduction control

Cause of death year 2010

Populatio

n

Affected

Background

Concentrati

on

Reduc

cion

scena

rio Polluta

nt

Rollback

Type

Avoi

ded

Deat

hs

(

Pop

ulati

on)

economic

benefits

analysis $

Alzheimers

disease 2010 121 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 9 12000

Diseases of the

heart 2010 470 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 35 35000

Influenza and

neumonia 2010 242 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 18 42500

Acute bronchitis

and bronchiolitis 2010 349 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 26 95000

Chronic lower

respiratory

diseases 2010 161 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 12 4500

$1 295000

PM25-related Mortalities Based on BenMAP-CE Estimate in 2010 Base Year with change in the concentrations levels

Health and Economic Benefits associated with the Response of PM25 Emission between

Base Year 2010 Increasing 7 Ugm3

Cause of death year 2010

Population

Affected

Deaths

avoided by

attaining 195

μgm3

standard

Background

Concentrati

on

Pollut

ant

Rollback

Type

Avoided

Deaths (

Populatio

n)

econo

mic

Unben

efits

analysi

s

Alzheimers

disease 2010 4524 195 PM25

25

microgmAcircsup3

Rollback 19 150000

Diseases of the

heart 2010 20358 195 PM25

25

microgmAcircsup3

Rollback 135 450000

Influenza and

neumonia 2010 126672 195 PM25

25

microgmAcircsup3

Rollback 38 525000

Acute bronchitis

and bronchiolitis 2010 162864 195 PM25

25

microgmAcircsup3

Rollback 36 122000

Chronic lower

respiratory

diseases 2010 99528 195 PM25

25

microgmAcircsup3

Rollback 12 650000

Conclusions

An excellent Pearson Correlation was established to analyze the relationship in the relative risks of hospitalization of Respiratory(RD) and cardiovascular (CVD) associated with ambient exposure caused by traffic emission in relation to their size andspecific sources of emission on different scenarios interior a border Urban Rural Urban restricted access (freeways andinterstates)

A significant correlation of PM1025 exposure from mobile emission and hospital admissions for selected Respiratory (RD) andcardiovascular (CVD) diagnoses was established The results showed that PM emissions in urban restricted access (freeways andinterstates) is mainly caused by traffic Therefore people living close to highways are more exposed higher vehicular emissions

Conclusions

We found statistically significant associations between mobile PM25 caused by traffic emission with Respiratory and Cardiovascular Diseases in the study areaSubsequently a correlation between cardio-respiratory mortality is established

A significant correlation of PM1025 exposure from mobile emission and hospital admissions for selected Respiratory (RD) and cardiovascular (CVD) diagnoses isestablished The results showed that PM emissions in urban restricted access (freeways and interstates) is mainly caused by traffic Therefore people living close tohighways receive higher vehicular emissions

The table shows the percentage of PM mobile exposure in the analyzed areas contributing to increase the risk of Respiratory and Cardiovascular Diseases

An examination was conducted of the synoptic and local meteorology for the June 2006 ozone episode using the WRF model to determine how meteorological parametersinfluence the formation transport and dispersion of ozone in the PdN The predominant synoptic feature of the ozone event day was the expansion intensification and slowprogression of an upper-level ridge of high pressure The high ozone episodes are associated with highly stable atmospheres strong temperature inversions with low mixingheights and therefore low mixing volumes Under these conditions emissions such as NOx lead to highly polluted conditions that favor ozone formation

BenMAP Conclusions

We have estimated the number and economic value of health impacts resulting

from changes in air pollution concentrations of PM 25 in the PdN region

Reduction of Pm 25 4 UGm3= Avoided 213 cases respiratory cardiovascular

diseses and Economic Benefits associated with the Response of PM25 Emission + $

1295000

Increase of PM25 7 ugm3 = increasing Dies= 326 economic Unbenefits= 2345000$

Bibliography

1 Dockery DW Pope CAI Xu X Spengler JD Ware JH Fay ME Ferris BG Speizer FE An association between air pollution and mortality in six US cities N Engl J Med 3291753ndash1759 (1993)

2 Samet JM Dominici F Curriero FC Coursac I Zeger SL Fine particulate air pollution and mortality in 20 US cities 1987ndash1994 N Engl J Med 3431742ndash1749 (2000)

3 Nel AE Diaz-Sanchez D Li N The role of particulate pollutants in pulmonary inflammation and asthma evidence for the involvement of organic chemicals and oxidative stress Curr Opin Pulm Med 20017 20ndash26

4 Westerholm R Karl-Erik E Exhaust emissions from lightand heavy-duty vehicles chemical composition impact of exhaust after treatment and fuel parameters Environ Health Perspect 102(suppl 4)13ndash23 (1994)

5 Bascom R Bromberg P Costa D Delvin R Dockery D Frampton M Lambert W Samet J Speizer F Utell

6 Health effects of outdoor air pollution Am J Respir Crit Care Med 1533ndash50 (1996)

7 Chow JC Watson JG Frazier CA Egami RT Goodrich A Ralph C Spatial and temporal source contributions to

8 PM10 and PM25 in Reno NV In PM-10 Implementation of Standards Transactions An APCAEPA International Speciality Conference San Francisco CA (Mathal CV Stonefield DH eds) PittsburghAPCA 1988439ndash457

9 overview In Particulate Matter Health and Regulatory Issues VIP-49 Proceedings of an International Specialty Conference 4ndash6 April 1995 Pittsburgh PA PittsburghAir and Waste Management Association 1995577ndash598

10 Kunzli N Kaiser R Medina S Studnicka M Chanel O

11 Filliger P Herry M Horak F Jr Puybonnieux-Texier V Quenel P et al Public-health impact of outdoor and traffic- related air pollution a European assessment Lancet 356795ndash801 (2000)

Bibliography

1 Sioutas C Delfino RJ Singh M Exposure assessment for atmospheric ultrafine particles (UFP) and implications in epidemiological research Environ Health Perspect 2005113947ndash955

2 Mosleh M Blau PJ Dumitrescu D (2004) Characteristics and morphology of wear particles from laboratory testing of disc brake materials Wear 2561128ndash1134

3 Kuumlnzli N et al (2000) Public-health impact of outdoor and traffi c-related air pollution a European assessment Lancet 356(9232)795ndash801

4 Dora C Phillips M eds (2000) Transport environment and health Copenhagen WHO Regional Office for Europe (WHO Regional Publications European Series No 89 httpwwweurowhointdocumente72015pdf accessed 26 November 2004)

5 Westerholm R Karl-Erik E Exhaust emissions from lightand

6 heavy-duty vehicles chemical composition impact of exhaust after treatment and fuel parameters Environ Health Perspect 102(suppl 4)13ndash23 (1994)

7 Fauser Tjell Mosbaek pigegaard Quantification of tire-Tread particles using extractable Organic Zinc as a Tracer Rubber Chemistry and Technology 1999 969Table shows some literature estimates of the contribution of tire wear to PM10 in air (Panko et al 2013) Gustafsson M Blomqvist G Gudmundsson A Dahl A Swietlicki E Bohgard M Lindbom J Ljungman A

8 Chen Y Shah N Huggins FE and Huffman GP (2006) Microanalysis of Ambient Particles from Lexington Ky by Electron Microscopy Atmos Environ 40 651ndash663

9 Donaldson K Tran CL Jimenez LA Duffin R Newby DE and Mills N (2005) Combustion-derived Nanoparticles A Review of Their Toxicology Following Inhalation Exposure Part Fibre Toxicol 2 10ndash23

10 Su D Serafino A Muller JO Jentoft RE Schlogl R and Fiorito S (2008) Cytotoxicity and Inflammatory Potential of Soot Particles of Low-emission Diesel Engines Environ Sci Technol 42 1761ndash1765

11 Maier KL Alessandrini F Beck-Speier I Hofer TPJ Diabatґe S Bitterle E Stoger T and Jakob T (2008) Health Effects of Ambient Particulate Matter-Biological Mechanisms and Inflammatory Responses to in Vitroand in Vivo Particle Exposures Inhalation Toxicol 20 319ndash337

Page 15: Studies of Air Pollutants and their Impact on Respiratory and ...€¦ · Ascarate Park C37 Monitoring Station: The National Ambient Air Quality Standard (NAAQS) for PM 10 and 2.5

Brake wear particulate matter

Brake wear particulate matter Chemical content (iron(Fe) copper(Cu) Antimony(Sb) barium(Ba) this type of particulate can cause severe respiratory and cardiovascular damages and it is also known that Sb has been classified as a possible human pulmonary carcinogen by the International Agency for Research on Cancer (IARC 1989 Et al 2013)

Fig images of brake wear particles generated at a road simulation study ( centre lt25 μm right lt10

μm) Source [Kukutschovaacute et al 2011]

Tire wear particulate matter

The tire wear particles of the tires are generated either by frictional forces between the treadand the road pavement The chemical content Fe Cr Pb Ti Cr Cu Zn Sr Y Zr Sn Sb Ba LaCe and Pb)

Fig Examples of near spherical particles PM 10 and 25 which are originate from interaction of tires and pavements Source [Dahl et al 2006]

Study Area

The Paso del Norte (PdN) region Selected two strategic areas of study El Paso County zip code 79905 Urban area and Dona Ana County Zip Code 880218802788072 Rural Restricted urban access (freeways and interstates)

Map of the area of the simulation by the MOVES model in the study area

Geographic Domain Zip Code 79905 Urban Area (El Paso County)

Zip Codes 88021880278807288048 (Dona Ana County)

Urban road Delta Dr St 31o 45rsquo 5637- 106o 27rsquo 1212 10 miles

Cordova Bridge of the Americas 31o 45rsquo 4367- 106o 27rsquo 0506 15 miles

478 Highway interstate 31o 46rsquo 1326- 106o 27rsquo 0327 05 miles

110 Highway interstate 31o 46rsquo 1210- 106o 27rsquo 0066 10 miles

10 Interstate Gateway Blvd 31o 46rsquo 397- 106o 26rsquo 4769 05 miles

Chamizal Loop 478 31o 46rsquo 668- 106o 26rsquo 5456 05 miles

Alameda Loop 20 31o 46rsquo 1323- 106o 27rsquo 0328 10 miles

Paisano Dr St Patriot freeway

route 62

31o 46rsquo 0669- 106o 27rsquo 212 15 miles

St Piedras 31o 46rsquo 1326- 106o 27rsquo 0327 10 miles

Dona Ana County Miles

Interstate 25 32o 23rsquo 0561 -106 48

1054 32o 23rsquo 3434- -

106 48 1054 32o 23rsquo

5660 106 48 4314

50

Geographic domain To obtain the simulation mobile data from modelMOVES2010a was configurated the coordinates selected in the study areas

El Paso County

PM25 Estimation from Aerosol Optical Depth (AOD) using

satellites

We examined the relationship

between Aerosol Optical Depth

(AOD) estimated from satellite data

at 5 km spatial resolution and the

mass of fine particles le25 μm in

aerodynamic diameter (PM25)

monitored on the ground in El PdN

area PM25 data was recorded from

air quality monitoring Chamizal

station (TCEQ) on different periods

Our analysis shows a significant

positive association between AOD

and PM25

Time-series and scatter plots of AOD estimated PM25 and surface PM25

Analysis of the meteorological factors and synoptic conditions leading to a local high

ozone event episode June 12-21 2006

Meteorology plays a critical role in determining atmospheric ozone concentrations A good synoptic scale weather forecast is essential to accurately forecast tropospheric and surface ozone concentrations

Figure 1 The domain configuration and Landuse categories

resolution 25 km domainFigure 2 The Geopotential height at 500 mb Figure 3 depicts the 850 mb at a lower altitude The

white regions observed in the graph correspond to

mountainous areas

Figure 4 Temperature at 2m height

above surface at 22 UTC June 18 2006

36 km resolution

Performance Evaluation

01020304050

Ju

ne

137

130

0

190

0

10

0

Ju

ne

157

130

0

190

0

10

0

Ju

ne

187

130

0

190

0

10

0

Tem

pe

ratu

re (⁰C

)

Local time (Hrs)

C41 June 13-19 2006

WRF_temperature

(⁰C)

TCEQ_temperature

(⁰C)

01020304050

June1

37

100

0

130

0

160

0

190

0

220

0

10

0

40

0

June1

57

100

0

130

0

160

0

190

0

220

0

10

0

40

0

June1

87

100

0

130

0

160

0

190

0

220

0

10

0

40

0

Rel

ativ

e h

um

idit

y (

)

Local time (Hrs)

C41 June 13-19 2006

WRF_rh () TCEQ_relative humidity ()

0

5

10

15

20

June

137 10

13

16

19

22 1 4

June

157 10

13

16

19

22 1 4

June

187 10

13

16

19

22 1 4

Win

d s

pee

d (

ms

Local time(Hrs)

C12 June 13-192006

WRF_wind speed (ms) TCEQ_ wind speed (ms)

We evaluate the WRF modelrsquos performance

by comparing against corresponding

experimental TCEQ data and performing the

required statistical analysis

HYSPLIT Model

HYSPLIT was simulated and showed that the ozone is mostly transported to El Paso from north western and south western US and Mexican regions during the 72 hours duration of the simulation

0

20

40

60

80

100

1200

00

10

02

00

30

04

00

50

06

00

70

08

00

90

01

00

01

10

01

20

01

30

01

40

01

50

01

60

01

70

01

80

01

90

02

00

02

10

02

20

02

30

0

Ho

url

y o

zon

e [

pp

b]

0102030405060708090

00

01

00

20

03

00

40

05

00

60

07

00

80

09

00

10

00

11

00

12

00

13

00

14

00

15

00

16

00

17

00

18

00

19

00

20

00

21

00

22

00

23

00

Ho

url

y o

zon

e [

pp

b]

June 18th June 19th

Performance Evaluation

01020304050

Ju

ne

137

130

0

190

0

10

0

Ju

ne

157

130

0

190

0

10

0

Ju

ne

187

130

0

190

0

10

0

Tem

pe

ratu

re (⁰C

)

Local time (Hrs)

C41 June 13-19 2006

WRF_temperature

(⁰C)

TCEQ_temperature

(⁰C)

0

50

100

150

June1

37

100

0

130

0

160

0

190

0

220

0

10

0

40

0

June1

57

100

0

130

0

160

0

190

0

220

0

10

0

40

0

June1

87

100

0

130

0

160

0

190

0

220

0

10

0

40

0Ozo

ne

(pp

b)

Local time (Hrs)

C41 June 13-19 2006

CAMx_ozone (ppbV) TCEQ_ozone (ppb)

0

10

20

30

40

50

June1

37

100

0

130

0

160

0

190

0

220

0

10

0

40

0

June1

57

100

0

130

0

160

0

190

0

220

0

10

0

40

0

June1

87

100

0

130

0

160

0

190

0

220

0

10

0

40

0

Rel

ativ

e h

um

idit

y (

)

Local time (Hrs)

C41 June 13-19 2006

WRF_rh () TCEQ_relative humidity ()

0

5

10

15

20

June

137 10

13

16

19

22 1 4

June

157 10

13

16

19

22 1 4

June

187 10

13

16

19

22 1 4W

ind

sp

eed

(m

sLocal time(Hrs)

C12 June 13-192006

WRF_wind speed (ms) TCEQ_ wind speed (ms)

Methodology

Medical Data The data by weekly monthly and year for daily emergency room and hospital admission for the respiratory

infections (RD) and cardiovascular diseases (CVD) was extracted from hospitals records located in the El PdN

the system includes data on type of admission primary and secondary causes of admissionRESPIRATORY DISEASE

Bronquitis amp Chronic Bronchitis 466 - 4661 491 - 4919

Asthma 463 - 4939

Emphysema 492

Respiratory failure 51881

HEART DISEASE

Accute Myocardial Infarction 410

Coronary Athersclerosis 4140

Other Ischemic Heart Disease 411-4139 4141-4149

Cardiac Dyshythmias 427

Essential hypertension 401

Acute myocardial infarction 410

Congestive Heart Failure 4280 4282-4284

Hypertensive heart disease 402

Table 1 ICD -9 Codes for Respiratory and Cardiovascular Diseases

0

50

100

150

200

250

300

Wee

k 1

Wee

k 2

Wee

k 3

Wee

k 4

Wee

k 5

Wee

k 6

Wee

k 7

Wee

k 8

Wee

k 9

Wee

k 1

0

Wee

k 1

1

Wee

k 1

2

Wee

k 1

3

Wee

k 1

4

Wee

k 1

5

Wee

k 1

6

Wee

k 1

7

Wee

k 1

8

Wee

k 1

9

Wee

k 2

0

Wee

k 2

1

Mo

rb

idit

y D

isch

arg

e fo

r a

ll R

esp

ira

tory

Dis

ease

IC

D-9

(

Ast

hm

aB

ro

nch

itis

)

Weekly Morbidity Discharges of all the Listed Diagnoses for All

Respiratory Disease During WinterSpring 2010

Asthma-Bronchitis

EPA MOVES Model for Estimating Emission

Inventories

Motor Vehicle Emission Simulator (MOVES 2010b) will be configuredin The El Paso North Region for Calculate five categories of PM10

PM25 total Emission inventories from all on-road traffic over a

variety of scales within periods of time selected weeks months

and years

Moves (Motor Vehicle Emission

Simulator)

The emission model is develop using the current equation to calculate direct traffic emissions from

vehicles in the form of PM is

Eext annual emissions are measured in grams of miles traveled by the vehicle (gVMT )

SL is the road surface loading in (gm2)

W is the average weight in tons of the vehicles on the road

K is the particle size multiplier for particle size range (eg gVMT for PM10 when using grams and miles)

P is the 7 number of wet days with at least 0254 mm of precipitation during the averaging period

N is the number of years considered in the averaging period

C is the particle size specific emissions factor in units of interest vehicle direct exhaust brake wear and tirewear

Modeling Simulation Domain and Emissions Scenarios

For simulations of mobile air quality emission inventories a motor vehicle emission simulator EPA (MOVES 2014a) was used

The modeling use input factors divided into seven section

parameters

On-Road Inventory local data

input

Scale

Geographic Bounds

Traffic intensity

Vehicle Type

Pollutants

Road Type

Fuel Types

Figure Source EPA US Environmental Protection Agency 2012- Moves 2010b Model

EPA Moves 2014a The modeling used input factors divided into six section

parameters On-Road Inventory local data input

Geographic Domains CountyNonattainment Area

Vehicle-Miles Traveled (VMT) is the total number of miles driven by all vehicles withina given time period and geographic area

Average speed range from 25 miles per

hour to 65 miles per hour

Vehicle Classes Motorcycle PassengerCarTruks light-duty Commercial Truck(6001-8500 lbs) Buses heave-duty trucksRefuse trucks School Bus Single UnitShort Haul-truck Single Unit Long Haul-truck Long Haul Truck Heavy-DutyVehicles (26001-33000 lbs)

Pollutants

Road TypeRural restricted Acces(Freeways and interstates) Rural and Restricted Acces Urban Restricted Acces Off-Network

Fuel Types Gasoline Diesel Fuel

Specific Road Types

Two road types for running emission from the MOVES can be

selected

(freeways and interstates)

Interior urban Urban

Figure Source EPA US Environmental Protection Agency 2012- Moves 2010b Model

VehiclesEquipment

This panel show which on-road vehicles will be modeled

Figure Source EPA US Environmental Protection Agency 2012- Moves 2010b Model

Long haul truck Short haul truck Inercity bus Ligth comercial truck

Passenger car Passenger truck Refuse truck

School bus Single unit long haul-truck

Single unit short haul-truck

Transit bus

Motor home

Motorcycle

Based on Department of Transportation Highway MOVES will Estimates Traffic

Emissions from Cars Trucks amp Motorcycles

Output Data Moves 2014a

Inventories of PM 10 25 Mobile Emission from all

on-Road Traffic

Exhaust Emission PM 10 25 gramsmile

Brake Wear Emission PM 10 25 gramsmile

Tire wear Emission PM 10 25 gramsmile

Date of Vehicle miles traveled (VMT) for

Day Week Month Year

Total Vehicle population

Vehicle age distribution

Simulation of Mobile Emission in the El PdN Region Zip Code 79905

Figure Total Emissions from road traffic in El Paso TX Area were estimated for PM10

Exhaust and Non exhaust emission in kilogramsmonth (Source EPA MOVES 2014a)

0

10000

20000

30000

40000

50000

PM

10 k

gM

on

th

Months

Monthly PM 10 Exhaust and Non-Exhaust Mobile Emissions 2010

On-Road Urban Restricted Area Zip Code 79905

Primary Exhaust PM 10 (kg) Primary PM 10 Brakewear (kg)

Primary PM 10 Tirewear (kg)

05000

100001500020000250003000035000400004500050000

PM

25

kg

Mo

nth

Months

Monthly PM 25 Exhaust and Non-Exhaust Mobile Emission 2010

On-Road Urban Restricted Area Zip Code 79905

Primary Exhaust PM 25 (kg) Primary PM 25 Brakewear (kg) Primary PM 25Tirewear (kg)

Figure Total Emissions from road traffic in El Paso TX Area were estimated for PM25

Exhaust and Non exhaust emission in kilogramsmonth (Source EPA MOVES 2014a)

Total Emissions from Road Traffic in El Paso County PM1025 Exhaust and Non exhaust Emission in kilogramsmonth

Taking the interests to the health risks related to PM 1025 mobile emission were simulated

Exhaust and Non-exhaust emissions contribute almost equally to total traffic-related PM1025 Emissions (Querol et al 2004 Bukowiecki et al 2009a Amato et al 2011)

Monthly PM 10 25 Exhaust and Non-Exhaust (BrakewearTirewear) Mobile

Emission 2010 On-Road Urban Restricted Area Zip Code 79905

Figure Total Emissions from road traffic in El Paso TX Area were estimated for PM10 25 Exhaust and Non Exhaust mobile

emission in kilograms per month (Source EPA MOVES)

0

10000

20000

30000

40000

50000

January February March April May June July August September October November December

PM

10

25

(K

ilog

ram

s)

Months

Summary- Monthly PM 10 25 Exhaust and Non-Exhaust Mobile

Emission 2010 On-Road Urban Restricted Area Zip Code 79905

Primary Exhaust PM 10 Primary PM 10 Brakewear Primary PM 10 Tirewear

Primary Exhaust PM 25 Primary PM 25 Brakewear Primary PM 25Tirewear

Exhaust Emissions PM1025 is reaching maximum emission 48000-42000 thousand of Kgmonth followedby Brake wear 29000-5000 thousand kgmonth and Tire wear with 9000-2000 kgmonth The results showthat the emissions of PM derived mainly from Exhaust and Brake are significantly higher in Urban Area

Annual Contribution of Mobile Emission PM 1025 (Kg) Zip Code 79905 El

Paso County 2010

Total Primary

Exhaust _PM10

39

Total Primary

Exhaust _PM25

36

Brakewear

particulate_PM10

18

Tirewear

particulate_PM10

4

Brakewear

particulate_PM25

2

Tirewear

particulate_PM25

1

0

5

10

15

20

25

30

35

40

45

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53

Fig Annual Average PM10 Concentrations at the

Chamizal C41 Station and PM1025 mobile

Concentration Zip code 79905

PM10 TCEQ (μgm3) Total Mobile Emission PM10 (Ugm3)

Fig Exhaust Emission is Contributing Approximately 74 of total

PM1025 Mobile Emissions following of Brake wear with 20 and Tire

wear with 5

Annual Average PM1025 ugm3 Mobile Emissions (Moves) 26 Chamizal C41

Monitoring Station (TCEQ Chamizal Station )

Predicting Mobile Emission and VTM

Estimation The PdN Region 2010

44E+09

46E+09

48E+09

5E+09

52E+09

54E+09

56E+09

58E+09

6E+09

62E+09

0

50000

100000

150000

200000

250000

300000

350000

20

10

20

11

20

12

20

13

20

14

20

15

20

16

20

17

20

18

20

21

20

22

20

23

20

24

20

25

20

26

20

27

20

28

20

29

20

30

EX

HA

US

T

EM

ISS

ION

MO

BIL

E (

KG

YE

AR

)

YEARS

Predict ing Mobile Exhaust Emission and VTM

Estimation

2010 - 2030 e l PdN Area

Total_ Exhaust PM10 Total_ Exhaust PM25 Distance (Miles)

Fig Predicting Mobile Exhaust PM1025 (kgMonth) Emission and VTM Estimation 2010

- 2030 el PdN Area

44E+09

46E+09

48E+09

5E+09

52E+09

54E+09

56E+09

58E+09

6E+09

62E+09

0

5000000

10000000

15000000

20000000

25000000

30000000

20

10

20

11

20

12

20

13

20

14

20

15

20

16

20

17

20

18

20

21

20

22

20

23

20

24

20

25

20

26

20

27

20

28

20

29

20

30

EX

HA

US

T

EM

ISS

ION

MO

BIL

E (

KG

YE

AR

)

YEARS

Predict ing Mobile Exhaust Emission and

VTM Estimation

2010 - 2030 e l PdN Area

CO NO2 NO NOx Distance

Fig Predicting Mobile Exhaust Emission and VTM Estimation

2010 - 2030 el PdN Area in El Paso TX Area were estimated for

Total CO NOx NO2 NO emission in kilograms per year

(Source EPA MOVES 2014a model)

The simulated Exhaust emissions in the future years shows a trend of reduction of this type of emissions in the

future years one factor should be the new hybrid technology is increasing by 476 since 2010 to 2015 and

use of catalytic converters diesel particulate filters and improved fuels and engines Non-exhaustive sources

will increase in the coming years because there is no control in the material of manufacture composed by Fe

Cu and Mn also not to be able to reduce the number of events of braking (Accelerations and decelerations)

45E+09

5E+09

55E+09

6E+09

65E+09

0

50000

100000

150000

200000

250000

201

0

201

1

201

2

201

3

201

4

201

5

201

6

201

7

201

8

202

1

202

2

202

3

202

4

202

5

202

6

202

7

202

8

202

9

203

0

NO

N-

EX

HA

US

T

EM

ISS

ION

MO

BIL

E

(KG

YE

AR

)

YEARS

Predicting Non Exhaust Mobile

Emission and VTM Estimation

2010 - 2030 el PdN Area

Brake_PM10 Tire_PM10 Distance (Miles)

Fig Predicting Mobile Exhaust PM1025 (kgMonth) Emission and VTM

Estimation 2010 - 2030 el PdN Area

Daily Avg PM1025

Levels of PM Mobile Emission Non-Exhaust -Rush Hour Periods Fall 2010 Zip Code

79905

00

100

200

300

400

500

600

Mo

bil

e P

M1

0 (k

g)

Rush Hours

Daily Avg PM10

Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush Hours

Periods 2010 Zip Code 79905

Total Primary Exhaust

_PM10 WinterSpring

Brakewear

particulate_PM10

WinterSpringTirewear particulate_PM10

WinterSpring

Total Primary Exhaust

_PM10 Summer

Brakewear

particulate_PM10 Summer

Tirewear Particulate_PM10

Summer

Total Primary Exhaust

_PM10 Fall

Brakewear

particulate_PM10 Fall

Tirewear particulate_PM10

Fall

00

50

100

150

200

250

300

350

Mo

bil

e P

M2

5 (k

g)

Rush hours

Daily Avg PM25

Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush

Hours Periods 2010 Zip Code 79905

Total Primary Exhaust _PM25

WinterSpring

Brakewear Particulate_PM25

WinterSpring

Tirewear particulate_PM25

WinterSpring

Total Primary Exhaust _PM25

Summer

Brakewear particulate_PM25

Summer

Tirewear particulate_PM25

Summer

Total Primary Exhaust _PM25

Fall

Brakewear particulate_PM25

Fall

Tirewear particulate_PM25

Fall

Figure Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush Hours Figure Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush Hours

GIS EMISSIONS INVENTORY SYSTEM A geographic information system (GIS) was used to established geographic scenarios with processed images of seasonal mobile

emissions in the PdN region Seasonal mapping is visualized for different types of pollutants Brakewear Exhaust and Tyrewear

Fg Graphics of GIS and Seasonal mobile Emission of particulate matter emission inventory Seasonal emission simulations were performed in kilograms and five contributing inputs factors were identified for

modeling 1) On the composition of the particulate material from different sources such as Exhaust and Non exhaust (Brake wear Tirewear) 2) The Vehicles Equipment clasification were selected according to

the use of gasoline and diesel fuel (motorcycle passenger car Light Duty Vehicles Trucks refuse truck Light Duty Vehicles Light Commercial Truck Light Duty Vehicles School Bus)

Winter Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

120354 67860 19065

Spring Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

139767 86702 24463

Summer Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

94747 62481 17630

Fall Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

75510 45542 12596

251 Descriptive Statistics Data Analysis

Weekly Correlation Analysis of Mobile Emission PM10 (Exhaust-Non-Exhaust) and Respiratory

Diagnoses WinterSpring Summer and Fall 2010

0

2

4

6

8

10

0

50

100

150

200

250

300

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21

Mo

rbid

ity

Dis

ch

arg

e

for

all R

esp

ira

tory

Dis

ea

se

ICD

-9

(A

sth

ma

-Bro

nc

hitis

)

WinterSpring Week

Weekly Avg Mobile PM10 Concentrations during

WinterSpring 2010 and its Influence on Respiratory

Diagnoses

Zip Code 79905

Total Medical data ZIP Code 79902

Total Mobile Emission PM10 (Ugm3)

0

1

2

3

4

5

6

7

0

20

40

60

80

100

Mo

rbid

ity

Dis

ch

arg

e

for

all R

esp

ira

tory

Dis

ea

se

ICD

-9

(Ast

hm

aB

ron

ch

itis

)

Weekly Avg Mobile PM10 Concentrations during

Summer 2010 and its Influence on Respiratory

Diagnoses

Summer 2010 Zip Code 79905

Total Mobile Emission PM10

Hospital Admission (Asthma-Bronchitis)

0

2

4

6

8

10

12

0

20

40

60

80

100

120

140

160

180

200

Mo

rbid

ity

dis

ch

arg

es

for

all r

esp

ira

tory

dis

ea

se

Weekly Avg Mobile PM10 Concentrations

during Fall 2010 and its Influence on Respiratory

Diagnoses

Zip Code 79905

Total Medical data ZIP Code 79902

Total Mobile Emission PM10 (Ugm3)

Mobile(Exhaust-Non-

Exhaust) PM10 and

Asthma-Bronchitis)

Linear R

Square

WinterSpring 734 ndash 39

Summer 614 ndash 32

Fall 548 -29

PM10 Mobile emission (Exhaust-Non-Exhaust)contributed significantly

association to the incidence of RD

Weekly Correlation Analysis of PM 25 Mobile Emission (Exhaust-Non-Exhaust)

and Cardiovascular Diagnoses WinterSpring Summer and Fall 2010

0010203040

00500

100015002000

Wee

k 1

Wee

k 2

Wee

k 3

Wee

k 4

Wee

k 5

Wee

k 6

Wee

k 7

Wee

k 8

Wee

k 9

Wee

k 1

0

Wee

k 1

1

Wee

k 1

2

Wee

k 1

3

Wee

k 1

4

Wee

k 1

5

Wee

k 1

6

Wee

k 1

7

Wee

k 1

8

Wee

k 1

9

Wee

k 2

0

Wee

k 2

1

Morb

idit

y d

isch

arg

es f

or

all

card

iovasc

ula

r d

isea

se

Weekly Avg PM25 Mobile Concentrations during

WinterSpring 2010 and its Influence on all Heart

Diagnoses

Zip Code 79905

Total All Heart Disease PM 25 mobile (μgm3)

0010203040

00

500

1000

1500

Mo

rbid

ity

dis

ch

arg

es

for

all

ca

rdio

va

scu

lar

dis

ea

se

Weeks

CORRELATION BETWEEN MOBILE PM25 ugm3

EXPOSURE TO HEART DISEASES SYMPTOMS

SUMMER SEASON 2010

Total All Heart Disease PM 25 mobile (μgm3)

Figure Statistical Analyses of the Relationship Between PM25 Caused by Traffic Emission( 26 of total Emission) with Heart diseases Source Hospital Admissions for Asthma Acute Bronchitis and Heart diseases in El Paso County zip code 79905 from Texas Health Care

Information Council in Austin Texas (Texas Health Care Information Council 2000)

00

10

20

30

40

0

50

100

150

We

ek 3

6

We

ek 3

7

We

ek 3

8

We

ek 3

9

We

ek 4

0

We

ek 4

1

We

ek 4

2

We

ek 4

3

We

ek 4

4

We

ek 4

5

We

ek 4

6

We

ek 4

7

We

ek 4

8

We

ek 4

9

We

ek 5

0

We

ek 5

1

We

ek 5

2

We

ek 5

3

Mo

rbid

ity

dis

ch

arg

es

for

all

ca

rdio

va

scu

lar

dis

ea

se

CORRELATION BETWEEN MOBILE PM25 ugm3

EXPOSURE TO HEART DISEASES SYMPTOMS FALL

SEASON 2010

Total All Heart Disease PM 25 mobile (μgm3)

Mobile(Exhaust-

Non-Exhaust)

PM10 and

Asthma-

Bronchitis)

Linear R

Square

WinterSpring 833 -42

Summer 620 -32

Fall 501-26

PM10 Mobile

emission (Exhaust-

Non-

Exhaust)contribut

ed significantly

association to the

incidence of CVD

Diseases

Monthly Brake Mobile Emission PM1025 kg During year 2010 and its Influence on

Respiratory Diagnoses Zip Code 79905

00200040006000800010000

010000200003000040000

PM

10

Mo

bile

(K

g)

Months

Monthly Brake Mobile Emission PM10 kg during year

2010 and its Influence on Respiratory Diagnoses

Zip Code 79905

Primary PM 10

Brakewear 00100020003000400050006000

0

1000

2000

3000

4000

PM

25

Mo

bil

e(K

g)

Months

Monthly Brake Mobile Emission PM25 during

year 2010 and its Influence on Heart Diagnoses

Zip Code 79905

Primary PM 25

Brakewear

Heart Diseases

Hospital

Admission

Brake Mobile Emission

PM10 kg Asthma-

Bronchitis)

Brake Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=969 Linear Square R=856

Monthly Mobile Exhaust Emission PM1025 During year 2010 and its Influence on

Respiratory Diagnoses Zip Code 79905

0

200

400

600

800

1000

0

10000

20000

30000

40000

50000

1 3 5 7 9 11

PM

10

(K

g m

on

th)

Months

Monthly Mobile Exhaust Emission PM10 during

year 2010 and its Influence on Respiratory

Diagnoses

Zip Code 79905

Primary Exhaust

PM 10

Respiratory Disease

(Asthma

Bronchitis) Hospital

Admission

0

100

200

300

400

500

600

0

10000

20000

30000

40000

50000

1 2 3 4 5 6 7 8 9 101112

PM

25

(K

g m

on

th)

Months

Monthly Exhaust Mobile Emission PM25 during

year 2010 and its Influence on Heart Diagnoses

Zip Code 79905

Primary Exhaust PM

25

Heart Diseases

Hospital Admission

Exhaust Mobile Emission

PM10 kg Asthma-

Bronchitis)

Exhaust Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=929 Linear Square R=831

Monthly Tire wear Mobile Emission PM1025 During year 2010 and its Influence on Heart

Diagnoses Zip Code 79905

0

100

200

300

400

500

600

700

800

900

0

1000

2000

3000

4000

5000

6000

7000

8000

9000

1 2 3 4 5 6 7 8 9 10 11 12

PM

10

(K

g m

on

th)

Months

Monthly Tirewear Mobile Emission PM10 during year 2010

and its Influence on Heart Diagnoses

Zip Code 79905

Primary PM 10 Tirewear

Mobile Emission

Respiratory Disease

(Asthma Bronchitis)

Hospital Admission

0

100

200

300

400

500

600

0

200

400

600

800

1000

1200

1400

1 2 3 4 5 6 7 8 9 10 11 12

PM

25

(K

g m

on

th)

Months

Monthly Tirewear Mobile Emission PM25 during year 2010

and its Influence on Respiratory Diagnoses

Zip Code 79905

Primary PM 25Tirewear

Mobile Emission

Heart Diseases Hospital

Admission

Exhaust Mobile Emission

PM10 kg Asthma-

Bronchitis)

Exhaust Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=769 Linear Square R=715

Dona Ana County Zip Codes

88021880278807288048

Primary

Exhaust

PM 10 Zip

code

79905

Total

Primary

Exhaust

PM10

Dona Ana

Primary

Exhaust

PM 25 Zip

Code

79905

Total

Primary

Exhaust

PM25

Dona Ana

Series1 430378 111773 391915 102123

0

100000

200000

300000

400000

500000

AX

IS T

ITLE

Annual Comparison of the Mobile

Exhaust Emissions El Paso County

and Dona Ana 2010

Primary

PM 10

Brakewea

r Zip code

79905

Brakewea

r

particulat

e_PM10

Dona Ana

Primary

PM 10

Tirewear

Zip code

79905

Tirewear

particulat

e_PM10

Dona Ana

Series1 262585 48573 73754 11864

050000

100000150000200000250000300000

AX

IS T

ITLE

Annual Comparison of the Mobile

Brakewear Emissions El Paso County

and Dona Ana 2010

Figure Comparison of the Annual Mobile Emissions

of Primary PM10 Non-Exhauts (Brake ) from Dona

Ana County New Mexico and El Paso Texas Units

in KgMonth

Figure Comparison of the Annual Mobile Emissions

of Primary PM10-Exhauts Emission from Dona Ana

County New Mexico and El Paso Texas Units in

KgMonth

Primary

PM 25

Brakewe

ar Ziphellip

Brakewe

ar

particula

te_PMhellip

Primary

PM

25Tirewe

ar Ziphellip

Tirewear

particula

te_PM25

Donahellip

Series1 32645 6071 10919 1779

0

10000

20000

30000

40000

AX

IS T

ITLE

Annual Comparison of the

Mobile Exhaust Emissions El Paso

County and Dona Ana 2010

Figure Comparison of the Annual Mobile Emissions

of Primary PM10-Exhauts Emission from Dona Ana

County New Mexico and El Paso Texas Units in

KgMonth

Monthly Mobile Emission PM1025 kg During year 2006

and its Influence on Respiratory Diagnoses Dona Ana

County Zip Code 880218802788072

0

100

200

300

0

5000

10000

15000

Axi

s Ti

tle

Axis Title

Monthly Mobile Exhaust Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Total PrimaryMobile Exhaust_PM10

All Respiratory ICD-9 (AsthmaBronchitis)

050100150200250300

010002000300040005000

Axi

s Ti

tle

Axis Title

Monthly Mobile Brake Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Brakewearparticulate_PM10

All RespiratoryICD -9 (AsthmaBronchitis)

050100150200250300

0200400600800

10001200

Axi

s Ti

tle

Axis Title

Monthly Mobile Tirewear Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Tirewearparticulate_PM10

All Respiratory ICD -9 (AsthmaBronchitis)

Mobile Exhauts

Emission PM10

kg Asthma-

Bronchitis)

Brake Mobile

Emission PM10

kg and Heart

Diagnoses

Tirewear Mobile

Emission PM10

kg and Heart

Diagnoses

Linear Square

R= 951

Linear Square

R=625

Linear Square

R=525

Mobile Exhauts

Emission PM25

kg Asthma-

Bronchitis)

Brake Mobile

Emission PM25

kg and Heart

Diagnoses

Tirewear Mobile

Emission PM25

kg and Heart

Diagnoses

Linear Square

R= 986

Linear Square

R=691

Linear Square

R=601

Results

The results showed that mobile PM emissions in the urban areas close to urban Road and highways is putting at risk public health

and the proportion of diseases attributable to this exposure is potentially large

Brake wear emissions is much lower in freeways due to significantly reduced number of braking events while tire wear is much

higher in areas where studded tires are used The emission of exhaust gases are much higher in areas where there is a high

vehicular traffic

Brake Mobile

Emission PM10 kg

Asthma-Bronchitis)

Brake Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square

R=969

Linear Square

R=856

Exhaust Mobile

Emission PM10 kg

Asthma-Bronchitis)

Exhaust Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square

R=929

Linear Square

R=831

Tirewear Mobile

Emission PM10 kg

Asthma-Bronchitis)

Tirewear Mobile

Emission PM25 kg

and Heart Diagnoses

Linear Square R=769 Linear Square R=715

Brake Mobile

Emission PM10 kg

and Heart

Diagnoses

Brake Mobile

Emission PM25 kg

and Heart

Diagnoses

Exhaust Mobile

Emission PM10 kg

Asthma-Bronchitis)

Linear Square

R=625

Linear Square

R=691

Linear Square R=

951

Exhaust Mobile

Emission PM25 kg

Asthma-

Bronchitis)

Tire wear Mobile

Emission PM10 kg and

Heart Diagnoses

Tirewear Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square R=

986

Linear Square R=525 Linear Square

R=601

El Paso County

Dona Ana

County

BenMAP-CE

In this analysis the Program of Mapping and Analysis of Environmental Benefits-Community Edition

(BenMAP-CE) was used to Estimate the number and economic value of health impacts resulting from changes

in air pollution PM 25 Ugm3 in The El Paso Area

Health and Economic Benefits associated with the Response of PM25 Emission between

Base Year 2010

Number of Mortalities in 2010 Base Year Based on El Paso County Texas Department of State Health Services

Number of Mortalities in 2010 Base Year Based on El Paso County Texas

Department of State Health Services

cause of death

year

2010

Populatio

n

Affected

Backgro

und

Concentr

ation Pollutant

Rollback

Type

Avoided

Deaths

(

Populatio

n)

alzheimers disease 2010 40716 125 PM25

25

microgmAcircsup3

Rollback 9

diseases of the

heart 2010 15834 125 PM25

25

microgmAcircsup3

Rollback 35

influenza and

neumonia 2010 81432 125 PM25

25

microgmAcircsup3

Rollback 18

acute bronchitis

and bronchiolitis 2010 117624 125 PM25

25

microgmAcircsup3

Rollback 26

chronic lower

respiratory diseases 2010 54288 125 PM25

25

microgmAcircsup3

Rollback 12

The Basin-wide decrease in 4 ugm3 PM25 concentration after this

reduction control

Cause of death year 2010

Populatio

n

Affected

Background

Concentrati

on

Reduc

cion

scena

rio Polluta

nt

Rollback

Type

Avoi

ded

Deat

hs

(

Pop

ulati

on)

economic

benefits

analysis $

Alzheimers

disease 2010 121 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 9 12000

Diseases of the

heart 2010 470 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 35 35000

Influenza and

neumonia 2010 242 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 18 42500

Acute bronchitis

and bronchiolitis 2010 349 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 26 95000

Chronic lower

respiratory

diseases 2010 161 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 12 4500

$1 295000

PM25-related Mortalities Based on BenMAP-CE Estimate in 2010 Base Year with change in the concentrations levels

Health and Economic Benefits associated with the Response of PM25 Emission between

Base Year 2010 Increasing 7 Ugm3

Cause of death year 2010

Population

Affected

Deaths

avoided by

attaining 195

μgm3

standard

Background

Concentrati

on

Pollut

ant

Rollback

Type

Avoided

Deaths (

Populatio

n)

econo

mic

Unben

efits

analysi

s

Alzheimers

disease 2010 4524 195 PM25

25

microgmAcircsup3

Rollback 19 150000

Diseases of the

heart 2010 20358 195 PM25

25

microgmAcircsup3

Rollback 135 450000

Influenza and

neumonia 2010 126672 195 PM25

25

microgmAcircsup3

Rollback 38 525000

Acute bronchitis

and bronchiolitis 2010 162864 195 PM25

25

microgmAcircsup3

Rollback 36 122000

Chronic lower

respiratory

diseases 2010 99528 195 PM25

25

microgmAcircsup3

Rollback 12 650000

Conclusions

An excellent Pearson Correlation was established to analyze the relationship in the relative risks of hospitalization of Respiratory(RD) and cardiovascular (CVD) associated with ambient exposure caused by traffic emission in relation to their size andspecific sources of emission on different scenarios interior a border Urban Rural Urban restricted access (freeways andinterstates)

A significant correlation of PM1025 exposure from mobile emission and hospital admissions for selected Respiratory (RD) andcardiovascular (CVD) diagnoses was established The results showed that PM emissions in urban restricted access (freeways andinterstates) is mainly caused by traffic Therefore people living close to highways are more exposed higher vehicular emissions

Conclusions

We found statistically significant associations between mobile PM25 caused by traffic emission with Respiratory and Cardiovascular Diseases in the study areaSubsequently a correlation between cardio-respiratory mortality is established

A significant correlation of PM1025 exposure from mobile emission and hospital admissions for selected Respiratory (RD) and cardiovascular (CVD) diagnoses isestablished The results showed that PM emissions in urban restricted access (freeways and interstates) is mainly caused by traffic Therefore people living close tohighways receive higher vehicular emissions

The table shows the percentage of PM mobile exposure in the analyzed areas contributing to increase the risk of Respiratory and Cardiovascular Diseases

An examination was conducted of the synoptic and local meteorology for the June 2006 ozone episode using the WRF model to determine how meteorological parametersinfluence the formation transport and dispersion of ozone in the PdN The predominant synoptic feature of the ozone event day was the expansion intensification and slowprogression of an upper-level ridge of high pressure The high ozone episodes are associated with highly stable atmospheres strong temperature inversions with low mixingheights and therefore low mixing volumes Under these conditions emissions such as NOx lead to highly polluted conditions that favor ozone formation

BenMAP Conclusions

We have estimated the number and economic value of health impacts resulting

from changes in air pollution concentrations of PM 25 in the PdN region

Reduction of Pm 25 4 UGm3= Avoided 213 cases respiratory cardiovascular

diseses and Economic Benefits associated with the Response of PM25 Emission + $

1295000

Increase of PM25 7 ugm3 = increasing Dies= 326 economic Unbenefits= 2345000$

Bibliography

1 Dockery DW Pope CAI Xu X Spengler JD Ware JH Fay ME Ferris BG Speizer FE An association between air pollution and mortality in six US cities N Engl J Med 3291753ndash1759 (1993)

2 Samet JM Dominici F Curriero FC Coursac I Zeger SL Fine particulate air pollution and mortality in 20 US cities 1987ndash1994 N Engl J Med 3431742ndash1749 (2000)

3 Nel AE Diaz-Sanchez D Li N The role of particulate pollutants in pulmonary inflammation and asthma evidence for the involvement of organic chemicals and oxidative stress Curr Opin Pulm Med 20017 20ndash26

4 Westerholm R Karl-Erik E Exhaust emissions from lightand heavy-duty vehicles chemical composition impact of exhaust after treatment and fuel parameters Environ Health Perspect 102(suppl 4)13ndash23 (1994)

5 Bascom R Bromberg P Costa D Delvin R Dockery D Frampton M Lambert W Samet J Speizer F Utell

6 Health effects of outdoor air pollution Am J Respir Crit Care Med 1533ndash50 (1996)

7 Chow JC Watson JG Frazier CA Egami RT Goodrich A Ralph C Spatial and temporal source contributions to

8 PM10 and PM25 in Reno NV In PM-10 Implementation of Standards Transactions An APCAEPA International Speciality Conference San Francisco CA (Mathal CV Stonefield DH eds) PittsburghAPCA 1988439ndash457

9 overview In Particulate Matter Health and Regulatory Issues VIP-49 Proceedings of an International Specialty Conference 4ndash6 April 1995 Pittsburgh PA PittsburghAir and Waste Management Association 1995577ndash598

10 Kunzli N Kaiser R Medina S Studnicka M Chanel O

11 Filliger P Herry M Horak F Jr Puybonnieux-Texier V Quenel P et al Public-health impact of outdoor and traffic- related air pollution a European assessment Lancet 356795ndash801 (2000)

Bibliography

1 Sioutas C Delfino RJ Singh M Exposure assessment for atmospheric ultrafine particles (UFP) and implications in epidemiological research Environ Health Perspect 2005113947ndash955

2 Mosleh M Blau PJ Dumitrescu D (2004) Characteristics and morphology of wear particles from laboratory testing of disc brake materials Wear 2561128ndash1134

3 Kuumlnzli N et al (2000) Public-health impact of outdoor and traffi c-related air pollution a European assessment Lancet 356(9232)795ndash801

4 Dora C Phillips M eds (2000) Transport environment and health Copenhagen WHO Regional Office for Europe (WHO Regional Publications European Series No 89 httpwwweurowhointdocumente72015pdf accessed 26 November 2004)

5 Westerholm R Karl-Erik E Exhaust emissions from lightand

6 heavy-duty vehicles chemical composition impact of exhaust after treatment and fuel parameters Environ Health Perspect 102(suppl 4)13ndash23 (1994)

7 Fauser Tjell Mosbaek pigegaard Quantification of tire-Tread particles using extractable Organic Zinc as a Tracer Rubber Chemistry and Technology 1999 969Table shows some literature estimates of the contribution of tire wear to PM10 in air (Panko et al 2013) Gustafsson M Blomqvist G Gudmundsson A Dahl A Swietlicki E Bohgard M Lindbom J Ljungman A

8 Chen Y Shah N Huggins FE and Huffman GP (2006) Microanalysis of Ambient Particles from Lexington Ky by Electron Microscopy Atmos Environ 40 651ndash663

9 Donaldson K Tran CL Jimenez LA Duffin R Newby DE and Mills N (2005) Combustion-derived Nanoparticles A Review of Their Toxicology Following Inhalation Exposure Part Fibre Toxicol 2 10ndash23

10 Su D Serafino A Muller JO Jentoft RE Schlogl R and Fiorito S (2008) Cytotoxicity and Inflammatory Potential of Soot Particles of Low-emission Diesel Engines Environ Sci Technol 42 1761ndash1765

11 Maier KL Alessandrini F Beck-Speier I Hofer TPJ Diabatґe S Bitterle E Stoger T and Jakob T (2008) Health Effects of Ambient Particulate Matter-Biological Mechanisms and Inflammatory Responses to in Vitroand in Vivo Particle Exposures Inhalation Toxicol 20 319ndash337

Page 16: Studies of Air Pollutants and their Impact on Respiratory and ...€¦ · Ascarate Park C37 Monitoring Station: The National Ambient Air Quality Standard (NAAQS) for PM 10 and 2.5

Tire wear particulate matter

The tire wear particles of the tires are generated either by frictional forces between the treadand the road pavement The chemical content Fe Cr Pb Ti Cr Cu Zn Sr Y Zr Sn Sb Ba LaCe and Pb)

Fig Examples of near spherical particles PM 10 and 25 which are originate from interaction of tires and pavements Source [Dahl et al 2006]

Study Area

The Paso del Norte (PdN) region Selected two strategic areas of study El Paso County zip code 79905 Urban area and Dona Ana County Zip Code 880218802788072 Rural Restricted urban access (freeways and interstates)

Map of the area of the simulation by the MOVES model in the study area

Geographic Domain Zip Code 79905 Urban Area (El Paso County)

Zip Codes 88021880278807288048 (Dona Ana County)

Urban road Delta Dr St 31o 45rsquo 5637- 106o 27rsquo 1212 10 miles

Cordova Bridge of the Americas 31o 45rsquo 4367- 106o 27rsquo 0506 15 miles

478 Highway interstate 31o 46rsquo 1326- 106o 27rsquo 0327 05 miles

110 Highway interstate 31o 46rsquo 1210- 106o 27rsquo 0066 10 miles

10 Interstate Gateway Blvd 31o 46rsquo 397- 106o 26rsquo 4769 05 miles

Chamizal Loop 478 31o 46rsquo 668- 106o 26rsquo 5456 05 miles

Alameda Loop 20 31o 46rsquo 1323- 106o 27rsquo 0328 10 miles

Paisano Dr St Patriot freeway

route 62

31o 46rsquo 0669- 106o 27rsquo 212 15 miles

St Piedras 31o 46rsquo 1326- 106o 27rsquo 0327 10 miles

Dona Ana County Miles

Interstate 25 32o 23rsquo 0561 -106 48

1054 32o 23rsquo 3434- -

106 48 1054 32o 23rsquo

5660 106 48 4314

50

Geographic domain To obtain the simulation mobile data from modelMOVES2010a was configurated the coordinates selected in the study areas

El Paso County

PM25 Estimation from Aerosol Optical Depth (AOD) using

satellites

We examined the relationship

between Aerosol Optical Depth

(AOD) estimated from satellite data

at 5 km spatial resolution and the

mass of fine particles le25 μm in

aerodynamic diameter (PM25)

monitored on the ground in El PdN

area PM25 data was recorded from

air quality monitoring Chamizal

station (TCEQ) on different periods

Our analysis shows a significant

positive association between AOD

and PM25

Time-series and scatter plots of AOD estimated PM25 and surface PM25

Analysis of the meteorological factors and synoptic conditions leading to a local high

ozone event episode June 12-21 2006

Meteorology plays a critical role in determining atmospheric ozone concentrations A good synoptic scale weather forecast is essential to accurately forecast tropospheric and surface ozone concentrations

Figure 1 The domain configuration and Landuse categories

resolution 25 km domainFigure 2 The Geopotential height at 500 mb Figure 3 depicts the 850 mb at a lower altitude The

white regions observed in the graph correspond to

mountainous areas

Figure 4 Temperature at 2m height

above surface at 22 UTC June 18 2006

36 km resolution

Performance Evaluation

01020304050

Ju

ne

137

130

0

190

0

10

0

Ju

ne

157

130

0

190

0

10

0

Ju

ne

187

130

0

190

0

10

0

Tem

pe

ratu

re (⁰C

)

Local time (Hrs)

C41 June 13-19 2006

WRF_temperature

(⁰C)

TCEQ_temperature

(⁰C)

01020304050

June1

37

100

0

130

0

160

0

190

0

220

0

10

0

40

0

June1

57

100

0

130

0

160

0

190

0

220

0

10

0

40

0

June1

87

100

0

130

0

160

0

190

0

220

0

10

0

40

0

Rel

ativ

e h

um

idit

y (

)

Local time (Hrs)

C41 June 13-19 2006

WRF_rh () TCEQ_relative humidity ()

0

5

10

15

20

June

137 10

13

16

19

22 1 4

June

157 10

13

16

19

22 1 4

June

187 10

13

16

19

22 1 4

Win

d s

pee

d (

ms

Local time(Hrs)

C12 June 13-192006

WRF_wind speed (ms) TCEQ_ wind speed (ms)

We evaluate the WRF modelrsquos performance

by comparing against corresponding

experimental TCEQ data and performing the

required statistical analysis

HYSPLIT Model

HYSPLIT was simulated and showed that the ozone is mostly transported to El Paso from north western and south western US and Mexican regions during the 72 hours duration of the simulation

0

20

40

60

80

100

1200

00

10

02

00

30

04

00

50

06

00

70

08

00

90

01

00

01

10

01

20

01

30

01

40

01

50

01

60

01

70

01

80

01

90

02

00

02

10

02

20

02

30

0

Ho

url

y o

zon

e [

pp

b]

0102030405060708090

00

01

00

20

03

00

40

05

00

60

07

00

80

09

00

10

00

11

00

12

00

13

00

14

00

15

00

16

00

17

00

18

00

19

00

20

00

21

00

22

00

23

00

Ho

url

y o

zon

e [

pp

b]

June 18th June 19th

Performance Evaluation

01020304050

Ju

ne

137

130

0

190

0

10

0

Ju

ne

157

130

0

190

0

10

0

Ju

ne

187

130

0

190

0

10

0

Tem

pe

ratu

re (⁰C

)

Local time (Hrs)

C41 June 13-19 2006

WRF_temperature

(⁰C)

TCEQ_temperature

(⁰C)

0

50

100

150

June1

37

100

0

130

0

160

0

190

0

220

0

10

0

40

0

June1

57

100

0

130

0

160

0

190

0

220

0

10

0

40

0

June1

87

100

0

130

0

160

0

190

0

220

0

10

0

40

0Ozo

ne

(pp

b)

Local time (Hrs)

C41 June 13-19 2006

CAMx_ozone (ppbV) TCEQ_ozone (ppb)

0

10

20

30

40

50

June1

37

100

0

130

0

160

0

190

0

220

0

10

0

40

0

June1

57

100

0

130

0

160

0

190

0

220

0

10

0

40

0

June1

87

100

0

130

0

160

0

190

0

220

0

10

0

40

0

Rel

ativ

e h

um

idit

y (

)

Local time (Hrs)

C41 June 13-19 2006

WRF_rh () TCEQ_relative humidity ()

0

5

10

15

20

June

137 10

13

16

19

22 1 4

June

157 10

13

16

19

22 1 4

June

187 10

13

16

19

22 1 4W

ind

sp

eed

(m

sLocal time(Hrs)

C12 June 13-192006

WRF_wind speed (ms) TCEQ_ wind speed (ms)

Methodology

Medical Data The data by weekly monthly and year for daily emergency room and hospital admission for the respiratory

infections (RD) and cardiovascular diseases (CVD) was extracted from hospitals records located in the El PdN

the system includes data on type of admission primary and secondary causes of admissionRESPIRATORY DISEASE

Bronquitis amp Chronic Bronchitis 466 - 4661 491 - 4919

Asthma 463 - 4939

Emphysema 492

Respiratory failure 51881

HEART DISEASE

Accute Myocardial Infarction 410

Coronary Athersclerosis 4140

Other Ischemic Heart Disease 411-4139 4141-4149

Cardiac Dyshythmias 427

Essential hypertension 401

Acute myocardial infarction 410

Congestive Heart Failure 4280 4282-4284

Hypertensive heart disease 402

Table 1 ICD -9 Codes for Respiratory and Cardiovascular Diseases

0

50

100

150

200

250

300

Wee

k 1

Wee

k 2

Wee

k 3

Wee

k 4

Wee

k 5

Wee

k 6

Wee

k 7

Wee

k 8

Wee

k 9

Wee

k 1

0

Wee

k 1

1

Wee

k 1

2

Wee

k 1

3

Wee

k 1

4

Wee

k 1

5

Wee

k 1

6

Wee

k 1

7

Wee

k 1

8

Wee

k 1

9

Wee

k 2

0

Wee

k 2

1

Mo

rb

idit

y D

isch

arg

e fo

r a

ll R

esp

ira

tory

Dis

ease

IC

D-9

(

Ast

hm

aB

ro

nch

itis

)

Weekly Morbidity Discharges of all the Listed Diagnoses for All

Respiratory Disease During WinterSpring 2010

Asthma-Bronchitis

EPA MOVES Model for Estimating Emission

Inventories

Motor Vehicle Emission Simulator (MOVES 2010b) will be configuredin The El Paso North Region for Calculate five categories of PM10

PM25 total Emission inventories from all on-road traffic over a

variety of scales within periods of time selected weeks months

and years

Moves (Motor Vehicle Emission

Simulator)

The emission model is develop using the current equation to calculate direct traffic emissions from

vehicles in the form of PM is

Eext annual emissions are measured in grams of miles traveled by the vehicle (gVMT )

SL is the road surface loading in (gm2)

W is the average weight in tons of the vehicles on the road

K is the particle size multiplier for particle size range (eg gVMT for PM10 when using grams and miles)

P is the 7 number of wet days with at least 0254 mm of precipitation during the averaging period

N is the number of years considered in the averaging period

C is the particle size specific emissions factor in units of interest vehicle direct exhaust brake wear and tirewear

Modeling Simulation Domain and Emissions Scenarios

For simulations of mobile air quality emission inventories a motor vehicle emission simulator EPA (MOVES 2014a) was used

The modeling use input factors divided into seven section

parameters

On-Road Inventory local data

input

Scale

Geographic Bounds

Traffic intensity

Vehicle Type

Pollutants

Road Type

Fuel Types

Figure Source EPA US Environmental Protection Agency 2012- Moves 2010b Model

EPA Moves 2014a The modeling used input factors divided into six section

parameters On-Road Inventory local data input

Geographic Domains CountyNonattainment Area

Vehicle-Miles Traveled (VMT) is the total number of miles driven by all vehicles withina given time period and geographic area

Average speed range from 25 miles per

hour to 65 miles per hour

Vehicle Classes Motorcycle PassengerCarTruks light-duty Commercial Truck(6001-8500 lbs) Buses heave-duty trucksRefuse trucks School Bus Single UnitShort Haul-truck Single Unit Long Haul-truck Long Haul Truck Heavy-DutyVehicles (26001-33000 lbs)

Pollutants

Road TypeRural restricted Acces(Freeways and interstates) Rural and Restricted Acces Urban Restricted Acces Off-Network

Fuel Types Gasoline Diesel Fuel

Specific Road Types

Two road types for running emission from the MOVES can be

selected

(freeways and interstates)

Interior urban Urban

Figure Source EPA US Environmental Protection Agency 2012- Moves 2010b Model

VehiclesEquipment

This panel show which on-road vehicles will be modeled

Figure Source EPA US Environmental Protection Agency 2012- Moves 2010b Model

Long haul truck Short haul truck Inercity bus Ligth comercial truck

Passenger car Passenger truck Refuse truck

School bus Single unit long haul-truck

Single unit short haul-truck

Transit bus

Motor home

Motorcycle

Based on Department of Transportation Highway MOVES will Estimates Traffic

Emissions from Cars Trucks amp Motorcycles

Output Data Moves 2014a

Inventories of PM 10 25 Mobile Emission from all

on-Road Traffic

Exhaust Emission PM 10 25 gramsmile

Brake Wear Emission PM 10 25 gramsmile

Tire wear Emission PM 10 25 gramsmile

Date of Vehicle miles traveled (VMT) for

Day Week Month Year

Total Vehicle population

Vehicle age distribution

Simulation of Mobile Emission in the El PdN Region Zip Code 79905

Figure Total Emissions from road traffic in El Paso TX Area were estimated for PM10

Exhaust and Non exhaust emission in kilogramsmonth (Source EPA MOVES 2014a)

0

10000

20000

30000

40000

50000

PM

10 k

gM

on

th

Months

Monthly PM 10 Exhaust and Non-Exhaust Mobile Emissions 2010

On-Road Urban Restricted Area Zip Code 79905

Primary Exhaust PM 10 (kg) Primary PM 10 Brakewear (kg)

Primary PM 10 Tirewear (kg)

05000

100001500020000250003000035000400004500050000

PM

25

kg

Mo

nth

Months

Monthly PM 25 Exhaust and Non-Exhaust Mobile Emission 2010

On-Road Urban Restricted Area Zip Code 79905

Primary Exhaust PM 25 (kg) Primary PM 25 Brakewear (kg) Primary PM 25Tirewear (kg)

Figure Total Emissions from road traffic in El Paso TX Area were estimated for PM25

Exhaust and Non exhaust emission in kilogramsmonth (Source EPA MOVES 2014a)

Total Emissions from Road Traffic in El Paso County PM1025 Exhaust and Non exhaust Emission in kilogramsmonth

Taking the interests to the health risks related to PM 1025 mobile emission were simulated

Exhaust and Non-exhaust emissions contribute almost equally to total traffic-related PM1025 Emissions (Querol et al 2004 Bukowiecki et al 2009a Amato et al 2011)

Monthly PM 10 25 Exhaust and Non-Exhaust (BrakewearTirewear) Mobile

Emission 2010 On-Road Urban Restricted Area Zip Code 79905

Figure Total Emissions from road traffic in El Paso TX Area were estimated for PM10 25 Exhaust and Non Exhaust mobile

emission in kilograms per month (Source EPA MOVES)

0

10000

20000

30000

40000

50000

January February March April May June July August September October November December

PM

10

25

(K

ilog

ram

s)

Months

Summary- Monthly PM 10 25 Exhaust and Non-Exhaust Mobile

Emission 2010 On-Road Urban Restricted Area Zip Code 79905

Primary Exhaust PM 10 Primary PM 10 Brakewear Primary PM 10 Tirewear

Primary Exhaust PM 25 Primary PM 25 Brakewear Primary PM 25Tirewear

Exhaust Emissions PM1025 is reaching maximum emission 48000-42000 thousand of Kgmonth followedby Brake wear 29000-5000 thousand kgmonth and Tire wear with 9000-2000 kgmonth The results showthat the emissions of PM derived mainly from Exhaust and Brake are significantly higher in Urban Area

Annual Contribution of Mobile Emission PM 1025 (Kg) Zip Code 79905 El

Paso County 2010

Total Primary

Exhaust _PM10

39

Total Primary

Exhaust _PM25

36

Brakewear

particulate_PM10

18

Tirewear

particulate_PM10

4

Brakewear

particulate_PM25

2

Tirewear

particulate_PM25

1

0

5

10

15

20

25

30

35

40

45

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53

Fig Annual Average PM10 Concentrations at the

Chamizal C41 Station and PM1025 mobile

Concentration Zip code 79905

PM10 TCEQ (μgm3) Total Mobile Emission PM10 (Ugm3)

Fig Exhaust Emission is Contributing Approximately 74 of total

PM1025 Mobile Emissions following of Brake wear with 20 and Tire

wear with 5

Annual Average PM1025 ugm3 Mobile Emissions (Moves) 26 Chamizal C41

Monitoring Station (TCEQ Chamizal Station )

Predicting Mobile Emission and VTM

Estimation The PdN Region 2010

44E+09

46E+09

48E+09

5E+09

52E+09

54E+09

56E+09

58E+09

6E+09

62E+09

0

50000

100000

150000

200000

250000

300000

350000

20

10

20

11

20

12

20

13

20

14

20

15

20

16

20

17

20

18

20

21

20

22

20

23

20

24

20

25

20

26

20

27

20

28

20

29

20

30

EX

HA

US

T

EM

ISS

ION

MO

BIL

E (

KG

YE

AR

)

YEARS

Predict ing Mobile Exhaust Emission and VTM

Estimation

2010 - 2030 e l PdN Area

Total_ Exhaust PM10 Total_ Exhaust PM25 Distance (Miles)

Fig Predicting Mobile Exhaust PM1025 (kgMonth) Emission and VTM Estimation 2010

- 2030 el PdN Area

44E+09

46E+09

48E+09

5E+09

52E+09

54E+09

56E+09

58E+09

6E+09

62E+09

0

5000000

10000000

15000000

20000000

25000000

30000000

20

10

20

11

20

12

20

13

20

14

20

15

20

16

20

17

20

18

20

21

20

22

20

23

20

24

20

25

20

26

20

27

20

28

20

29

20

30

EX

HA

US

T

EM

ISS

ION

MO

BIL

E (

KG

YE

AR

)

YEARS

Predict ing Mobile Exhaust Emission and

VTM Estimation

2010 - 2030 e l PdN Area

CO NO2 NO NOx Distance

Fig Predicting Mobile Exhaust Emission and VTM Estimation

2010 - 2030 el PdN Area in El Paso TX Area were estimated for

Total CO NOx NO2 NO emission in kilograms per year

(Source EPA MOVES 2014a model)

The simulated Exhaust emissions in the future years shows a trend of reduction of this type of emissions in the

future years one factor should be the new hybrid technology is increasing by 476 since 2010 to 2015 and

use of catalytic converters diesel particulate filters and improved fuels and engines Non-exhaustive sources

will increase in the coming years because there is no control in the material of manufacture composed by Fe

Cu and Mn also not to be able to reduce the number of events of braking (Accelerations and decelerations)

45E+09

5E+09

55E+09

6E+09

65E+09

0

50000

100000

150000

200000

250000

201

0

201

1

201

2

201

3

201

4

201

5

201

6

201

7

201

8

202

1

202

2

202

3

202

4

202

5

202

6

202

7

202

8

202

9

203

0

NO

N-

EX

HA

US

T

EM

ISS

ION

MO

BIL

E

(KG

YE

AR

)

YEARS

Predicting Non Exhaust Mobile

Emission and VTM Estimation

2010 - 2030 el PdN Area

Brake_PM10 Tire_PM10 Distance (Miles)

Fig Predicting Mobile Exhaust PM1025 (kgMonth) Emission and VTM

Estimation 2010 - 2030 el PdN Area

Daily Avg PM1025

Levels of PM Mobile Emission Non-Exhaust -Rush Hour Periods Fall 2010 Zip Code

79905

00

100

200

300

400

500

600

Mo

bil

e P

M1

0 (k

g)

Rush Hours

Daily Avg PM10

Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush Hours

Periods 2010 Zip Code 79905

Total Primary Exhaust

_PM10 WinterSpring

Brakewear

particulate_PM10

WinterSpringTirewear particulate_PM10

WinterSpring

Total Primary Exhaust

_PM10 Summer

Brakewear

particulate_PM10 Summer

Tirewear Particulate_PM10

Summer

Total Primary Exhaust

_PM10 Fall

Brakewear

particulate_PM10 Fall

Tirewear particulate_PM10

Fall

00

50

100

150

200

250

300

350

Mo

bil

e P

M2

5 (k

g)

Rush hours

Daily Avg PM25

Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush

Hours Periods 2010 Zip Code 79905

Total Primary Exhaust _PM25

WinterSpring

Brakewear Particulate_PM25

WinterSpring

Tirewear particulate_PM25

WinterSpring

Total Primary Exhaust _PM25

Summer

Brakewear particulate_PM25

Summer

Tirewear particulate_PM25

Summer

Total Primary Exhaust _PM25

Fall

Brakewear particulate_PM25

Fall

Tirewear particulate_PM25

Fall

Figure Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush Hours Figure Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush Hours

GIS EMISSIONS INVENTORY SYSTEM A geographic information system (GIS) was used to established geographic scenarios with processed images of seasonal mobile

emissions in the PdN region Seasonal mapping is visualized for different types of pollutants Brakewear Exhaust and Tyrewear

Fg Graphics of GIS and Seasonal mobile Emission of particulate matter emission inventory Seasonal emission simulations were performed in kilograms and five contributing inputs factors were identified for

modeling 1) On the composition of the particulate material from different sources such as Exhaust and Non exhaust (Brake wear Tirewear) 2) The Vehicles Equipment clasification were selected according to

the use of gasoline and diesel fuel (motorcycle passenger car Light Duty Vehicles Trucks refuse truck Light Duty Vehicles Light Commercial Truck Light Duty Vehicles School Bus)

Winter Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

120354 67860 19065

Spring Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

139767 86702 24463

Summer Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

94747 62481 17630

Fall Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

75510 45542 12596

251 Descriptive Statistics Data Analysis

Weekly Correlation Analysis of Mobile Emission PM10 (Exhaust-Non-Exhaust) and Respiratory

Diagnoses WinterSpring Summer and Fall 2010

0

2

4

6

8

10

0

50

100

150

200

250

300

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21

Mo

rbid

ity

Dis

ch

arg

e

for

all R

esp

ira

tory

Dis

ea

se

ICD

-9

(A

sth

ma

-Bro

nc

hitis

)

WinterSpring Week

Weekly Avg Mobile PM10 Concentrations during

WinterSpring 2010 and its Influence on Respiratory

Diagnoses

Zip Code 79905

Total Medical data ZIP Code 79902

Total Mobile Emission PM10 (Ugm3)

0

1

2

3

4

5

6

7

0

20

40

60

80

100

Mo

rbid

ity

Dis

ch

arg

e

for

all R

esp

ira

tory

Dis

ea

se

ICD

-9

(Ast

hm

aB

ron

ch

itis

)

Weekly Avg Mobile PM10 Concentrations during

Summer 2010 and its Influence on Respiratory

Diagnoses

Summer 2010 Zip Code 79905

Total Mobile Emission PM10

Hospital Admission (Asthma-Bronchitis)

0

2

4

6

8

10

12

0

20

40

60

80

100

120

140

160

180

200

Mo

rbid

ity

dis

ch

arg

es

for

all r

esp

ira

tory

dis

ea

se

Weekly Avg Mobile PM10 Concentrations

during Fall 2010 and its Influence on Respiratory

Diagnoses

Zip Code 79905

Total Medical data ZIP Code 79902

Total Mobile Emission PM10 (Ugm3)

Mobile(Exhaust-Non-

Exhaust) PM10 and

Asthma-Bronchitis)

Linear R

Square

WinterSpring 734 ndash 39

Summer 614 ndash 32

Fall 548 -29

PM10 Mobile emission (Exhaust-Non-Exhaust)contributed significantly

association to the incidence of RD

Weekly Correlation Analysis of PM 25 Mobile Emission (Exhaust-Non-Exhaust)

and Cardiovascular Diagnoses WinterSpring Summer and Fall 2010

0010203040

00500

100015002000

Wee

k 1

Wee

k 2

Wee

k 3

Wee

k 4

Wee

k 5

Wee

k 6

Wee

k 7

Wee

k 8

Wee

k 9

Wee

k 1

0

Wee

k 1

1

Wee

k 1

2

Wee

k 1

3

Wee

k 1

4

Wee

k 1

5

Wee

k 1

6

Wee

k 1

7

Wee

k 1

8

Wee

k 1

9

Wee

k 2

0

Wee

k 2

1

Morb

idit

y d

isch

arg

es f

or

all

card

iovasc

ula

r d

isea

se

Weekly Avg PM25 Mobile Concentrations during

WinterSpring 2010 and its Influence on all Heart

Diagnoses

Zip Code 79905

Total All Heart Disease PM 25 mobile (μgm3)

0010203040

00

500

1000

1500

Mo

rbid

ity

dis

ch

arg

es

for

all

ca

rdio

va

scu

lar

dis

ea

se

Weeks

CORRELATION BETWEEN MOBILE PM25 ugm3

EXPOSURE TO HEART DISEASES SYMPTOMS

SUMMER SEASON 2010

Total All Heart Disease PM 25 mobile (μgm3)

Figure Statistical Analyses of the Relationship Between PM25 Caused by Traffic Emission( 26 of total Emission) with Heart diseases Source Hospital Admissions for Asthma Acute Bronchitis and Heart diseases in El Paso County zip code 79905 from Texas Health Care

Information Council in Austin Texas (Texas Health Care Information Council 2000)

00

10

20

30

40

0

50

100

150

We

ek 3

6

We

ek 3

7

We

ek 3

8

We

ek 3

9

We

ek 4

0

We

ek 4

1

We

ek 4

2

We

ek 4

3

We

ek 4

4

We

ek 4

5

We

ek 4

6

We

ek 4

7

We

ek 4

8

We

ek 4

9

We

ek 5

0

We

ek 5

1

We

ek 5

2

We

ek 5

3

Mo

rbid

ity

dis

ch

arg

es

for

all

ca

rdio

va

scu

lar

dis

ea

se

CORRELATION BETWEEN MOBILE PM25 ugm3

EXPOSURE TO HEART DISEASES SYMPTOMS FALL

SEASON 2010

Total All Heart Disease PM 25 mobile (μgm3)

Mobile(Exhaust-

Non-Exhaust)

PM10 and

Asthma-

Bronchitis)

Linear R

Square

WinterSpring 833 -42

Summer 620 -32

Fall 501-26

PM10 Mobile

emission (Exhaust-

Non-

Exhaust)contribut

ed significantly

association to the

incidence of CVD

Diseases

Monthly Brake Mobile Emission PM1025 kg During year 2010 and its Influence on

Respiratory Diagnoses Zip Code 79905

00200040006000800010000

010000200003000040000

PM

10

Mo

bile

(K

g)

Months

Monthly Brake Mobile Emission PM10 kg during year

2010 and its Influence on Respiratory Diagnoses

Zip Code 79905

Primary PM 10

Brakewear 00100020003000400050006000

0

1000

2000

3000

4000

PM

25

Mo

bil

e(K

g)

Months

Monthly Brake Mobile Emission PM25 during

year 2010 and its Influence on Heart Diagnoses

Zip Code 79905

Primary PM 25

Brakewear

Heart Diseases

Hospital

Admission

Brake Mobile Emission

PM10 kg Asthma-

Bronchitis)

Brake Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=969 Linear Square R=856

Monthly Mobile Exhaust Emission PM1025 During year 2010 and its Influence on

Respiratory Diagnoses Zip Code 79905

0

200

400

600

800

1000

0

10000

20000

30000

40000

50000

1 3 5 7 9 11

PM

10

(K

g m

on

th)

Months

Monthly Mobile Exhaust Emission PM10 during

year 2010 and its Influence on Respiratory

Diagnoses

Zip Code 79905

Primary Exhaust

PM 10

Respiratory Disease

(Asthma

Bronchitis) Hospital

Admission

0

100

200

300

400

500

600

0

10000

20000

30000

40000

50000

1 2 3 4 5 6 7 8 9 101112

PM

25

(K

g m

on

th)

Months

Monthly Exhaust Mobile Emission PM25 during

year 2010 and its Influence on Heart Diagnoses

Zip Code 79905

Primary Exhaust PM

25

Heart Diseases

Hospital Admission

Exhaust Mobile Emission

PM10 kg Asthma-

Bronchitis)

Exhaust Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=929 Linear Square R=831

Monthly Tire wear Mobile Emission PM1025 During year 2010 and its Influence on Heart

Diagnoses Zip Code 79905

0

100

200

300

400

500

600

700

800

900

0

1000

2000

3000

4000

5000

6000

7000

8000

9000

1 2 3 4 5 6 7 8 9 10 11 12

PM

10

(K

g m

on

th)

Months

Monthly Tirewear Mobile Emission PM10 during year 2010

and its Influence on Heart Diagnoses

Zip Code 79905

Primary PM 10 Tirewear

Mobile Emission

Respiratory Disease

(Asthma Bronchitis)

Hospital Admission

0

100

200

300

400

500

600

0

200

400

600

800

1000

1200

1400

1 2 3 4 5 6 7 8 9 10 11 12

PM

25

(K

g m

on

th)

Months

Monthly Tirewear Mobile Emission PM25 during year 2010

and its Influence on Respiratory Diagnoses

Zip Code 79905

Primary PM 25Tirewear

Mobile Emission

Heart Diseases Hospital

Admission

Exhaust Mobile Emission

PM10 kg Asthma-

Bronchitis)

Exhaust Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=769 Linear Square R=715

Dona Ana County Zip Codes

88021880278807288048

Primary

Exhaust

PM 10 Zip

code

79905

Total

Primary

Exhaust

PM10

Dona Ana

Primary

Exhaust

PM 25 Zip

Code

79905

Total

Primary

Exhaust

PM25

Dona Ana

Series1 430378 111773 391915 102123

0

100000

200000

300000

400000

500000

AX

IS T

ITLE

Annual Comparison of the Mobile

Exhaust Emissions El Paso County

and Dona Ana 2010

Primary

PM 10

Brakewea

r Zip code

79905

Brakewea

r

particulat

e_PM10

Dona Ana

Primary

PM 10

Tirewear

Zip code

79905

Tirewear

particulat

e_PM10

Dona Ana

Series1 262585 48573 73754 11864

050000

100000150000200000250000300000

AX

IS T

ITLE

Annual Comparison of the Mobile

Brakewear Emissions El Paso County

and Dona Ana 2010

Figure Comparison of the Annual Mobile Emissions

of Primary PM10 Non-Exhauts (Brake ) from Dona

Ana County New Mexico and El Paso Texas Units

in KgMonth

Figure Comparison of the Annual Mobile Emissions

of Primary PM10-Exhauts Emission from Dona Ana

County New Mexico and El Paso Texas Units in

KgMonth

Primary

PM 25

Brakewe

ar Ziphellip

Brakewe

ar

particula

te_PMhellip

Primary

PM

25Tirewe

ar Ziphellip

Tirewear

particula

te_PM25

Donahellip

Series1 32645 6071 10919 1779

0

10000

20000

30000

40000

AX

IS T

ITLE

Annual Comparison of the

Mobile Exhaust Emissions El Paso

County and Dona Ana 2010

Figure Comparison of the Annual Mobile Emissions

of Primary PM10-Exhauts Emission from Dona Ana

County New Mexico and El Paso Texas Units in

KgMonth

Monthly Mobile Emission PM1025 kg During year 2006

and its Influence on Respiratory Diagnoses Dona Ana

County Zip Code 880218802788072

0

100

200

300

0

5000

10000

15000

Axi

s Ti

tle

Axis Title

Monthly Mobile Exhaust Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Total PrimaryMobile Exhaust_PM10

All Respiratory ICD-9 (AsthmaBronchitis)

050100150200250300

010002000300040005000

Axi

s Ti

tle

Axis Title

Monthly Mobile Brake Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Brakewearparticulate_PM10

All RespiratoryICD -9 (AsthmaBronchitis)

050100150200250300

0200400600800

10001200

Axi

s Ti

tle

Axis Title

Monthly Mobile Tirewear Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Tirewearparticulate_PM10

All Respiratory ICD -9 (AsthmaBronchitis)

Mobile Exhauts

Emission PM10

kg Asthma-

Bronchitis)

Brake Mobile

Emission PM10

kg and Heart

Diagnoses

Tirewear Mobile

Emission PM10

kg and Heart

Diagnoses

Linear Square

R= 951

Linear Square

R=625

Linear Square

R=525

Mobile Exhauts

Emission PM25

kg Asthma-

Bronchitis)

Brake Mobile

Emission PM25

kg and Heart

Diagnoses

Tirewear Mobile

Emission PM25

kg and Heart

Diagnoses

Linear Square

R= 986

Linear Square

R=691

Linear Square

R=601

Results

The results showed that mobile PM emissions in the urban areas close to urban Road and highways is putting at risk public health

and the proportion of diseases attributable to this exposure is potentially large

Brake wear emissions is much lower in freeways due to significantly reduced number of braking events while tire wear is much

higher in areas where studded tires are used The emission of exhaust gases are much higher in areas where there is a high

vehicular traffic

Brake Mobile

Emission PM10 kg

Asthma-Bronchitis)

Brake Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square

R=969

Linear Square

R=856

Exhaust Mobile

Emission PM10 kg

Asthma-Bronchitis)

Exhaust Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square

R=929

Linear Square

R=831

Tirewear Mobile

Emission PM10 kg

Asthma-Bronchitis)

Tirewear Mobile

Emission PM25 kg

and Heart Diagnoses

Linear Square R=769 Linear Square R=715

Brake Mobile

Emission PM10 kg

and Heart

Diagnoses

Brake Mobile

Emission PM25 kg

and Heart

Diagnoses

Exhaust Mobile

Emission PM10 kg

Asthma-Bronchitis)

Linear Square

R=625

Linear Square

R=691

Linear Square R=

951

Exhaust Mobile

Emission PM25 kg

Asthma-

Bronchitis)

Tire wear Mobile

Emission PM10 kg and

Heart Diagnoses

Tirewear Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square R=

986

Linear Square R=525 Linear Square

R=601

El Paso County

Dona Ana

County

BenMAP-CE

In this analysis the Program of Mapping and Analysis of Environmental Benefits-Community Edition

(BenMAP-CE) was used to Estimate the number and economic value of health impacts resulting from changes

in air pollution PM 25 Ugm3 in The El Paso Area

Health and Economic Benefits associated with the Response of PM25 Emission between

Base Year 2010

Number of Mortalities in 2010 Base Year Based on El Paso County Texas Department of State Health Services

Number of Mortalities in 2010 Base Year Based on El Paso County Texas

Department of State Health Services

cause of death

year

2010

Populatio

n

Affected

Backgro

und

Concentr

ation Pollutant

Rollback

Type

Avoided

Deaths

(

Populatio

n)

alzheimers disease 2010 40716 125 PM25

25

microgmAcircsup3

Rollback 9

diseases of the

heart 2010 15834 125 PM25

25

microgmAcircsup3

Rollback 35

influenza and

neumonia 2010 81432 125 PM25

25

microgmAcircsup3

Rollback 18

acute bronchitis

and bronchiolitis 2010 117624 125 PM25

25

microgmAcircsup3

Rollback 26

chronic lower

respiratory diseases 2010 54288 125 PM25

25

microgmAcircsup3

Rollback 12

The Basin-wide decrease in 4 ugm3 PM25 concentration after this

reduction control

Cause of death year 2010

Populatio

n

Affected

Background

Concentrati

on

Reduc

cion

scena

rio Polluta

nt

Rollback

Type

Avoi

ded

Deat

hs

(

Pop

ulati

on)

economic

benefits

analysis $

Alzheimers

disease 2010 121 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 9 12000

Diseases of the

heart 2010 470 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 35 35000

Influenza and

neumonia 2010 242 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 18 42500

Acute bronchitis

and bronchiolitis 2010 349 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 26 95000

Chronic lower

respiratory

diseases 2010 161 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 12 4500

$1 295000

PM25-related Mortalities Based on BenMAP-CE Estimate in 2010 Base Year with change in the concentrations levels

Health and Economic Benefits associated with the Response of PM25 Emission between

Base Year 2010 Increasing 7 Ugm3

Cause of death year 2010

Population

Affected

Deaths

avoided by

attaining 195

μgm3

standard

Background

Concentrati

on

Pollut

ant

Rollback

Type

Avoided

Deaths (

Populatio

n)

econo

mic

Unben

efits

analysi

s

Alzheimers

disease 2010 4524 195 PM25

25

microgmAcircsup3

Rollback 19 150000

Diseases of the

heart 2010 20358 195 PM25

25

microgmAcircsup3

Rollback 135 450000

Influenza and

neumonia 2010 126672 195 PM25

25

microgmAcircsup3

Rollback 38 525000

Acute bronchitis

and bronchiolitis 2010 162864 195 PM25

25

microgmAcircsup3

Rollback 36 122000

Chronic lower

respiratory

diseases 2010 99528 195 PM25

25

microgmAcircsup3

Rollback 12 650000

Conclusions

An excellent Pearson Correlation was established to analyze the relationship in the relative risks of hospitalization of Respiratory(RD) and cardiovascular (CVD) associated with ambient exposure caused by traffic emission in relation to their size andspecific sources of emission on different scenarios interior a border Urban Rural Urban restricted access (freeways andinterstates)

A significant correlation of PM1025 exposure from mobile emission and hospital admissions for selected Respiratory (RD) andcardiovascular (CVD) diagnoses was established The results showed that PM emissions in urban restricted access (freeways andinterstates) is mainly caused by traffic Therefore people living close to highways are more exposed higher vehicular emissions

Conclusions

We found statistically significant associations between mobile PM25 caused by traffic emission with Respiratory and Cardiovascular Diseases in the study areaSubsequently a correlation between cardio-respiratory mortality is established

A significant correlation of PM1025 exposure from mobile emission and hospital admissions for selected Respiratory (RD) and cardiovascular (CVD) diagnoses isestablished The results showed that PM emissions in urban restricted access (freeways and interstates) is mainly caused by traffic Therefore people living close tohighways receive higher vehicular emissions

The table shows the percentage of PM mobile exposure in the analyzed areas contributing to increase the risk of Respiratory and Cardiovascular Diseases

An examination was conducted of the synoptic and local meteorology for the June 2006 ozone episode using the WRF model to determine how meteorological parametersinfluence the formation transport and dispersion of ozone in the PdN The predominant synoptic feature of the ozone event day was the expansion intensification and slowprogression of an upper-level ridge of high pressure The high ozone episodes are associated with highly stable atmospheres strong temperature inversions with low mixingheights and therefore low mixing volumes Under these conditions emissions such as NOx lead to highly polluted conditions that favor ozone formation

BenMAP Conclusions

We have estimated the number and economic value of health impacts resulting

from changes in air pollution concentrations of PM 25 in the PdN region

Reduction of Pm 25 4 UGm3= Avoided 213 cases respiratory cardiovascular

diseses and Economic Benefits associated with the Response of PM25 Emission + $

1295000

Increase of PM25 7 ugm3 = increasing Dies= 326 economic Unbenefits= 2345000$

Bibliography

1 Dockery DW Pope CAI Xu X Spengler JD Ware JH Fay ME Ferris BG Speizer FE An association between air pollution and mortality in six US cities N Engl J Med 3291753ndash1759 (1993)

2 Samet JM Dominici F Curriero FC Coursac I Zeger SL Fine particulate air pollution and mortality in 20 US cities 1987ndash1994 N Engl J Med 3431742ndash1749 (2000)

3 Nel AE Diaz-Sanchez D Li N The role of particulate pollutants in pulmonary inflammation and asthma evidence for the involvement of organic chemicals and oxidative stress Curr Opin Pulm Med 20017 20ndash26

4 Westerholm R Karl-Erik E Exhaust emissions from lightand heavy-duty vehicles chemical composition impact of exhaust after treatment and fuel parameters Environ Health Perspect 102(suppl 4)13ndash23 (1994)

5 Bascom R Bromberg P Costa D Delvin R Dockery D Frampton M Lambert W Samet J Speizer F Utell

6 Health effects of outdoor air pollution Am J Respir Crit Care Med 1533ndash50 (1996)

7 Chow JC Watson JG Frazier CA Egami RT Goodrich A Ralph C Spatial and temporal source contributions to

8 PM10 and PM25 in Reno NV In PM-10 Implementation of Standards Transactions An APCAEPA International Speciality Conference San Francisco CA (Mathal CV Stonefield DH eds) PittsburghAPCA 1988439ndash457

9 overview In Particulate Matter Health and Regulatory Issues VIP-49 Proceedings of an International Specialty Conference 4ndash6 April 1995 Pittsburgh PA PittsburghAir and Waste Management Association 1995577ndash598

10 Kunzli N Kaiser R Medina S Studnicka M Chanel O

11 Filliger P Herry M Horak F Jr Puybonnieux-Texier V Quenel P et al Public-health impact of outdoor and traffic- related air pollution a European assessment Lancet 356795ndash801 (2000)

Bibliography

1 Sioutas C Delfino RJ Singh M Exposure assessment for atmospheric ultrafine particles (UFP) and implications in epidemiological research Environ Health Perspect 2005113947ndash955

2 Mosleh M Blau PJ Dumitrescu D (2004) Characteristics and morphology of wear particles from laboratory testing of disc brake materials Wear 2561128ndash1134

3 Kuumlnzli N et al (2000) Public-health impact of outdoor and traffi c-related air pollution a European assessment Lancet 356(9232)795ndash801

4 Dora C Phillips M eds (2000) Transport environment and health Copenhagen WHO Regional Office for Europe (WHO Regional Publications European Series No 89 httpwwweurowhointdocumente72015pdf accessed 26 November 2004)

5 Westerholm R Karl-Erik E Exhaust emissions from lightand

6 heavy-duty vehicles chemical composition impact of exhaust after treatment and fuel parameters Environ Health Perspect 102(suppl 4)13ndash23 (1994)

7 Fauser Tjell Mosbaek pigegaard Quantification of tire-Tread particles using extractable Organic Zinc as a Tracer Rubber Chemistry and Technology 1999 969Table shows some literature estimates of the contribution of tire wear to PM10 in air (Panko et al 2013) Gustafsson M Blomqvist G Gudmundsson A Dahl A Swietlicki E Bohgard M Lindbom J Ljungman A

8 Chen Y Shah N Huggins FE and Huffman GP (2006) Microanalysis of Ambient Particles from Lexington Ky by Electron Microscopy Atmos Environ 40 651ndash663

9 Donaldson K Tran CL Jimenez LA Duffin R Newby DE and Mills N (2005) Combustion-derived Nanoparticles A Review of Their Toxicology Following Inhalation Exposure Part Fibre Toxicol 2 10ndash23

10 Su D Serafino A Muller JO Jentoft RE Schlogl R and Fiorito S (2008) Cytotoxicity and Inflammatory Potential of Soot Particles of Low-emission Diesel Engines Environ Sci Technol 42 1761ndash1765

11 Maier KL Alessandrini F Beck-Speier I Hofer TPJ Diabatґe S Bitterle E Stoger T and Jakob T (2008) Health Effects of Ambient Particulate Matter-Biological Mechanisms and Inflammatory Responses to in Vitroand in Vivo Particle Exposures Inhalation Toxicol 20 319ndash337

Page 17: Studies of Air Pollutants and their Impact on Respiratory and ...€¦ · Ascarate Park C37 Monitoring Station: The National Ambient Air Quality Standard (NAAQS) for PM 10 and 2.5

Study Area

The Paso del Norte (PdN) region Selected two strategic areas of study El Paso County zip code 79905 Urban area and Dona Ana County Zip Code 880218802788072 Rural Restricted urban access (freeways and interstates)

Map of the area of the simulation by the MOVES model in the study area

Geographic Domain Zip Code 79905 Urban Area (El Paso County)

Zip Codes 88021880278807288048 (Dona Ana County)

Urban road Delta Dr St 31o 45rsquo 5637- 106o 27rsquo 1212 10 miles

Cordova Bridge of the Americas 31o 45rsquo 4367- 106o 27rsquo 0506 15 miles

478 Highway interstate 31o 46rsquo 1326- 106o 27rsquo 0327 05 miles

110 Highway interstate 31o 46rsquo 1210- 106o 27rsquo 0066 10 miles

10 Interstate Gateway Blvd 31o 46rsquo 397- 106o 26rsquo 4769 05 miles

Chamizal Loop 478 31o 46rsquo 668- 106o 26rsquo 5456 05 miles

Alameda Loop 20 31o 46rsquo 1323- 106o 27rsquo 0328 10 miles

Paisano Dr St Patriot freeway

route 62

31o 46rsquo 0669- 106o 27rsquo 212 15 miles

St Piedras 31o 46rsquo 1326- 106o 27rsquo 0327 10 miles

Dona Ana County Miles

Interstate 25 32o 23rsquo 0561 -106 48

1054 32o 23rsquo 3434- -

106 48 1054 32o 23rsquo

5660 106 48 4314

50

Geographic domain To obtain the simulation mobile data from modelMOVES2010a was configurated the coordinates selected in the study areas

El Paso County

PM25 Estimation from Aerosol Optical Depth (AOD) using

satellites

We examined the relationship

between Aerosol Optical Depth

(AOD) estimated from satellite data

at 5 km spatial resolution and the

mass of fine particles le25 μm in

aerodynamic diameter (PM25)

monitored on the ground in El PdN

area PM25 data was recorded from

air quality monitoring Chamizal

station (TCEQ) on different periods

Our analysis shows a significant

positive association between AOD

and PM25

Time-series and scatter plots of AOD estimated PM25 and surface PM25

Analysis of the meteorological factors and synoptic conditions leading to a local high

ozone event episode June 12-21 2006

Meteorology plays a critical role in determining atmospheric ozone concentrations A good synoptic scale weather forecast is essential to accurately forecast tropospheric and surface ozone concentrations

Figure 1 The domain configuration and Landuse categories

resolution 25 km domainFigure 2 The Geopotential height at 500 mb Figure 3 depicts the 850 mb at a lower altitude The

white regions observed in the graph correspond to

mountainous areas

Figure 4 Temperature at 2m height

above surface at 22 UTC June 18 2006

36 km resolution

Performance Evaluation

01020304050

Ju

ne

137

130

0

190

0

10

0

Ju

ne

157

130

0

190

0

10

0

Ju

ne

187

130

0

190

0

10

0

Tem

pe

ratu

re (⁰C

)

Local time (Hrs)

C41 June 13-19 2006

WRF_temperature

(⁰C)

TCEQ_temperature

(⁰C)

01020304050

June1

37

100

0

130

0

160

0

190

0

220

0

10

0

40

0

June1

57

100

0

130

0

160

0

190

0

220

0

10

0

40

0

June1

87

100

0

130

0

160

0

190

0

220

0

10

0

40

0

Rel

ativ

e h

um

idit

y (

)

Local time (Hrs)

C41 June 13-19 2006

WRF_rh () TCEQ_relative humidity ()

0

5

10

15

20

June

137 10

13

16

19

22 1 4

June

157 10

13

16

19

22 1 4

June

187 10

13

16

19

22 1 4

Win

d s

pee

d (

ms

Local time(Hrs)

C12 June 13-192006

WRF_wind speed (ms) TCEQ_ wind speed (ms)

We evaluate the WRF modelrsquos performance

by comparing against corresponding

experimental TCEQ data and performing the

required statistical analysis

HYSPLIT Model

HYSPLIT was simulated and showed that the ozone is mostly transported to El Paso from north western and south western US and Mexican regions during the 72 hours duration of the simulation

0

20

40

60

80

100

1200

00

10

02

00

30

04

00

50

06

00

70

08

00

90

01

00

01

10

01

20

01

30

01

40

01

50

01

60

01

70

01

80

01

90

02

00

02

10

02

20

02

30

0

Ho

url

y o

zon

e [

pp

b]

0102030405060708090

00

01

00

20

03

00

40

05

00

60

07

00

80

09

00

10

00

11

00

12

00

13

00

14

00

15

00

16

00

17

00

18

00

19

00

20

00

21

00

22

00

23

00

Ho

url

y o

zon

e [

pp

b]

June 18th June 19th

Performance Evaluation

01020304050

Ju

ne

137

130

0

190

0

10

0

Ju

ne

157

130

0

190

0

10

0

Ju

ne

187

130

0

190

0

10

0

Tem

pe

ratu

re (⁰C

)

Local time (Hrs)

C41 June 13-19 2006

WRF_temperature

(⁰C)

TCEQ_temperature

(⁰C)

0

50

100

150

June1

37

100

0

130

0

160

0

190

0

220

0

10

0

40

0

June1

57

100

0

130

0

160

0

190

0

220

0

10

0

40

0

June1

87

100

0

130

0

160

0

190

0

220

0

10

0

40

0Ozo

ne

(pp

b)

Local time (Hrs)

C41 June 13-19 2006

CAMx_ozone (ppbV) TCEQ_ozone (ppb)

0

10

20

30

40

50

June1

37

100

0

130

0

160

0

190

0

220

0

10

0

40

0

June1

57

100

0

130

0

160

0

190

0

220

0

10

0

40

0

June1

87

100

0

130

0

160

0

190

0

220

0

10

0

40

0

Rel

ativ

e h

um

idit

y (

)

Local time (Hrs)

C41 June 13-19 2006

WRF_rh () TCEQ_relative humidity ()

0

5

10

15

20

June

137 10

13

16

19

22 1 4

June

157 10

13

16

19

22 1 4

June

187 10

13

16

19

22 1 4W

ind

sp

eed

(m

sLocal time(Hrs)

C12 June 13-192006

WRF_wind speed (ms) TCEQ_ wind speed (ms)

Methodology

Medical Data The data by weekly monthly and year for daily emergency room and hospital admission for the respiratory

infections (RD) and cardiovascular diseases (CVD) was extracted from hospitals records located in the El PdN

the system includes data on type of admission primary and secondary causes of admissionRESPIRATORY DISEASE

Bronquitis amp Chronic Bronchitis 466 - 4661 491 - 4919

Asthma 463 - 4939

Emphysema 492

Respiratory failure 51881

HEART DISEASE

Accute Myocardial Infarction 410

Coronary Athersclerosis 4140

Other Ischemic Heart Disease 411-4139 4141-4149

Cardiac Dyshythmias 427

Essential hypertension 401

Acute myocardial infarction 410

Congestive Heart Failure 4280 4282-4284

Hypertensive heart disease 402

Table 1 ICD -9 Codes for Respiratory and Cardiovascular Diseases

0

50

100

150

200

250

300

Wee

k 1

Wee

k 2

Wee

k 3

Wee

k 4

Wee

k 5

Wee

k 6

Wee

k 7

Wee

k 8

Wee

k 9

Wee

k 1

0

Wee

k 1

1

Wee

k 1

2

Wee

k 1

3

Wee

k 1

4

Wee

k 1

5

Wee

k 1

6

Wee

k 1

7

Wee

k 1

8

Wee

k 1

9

Wee

k 2

0

Wee

k 2

1

Mo

rb

idit

y D

isch

arg

e fo

r a

ll R

esp

ira

tory

Dis

ease

IC

D-9

(

Ast

hm

aB

ro

nch

itis

)

Weekly Morbidity Discharges of all the Listed Diagnoses for All

Respiratory Disease During WinterSpring 2010

Asthma-Bronchitis

EPA MOVES Model for Estimating Emission

Inventories

Motor Vehicle Emission Simulator (MOVES 2010b) will be configuredin The El Paso North Region for Calculate five categories of PM10

PM25 total Emission inventories from all on-road traffic over a

variety of scales within periods of time selected weeks months

and years

Moves (Motor Vehicle Emission

Simulator)

The emission model is develop using the current equation to calculate direct traffic emissions from

vehicles in the form of PM is

Eext annual emissions are measured in grams of miles traveled by the vehicle (gVMT )

SL is the road surface loading in (gm2)

W is the average weight in tons of the vehicles on the road

K is the particle size multiplier for particle size range (eg gVMT for PM10 when using grams and miles)

P is the 7 number of wet days with at least 0254 mm of precipitation during the averaging period

N is the number of years considered in the averaging period

C is the particle size specific emissions factor in units of interest vehicle direct exhaust brake wear and tirewear

Modeling Simulation Domain and Emissions Scenarios

For simulations of mobile air quality emission inventories a motor vehicle emission simulator EPA (MOVES 2014a) was used

The modeling use input factors divided into seven section

parameters

On-Road Inventory local data

input

Scale

Geographic Bounds

Traffic intensity

Vehicle Type

Pollutants

Road Type

Fuel Types

Figure Source EPA US Environmental Protection Agency 2012- Moves 2010b Model

EPA Moves 2014a The modeling used input factors divided into six section

parameters On-Road Inventory local data input

Geographic Domains CountyNonattainment Area

Vehicle-Miles Traveled (VMT) is the total number of miles driven by all vehicles withina given time period and geographic area

Average speed range from 25 miles per

hour to 65 miles per hour

Vehicle Classes Motorcycle PassengerCarTruks light-duty Commercial Truck(6001-8500 lbs) Buses heave-duty trucksRefuse trucks School Bus Single UnitShort Haul-truck Single Unit Long Haul-truck Long Haul Truck Heavy-DutyVehicles (26001-33000 lbs)

Pollutants

Road TypeRural restricted Acces(Freeways and interstates) Rural and Restricted Acces Urban Restricted Acces Off-Network

Fuel Types Gasoline Diesel Fuel

Specific Road Types

Two road types for running emission from the MOVES can be

selected

(freeways and interstates)

Interior urban Urban

Figure Source EPA US Environmental Protection Agency 2012- Moves 2010b Model

VehiclesEquipment

This panel show which on-road vehicles will be modeled

Figure Source EPA US Environmental Protection Agency 2012- Moves 2010b Model

Long haul truck Short haul truck Inercity bus Ligth comercial truck

Passenger car Passenger truck Refuse truck

School bus Single unit long haul-truck

Single unit short haul-truck

Transit bus

Motor home

Motorcycle

Based on Department of Transportation Highway MOVES will Estimates Traffic

Emissions from Cars Trucks amp Motorcycles

Output Data Moves 2014a

Inventories of PM 10 25 Mobile Emission from all

on-Road Traffic

Exhaust Emission PM 10 25 gramsmile

Brake Wear Emission PM 10 25 gramsmile

Tire wear Emission PM 10 25 gramsmile

Date of Vehicle miles traveled (VMT) for

Day Week Month Year

Total Vehicle population

Vehicle age distribution

Simulation of Mobile Emission in the El PdN Region Zip Code 79905

Figure Total Emissions from road traffic in El Paso TX Area were estimated for PM10

Exhaust and Non exhaust emission in kilogramsmonth (Source EPA MOVES 2014a)

0

10000

20000

30000

40000

50000

PM

10 k

gM

on

th

Months

Monthly PM 10 Exhaust and Non-Exhaust Mobile Emissions 2010

On-Road Urban Restricted Area Zip Code 79905

Primary Exhaust PM 10 (kg) Primary PM 10 Brakewear (kg)

Primary PM 10 Tirewear (kg)

05000

100001500020000250003000035000400004500050000

PM

25

kg

Mo

nth

Months

Monthly PM 25 Exhaust and Non-Exhaust Mobile Emission 2010

On-Road Urban Restricted Area Zip Code 79905

Primary Exhaust PM 25 (kg) Primary PM 25 Brakewear (kg) Primary PM 25Tirewear (kg)

Figure Total Emissions from road traffic in El Paso TX Area were estimated for PM25

Exhaust and Non exhaust emission in kilogramsmonth (Source EPA MOVES 2014a)

Total Emissions from Road Traffic in El Paso County PM1025 Exhaust and Non exhaust Emission in kilogramsmonth

Taking the interests to the health risks related to PM 1025 mobile emission were simulated

Exhaust and Non-exhaust emissions contribute almost equally to total traffic-related PM1025 Emissions (Querol et al 2004 Bukowiecki et al 2009a Amato et al 2011)

Monthly PM 10 25 Exhaust and Non-Exhaust (BrakewearTirewear) Mobile

Emission 2010 On-Road Urban Restricted Area Zip Code 79905

Figure Total Emissions from road traffic in El Paso TX Area were estimated for PM10 25 Exhaust and Non Exhaust mobile

emission in kilograms per month (Source EPA MOVES)

0

10000

20000

30000

40000

50000

January February March April May June July August September October November December

PM

10

25

(K

ilog

ram

s)

Months

Summary- Monthly PM 10 25 Exhaust and Non-Exhaust Mobile

Emission 2010 On-Road Urban Restricted Area Zip Code 79905

Primary Exhaust PM 10 Primary PM 10 Brakewear Primary PM 10 Tirewear

Primary Exhaust PM 25 Primary PM 25 Brakewear Primary PM 25Tirewear

Exhaust Emissions PM1025 is reaching maximum emission 48000-42000 thousand of Kgmonth followedby Brake wear 29000-5000 thousand kgmonth and Tire wear with 9000-2000 kgmonth The results showthat the emissions of PM derived mainly from Exhaust and Brake are significantly higher in Urban Area

Annual Contribution of Mobile Emission PM 1025 (Kg) Zip Code 79905 El

Paso County 2010

Total Primary

Exhaust _PM10

39

Total Primary

Exhaust _PM25

36

Brakewear

particulate_PM10

18

Tirewear

particulate_PM10

4

Brakewear

particulate_PM25

2

Tirewear

particulate_PM25

1

0

5

10

15

20

25

30

35

40

45

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53

Fig Annual Average PM10 Concentrations at the

Chamizal C41 Station and PM1025 mobile

Concentration Zip code 79905

PM10 TCEQ (μgm3) Total Mobile Emission PM10 (Ugm3)

Fig Exhaust Emission is Contributing Approximately 74 of total

PM1025 Mobile Emissions following of Brake wear with 20 and Tire

wear with 5

Annual Average PM1025 ugm3 Mobile Emissions (Moves) 26 Chamizal C41

Monitoring Station (TCEQ Chamizal Station )

Predicting Mobile Emission and VTM

Estimation The PdN Region 2010

44E+09

46E+09

48E+09

5E+09

52E+09

54E+09

56E+09

58E+09

6E+09

62E+09

0

50000

100000

150000

200000

250000

300000

350000

20

10

20

11

20

12

20

13

20

14

20

15

20

16

20

17

20

18

20

21

20

22

20

23

20

24

20

25

20

26

20

27

20

28

20

29

20

30

EX

HA

US

T

EM

ISS

ION

MO

BIL

E (

KG

YE

AR

)

YEARS

Predict ing Mobile Exhaust Emission and VTM

Estimation

2010 - 2030 e l PdN Area

Total_ Exhaust PM10 Total_ Exhaust PM25 Distance (Miles)

Fig Predicting Mobile Exhaust PM1025 (kgMonth) Emission and VTM Estimation 2010

- 2030 el PdN Area

44E+09

46E+09

48E+09

5E+09

52E+09

54E+09

56E+09

58E+09

6E+09

62E+09

0

5000000

10000000

15000000

20000000

25000000

30000000

20

10

20

11

20

12

20

13

20

14

20

15

20

16

20

17

20

18

20

21

20

22

20

23

20

24

20

25

20

26

20

27

20

28

20

29

20

30

EX

HA

US

T

EM

ISS

ION

MO

BIL

E (

KG

YE

AR

)

YEARS

Predict ing Mobile Exhaust Emission and

VTM Estimation

2010 - 2030 e l PdN Area

CO NO2 NO NOx Distance

Fig Predicting Mobile Exhaust Emission and VTM Estimation

2010 - 2030 el PdN Area in El Paso TX Area were estimated for

Total CO NOx NO2 NO emission in kilograms per year

(Source EPA MOVES 2014a model)

The simulated Exhaust emissions in the future years shows a trend of reduction of this type of emissions in the

future years one factor should be the new hybrid technology is increasing by 476 since 2010 to 2015 and

use of catalytic converters diesel particulate filters and improved fuels and engines Non-exhaustive sources

will increase in the coming years because there is no control in the material of manufacture composed by Fe

Cu and Mn also not to be able to reduce the number of events of braking (Accelerations and decelerations)

45E+09

5E+09

55E+09

6E+09

65E+09

0

50000

100000

150000

200000

250000

201

0

201

1

201

2

201

3

201

4

201

5

201

6

201

7

201

8

202

1

202

2

202

3

202

4

202

5

202

6

202

7

202

8

202

9

203

0

NO

N-

EX

HA

US

T

EM

ISS

ION

MO

BIL

E

(KG

YE

AR

)

YEARS

Predicting Non Exhaust Mobile

Emission and VTM Estimation

2010 - 2030 el PdN Area

Brake_PM10 Tire_PM10 Distance (Miles)

Fig Predicting Mobile Exhaust PM1025 (kgMonth) Emission and VTM

Estimation 2010 - 2030 el PdN Area

Daily Avg PM1025

Levels of PM Mobile Emission Non-Exhaust -Rush Hour Periods Fall 2010 Zip Code

79905

00

100

200

300

400

500

600

Mo

bil

e P

M1

0 (k

g)

Rush Hours

Daily Avg PM10

Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush Hours

Periods 2010 Zip Code 79905

Total Primary Exhaust

_PM10 WinterSpring

Brakewear

particulate_PM10

WinterSpringTirewear particulate_PM10

WinterSpring

Total Primary Exhaust

_PM10 Summer

Brakewear

particulate_PM10 Summer

Tirewear Particulate_PM10

Summer

Total Primary Exhaust

_PM10 Fall

Brakewear

particulate_PM10 Fall

Tirewear particulate_PM10

Fall

00

50

100

150

200

250

300

350

Mo

bil

e P

M2

5 (k

g)

Rush hours

Daily Avg PM25

Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush

Hours Periods 2010 Zip Code 79905

Total Primary Exhaust _PM25

WinterSpring

Brakewear Particulate_PM25

WinterSpring

Tirewear particulate_PM25

WinterSpring

Total Primary Exhaust _PM25

Summer

Brakewear particulate_PM25

Summer

Tirewear particulate_PM25

Summer

Total Primary Exhaust _PM25

Fall

Brakewear particulate_PM25

Fall

Tirewear particulate_PM25

Fall

Figure Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush Hours Figure Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush Hours

GIS EMISSIONS INVENTORY SYSTEM A geographic information system (GIS) was used to established geographic scenarios with processed images of seasonal mobile

emissions in the PdN region Seasonal mapping is visualized for different types of pollutants Brakewear Exhaust and Tyrewear

Fg Graphics of GIS and Seasonal mobile Emission of particulate matter emission inventory Seasonal emission simulations were performed in kilograms and five contributing inputs factors were identified for

modeling 1) On the composition of the particulate material from different sources such as Exhaust and Non exhaust (Brake wear Tirewear) 2) The Vehicles Equipment clasification were selected according to

the use of gasoline and diesel fuel (motorcycle passenger car Light Duty Vehicles Trucks refuse truck Light Duty Vehicles Light Commercial Truck Light Duty Vehicles School Bus)

Winter Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

120354 67860 19065

Spring Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

139767 86702 24463

Summer Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

94747 62481 17630

Fall Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

75510 45542 12596

251 Descriptive Statistics Data Analysis

Weekly Correlation Analysis of Mobile Emission PM10 (Exhaust-Non-Exhaust) and Respiratory

Diagnoses WinterSpring Summer and Fall 2010

0

2

4

6

8

10

0

50

100

150

200

250

300

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21

Mo

rbid

ity

Dis

ch

arg

e

for

all R

esp

ira

tory

Dis

ea

se

ICD

-9

(A

sth

ma

-Bro

nc

hitis

)

WinterSpring Week

Weekly Avg Mobile PM10 Concentrations during

WinterSpring 2010 and its Influence on Respiratory

Diagnoses

Zip Code 79905

Total Medical data ZIP Code 79902

Total Mobile Emission PM10 (Ugm3)

0

1

2

3

4

5

6

7

0

20

40

60

80

100

Mo

rbid

ity

Dis

ch

arg

e

for

all R

esp

ira

tory

Dis

ea

se

ICD

-9

(Ast

hm

aB

ron

ch

itis

)

Weekly Avg Mobile PM10 Concentrations during

Summer 2010 and its Influence on Respiratory

Diagnoses

Summer 2010 Zip Code 79905

Total Mobile Emission PM10

Hospital Admission (Asthma-Bronchitis)

0

2

4

6

8

10

12

0

20

40

60

80

100

120

140

160

180

200

Mo

rbid

ity

dis

ch

arg

es

for

all r

esp

ira

tory

dis

ea

se

Weekly Avg Mobile PM10 Concentrations

during Fall 2010 and its Influence on Respiratory

Diagnoses

Zip Code 79905

Total Medical data ZIP Code 79902

Total Mobile Emission PM10 (Ugm3)

Mobile(Exhaust-Non-

Exhaust) PM10 and

Asthma-Bronchitis)

Linear R

Square

WinterSpring 734 ndash 39

Summer 614 ndash 32

Fall 548 -29

PM10 Mobile emission (Exhaust-Non-Exhaust)contributed significantly

association to the incidence of RD

Weekly Correlation Analysis of PM 25 Mobile Emission (Exhaust-Non-Exhaust)

and Cardiovascular Diagnoses WinterSpring Summer and Fall 2010

0010203040

00500

100015002000

Wee

k 1

Wee

k 2

Wee

k 3

Wee

k 4

Wee

k 5

Wee

k 6

Wee

k 7

Wee

k 8

Wee

k 9

Wee

k 1

0

Wee

k 1

1

Wee

k 1

2

Wee

k 1

3

Wee

k 1

4

Wee

k 1

5

Wee

k 1

6

Wee

k 1

7

Wee

k 1

8

Wee

k 1

9

Wee

k 2

0

Wee

k 2

1

Morb

idit

y d

isch

arg

es f

or

all

card

iovasc

ula

r d

isea

se

Weekly Avg PM25 Mobile Concentrations during

WinterSpring 2010 and its Influence on all Heart

Diagnoses

Zip Code 79905

Total All Heart Disease PM 25 mobile (μgm3)

0010203040

00

500

1000

1500

Mo

rbid

ity

dis

ch

arg

es

for

all

ca

rdio

va

scu

lar

dis

ea

se

Weeks

CORRELATION BETWEEN MOBILE PM25 ugm3

EXPOSURE TO HEART DISEASES SYMPTOMS

SUMMER SEASON 2010

Total All Heart Disease PM 25 mobile (μgm3)

Figure Statistical Analyses of the Relationship Between PM25 Caused by Traffic Emission( 26 of total Emission) with Heart diseases Source Hospital Admissions for Asthma Acute Bronchitis and Heart diseases in El Paso County zip code 79905 from Texas Health Care

Information Council in Austin Texas (Texas Health Care Information Council 2000)

00

10

20

30

40

0

50

100

150

We

ek 3

6

We

ek 3

7

We

ek 3

8

We

ek 3

9

We

ek 4

0

We

ek 4

1

We

ek 4

2

We

ek 4

3

We

ek 4

4

We

ek 4

5

We

ek 4

6

We

ek 4

7

We

ek 4

8

We

ek 4

9

We

ek 5

0

We

ek 5

1

We

ek 5

2

We

ek 5

3

Mo

rbid

ity

dis

ch

arg

es

for

all

ca

rdio

va

scu

lar

dis

ea

se

CORRELATION BETWEEN MOBILE PM25 ugm3

EXPOSURE TO HEART DISEASES SYMPTOMS FALL

SEASON 2010

Total All Heart Disease PM 25 mobile (μgm3)

Mobile(Exhaust-

Non-Exhaust)

PM10 and

Asthma-

Bronchitis)

Linear R

Square

WinterSpring 833 -42

Summer 620 -32

Fall 501-26

PM10 Mobile

emission (Exhaust-

Non-

Exhaust)contribut

ed significantly

association to the

incidence of CVD

Diseases

Monthly Brake Mobile Emission PM1025 kg During year 2010 and its Influence on

Respiratory Diagnoses Zip Code 79905

00200040006000800010000

010000200003000040000

PM

10

Mo

bile

(K

g)

Months

Monthly Brake Mobile Emission PM10 kg during year

2010 and its Influence on Respiratory Diagnoses

Zip Code 79905

Primary PM 10

Brakewear 00100020003000400050006000

0

1000

2000

3000

4000

PM

25

Mo

bil

e(K

g)

Months

Monthly Brake Mobile Emission PM25 during

year 2010 and its Influence on Heart Diagnoses

Zip Code 79905

Primary PM 25

Brakewear

Heart Diseases

Hospital

Admission

Brake Mobile Emission

PM10 kg Asthma-

Bronchitis)

Brake Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=969 Linear Square R=856

Monthly Mobile Exhaust Emission PM1025 During year 2010 and its Influence on

Respiratory Diagnoses Zip Code 79905

0

200

400

600

800

1000

0

10000

20000

30000

40000

50000

1 3 5 7 9 11

PM

10

(K

g m

on

th)

Months

Monthly Mobile Exhaust Emission PM10 during

year 2010 and its Influence on Respiratory

Diagnoses

Zip Code 79905

Primary Exhaust

PM 10

Respiratory Disease

(Asthma

Bronchitis) Hospital

Admission

0

100

200

300

400

500

600

0

10000

20000

30000

40000

50000

1 2 3 4 5 6 7 8 9 101112

PM

25

(K

g m

on

th)

Months

Monthly Exhaust Mobile Emission PM25 during

year 2010 and its Influence on Heart Diagnoses

Zip Code 79905

Primary Exhaust PM

25

Heart Diseases

Hospital Admission

Exhaust Mobile Emission

PM10 kg Asthma-

Bronchitis)

Exhaust Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=929 Linear Square R=831

Monthly Tire wear Mobile Emission PM1025 During year 2010 and its Influence on Heart

Diagnoses Zip Code 79905

0

100

200

300

400

500

600

700

800

900

0

1000

2000

3000

4000

5000

6000

7000

8000

9000

1 2 3 4 5 6 7 8 9 10 11 12

PM

10

(K

g m

on

th)

Months

Monthly Tirewear Mobile Emission PM10 during year 2010

and its Influence on Heart Diagnoses

Zip Code 79905

Primary PM 10 Tirewear

Mobile Emission

Respiratory Disease

(Asthma Bronchitis)

Hospital Admission

0

100

200

300

400

500

600

0

200

400

600

800

1000

1200

1400

1 2 3 4 5 6 7 8 9 10 11 12

PM

25

(K

g m

on

th)

Months

Monthly Tirewear Mobile Emission PM25 during year 2010

and its Influence on Respiratory Diagnoses

Zip Code 79905

Primary PM 25Tirewear

Mobile Emission

Heart Diseases Hospital

Admission

Exhaust Mobile Emission

PM10 kg Asthma-

Bronchitis)

Exhaust Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=769 Linear Square R=715

Dona Ana County Zip Codes

88021880278807288048

Primary

Exhaust

PM 10 Zip

code

79905

Total

Primary

Exhaust

PM10

Dona Ana

Primary

Exhaust

PM 25 Zip

Code

79905

Total

Primary

Exhaust

PM25

Dona Ana

Series1 430378 111773 391915 102123

0

100000

200000

300000

400000

500000

AX

IS T

ITLE

Annual Comparison of the Mobile

Exhaust Emissions El Paso County

and Dona Ana 2010

Primary

PM 10

Brakewea

r Zip code

79905

Brakewea

r

particulat

e_PM10

Dona Ana

Primary

PM 10

Tirewear

Zip code

79905

Tirewear

particulat

e_PM10

Dona Ana

Series1 262585 48573 73754 11864

050000

100000150000200000250000300000

AX

IS T

ITLE

Annual Comparison of the Mobile

Brakewear Emissions El Paso County

and Dona Ana 2010

Figure Comparison of the Annual Mobile Emissions

of Primary PM10 Non-Exhauts (Brake ) from Dona

Ana County New Mexico and El Paso Texas Units

in KgMonth

Figure Comparison of the Annual Mobile Emissions

of Primary PM10-Exhauts Emission from Dona Ana

County New Mexico and El Paso Texas Units in

KgMonth

Primary

PM 25

Brakewe

ar Ziphellip

Brakewe

ar

particula

te_PMhellip

Primary

PM

25Tirewe

ar Ziphellip

Tirewear

particula

te_PM25

Donahellip

Series1 32645 6071 10919 1779

0

10000

20000

30000

40000

AX

IS T

ITLE

Annual Comparison of the

Mobile Exhaust Emissions El Paso

County and Dona Ana 2010

Figure Comparison of the Annual Mobile Emissions

of Primary PM10-Exhauts Emission from Dona Ana

County New Mexico and El Paso Texas Units in

KgMonth

Monthly Mobile Emission PM1025 kg During year 2006

and its Influence on Respiratory Diagnoses Dona Ana

County Zip Code 880218802788072

0

100

200

300

0

5000

10000

15000

Axi

s Ti

tle

Axis Title

Monthly Mobile Exhaust Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Total PrimaryMobile Exhaust_PM10

All Respiratory ICD-9 (AsthmaBronchitis)

050100150200250300

010002000300040005000

Axi

s Ti

tle

Axis Title

Monthly Mobile Brake Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Brakewearparticulate_PM10

All RespiratoryICD -9 (AsthmaBronchitis)

050100150200250300

0200400600800

10001200

Axi

s Ti

tle

Axis Title

Monthly Mobile Tirewear Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Tirewearparticulate_PM10

All Respiratory ICD -9 (AsthmaBronchitis)

Mobile Exhauts

Emission PM10

kg Asthma-

Bronchitis)

Brake Mobile

Emission PM10

kg and Heart

Diagnoses

Tirewear Mobile

Emission PM10

kg and Heart

Diagnoses

Linear Square

R= 951

Linear Square

R=625

Linear Square

R=525

Mobile Exhauts

Emission PM25

kg Asthma-

Bronchitis)

Brake Mobile

Emission PM25

kg and Heart

Diagnoses

Tirewear Mobile

Emission PM25

kg and Heart

Diagnoses

Linear Square

R= 986

Linear Square

R=691

Linear Square

R=601

Results

The results showed that mobile PM emissions in the urban areas close to urban Road and highways is putting at risk public health

and the proportion of diseases attributable to this exposure is potentially large

Brake wear emissions is much lower in freeways due to significantly reduced number of braking events while tire wear is much

higher in areas where studded tires are used The emission of exhaust gases are much higher in areas where there is a high

vehicular traffic

Brake Mobile

Emission PM10 kg

Asthma-Bronchitis)

Brake Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square

R=969

Linear Square

R=856

Exhaust Mobile

Emission PM10 kg

Asthma-Bronchitis)

Exhaust Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square

R=929

Linear Square

R=831

Tirewear Mobile

Emission PM10 kg

Asthma-Bronchitis)

Tirewear Mobile

Emission PM25 kg

and Heart Diagnoses

Linear Square R=769 Linear Square R=715

Brake Mobile

Emission PM10 kg

and Heart

Diagnoses

Brake Mobile

Emission PM25 kg

and Heart

Diagnoses

Exhaust Mobile

Emission PM10 kg

Asthma-Bronchitis)

Linear Square

R=625

Linear Square

R=691

Linear Square R=

951

Exhaust Mobile

Emission PM25 kg

Asthma-

Bronchitis)

Tire wear Mobile

Emission PM10 kg and

Heart Diagnoses

Tirewear Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square R=

986

Linear Square R=525 Linear Square

R=601

El Paso County

Dona Ana

County

BenMAP-CE

In this analysis the Program of Mapping and Analysis of Environmental Benefits-Community Edition

(BenMAP-CE) was used to Estimate the number and economic value of health impacts resulting from changes

in air pollution PM 25 Ugm3 in The El Paso Area

Health and Economic Benefits associated with the Response of PM25 Emission between

Base Year 2010

Number of Mortalities in 2010 Base Year Based on El Paso County Texas Department of State Health Services

Number of Mortalities in 2010 Base Year Based on El Paso County Texas

Department of State Health Services

cause of death

year

2010

Populatio

n

Affected

Backgro

und

Concentr

ation Pollutant

Rollback

Type

Avoided

Deaths

(

Populatio

n)

alzheimers disease 2010 40716 125 PM25

25

microgmAcircsup3

Rollback 9

diseases of the

heart 2010 15834 125 PM25

25

microgmAcircsup3

Rollback 35

influenza and

neumonia 2010 81432 125 PM25

25

microgmAcircsup3

Rollback 18

acute bronchitis

and bronchiolitis 2010 117624 125 PM25

25

microgmAcircsup3

Rollback 26

chronic lower

respiratory diseases 2010 54288 125 PM25

25

microgmAcircsup3

Rollback 12

The Basin-wide decrease in 4 ugm3 PM25 concentration after this

reduction control

Cause of death year 2010

Populatio

n

Affected

Background

Concentrati

on

Reduc

cion

scena

rio Polluta

nt

Rollback

Type

Avoi

ded

Deat

hs

(

Pop

ulati

on)

economic

benefits

analysis $

Alzheimers

disease 2010 121 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 9 12000

Diseases of the

heart 2010 470 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 35 35000

Influenza and

neumonia 2010 242 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 18 42500

Acute bronchitis

and bronchiolitis 2010 349 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 26 95000

Chronic lower

respiratory

diseases 2010 161 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 12 4500

$1 295000

PM25-related Mortalities Based on BenMAP-CE Estimate in 2010 Base Year with change in the concentrations levels

Health and Economic Benefits associated with the Response of PM25 Emission between

Base Year 2010 Increasing 7 Ugm3

Cause of death year 2010

Population

Affected

Deaths

avoided by

attaining 195

μgm3

standard

Background

Concentrati

on

Pollut

ant

Rollback

Type

Avoided

Deaths (

Populatio

n)

econo

mic

Unben

efits

analysi

s

Alzheimers

disease 2010 4524 195 PM25

25

microgmAcircsup3

Rollback 19 150000

Diseases of the

heart 2010 20358 195 PM25

25

microgmAcircsup3

Rollback 135 450000

Influenza and

neumonia 2010 126672 195 PM25

25

microgmAcircsup3

Rollback 38 525000

Acute bronchitis

and bronchiolitis 2010 162864 195 PM25

25

microgmAcircsup3

Rollback 36 122000

Chronic lower

respiratory

diseases 2010 99528 195 PM25

25

microgmAcircsup3

Rollback 12 650000

Conclusions

An excellent Pearson Correlation was established to analyze the relationship in the relative risks of hospitalization of Respiratory(RD) and cardiovascular (CVD) associated with ambient exposure caused by traffic emission in relation to their size andspecific sources of emission on different scenarios interior a border Urban Rural Urban restricted access (freeways andinterstates)

A significant correlation of PM1025 exposure from mobile emission and hospital admissions for selected Respiratory (RD) andcardiovascular (CVD) diagnoses was established The results showed that PM emissions in urban restricted access (freeways andinterstates) is mainly caused by traffic Therefore people living close to highways are more exposed higher vehicular emissions

Conclusions

We found statistically significant associations between mobile PM25 caused by traffic emission with Respiratory and Cardiovascular Diseases in the study areaSubsequently a correlation between cardio-respiratory mortality is established

A significant correlation of PM1025 exposure from mobile emission and hospital admissions for selected Respiratory (RD) and cardiovascular (CVD) diagnoses isestablished The results showed that PM emissions in urban restricted access (freeways and interstates) is mainly caused by traffic Therefore people living close tohighways receive higher vehicular emissions

The table shows the percentage of PM mobile exposure in the analyzed areas contributing to increase the risk of Respiratory and Cardiovascular Diseases

An examination was conducted of the synoptic and local meteorology for the June 2006 ozone episode using the WRF model to determine how meteorological parametersinfluence the formation transport and dispersion of ozone in the PdN The predominant synoptic feature of the ozone event day was the expansion intensification and slowprogression of an upper-level ridge of high pressure The high ozone episodes are associated with highly stable atmospheres strong temperature inversions with low mixingheights and therefore low mixing volumes Under these conditions emissions such as NOx lead to highly polluted conditions that favor ozone formation

BenMAP Conclusions

We have estimated the number and economic value of health impacts resulting

from changes in air pollution concentrations of PM 25 in the PdN region

Reduction of Pm 25 4 UGm3= Avoided 213 cases respiratory cardiovascular

diseses and Economic Benefits associated with the Response of PM25 Emission + $

1295000

Increase of PM25 7 ugm3 = increasing Dies= 326 economic Unbenefits= 2345000$

Bibliography

1 Dockery DW Pope CAI Xu X Spengler JD Ware JH Fay ME Ferris BG Speizer FE An association between air pollution and mortality in six US cities N Engl J Med 3291753ndash1759 (1993)

2 Samet JM Dominici F Curriero FC Coursac I Zeger SL Fine particulate air pollution and mortality in 20 US cities 1987ndash1994 N Engl J Med 3431742ndash1749 (2000)

3 Nel AE Diaz-Sanchez D Li N The role of particulate pollutants in pulmonary inflammation and asthma evidence for the involvement of organic chemicals and oxidative stress Curr Opin Pulm Med 20017 20ndash26

4 Westerholm R Karl-Erik E Exhaust emissions from lightand heavy-duty vehicles chemical composition impact of exhaust after treatment and fuel parameters Environ Health Perspect 102(suppl 4)13ndash23 (1994)

5 Bascom R Bromberg P Costa D Delvin R Dockery D Frampton M Lambert W Samet J Speizer F Utell

6 Health effects of outdoor air pollution Am J Respir Crit Care Med 1533ndash50 (1996)

7 Chow JC Watson JG Frazier CA Egami RT Goodrich A Ralph C Spatial and temporal source contributions to

8 PM10 and PM25 in Reno NV In PM-10 Implementation of Standards Transactions An APCAEPA International Speciality Conference San Francisco CA (Mathal CV Stonefield DH eds) PittsburghAPCA 1988439ndash457

9 overview In Particulate Matter Health and Regulatory Issues VIP-49 Proceedings of an International Specialty Conference 4ndash6 April 1995 Pittsburgh PA PittsburghAir and Waste Management Association 1995577ndash598

10 Kunzli N Kaiser R Medina S Studnicka M Chanel O

11 Filliger P Herry M Horak F Jr Puybonnieux-Texier V Quenel P et al Public-health impact of outdoor and traffic- related air pollution a European assessment Lancet 356795ndash801 (2000)

Bibliography

1 Sioutas C Delfino RJ Singh M Exposure assessment for atmospheric ultrafine particles (UFP) and implications in epidemiological research Environ Health Perspect 2005113947ndash955

2 Mosleh M Blau PJ Dumitrescu D (2004) Characteristics and morphology of wear particles from laboratory testing of disc brake materials Wear 2561128ndash1134

3 Kuumlnzli N et al (2000) Public-health impact of outdoor and traffi c-related air pollution a European assessment Lancet 356(9232)795ndash801

4 Dora C Phillips M eds (2000) Transport environment and health Copenhagen WHO Regional Office for Europe (WHO Regional Publications European Series No 89 httpwwweurowhointdocumente72015pdf accessed 26 November 2004)

5 Westerholm R Karl-Erik E Exhaust emissions from lightand

6 heavy-duty vehicles chemical composition impact of exhaust after treatment and fuel parameters Environ Health Perspect 102(suppl 4)13ndash23 (1994)

7 Fauser Tjell Mosbaek pigegaard Quantification of tire-Tread particles using extractable Organic Zinc as a Tracer Rubber Chemistry and Technology 1999 969Table shows some literature estimates of the contribution of tire wear to PM10 in air (Panko et al 2013) Gustafsson M Blomqvist G Gudmundsson A Dahl A Swietlicki E Bohgard M Lindbom J Ljungman A

8 Chen Y Shah N Huggins FE and Huffman GP (2006) Microanalysis of Ambient Particles from Lexington Ky by Electron Microscopy Atmos Environ 40 651ndash663

9 Donaldson K Tran CL Jimenez LA Duffin R Newby DE and Mills N (2005) Combustion-derived Nanoparticles A Review of Their Toxicology Following Inhalation Exposure Part Fibre Toxicol 2 10ndash23

10 Su D Serafino A Muller JO Jentoft RE Schlogl R and Fiorito S (2008) Cytotoxicity and Inflammatory Potential of Soot Particles of Low-emission Diesel Engines Environ Sci Technol 42 1761ndash1765

11 Maier KL Alessandrini F Beck-Speier I Hofer TPJ Diabatґe S Bitterle E Stoger T and Jakob T (2008) Health Effects of Ambient Particulate Matter-Biological Mechanisms and Inflammatory Responses to in Vitroand in Vivo Particle Exposures Inhalation Toxicol 20 319ndash337

Page 18: Studies of Air Pollutants and their Impact on Respiratory and ...€¦ · Ascarate Park C37 Monitoring Station: The National Ambient Air Quality Standard (NAAQS) for PM 10 and 2.5

Geographic Domain Zip Code 79905 Urban Area (El Paso County)

Zip Codes 88021880278807288048 (Dona Ana County)

Urban road Delta Dr St 31o 45rsquo 5637- 106o 27rsquo 1212 10 miles

Cordova Bridge of the Americas 31o 45rsquo 4367- 106o 27rsquo 0506 15 miles

478 Highway interstate 31o 46rsquo 1326- 106o 27rsquo 0327 05 miles

110 Highway interstate 31o 46rsquo 1210- 106o 27rsquo 0066 10 miles

10 Interstate Gateway Blvd 31o 46rsquo 397- 106o 26rsquo 4769 05 miles

Chamizal Loop 478 31o 46rsquo 668- 106o 26rsquo 5456 05 miles

Alameda Loop 20 31o 46rsquo 1323- 106o 27rsquo 0328 10 miles

Paisano Dr St Patriot freeway

route 62

31o 46rsquo 0669- 106o 27rsquo 212 15 miles

St Piedras 31o 46rsquo 1326- 106o 27rsquo 0327 10 miles

Dona Ana County Miles

Interstate 25 32o 23rsquo 0561 -106 48

1054 32o 23rsquo 3434- -

106 48 1054 32o 23rsquo

5660 106 48 4314

50

Geographic domain To obtain the simulation mobile data from modelMOVES2010a was configurated the coordinates selected in the study areas

El Paso County

PM25 Estimation from Aerosol Optical Depth (AOD) using

satellites

We examined the relationship

between Aerosol Optical Depth

(AOD) estimated from satellite data

at 5 km spatial resolution and the

mass of fine particles le25 μm in

aerodynamic diameter (PM25)

monitored on the ground in El PdN

area PM25 data was recorded from

air quality monitoring Chamizal

station (TCEQ) on different periods

Our analysis shows a significant

positive association between AOD

and PM25

Time-series and scatter plots of AOD estimated PM25 and surface PM25

Analysis of the meteorological factors and synoptic conditions leading to a local high

ozone event episode June 12-21 2006

Meteorology plays a critical role in determining atmospheric ozone concentrations A good synoptic scale weather forecast is essential to accurately forecast tropospheric and surface ozone concentrations

Figure 1 The domain configuration and Landuse categories

resolution 25 km domainFigure 2 The Geopotential height at 500 mb Figure 3 depicts the 850 mb at a lower altitude The

white regions observed in the graph correspond to

mountainous areas

Figure 4 Temperature at 2m height

above surface at 22 UTC June 18 2006

36 km resolution

Performance Evaluation

01020304050

Ju

ne

137

130

0

190

0

10

0

Ju

ne

157

130

0

190

0

10

0

Ju

ne

187

130

0

190

0

10

0

Tem

pe

ratu

re (⁰C

)

Local time (Hrs)

C41 June 13-19 2006

WRF_temperature

(⁰C)

TCEQ_temperature

(⁰C)

01020304050

June1

37

100

0

130

0

160

0

190

0

220

0

10

0

40

0

June1

57

100

0

130

0

160

0

190

0

220

0

10

0

40

0

June1

87

100

0

130

0

160

0

190

0

220

0

10

0

40

0

Rel

ativ

e h

um

idit

y (

)

Local time (Hrs)

C41 June 13-19 2006

WRF_rh () TCEQ_relative humidity ()

0

5

10

15

20

June

137 10

13

16

19

22 1 4

June

157 10

13

16

19

22 1 4

June

187 10

13

16

19

22 1 4

Win

d s

pee

d (

ms

Local time(Hrs)

C12 June 13-192006

WRF_wind speed (ms) TCEQ_ wind speed (ms)

We evaluate the WRF modelrsquos performance

by comparing against corresponding

experimental TCEQ data and performing the

required statistical analysis

HYSPLIT Model

HYSPLIT was simulated and showed that the ozone is mostly transported to El Paso from north western and south western US and Mexican regions during the 72 hours duration of the simulation

0

20

40

60

80

100

1200

00

10

02

00

30

04

00

50

06

00

70

08

00

90

01

00

01

10

01

20

01

30

01

40

01

50

01

60

01

70

01

80

01

90

02

00

02

10

02

20

02

30

0

Ho

url

y o

zon

e [

pp

b]

0102030405060708090

00

01

00

20

03

00

40

05

00

60

07

00

80

09

00

10

00

11

00

12

00

13

00

14

00

15

00

16

00

17

00

18

00

19

00

20

00

21

00

22

00

23

00

Ho

url

y o

zon

e [

pp

b]

June 18th June 19th

Performance Evaluation

01020304050

Ju

ne

137

130

0

190

0

10

0

Ju

ne

157

130

0

190

0

10

0

Ju

ne

187

130

0

190

0

10

0

Tem

pe

ratu

re (⁰C

)

Local time (Hrs)

C41 June 13-19 2006

WRF_temperature

(⁰C)

TCEQ_temperature

(⁰C)

0

50

100

150

June1

37

100

0

130

0

160

0

190

0

220

0

10

0

40

0

June1

57

100

0

130

0

160

0

190

0

220

0

10

0

40

0

June1

87

100

0

130

0

160

0

190

0

220

0

10

0

40

0Ozo

ne

(pp

b)

Local time (Hrs)

C41 June 13-19 2006

CAMx_ozone (ppbV) TCEQ_ozone (ppb)

0

10

20

30

40

50

June1

37

100

0

130

0

160

0

190

0

220

0

10

0

40

0

June1

57

100

0

130

0

160

0

190

0

220

0

10

0

40

0

June1

87

100

0

130

0

160

0

190

0

220

0

10

0

40

0

Rel

ativ

e h

um

idit

y (

)

Local time (Hrs)

C41 June 13-19 2006

WRF_rh () TCEQ_relative humidity ()

0

5

10

15

20

June

137 10

13

16

19

22 1 4

June

157 10

13

16

19

22 1 4

June

187 10

13

16

19

22 1 4W

ind

sp

eed

(m

sLocal time(Hrs)

C12 June 13-192006

WRF_wind speed (ms) TCEQ_ wind speed (ms)

Methodology

Medical Data The data by weekly monthly and year for daily emergency room and hospital admission for the respiratory

infections (RD) and cardiovascular diseases (CVD) was extracted from hospitals records located in the El PdN

the system includes data on type of admission primary and secondary causes of admissionRESPIRATORY DISEASE

Bronquitis amp Chronic Bronchitis 466 - 4661 491 - 4919

Asthma 463 - 4939

Emphysema 492

Respiratory failure 51881

HEART DISEASE

Accute Myocardial Infarction 410

Coronary Athersclerosis 4140

Other Ischemic Heart Disease 411-4139 4141-4149

Cardiac Dyshythmias 427

Essential hypertension 401

Acute myocardial infarction 410

Congestive Heart Failure 4280 4282-4284

Hypertensive heart disease 402

Table 1 ICD -9 Codes for Respiratory and Cardiovascular Diseases

0

50

100

150

200

250

300

Wee

k 1

Wee

k 2

Wee

k 3

Wee

k 4

Wee

k 5

Wee

k 6

Wee

k 7

Wee

k 8

Wee

k 9

Wee

k 1

0

Wee

k 1

1

Wee

k 1

2

Wee

k 1

3

Wee

k 1

4

Wee

k 1

5

Wee

k 1

6

Wee

k 1

7

Wee

k 1

8

Wee

k 1

9

Wee

k 2

0

Wee

k 2

1

Mo

rb

idit

y D

isch

arg

e fo

r a

ll R

esp

ira

tory

Dis

ease

IC

D-9

(

Ast

hm

aB

ro

nch

itis

)

Weekly Morbidity Discharges of all the Listed Diagnoses for All

Respiratory Disease During WinterSpring 2010

Asthma-Bronchitis

EPA MOVES Model for Estimating Emission

Inventories

Motor Vehicle Emission Simulator (MOVES 2010b) will be configuredin The El Paso North Region for Calculate five categories of PM10

PM25 total Emission inventories from all on-road traffic over a

variety of scales within periods of time selected weeks months

and years

Moves (Motor Vehicle Emission

Simulator)

The emission model is develop using the current equation to calculate direct traffic emissions from

vehicles in the form of PM is

Eext annual emissions are measured in grams of miles traveled by the vehicle (gVMT )

SL is the road surface loading in (gm2)

W is the average weight in tons of the vehicles on the road

K is the particle size multiplier for particle size range (eg gVMT for PM10 when using grams and miles)

P is the 7 number of wet days with at least 0254 mm of precipitation during the averaging period

N is the number of years considered in the averaging period

C is the particle size specific emissions factor in units of interest vehicle direct exhaust brake wear and tirewear

Modeling Simulation Domain and Emissions Scenarios

For simulations of mobile air quality emission inventories a motor vehicle emission simulator EPA (MOVES 2014a) was used

The modeling use input factors divided into seven section

parameters

On-Road Inventory local data

input

Scale

Geographic Bounds

Traffic intensity

Vehicle Type

Pollutants

Road Type

Fuel Types

Figure Source EPA US Environmental Protection Agency 2012- Moves 2010b Model

EPA Moves 2014a The modeling used input factors divided into six section

parameters On-Road Inventory local data input

Geographic Domains CountyNonattainment Area

Vehicle-Miles Traveled (VMT) is the total number of miles driven by all vehicles withina given time period and geographic area

Average speed range from 25 miles per

hour to 65 miles per hour

Vehicle Classes Motorcycle PassengerCarTruks light-duty Commercial Truck(6001-8500 lbs) Buses heave-duty trucksRefuse trucks School Bus Single UnitShort Haul-truck Single Unit Long Haul-truck Long Haul Truck Heavy-DutyVehicles (26001-33000 lbs)

Pollutants

Road TypeRural restricted Acces(Freeways and interstates) Rural and Restricted Acces Urban Restricted Acces Off-Network

Fuel Types Gasoline Diesel Fuel

Specific Road Types

Two road types for running emission from the MOVES can be

selected

(freeways and interstates)

Interior urban Urban

Figure Source EPA US Environmental Protection Agency 2012- Moves 2010b Model

VehiclesEquipment

This panel show which on-road vehicles will be modeled

Figure Source EPA US Environmental Protection Agency 2012- Moves 2010b Model

Long haul truck Short haul truck Inercity bus Ligth comercial truck

Passenger car Passenger truck Refuse truck

School bus Single unit long haul-truck

Single unit short haul-truck

Transit bus

Motor home

Motorcycle

Based on Department of Transportation Highway MOVES will Estimates Traffic

Emissions from Cars Trucks amp Motorcycles

Output Data Moves 2014a

Inventories of PM 10 25 Mobile Emission from all

on-Road Traffic

Exhaust Emission PM 10 25 gramsmile

Brake Wear Emission PM 10 25 gramsmile

Tire wear Emission PM 10 25 gramsmile

Date of Vehicle miles traveled (VMT) for

Day Week Month Year

Total Vehicle population

Vehicle age distribution

Simulation of Mobile Emission in the El PdN Region Zip Code 79905

Figure Total Emissions from road traffic in El Paso TX Area were estimated for PM10

Exhaust and Non exhaust emission in kilogramsmonth (Source EPA MOVES 2014a)

0

10000

20000

30000

40000

50000

PM

10 k

gM

on

th

Months

Monthly PM 10 Exhaust and Non-Exhaust Mobile Emissions 2010

On-Road Urban Restricted Area Zip Code 79905

Primary Exhaust PM 10 (kg) Primary PM 10 Brakewear (kg)

Primary PM 10 Tirewear (kg)

05000

100001500020000250003000035000400004500050000

PM

25

kg

Mo

nth

Months

Monthly PM 25 Exhaust and Non-Exhaust Mobile Emission 2010

On-Road Urban Restricted Area Zip Code 79905

Primary Exhaust PM 25 (kg) Primary PM 25 Brakewear (kg) Primary PM 25Tirewear (kg)

Figure Total Emissions from road traffic in El Paso TX Area were estimated for PM25

Exhaust and Non exhaust emission in kilogramsmonth (Source EPA MOVES 2014a)

Total Emissions from Road Traffic in El Paso County PM1025 Exhaust and Non exhaust Emission in kilogramsmonth

Taking the interests to the health risks related to PM 1025 mobile emission were simulated

Exhaust and Non-exhaust emissions contribute almost equally to total traffic-related PM1025 Emissions (Querol et al 2004 Bukowiecki et al 2009a Amato et al 2011)

Monthly PM 10 25 Exhaust and Non-Exhaust (BrakewearTirewear) Mobile

Emission 2010 On-Road Urban Restricted Area Zip Code 79905

Figure Total Emissions from road traffic in El Paso TX Area were estimated for PM10 25 Exhaust and Non Exhaust mobile

emission in kilograms per month (Source EPA MOVES)

0

10000

20000

30000

40000

50000

January February March April May June July August September October November December

PM

10

25

(K

ilog

ram

s)

Months

Summary- Monthly PM 10 25 Exhaust and Non-Exhaust Mobile

Emission 2010 On-Road Urban Restricted Area Zip Code 79905

Primary Exhaust PM 10 Primary PM 10 Brakewear Primary PM 10 Tirewear

Primary Exhaust PM 25 Primary PM 25 Brakewear Primary PM 25Tirewear

Exhaust Emissions PM1025 is reaching maximum emission 48000-42000 thousand of Kgmonth followedby Brake wear 29000-5000 thousand kgmonth and Tire wear with 9000-2000 kgmonth The results showthat the emissions of PM derived mainly from Exhaust and Brake are significantly higher in Urban Area

Annual Contribution of Mobile Emission PM 1025 (Kg) Zip Code 79905 El

Paso County 2010

Total Primary

Exhaust _PM10

39

Total Primary

Exhaust _PM25

36

Brakewear

particulate_PM10

18

Tirewear

particulate_PM10

4

Brakewear

particulate_PM25

2

Tirewear

particulate_PM25

1

0

5

10

15

20

25

30

35

40

45

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53

Fig Annual Average PM10 Concentrations at the

Chamizal C41 Station and PM1025 mobile

Concentration Zip code 79905

PM10 TCEQ (μgm3) Total Mobile Emission PM10 (Ugm3)

Fig Exhaust Emission is Contributing Approximately 74 of total

PM1025 Mobile Emissions following of Brake wear with 20 and Tire

wear with 5

Annual Average PM1025 ugm3 Mobile Emissions (Moves) 26 Chamizal C41

Monitoring Station (TCEQ Chamizal Station )

Predicting Mobile Emission and VTM

Estimation The PdN Region 2010

44E+09

46E+09

48E+09

5E+09

52E+09

54E+09

56E+09

58E+09

6E+09

62E+09

0

50000

100000

150000

200000

250000

300000

350000

20

10

20

11

20

12

20

13

20

14

20

15

20

16

20

17

20

18

20

21

20

22

20

23

20

24

20

25

20

26

20

27

20

28

20

29

20

30

EX

HA

US

T

EM

ISS

ION

MO

BIL

E (

KG

YE

AR

)

YEARS

Predict ing Mobile Exhaust Emission and VTM

Estimation

2010 - 2030 e l PdN Area

Total_ Exhaust PM10 Total_ Exhaust PM25 Distance (Miles)

Fig Predicting Mobile Exhaust PM1025 (kgMonth) Emission and VTM Estimation 2010

- 2030 el PdN Area

44E+09

46E+09

48E+09

5E+09

52E+09

54E+09

56E+09

58E+09

6E+09

62E+09

0

5000000

10000000

15000000

20000000

25000000

30000000

20

10

20

11

20

12

20

13

20

14

20

15

20

16

20

17

20

18

20

21

20

22

20

23

20

24

20

25

20

26

20

27

20

28

20

29

20

30

EX

HA

US

T

EM

ISS

ION

MO

BIL

E (

KG

YE

AR

)

YEARS

Predict ing Mobile Exhaust Emission and

VTM Estimation

2010 - 2030 e l PdN Area

CO NO2 NO NOx Distance

Fig Predicting Mobile Exhaust Emission and VTM Estimation

2010 - 2030 el PdN Area in El Paso TX Area were estimated for

Total CO NOx NO2 NO emission in kilograms per year

(Source EPA MOVES 2014a model)

The simulated Exhaust emissions in the future years shows a trend of reduction of this type of emissions in the

future years one factor should be the new hybrid technology is increasing by 476 since 2010 to 2015 and

use of catalytic converters diesel particulate filters and improved fuels and engines Non-exhaustive sources

will increase in the coming years because there is no control in the material of manufacture composed by Fe

Cu and Mn also not to be able to reduce the number of events of braking (Accelerations and decelerations)

45E+09

5E+09

55E+09

6E+09

65E+09

0

50000

100000

150000

200000

250000

201

0

201

1

201

2

201

3

201

4

201

5

201

6

201

7

201

8

202

1

202

2

202

3

202

4

202

5

202

6

202

7

202

8

202

9

203

0

NO

N-

EX

HA

US

T

EM

ISS

ION

MO

BIL

E

(KG

YE

AR

)

YEARS

Predicting Non Exhaust Mobile

Emission and VTM Estimation

2010 - 2030 el PdN Area

Brake_PM10 Tire_PM10 Distance (Miles)

Fig Predicting Mobile Exhaust PM1025 (kgMonth) Emission and VTM

Estimation 2010 - 2030 el PdN Area

Daily Avg PM1025

Levels of PM Mobile Emission Non-Exhaust -Rush Hour Periods Fall 2010 Zip Code

79905

00

100

200

300

400

500

600

Mo

bil

e P

M1

0 (k

g)

Rush Hours

Daily Avg PM10

Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush Hours

Periods 2010 Zip Code 79905

Total Primary Exhaust

_PM10 WinterSpring

Brakewear

particulate_PM10

WinterSpringTirewear particulate_PM10

WinterSpring

Total Primary Exhaust

_PM10 Summer

Brakewear

particulate_PM10 Summer

Tirewear Particulate_PM10

Summer

Total Primary Exhaust

_PM10 Fall

Brakewear

particulate_PM10 Fall

Tirewear particulate_PM10

Fall

00

50

100

150

200

250

300

350

Mo

bil

e P

M2

5 (k

g)

Rush hours

Daily Avg PM25

Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush

Hours Periods 2010 Zip Code 79905

Total Primary Exhaust _PM25

WinterSpring

Brakewear Particulate_PM25

WinterSpring

Tirewear particulate_PM25

WinterSpring

Total Primary Exhaust _PM25

Summer

Brakewear particulate_PM25

Summer

Tirewear particulate_PM25

Summer

Total Primary Exhaust _PM25

Fall

Brakewear particulate_PM25

Fall

Tirewear particulate_PM25

Fall

Figure Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush Hours Figure Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush Hours

GIS EMISSIONS INVENTORY SYSTEM A geographic information system (GIS) was used to established geographic scenarios with processed images of seasonal mobile

emissions in the PdN region Seasonal mapping is visualized for different types of pollutants Brakewear Exhaust and Tyrewear

Fg Graphics of GIS and Seasonal mobile Emission of particulate matter emission inventory Seasonal emission simulations were performed in kilograms and five contributing inputs factors were identified for

modeling 1) On the composition of the particulate material from different sources such as Exhaust and Non exhaust (Brake wear Tirewear) 2) The Vehicles Equipment clasification were selected according to

the use of gasoline and diesel fuel (motorcycle passenger car Light Duty Vehicles Trucks refuse truck Light Duty Vehicles Light Commercial Truck Light Duty Vehicles School Bus)

Winter Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

120354 67860 19065

Spring Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

139767 86702 24463

Summer Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

94747 62481 17630

Fall Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

75510 45542 12596

251 Descriptive Statistics Data Analysis

Weekly Correlation Analysis of Mobile Emission PM10 (Exhaust-Non-Exhaust) and Respiratory

Diagnoses WinterSpring Summer and Fall 2010

0

2

4

6

8

10

0

50

100

150

200

250

300

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21

Mo

rbid

ity

Dis

ch

arg

e

for

all R

esp

ira

tory

Dis

ea

se

ICD

-9

(A

sth

ma

-Bro

nc

hitis

)

WinterSpring Week

Weekly Avg Mobile PM10 Concentrations during

WinterSpring 2010 and its Influence on Respiratory

Diagnoses

Zip Code 79905

Total Medical data ZIP Code 79902

Total Mobile Emission PM10 (Ugm3)

0

1

2

3

4

5

6

7

0

20

40

60

80

100

Mo

rbid

ity

Dis

ch

arg

e

for

all R

esp

ira

tory

Dis

ea

se

ICD

-9

(Ast

hm

aB

ron

ch

itis

)

Weekly Avg Mobile PM10 Concentrations during

Summer 2010 and its Influence on Respiratory

Diagnoses

Summer 2010 Zip Code 79905

Total Mobile Emission PM10

Hospital Admission (Asthma-Bronchitis)

0

2

4

6

8

10

12

0

20

40

60

80

100

120

140

160

180

200

Mo

rbid

ity

dis

ch

arg

es

for

all r

esp

ira

tory

dis

ea

se

Weekly Avg Mobile PM10 Concentrations

during Fall 2010 and its Influence on Respiratory

Diagnoses

Zip Code 79905

Total Medical data ZIP Code 79902

Total Mobile Emission PM10 (Ugm3)

Mobile(Exhaust-Non-

Exhaust) PM10 and

Asthma-Bronchitis)

Linear R

Square

WinterSpring 734 ndash 39

Summer 614 ndash 32

Fall 548 -29

PM10 Mobile emission (Exhaust-Non-Exhaust)contributed significantly

association to the incidence of RD

Weekly Correlation Analysis of PM 25 Mobile Emission (Exhaust-Non-Exhaust)

and Cardiovascular Diagnoses WinterSpring Summer and Fall 2010

0010203040

00500

100015002000

Wee

k 1

Wee

k 2

Wee

k 3

Wee

k 4

Wee

k 5

Wee

k 6

Wee

k 7

Wee

k 8

Wee

k 9

Wee

k 1

0

Wee

k 1

1

Wee

k 1

2

Wee

k 1

3

Wee

k 1

4

Wee

k 1

5

Wee

k 1

6

Wee

k 1

7

Wee

k 1

8

Wee

k 1

9

Wee

k 2

0

Wee

k 2

1

Morb

idit

y d

isch

arg

es f

or

all

card

iovasc

ula

r d

isea

se

Weekly Avg PM25 Mobile Concentrations during

WinterSpring 2010 and its Influence on all Heart

Diagnoses

Zip Code 79905

Total All Heart Disease PM 25 mobile (μgm3)

0010203040

00

500

1000

1500

Mo

rbid

ity

dis

ch

arg

es

for

all

ca

rdio

va

scu

lar

dis

ea

se

Weeks

CORRELATION BETWEEN MOBILE PM25 ugm3

EXPOSURE TO HEART DISEASES SYMPTOMS

SUMMER SEASON 2010

Total All Heart Disease PM 25 mobile (μgm3)

Figure Statistical Analyses of the Relationship Between PM25 Caused by Traffic Emission( 26 of total Emission) with Heart diseases Source Hospital Admissions for Asthma Acute Bronchitis and Heart diseases in El Paso County zip code 79905 from Texas Health Care

Information Council in Austin Texas (Texas Health Care Information Council 2000)

00

10

20

30

40

0

50

100

150

We

ek 3

6

We

ek 3

7

We

ek 3

8

We

ek 3

9

We

ek 4

0

We

ek 4

1

We

ek 4

2

We

ek 4

3

We

ek 4

4

We

ek 4

5

We

ek 4

6

We

ek 4

7

We

ek 4

8

We

ek 4

9

We

ek 5

0

We

ek 5

1

We

ek 5

2

We

ek 5

3

Mo

rbid

ity

dis

ch

arg

es

for

all

ca

rdio

va

scu

lar

dis

ea

se

CORRELATION BETWEEN MOBILE PM25 ugm3

EXPOSURE TO HEART DISEASES SYMPTOMS FALL

SEASON 2010

Total All Heart Disease PM 25 mobile (μgm3)

Mobile(Exhaust-

Non-Exhaust)

PM10 and

Asthma-

Bronchitis)

Linear R

Square

WinterSpring 833 -42

Summer 620 -32

Fall 501-26

PM10 Mobile

emission (Exhaust-

Non-

Exhaust)contribut

ed significantly

association to the

incidence of CVD

Diseases

Monthly Brake Mobile Emission PM1025 kg During year 2010 and its Influence on

Respiratory Diagnoses Zip Code 79905

00200040006000800010000

010000200003000040000

PM

10

Mo

bile

(K

g)

Months

Monthly Brake Mobile Emission PM10 kg during year

2010 and its Influence on Respiratory Diagnoses

Zip Code 79905

Primary PM 10

Brakewear 00100020003000400050006000

0

1000

2000

3000

4000

PM

25

Mo

bil

e(K

g)

Months

Monthly Brake Mobile Emission PM25 during

year 2010 and its Influence on Heart Diagnoses

Zip Code 79905

Primary PM 25

Brakewear

Heart Diseases

Hospital

Admission

Brake Mobile Emission

PM10 kg Asthma-

Bronchitis)

Brake Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=969 Linear Square R=856

Monthly Mobile Exhaust Emission PM1025 During year 2010 and its Influence on

Respiratory Diagnoses Zip Code 79905

0

200

400

600

800

1000

0

10000

20000

30000

40000

50000

1 3 5 7 9 11

PM

10

(K

g m

on

th)

Months

Monthly Mobile Exhaust Emission PM10 during

year 2010 and its Influence on Respiratory

Diagnoses

Zip Code 79905

Primary Exhaust

PM 10

Respiratory Disease

(Asthma

Bronchitis) Hospital

Admission

0

100

200

300

400

500

600

0

10000

20000

30000

40000

50000

1 2 3 4 5 6 7 8 9 101112

PM

25

(K

g m

on

th)

Months

Monthly Exhaust Mobile Emission PM25 during

year 2010 and its Influence on Heart Diagnoses

Zip Code 79905

Primary Exhaust PM

25

Heart Diseases

Hospital Admission

Exhaust Mobile Emission

PM10 kg Asthma-

Bronchitis)

Exhaust Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=929 Linear Square R=831

Monthly Tire wear Mobile Emission PM1025 During year 2010 and its Influence on Heart

Diagnoses Zip Code 79905

0

100

200

300

400

500

600

700

800

900

0

1000

2000

3000

4000

5000

6000

7000

8000

9000

1 2 3 4 5 6 7 8 9 10 11 12

PM

10

(K

g m

on

th)

Months

Monthly Tirewear Mobile Emission PM10 during year 2010

and its Influence on Heart Diagnoses

Zip Code 79905

Primary PM 10 Tirewear

Mobile Emission

Respiratory Disease

(Asthma Bronchitis)

Hospital Admission

0

100

200

300

400

500

600

0

200

400

600

800

1000

1200

1400

1 2 3 4 5 6 7 8 9 10 11 12

PM

25

(K

g m

on

th)

Months

Monthly Tirewear Mobile Emission PM25 during year 2010

and its Influence on Respiratory Diagnoses

Zip Code 79905

Primary PM 25Tirewear

Mobile Emission

Heart Diseases Hospital

Admission

Exhaust Mobile Emission

PM10 kg Asthma-

Bronchitis)

Exhaust Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=769 Linear Square R=715

Dona Ana County Zip Codes

88021880278807288048

Primary

Exhaust

PM 10 Zip

code

79905

Total

Primary

Exhaust

PM10

Dona Ana

Primary

Exhaust

PM 25 Zip

Code

79905

Total

Primary

Exhaust

PM25

Dona Ana

Series1 430378 111773 391915 102123

0

100000

200000

300000

400000

500000

AX

IS T

ITLE

Annual Comparison of the Mobile

Exhaust Emissions El Paso County

and Dona Ana 2010

Primary

PM 10

Brakewea

r Zip code

79905

Brakewea

r

particulat

e_PM10

Dona Ana

Primary

PM 10

Tirewear

Zip code

79905

Tirewear

particulat

e_PM10

Dona Ana

Series1 262585 48573 73754 11864

050000

100000150000200000250000300000

AX

IS T

ITLE

Annual Comparison of the Mobile

Brakewear Emissions El Paso County

and Dona Ana 2010

Figure Comparison of the Annual Mobile Emissions

of Primary PM10 Non-Exhauts (Brake ) from Dona

Ana County New Mexico and El Paso Texas Units

in KgMonth

Figure Comparison of the Annual Mobile Emissions

of Primary PM10-Exhauts Emission from Dona Ana

County New Mexico and El Paso Texas Units in

KgMonth

Primary

PM 25

Brakewe

ar Ziphellip

Brakewe

ar

particula

te_PMhellip

Primary

PM

25Tirewe

ar Ziphellip

Tirewear

particula

te_PM25

Donahellip

Series1 32645 6071 10919 1779

0

10000

20000

30000

40000

AX

IS T

ITLE

Annual Comparison of the

Mobile Exhaust Emissions El Paso

County and Dona Ana 2010

Figure Comparison of the Annual Mobile Emissions

of Primary PM10-Exhauts Emission from Dona Ana

County New Mexico and El Paso Texas Units in

KgMonth

Monthly Mobile Emission PM1025 kg During year 2006

and its Influence on Respiratory Diagnoses Dona Ana

County Zip Code 880218802788072

0

100

200

300

0

5000

10000

15000

Axi

s Ti

tle

Axis Title

Monthly Mobile Exhaust Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Total PrimaryMobile Exhaust_PM10

All Respiratory ICD-9 (AsthmaBronchitis)

050100150200250300

010002000300040005000

Axi

s Ti

tle

Axis Title

Monthly Mobile Brake Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Brakewearparticulate_PM10

All RespiratoryICD -9 (AsthmaBronchitis)

050100150200250300

0200400600800

10001200

Axi

s Ti

tle

Axis Title

Monthly Mobile Tirewear Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Tirewearparticulate_PM10

All Respiratory ICD -9 (AsthmaBronchitis)

Mobile Exhauts

Emission PM10

kg Asthma-

Bronchitis)

Brake Mobile

Emission PM10

kg and Heart

Diagnoses

Tirewear Mobile

Emission PM10

kg and Heart

Diagnoses

Linear Square

R= 951

Linear Square

R=625

Linear Square

R=525

Mobile Exhauts

Emission PM25

kg Asthma-

Bronchitis)

Brake Mobile

Emission PM25

kg and Heart

Diagnoses

Tirewear Mobile

Emission PM25

kg and Heart

Diagnoses

Linear Square

R= 986

Linear Square

R=691

Linear Square

R=601

Results

The results showed that mobile PM emissions in the urban areas close to urban Road and highways is putting at risk public health

and the proportion of diseases attributable to this exposure is potentially large

Brake wear emissions is much lower in freeways due to significantly reduced number of braking events while tire wear is much

higher in areas where studded tires are used The emission of exhaust gases are much higher in areas where there is a high

vehicular traffic

Brake Mobile

Emission PM10 kg

Asthma-Bronchitis)

Brake Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square

R=969

Linear Square

R=856

Exhaust Mobile

Emission PM10 kg

Asthma-Bronchitis)

Exhaust Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square

R=929

Linear Square

R=831

Tirewear Mobile

Emission PM10 kg

Asthma-Bronchitis)

Tirewear Mobile

Emission PM25 kg

and Heart Diagnoses

Linear Square R=769 Linear Square R=715

Brake Mobile

Emission PM10 kg

and Heart

Diagnoses

Brake Mobile

Emission PM25 kg

and Heart

Diagnoses

Exhaust Mobile

Emission PM10 kg

Asthma-Bronchitis)

Linear Square

R=625

Linear Square

R=691

Linear Square R=

951

Exhaust Mobile

Emission PM25 kg

Asthma-

Bronchitis)

Tire wear Mobile

Emission PM10 kg and

Heart Diagnoses

Tirewear Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square R=

986

Linear Square R=525 Linear Square

R=601

El Paso County

Dona Ana

County

BenMAP-CE

In this analysis the Program of Mapping and Analysis of Environmental Benefits-Community Edition

(BenMAP-CE) was used to Estimate the number and economic value of health impacts resulting from changes

in air pollution PM 25 Ugm3 in The El Paso Area

Health and Economic Benefits associated with the Response of PM25 Emission between

Base Year 2010

Number of Mortalities in 2010 Base Year Based on El Paso County Texas Department of State Health Services

Number of Mortalities in 2010 Base Year Based on El Paso County Texas

Department of State Health Services

cause of death

year

2010

Populatio

n

Affected

Backgro

und

Concentr

ation Pollutant

Rollback

Type

Avoided

Deaths

(

Populatio

n)

alzheimers disease 2010 40716 125 PM25

25

microgmAcircsup3

Rollback 9

diseases of the

heart 2010 15834 125 PM25

25

microgmAcircsup3

Rollback 35

influenza and

neumonia 2010 81432 125 PM25

25

microgmAcircsup3

Rollback 18

acute bronchitis

and bronchiolitis 2010 117624 125 PM25

25

microgmAcircsup3

Rollback 26

chronic lower

respiratory diseases 2010 54288 125 PM25

25

microgmAcircsup3

Rollback 12

The Basin-wide decrease in 4 ugm3 PM25 concentration after this

reduction control

Cause of death year 2010

Populatio

n

Affected

Background

Concentrati

on

Reduc

cion

scena

rio Polluta

nt

Rollback

Type

Avoi

ded

Deat

hs

(

Pop

ulati

on)

economic

benefits

analysis $

Alzheimers

disease 2010 121 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 9 12000

Diseases of the

heart 2010 470 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 35 35000

Influenza and

neumonia 2010 242 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 18 42500

Acute bronchitis

and bronchiolitis 2010 349 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 26 95000

Chronic lower

respiratory

diseases 2010 161 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 12 4500

$1 295000

PM25-related Mortalities Based on BenMAP-CE Estimate in 2010 Base Year with change in the concentrations levels

Health and Economic Benefits associated with the Response of PM25 Emission between

Base Year 2010 Increasing 7 Ugm3

Cause of death year 2010

Population

Affected

Deaths

avoided by

attaining 195

μgm3

standard

Background

Concentrati

on

Pollut

ant

Rollback

Type

Avoided

Deaths (

Populatio

n)

econo

mic

Unben

efits

analysi

s

Alzheimers

disease 2010 4524 195 PM25

25

microgmAcircsup3

Rollback 19 150000

Diseases of the

heart 2010 20358 195 PM25

25

microgmAcircsup3

Rollback 135 450000

Influenza and

neumonia 2010 126672 195 PM25

25

microgmAcircsup3

Rollback 38 525000

Acute bronchitis

and bronchiolitis 2010 162864 195 PM25

25

microgmAcircsup3

Rollback 36 122000

Chronic lower

respiratory

diseases 2010 99528 195 PM25

25

microgmAcircsup3

Rollback 12 650000

Conclusions

An excellent Pearson Correlation was established to analyze the relationship in the relative risks of hospitalization of Respiratory(RD) and cardiovascular (CVD) associated with ambient exposure caused by traffic emission in relation to their size andspecific sources of emission on different scenarios interior a border Urban Rural Urban restricted access (freeways andinterstates)

A significant correlation of PM1025 exposure from mobile emission and hospital admissions for selected Respiratory (RD) andcardiovascular (CVD) diagnoses was established The results showed that PM emissions in urban restricted access (freeways andinterstates) is mainly caused by traffic Therefore people living close to highways are more exposed higher vehicular emissions

Conclusions

We found statistically significant associations between mobile PM25 caused by traffic emission with Respiratory and Cardiovascular Diseases in the study areaSubsequently a correlation between cardio-respiratory mortality is established

A significant correlation of PM1025 exposure from mobile emission and hospital admissions for selected Respiratory (RD) and cardiovascular (CVD) diagnoses isestablished The results showed that PM emissions in urban restricted access (freeways and interstates) is mainly caused by traffic Therefore people living close tohighways receive higher vehicular emissions

The table shows the percentage of PM mobile exposure in the analyzed areas contributing to increase the risk of Respiratory and Cardiovascular Diseases

An examination was conducted of the synoptic and local meteorology for the June 2006 ozone episode using the WRF model to determine how meteorological parametersinfluence the formation transport and dispersion of ozone in the PdN The predominant synoptic feature of the ozone event day was the expansion intensification and slowprogression of an upper-level ridge of high pressure The high ozone episodes are associated with highly stable atmospheres strong temperature inversions with low mixingheights and therefore low mixing volumes Under these conditions emissions such as NOx lead to highly polluted conditions that favor ozone formation

BenMAP Conclusions

We have estimated the number and economic value of health impacts resulting

from changes in air pollution concentrations of PM 25 in the PdN region

Reduction of Pm 25 4 UGm3= Avoided 213 cases respiratory cardiovascular

diseses and Economic Benefits associated with the Response of PM25 Emission + $

1295000

Increase of PM25 7 ugm3 = increasing Dies= 326 economic Unbenefits= 2345000$

Bibliography

1 Dockery DW Pope CAI Xu X Spengler JD Ware JH Fay ME Ferris BG Speizer FE An association between air pollution and mortality in six US cities N Engl J Med 3291753ndash1759 (1993)

2 Samet JM Dominici F Curriero FC Coursac I Zeger SL Fine particulate air pollution and mortality in 20 US cities 1987ndash1994 N Engl J Med 3431742ndash1749 (2000)

3 Nel AE Diaz-Sanchez D Li N The role of particulate pollutants in pulmonary inflammation and asthma evidence for the involvement of organic chemicals and oxidative stress Curr Opin Pulm Med 20017 20ndash26

4 Westerholm R Karl-Erik E Exhaust emissions from lightand heavy-duty vehicles chemical composition impact of exhaust after treatment and fuel parameters Environ Health Perspect 102(suppl 4)13ndash23 (1994)

5 Bascom R Bromberg P Costa D Delvin R Dockery D Frampton M Lambert W Samet J Speizer F Utell

6 Health effects of outdoor air pollution Am J Respir Crit Care Med 1533ndash50 (1996)

7 Chow JC Watson JG Frazier CA Egami RT Goodrich A Ralph C Spatial and temporal source contributions to

8 PM10 and PM25 in Reno NV In PM-10 Implementation of Standards Transactions An APCAEPA International Speciality Conference San Francisco CA (Mathal CV Stonefield DH eds) PittsburghAPCA 1988439ndash457

9 overview In Particulate Matter Health and Regulatory Issues VIP-49 Proceedings of an International Specialty Conference 4ndash6 April 1995 Pittsburgh PA PittsburghAir and Waste Management Association 1995577ndash598

10 Kunzli N Kaiser R Medina S Studnicka M Chanel O

11 Filliger P Herry M Horak F Jr Puybonnieux-Texier V Quenel P et al Public-health impact of outdoor and traffic- related air pollution a European assessment Lancet 356795ndash801 (2000)

Bibliography

1 Sioutas C Delfino RJ Singh M Exposure assessment for atmospheric ultrafine particles (UFP) and implications in epidemiological research Environ Health Perspect 2005113947ndash955

2 Mosleh M Blau PJ Dumitrescu D (2004) Characteristics and morphology of wear particles from laboratory testing of disc brake materials Wear 2561128ndash1134

3 Kuumlnzli N et al (2000) Public-health impact of outdoor and traffi c-related air pollution a European assessment Lancet 356(9232)795ndash801

4 Dora C Phillips M eds (2000) Transport environment and health Copenhagen WHO Regional Office for Europe (WHO Regional Publications European Series No 89 httpwwweurowhointdocumente72015pdf accessed 26 November 2004)

5 Westerholm R Karl-Erik E Exhaust emissions from lightand

6 heavy-duty vehicles chemical composition impact of exhaust after treatment and fuel parameters Environ Health Perspect 102(suppl 4)13ndash23 (1994)

7 Fauser Tjell Mosbaek pigegaard Quantification of tire-Tread particles using extractable Organic Zinc as a Tracer Rubber Chemistry and Technology 1999 969Table shows some literature estimates of the contribution of tire wear to PM10 in air (Panko et al 2013) Gustafsson M Blomqvist G Gudmundsson A Dahl A Swietlicki E Bohgard M Lindbom J Ljungman A

8 Chen Y Shah N Huggins FE and Huffman GP (2006) Microanalysis of Ambient Particles from Lexington Ky by Electron Microscopy Atmos Environ 40 651ndash663

9 Donaldson K Tran CL Jimenez LA Duffin R Newby DE and Mills N (2005) Combustion-derived Nanoparticles A Review of Their Toxicology Following Inhalation Exposure Part Fibre Toxicol 2 10ndash23

10 Su D Serafino A Muller JO Jentoft RE Schlogl R and Fiorito S (2008) Cytotoxicity and Inflammatory Potential of Soot Particles of Low-emission Diesel Engines Environ Sci Technol 42 1761ndash1765

11 Maier KL Alessandrini F Beck-Speier I Hofer TPJ Diabatґe S Bitterle E Stoger T and Jakob T (2008) Health Effects of Ambient Particulate Matter-Biological Mechanisms and Inflammatory Responses to in Vitroand in Vivo Particle Exposures Inhalation Toxicol 20 319ndash337

Page 19: Studies of Air Pollutants and their Impact on Respiratory and ...€¦ · Ascarate Park C37 Monitoring Station: The National Ambient Air Quality Standard (NAAQS) for PM 10 and 2.5

PM25 Estimation from Aerosol Optical Depth (AOD) using

satellites

We examined the relationship

between Aerosol Optical Depth

(AOD) estimated from satellite data

at 5 km spatial resolution and the

mass of fine particles le25 μm in

aerodynamic diameter (PM25)

monitored on the ground in El PdN

area PM25 data was recorded from

air quality monitoring Chamizal

station (TCEQ) on different periods

Our analysis shows a significant

positive association between AOD

and PM25

Time-series and scatter plots of AOD estimated PM25 and surface PM25

Analysis of the meteorological factors and synoptic conditions leading to a local high

ozone event episode June 12-21 2006

Meteorology plays a critical role in determining atmospheric ozone concentrations A good synoptic scale weather forecast is essential to accurately forecast tropospheric and surface ozone concentrations

Figure 1 The domain configuration and Landuse categories

resolution 25 km domainFigure 2 The Geopotential height at 500 mb Figure 3 depicts the 850 mb at a lower altitude The

white regions observed in the graph correspond to

mountainous areas

Figure 4 Temperature at 2m height

above surface at 22 UTC June 18 2006

36 km resolution

Performance Evaluation

01020304050

Ju

ne

137

130

0

190

0

10

0

Ju

ne

157

130

0

190

0

10

0

Ju

ne

187

130

0

190

0

10

0

Tem

pe

ratu

re (⁰C

)

Local time (Hrs)

C41 June 13-19 2006

WRF_temperature

(⁰C)

TCEQ_temperature

(⁰C)

01020304050

June1

37

100

0

130

0

160

0

190

0

220

0

10

0

40

0

June1

57

100

0

130

0

160

0

190

0

220

0

10

0

40

0

June1

87

100

0

130

0

160

0

190

0

220

0

10

0

40

0

Rel

ativ

e h

um

idit

y (

)

Local time (Hrs)

C41 June 13-19 2006

WRF_rh () TCEQ_relative humidity ()

0

5

10

15

20

June

137 10

13

16

19

22 1 4

June

157 10

13

16

19

22 1 4

June

187 10

13

16

19

22 1 4

Win

d s

pee

d (

ms

Local time(Hrs)

C12 June 13-192006

WRF_wind speed (ms) TCEQ_ wind speed (ms)

We evaluate the WRF modelrsquos performance

by comparing against corresponding

experimental TCEQ data and performing the

required statistical analysis

HYSPLIT Model

HYSPLIT was simulated and showed that the ozone is mostly transported to El Paso from north western and south western US and Mexican regions during the 72 hours duration of the simulation

0

20

40

60

80

100

1200

00

10

02

00

30

04

00

50

06

00

70

08

00

90

01

00

01

10

01

20

01

30

01

40

01

50

01

60

01

70

01

80

01

90

02

00

02

10

02

20

02

30

0

Ho

url

y o

zon

e [

pp

b]

0102030405060708090

00

01

00

20

03

00

40

05

00

60

07

00

80

09

00

10

00

11

00

12

00

13

00

14

00

15

00

16

00

17

00

18

00

19

00

20

00

21

00

22

00

23

00

Ho

url

y o

zon

e [

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b]

June 18th June 19th

Performance Evaluation

01020304050

Ju

ne

137

130

0

190

0

10

0

Ju

ne

157

130

0

190

0

10

0

Ju

ne

187

130

0

190

0

10

0

Tem

pe

ratu

re (⁰C

)

Local time (Hrs)

C41 June 13-19 2006

WRF_temperature

(⁰C)

TCEQ_temperature

(⁰C)

0

50

100

150

June1

37

100

0

130

0

160

0

190

0

220

0

10

0

40

0

June1

57

100

0

130

0

160

0

190

0

220

0

10

0

40

0

June1

87

100

0

130

0

160

0

190

0

220

0

10

0

40

0Ozo

ne

(pp

b)

Local time (Hrs)

C41 June 13-19 2006

CAMx_ozone (ppbV) TCEQ_ozone (ppb)

0

10

20

30

40

50

June1

37

100

0

130

0

160

0

190

0

220

0

10

0

40

0

June1

57

100

0

130

0

160

0

190

0

220

0

10

0

40

0

June1

87

100

0

130

0

160

0

190

0

220

0

10

0

40

0

Rel

ativ

e h

um

idit

y (

)

Local time (Hrs)

C41 June 13-19 2006

WRF_rh () TCEQ_relative humidity ()

0

5

10

15

20

June

137 10

13

16

19

22 1 4

June

157 10

13

16

19

22 1 4

June

187 10

13

16

19

22 1 4W

ind

sp

eed

(m

sLocal time(Hrs)

C12 June 13-192006

WRF_wind speed (ms) TCEQ_ wind speed (ms)

Methodology

Medical Data The data by weekly monthly and year for daily emergency room and hospital admission for the respiratory

infections (RD) and cardiovascular diseases (CVD) was extracted from hospitals records located in the El PdN

the system includes data on type of admission primary and secondary causes of admissionRESPIRATORY DISEASE

Bronquitis amp Chronic Bronchitis 466 - 4661 491 - 4919

Asthma 463 - 4939

Emphysema 492

Respiratory failure 51881

HEART DISEASE

Accute Myocardial Infarction 410

Coronary Athersclerosis 4140

Other Ischemic Heart Disease 411-4139 4141-4149

Cardiac Dyshythmias 427

Essential hypertension 401

Acute myocardial infarction 410

Congestive Heart Failure 4280 4282-4284

Hypertensive heart disease 402

Table 1 ICD -9 Codes for Respiratory and Cardiovascular Diseases

0

50

100

150

200

250

300

Wee

k 1

Wee

k 2

Wee

k 3

Wee

k 4

Wee

k 5

Wee

k 6

Wee

k 7

Wee

k 8

Wee

k 9

Wee

k 1

0

Wee

k 1

1

Wee

k 1

2

Wee

k 1

3

Wee

k 1

4

Wee

k 1

5

Wee

k 1

6

Wee

k 1

7

Wee

k 1

8

Wee

k 1

9

Wee

k 2

0

Wee

k 2

1

Mo

rb

idit

y D

isch

arg

e fo

r a

ll R

esp

ira

tory

Dis

ease

IC

D-9

(

Ast

hm

aB

ro

nch

itis

)

Weekly Morbidity Discharges of all the Listed Diagnoses for All

Respiratory Disease During WinterSpring 2010

Asthma-Bronchitis

EPA MOVES Model for Estimating Emission

Inventories

Motor Vehicle Emission Simulator (MOVES 2010b) will be configuredin The El Paso North Region for Calculate five categories of PM10

PM25 total Emission inventories from all on-road traffic over a

variety of scales within periods of time selected weeks months

and years

Moves (Motor Vehicle Emission

Simulator)

The emission model is develop using the current equation to calculate direct traffic emissions from

vehicles in the form of PM is

Eext annual emissions are measured in grams of miles traveled by the vehicle (gVMT )

SL is the road surface loading in (gm2)

W is the average weight in tons of the vehicles on the road

K is the particle size multiplier for particle size range (eg gVMT for PM10 when using grams and miles)

P is the 7 number of wet days with at least 0254 mm of precipitation during the averaging period

N is the number of years considered in the averaging period

C is the particle size specific emissions factor in units of interest vehicle direct exhaust brake wear and tirewear

Modeling Simulation Domain and Emissions Scenarios

For simulations of mobile air quality emission inventories a motor vehicle emission simulator EPA (MOVES 2014a) was used

The modeling use input factors divided into seven section

parameters

On-Road Inventory local data

input

Scale

Geographic Bounds

Traffic intensity

Vehicle Type

Pollutants

Road Type

Fuel Types

Figure Source EPA US Environmental Protection Agency 2012- Moves 2010b Model

EPA Moves 2014a The modeling used input factors divided into six section

parameters On-Road Inventory local data input

Geographic Domains CountyNonattainment Area

Vehicle-Miles Traveled (VMT) is the total number of miles driven by all vehicles withina given time period and geographic area

Average speed range from 25 miles per

hour to 65 miles per hour

Vehicle Classes Motorcycle PassengerCarTruks light-duty Commercial Truck(6001-8500 lbs) Buses heave-duty trucksRefuse trucks School Bus Single UnitShort Haul-truck Single Unit Long Haul-truck Long Haul Truck Heavy-DutyVehicles (26001-33000 lbs)

Pollutants

Road TypeRural restricted Acces(Freeways and interstates) Rural and Restricted Acces Urban Restricted Acces Off-Network

Fuel Types Gasoline Diesel Fuel

Specific Road Types

Two road types for running emission from the MOVES can be

selected

(freeways and interstates)

Interior urban Urban

Figure Source EPA US Environmental Protection Agency 2012- Moves 2010b Model

VehiclesEquipment

This panel show which on-road vehicles will be modeled

Figure Source EPA US Environmental Protection Agency 2012- Moves 2010b Model

Long haul truck Short haul truck Inercity bus Ligth comercial truck

Passenger car Passenger truck Refuse truck

School bus Single unit long haul-truck

Single unit short haul-truck

Transit bus

Motor home

Motorcycle

Based on Department of Transportation Highway MOVES will Estimates Traffic

Emissions from Cars Trucks amp Motorcycles

Output Data Moves 2014a

Inventories of PM 10 25 Mobile Emission from all

on-Road Traffic

Exhaust Emission PM 10 25 gramsmile

Brake Wear Emission PM 10 25 gramsmile

Tire wear Emission PM 10 25 gramsmile

Date of Vehicle miles traveled (VMT) for

Day Week Month Year

Total Vehicle population

Vehicle age distribution

Simulation of Mobile Emission in the El PdN Region Zip Code 79905

Figure Total Emissions from road traffic in El Paso TX Area were estimated for PM10

Exhaust and Non exhaust emission in kilogramsmonth (Source EPA MOVES 2014a)

0

10000

20000

30000

40000

50000

PM

10 k

gM

on

th

Months

Monthly PM 10 Exhaust and Non-Exhaust Mobile Emissions 2010

On-Road Urban Restricted Area Zip Code 79905

Primary Exhaust PM 10 (kg) Primary PM 10 Brakewear (kg)

Primary PM 10 Tirewear (kg)

05000

100001500020000250003000035000400004500050000

PM

25

kg

Mo

nth

Months

Monthly PM 25 Exhaust and Non-Exhaust Mobile Emission 2010

On-Road Urban Restricted Area Zip Code 79905

Primary Exhaust PM 25 (kg) Primary PM 25 Brakewear (kg) Primary PM 25Tirewear (kg)

Figure Total Emissions from road traffic in El Paso TX Area were estimated for PM25

Exhaust and Non exhaust emission in kilogramsmonth (Source EPA MOVES 2014a)

Total Emissions from Road Traffic in El Paso County PM1025 Exhaust and Non exhaust Emission in kilogramsmonth

Taking the interests to the health risks related to PM 1025 mobile emission were simulated

Exhaust and Non-exhaust emissions contribute almost equally to total traffic-related PM1025 Emissions (Querol et al 2004 Bukowiecki et al 2009a Amato et al 2011)

Monthly PM 10 25 Exhaust and Non-Exhaust (BrakewearTirewear) Mobile

Emission 2010 On-Road Urban Restricted Area Zip Code 79905

Figure Total Emissions from road traffic in El Paso TX Area were estimated for PM10 25 Exhaust and Non Exhaust mobile

emission in kilograms per month (Source EPA MOVES)

0

10000

20000

30000

40000

50000

January February March April May June July August September October November December

PM

10

25

(K

ilog

ram

s)

Months

Summary- Monthly PM 10 25 Exhaust and Non-Exhaust Mobile

Emission 2010 On-Road Urban Restricted Area Zip Code 79905

Primary Exhaust PM 10 Primary PM 10 Brakewear Primary PM 10 Tirewear

Primary Exhaust PM 25 Primary PM 25 Brakewear Primary PM 25Tirewear

Exhaust Emissions PM1025 is reaching maximum emission 48000-42000 thousand of Kgmonth followedby Brake wear 29000-5000 thousand kgmonth and Tire wear with 9000-2000 kgmonth The results showthat the emissions of PM derived mainly from Exhaust and Brake are significantly higher in Urban Area

Annual Contribution of Mobile Emission PM 1025 (Kg) Zip Code 79905 El

Paso County 2010

Total Primary

Exhaust _PM10

39

Total Primary

Exhaust _PM25

36

Brakewear

particulate_PM10

18

Tirewear

particulate_PM10

4

Brakewear

particulate_PM25

2

Tirewear

particulate_PM25

1

0

5

10

15

20

25

30

35

40

45

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53

Fig Annual Average PM10 Concentrations at the

Chamizal C41 Station and PM1025 mobile

Concentration Zip code 79905

PM10 TCEQ (μgm3) Total Mobile Emission PM10 (Ugm3)

Fig Exhaust Emission is Contributing Approximately 74 of total

PM1025 Mobile Emissions following of Brake wear with 20 and Tire

wear with 5

Annual Average PM1025 ugm3 Mobile Emissions (Moves) 26 Chamizal C41

Monitoring Station (TCEQ Chamizal Station )

Predicting Mobile Emission and VTM

Estimation The PdN Region 2010

44E+09

46E+09

48E+09

5E+09

52E+09

54E+09

56E+09

58E+09

6E+09

62E+09

0

50000

100000

150000

200000

250000

300000

350000

20

10

20

11

20

12

20

13

20

14

20

15

20

16

20

17

20

18

20

21

20

22

20

23

20

24

20

25

20

26

20

27

20

28

20

29

20

30

EX

HA

US

T

EM

ISS

ION

MO

BIL

E (

KG

YE

AR

)

YEARS

Predict ing Mobile Exhaust Emission and VTM

Estimation

2010 - 2030 e l PdN Area

Total_ Exhaust PM10 Total_ Exhaust PM25 Distance (Miles)

Fig Predicting Mobile Exhaust PM1025 (kgMonth) Emission and VTM Estimation 2010

- 2030 el PdN Area

44E+09

46E+09

48E+09

5E+09

52E+09

54E+09

56E+09

58E+09

6E+09

62E+09

0

5000000

10000000

15000000

20000000

25000000

30000000

20

10

20

11

20

12

20

13

20

14

20

15

20

16

20

17

20

18

20

21

20

22

20

23

20

24

20

25

20

26

20

27

20

28

20

29

20

30

EX

HA

US

T

EM

ISS

ION

MO

BIL

E (

KG

YE

AR

)

YEARS

Predict ing Mobile Exhaust Emission and

VTM Estimation

2010 - 2030 e l PdN Area

CO NO2 NO NOx Distance

Fig Predicting Mobile Exhaust Emission and VTM Estimation

2010 - 2030 el PdN Area in El Paso TX Area were estimated for

Total CO NOx NO2 NO emission in kilograms per year

(Source EPA MOVES 2014a model)

The simulated Exhaust emissions in the future years shows a trend of reduction of this type of emissions in the

future years one factor should be the new hybrid technology is increasing by 476 since 2010 to 2015 and

use of catalytic converters diesel particulate filters and improved fuels and engines Non-exhaustive sources

will increase in the coming years because there is no control in the material of manufacture composed by Fe

Cu and Mn also not to be able to reduce the number of events of braking (Accelerations and decelerations)

45E+09

5E+09

55E+09

6E+09

65E+09

0

50000

100000

150000

200000

250000

201

0

201

1

201

2

201

3

201

4

201

5

201

6

201

7

201

8

202

1

202

2

202

3

202

4

202

5

202

6

202

7

202

8

202

9

203

0

NO

N-

EX

HA

US

T

EM

ISS

ION

MO

BIL

E

(KG

YE

AR

)

YEARS

Predicting Non Exhaust Mobile

Emission and VTM Estimation

2010 - 2030 el PdN Area

Brake_PM10 Tire_PM10 Distance (Miles)

Fig Predicting Mobile Exhaust PM1025 (kgMonth) Emission and VTM

Estimation 2010 - 2030 el PdN Area

Daily Avg PM1025

Levels of PM Mobile Emission Non-Exhaust -Rush Hour Periods Fall 2010 Zip Code

79905

00

100

200

300

400

500

600

Mo

bil

e P

M1

0 (k

g)

Rush Hours

Daily Avg PM10

Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush Hours

Periods 2010 Zip Code 79905

Total Primary Exhaust

_PM10 WinterSpring

Brakewear

particulate_PM10

WinterSpringTirewear particulate_PM10

WinterSpring

Total Primary Exhaust

_PM10 Summer

Brakewear

particulate_PM10 Summer

Tirewear Particulate_PM10

Summer

Total Primary Exhaust

_PM10 Fall

Brakewear

particulate_PM10 Fall

Tirewear particulate_PM10

Fall

00

50

100

150

200

250

300

350

Mo

bil

e P

M2

5 (k

g)

Rush hours

Daily Avg PM25

Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush

Hours Periods 2010 Zip Code 79905

Total Primary Exhaust _PM25

WinterSpring

Brakewear Particulate_PM25

WinterSpring

Tirewear particulate_PM25

WinterSpring

Total Primary Exhaust _PM25

Summer

Brakewear particulate_PM25

Summer

Tirewear particulate_PM25

Summer

Total Primary Exhaust _PM25

Fall

Brakewear particulate_PM25

Fall

Tirewear particulate_PM25

Fall

Figure Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush Hours Figure Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush Hours

GIS EMISSIONS INVENTORY SYSTEM A geographic information system (GIS) was used to established geographic scenarios with processed images of seasonal mobile

emissions in the PdN region Seasonal mapping is visualized for different types of pollutants Brakewear Exhaust and Tyrewear

Fg Graphics of GIS and Seasonal mobile Emission of particulate matter emission inventory Seasonal emission simulations were performed in kilograms and five contributing inputs factors were identified for

modeling 1) On the composition of the particulate material from different sources such as Exhaust and Non exhaust (Brake wear Tirewear) 2) The Vehicles Equipment clasification were selected according to

the use of gasoline and diesel fuel (motorcycle passenger car Light Duty Vehicles Trucks refuse truck Light Duty Vehicles Light Commercial Truck Light Duty Vehicles School Bus)

Winter Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

120354 67860 19065

Spring Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

139767 86702 24463

Summer Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

94747 62481 17630

Fall Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

75510 45542 12596

251 Descriptive Statistics Data Analysis

Weekly Correlation Analysis of Mobile Emission PM10 (Exhaust-Non-Exhaust) and Respiratory

Diagnoses WinterSpring Summer and Fall 2010

0

2

4

6

8

10

0

50

100

150

200

250

300

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21

Mo

rbid

ity

Dis

ch

arg

e

for

all R

esp

ira

tory

Dis

ea

se

ICD

-9

(A

sth

ma

-Bro

nc

hitis

)

WinterSpring Week

Weekly Avg Mobile PM10 Concentrations during

WinterSpring 2010 and its Influence on Respiratory

Diagnoses

Zip Code 79905

Total Medical data ZIP Code 79902

Total Mobile Emission PM10 (Ugm3)

0

1

2

3

4

5

6

7

0

20

40

60

80

100

Mo

rbid

ity

Dis

ch

arg

e

for

all R

esp

ira

tory

Dis

ea

se

ICD

-9

(Ast

hm

aB

ron

ch

itis

)

Weekly Avg Mobile PM10 Concentrations during

Summer 2010 and its Influence on Respiratory

Diagnoses

Summer 2010 Zip Code 79905

Total Mobile Emission PM10

Hospital Admission (Asthma-Bronchitis)

0

2

4

6

8

10

12

0

20

40

60

80

100

120

140

160

180

200

Mo

rbid

ity

dis

ch

arg

es

for

all r

esp

ira

tory

dis

ea

se

Weekly Avg Mobile PM10 Concentrations

during Fall 2010 and its Influence on Respiratory

Diagnoses

Zip Code 79905

Total Medical data ZIP Code 79902

Total Mobile Emission PM10 (Ugm3)

Mobile(Exhaust-Non-

Exhaust) PM10 and

Asthma-Bronchitis)

Linear R

Square

WinterSpring 734 ndash 39

Summer 614 ndash 32

Fall 548 -29

PM10 Mobile emission (Exhaust-Non-Exhaust)contributed significantly

association to the incidence of RD

Weekly Correlation Analysis of PM 25 Mobile Emission (Exhaust-Non-Exhaust)

and Cardiovascular Diagnoses WinterSpring Summer and Fall 2010

0010203040

00500

100015002000

Wee

k 1

Wee

k 2

Wee

k 3

Wee

k 4

Wee

k 5

Wee

k 6

Wee

k 7

Wee

k 8

Wee

k 9

Wee

k 1

0

Wee

k 1

1

Wee

k 1

2

Wee

k 1

3

Wee

k 1

4

Wee

k 1

5

Wee

k 1

6

Wee

k 1

7

Wee

k 1

8

Wee

k 1

9

Wee

k 2

0

Wee

k 2

1

Morb

idit

y d

isch

arg

es f

or

all

card

iovasc

ula

r d

isea

se

Weekly Avg PM25 Mobile Concentrations during

WinterSpring 2010 and its Influence on all Heart

Diagnoses

Zip Code 79905

Total All Heart Disease PM 25 mobile (μgm3)

0010203040

00

500

1000

1500

Mo

rbid

ity

dis

ch

arg

es

for

all

ca

rdio

va

scu

lar

dis

ea

se

Weeks

CORRELATION BETWEEN MOBILE PM25 ugm3

EXPOSURE TO HEART DISEASES SYMPTOMS

SUMMER SEASON 2010

Total All Heart Disease PM 25 mobile (μgm3)

Figure Statistical Analyses of the Relationship Between PM25 Caused by Traffic Emission( 26 of total Emission) with Heart diseases Source Hospital Admissions for Asthma Acute Bronchitis and Heart diseases in El Paso County zip code 79905 from Texas Health Care

Information Council in Austin Texas (Texas Health Care Information Council 2000)

00

10

20

30

40

0

50

100

150

We

ek 3

6

We

ek 3

7

We

ek 3

8

We

ek 3

9

We

ek 4

0

We

ek 4

1

We

ek 4

2

We

ek 4

3

We

ek 4

4

We

ek 4

5

We

ek 4

6

We

ek 4

7

We

ek 4

8

We

ek 4

9

We

ek 5

0

We

ek 5

1

We

ek 5

2

We

ek 5

3

Mo

rbid

ity

dis

ch

arg

es

for

all

ca

rdio

va

scu

lar

dis

ea

se

CORRELATION BETWEEN MOBILE PM25 ugm3

EXPOSURE TO HEART DISEASES SYMPTOMS FALL

SEASON 2010

Total All Heart Disease PM 25 mobile (μgm3)

Mobile(Exhaust-

Non-Exhaust)

PM10 and

Asthma-

Bronchitis)

Linear R

Square

WinterSpring 833 -42

Summer 620 -32

Fall 501-26

PM10 Mobile

emission (Exhaust-

Non-

Exhaust)contribut

ed significantly

association to the

incidence of CVD

Diseases

Monthly Brake Mobile Emission PM1025 kg During year 2010 and its Influence on

Respiratory Diagnoses Zip Code 79905

00200040006000800010000

010000200003000040000

PM

10

Mo

bile

(K

g)

Months

Monthly Brake Mobile Emission PM10 kg during year

2010 and its Influence on Respiratory Diagnoses

Zip Code 79905

Primary PM 10

Brakewear 00100020003000400050006000

0

1000

2000

3000

4000

PM

25

Mo

bil

e(K

g)

Months

Monthly Brake Mobile Emission PM25 during

year 2010 and its Influence on Heart Diagnoses

Zip Code 79905

Primary PM 25

Brakewear

Heart Diseases

Hospital

Admission

Brake Mobile Emission

PM10 kg Asthma-

Bronchitis)

Brake Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=969 Linear Square R=856

Monthly Mobile Exhaust Emission PM1025 During year 2010 and its Influence on

Respiratory Diagnoses Zip Code 79905

0

200

400

600

800

1000

0

10000

20000

30000

40000

50000

1 3 5 7 9 11

PM

10

(K

g m

on

th)

Months

Monthly Mobile Exhaust Emission PM10 during

year 2010 and its Influence on Respiratory

Diagnoses

Zip Code 79905

Primary Exhaust

PM 10

Respiratory Disease

(Asthma

Bronchitis) Hospital

Admission

0

100

200

300

400

500

600

0

10000

20000

30000

40000

50000

1 2 3 4 5 6 7 8 9 101112

PM

25

(K

g m

on

th)

Months

Monthly Exhaust Mobile Emission PM25 during

year 2010 and its Influence on Heart Diagnoses

Zip Code 79905

Primary Exhaust PM

25

Heart Diseases

Hospital Admission

Exhaust Mobile Emission

PM10 kg Asthma-

Bronchitis)

Exhaust Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=929 Linear Square R=831

Monthly Tire wear Mobile Emission PM1025 During year 2010 and its Influence on Heart

Diagnoses Zip Code 79905

0

100

200

300

400

500

600

700

800

900

0

1000

2000

3000

4000

5000

6000

7000

8000

9000

1 2 3 4 5 6 7 8 9 10 11 12

PM

10

(K

g m

on

th)

Months

Monthly Tirewear Mobile Emission PM10 during year 2010

and its Influence on Heart Diagnoses

Zip Code 79905

Primary PM 10 Tirewear

Mobile Emission

Respiratory Disease

(Asthma Bronchitis)

Hospital Admission

0

100

200

300

400

500

600

0

200

400

600

800

1000

1200

1400

1 2 3 4 5 6 7 8 9 10 11 12

PM

25

(K

g m

on

th)

Months

Monthly Tirewear Mobile Emission PM25 during year 2010

and its Influence on Respiratory Diagnoses

Zip Code 79905

Primary PM 25Tirewear

Mobile Emission

Heart Diseases Hospital

Admission

Exhaust Mobile Emission

PM10 kg Asthma-

Bronchitis)

Exhaust Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=769 Linear Square R=715

Dona Ana County Zip Codes

88021880278807288048

Primary

Exhaust

PM 10 Zip

code

79905

Total

Primary

Exhaust

PM10

Dona Ana

Primary

Exhaust

PM 25 Zip

Code

79905

Total

Primary

Exhaust

PM25

Dona Ana

Series1 430378 111773 391915 102123

0

100000

200000

300000

400000

500000

AX

IS T

ITLE

Annual Comparison of the Mobile

Exhaust Emissions El Paso County

and Dona Ana 2010

Primary

PM 10

Brakewea

r Zip code

79905

Brakewea

r

particulat

e_PM10

Dona Ana

Primary

PM 10

Tirewear

Zip code

79905

Tirewear

particulat

e_PM10

Dona Ana

Series1 262585 48573 73754 11864

050000

100000150000200000250000300000

AX

IS T

ITLE

Annual Comparison of the Mobile

Brakewear Emissions El Paso County

and Dona Ana 2010

Figure Comparison of the Annual Mobile Emissions

of Primary PM10 Non-Exhauts (Brake ) from Dona

Ana County New Mexico and El Paso Texas Units

in KgMonth

Figure Comparison of the Annual Mobile Emissions

of Primary PM10-Exhauts Emission from Dona Ana

County New Mexico and El Paso Texas Units in

KgMonth

Primary

PM 25

Brakewe

ar Ziphellip

Brakewe

ar

particula

te_PMhellip

Primary

PM

25Tirewe

ar Ziphellip

Tirewear

particula

te_PM25

Donahellip

Series1 32645 6071 10919 1779

0

10000

20000

30000

40000

AX

IS T

ITLE

Annual Comparison of the

Mobile Exhaust Emissions El Paso

County and Dona Ana 2010

Figure Comparison of the Annual Mobile Emissions

of Primary PM10-Exhauts Emission from Dona Ana

County New Mexico and El Paso Texas Units in

KgMonth

Monthly Mobile Emission PM1025 kg During year 2006

and its Influence on Respiratory Diagnoses Dona Ana

County Zip Code 880218802788072

0

100

200

300

0

5000

10000

15000

Axi

s Ti

tle

Axis Title

Monthly Mobile Exhaust Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Total PrimaryMobile Exhaust_PM10

All Respiratory ICD-9 (AsthmaBronchitis)

050100150200250300

010002000300040005000

Axi

s Ti

tle

Axis Title

Monthly Mobile Brake Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Brakewearparticulate_PM10

All RespiratoryICD -9 (AsthmaBronchitis)

050100150200250300

0200400600800

10001200

Axi

s Ti

tle

Axis Title

Monthly Mobile Tirewear Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Tirewearparticulate_PM10

All Respiratory ICD -9 (AsthmaBronchitis)

Mobile Exhauts

Emission PM10

kg Asthma-

Bronchitis)

Brake Mobile

Emission PM10

kg and Heart

Diagnoses

Tirewear Mobile

Emission PM10

kg and Heart

Diagnoses

Linear Square

R= 951

Linear Square

R=625

Linear Square

R=525

Mobile Exhauts

Emission PM25

kg Asthma-

Bronchitis)

Brake Mobile

Emission PM25

kg and Heart

Diagnoses

Tirewear Mobile

Emission PM25

kg and Heart

Diagnoses

Linear Square

R= 986

Linear Square

R=691

Linear Square

R=601

Results

The results showed that mobile PM emissions in the urban areas close to urban Road and highways is putting at risk public health

and the proportion of diseases attributable to this exposure is potentially large

Brake wear emissions is much lower in freeways due to significantly reduced number of braking events while tire wear is much

higher in areas where studded tires are used The emission of exhaust gases are much higher in areas where there is a high

vehicular traffic

Brake Mobile

Emission PM10 kg

Asthma-Bronchitis)

Brake Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square

R=969

Linear Square

R=856

Exhaust Mobile

Emission PM10 kg

Asthma-Bronchitis)

Exhaust Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square

R=929

Linear Square

R=831

Tirewear Mobile

Emission PM10 kg

Asthma-Bronchitis)

Tirewear Mobile

Emission PM25 kg

and Heart Diagnoses

Linear Square R=769 Linear Square R=715

Brake Mobile

Emission PM10 kg

and Heart

Diagnoses

Brake Mobile

Emission PM25 kg

and Heart

Diagnoses

Exhaust Mobile

Emission PM10 kg

Asthma-Bronchitis)

Linear Square

R=625

Linear Square

R=691

Linear Square R=

951

Exhaust Mobile

Emission PM25 kg

Asthma-

Bronchitis)

Tire wear Mobile

Emission PM10 kg and

Heart Diagnoses

Tirewear Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square R=

986

Linear Square R=525 Linear Square

R=601

El Paso County

Dona Ana

County

BenMAP-CE

In this analysis the Program of Mapping and Analysis of Environmental Benefits-Community Edition

(BenMAP-CE) was used to Estimate the number and economic value of health impacts resulting from changes

in air pollution PM 25 Ugm3 in The El Paso Area

Health and Economic Benefits associated with the Response of PM25 Emission between

Base Year 2010

Number of Mortalities in 2010 Base Year Based on El Paso County Texas Department of State Health Services

Number of Mortalities in 2010 Base Year Based on El Paso County Texas

Department of State Health Services

cause of death

year

2010

Populatio

n

Affected

Backgro

und

Concentr

ation Pollutant

Rollback

Type

Avoided

Deaths

(

Populatio

n)

alzheimers disease 2010 40716 125 PM25

25

microgmAcircsup3

Rollback 9

diseases of the

heart 2010 15834 125 PM25

25

microgmAcircsup3

Rollback 35

influenza and

neumonia 2010 81432 125 PM25

25

microgmAcircsup3

Rollback 18

acute bronchitis

and bronchiolitis 2010 117624 125 PM25

25

microgmAcircsup3

Rollback 26

chronic lower

respiratory diseases 2010 54288 125 PM25

25

microgmAcircsup3

Rollback 12

The Basin-wide decrease in 4 ugm3 PM25 concentration after this

reduction control

Cause of death year 2010

Populatio

n

Affected

Background

Concentrati

on

Reduc

cion

scena

rio Polluta

nt

Rollback

Type

Avoi

ded

Deat

hs

(

Pop

ulati

on)

economic

benefits

analysis $

Alzheimers

disease 2010 121 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 9 12000

Diseases of the

heart 2010 470 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 35 35000

Influenza and

neumonia 2010 242 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 18 42500

Acute bronchitis

and bronchiolitis 2010 349 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 26 95000

Chronic lower

respiratory

diseases 2010 161 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 12 4500

$1 295000

PM25-related Mortalities Based on BenMAP-CE Estimate in 2010 Base Year with change in the concentrations levels

Health and Economic Benefits associated with the Response of PM25 Emission between

Base Year 2010 Increasing 7 Ugm3

Cause of death year 2010

Population

Affected

Deaths

avoided by

attaining 195

μgm3

standard

Background

Concentrati

on

Pollut

ant

Rollback

Type

Avoided

Deaths (

Populatio

n)

econo

mic

Unben

efits

analysi

s

Alzheimers

disease 2010 4524 195 PM25

25

microgmAcircsup3

Rollback 19 150000

Diseases of the

heart 2010 20358 195 PM25

25

microgmAcircsup3

Rollback 135 450000

Influenza and

neumonia 2010 126672 195 PM25

25

microgmAcircsup3

Rollback 38 525000

Acute bronchitis

and bronchiolitis 2010 162864 195 PM25

25

microgmAcircsup3

Rollback 36 122000

Chronic lower

respiratory

diseases 2010 99528 195 PM25

25

microgmAcircsup3

Rollback 12 650000

Conclusions

An excellent Pearson Correlation was established to analyze the relationship in the relative risks of hospitalization of Respiratory(RD) and cardiovascular (CVD) associated with ambient exposure caused by traffic emission in relation to their size andspecific sources of emission on different scenarios interior a border Urban Rural Urban restricted access (freeways andinterstates)

A significant correlation of PM1025 exposure from mobile emission and hospital admissions for selected Respiratory (RD) andcardiovascular (CVD) diagnoses was established The results showed that PM emissions in urban restricted access (freeways andinterstates) is mainly caused by traffic Therefore people living close to highways are more exposed higher vehicular emissions

Conclusions

We found statistically significant associations between mobile PM25 caused by traffic emission with Respiratory and Cardiovascular Diseases in the study areaSubsequently a correlation between cardio-respiratory mortality is established

A significant correlation of PM1025 exposure from mobile emission and hospital admissions for selected Respiratory (RD) and cardiovascular (CVD) diagnoses isestablished The results showed that PM emissions in urban restricted access (freeways and interstates) is mainly caused by traffic Therefore people living close tohighways receive higher vehicular emissions

The table shows the percentage of PM mobile exposure in the analyzed areas contributing to increase the risk of Respiratory and Cardiovascular Diseases

An examination was conducted of the synoptic and local meteorology for the June 2006 ozone episode using the WRF model to determine how meteorological parametersinfluence the formation transport and dispersion of ozone in the PdN The predominant synoptic feature of the ozone event day was the expansion intensification and slowprogression of an upper-level ridge of high pressure The high ozone episodes are associated with highly stable atmospheres strong temperature inversions with low mixingheights and therefore low mixing volumes Under these conditions emissions such as NOx lead to highly polluted conditions that favor ozone formation

BenMAP Conclusions

We have estimated the number and economic value of health impacts resulting

from changes in air pollution concentrations of PM 25 in the PdN region

Reduction of Pm 25 4 UGm3= Avoided 213 cases respiratory cardiovascular

diseses and Economic Benefits associated with the Response of PM25 Emission + $

1295000

Increase of PM25 7 ugm3 = increasing Dies= 326 economic Unbenefits= 2345000$

Bibliography

1 Dockery DW Pope CAI Xu X Spengler JD Ware JH Fay ME Ferris BG Speizer FE An association between air pollution and mortality in six US cities N Engl J Med 3291753ndash1759 (1993)

2 Samet JM Dominici F Curriero FC Coursac I Zeger SL Fine particulate air pollution and mortality in 20 US cities 1987ndash1994 N Engl J Med 3431742ndash1749 (2000)

3 Nel AE Diaz-Sanchez D Li N The role of particulate pollutants in pulmonary inflammation and asthma evidence for the involvement of organic chemicals and oxidative stress Curr Opin Pulm Med 20017 20ndash26

4 Westerholm R Karl-Erik E Exhaust emissions from lightand heavy-duty vehicles chemical composition impact of exhaust after treatment and fuel parameters Environ Health Perspect 102(suppl 4)13ndash23 (1994)

5 Bascom R Bromberg P Costa D Delvin R Dockery D Frampton M Lambert W Samet J Speizer F Utell

6 Health effects of outdoor air pollution Am J Respir Crit Care Med 1533ndash50 (1996)

7 Chow JC Watson JG Frazier CA Egami RT Goodrich A Ralph C Spatial and temporal source contributions to

8 PM10 and PM25 in Reno NV In PM-10 Implementation of Standards Transactions An APCAEPA International Speciality Conference San Francisco CA (Mathal CV Stonefield DH eds) PittsburghAPCA 1988439ndash457

9 overview In Particulate Matter Health and Regulatory Issues VIP-49 Proceedings of an International Specialty Conference 4ndash6 April 1995 Pittsburgh PA PittsburghAir and Waste Management Association 1995577ndash598

10 Kunzli N Kaiser R Medina S Studnicka M Chanel O

11 Filliger P Herry M Horak F Jr Puybonnieux-Texier V Quenel P et al Public-health impact of outdoor and traffic- related air pollution a European assessment Lancet 356795ndash801 (2000)

Bibliography

1 Sioutas C Delfino RJ Singh M Exposure assessment for atmospheric ultrafine particles (UFP) and implications in epidemiological research Environ Health Perspect 2005113947ndash955

2 Mosleh M Blau PJ Dumitrescu D (2004) Characteristics and morphology of wear particles from laboratory testing of disc brake materials Wear 2561128ndash1134

3 Kuumlnzli N et al (2000) Public-health impact of outdoor and traffi c-related air pollution a European assessment Lancet 356(9232)795ndash801

4 Dora C Phillips M eds (2000) Transport environment and health Copenhagen WHO Regional Office for Europe (WHO Regional Publications European Series No 89 httpwwweurowhointdocumente72015pdf accessed 26 November 2004)

5 Westerholm R Karl-Erik E Exhaust emissions from lightand

6 heavy-duty vehicles chemical composition impact of exhaust after treatment and fuel parameters Environ Health Perspect 102(suppl 4)13ndash23 (1994)

7 Fauser Tjell Mosbaek pigegaard Quantification of tire-Tread particles using extractable Organic Zinc as a Tracer Rubber Chemistry and Technology 1999 969Table shows some literature estimates of the contribution of tire wear to PM10 in air (Panko et al 2013) Gustafsson M Blomqvist G Gudmundsson A Dahl A Swietlicki E Bohgard M Lindbom J Ljungman A

8 Chen Y Shah N Huggins FE and Huffman GP (2006) Microanalysis of Ambient Particles from Lexington Ky by Electron Microscopy Atmos Environ 40 651ndash663

9 Donaldson K Tran CL Jimenez LA Duffin R Newby DE and Mills N (2005) Combustion-derived Nanoparticles A Review of Their Toxicology Following Inhalation Exposure Part Fibre Toxicol 2 10ndash23

10 Su D Serafino A Muller JO Jentoft RE Schlogl R and Fiorito S (2008) Cytotoxicity and Inflammatory Potential of Soot Particles of Low-emission Diesel Engines Environ Sci Technol 42 1761ndash1765

11 Maier KL Alessandrini F Beck-Speier I Hofer TPJ Diabatґe S Bitterle E Stoger T and Jakob T (2008) Health Effects of Ambient Particulate Matter-Biological Mechanisms and Inflammatory Responses to in Vitroand in Vivo Particle Exposures Inhalation Toxicol 20 319ndash337

Page 20: Studies of Air Pollutants and their Impact on Respiratory and ...€¦ · Ascarate Park C37 Monitoring Station: The National Ambient Air Quality Standard (NAAQS) for PM 10 and 2.5

Analysis of the meteorological factors and synoptic conditions leading to a local high

ozone event episode June 12-21 2006

Meteorology plays a critical role in determining atmospheric ozone concentrations A good synoptic scale weather forecast is essential to accurately forecast tropospheric and surface ozone concentrations

Figure 1 The domain configuration and Landuse categories

resolution 25 km domainFigure 2 The Geopotential height at 500 mb Figure 3 depicts the 850 mb at a lower altitude The

white regions observed in the graph correspond to

mountainous areas

Figure 4 Temperature at 2m height

above surface at 22 UTC June 18 2006

36 km resolution

Performance Evaluation

01020304050

Ju

ne

137

130

0

190

0

10

0

Ju

ne

157

130

0

190

0

10

0

Ju

ne

187

130

0

190

0

10

0

Tem

pe

ratu

re (⁰C

)

Local time (Hrs)

C41 June 13-19 2006

WRF_temperature

(⁰C)

TCEQ_temperature

(⁰C)

01020304050

June1

37

100

0

130

0

160

0

190

0

220

0

10

0

40

0

June1

57

100

0

130

0

160

0

190

0

220

0

10

0

40

0

June1

87

100

0

130

0

160

0

190

0

220

0

10

0

40

0

Rel

ativ

e h

um

idit

y (

)

Local time (Hrs)

C41 June 13-19 2006

WRF_rh () TCEQ_relative humidity ()

0

5

10

15

20

June

137 10

13

16

19

22 1 4

June

157 10

13

16

19

22 1 4

June

187 10

13

16

19

22 1 4

Win

d s

pee

d (

ms

Local time(Hrs)

C12 June 13-192006

WRF_wind speed (ms) TCEQ_ wind speed (ms)

We evaluate the WRF modelrsquos performance

by comparing against corresponding

experimental TCEQ data and performing the

required statistical analysis

HYSPLIT Model

HYSPLIT was simulated and showed that the ozone is mostly transported to El Paso from north western and south western US and Mexican regions during the 72 hours duration of the simulation

0

20

40

60

80

100

1200

00

10

02

00

30

04

00

50

06

00

70

08

00

90

01

00

01

10

01

20

01

30

01

40

01

50

01

60

01

70

01

80

01

90

02

00

02

10

02

20

02

30

0

Ho

url

y o

zon

e [

pp

b]

0102030405060708090

00

01

00

20

03

00

40

05

00

60

07

00

80

09

00

10

00

11

00

12

00

13

00

14

00

15

00

16

00

17

00

18

00

19

00

20

00

21

00

22

00

23

00

Ho

url

y o

zon

e [

pp

b]

June 18th June 19th

Performance Evaluation

01020304050

Ju

ne

137

130

0

190

0

10

0

Ju

ne

157

130

0

190

0

10

0

Ju

ne

187

130

0

190

0

10

0

Tem

pe

ratu

re (⁰C

)

Local time (Hrs)

C41 June 13-19 2006

WRF_temperature

(⁰C)

TCEQ_temperature

(⁰C)

0

50

100

150

June1

37

100

0

130

0

160

0

190

0

220

0

10

0

40

0

June1

57

100

0

130

0

160

0

190

0

220

0

10

0

40

0

June1

87

100

0

130

0

160

0

190

0

220

0

10

0

40

0Ozo

ne

(pp

b)

Local time (Hrs)

C41 June 13-19 2006

CAMx_ozone (ppbV) TCEQ_ozone (ppb)

0

10

20

30

40

50

June1

37

100

0

130

0

160

0

190

0

220

0

10

0

40

0

June1

57

100

0

130

0

160

0

190

0

220

0

10

0

40

0

June1

87

100

0

130

0

160

0

190

0

220

0

10

0

40

0

Rel

ativ

e h

um

idit

y (

)

Local time (Hrs)

C41 June 13-19 2006

WRF_rh () TCEQ_relative humidity ()

0

5

10

15

20

June

137 10

13

16

19

22 1 4

June

157 10

13

16

19

22 1 4

June

187 10

13

16

19

22 1 4W

ind

sp

eed

(m

sLocal time(Hrs)

C12 June 13-192006

WRF_wind speed (ms) TCEQ_ wind speed (ms)

Methodology

Medical Data The data by weekly monthly and year for daily emergency room and hospital admission for the respiratory

infections (RD) and cardiovascular diseases (CVD) was extracted from hospitals records located in the El PdN

the system includes data on type of admission primary and secondary causes of admissionRESPIRATORY DISEASE

Bronquitis amp Chronic Bronchitis 466 - 4661 491 - 4919

Asthma 463 - 4939

Emphysema 492

Respiratory failure 51881

HEART DISEASE

Accute Myocardial Infarction 410

Coronary Athersclerosis 4140

Other Ischemic Heart Disease 411-4139 4141-4149

Cardiac Dyshythmias 427

Essential hypertension 401

Acute myocardial infarction 410

Congestive Heart Failure 4280 4282-4284

Hypertensive heart disease 402

Table 1 ICD -9 Codes for Respiratory and Cardiovascular Diseases

0

50

100

150

200

250

300

Wee

k 1

Wee

k 2

Wee

k 3

Wee

k 4

Wee

k 5

Wee

k 6

Wee

k 7

Wee

k 8

Wee

k 9

Wee

k 1

0

Wee

k 1

1

Wee

k 1

2

Wee

k 1

3

Wee

k 1

4

Wee

k 1

5

Wee

k 1

6

Wee

k 1

7

Wee

k 1

8

Wee

k 1

9

Wee

k 2

0

Wee

k 2

1

Mo

rb

idit

y D

isch

arg

e fo

r a

ll R

esp

ira

tory

Dis

ease

IC

D-9

(

Ast

hm

aB

ro

nch

itis

)

Weekly Morbidity Discharges of all the Listed Diagnoses for All

Respiratory Disease During WinterSpring 2010

Asthma-Bronchitis

EPA MOVES Model for Estimating Emission

Inventories

Motor Vehicle Emission Simulator (MOVES 2010b) will be configuredin The El Paso North Region for Calculate five categories of PM10

PM25 total Emission inventories from all on-road traffic over a

variety of scales within periods of time selected weeks months

and years

Moves (Motor Vehicle Emission

Simulator)

The emission model is develop using the current equation to calculate direct traffic emissions from

vehicles in the form of PM is

Eext annual emissions are measured in grams of miles traveled by the vehicle (gVMT )

SL is the road surface loading in (gm2)

W is the average weight in tons of the vehicles on the road

K is the particle size multiplier for particle size range (eg gVMT for PM10 when using grams and miles)

P is the 7 number of wet days with at least 0254 mm of precipitation during the averaging period

N is the number of years considered in the averaging period

C is the particle size specific emissions factor in units of interest vehicle direct exhaust brake wear and tirewear

Modeling Simulation Domain and Emissions Scenarios

For simulations of mobile air quality emission inventories a motor vehicle emission simulator EPA (MOVES 2014a) was used

The modeling use input factors divided into seven section

parameters

On-Road Inventory local data

input

Scale

Geographic Bounds

Traffic intensity

Vehicle Type

Pollutants

Road Type

Fuel Types

Figure Source EPA US Environmental Protection Agency 2012- Moves 2010b Model

EPA Moves 2014a The modeling used input factors divided into six section

parameters On-Road Inventory local data input

Geographic Domains CountyNonattainment Area

Vehicle-Miles Traveled (VMT) is the total number of miles driven by all vehicles withina given time period and geographic area

Average speed range from 25 miles per

hour to 65 miles per hour

Vehicle Classes Motorcycle PassengerCarTruks light-duty Commercial Truck(6001-8500 lbs) Buses heave-duty trucksRefuse trucks School Bus Single UnitShort Haul-truck Single Unit Long Haul-truck Long Haul Truck Heavy-DutyVehicles (26001-33000 lbs)

Pollutants

Road TypeRural restricted Acces(Freeways and interstates) Rural and Restricted Acces Urban Restricted Acces Off-Network

Fuel Types Gasoline Diesel Fuel

Specific Road Types

Two road types for running emission from the MOVES can be

selected

(freeways and interstates)

Interior urban Urban

Figure Source EPA US Environmental Protection Agency 2012- Moves 2010b Model

VehiclesEquipment

This panel show which on-road vehicles will be modeled

Figure Source EPA US Environmental Protection Agency 2012- Moves 2010b Model

Long haul truck Short haul truck Inercity bus Ligth comercial truck

Passenger car Passenger truck Refuse truck

School bus Single unit long haul-truck

Single unit short haul-truck

Transit bus

Motor home

Motorcycle

Based on Department of Transportation Highway MOVES will Estimates Traffic

Emissions from Cars Trucks amp Motorcycles

Output Data Moves 2014a

Inventories of PM 10 25 Mobile Emission from all

on-Road Traffic

Exhaust Emission PM 10 25 gramsmile

Brake Wear Emission PM 10 25 gramsmile

Tire wear Emission PM 10 25 gramsmile

Date of Vehicle miles traveled (VMT) for

Day Week Month Year

Total Vehicle population

Vehicle age distribution

Simulation of Mobile Emission in the El PdN Region Zip Code 79905

Figure Total Emissions from road traffic in El Paso TX Area were estimated for PM10

Exhaust and Non exhaust emission in kilogramsmonth (Source EPA MOVES 2014a)

0

10000

20000

30000

40000

50000

PM

10 k

gM

on

th

Months

Monthly PM 10 Exhaust and Non-Exhaust Mobile Emissions 2010

On-Road Urban Restricted Area Zip Code 79905

Primary Exhaust PM 10 (kg) Primary PM 10 Brakewear (kg)

Primary PM 10 Tirewear (kg)

05000

100001500020000250003000035000400004500050000

PM

25

kg

Mo

nth

Months

Monthly PM 25 Exhaust and Non-Exhaust Mobile Emission 2010

On-Road Urban Restricted Area Zip Code 79905

Primary Exhaust PM 25 (kg) Primary PM 25 Brakewear (kg) Primary PM 25Tirewear (kg)

Figure Total Emissions from road traffic in El Paso TX Area were estimated for PM25

Exhaust and Non exhaust emission in kilogramsmonth (Source EPA MOVES 2014a)

Total Emissions from Road Traffic in El Paso County PM1025 Exhaust and Non exhaust Emission in kilogramsmonth

Taking the interests to the health risks related to PM 1025 mobile emission were simulated

Exhaust and Non-exhaust emissions contribute almost equally to total traffic-related PM1025 Emissions (Querol et al 2004 Bukowiecki et al 2009a Amato et al 2011)

Monthly PM 10 25 Exhaust and Non-Exhaust (BrakewearTirewear) Mobile

Emission 2010 On-Road Urban Restricted Area Zip Code 79905

Figure Total Emissions from road traffic in El Paso TX Area were estimated for PM10 25 Exhaust and Non Exhaust mobile

emission in kilograms per month (Source EPA MOVES)

0

10000

20000

30000

40000

50000

January February March April May June July August September October November December

PM

10

25

(K

ilog

ram

s)

Months

Summary- Monthly PM 10 25 Exhaust and Non-Exhaust Mobile

Emission 2010 On-Road Urban Restricted Area Zip Code 79905

Primary Exhaust PM 10 Primary PM 10 Brakewear Primary PM 10 Tirewear

Primary Exhaust PM 25 Primary PM 25 Brakewear Primary PM 25Tirewear

Exhaust Emissions PM1025 is reaching maximum emission 48000-42000 thousand of Kgmonth followedby Brake wear 29000-5000 thousand kgmonth and Tire wear with 9000-2000 kgmonth The results showthat the emissions of PM derived mainly from Exhaust and Brake are significantly higher in Urban Area

Annual Contribution of Mobile Emission PM 1025 (Kg) Zip Code 79905 El

Paso County 2010

Total Primary

Exhaust _PM10

39

Total Primary

Exhaust _PM25

36

Brakewear

particulate_PM10

18

Tirewear

particulate_PM10

4

Brakewear

particulate_PM25

2

Tirewear

particulate_PM25

1

0

5

10

15

20

25

30

35

40

45

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53

Fig Annual Average PM10 Concentrations at the

Chamizal C41 Station and PM1025 mobile

Concentration Zip code 79905

PM10 TCEQ (μgm3) Total Mobile Emission PM10 (Ugm3)

Fig Exhaust Emission is Contributing Approximately 74 of total

PM1025 Mobile Emissions following of Brake wear with 20 and Tire

wear with 5

Annual Average PM1025 ugm3 Mobile Emissions (Moves) 26 Chamizal C41

Monitoring Station (TCEQ Chamizal Station )

Predicting Mobile Emission and VTM

Estimation The PdN Region 2010

44E+09

46E+09

48E+09

5E+09

52E+09

54E+09

56E+09

58E+09

6E+09

62E+09

0

50000

100000

150000

200000

250000

300000

350000

20

10

20

11

20

12

20

13

20

14

20

15

20

16

20

17

20

18

20

21

20

22

20

23

20

24

20

25

20

26

20

27

20

28

20

29

20

30

EX

HA

US

T

EM

ISS

ION

MO

BIL

E (

KG

YE

AR

)

YEARS

Predict ing Mobile Exhaust Emission and VTM

Estimation

2010 - 2030 e l PdN Area

Total_ Exhaust PM10 Total_ Exhaust PM25 Distance (Miles)

Fig Predicting Mobile Exhaust PM1025 (kgMonth) Emission and VTM Estimation 2010

- 2030 el PdN Area

44E+09

46E+09

48E+09

5E+09

52E+09

54E+09

56E+09

58E+09

6E+09

62E+09

0

5000000

10000000

15000000

20000000

25000000

30000000

20

10

20

11

20

12

20

13

20

14

20

15

20

16

20

17

20

18

20

21

20

22

20

23

20

24

20

25

20

26

20

27

20

28

20

29

20

30

EX

HA

US

T

EM

ISS

ION

MO

BIL

E (

KG

YE

AR

)

YEARS

Predict ing Mobile Exhaust Emission and

VTM Estimation

2010 - 2030 e l PdN Area

CO NO2 NO NOx Distance

Fig Predicting Mobile Exhaust Emission and VTM Estimation

2010 - 2030 el PdN Area in El Paso TX Area were estimated for

Total CO NOx NO2 NO emission in kilograms per year

(Source EPA MOVES 2014a model)

The simulated Exhaust emissions in the future years shows a trend of reduction of this type of emissions in the

future years one factor should be the new hybrid technology is increasing by 476 since 2010 to 2015 and

use of catalytic converters diesel particulate filters and improved fuels and engines Non-exhaustive sources

will increase in the coming years because there is no control in the material of manufacture composed by Fe

Cu and Mn also not to be able to reduce the number of events of braking (Accelerations and decelerations)

45E+09

5E+09

55E+09

6E+09

65E+09

0

50000

100000

150000

200000

250000

201

0

201

1

201

2

201

3

201

4

201

5

201

6

201

7

201

8

202

1

202

2

202

3

202

4

202

5

202

6

202

7

202

8

202

9

203

0

NO

N-

EX

HA

US

T

EM

ISS

ION

MO

BIL

E

(KG

YE

AR

)

YEARS

Predicting Non Exhaust Mobile

Emission and VTM Estimation

2010 - 2030 el PdN Area

Brake_PM10 Tire_PM10 Distance (Miles)

Fig Predicting Mobile Exhaust PM1025 (kgMonth) Emission and VTM

Estimation 2010 - 2030 el PdN Area

Daily Avg PM1025

Levels of PM Mobile Emission Non-Exhaust -Rush Hour Periods Fall 2010 Zip Code

79905

00

100

200

300

400

500

600

Mo

bil

e P

M1

0 (k

g)

Rush Hours

Daily Avg PM10

Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush Hours

Periods 2010 Zip Code 79905

Total Primary Exhaust

_PM10 WinterSpring

Brakewear

particulate_PM10

WinterSpringTirewear particulate_PM10

WinterSpring

Total Primary Exhaust

_PM10 Summer

Brakewear

particulate_PM10 Summer

Tirewear Particulate_PM10

Summer

Total Primary Exhaust

_PM10 Fall

Brakewear

particulate_PM10 Fall

Tirewear particulate_PM10

Fall

00

50

100

150

200

250

300

350

Mo

bil

e P

M2

5 (k

g)

Rush hours

Daily Avg PM25

Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush

Hours Periods 2010 Zip Code 79905

Total Primary Exhaust _PM25

WinterSpring

Brakewear Particulate_PM25

WinterSpring

Tirewear particulate_PM25

WinterSpring

Total Primary Exhaust _PM25

Summer

Brakewear particulate_PM25

Summer

Tirewear particulate_PM25

Summer

Total Primary Exhaust _PM25

Fall

Brakewear particulate_PM25

Fall

Tirewear particulate_PM25

Fall

Figure Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush Hours Figure Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush Hours

GIS EMISSIONS INVENTORY SYSTEM A geographic information system (GIS) was used to established geographic scenarios with processed images of seasonal mobile

emissions in the PdN region Seasonal mapping is visualized for different types of pollutants Brakewear Exhaust and Tyrewear

Fg Graphics of GIS and Seasonal mobile Emission of particulate matter emission inventory Seasonal emission simulations were performed in kilograms and five contributing inputs factors were identified for

modeling 1) On the composition of the particulate material from different sources such as Exhaust and Non exhaust (Brake wear Tirewear) 2) The Vehicles Equipment clasification were selected according to

the use of gasoline and diesel fuel (motorcycle passenger car Light Duty Vehicles Trucks refuse truck Light Duty Vehicles Light Commercial Truck Light Duty Vehicles School Bus)

Winter Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

120354 67860 19065

Spring Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

139767 86702 24463

Summer Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

94747 62481 17630

Fall Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

75510 45542 12596

251 Descriptive Statistics Data Analysis

Weekly Correlation Analysis of Mobile Emission PM10 (Exhaust-Non-Exhaust) and Respiratory

Diagnoses WinterSpring Summer and Fall 2010

0

2

4

6

8

10

0

50

100

150

200

250

300

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21

Mo

rbid

ity

Dis

ch

arg

e

for

all R

esp

ira

tory

Dis

ea

se

ICD

-9

(A

sth

ma

-Bro

nc

hitis

)

WinterSpring Week

Weekly Avg Mobile PM10 Concentrations during

WinterSpring 2010 and its Influence on Respiratory

Diagnoses

Zip Code 79905

Total Medical data ZIP Code 79902

Total Mobile Emission PM10 (Ugm3)

0

1

2

3

4

5

6

7

0

20

40

60

80

100

Mo

rbid

ity

Dis

ch

arg

e

for

all R

esp

ira

tory

Dis

ea

se

ICD

-9

(Ast

hm

aB

ron

ch

itis

)

Weekly Avg Mobile PM10 Concentrations during

Summer 2010 and its Influence on Respiratory

Diagnoses

Summer 2010 Zip Code 79905

Total Mobile Emission PM10

Hospital Admission (Asthma-Bronchitis)

0

2

4

6

8

10

12

0

20

40

60

80

100

120

140

160

180

200

Mo

rbid

ity

dis

ch

arg

es

for

all r

esp

ira

tory

dis

ea

se

Weekly Avg Mobile PM10 Concentrations

during Fall 2010 and its Influence on Respiratory

Diagnoses

Zip Code 79905

Total Medical data ZIP Code 79902

Total Mobile Emission PM10 (Ugm3)

Mobile(Exhaust-Non-

Exhaust) PM10 and

Asthma-Bronchitis)

Linear R

Square

WinterSpring 734 ndash 39

Summer 614 ndash 32

Fall 548 -29

PM10 Mobile emission (Exhaust-Non-Exhaust)contributed significantly

association to the incidence of RD

Weekly Correlation Analysis of PM 25 Mobile Emission (Exhaust-Non-Exhaust)

and Cardiovascular Diagnoses WinterSpring Summer and Fall 2010

0010203040

00500

100015002000

Wee

k 1

Wee

k 2

Wee

k 3

Wee

k 4

Wee

k 5

Wee

k 6

Wee

k 7

Wee

k 8

Wee

k 9

Wee

k 1

0

Wee

k 1

1

Wee

k 1

2

Wee

k 1

3

Wee

k 1

4

Wee

k 1

5

Wee

k 1

6

Wee

k 1

7

Wee

k 1

8

Wee

k 1

9

Wee

k 2

0

Wee

k 2

1

Morb

idit

y d

isch

arg

es f

or

all

card

iovasc

ula

r d

isea

se

Weekly Avg PM25 Mobile Concentrations during

WinterSpring 2010 and its Influence on all Heart

Diagnoses

Zip Code 79905

Total All Heart Disease PM 25 mobile (μgm3)

0010203040

00

500

1000

1500

Mo

rbid

ity

dis

ch

arg

es

for

all

ca

rdio

va

scu

lar

dis

ea

se

Weeks

CORRELATION BETWEEN MOBILE PM25 ugm3

EXPOSURE TO HEART DISEASES SYMPTOMS

SUMMER SEASON 2010

Total All Heart Disease PM 25 mobile (μgm3)

Figure Statistical Analyses of the Relationship Between PM25 Caused by Traffic Emission( 26 of total Emission) with Heart diseases Source Hospital Admissions for Asthma Acute Bronchitis and Heart diseases in El Paso County zip code 79905 from Texas Health Care

Information Council in Austin Texas (Texas Health Care Information Council 2000)

00

10

20

30

40

0

50

100

150

We

ek 3

6

We

ek 3

7

We

ek 3

8

We

ek 3

9

We

ek 4

0

We

ek 4

1

We

ek 4

2

We

ek 4

3

We

ek 4

4

We

ek 4

5

We

ek 4

6

We

ek 4

7

We

ek 4

8

We

ek 4

9

We

ek 5

0

We

ek 5

1

We

ek 5

2

We

ek 5

3

Mo

rbid

ity

dis

ch

arg

es

for

all

ca

rdio

va

scu

lar

dis

ea

se

CORRELATION BETWEEN MOBILE PM25 ugm3

EXPOSURE TO HEART DISEASES SYMPTOMS FALL

SEASON 2010

Total All Heart Disease PM 25 mobile (μgm3)

Mobile(Exhaust-

Non-Exhaust)

PM10 and

Asthma-

Bronchitis)

Linear R

Square

WinterSpring 833 -42

Summer 620 -32

Fall 501-26

PM10 Mobile

emission (Exhaust-

Non-

Exhaust)contribut

ed significantly

association to the

incidence of CVD

Diseases

Monthly Brake Mobile Emission PM1025 kg During year 2010 and its Influence on

Respiratory Diagnoses Zip Code 79905

00200040006000800010000

010000200003000040000

PM

10

Mo

bile

(K

g)

Months

Monthly Brake Mobile Emission PM10 kg during year

2010 and its Influence on Respiratory Diagnoses

Zip Code 79905

Primary PM 10

Brakewear 00100020003000400050006000

0

1000

2000

3000

4000

PM

25

Mo

bil

e(K

g)

Months

Monthly Brake Mobile Emission PM25 during

year 2010 and its Influence on Heart Diagnoses

Zip Code 79905

Primary PM 25

Brakewear

Heart Diseases

Hospital

Admission

Brake Mobile Emission

PM10 kg Asthma-

Bronchitis)

Brake Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=969 Linear Square R=856

Monthly Mobile Exhaust Emission PM1025 During year 2010 and its Influence on

Respiratory Diagnoses Zip Code 79905

0

200

400

600

800

1000

0

10000

20000

30000

40000

50000

1 3 5 7 9 11

PM

10

(K

g m

on

th)

Months

Monthly Mobile Exhaust Emission PM10 during

year 2010 and its Influence on Respiratory

Diagnoses

Zip Code 79905

Primary Exhaust

PM 10

Respiratory Disease

(Asthma

Bronchitis) Hospital

Admission

0

100

200

300

400

500

600

0

10000

20000

30000

40000

50000

1 2 3 4 5 6 7 8 9 101112

PM

25

(K

g m

on

th)

Months

Monthly Exhaust Mobile Emission PM25 during

year 2010 and its Influence on Heart Diagnoses

Zip Code 79905

Primary Exhaust PM

25

Heart Diseases

Hospital Admission

Exhaust Mobile Emission

PM10 kg Asthma-

Bronchitis)

Exhaust Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=929 Linear Square R=831

Monthly Tire wear Mobile Emission PM1025 During year 2010 and its Influence on Heart

Diagnoses Zip Code 79905

0

100

200

300

400

500

600

700

800

900

0

1000

2000

3000

4000

5000

6000

7000

8000

9000

1 2 3 4 5 6 7 8 9 10 11 12

PM

10

(K

g m

on

th)

Months

Monthly Tirewear Mobile Emission PM10 during year 2010

and its Influence on Heart Diagnoses

Zip Code 79905

Primary PM 10 Tirewear

Mobile Emission

Respiratory Disease

(Asthma Bronchitis)

Hospital Admission

0

100

200

300

400

500

600

0

200

400

600

800

1000

1200

1400

1 2 3 4 5 6 7 8 9 10 11 12

PM

25

(K

g m

on

th)

Months

Monthly Tirewear Mobile Emission PM25 during year 2010

and its Influence on Respiratory Diagnoses

Zip Code 79905

Primary PM 25Tirewear

Mobile Emission

Heart Diseases Hospital

Admission

Exhaust Mobile Emission

PM10 kg Asthma-

Bronchitis)

Exhaust Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=769 Linear Square R=715

Dona Ana County Zip Codes

88021880278807288048

Primary

Exhaust

PM 10 Zip

code

79905

Total

Primary

Exhaust

PM10

Dona Ana

Primary

Exhaust

PM 25 Zip

Code

79905

Total

Primary

Exhaust

PM25

Dona Ana

Series1 430378 111773 391915 102123

0

100000

200000

300000

400000

500000

AX

IS T

ITLE

Annual Comparison of the Mobile

Exhaust Emissions El Paso County

and Dona Ana 2010

Primary

PM 10

Brakewea

r Zip code

79905

Brakewea

r

particulat

e_PM10

Dona Ana

Primary

PM 10

Tirewear

Zip code

79905

Tirewear

particulat

e_PM10

Dona Ana

Series1 262585 48573 73754 11864

050000

100000150000200000250000300000

AX

IS T

ITLE

Annual Comparison of the Mobile

Brakewear Emissions El Paso County

and Dona Ana 2010

Figure Comparison of the Annual Mobile Emissions

of Primary PM10 Non-Exhauts (Brake ) from Dona

Ana County New Mexico and El Paso Texas Units

in KgMonth

Figure Comparison of the Annual Mobile Emissions

of Primary PM10-Exhauts Emission from Dona Ana

County New Mexico and El Paso Texas Units in

KgMonth

Primary

PM 25

Brakewe

ar Ziphellip

Brakewe

ar

particula

te_PMhellip

Primary

PM

25Tirewe

ar Ziphellip

Tirewear

particula

te_PM25

Donahellip

Series1 32645 6071 10919 1779

0

10000

20000

30000

40000

AX

IS T

ITLE

Annual Comparison of the

Mobile Exhaust Emissions El Paso

County and Dona Ana 2010

Figure Comparison of the Annual Mobile Emissions

of Primary PM10-Exhauts Emission from Dona Ana

County New Mexico and El Paso Texas Units in

KgMonth

Monthly Mobile Emission PM1025 kg During year 2006

and its Influence on Respiratory Diagnoses Dona Ana

County Zip Code 880218802788072

0

100

200

300

0

5000

10000

15000

Axi

s Ti

tle

Axis Title

Monthly Mobile Exhaust Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Total PrimaryMobile Exhaust_PM10

All Respiratory ICD-9 (AsthmaBronchitis)

050100150200250300

010002000300040005000

Axi

s Ti

tle

Axis Title

Monthly Mobile Brake Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Brakewearparticulate_PM10

All RespiratoryICD -9 (AsthmaBronchitis)

050100150200250300

0200400600800

10001200

Axi

s Ti

tle

Axis Title

Monthly Mobile Tirewear Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Tirewearparticulate_PM10

All Respiratory ICD -9 (AsthmaBronchitis)

Mobile Exhauts

Emission PM10

kg Asthma-

Bronchitis)

Brake Mobile

Emission PM10

kg and Heart

Diagnoses

Tirewear Mobile

Emission PM10

kg and Heart

Diagnoses

Linear Square

R= 951

Linear Square

R=625

Linear Square

R=525

Mobile Exhauts

Emission PM25

kg Asthma-

Bronchitis)

Brake Mobile

Emission PM25

kg and Heart

Diagnoses

Tirewear Mobile

Emission PM25

kg and Heart

Diagnoses

Linear Square

R= 986

Linear Square

R=691

Linear Square

R=601

Results

The results showed that mobile PM emissions in the urban areas close to urban Road and highways is putting at risk public health

and the proportion of diseases attributable to this exposure is potentially large

Brake wear emissions is much lower in freeways due to significantly reduced number of braking events while tire wear is much

higher in areas where studded tires are used The emission of exhaust gases are much higher in areas where there is a high

vehicular traffic

Brake Mobile

Emission PM10 kg

Asthma-Bronchitis)

Brake Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square

R=969

Linear Square

R=856

Exhaust Mobile

Emission PM10 kg

Asthma-Bronchitis)

Exhaust Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square

R=929

Linear Square

R=831

Tirewear Mobile

Emission PM10 kg

Asthma-Bronchitis)

Tirewear Mobile

Emission PM25 kg

and Heart Diagnoses

Linear Square R=769 Linear Square R=715

Brake Mobile

Emission PM10 kg

and Heart

Diagnoses

Brake Mobile

Emission PM25 kg

and Heart

Diagnoses

Exhaust Mobile

Emission PM10 kg

Asthma-Bronchitis)

Linear Square

R=625

Linear Square

R=691

Linear Square R=

951

Exhaust Mobile

Emission PM25 kg

Asthma-

Bronchitis)

Tire wear Mobile

Emission PM10 kg and

Heart Diagnoses

Tirewear Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square R=

986

Linear Square R=525 Linear Square

R=601

El Paso County

Dona Ana

County

BenMAP-CE

In this analysis the Program of Mapping and Analysis of Environmental Benefits-Community Edition

(BenMAP-CE) was used to Estimate the number and economic value of health impacts resulting from changes

in air pollution PM 25 Ugm3 in The El Paso Area

Health and Economic Benefits associated with the Response of PM25 Emission between

Base Year 2010

Number of Mortalities in 2010 Base Year Based on El Paso County Texas Department of State Health Services

Number of Mortalities in 2010 Base Year Based on El Paso County Texas

Department of State Health Services

cause of death

year

2010

Populatio

n

Affected

Backgro

und

Concentr

ation Pollutant

Rollback

Type

Avoided

Deaths

(

Populatio

n)

alzheimers disease 2010 40716 125 PM25

25

microgmAcircsup3

Rollback 9

diseases of the

heart 2010 15834 125 PM25

25

microgmAcircsup3

Rollback 35

influenza and

neumonia 2010 81432 125 PM25

25

microgmAcircsup3

Rollback 18

acute bronchitis

and bronchiolitis 2010 117624 125 PM25

25

microgmAcircsup3

Rollback 26

chronic lower

respiratory diseases 2010 54288 125 PM25

25

microgmAcircsup3

Rollback 12

The Basin-wide decrease in 4 ugm3 PM25 concentration after this

reduction control

Cause of death year 2010

Populatio

n

Affected

Background

Concentrati

on

Reduc

cion

scena

rio Polluta

nt

Rollback

Type

Avoi

ded

Deat

hs

(

Pop

ulati

on)

economic

benefits

analysis $

Alzheimers

disease 2010 121 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 9 12000

Diseases of the

heart 2010 470 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 35 35000

Influenza and

neumonia 2010 242 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 18 42500

Acute bronchitis

and bronchiolitis 2010 349 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 26 95000

Chronic lower

respiratory

diseases 2010 161 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 12 4500

$1 295000

PM25-related Mortalities Based on BenMAP-CE Estimate in 2010 Base Year with change in the concentrations levels

Health and Economic Benefits associated with the Response of PM25 Emission between

Base Year 2010 Increasing 7 Ugm3

Cause of death year 2010

Population

Affected

Deaths

avoided by

attaining 195

μgm3

standard

Background

Concentrati

on

Pollut

ant

Rollback

Type

Avoided

Deaths (

Populatio

n)

econo

mic

Unben

efits

analysi

s

Alzheimers

disease 2010 4524 195 PM25

25

microgmAcircsup3

Rollback 19 150000

Diseases of the

heart 2010 20358 195 PM25

25

microgmAcircsup3

Rollback 135 450000

Influenza and

neumonia 2010 126672 195 PM25

25

microgmAcircsup3

Rollback 38 525000

Acute bronchitis

and bronchiolitis 2010 162864 195 PM25

25

microgmAcircsup3

Rollback 36 122000

Chronic lower

respiratory

diseases 2010 99528 195 PM25

25

microgmAcircsup3

Rollback 12 650000

Conclusions

An excellent Pearson Correlation was established to analyze the relationship in the relative risks of hospitalization of Respiratory(RD) and cardiovascular (CVD) associated with ambient exposure caused by traffic emission in relation to their size andspecific sources of emission on different scenarios interior a border Urban Rural Urban restricted access (freeways andinterstates)

A significant correlation of PM1025 exposure from mobile emission and hospital admissions for selected Respiratory (RD) andcardiovascular (CVD) diagnoses was established The results showed that PM emissions in urban restricted access (freeways andinterstates) is mainly caused by traffic Therefore people living close to highways are more exposed higher vehicular emissions

Conclusions

We found statistically significant associations between mobile PM25 caused by traffic emission with Respiratory and Cardiovascular Diseases in the study areaSubsequently a correlation between cardio-respiratory mortality is established

A significant correlation of PM1025 exposure from mobile emission and hospital admissions for selected Respiratory (RD) and cardiovascular (CVD) diagnoses isestablished The results showed that PM emissions in urban restricted access (freeways and interstates) is mainly caused by traffic Therefore people living close tohighways receive higher vehicular emissions

The table shows the percentage of PM mobile exposure in the analyzed areas contributing to increase the risk of Respiratory and Cardiovascular Diseases

An examination was conducted of the synoptic and local meteorology for the June 2006 ozone episode using the WRF model to determine how meteorological parametersinfluence the formation transport and dispersion of ozone in the PdN The predominant synoptic feature of the ozone event day was the expansion intensification and slowprogression of an upper-level ridge of high pressure The high ozone episodes are associated with highly stable atmospheres strong temperature inversions with low mixingheights and therefore low mixing volumes Under these conditions emissions such as NOx lead to highly polluted conditions that favor ozone formation

BenMAP Conclusions

We have estimated the number and economic value of health impacts resulting

from changes in air pollution concentrations of PM 25 in the PdN region

Reduction of Pm 25 4 UGm3= Avoided 213 cases respiratory cardiovascular

diseses and Economic Benefits associated with the Response of PM25 Emission + $

1295000

Increase of PM25 7 ugm3 = increasing Dies= 326 economic Unbenefits= 2345000$

Bibliography

1 Dockery DW Pope CAI Xu X Spengler JD Ware JH Fay ME Ferris BG Speizer FE An association between air pollution and mortality in six US cities N Engl J Med 3291753ndash1759 (1993)

2 Samet JM Dominici F Curriero FC Coursac I Zeger SL Fine particulate air pollution and mortality in 20 US cities 1987ndash1994 N Engl J Med 3431742ndash1749 (2000)

3 Nel AE Diaz-Sanchez D Li N The role of particulate pollutants in pulmonary inflammation and asthma evidence for the involvement of organic chemicals and oxidative stress Curr Opin Pulm Med 20017 20ndash26

4 Westerholm R Karl-Erik E Exhaust emissions from lightand heavy-duty vehicles chemical composition impact of exhaust after treatment and fuel parameters Environ Health Perspect 102(suppl 4)13ndash23 (1994)

5 Bascom R Bromberg P Costa D Delvin R Dockery D Frampton M Lambert W Samet J Speizer F Utell

6 Health effects of outdoor air pollution Am J Respir Crit Care Med 1533ndash50 (1996)

7 Chow JC Watson JG Frazier CA Egami RT Goodrich A Ralph C Spatial and temporal source contributions to

8 PM10 and PM25 in Reno NV In PM-10 Implementation of Standards Transactions An APCAEPA International Speciality Conference San Francisco CA (Mathal CV Stonefield DH eds) PittsburghAPCA 1988439ndash457

9 overview In Particulate Matter Health and Regulatory Issues VIP-49 Proceedings of an International Specialty Conference 4ndash6 April 1995 Pittsburgh PA PittsburghAir and Waste Management Association 1995577ndash598

10 Kunzli N Kaiser R Medina S Studnicka M Chanel O

11 Filliger P Herry M Horak F Jr Puybonnieux-Texier V Quenel P et al Public-health impact of outdoor and traffic- related air pollution a European assessment Lancet 356795ndash801 (2000)

Bibliography

1 Sioutas C Delfino RJ Singh M Exposure assessment for atmospheric ultrafine particles (UFP) and implications in epidemiological research Environ Health Perspect 2005113947ndash955

2 Mosleh M Blau PJ Dumitrescu D (2004) Characteristics and morphology of wear particles from laboratory testing of disc brake materials Wear 2561128ndash1134

3 Kuumlnzli N et al (2000) Public-health impact of outdoor and traffi c-related air pollution a European assessment Lancet 356(9232)795ndash801

4 Dora C Phillips M eds (2000) Transport environment and health Copenhagen WHO Regional Office for Europe (WHO Regional Publications European Series No 89 httpwwweurowhointdocumente72015pdf accessed 26 November 2004)

5 Westerholm R Karl-Erik E Exhaust emissions from lightand

6 heavy-duty vehicles chemical composition impact of exhaust after treatment and fuel parameters Environ Health Perspect 102(suppl 4)13ndash23 (1994)

7 Fauser Tjell Mosbaek pigegaard Quantification of tire-Tread particles using extractable Organic Zinc as a Tracer Rubber Chemistry and Technology 1999 969Table shows some literature estimates of the contribution of tire wear to PM10 in air (Panko et al 2013) Gustafsson M Blomqvist G Gudmundsson A Dahl A Swietlicki E Bohgard M Lindbom J Ljungman A

8 Chen Y Shah N Huggins FE and Huffman GP (2006) Microanalysis of Ambient Particles from Lexington Ky by Electron Microscopy Atmos Environ 40 651ndash663

9 Donaldson K Tran CL Jimenez LA Duffin R Newby DE and Mills N (2005) Combustion-derived Nanoparticles A Review of Their Toxicology Following Inhalation Exposure Part Fibre Toxicol 2 10ndash23

10 Su D Serafino A Muller JO Jentoft RE Schlogl R and Fiorito S (2008) Cytotoxicity and Inflammatory Potential of Soot Particles of Low-emission Diesel Engines Environ Sci Technol 42 1761ndash1765

11 Maier KL Alessandrini F Beck-Speier I Hofer TPJ Diabatґe S Bitterle E Stoger T and Jakob T (2008) Health Effects of Ambient Particulate Matter-Biological Mechanisms and Inflammatory Responses to in Vitroand in Vivo Particle Exposures Inhalation Toxicol 20 319ndash337

Page 21: Studies of Air Pollutants and their Impact on Respiratory and ...€¦ · Ascarate Park C37 Monitoring Station: The National Ambient Air Quality Standard (NAAQS) for PM 10 and 2.5

Performance Evaluation

01020304050

Ju

ne

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ne

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Ju

ne

187

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10

0

Tem

pe

ratu

re (⁰C

)

Local time (Hrs)

C41 June 13-19 2006

WRF_temperature

(⁰C)

TCEQ_temperature

(⁰C)

01020304050

June1

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June1

87

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ativ

e h

um

idit

y (

)

Local time (Hrs)

C41 June 13-19 2006

WRF_rh () TCEQ_relative humidity ()

0

5

10

15

20

June

137 10

13

16

19

22 1 4

June

157 10

13

16

19

22 1 4

June

187 10

13

16

19

22 1 4

Win

d s

pee

d (

ms

Local time(Hrs)

C12 June 13-192006

WRF_wind speed (ms) TCEQ_ wind speed (ms)

We evaluate the WRF modelrsquos performance

by comparing against corresponding

experimental TCEQ data and performing the

required statistical analysis

HYSPLIT Model

HYSPLIT was simulated and showed that the ozone is mostly transported to El Paso from north western and south western US and Mexican regions during the 72 hours duration of the simulation

0

20

40

60

80

100

1200

00

10

02

00

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90

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Ho

url

y o

zon

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pp

b]

0102030405060708090

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60

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url

y o

zon

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pp

b]

June 18th June 19th

Performance Evaluation

01020304050

Ju

ne

137

130

0

190

0

10

0

Ju

ne

157

130

0

190

0

10

0

Ju

ne

187

130

0

190

0

10

0

Tem

pe

ratu

re (⁰C

)

Local time (Hrs)

C41 June 13-19 2006

WRF_temperature

(⁰C)

TCEQ_temperature

(⁰C)

0

50

100

150

June1

37

100

0

130

0

160

0

190

0

220

0

10

0

40

0

June1

57

100

0

130

0

160

0

190

0

220

0

10

0

40

0

June1

87

100

0

130

0

160

0

190

0

220

0

10

0

40

0Ozo

ne

(pp

b)

Local time (Hrs)

C41 June 13-19 2006

CAMx_ozone (ppbV) TCEQ_ozone (ppb)

0

10

20

30

40

50

June1

37

100

0

130

0

160

0

190

0

220

0

10

0

40

0

June1

57

100

0

130

0

160

0

190

0

220

0

10

0

40

0

June1

87

100

0

130

0

160

0

190

0

220

0

10

0

40

0

Rel

ativ

e h

um

idit

y (

)

Local time (Hrs)

C41 June 13-19 2006

WRF_rh () TCEQ_relative humidity ()

0

5

10

15

20

June

137 10

13

16

19

22 1 4

June

157 10

13

16

19

22 1 4

June

187 10

13

16

19

22 1 4W

ind

sp

eed

(m

sLocal time(Hrs)

C12 June 13-192006

WRF_wind speed (ms) TCEQ_ wind speed (ms)

Methodology

Medical Data The data by weekly monthly and year for daily emergency room and hospital admission for the respiratory

infections (RD) and cardiovascular diseases (CVD) was extracted from hospitals records located in the El PdN

the system includes data on type of admission primary and secondary causes of admissionRESPIRATORY DISEASE

Bronquitis amp Chronic Bronchitis 466 - 4661 491 - 4919

Asthma 463 - 4939

Emphysema 492

Respiratory failure 51881

HEART DISEASE

Accute Myocardial Infarction 410

Coronary Athersclerosis 4140

Other Ischemic Heart Disease 411-4139 4141-4149

Cardiac Dyshythmias 427

Essential hypertension 401

Acute myocardial infarction 410

Congestive Heart Failure 4280 4282-4284

Hypertensive heart disease 402

Table 1 ICD -9 Codes for Respiratory and Cardiovascular Diseases

0

50

100

150

200

250

300

Wee

k 1

Wee

k 2

Wee

k 3

Wee

k 4

Wee

k 5

Wee

k 6

Wee

k 7

Wee

k 8

Wee

k 9

Wee

k 1

0

Wee

k 1

1

Wee

k 1

2

Wee

k 1

3

Wee

k 1

4

Wee

k 1

5

Wee

k 1

6

Wee

k 1

7

Wee

k 1

8

Wee

k 1

9

Wee

k 2

0

Wee

k 2

1

Mo

rb

idit

y D

isch

arg

e fo

r a

ll R

esp

ira

tory

Dis

ease

IC

D-9

(

Ast

hm

aB

ro

nch

itis

)

Weekly Morbidity Discharges of all the Listed Diagnoses for All

Respiratory Disease During WinterSpring 2010

Asthma-Bronchitis

EPA MOVES Model for Estimating Emission

Inventories

Motor Vehicle Emission Simulator (MOVES 2010b) will be configuredin The El Paso North Region for Calculate five categories of PM10

PM25 total Emission inventories from all on-road traffic over a

variety of scales within periods of time selected weeks months

and years

Moves (Motor Vehicle Emission

Simulator)

The emission model is develop using the current equation to calculate direct traffic emissions from

vehicles in the form of PM is

Eext annual emissions are measured in grams of miles traveled by the vehicle (gVMT )

SL is the road surface loading in (gm2)

W is the average weight in tons of the vehicles on the road

K is the particle size multiplier for particle size range (eg gVMT for PM10 when using grams and miles)

P is the 7 number of wet days with at least 0254 mm of precipitation during the averaging period

N is the number of years considered in the averaging period

C is the particle size specific emissions factor in units of interest vehicle direct exhaust brake wear and tirewear

Modeling Simulation Domain and Emissions Scenarios

For simulations of mobile air quality emission inventories a motor vehicle emission simulator EPA (MOVES 2014a) was used

The modeling use input factors divided into seven section

parameters

On-Road Inventory local data

input

Scale

Geographic Bounds

Traffic intensity

Vehicle Type

Pollutants

Road Type

Fuel Types

Figure Source EPA US Environmental Protection Agency 2012- Moves 2010b Model

EPA Moves 2014a The modeling used input factors divided into six section

parameters On-Road Inventory local data input

Geographic Domains CountyNonattainment Area

Vehicle-Miles Traveled (VMT) is the total number of miles driven by all vehicles withina given time period and geographic area

Average speed range from 25 miles per

hour to 65 miles per hour

Vehicle Classes Motorcycle PassengerCarTruks light-duty Commercial Truck(6001-8500 lbs) Buses heave-duty trucksRefuse trucks School Bus Single UnitShort Haul-truck Single Unit Long Haul-truck Long Haul Truck Heavy-DutyVehicles (26001-33000 lbs)

Pollutants

Road TypeRural restricted Acces(Freeways and interstates) Rural and Restricted Acces Urban Restricted Acces Off-Network

Fuel Types Gasoline Diesel Fuel

Specific Road Types

Two road types for running emission from the MOVES can be

selected

(freeways and interstates)

Interior urban Urban

Figure Source EPA US Environmental Protection Agency 2012- Moves 2010b Model

VehiclesEquipment

This panel show which on-road vehicles will be modeled

Figure Source EPA US Environmental Protection Agency 2012- Moves 2010b Model

Long haul truck Short haul truck Inercity bus Ligth comercial truck

Passenger car Passenger truck Refuse truck

School bus Single unit long haul-truck

Single unit short haul-truck

Transit bus

Motor home

Motorcycle

Based on Department of Transportation Highway MOVES will Estimates Traffic

Emissions from Cars Trucks amp Motorcycles

Output Data Moves 2014a

Inventories of PM 10 25 Mobile Emission from all

on-Road Traffic

Exhaust Emission PM 10 25 gramsmile

Brake Wear Emission PM 10 25 gramsmile

Tire wear Emission PM 10 25 gramsmile

Date of Vehicle miles traveled (VMT) for

Day Week Month Year

Total Vehicle population

Vehicle age distribution

Simulation of Mobile Emission in the El PdN Region Zip Code 79905

Figure Total Emissions from road traffic in El Paso TX Area were estimated for PM10

Exhaust and Non exhaust emission in kilogramsmonth (Source EPA MOVES 2014a)

0

10000

20000

30000

40000

50000

PM

10 k

gM

on

th

Months

Monthly PM 10 Exhaust and Non-Exhaust Mobile Emissions 2010

On-Road Urban Restricted Area Zip Code 79905

Primary Exhaust PM 10 (kg) Primary PM 10 Brakewear (kg)

Primary PM 10 Tirewear (kg)

05000

100001500020000250003000035000400004500050000

PM

25

kg

Mo

nth

Months

Monthly PM 25 Exhaust and Non-Exhaust Mobile Emission 2010

On-Road Urban Restricted Area Zip Code 79905

Primary Exhaust PM 25 (kg) Primary PM 25 Brakewear (kg) Primary PM 25Tirewear (kg)

Figure Total Emissions from road traffic in El Paso TX Area were estimated for PM25

Exhaust and Non exhaust emission in kilogramsmonth (Source EPA MOVES 2014a)

Total Emissions from Road Traffic in El Paso County PM1025 Exhaust and Non exhaust Emission in kilogramsmonth

Taking the interests to the health risks related to PM 1025 mobile emission were simulated

Exhaust and Non-exhaust emissions contribute almost equally to total traffic-related PM1025 Emissions (Querol et al 2004 Bukowiecki et al 2009a Amato et al 2011)

Monthly PM 10 25 Exhaust and Non-Exhaust (BrakewearTirewear) Mobile

Emission 2010 On-Road Urban Restricted Area Zip Code 79905

Figure Total Emissions from road traffic in El Paso TX Area were estimated for PM10 25 Exhaust and Non Exhaust mobile

emission in kilograms per month (Source EPA MOVES)

0

10000

20000

30000

40000

50000

January February March April May June July August September October November December

PM

10

25

(K

ilog

ram

s)

Months

Summary- Monthly PM 10 25 Exhaust and Non-Exhaust Mobile

Emission 2010 On-Road Urban Restricted Area Zip Code 79905

Primary Exhaust PM 10 Primary PM 10 Brakewear Primary PM 10 Tirewear

Primary Exhaust PM 25 Primary PM 25 Brakewear Primary PM 25Tirewear

Exhaust Emissions PM1025 is reaching maximum emission 48000-42000 thousand of Kgmonth followedby Brake wear 29000-5000 thousand kgmonth and Tire wear with 9000-2000 kgmonth The results showthat the emissions of PM derived mainly from Exhaust and Brake are significantly higher in Urban Area

Annual Contribution of Mobile Emission PM 1025 (Kg) Zip Code 79905 El

Paso County 2010

Total Primary

Exhaust _PM10

39

Total Primary

Exhaust _PM25

36

Brakewear

particulate_PM10

18

Tirewear

particulate_PM10

4

Brakewear

particulate_PM25

2

Tirewear

particulate_PM25

1

0

5

10

15

20

25

30

35

40

45

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53

Fig Annual Average PM10 Concentrations at the

Chamizal C41 Station and PM1025 mobile

Concentration Zip code 79905

PM10 TCEQ (μgm3) Total Mobile Emission PM10 (Ugm3)

Fig Exhaust Emission is Contributing Approximately 74 of total

PM1025 Mobile Emissions following of Brake wear with 20 and Tire

wear with 5

Annual Average PM1025 ugm3 Mobile Emissions (Moves) 26 Chamizal C41

Monitoring Station (TCEQ Chamizal Station )

Predicting Mobile Emission and VTM

Estimation The PdN Region 2010

44E+09

46E+09

48E+09

5E+09

52E+09

54E+09

56E+09

58E+09

6E+09

62E+09

0

50000

100000

150000

200000

250000

300000

350000

20

10

20

11

20

12

20

13

20

14

20

15

20

16

20

17

20

18

20

21

20

22

20

23

20

24

20

25

20

26

20

27

20

28

20

29

20

30

EX

HA

US

T

EM

ISS

ION

MO

BIL

E (

KG

YE

AR

)

YEARS

Predict ing Mobile Exhaust Emission and VTM

Estimation

2010 - 2030 e l PdN Area

Total_ Exhaust PM10 Total_ Exhaust PM25 Distance (Miles)

Fig Predicting Mobile Exhaust PM1025 (kgMonth) Emission and VTM Estimation 2010

- 2030 el PdN Area

44E+09

46E+09

48E+09

5E+09

52E+09

54E+09

56E+09

58E+09

6E+09

62E+09

0

5000000

10000000

15000000

20000000

25000000

30000000

20

10

20

11

20

12

20

13

20

14

20

15

20

16

20

17

20

18

20

21

20

22

20

23

20

24

20

25

20

26

20

27

20

28

20

29

20

30

EX

HA

US

T

EM

ISS

ION

MO

BIL

E (

KG

YE

AR

)

YEARS

Predict ing Mobile Exhaust Emission and

VTM Estimation

2010 - 2030 e l PdN Area

CO NO2 NO NOx Distance

Fig Predicting Mobile Exhaust Emission and VTM Estimation

2010 - 2030 el PdN Area in El Paso TX Area were estimated for

Total CO NOx NO2 NO emission in kilograms per year

(Source EPA MOVES 2014a model)

The simulated Exhaust emissions in the future years shows a trend of reduction of this type of emissions in the

future years one factor should be the new hybrid technology is increasing by 476 since 2010 to 2015 and

use of catalytic converters diesel particulate filters and improved fuels and engines Non-exhaustive sources

will increase in the coming years because there is no control in the material of manufacture composed by Fe

Cu and Mn also not to be able to reduce the number of events of braking (Accelerations and decelerations)

45E+09

5E+09

55E+09

6E+09

65E+09

0

50000

100000

150000

200000

250000

201

0

201

1

201

2

201

3

201

4

201

5

201

6

201

7

201

8

202

1

202

2

202

3

202

4

202

5

202

6

202

7

202

8

202

9

203

0

NO

N-

EX

HA

US

T

EM

ISS

ION

MO

BIL

E

(KG

YE

AR

)

YEARS

Predicting Non Exhaust Mobile

Emission and VTM Estimation

2010 - 2030 el PdN Area

Brake_PM10 Tire_PM10 Distance (Miles)

Fig Predicting Mobile Exhaust PM1025 (kgMonth) Emission and VTM

Estimation 2010 - 2030 el PdN Area

Daily Avg PM1025

Levels of PM Mobile Emission Non-Exhaust -Rush Hour Periods Fall 2010 Zip Code

79905

00

100

200

300

400

500

600

Mo

bil

e P

M1

0 (k

g)

Rush Hours

Daily Avg PM10

Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush Hours

Periods 2010 Zip Code 79905

Total Primary Exhaust

_PM10 WinterSpring

Brakewear

particulate_PM10

WinterSpringTirewear particulate_PM10

WinterSpring

Total Primary Exhaust

_PM10 Summer

Brakewear

particulate_PM10 Summer

Tirewear Particulate_PM10

Summer

Total Primary Exhaust

_PM10 Fall

Brakewear

particulate_PM10 Fall

Tirewear particulate_PM10

Fall

00

50

100

150

200

250

300

350

Mo

bil

e P

M2

5 (k

g)

Rush hours

Daily Avg PM25

Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush

Hours Periods 2010 Zip Code 79905

Total Primary Exhaust _PM25

WinterSpring

Brakewear Particulate_PM25

WinterSpring

Tirewear particulate_PM25

WinterSpring

Total Primary Exhaust _PM25

Summer

Brakewear particulate_PM25

Summer

Tirewear particulate_PM25

Summer

Total Primary Exhaust _PM25

Fall

Brakewear particulate_PM25

Fall

Tirewear particulate_PM25

Fall

Figure Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush Hours Figure Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush Hours

GIS EMISSIONS INVENTORY SYSTEM A geographic information system (GIS) was used to established geographic scenarios with processed images of seasonal mobile

emissions in the PdN region Seasonal mapping is visualized for different types of pollutants Brakewear Exhaust and Tyrewear

Fg Graphics of GIS and Seasonal mobile Emission of particulate matter emission inventory Seasonal emission simulations were performed in kilograms and five contributing inputs factors were identified for

modeling 1) On the composition of the particulate material from different sources such as Exhaust and Non exhaust (Brake wear Tirewear) 2) The Vehicles Equipment clasification were selected according to

the use of gasoline and diesel fuel (motorcycle passenger car Light Duty Vehicles Trucks refuse truck Light Duty Vehicles Light Commercial Truck Light Duty Vehicles School Bus)

Winter Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

120354 67860 19065

Spring Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

139767 86702 24463

Summer Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

94747 62481 17630

Fall Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

75510 45542 12596

251 Descriptive Statistics Data Analysis

Weekly Correlation Analysis of Mobile Emission PM10 (Exhaust-Non-Exhaust) and Respiratory

Diagnoses WinterSpring Summer and Fall 2010

0

2

4

6

8

10

0

50

100

150

200

250

300

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21

Mo

rbid

ity

Dis

ch

arg

e

for

all R

esp

ira

tory

Dis

ea

se

ICD

-9

(A

sth

ma

-Bro

nc

hitis

)

WinterSpring Week

Weekly Avg Mobile PM10 Concentrations during

WinterSpring 2010 and its Influence on Respiratory

Diagnoses

Zip Code 79905

Total Medical data ZIP Code 79902

Total Mobile Emission PM10 (Ugm3)

0

1

2

3

4

5

6

7

0

20

40

60

80

100

Mo

rbid

ity

Dis

ch

arg

e

for

all R

esp

ira

tory

Dis

ea

se

ICD

-9

(Ast

hm

aB

ron

ch

itis

)

Weekly Avg Mobile PM10 Concentrations during

Summer 2010 and its Influence on Respiratory

Diagnoses

Summer 2010 Zip Code 79905

Total Mobile Emission PM10

Hospital Admission (Asthma-Bronchitis)

0

2

4

6

8

10

12

0

20

40

60

80

100

120

140

160

180

200

Mo

rbid

ity

dis

ch

arg

es

for

all r

esp

ira

tory

dis

ea

se

Weekly Avg Mobile PM10 Concentrations

during Fall 2010 and its Influence on Respiratory

Diagnoses

Zip Code 79905

Total Medical data ZIP Code 79902

Total Mobile Emission PM10 (Ugm3)

Mobile(Exhaust-Non-

Exhaust) PM10 and

Asthma-Bronchitis)

Linear R

Square

WinterSpring 734 ndash 39

Summer 614 ndash 32

Fall 548 -29

PM10 Mobile emission (Exhaust-Non-Exhaust)contributed significantly

association to the incidence of RD

Weekly Correlation Analysis of PM 25 Mobile Emission (Exhaust-Non-Exhaust)

and Cardiovascular Diagnoses WinterSpring Summer and Fall 2010

0010203040

00500

100015002000

Wee

k 1

Wee

k 2

Wee

k 3

Wee

k 4

Wee

k 5

Wee

k 6

Wee

k 7

Wee

k 8

Wee

k 9

Wee

k 1

0

Wee

k 1

1

Wee

k 1

2

Wee

k 1

3

Wee

k 1

4

Wee

k 1

5

Wee

k 1

6

Wee

k 1

7

Wee

k 1

8

Wee

k 1

9

Wee

k 2

0

Wee

k 2

1

Morb

idit

y d

isch

arg

es f

or

all

card

iovasc

ula

r d

isea

se

Weekly Avg PM25 Mobile Concentrations during

WinterSpring 2010 and its Influence on all Heart

Diagnoses

Zip Code 79905

Total All Heart Disease PM 25 mobile (μgm3)

0010203040

00

500

1000

1500

Mo

rbid

ity

dis

ch

arg

es

for

all

ca

rdio

va

scu

lar

dis

ea

se

Weeks

CORRELATION BETWEEN MOBILE PM25 ugm3

EXPOSURE TO HEART DISEASES SYMPTOMS

SUMMER SEASON 2010

Total All Heart Disease PM 25 mobile (μgm3)

Figure Statistical Analyses of the Relationship Between PM25 Caused by Traffic Emission( 26 of total Emission) with Heart diseases Source Hospital Admissions for Asthma Acute Bronchitis and Heart diseases in El Paso County zip code 79905 from Texas Health Care

Information Council in Austin Texas (Texas Health Care Information Council 2000)

00

10

20

30

40

0

50

100

150

We

ek 3

6

We

ek 3

7

We

ek 3

8

We

ek 3

9

We

ek 4

0

We

ek 4

1

We

ek 4

2

We

ek 4

3

We

ek 4

4

We

ek 4

5

We

ek 4

6

We

ek 4

7

We

ek 4

8

We

ek 4

9

We

ek 5

0

We

ek 5

1

We

ek 5

2

We

ek 5

3

Mo

rbid

ity

dis

ch

arg

es

for

all

ca

rdio

va

scu

lar

dis

ea

se

CORRELATION BETWEEN MOBILE PM25 ugm3

EXPOSURE TO HEART DISEASES SYMPTOMS FALL

SEASON 2010

Total All Heart Disease PM 25 mobile (μgm3)

Mobile(Exhaust-

Non-Exhaust)

PM10 and

Asthma-

Bronchitis)

Linear R

Square

WinterSpring 833 -42

Summer 620 -32

Fall 501-26

PM10 Mobile

emission (Exhaust-

Non-

Exhaust)contribut

ed significantly

association to the

incidence of CVD

Diseases

Monthly Brake Mobile Emission PM1025 kg During year 2010 and its Influence on

Respiratory Diagnoses Zip Code 79905

00200040006000800010000

010000200003000040000

PM

10

Mo

bile

(K

g)

Months

Monthly Brake Mobile Emission PM10 kg during year

2010 and its Influence on Respiratory Diagnoses

Zip Code 79905

Primary PM 10

Brakewear 00100020003000400050006000

0

1000

2000

3000

4000

PM

25

Mo

bil

e(K

g)

Months

Monthly Brake Mobile Emission PM25 during

year 2010 and its Influence on Heart Diagnoses

Zip Code 79905

Primary PM 25

Brakewear

Heart Diseases

Hospital

Admission

Brake Mobile Emission

PM10 kg Asthma-

Bronchitis)

Brake Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=969 Linear Square R=856

Monthly Mobile Exhaust Emission PM1025 During year 2010 and its Influence on

Respiratory Diagnoses Zip Code 79905

0

200

400

600

800

1000

0

10000

20000

30000

40000

50000

1 3 5 7 9 11

PM

10

(K

g m

on

th)

Months

Monthly Mobile Exhaust Emission PM10 during

year 2010 and its Influence on Respiratory

Diagnoses

Zip Code 79905

Primary Exhaust

PM 10

Respiratory Disease

(Asthma

Bronchitis) Hospital

Admission

0

100

200

300

400

500

600

0

10000

20000

30000

40000

50000

1 2 3 4 5 6 7 8 9 101112

PM

25

(K

g m

on

th)

Months

Monthly Exhaust Mobile Emission PM25 during

year 2010 and its Influence on Heart Diagnoses

Zip Code 79905

Primary Exhaust PM

25

Heart Diseases

Hospital Admission

Exhaust Mobile Emission

PM10 kg Asthma-

Bronchitis)

Exhaust Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=929 Linear Square R=831

Monthly Tire wear Mobile Emission PM1025 During year 2010 and its Influence on Heart

Diagnoses Zip Code 79905

0

100

200

300

400

500

600

700

800

900

0

1000

2000

3000

4000

5000

6000

7000

8000

9000

1 2 3 4 5 6 7 8 9 10 11 12

PM

10

(K

g m

on

th)

Months

Monthly Tirewear Mobile Emission PM10 during year 2010

and its Influence on Heart Diagnoses

Zip Code 79905

Primary PM 10 Tirewear

Mobile Emission

Respiratory Disease

(Asthma Bronchitis)

Hospital Admission

0

100

200

300

400

500

600

0

200

400

600

800

1000

1200

1400

1 2 3 4 5 6 7 8 9 10 11 12

PM

25

(K

g m

on

th)

Months

Monthly Tirewear Mobile Emission PM25 during year 2010

and its Influence on Respiratory Diagnoses

Zip Code 79905

Primary PM 25Tirewear

Mobile Emission

Heart Diseases Hospital

Admission

Exhaust Mobile Emission

PM10 kg Asthma-

Bronchitis)

Exhaust Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=769 Linear Square R=715

Dona Ana County Zip Codes

88021880278807288048

Primary

Exhaust

PM 10 Zip

code

79905

Total

Primary

Exhaust

PM10

Dona Ana

Primary

Exhaust

PM 25 Zip

Code

79905

Total

Primary

Exhaust

PM25

Dona Ana

Series1 430378 111773 391915 102123

0

100000

200000

300000

400000

500000

AX

IS T

ITLE

Annual Comparison of the Mobile

Exhaust Emissions El Paso County

and Dona Ana 2010

Primary

PM 10

Brakewea

r Zip code

79905

Brakewea

r

particulat

e_PM10

Dona Ana

Primary

PM 10

Tirewear

Zip code

79905

Tirewear

particulat

e_PM10

Dona Ana

Series1 262585 48573 73754 11864

050000

100000150000200000250000300000

AX

IS T

ITLE

Annual Comparison of the Mobile

Brakewear Emissions El Paso County

and Dona Ana 2010

Figure Comparison of the Annual Mobile Emissions

of Primary PM10 Non-Exhauts (Brake ) from Dona

Ana County New Mexico and El Paso Texas Units

in KgMonth

Figure Comparison of the Annual Mobile Emissions

of Primary PM10-Exhauts Emission from Dona Ana

County New Mexico and El Paso Texas Units in

KgMonth

Primary

PM 25

Brakewe

ar Ziphellip

Brakewe

ar

particula

te_PMhellip

Primary

PM

25Tirewe

ar Ziphellip

Tirewear

particula

te_PM25

Donahellip

Series1 32645 6071 10919 1779

0

10000

20000

30000

40000

AX

IS T

ITLE

Annual Comparison of the

Mobile Exhaust Emissions El Paso

County and Dona Ana 2010

Figure Comparison of the Annual Mobile Emissions

of Primary PM10-Exhauts Emission from Dona Ana

County New Mexico and El Paso Texas Units in

KgMonth

Monthly Mobile Emission PM1025 kg During year 2006

and its Influence on Respiratory Diagnoses Dona Ana

County Zip Code 880218802788072

0

100

200

300

0

5000

10000

15000

Axi

s Ti

tle

Axis Title

Monthly Mobile Exhaust Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Total PrimaryMobile Exhaust_PM10

All Respiratory ICD-9 (AsthmaBronchitis)

050100150200250300

010002000300040005000

Axi

s Ti

tle

Axis Title

Monthly Mobile Brake Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Brakewearparticulate_PM10

All RespiratoryICD -9 (AsthmaBronchitis)

050100150200250300

0200400600800

10001200

Axi

s Ti

tle

Axis Title

Monthly Mobile Tirewear Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Tirewearparticulate_PM10

All Respiratory ICD -9 (AsthmaBronchitis)

Mobile Exhauts

Emission PM10

kg Asthma-

Bronchitis)

Brake Mobile

Emission PM10

kg and Heart

Diagnoses

Tirewear Mobile

Emission PM10

kg and Heart

Diagnoses

Linear Square

R= 951

Linear Square

R=625

Linear Square

R=525

Mobile Exhauts

Emission PM25

kg Asthma-

Bronchitis)

Brake Mobile

Emission PM25

kg and Heart

Diagnoses

Tirewear Mobile

Emission PM25

kg and Heart

Diagnoses

Linear Square

R= 986

Linear Square

R=691

Linear Square

R=601

Results

The results showed that mobile PM emissions in the urban areas close to urban Road and highways is putting at risk public health

and the proportion of diseases attributable to this exposure is potentially large

Brake wear emissions is much lower in freeways due to significantly reduced number of braking events while tire wear is much

higher in areas where studded tires are used The emission of exhaust gases are much higher in areas where there is a high

vehicular traffic

Brake Mobile

Emission PM10 kg

Asthma-Bronchitis)

Brake Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square

R=969

Linear Square

R=856

Exhaust Mobile

Emission PM10 kg

Asthma-Bronchitis)

Exhaust Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square

R=929

Linear Square

R=831

Tirewear Mobile

Emission PM10 kg

Asthma-Bronchitis)

Tirewear Mobile

Emission PM25 kg

and Heart Diagnoses

Linear Square R=769 Linear Square R=715

Brake Mobile

Emission PM10 kg

and Heart

Diagnoses

Brake Mobile

Emission PM25 kg

and Heart

Diagnoses

Exhaust Mobile

Emission PM10 kg

Asthma-Bronchitis)

Linear Square

R=625

Linear Square

R=691

Linear Square R=

951

Exhaust Mobile

Emission PM25 kg

Asthma-

Bronchitis)

Tire wear Mobile

Emission PM10 kg and

Heart Diagnoses

Tirewear Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square R=

986

Linear Square R=525 Linear Square

R=601

El Paso County

Dona Ana

County

BenMAP-CE

In this analysis the Program of Mapping and Analysis of Environmental Benefits-Community Edition

(BenMAP-CE) was used to Estimate the number and economic value of health impacts resulting from changes

in air pollution PM 25 Ugm3 in The El Paso Area

Health and Economic Benefits associated with the Response of PM25 Emission between

Base Year 2010

Number of Mortalities in 2010 Base Year Based on El Paso County Texas Department of State Health Services

Number of Mortalities in 2010 Base Year Based on El Paso County Texas

Department of State Health Services

cause of death

year

2010

Populatio

n

Affected

Backgro

und

Concentr

ation Pollutant

Rollback

Type

Avoided

Deaths

(

Populatio

n)

alzheimers disease 2010 40716 125 PM25

25

microgmAcircsup3

Rollback 9

diseases of the

heart 2010 15834 125 PM25

25

microgmAcircsup3

Rollback 35

influenza and

neumonia 2010 81432 125 PM25

25

microgmAcircsup3

Rollback 18

acute bronchitis

and bronchiolitis 2010 117624 125 PM25

25

microgmAcircsup3

Rollback 26

chronic lower

respiratory diseases 2010 54288 125 PM25

25

microgmAcircsup3

Rollback 12

The Basin-wide decrease in 4 ugm3 PM25 concentration after this

reduction control

Cause of death year 2010

Populatio

n

Affected

Background

Concentrati

on

Reduc

cion

scena

rio Polluta

nt

Rollback

Type

Avoi

ded

Deat

hs

(

Pop

ulati

on)

economic

benefits

analysis $

Alzheimers

disease 2010 121 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 9 12000

Diseases of the

heart 2010 470 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 35 35000

Influenza and

neumonia 2010 242 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 18 42500

Acute bronchitis

and bronchiolitis 2010 349 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 26 95000

Chronic lower

respiratory

diseases 2010 161 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 12 4500

$1 295000

PM25-related Mortalities Based on BenMAP-CE Estimate in 2010 Base Year with change in the concentrations levels

Health and Economic Benefits associated with the Response of PM25 Emission between

Base Year 2010 Increasing 7 Ugm3

Cause of death year 2010

Population

Affected

Deaths

avoided by

attaining 195

μgm3

standard

Background

Concentrati

on

Pollut

ant

Rollback

Type

Avoided

Deaths (

Populatio

n)

econo

mic

Unben

efits

analysi

s

Alzheimers

disease 2010 4524 195 PM25

25

microgmAcircsup3

Rollback 19 150000

Diseases of the

heart 2010 20358 195 PM25

25

microgmAcircsup3

Rollback 135 450000

Influenza and

neumonia 2010 126672 195 PM25

25

microgmAcircsup3

Rollback 38 525000

Acute bronchitis

and bronchiolitis 2010 162864 195 PM25

25

microgmAcircsup3

Rollback 36 122000

Chronic lower

respiratory

diseases 2010 99528 195 PM25

25

microgmAcircsup3

Rollback 12 650000

Conclusions

An excellent Pearson Correlation was established to analyze the relationship in the relative risks of hospitalization of Respiratory(RD) and cardiovascular (CVD) associated with ambient exposure caused by traffic emission in relation to their size andspecific sources of emission on different scenarios interior a border Urban Rural Urban restricted access (freeways andinterstates)

A significant correlation of PM1025 exposure from mobile emission and hospital admissions for selected Respiratory (RD) andcardiovascular (CVD) diagnoses was established The results showed that PM emissions in urban restricted access (freeways andinterstates) is mainly caused by traffic Therefore people living close to highways are more exposed higher vehicular emissions

Conclusions

We found statistically significant associations between mobile PM25 caused by traffic emission with Respiratory and Cardiovascular Diseases in the study areaSubsequently a correlation between cardio-respiratory mortality is established

A significant correlation of PM1025 exposure from mobile emission and hospital admissions for selected Respiratory (RD) and cardiovascular (CVD) diagnoses isestablished The results showed that PM emissions in urban restricted access (freeways and interstates) is mainly caused by traffic Therefore people living close tohighways receive higher vehicular emissions

The table shows the percentage of PM mobile exposure in the analyzed areas contributing to increase the risk of Respiratory and Cardiovascular Diseases

An examination was conducted of the synoptic and local meteorology for the June 2006 ozone episode using the WRF model to determine how meteorological parametersinfluence the formation transport and dispersion of ozone in the PdN The predominant synoptic feature of the ozone event day was the expansion intensification and slowprogression of an upper-level ridge of high pressure The high ozone episodes are associated with highly stable atmospheres strong temperature inversions with low mixingheights and therefore low mixing volumes Under these conditions emissions such as NOx lead to highly polluted conditions that favor ozone formation

BenMAP Conclusions

We have estimated the number and economic value of health impacts resulting

from changes in air pollution concentrations of PM 25 in the PdN region

Reduction of Pm 25 4 UGm3= Avoided 213 cases respiratory cardiovascular

diseses and Economic Benefits associated with the Response of PM25 Emission + $

1295000

Increase of PM25 7 ugm3 = increasing Dies= 326 economic Unbenefits= 2345000$

Bibliography

1 Dockery DW Pope CAI Xu X Spengler JD Ware JH Fay ME Ferris BG Speizer FE An association between air pollution and mortality in six US cities N Engl J Med 3291753ndash1759 (1993)

2 Samet JM Dominici F Curriero FC Coursac I Zeger SL Fine particulate air pollution and mortality in 20 US cities 1987ndash1994 N Engl J Med 3431742ndash1749 (2000)

3 Nel AE Diaz-Sanchez D Li N The role of particulate pollutants in pulmonary inflammation and asthma evidence for the involvement of organic chemicals and oxidative stress Curr Opin Pulm Med 20017 20ndash26

4 Westerholm R Karl-Erik E Exhaust emissions from lightand heavy-duty vehicles chemical composition impact of exhaust after treatment and fuel parameters Environ Health Perspect 102(suppl 4)13ndash23 (1994)

5 Bascom R Bromberg P Costa D Delvin R Dockery D Frampton M Lambert W Samet J Speizer F Utell

6 Health effects of outdoor air pollution Am J Respir Crit Care Med 1533ndash50 (1996)

7 Chow JC Watson JG Frazier CA Egami RT Goodrich A Ralph C Spatial and temporal source contributions to

8 PM10 and PM25 in Reno NV In PM-10 Implementation of Standards Transactions An APCAEPA International Speciality Conference San Francisco CA (Mathal CV Stonefield DH eds) PittsburghAPCA 1988439ndash457

9 overview In Particulate Matter Health and Regulatory Issues VIP-49 Proceedings of an International Specialty Conference 4ndash6 April 1995 Pittsburgh PA PittsburghAir and Waste Management Association 1995577ndash598

10 Kunzli N Kaiser R Medina S Studnicka M Chanel O

11 Filliger P Herry M Horak F Jr Puybonnieux-Texier V Quenel P et al Public-health impact of outdoor and traffic- related air pollution a European assessment Lancet 356795ndash801 (2000)

Bibliography

1 Sioutas C Delfino RJ Singh M Exposure assessment for atmospheric ultrafine particles (UFP) and implications in epidemiological research Environ Health Perspect 2005113947ndash955

2 Mosleh M Blau PJ Dumitrescu D (2004) Characteristics and morphology of wear particles from laboratory testing of disc brake materials Wear 2561128ndash1134

3 Kuumlnzli N et al (2000) Public-health impact of outdoor and traffi c-related air pollution a European assessment Lancet 356(9232)795ndash801

4 Dora C Phillips M eds (2000) Transport environment and health Copenhagen WHO Regional Office for Europe (WHO Regional Publications European Series No 89 httpwwweurowhointdocumente72015pdf accessed 26 November 2004)

5 Westerholm R Karl-Erik E Exhaust emissions from lightand

6 heavy-duty vehicles chemical composition impact of exhaust after treatment and fuel parameters Environ Health Perspect 102(suppl 4)13ndash23 (1994)

7 Fauser Tjell Mosbaek pigegaard Quantification of tire-Tread particles using extractable Organic Zinc as a Tracer Rubber Chemistry and Technology 1999 969Table shows some literature estimates of the contribution of tire wear to PM10 in air (Panko et al 2013) Gustafsson M Blomqvist G Gudmundsson A Dahl A Swietlicki E Bohgard M Lindbom J Ljungman A

8 Chen Y Shah N Huggins FE and Huffman GP (2006) Microanalysis of Ambient Particles from Lexington Ky by Electron Microscopy Atmos Environ 40 651ndash663

9 Donaldson K Tran CL Jimenez LA Duffin R Newby DE and Mills N (2005) Combustion-derived Nanoparticles A Review of Their Toxicology Following Inhalation Exposure Part Fibre Toxicol 2 10ndash23

10 Su D Serafino A Muller JO Jentoft RE Schlogl R and Fiorito S (2008) Cytotoxicity and Inflammatory Potential of Soot Particles of Low-emission Diesel Engines Environ Sci Technol 42 1761ndash1765

11 Maier KL Alessandrini F Beck-Speier I Hofer TPJ Diabatґe S Bitterle E Stoger T and Jakob T (2008) Health Effects of Ambient Particulate Matter-Biological Mechanisms and Inflammatory Responses to in Vitroand in Vivo Particle Exposures Inhalation Toxicol 20 319ndash337

Page 22: Studies of Air Pollutants and their Impact on Respiratory and ...€¦ · Ascarate Park C37 Monitoring Station: The National Ambient Air Quality Standard (NAAQS) for PM 10 and 2.5

HYSPLIT Model

HYSPLIT was simulated and showed that the ozone is mostly transported to El Paso from north western and south western US and Mexican regions during the 72 hours duration of the simulation

0

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June 18th June 19th

Performance Evaluation

01020304050

Ju

ne

137

130

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190

0

10

0

Ju

ne

157

130

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190

0

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0

Ju

ne

187

130

0

190

0

10

0

Tem

pe

ratu

re (⁰C

)

Local time (Hrs)

C41 June 13-19 2006

WRF_temperature

(⁰C)

TCEQ_temperature

(⁰C)

0

50

100

150

June1

37

100

0

130

0

160

0

190

0

220

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June1

57

100

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June1

87

100

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0Ozo

ne

(pp

b)

Local time (Hrs)

C41 June 13-19 2006

CAMx_ozone (ppbV) TCEQ_ozone (ppb)

0

10

20

30

40

50

June1

37

100

0

130

0

160

0

190

0

220

0

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0

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June1

57

100

0

130

0

160

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190

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220

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10

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40

0

June1

87

100

0

130

0

160

0

190

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220

0

10

0

40

0

Rel

ativ

e h

um

idit

y (

)

Local time (Hrs)

C41 June 13-19 2006

WRF_rh () TCEQ_relative humidity ()

0

5

10

15

20

June

137 10

13

16

19

22 1 4

June

157 10

13

16

19

22 1 4

June

187 10

13

16

19

22 1 4W

ind

sp

eed

(m

sLocal time(Hrs)

C12 June 13-192006

WRF_wind speed (ms) TCEQ_ wind speed (ms)

Methodology

Medical Data The data by weekly monthly and year for daily emergency room and hospital admission for the respiratory

infections (RD) and cardiovascular diseases (CVD) was extracted from hospitals records located in the El PdN

the system includes data on type of admission primary and secondary causes of admissionRESPIRATORY DISEASE

Bronquitis amp Chronic Bronchitis 466 - 4661 491 - 4919

Asthma 463 - 4939

Emphysema 492

Respiratory failure 51881

HEART DISEASE

Accute Myocardial Infarction 410

Coronary Athersclerosis 4140

Other Ischemic Heart Disease 411-4139 4141-4149

Cardiac Dyshythmias 427

Essential hypertension 401

Acute myocardial infarction 410

Congestive Heart Failure 4280 4282-4284

Hypertensive heart disease 402

Table 1 ICD -9 Codes for Respiratory and Cardiovascular Diseases

0

50

100

150

200

250

300

Wee

k 1

Wee

k 2

Wee

k 3

Wee

k 4

Wee

k 5

Wee

k 6

Wee

k 7

Wee

k 8

Wee

k 9

Wee

k 1

0

Wee

k 1

1

Wee

k 1

2

Wee

k 1

3

Wee

k 1

4

Wee

k 1

5

Wee

k 1

6

Wee

k 1

7

Wee

k 1

8

Wee

k 1

9

Wee

k 2

0

Wee

k 2

1

Mo

rb

idit

y D

isch

arg

e fo

r a

ll R

esp

ira

tory

Dis

ease

IC

D-9

(

Ast

hm

aB

ro

nch

itis

)

Weekly Morbidity Discharges of all the Listed Diagnoses for All

Respiratory Disease During WinterSpring 2010

Asthma-Bronchitis

EPA MOVES Model for Estimating Emission

Inventories

Motor Vehicle Emission Simulator (MOVES 2010b) will be configuredin The El Paso North Region for Calculate five categories of PM10

PM25 total Emission inventories from all on-road traffic over a

variety of scales within periods of time selected weeks months

and years

Moves (Motor Vehicle Emission

Simulator)

The emission model is develop using the current equation to calculate direct traffic emissions from

vehicles in the form of PM is

Eext annual emissions are measured in grams of miles traveled by the vehicle (gVMT )

SL is the road surface loading in (gm2)

W is the average weight in tons of the vehicles on the road

K is the particle size multiplier for particle size range (eg gVMT for PM10 when using grams and miles)

P is the 7 number of wet days with at least 0254 mm of precipitation during the averaging period

N is the number of years considered in the averaging period

C is the particle size specific emissions factor in units of interest vehicle direct exhaust brake wear and tirewear

Modeling Simulation Domain and Emissions Scenarios

For simulations of mobile air quality emission inventories a motor vehicle emission simulator EPA (MOVES 2014a) was used

The modeling use input factors divided into seven section

parameters

On-Road Inventory local data

input

Scale

Geographic Bounds

Traffic intensity

Vehicle Type

Pollutants

Road Type

Fuel Types

Figure Source EPA US Environmental Protection Agency 2012- Moves 2010b Model

EPA Moves 2014a The modeling used input factors divided into six section

parameters On-Road Inventory local data input

Geographic Domains CountyNonattainment Area

Vehicle-Miles Traveled (VMT) is the total number of miles driven by all vehicles withina given time period and geographic area

Average speed range from 25 miles per

hour to 65 miles per hour

Vehicle Classes Motorcycle PassengerCarTruks light-duty Commercial Truck(6001-8500 lbs) Buses heave-duty trucksRefuse trucks School Bus Single UnitShort Haul-truck Single Unit Long Haul-truck Long Haul Truck Heavy-DutyVehicles (26001-33000 lbs)

Pollutants

Road TypeRural restricted Acces(Freeways and interstates) Rural and Restricted Acces Urban Restricted Acces Off-Network

Fuel Types Gasoline Diesel Fuel

Specific Road Types

Two road types for running emission from the MOVES can be

selected

(freeways and interstates)

Interior urban Urban

Figure Source EPA US Environmental Protection Agency 2012- Moves 2010b Model

VehiclesEquipment

This panel show which on-road vehicles will be modeled

Figure Source EPA US Environmental Protection Agency 2012- Moves 2010b Model

Long haul truck Short haul truck Inercity bus Ligth comercial truck

Passenger car Passenger truck Refuse truck

School bus Single unit long haul-truck

Single unit short haul-truck

Transit bus

Motor home

Motorcycle

Based on Department of Transportation Highway MOVES will Estimates Traffic

Emissions from Cars Trucks amp Motorcycles

Output Data Moves 2014a

Inventories of PM 10 25 Mobile Emission from all

on-Road Traffic

Exhaust Emission PM 10 25 gramsmile

Brake Wear Emission PM 10 25 gramsmile

Tire wear Emission PM 10 25 gramsmile

Date of Vehicle miles traveled (VMT) for

Day Week Month Year

Total Vehicle population

Vehicle age distribution

Simulation of Mobile Emission in the El PdN Region Zip Code 79905

Figure Total Emissions from road traffic in El Paso TX Area were estimated for PM10

Exhaust and Non exhaust emission in kilogramsmonth (Source EPA MOVES 2014a)

0

10000

20000

30000

40000

50000

PM

10 k

gM

on

th

Months

Monthly PM 10 Exhaust and Non-Exhaust Mobile Emissions 2010

On-Road Urban Restricted Area Zip Code 79905

Primary Exhaust PM 10 (kg) Primary PM 10 Brakewear (kg)

Primary PM 10 Tirewear (kg)

05000

100001500020000250003000035000400004500050000

PM

25

kg

Mo

nth

Months

Monthly PM 25 Exhaust and Non-Exhaust Mobile Emission 2010

On-Road Urban Restricted Area Zip Code 79905

Primary Exhaust PM 25 (kg) Primary PM 25 Brakewear (kg) Primary PM 25Tirewear (kg)

Figure Total Emissions from road traffic in El Paso TX Area were estimated for PM25

Exhaust and Non exhaust emission in kilogramsmonth (Source EPA MOVES 2014a)

Total Emissions from Road Traffic in El Paso County PM1025 Exhaust and Non exhaust Emission in kilogramsmonth

Taking the interests to the health risks related to PM 1025 mobile emission were simulated

Exhaust and Non-exhaust emissions contribute almost equally to total traffic-related PM1025 Emissions (Querol et al 2004 Bukowiecki et al 2009a Amato et al 2011)

Monthly PM 10 25 Exhaust and Non-Exhaust (BrakewearTirewear) Mobile

Emission 2010 On-Road Urban Restricted Area Zip Code 79905

Figure Total Emissions from road traffic in El Paso TX Area were estimated for PM10 25 Exhaust and Non Exhaust mobile

emission in kilograms per month (Source EPA MOVES)

0

10000

20000

30000

40000

50000

January February March April May June July August September October November December

PM

10

25

(K

ilog

ram

s)

Months

Summary- Monthly PM 10 25 Exhaust and Non-Exhaust Mobile

Emission 2010 On-Road Urban Restricted Area Zip Code 79905

Primary Exhaust PM 10 Primary PM 10 Brakewear Primary PM 10 Tirewear

Primary Exhaust PM 25 Primary PM 25 Brakewear Primary PM 25Tirewear

Exhaust Emissions PM1025 is reaching maximum emission 48000-42000 thousand of Kgmonth followedby Brake wear 29000-5000 thousand kgmonth and Tire wear with 9000-2000 kgmonth The results showthat the emissions of PM derived mainly from Exhaust and Brake are significantly higher in Urban Area

Annual Contribution of Mobile Emission PM 1025 (Kg) Zip Code 79905 El

Paso County 2010

Total Primary

Exhaust _PM10

39

Total Primary

Exhaust _PM25

36

Brakewear

particulate_PM10

18

Tirewear

particulate_PM10

4

Brakewear

particulate_PM25

2

Tirewear

particulate_PM25

1

0

5

10

15

20

25

30

35

40

45

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53

Fig Annual Average PM10 Concentrations at the

Chamizal C41 Station and PM1025 mobile

Concentration Zip code 79905

PM10 TCEQ (μgm3) Total Mobile Emission PM10 (Ugm3)

Fig Exhaust Emission is Contributing Approximately 74 of total

PM1025 Mobile Emissions following of Brake wear with 20 and Tire

wear with 5

Annual Average PM1025 ugm3 Mobile Emissions (Moves) 26 Chamizal C41

Monitoring Station (TCEQ Chamizal Station )

Predicting Mobile Emission and VTM

Estimation The PdN Region 2010

44E+09

46E+09

48E+09

5E+09

52E+09

54E+09

56E+09

58E+09

6E+09

62E+09

0

50000

100000

150000

200000

250000

300000

350000

20

10

20

11

20

12

20

13

20

14

20

15

20

16

20

17

20

18

20

21

20

22

20

23

20

24

20

25

20

26

20

27

20

28

20

29

20

30

EX

HA

US

T

EM

ISS

ION

MO

BIL

E (

KG

YE

AR

)

YEARS

Predict ing Mobile Exhaust Emission and VTM

Estimation

2010 - 2030 e l PdN Area

Total_ Exhaust PM10 Total_ Exhaust PM25 Distance (Miles)

Fig Predicting Mobile Exhaust PM1025 (kgMonth) Emission and VTM Estimation 2010

- 2030 el PdN Area

44E+09

46E+09

48E+09

5E+09

52E+09

54E+09

56E+09

58E+09

6E+09

62E+09

0

5000000

10000000

15000000

20000000

25000000

30000000

20

10

20

11

20

12

20

13

20

14

20

15

20

16

20

17

20

18

20

21

20

22

20

23

20

24

20

25

20

26

20

27

20

28

20

29

20

30

EX

HA

US

T

EM

ISS

ION

MO

BIL

E (

KG

YE

AR

)

YEARS

Predict ing Mobile Exhaust Emission and

VTM Estimation

2010 - 2030 e l PdN Area

CO NO2 NO NOx Distance

Fig Predicting Mobile Exhaust Emission and VTM Estimation

2010 - 2030 el PdN Area in El Paso TX Area were estimated for

Total CO NOx NO2 NO emission in kilograms per year

(Source EPA MOVES 2014a model)

The simulated Exhaust emissions in the future years shows a trend of reduction of this type of emissions in the

future years one factor should be the new hybrid technology is increasing by 476 since 2010 to 2015 and

use of catalytic converters diesel particulate filters and improved fuels and engines Non-exhaustive sources

will increase in the coming years because there is no control in the material of manufacture composed by Fe

Cu and Mn also not to be able to reduce the number of events of braking (Accelerations and decelerations)

45E+09

5E+09

55E+09

6E+09

65E+09

0

50000

100000

150000

200000

250000

201

0

201

1

201

2

201

3

201

4

201

5

201

6

201

7

201

8

202

1

202

2

202

3

202

4

202

5

202

6

202

7

202

8

202

9

203

0

NO

N-

EX

HA

US

T

EM

ISS

ION

MO

BIL

E

(KG

YE

AR

)

YEARS

Predicting Non Exhaust Mobile

Emission and VTM Estimation

2010 - 2030 el PdN Area

Brake_PM10 Tire_PM10 Distance (Miles)

Fig Predicting Mobile Exhaust PM1025 (kgMonth) Emission and VTM

Estimation 2010 - 2030 el PdN Area

Daily Avg PM1025

Levels of PM Mobile Emission Non-Exhaust -Rush Hour Periods Fall 2010 Zip Code

79905

00

100

200

300

400

500

600

Mo

bil

e P

M1

0 (k

g)

Rush Hours

Daily Avg PM10

Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush Hours

Periods 2010 Zip Code 79905

Total Primary Exhaust

_PM10 WinterSpring

Brakewear

particulate_PM10

WinterSpringTirewear particulate_PM10

WinterSpring

Total Primary Exhaust

_PM10 Summer

Brakewear

particulate_PM10 Summer

Tirewear Particulate_PM10

Summer

Total Primary Exhaust

_PM10 Fall

Brakewear

particulate_PM10 Fall

Tirewear particulate_PM10

Fall

00

50

100

150

200

250

300

350

Mo

bil

e P

M2

5 (k

g)

Rush hours

Daily Avg PM25

Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush

Hours Periods 2010 Zip Code 79905

Total Primary Exhaust _PM25

WinterSpring

Brakewear Particulate_PM25

WinterSpring

Tirewear particulate_PM25

WinterSpring

Total Primary Exhaust _PM25

Summer

Brakewear particulate_PM25

Summer

Tirewear particulate_PM25

Summer

Total Primary Exhaust _PM25

Fall

Brakewear particulate_PM25

Fall

Tirewear particulate_PM25

Fall

Figure Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush Hours Figure Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush Hours

GIS EMISSIONS INVENTORY SYSTEM A geographic information system (GIS) was used to established geographic scenarios with processed images of seasonal mobile

emissions in the PdN region Seasonal mapping is visualized for different types of pollutants Brakewear Exhaust and Tyrewear

Fg Graphics of GIS and Seasonal mobile Emission of particulate matter emission inventory Seasonal emission simulations were performed in kilograms and five contributing inputs factors were identified for

modeling 1) On the composition of the particulate material from different sources such as Exhaust and Non exhaust (Brake wear Tirewear) 2) The Vehicles Equipment clasification were selected according to

the use of gasoline and diesel fuel (motorcycle passenger car Light Duty Vehicles Trucks refuse truck Light Duty Vehicles Light Commercial Truck Light Duty Vehicles School Bus)

Winter Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

120354 67860 19065

Spring Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

139767 86702 24463

Summer Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

94747 62481 17630

Fall Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

75510 45542 12596

251 Descriptive Statistics Data Analysis

Weekly Correlation Analysis of Mobile Emission PM10 (Exhaust-Non-Exhaust) and Respiratory

Diagnoses WinterSpring Summer and Fall 2010

0

2

4

6

8

10

0

50

100

150

200

250

300

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21

Mo

rbid

ity

Dis

ch

arg

e

for

all R

esp

ira

tory

Dis

ea

se

ICD

-9

(A

sth

ma

-Bro

nc

hitis

)

WinterSpring Week

Weekly Avg Mobile PM10 Concentrations during

WinterSpring 2010 and its Influence on Respiratory

Diagnoses

Zip Code 79905

Total Medical data ZIP Code 79902

Total Mobile Emission PM10 (Ugm3)

0

1

2

3

4

5

6

7

0

20

40

60

80

100

Mo

rbid

ity

Dis

ch

arg

e

for

all R

esp

ira

tory

Dis

ea

se

ICD

-9

(Ast

hm

aB

ron

ch

itis

)

Weekly Avg Mobile PM10 Concentrations during

Summer 2010 and its Influence on Respiratory

Diagnoses

Summer 2010 Zip Code 79905

Total Mobile Emission PM10

Hospital Admission (Asthma-Bronchitis)

0

2

4

6

8

10

12

0

20

40

60

80

100

120

140

160

180

200

Mo

rbid

ity

dis

ch

arg

es

for

all r

esp

ira

tory

dis

ea

se

Weekly Avg Mobile PM10 Concentrations

during Fall 2010 and its Influence on Respiratory

Diagnoses

Zip Code 79905

Total Medical data ZIP Code 79902

Total Mobile Emission PM10 (Ugm3)

Mobile(Exhaust-Non-

Exhaust) PM10 and

Asthma-Bronchitis)

Linear R

Square

WinterSpring 734 ndash 39

Summer 614 ndash 32

Fall 548 -29

PM10 Mobile emission (Exhaust-Non-Exhaust)contributed significantly

association to the incidence of RD

Weekly Correlation Analysis of PM 25 Mobile Emission (Exhaust-Non-Exhaust)

and Cardiovascular Diagnoses WinterSpring Summer and Fall 2010

0010203040

00500

100015002000

Wee

k 1

Wee

k 2

Wee

k 3

Wee

k 4

Wee

k 5

Wee

k 6

Wee

k 7

Wee

k 8

Wee

k 9

Wee

k 1

0

Wee

k 1

1

Wee

k 1

2

Wee

k 1

3

Wee

k 1

4

Wee

k 1

5

Wee

k 1

6

Wee

k 1

7

Wee

k 1

8

Wee

k 1

9

Wee

k 2

0

Wee

k 2

1

Morb

idit

y d

isch

arg

es f

or

all

card

iovasc

ula

r d

isea

se

Weekly Avg PM25 Mobile Concentrations during

WinterSpring 2010 and its Influence on all Heart

Diagnoses

Zip Code 79905

Total All Heart Disease PM 25 mobile (μgm3)

0010203040

00

500

1000

1500

Mo

rbid

ity

dis

ch

arg

es

for

all

ca

rdio

va

scu

lar

dis

ea

se

Weeks

CORRELATION BETWEEN MOBILE PM25 ugm3

EXPOSURE TO HEART DISEASES SYMPTOMS

SUMMER SEASON 2010

Total All Heart Disease PM 25 mobile (μgm3)

Figure Statistical Analyses of the Relationship Between PM25 Caused by Traffic Emission( 26 of total Emission) with Heart diseases Source Hospital Admissions for Asthma Acute Bronchitis and Heart diseases in El Paso County zip code 79905 from Texas Health Care

Information Council in Austin Texas (Texas Health Care Information Council 2000)

00

10

20

30

40

0

50

100

150

We

ek 3

6

We

ek 3

7

We

ek 3

8

We

ek 3

9

We

ek 4

0

We

ek 4

1

We

ek 4

2

We

ek 4

3

We

ek 4

4

We

ek 4

5

We

ek 4

6

We

ek 4

7

We

ek 4

8

We

ek 4

9

We

ek 5

0

We

ek 5

1

We

ek 5

2

We

ek 5

3

Mo

rbid

ity

dis

ch

arg

es

for

all

ca

rdio

va

scu

lar

dis

ea

se

CORRELATION BETWEEN MOBILE PM25 ugm3

EXPOSURE TO HEART DISEASES SYMPTOMS FALL

SEASON 2010

Total All Heart Disease PM 25 mobile (μgm3)

Mobile(Exhaust-

Non-Exhaust)

PM10 and

Asthma-

Bronchitis)

Linear R

Square

WinterSpring 833 -42

Summer 620 -32

Fall 501-26

PM10 Mobile

emission (Exhaust-

Non-

Exhaust)contribut

ed significantly

association to the

incidence of CVD

Diseases

Monthly Brake Mobile Emission PM1025 kg During year 2010 and its Influence on

Respiratory Diagnoses Zip Code 79905

00200040006000800010000

010000200003000040000

PM

10

Mo

bile

(K

g)

Months

Monthly Brake Mobile Emission PM10 kg during year

2010 and its Influence on Respiratory Diagnoses

Zip Code 79905

Primary PM 10

Brakewear 00100020003000400050006000

0

1000

2000

3000

4000

PM

25

Mo

bil

e(K

g)

Months

Monthly Brake Mobile Emission PM25 during

year 2010 and its Influence on Heart Diagnoses

Zip Code 79905

Primary PM 25

Brakewear

Heart Diseases

Hospital

Admission

Brake Mobile Emission

PM10 kg Asthma-

Bronchitis)

Brake Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=969 Linear Square R=856

Monthly Mobile Exhaust Emission PM1025 During year 2010 and its Influence on

Respiratory Diagnoses Zip Code 79905

0

200

400

600

800

1000

0

10000

20000

30000

40000

50000

1 3 5 7 9 11

PM

10

(K

g m

on

th)

Months

Monthly Mobile Exhaust Emission PM10 during

year 2010 and its Influence on Respiratory

Diagnoses

Zip Code 79905

Primary Exhaust

PM 10

Respiratory Disease

(Asthma

Bronchitis) Hospital

Admission

0

100

200

300

400

500

600

0

10000

20000

30000

40000

50000

1 2 3 4 5 6 7 8 9 101112

PM

25

(K

g m

on

th)

Months

Monthly Exhaust Mobile Emission PM25 during

year 2010 and its Influence on Heart Diagnoses

Zip Code 79905

Primary Exhaust PM

25

Heart Diseases

Hospital Admission

Exhaust Mobile Emission

PM10 kg Asthma-

Bronchitis)

Exhaust Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=929 Linear Square R=831

Monthly Tire wear Mobile Emission PM1025 During year 2010 and its Influence on Heart

Diagnoses Zip Code 79905

0

100

200

300

400

500

600

700

800

900

0

1000

2000

3000

4000

5000

6000

7000

8000

9000

1 2 3 4 5 6 7 8 9 10 11 12

PM

10

(K

g m

on

th)

Months

Monthly Tirewear Mobile Emission PM10 during year 2010

and its Influence on Heart Diagnoses

Zip Code 79905

Primary PM 10 Tirewear

Mobile Emission

Respiratory Disease

(Asthma Bronchitis)

Hospital Admission

0

100

200

300

400

500

600

0

200

400

600

800

1000

1200

1400

1 2 3 4 5 6 7 8 9 10 11 12

PM

25

(K

g m

on

th)

Months

Monthly Tirewear Mobile Emission PM25 during year 2010

and its Influence on Respiratory Diagnoses

Zip Code 79905

Primary PM 25Tirewear

Mobile Emission

Heart Diseases Hospital

Admission

Exhaust Mobile Emission

PM10 kg Asthma-

Bronchitis)

Exhaust Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=769 Linear Square R=715

Dona Ana County Zip Codes

88021880278807288048

Primary

Exhaust

PM 10 Zip

code

79905

Total

Primary

Exhaust

PM10

Dona Ana

Primary

Exhaust

PM 25 Zip

Code

79905

Total

Primary

Exhaust

PM25

Dona Ana

Series1 430378 111773 391915 102123

0

100000

200000

300000

400000

500000

AX

IS T

ITLE

Annual Comparison of the Mobile

Exhaust Emissions El Paso County

and Dona Ana 2010

Primary

PM 10

Brakewea

r Zip code

79905

Brakewea

r

particulat

e_PM10

Dona Ana

Primary

PM 10

Tirewear

Zip code

79905

Tirewear

particulat

e_PM10

Dona Ana

Series1 262585 48573 73754 11864

050000

100000150000200000250000300000

AX

IS T

ITLE

Annual Comparison of the Mobile

Brakewear Emissions El Paso County

and Dona Ana 2010

Figure Comparison of the Annual Mobile Emissions

of Primary PM10 Non-Exhauts (Brake ) from Dona

Ana County New Mexico and El Paso Texas Units

in KgMonth

Figure Comparison of the Annual Mobile Emissions

of Primary PM10-Exhauts Emission from Dona Ana

County New Mexico and El Paso Texas Units in

KgMonth

Primary

PM 25

Brakewe

ar Ziphellip

Brakewe

ar

particula

te_PMhellip

Primary

PM

25Tirewe

ar Ziphellip

Tirewear

particula

te_PM25

Donahellip

Series1 32645 6071 10919 1779

0

10000

20000

30000

40000

AX

IS T

ITLE

Annual Comparison of the

Mobile Exhaust Emissions El Paso

County and Dona Ana 2010

Figure Comparison of the Annual Mobile Emissions

of Primary PM10-Exhauts Emission from Dona Ana

County New Mexico and El Paso Texas Units in

KgMonth

Monthly Mobile Emission PM1025 kg During year 2006

and its Influence on Respiratory Diagnoses Dona Ana

County Zip Code 880218802788072

0

100

200

300

0

5000

10000

15000

Axi

s Ti

tle

Axis Title

Monthly Mobile Exhaust Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Total PrimaryMobile Exhaust_PM10

All Respiratory ICD-9 (AsthmaBronchitis)

050100150200250300

010002000300040005000

Axi

s Ti

tle

Axis Title

Monthly Mobile Brake Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Brakewearparticulate_PM10

All RespiratoryICD -9 (AsthmaBronchitis)

050100150200250300

0200400600800

10001200

Axi

s Ti

tle

Axis Title

Monthly Mobile Tirewear Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Tirewearparticulate_PM10

All Respiratory ICD -9 (AsthmaBronchitis)

Mobile Exhauts

Emission PM10

kg Asthma-

Bronchitis)

Brake Mobile

Emission PM10

kg and Heart

Diagnoses

Tirewear Mobile

Emission PM10

kg and Heart

Diagnoses

Linear Square

R= 951

Linear Square

R=625

Linear Square

R=525

Mobile Exhauts

Emission PM25

kg Asthma-

Bronchitis)

Brake Mobile

Emission PM25

kg and Heart

Diagnoses

Tirewear Mobile

Emission PM25

kg and Heart

Diagnoses

Linear Square

R= 986

Linear Square

R=691

Linear Square

R=601

Results

The results showed that mobile PM emissions in the urban areas close to urban Road and highways is putting at risk public health

and the proportion of diseases attributable to this exposure is potentially large

Brake wear emissions is much lower in freeways due to significantly reduced number of braking events while tire wear is much

higher in areas where studded tires are used The emission of exhaust gases are much higher in areas where there is a high

vehicular traffic

Brake Mobile

Emission PM10 kg

Asthma-Bronchitis)

Brake Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square

R=969

Linear Square

R=856

Exhaust Mobile

Emission PM10 kg

Asthma-Bronchitis)

Exhaust Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square

R=929

Linear Square

R=831

Tirewear Mobile

Emission PM10 kg

Asthma-Bronchitis)

Tirewear Mobile

Emission PM25 kg

and Heart Diagnoses

Linear Square R=769 Linear Square R=715

Brake Mobile

Emission PM10 kg

and Heart

Diagnoses

Brake Mobile

Emission PM25 kg

and Heart

Diagnoses

Exhaust Mobile

Emission PM10 kg

Asthma-Bronchitis)

Linear Square

R=625

Linear Square

R=691

Linear Square R=

951

Exhaust Mobile

Emission PM25 kg

Asthma-

Bronchitis)

Tire wear Mobile

Emission PM10 kg and

Heart Diagnoses

Tirewear Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square R=

986

Linear Square R=525 Linear Square

R=601

El Paso County

Dona Ana

County

BenMAP-CE

In this analysis the Program of Mapping and Analysis of Environmental Benefits-Community Edition

(BenMAP-CE) was used to Estimate the number and economic value of health impacts resulting from changes

in air pollution PM 25 Ugm3 in The El Paso Area

Health and Economic Benefits associated with the Response of PM25 Emission between

Base Year 2010

Number of Mortalities in 2010 Base Year Based on El Paso County Texas Department of State Health Services

Number of Mortalities in 2010 Base Year Based on El Paso County Texas

Department of State Health Services

cause of death

year

2010

Populatio

n

Affected

Backgro

und

Concentr

ation Pollutant

Rollback

Type

Avoided

Deaths

(

Populatio

n)

alzheimers disease 2010 40716 125 PM25

25

microgmAcircsup3

Rollback 9

diseases of the

heart 2010 15834 125 PM25

25

microgmAcircsup3

Rollback 35

influenza and

neumonia 2010 81432 125 PM25

25

microgmAcircsup3

Rollback 18

acute bronchitis

and bronchiolitis 2010 117624 125 PM25

25

microgmAcircsup3

Rollback 26

chronic lower

respiratory diseases 2010 54288 125 PM25

25

microgmAcircsup3

Rollback 12

The Basin-wide decrease in 4 ugm3 PM25 concentration after this

reduction control

Cause of death year 2010

Populatio

n

Affected

Background

Concentrati

on

Reduc

cion

scena

rio Polluta

nt

Rollback

Type

Avoi

ded

Deat

hs

(

Pop

ulati

on)

economic

benefits

analysis $

Alzheimers

disease 2010 121 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 9 12000

Diseases of the

heart 2010 470 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 35 35000

Influenza and

neumonia 2010 242 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 18 42500

Acute bronchitis

and bronchiolitis 2010 349 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 26 95000

Chronic lower

respiratory

diseases 2010 161 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 12 4500

$1 295000

PM25-related Mortalities Based on BenMAP-CE Estimate in 2010 Base Year with change in the concentrations levels

Health and Economic Benefits associated with the Response of PM25 Emission between

Base Year 2010 Increasing 7 Ugm3

Cause of death year 2010

Population

Affected

Deaths

avoided by

attaining 195

μgm3

standard

Background

Concentrati

on

Pollut

ant

Rollback

Type

Avoided

Deaths (

Populatio

n)

econo

mic

Unben

efits

analysi

s

Alzheimers

disease 2010 4524 195 PM25

25

microgmAcircsup3

Rollback 19 150000

Diseases of the

heart 2010 20358 195 PM25

25

microgmAcircsup3

Rollback 135 450000

Influenza and

neumonia 2010 126672 195 PM25

25

microgmAcircsup3

Rollback 38 525000

Acute bronchitis

and bronchiolitis 2010 162864 195 PM25

25

microgmAcircsup3

Rollback 36 122000

Chronic lower

respiratory

diseases 2010 99528 195 PM25

25

microgmAcircsup3

Rollback 12 650000

Conclusions

An excellent Pearson Correlation was established to analyze the relationship in the relative risks of hospitalization of Respiratory(RD) and cardiovascular (CVD) associated with ambient exposure caused by traffic emission in relation to their size andspecific sources of emission on different scenarios interior a border Urban Rural Urban restricted access (freeways andinterstates)

A significant correlation of PM1025 exposure from mobile emission and hospital admissions for selected Respiratory (RD) andcardiovascular (CVD) diagnoses was established The results showed that PM emissions in urban restricted access (freeways andinterstates) is mainly caused by traffic Therefore people living close to highways are more exposed higher vehicular emissions

Conclusions

We found statistically significant associations between mobile PM25 caused by traffic emission with Respiratory and Cardiovascular Diseases in the study areaSubsequently a correlation between cardio-respiratory mortality is established

A significant correlation of PM1025 exposure from mobile emission and hospital admissions for selected Respiratory (RD) and cardiovascular (CVD) diagnoses isestablished The results showed that PM emissions in urban restricted access (freeways and interstates) is mainly caused by traffic Therefore people living close tohighways receive higher vehicular emissions

The table shows the percentage of PM mobile exposure in the analyzed areas contributing to increase the risk of Respiratory and Cardiovascular Diseases

An examination was conducted of the synoptic and local meteorology for the June 2006 ozone episode using the WRF model to determine how meteorological parametersinfluence the formation transport and dispersion of ozone in the PdN The predominant synoptic feature of the ozone event day was the expansion intensification and slowprogression of an upper-level ridge of high pressure The high ozone episodes are associated with highly stable atmospheres strong temperature inversions with low mixingheights and therefore low mixing volumes Under these conditions emissions such as NOx lead to highly polluted conditions that favor ozone formation

BenMAP Conclusions

We have estimated the number and economic value of health impacts resulting

from changes in air pollution concentrations of PM 25 in the PdN region

Reduction of Pm 25 4 UGm3= Avoided 213 cases respiratory cardiovascular

diseses and Economic Benefits associated with the Response of PM25 Emission + $

1295000

Increase of PM25 7 ugm3 = increasing Dies= 326 economic Unbenefits= 2345000$

Bibliography

1 Dockery DW Pope CAI Xu X Spengler JD Ware JH Fay ME Ferris BG Speizer FE An association between air pollution and mortality in six US cities N Engl J Med 3291753ndash1759 (1993)

2 Samet JM Dominici F Curriero FC Coursac I Zeger SL Fine particulate air pollution and mortality in 20 US cities 1987ndash1994 N Engl J Med 3431742ndash1749 (2000)

3 Nel AE Diaz-Sanchez D Li N The role of particulate pollutants in pulmonary inflammation and asthma evidence for the involvement of organic chemicals and oxidative stress Curr Opin Pulm Med 20017 20ndash26

4 Westerholm R Karl-Erik E Exhaust emissions from lightand heavy-duty vehicles chemical composition impact of exhaust after treatment and fuel parameters Environ Health Perspect 102(suppl 4)13ndash23 (1994)

5 Bascom R Bromberg P Costa D Delvin R Dockery D Frampton M Lambert W Samet J Speizer F Utell

6 Health effects of outdoor air pollution Am J Respir Crit Care Med 1533ndash50 (1996)

7 Chow JC Watson JG Frazier CA Egami RT Goodrich A Ralph C Spatial and temporal source contributions to

8 PM10 and PM25 in Reno NV In PM-10 Implementation of Standards Transactions An APCAEPA International Speciality Conference San Francisco CA (Mathal CV Stonefield DH eds) PittsburghAPCA 1988439ndash457

9 overview In Particulate Matter Health and Regulatory Issues VIP-49 Proceedings of an International Specialty Conference 4ndash6 April 1995 Pittsburgh PA PittsburghAir and Waste Management Association 1995577ndash598

10 Kunzli N Kaiser R Medina S Studnicka M Chanel O

11 Filliger P Herry M Horak F Jr Puybonnieux-Texier V Quenel P et al Public-health impact of outdoor and traffic- related air pollution a European assessment Lancet 356795ndash801 (2000)

Bibliography

1 Sioutas C Delfino RJ Singh M Exposure assessment for atmospheric ultrafine particles (UFP) and implications in epidemiological research Environ Health Perspect 2005113947ndash955

2 Mosleh M Blau PJ Dumitrescu D (2004) Characteristics and morphology of wear particles from laboratory testing of disc brake materials Wear 2561128ndash1134

3 Kuumlnzli N et al (2000) Public-health impact of outdoor and traffi c-related air pollution a European assessment Lancet 356(9232)795ndash801

4 Dora C Phillips M eds (2000) Transport environment and health Copenhagen WHO Regional Office for Europe (WHO Regional Publications European Series No 89 httpwwweurowhointdocumente72015pdf accessed 26 November 2004)

5 Westerholm R Karl-Erik E Exhaust emissions from lightand

6 heavy-duty vehicles chemical composition impact of exhaust after treatment and fuel parameters Environ Health Perspect 102(suppl 4)13ndash23 (1994)

7 Fauser Tjell Mosbaek pigegaard Quantification of tire-Tread particles using extractable Organic Zinc as a Tracer Rubber Chemistry and Technology 1999 969Table shows some literature estimates of the contribution of tire wear to PM10 in air (Panko et al 2013) Gustafsson M Blomqvist G Gudmundsson A Dahl A Swietlicki E Bohgard M Lindbom J Ljungman A

8 Chen Y Shah N Huggins FE and Huffman GP (2006) Microanalysis of Ambient Particles from Lexington Ky by Electron Microscopy Atmos Environ 40 651ndash663

9 Donaldson K Tran CL Jimenez LA Duffin R Newby DE and Mills N (2005) Combustion-derived Nanoparticles A Review of Their Toxicology Following Inhalation Exposure Part Fibre Toxicol 2 10ndash23

10 Su D Serafino A Muller JO Jentoft RE Schlogl R and Fiorito S (2008) Cytotoxicity and Inflammatory Potential of Soot Particles of Low-emission Diesel Engines Environ Sci Technol 42 1761ndash1765

11 Maier KL Alessandrini F Beck-Speier I Hofer TPJ Diabatґe S Bitterle E Stoger T and Jakob T (2008) Health Effects of Ambient Particulate Matter-Biological Mechanisms and Inflammatory Responses to in Vitroand in Vivo Particle Exposures Inhalation Toxicol 20 319ndash337

Page 23: Studies of Air Pollutants and their Impact on Respiratory and ...€¦ · Ascarate Park C37 Monitoring Station: The National Ambient Air Quality Standard (NAAQS) for PM 10 and 2.5

Performance Evaluation

01020304050

Ju

ne

137

130

0

190

0

10

0

Ju

ne

157

130

0

190

0

10

0

Ju

ne

187

130

0

190

0

10

0

Tem

pe

ratu

re (⁰C

)

Local time (Hrs)

C41 June 13-19 2006

WRF_temperature

(⁰C)

TCEQ_temperature

(⁰C)

0

50

100

150

June1

37

100

0

130

0

160

0

190

0

220

0

10

0

40

0

June1

57

100

0

130

0

160

0

190

0

220

0

10

0

40

0

June1

87

100

0

130

0

160

0

190

0

220

0

10

0

40

0Ozo

ne

(pp

b)

Local time (Hrs)

C41 June 13-19 2006

CAMx_ozone (ppbV) TCEQ_ozone (ppb)

0

10

20

30

40

50

June1

37

100

0

130

0

160

0

190

0

220

0

10

0

40

0

June1

57

100

0

130

0

160

0

190

0

220

0

10

0

40

0

June1

87

100

0

130

0

160

0

190

0

220

0

10

0

40

0

Rel

ativ

e h

um

idit

y (

)

Local time (Hrs)

C41 June 13-19 2006

WRF_rh () TCEQ_relative humidity ()

0

5

10

15

20

June

137 10

13

16

19

22 1 4

June

157 10

13

16

19

22 1 4

June

187 10

13

16

19

22 1 4W

ind

sp

eed

(m

sLocal time(Hrs)

C12 June 13-192006

WRF_wind speed (ms) TCEQ_ wind speed (ms)

Methodology

Medical Data The data by weekly monthly and year for daily emergency room and hospital admission for the respiratory

infections (RD) and cardiovascular diseases (CVD) was extracted from hospitals records located in the El PdN

the system includes data on type of admission primary and secondary causes of admissionRESPIRATORY DISEASE

Bronquitis amp Chronic Bronchitis 466 - 4661 491 - 4919

Asthma 463 - 4939

Emphysema 492

Respiratory failure 51881

HEART DISEASE

Accute Myocardial Infarction 410

Coronary Athersclerosis 4140

Other Ischemic Heart Disease 411-4139 4141-4149

Cardiac Dyshythmias 427

Essential hypertension 401

Acute myocardial infarction 410

Congestive Heart Failure 4280 4282-4284

Hypertensive heart disease 402

Table 1 ICD -9 Codes for Respiratory and Cardiovascular Diseases

0

50

100

150

200

250

300

Wee

k 1

Wee

k 2

Wee

k 3

Wee

k 4

Wee

k 5

Wee

k 6

Wee

k 7

Wee

k 8

Wee

k 9

Wee

k 1

0

Wee

k 1

1

Wee

k 1

2

Wee

k 1

3

Wee

k 1

4

Wee

k 1

5

Wee

k 1

6

Wee

k 1

7

Wee

k 1

8

Wee

k 1

9

Wee

k 2

0

Wee

k 2

1

Mo

rb

idit

y D

isch

arg

e fo

r a

ll R

esp

ira

tory

Dis

ease

IC

D-9

(

Ast

hm

aB

ro

nch

itis

)

Weekly Morbidity Discharges of all the Listed Diagnoses for All

Respiratory Disease During WinterSpring 2010

Asthma-Bronchitis

EPA MOVES Model for Estimating Emission

Inventories

Motor Vehicle Emission Simulator (MOVES 2010b) will be configuredin The El Paso North Region for Calculate five categories of PM10

PM25 total Emission inventories from all on-road traffic over a

variety of scales within periods of time selected weeks months

and years

Moves (Motor Vehicle Emission

Simulator)

The emission model is develop using the current equation to calculate direct traffic emissions from

vehicles in the form of PM is

Eext annual emissions are measured in grams of miles traveled by the vehicle (gVMT )

SL is the road surface loading in (gm2)

W is the average weight in tons of the vehicles on the road

K is the particle size multiplier for particle size range (eg gVMT for PM10 when using grams and miles)

P is the 7 number of wet days with at least 0254 mm of precipitation during the averaging period

N is the number of years considered in the averaging period

C is the particle size specific emissions factor in units of interest vehicle direct exhaust brake wear and tirewear

Modeling Simulation Domain and Emissions Scenarios

For simulations of mobile air quality emission inventories a motor vehicle emission simulator EPA (MOVES 2014a) was used

The modeling use input factors divided into seven section

parameters

On-Road Inventory local data

input

Scale

Geographic Bounds

Traffic intensity

Vehicle Type

Pollutants

Road Type

Fuel Types

Figure Source EPA US Environmental Protection Agency 2012- Moves 2010b Model

EPA Moves 2014a The modeling used input factors divided into six section

parameters On-Road Inventory local data input

Geographic Domains CountyNonattainment Area

Vehicle-Miles Traveled (VMT) is the total number of miles driven by all vehicles withina given time period and geographic area

Average speed range from 25 miles per

hour to 65 miles per hour

Vehicle Classes Motorcycle PassengerCarTruks light-duty Commercial Truck(6001-8500 lbs) Buses heave-duty trucksRefuse trucks School Bus Single UnitShort Haul-truck Single Unit Long Haul-truck Long Haul Truck Heavy-DutyVehicles (26001-33000 lbs)

Pollutants

Road TypeRural restricted Acces(Freeways and interstates) Rural and Restricted Acces Urban Restricted Acces Off-Network

Fuel Types Gasoline Diesel Fuel

Specific Road Types

Two road types for running emission from the MOVES can be

selected

(freeways and interstates)

Interior urban Urban

Figure Source EPA US Environmental Protection Agency 2012- Moves 2010b Model

VehiclesEquipment

This panel show which on-road vehicles will be modeled

Figure Source EPA US Environmental Protection Agency 2012- Moves 2010b Model

Long haul truck Short haul truck Inercity bus Ligth comercial truck

Passenger car Passenger truck Refuse truck

School bus Single unit long haul-truck

Single unit short haul-truck

Transit bus

Motor home

Motorcycle

Based on Department of Transportation Highway MOVES will Estimates Traffic

Emissions from Cars Trucks amp Motorcycles

Output Data Moves 2014a

Inventories of PM 10 25 Mobile Emission from all

on-Road Traffic

Exhaust Emission PM 10 25 gramsmile

Brake Wear Emission PM 10 25 gramsmile

Tire wear Emission PM 10 25 gramsmile

Date of Vehicle miles traveled (VMT) for

Day Week Month Year

Total Vehicle population

Vehicle age distribution

Simulation of Mobile Emission in the El PdN Region Zip Code 79905

Figure Total Emissions from road traffic in El Paso TX Area were estimated for PM10

Exhaust and Non exhaust emission in kilogramsmonth (Source EPA MOVES 2014a)

0

10000

20000

30000

40000

50000

PM

10 k

gM

on

th

Months

Monthly PM 10 Exhaust and Non-Exhaust Mobile Emissions 2010

On-Road Urban Restricted Area Zip Code 79905

Primary Exhaust PM 10 (kg) Primary PM 10 Brakewear (kg)

Primary PM 10 Tirewear (kg)

05000

100001500020000250003000035000400004500050000

PM

25

kg

Mo

nth

Months

Monthly PM 25 Exhaust and Non-Exhaust Mobile Emission 2010

On-Road Urban Restricted Area Zip Code 79905

Primary Exhaust PM 25 (kg) Primary PM 25 Brakewear (kg) Primary PM 25Tirewear (kg)

Figure Total Emissions from road traffic in El Paso TX Area were estimated for PM25

Exhaust and Non exhaust emission in kilogramsmonth (Source EPA MOVES 2014a)

Total Emissions from Road Traffic in El Paso County PM1025 Exhaust and Non exhaust Emission in kilogramsmonth

Taking the interests to the health risks related to PM 1025 mobile emission were simulated

Exhaust and Non-exhaust emissions contribute almost equally to total traffic-related PM1025 Emissions (Querol et al 2004 Bukowiecki et al 2009a Amato et al 2011)

Monthly PM 10 25 Exhaust and Non-Exhaust (BrakewearTirewear) Mobile

Emission 2010 On-Road Urban Restricted Area Zip Code 79905

Figure Total Emissions from road traffic in El Paso TX Area were estimated for PM10 25 Exhaust and Non Exhaust mobile

emission in kilograms per month (Source EPA MOVES)

0

10000

20000

30000

40000

50000

January February March April May June July August September October November December

PM

10

25

(K

ilog

ram

s)

Months

Summary- Monthly PM 10 25 Exhaust and Non-Exhaust Mobile

Emission 2010 On-Road Urban Restricted Area Zip Code 79905

Primary Exhaust PM 10 Primary PM 10 Brakewear Primary PM 10 Tirewear

Primary Exhaust PM 25 Primary PM 25 Brakewear Primary PM 25Tirewear

Exhaust Emissions PM1025 is reaching maximum emission 48000-42000 thousand of Kgmonth followedby Brake wear 29000-5000 thousand kgmonth and Tire wear with 9000-2000 kgmonth The results showthat the emissions of PM derived mainly from Exhaust and Brake are significantly higher in Urban Area

Annual Contribution of Mobile Emission PM 1025 (Kg) Zip Code 79905 El

Paso County 2010

Total Primary

Exhaust _PM10

39

Total Primary

Exhaust _PM25

36

Brakewear

particulate_PM10

18

Tirewear

particulate_PM10

4

Brakewear

particulate_PM25

2

Tirewear

particulate_PM25

1

0

5

10

15

20

25

30

35

40

45

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53

Fig Annual Average PM10 Concentrations at the

Chamizal C41 Station and PM1025 mobile

Concentration Zip code 79905

PM10 TCEQ (μgm3) Total Mobile Emission PM10 (Ugm3)

Fig Exhaust Emission is Contributing Approximately 74 of total

PM1025 Mobile Emissions following of Brake wear with 20 and Tire

wear with 5

Annual Average PM1025 ugm3 Mobile Emissions (Moves) 26 Chamizal C41

Monitoring Station (TCEQ Chamizal Station )

Predicting Mobile Emission and VTM

Estimation The PdN Region 2010

44E+09

46E+09

48E+09

5E+09

52E+09

54E+09

56E+09

58E+09

6E+09

62E+09

0

50000

100000

150000

200000

250000

300000

350000

20

10

20

11

20

12

20

13

20

14

20

15

20

16

20

17

20

18

20

21

20

22

20

23

20

24

20

25

20

26

20

27

20

28

20

29

20

30

EX

HA

US

T

EM

ISS

ION

MO

BIL

E (

KG

YE

AR

)

YEARS

Predict ing Mobile Exhaust Emission and VTM

Estimation

2010 - 2030 e l PdN Area

Total_ Exhaust PM10 Total_ Exhaust PM25 Distance (Miles)

Fig Predicting Mobile Exhaust PM1025 (kgMonth) Emission and VTM Estimation 2010

- 2030 el PdN Area

44E+09

46E+09

48E+09

5E+09

52E+09

54E+09

56E+09

58E+09

6E+09

62E+09

0

5000000

10000000

15000000

20000000

25000000

30000000

20

10

20

11

20

12

20

13

20

14

20

15

20

16

20

17

20

18

20

21

20

22

20

23

20

24

20

25

20

26

20

27

20

28

20

29

20

30

EX

HA

US

T

EM

ISS

ION

MO

BIL

E (

KG

YE

AR

)

YEARS

Predict ing Mobile Exhaust Emission and

VTM Estimation

2010 - 2030 e l PdN Area

CO NO2 NO NOx Distance

Fig Predicting Mobile Exhaust Emission and VTM Estimation

2010 - 2030 el PdN Area in El Paso TX Area were estimated for

Total CO NOx NO2 NO emission in kilograms per year

(Source EPA MOVES 2014a model)

The simulated Exhaust emissions in the future years shows a trend of reduction of this type of emissions in the

future years one factor should be the new hybrid technology is increasing by 476 since 2010 to 2015 and

use of catalytic converters diesel particulate filters and improved fuels and engines Non-exhaustive sources

will increase in the coming years because there is no control in the material of manufacture composed by Fe

Cu and Mn also not to be able to reduce the number of events of braking (Accelerations and decelerations)

45E+09

5E+09

55E+09

6E+09

65E+09

0

50000

100000

150000

200000

250000

201

0

201

1

201

2

201

3

201

4

201

5

201

6

201

7

201

8

202

1

202

2

202

3

202

4

202

5

202

6

202

7

202

8

202

9

203

0

NO

N-

EX

HA

US

T

EM

ISS

ION

MO

BIL

E

(KG

YE

AR

)

YEARS

Predicting Non Exhaust Mobile

Emission and VTM Estimation

2010 - 2030 el PdN Area

Brake_PM10 Tire_PM10 Distance (Miles)

Fig Predicting Mobile Exhaust PM1025 (kgMonth) Emission and VTM

Estimation 2010 - 2030 el PdN Area

Daily Avg PM1025

Levels of PM Mobile Emission Non-Exhaust -Rush Hour Periods Fall 2010 Zip Code

79905

00

100

200

300

400

500

600

Mo

bil

e P

M1

0 (k

g)

Rush Hours

Daily Avg PM10

Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush Hours

Periods 2010 Zip Code 79905

Total Primary Exhaust

_PM10 WinterSpring

Brakewear

particulate_PM10

WinterSpringTirewear particulate_PM10

WinterSpring

Total Primary Exhaust

_PM10 Summer

Brakewear

particulate_PM10 Summer

Tirewear Particulate_PM10

Summer

Total Primary Exhaust

_PM10 Fall

Brakewear

particulate_PM10 Fall

Tirewear particulate_PM10

Fall

00

50

100

150

200

250

300

350

Mo

bil

e P

M2

5 (k

g)

Rush hours

Daily Avg PM25

Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush

Hours Periods 2010 Zip Code 79905

Total Primary Exhaust _PM25

WinterSpring

Brakewear Particulate_PM25

WinterSpring

Tirewear particulate_PM25

WinterSpring

Total Primary Exhaust _PM25

Summer

Brakewear particulate_PM25

Summer

Tirewear particulate_PM25

Summer

Total Primary Exhaust _PM25

Fall

Brakewear particulate_PM25

Fall

Tirewear particulate_PM25

Fall

Figure Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush Hours Figure Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush Hours

GIS EMISSIONS INVENTORY SYSTEM A geographic information system (GIS) was used to established geographic scenarios with processed images of seasonal mobile

emissions in the PdN region Seasonal mapping is visualized for different types of pollutants Brakewear Exhaust and Tyrewear

Fg Graphics of GIS and Seasonal mobile Emission of particulate matter emission inventory Seasonal emission simulations were performed in kilograms and five contributing inputs factors were identified for

modeling 1) On the composition of the particulate material from different sources such as Exhaust and Non exhaust (Brake wear Tirewear) 2) The Vehicles Equipment clasification were selected according to

the use of gasoline and diesel fuel (motorcycle passenger car Light Duty Vehicles Trucks refuse truck Light Duty Vehicles Light Commercial Truck Light Duty Vehicles School Bus)

Winter Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

120354 67860 19065

Spring Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

139767 86702 24463

Summer Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

94747 62481 17630

Fall Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

75510 45542 12596

251 Descriptive Statistics Data Analysis

Weekly Correlation Analysis of Mobile Emission PM10 (Exhaust-Non-Exhaust) and Respiratory

Diagnoses WinterSpring Summer and Fall 2010

0

2

4

6

8

10

0

50

100

150

200

250

300

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21

Mo

rbid

ity

Dis

ch

arg

e

for

all R

esp

ira

tory

Dis

ea

se

ICD

-9

(A

sth

ma

-Bro

nc

hitis

)

WinterSpring Week

Weekly Avg Mobile PM10 Concentrations during

WinterSpring 2010 and its Influence on Respiratory

Diagnoses

Zip Code 79905

Total Medical data ZIP Code 79902

Total Mobile Emission PM10 (Ugm3)

0

1

2

3

4

5

6

7

0

20

40

60

80

100

Mo

rbid

ity

Dis

ch

arg

e

for

all R

esp

ira

tory

Dis

ea

se

ICD

-9

(Ast

hm

aB

ron

ch

itis

)

Weekly Avg Mobile PM10 Concentrations during

Summer 2010 and its Influence on Respiratory

Diagnoses

Summer 2010 Zip Code 79905

Total Mobile Emission PM10

Hospital Admission (Asthma-Bronchitis)

0

2

4

6

8

10

12

0

20

40

60

80

100

120

140

160

180

200

Mo

rbid

ity

dis

ch

arg

es

for

all r

esp

ira

tory

dis

ea

se

Weekly Avg Mobile PM10 Concentrations

during Fall 2010 and its Influence on Respiratory

Diagnoses

Zip Code 79905

Total Medical data ZIP Code 79902

Total Mobile Emission PM10 (Ugm3)

Mobile(Exhaust-Non-

Exhaust) PM10 and

Asthma-Bronchitis)

Linear R

Square

WinterSpring 734 ndash 39

Summer 614 ndash 32

Fall 548 -29

PM10 Mobile emission (Exhaust-Non-Exhaust)contributed significantly

association to the incidence of RD

Weekly Correlation Analysis of PM 25 Mobile Emission (Exhaust-Non-Exhaust)

and Cardiovascular Diagnoses WinterSpring Summer and Fall 2010

0010203040

00500

100015002000

Wee

k 1

Wee

k 2

Wee

k 3

Wee

k 4

Wee

k 5

Wee

k 6

Wee

k 7

Wee

k 8

Wee

k 9

Wee

k 1

0

Wee

k 1

1

Wee

k 1

2

Wee

k 1

3

Wee

k 1

4

Wee

k 1

5

Wee

k 1

6

Wee

k 1

7

Wee

k 1

8

Wee

k 1

9

Wee

k 2

0

Wee

k 2

1

Morb

idit

y d

isch

arg

es f

or

all

card

iovasc

ula

r d

isea

se

Weekly Avg PM25 Mobile Concentrations during

WinterSpring 2010 and its Influence on all Heart

Diagnoses

Zip Code 79905

Total All Heart Disease PM 25 mobile (μgm3)

0010203040

00

500

1000

1500

Mo

rbid

ity

dis

ch

arg

es

for

all

ca

rdio

va

scu

lar

dis

ea

se

Weeks

CORRELATION BETWEEN MOBILE PM25 ugm3

EXPOSURE TO HEART DISEASES SYMPTOMS

SUMMER SEASON 2010

Total All Heart Disease PM 25 mobile (μgm3)

Figure Statistical Analyses of the Relationship Between PM25 Caused by Traffic Emission( 26 of total Emission) with Heart diseases Source Hospital Admissions for Asthma Acute Bronchitis and Heart diseases in El Paso County zip code 79905 from Texas Health Care

Information Council in Austin Texas (Texas Health Care Information Council 2000)

00

10

20

30

40

0

50

100

150

We

ek 3

6

We

ek 3

7

We

ek 3

8

We

ek 3

9

We

ek 4

0

We

ek 4

1

We

ek 4

2

We

ek 4

3

We

ek 4

4

We

ek 4

5

We

ek 4

6

We

ek 4

7

We

ek 4

8

We

ek 4

9

We

ek 5

0

We

ek 5

1

We

ek 5

2

We

ek 5

3

Mo

rbid

ity

dis

ch

arg

es

for

all

ca

rdio

va

scu

lar

dis

ea

se

CORRELATION BETWEEN MOBILE PM25 ugm3

EXPOSURE TO HEART DISEASES SYMPTOMS FALL

SEASON 2010

Total All Heart Disease PM 25 mobile (μgm3)

Mobile(Exhaust-

Non-Exhaust)

PM10 and

Asthma-

Bronchitis)

Linear R

Square

WinterSpring 833 -42

Summer 620 -32

Fall 501-26

PM10 Mobile

emission (Exhaust-

Non-

Exhaust)contribut

ed significantly

association to the

incidence of CVD

Diseases

Monthly Brake Mobile Emission PM1025 kg During year 2010 and its Influence on

Respiratory Diagnoses Zip Code 79905

00200040006000800010000

010000200003000040000

PM

10

Mo

bile

(K

g)

Months

Monthly Brake Mobile Emission PM10 kg during year

2010 and its Influence on Respiratory Diagnoses

Zip Code 79905

Primary PM 10

Brakewear 00100020003000400050006000

0

1000

2000

3000

4000

PM

25

Mo

bil

e(K

g)

Months

Monthly Brake Mobile Emission PM25 during

year 2010 and its Influence on Heart Diagnoses

Zip Code 79905

Primary PM 25

Brakewear

Heart Diseases

Hospital

Admission

Brake Mobile Emission

PM10 kg Asthma-

Bronchitis)

Brake Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=969 Linear Square R=856

Monthly Mobile Exhaust Emission PM1025 During year 2010 and its Influence on

Respiratory Diagnoses Zip Code 79905

0

200

400

600

800

1000

0

10000

20000

30000

40000

50000

1 3 5 7 9 11

PM

10

(K

g m

on

th)

Months

Monthly Mobile Exhaust Emission PM10 during

year 2010 and its Influence on Respiratory

Diagnoses

Zip Code 79905

Primary Exhaust

PM 10

Respiratory Disease

(Asthma

Bronchitis) Hospital

Admission

0

100

200

300

400

500

600

0

10000

20000

30000

40000

50000

1 2 3 4 5 6 7 8 9 101112

PM

25

(K

g m

on

th)

Months

Monthly Exhaust Mobile Emission PM25 during

year 2010 and its Influence on Heart Diagnoses

Zip Code 79905

Primary Exhaust PM

25

Heart Diseases

Hospital Admission

Exhaust Mobile Emission

PM10 kg Asthma-

Bronchitis)

Exhaust Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=929 Linear Square R=831

Monthly Tire wear Mobile Emission PM1025 During year 2010 and its Influence on Heart

Diagnoses Zip Code 79905

0

100

200

300

400

500

600

700

800

900

0

1000

2000

3000

4000

5000

6000

7000

8000

9000

1 2 3 4 5 6 7 8 9 10 11 12

PM

10

(K

g m

on

th)

Months

Monthly Tirewear Mobile Emission PM10 during year 2010

and its Influence on Heart Diagnoses

Zip Code 79905

Primary PM 10 Tirewear

Mobile Emission

Respiratory Disease

(Asthma Bronchitis)

Hospital Admission

0

100

200

300

400

500

600

0

200

400

600

800

1000

1200

1400

1 2 3 4 5 6 7 8 9 10 11 12

PM

25

(K

g m

on

th)

Months

Monthly Tirewear Mobile Emission PM25 during year 2010

and its Influence on Respiratory Diagnoses

Zip Code 79905

Primary PM 25Tirewear

Mobile Emission

Heart Diseases Hospital

Admission

Exhaust Mobile Emission

PM10 kg Asthma-

Bronchitis)

Exhaust Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=769 Linear Square R=715

Dona Ana County Zip Codes

88021880278807288048

Primary

Exhaust

PM 10 Zip

code

79905

Total

Primary

Exhaust

PM10

Dona Ana

Primary

Exhaust

PM 25 Zip

Code

79905

Total

Primary

Exhaust

PM25

Dona Ana

Series1 430378 111773 391915 102123

0

100000

200000

300000

400000

500000

AX

IS T

ITLE

Annual Comparison of the Mobile

Exhaust Emissions El Paso County

and Dona Ana 2010

Primary

PM 10

Brakewea

r Zip code

79905

Brakewea

r

particulat

e_PM10

Dona Ana

Primary

PM 10

Tirewear

Zip code

79905

Tirewear

particulat

e_PM10

Dona Ana

Series1 262585 48573 73754 11864

050000

100000150000200000250000300000

AX

IS T

ITLE

Annual Comparison of the Mobile

Brakewear Emissions El Paso County

and Dona Ana 2010

Figure Comparison of the Annual Mobile Emissions

of Primary PM10 Non-Exhauts (Brake ) from Dona

Ana County New Mexico and El Paso Texas Units

in KgMonth

Figure Comparison of the Annual Mobile Emissions

of Primary PM10-Exhauts Emission from Dona Ana

County New Mexico and El Paso Texas Units in

KgMonth

Primary

PM 25

Brakewe

ar Ziphellip

Brakewe

ar

particula

te_PMhellip

Primary

PM

25Tirewe

ar Ziphellip

Tirewear

particula

te_PM25

Donahellip

Series1 32645 6071 10919 1779

0

10000

20000

30000

40000

AX

IS T

ITLE

Annual Comparison of the

Mobile Exhaust Emissions El Paso

County and Dona Ana 2010

Figure Comparison of the Annual Mobile Emissions

of Primary PM10-Exhauts Emission from Dona Ana

County New Mexico and El Paso Texas Units in

KgMonth

Monthly Mobile Emission PM1025 kg During year 2006

and its Influence on Respiratory Diagnoses Dona Ana

County Zip Code 880218802788072

0

100

200

300

0

5000

10000

15000

Axi

s Ti

tle

Axis Title

Monthly Mobile Exhaust Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Total PrimaryMobile Exhaust_PM10

All Respiratory ICD-9 (AsthmaBronchitis)

050100150200250300

010002000300040005000

Axi

s Ti

tle

Axis Title

Monthly Mobile Brake Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Brakewearparticulate_PM10

All RespiratoryICD -9 (AsthmaBronchitis)

050100150200250300

0200400600800

10001200

Axi

s Ti

tle

Axis Title

Monthly Mobile Tirewear Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Tirewearparticulate_PM10

All Respiratory ICD -9 (AsthmaBronchitis)

Mobile Exhauts

Emission PM10

kg Asthma-

Bronchitis)

Brake Mobile

Emission PM10

kg and Heart

Diagnoses

Tirewear Mobile

Emission PM10

kg and Heart

Diagnoses

Linear Square

R= 951

Linear Square

R=625

Linear Square

R=525

Mobile Exhauts

Emission PM25

kg Asthma-

Bronchitis)

Brake Mobile

Emission PM25

kg and Heart

Diagnoses

Tirewear Mobile

Emission PM25

kg and Heart

Diagnoses

Linear Square

R= 986

Linear Square

R=691

Linear Square

R=601

Results

The results showed that mobile PM emissions in the urban areas close to urban Road and highways is putting at risk public health

and the proportion of diseases attributable to this exposure is potentially large

Brake wear emissions is much lower in freeways due to significantly reduced number of braking events while tire wear is much

higher in areas where studded tires are used The emission of exhaust gases are much higher in areas where there is a high

vehicular traffic

Brake Mobile

Emission PM10 kg

Asthma-Bronchitis)

Brake Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square

R=969

Linear Square

R=856

Exhaust Mobile

Emission PM10 kg

Asthma-Bronchitis)

Exhaust Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square

R=929

Linear Square

R=831

Tirewear Mobile

Emission PM10 kg

Asthma-Bronchitis)

Tirewear Mobile

Emission PM25 kg

and Heart Diagnoses

Linear Square R=769 Linear Square R=715

Brake Mobile

Emission PM10 kg

and Heart

Diagnoses

Brake Mobile

Emission PM25 kg

and Heart

Diagnoses

Exhaust Mobile

Emission PM10 kg

Asthma-Bronchitis)

Linear Square

R=625

Linear Square

R=691

Linear Square R=

951

Exhaust Mobile

Emission PM25 kg

Asthma-

Bronchitis)

Tire wear Mobile

Emission PM10 kg and

Heart Diagnoses

Tirewear Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square R=

986

Linear Square R=525 Linear Square

R=601

El Paso County

Dona Ana

County

BenMAP-CE

In this analysis the Program of Mapping and Analysis of Environmental Benefits-Community Edition

(BenMAP-CE) was used to Estimate the number and economic value of health impacts resulting from changes

in air pollution PM 25 Ugm3 in The El Paso Area

Health and Economic Benefits associated with the Response of PM25 Emission between

Base Year 2010

Number of Mortalities in 2010 Base Year Based on El Paso County Texas Department of State Health Services

Number of Mortalities in 2010 Base Year Based on El Paso County Texas

Department of State Health Services

cause of death

year

2010

Populatio

n

Affected

Backgro

und

Concentr

ation Pollutant

Rollback

Type

Avoided

Deaths

(

Populatio

n)

alzheimers disease 2010 40716 125 PM25

25

microgmAcircsup3

Rollback 9

diseases of the

heart 2010 15834 125 PM25

25

microgmAcircsup3

Rollback 35

influenza and

neumonia 2010 81432 125 PM25

25

microgmAcircsup3

Rollback 18

acute bronchitis

and bronchiolitis 2010 117624 125 PM25

25

microgmAcircsup3

Rollback 26

chronic lower

respiratory diseases 2010 54288 125 PM25

25

microgmAcircsup3

Rollback 12

The Basin-wide decrease in 4 ugm3 PM25 concentration after this

reduction control

Cause of death year 2010

Populatio

n

Affected

Background

Concentrati

on

Reduc

cion

scena

rio Polluta

nt

Rollback

Type

Avoi

ded

Deat

hs

(

Pop

ulati

on)

economic

benefits

analysis $

Alzheimers

disease 2010 121 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 9 12000

Diseases of the

heart 2010 470 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 35 35000

Influenza and

neumonia 2010 242 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 18 42500

Acute bronchitis

and bronchiolitis 2010 349 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 26 95000

Chronic lower

respiratory

diseases 2010 161 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 12 4500

$1 295000

PM25-related Mortalities Based on BenMAP-CE Estimate in 2010 Base Year with change in the concentrations levels

Health and Economic Benefits associated with the Response of PM25 Emission between

Base Year 2010 Increasing 7 Ugm3

Cause of death year 2010

Population

Affected

Deaths

avoided by

attaining 195

μgm3

standard

Background

Concentrati

on

Pollut

ant

Rollback

Type

Avoided

Deaths (

Populatio

n)

econo

mic

Unben

efits

analysi

s

Alzheimers

disease 2010 4524 195 PM25

25

microgmAcircsup3

Rollback 19 150000

Diseases of the

heart 2010 20358 195 PM25

25

microgmAcircsup3

Rollback 135 450000

Influenza and

neumonia 2010 126672 195 PM25

25

microgmAcircsup3

Rollback 38 525000

Acute bronchitis

and bronchiolitis 2010 162864 195 PM25

25

microgmAcircsup3

Rollback 36 122000

Chronic lower

respiratory

diseases 2010 99528 195 PM25

25

microgmAcircsup3

Rollback 12 650000

Conclusions

An excellent Pearson Correlation was established to analyze the relationship in the relative risks of hospitalization of Respiratory(RD) and cardiovascular (CVD) associated with ambient exposure caused by traffic emission in relation to their size andspecific sources of emission on different scenarios interior a border Urban Rural Urban restricted access (freeways andinterstates)

A significant correlation of PM1025 exposure from mobile emission and hospital admissions for selected Respiratory (RD) andcardiovascular (CVD) diagnoses was established The results showed that PM emissions in urban restricted access (freeways andinterstates) is mainly caused by traffic Therefore people living close to highways are more exposed higher vehicular emissions

Conclusions

We found statistically significant associations between mobile PM25 caused by traffic emission with Respiratory and Cardiovascular Diseases in the study areaSubsequently a correlation between cardio-respiratory mortality is established

A significant correlation of PM1025 exposure from mobile emission and hospital admissions for selected Respiratory (RD) and cardiovascular (CVD) diagnoses isestablished The results showed that PM emissions in urban restricted access (freeways and interstates) is mainly caused by traffic Therefore people living close tohighways receive higher vehicular emissions

The table shows the percentage of PM mobile exposure in the analyzed areas contributing to increase the risk of Respiratory and Cardiovascular Diseases

An examination was conducted of the synoptic and local meteorology for the June 2006 ozone episode using the WRF model to determine how meteorological parametersinfluence the formation transport and dispersion of ozone in the PdN The predominant synoptic feature of the ozone event day was the expansion intensification and slowprogression of an upper-level ridge of high pressure The high ozone episodes are associated with highly stable atmospheres strong temperature inversions with low mixingheights and therefore low mixing volumes Under these conditions emissions such as NOx lead to highly polluted conditions that favor ozone formation

BenMAP Conclusions

We have estimated the number and economic value of health impacts resulting

from changes in air pollution concentrations of PM 25 in the PdN region

Reduction of Pm 25 4 UGm3= Avoided 213 cases respiratory cardiovascular

diseses and Economic Benefits associated with the Response of PM25 Emission + $

1295000

Increase of PM25 7 ugm3 = increasing Dies= 326 economic Unbenefits= 2345000$

Bibliography

1 Dockery DW Pope CAI Xu X Spengler JD Ware JH Fay ME Ferris BG Speizer FE An association between air pollution and mortality in six US cities N Engl J Med 3291753ndash1759 (1993)

2 Samet JM Dominici F Curriero FC Coursac I Zeger SL Fine particulate air pollution and mortality in 20 US cities 1987ndash1994 N Engl J Med 3431742ndash1749 (2000)

3 Nel AE Diaz-Sanchez D Li N The role of particulate pollutants in pulmonary inflammation and asthma evidence for the involvement of organic chemicals and oxidative stress Curr Opin Pulm Med 20017 20ndash26

4 Westerholm R Karl-Erik E Exhaust emissions from lightand heavy-duty vehicles chemical composition impact of exhaust after treatment and fuel parameters Environ Health Perspect 102(suppl 4)13ndash23 (1994)

5 Bascom R Bromberg P Costa D Delvin R Dockery D Frampton M Lambert W Samet J Speizer F Utell

6 Health effects of outdoor air pollution Am J Respir Crit Care Med 1533ndash50 (1996)

7 Chow JC Watson JG Frazier CA Egami RT Goodrich A Ralph C Spatial and temporal source contributions to

8 PM10 and PM25 in Reno NV In PM-10 Implementation of Standards Transactions An APCAEPA International Speciality Conference San Francisco CA (Mathal CV Stonefield DH eds) PittsburghAPCA 1988439ndash457

9 overview In Particulate Matter Health and Regulatory Issues VIP-49 Proceedings of an International Specialty Conference 4ndash6 April 1995 Pittsburgh PA PittsburghAir and Waste Management Association 1995577ndash598

10 Kunzli N Kaiser R Medina S Studnicka M Chanel O

11 Filliger P Herry M Horak F Jr Puybonnieux-Texier V Quenel P et al Public-health impact of outdoor and traffic- related air pollution a European assessment Lancet 356795ndash801 (2000)

Bibliography

1 Sioutas C Delfino RJ Singh M Exposure assessment for atmospheric ultrafine particles (UFP) and implications in epidemiological research Environ Health Perspect 2005113947ndash955

2 Mosleh M Blau PJ Dumitrescu D (2004) Characteristics and morphology of wear particles from laboratory testing of disc brake materials Wear 2561128ndash1134

3 Kuumlnzli N et al (2000) Public-health impact of outdoor and traffi c-related air pollution a European assessment Lancet 356(9232)795ndash801

4 Dora C Phillips M eds (2000) Transport environment and health Copenhagen WHO Regional Office for Europe (WHO Regional Publications European Series No 89 httpwwweurowhointdocumente72015pdf accessed 26 November 2004)

5 Westerholm R Karl-Erik E Exhaust emissions from lightand

6 heavy-duty vehicles chemical composition impact of exhaust after treatment and fuel parameters Environ Health Perspect 102(suppl 4)13ndash23 (1994)

7 Fauser Tjell Mosbaek pigegaard Quantification of tire-Tread particles using extractable Organic Zinc as a Tracer Rubber Chemistry and Technology 1999 969Table shows some literature estimates of the contribution of tire wear to PM10 in air (Panko et al 2013) Gustafsson M Blomqvist G Gudmundsson A Dahl A Swietlicki E Bohgard M Lindbom J Ljungman A

8 Chen Y Shah N Huggins FE and Huffman GP (2006) Microanalysis of Ambient Particles from Lexington Ky by Electron Microscopy Atmos Environ 40 651ndash663

9 Donaldson K Tran CL Jimenez LA Duffin R Newby DE and Mills N (2005) Combustion-derived Nanoparticles A Review of Their Toxicology Following Inhalation Exposure Part Fibre Toxicol 2 10ndash23

10 Su D Serafino A Muller JO Jentoft RE Schlogl R and Fiorito S (2008) Cytotoxicity and Inflammatory Potential of Soot Particles of Low-emission Diesel Engines Environ Sci Technol 42 1761ndash1765

11 Maier KL Alessandrini F Beck-Speier I Hofer TPJ Diabatґe S Bitterle E Stoger T and Jakob T (2008) Health Effects of Ambient Particulate Matter-Biological Mechanisms and Inflammatory Responses to in Vitroand in Vivo Particle Exposures Inhalation Toxicol 20 319ndash337

Page 24: Studies of Air Pollutants and their Impact on Respiratory and ...€¦ · Ascarate Park C37 Monitoring Station: The National Ambient Air Quality Standard (NAAQS) for PM 10 and 2.5

Methodology

Medical Data The data by weekly monthly and year for daily emergency room and hospital admission for the respiratory

infections (RD) and cardiovascular diseases (CVD) was extracted from hospitals records located in the El PdN

the system includes data on type of admission primary and secondary causes of admissionRESPIRATORY DISEASE

Bronquitis amp Chronic Bronchitis 466 - 4661 491 - 4919

Asthma 463 - 4939

Emphysema 492

Respiratory failure 51881

HEART DISEASE

Accute Myocardial Infarction 410

Coronary Athersclerosis 4140

Other Ischemic Heart Disease 411-4139 4141-4149

Cardiac Dyshythmias 427

Essential hypertension 401

Acute myocardial infarction 410

Congestive Heart Failure 4280 4282-4284

Hypertensive heart disease 402

Table 1 ICD -9 Codes for Respiratory and Cardiovascular Diseases

0

50

100

150

200

250

300

Wee

k 1

Wee

k 2

Wee

k 3

Wee

k 4

Wee

k 5

Wee

k 6

Wee

k 7

Wee

k 8

Wee

k 9

Wee

k 1

0

Wee

k 1

1

Wee

k 1

2

Wee

k 1

3

Wee

k 1

4

Wee

k 1

5

Wee

k 1

6

Wee

k 1

7

Wee

k 1

8

Wee

k 1

9

Wee

k 2

0

Wee

k 2

1

Mo

rb

idit

y D

isch

arg

e fo

r a

ll R

esp

ira

tory

Dis

ease

IC

D-9

(

Ast

hm

aB

ro

nch

itis

)

Weekly Morbidity Discharges of all the Listed Diagnoses for All

Respiratory Disease During WinterSpring 2010

Asthma-Bronchitis

EPA MOVES Model for Estimating Emission

Inventories

Motor Vehicle Emission Simulator (MOVES 2010b) will be configuredin The El Paso North Region for Calculate five categories of PM10

PM25 total Emission inventories from all on-road traffic over a

variety of scales within periods of time selected weeks months

and years

Moves (Motor Vehicle Emission

Simulator)

The emission model is develop using the current equation to calculate direct traffic emissions from

vehicles in the form of PM is

Eext annual emissions are measured in grams of miles traveled by the vehicle (gVMT )

SL is the road surface loading in (gm2)

W is the average weight in tons of the vehicles on the road

K is the particle size multiplier for particle size range (eg gVMT for PM10 when using grams and miles)

P is the 7 number of wet days with at least 0254 mm of precipitation during the averaging period

N is the number of years considered in the averaging period

C is the particle size specific emissions factor in units of interest vehicle direct exhaust brake wear and tirewear

Modeling Simulation Domain and Emissions Scenarios

For simulations of mobile air quality emission inventories a motor vehicle emission simulator EPA (MOVES 2014a) was used

The modeling use input factors divided into seven section

parameters

On-Road Inventory local data

input

Scale

Geographic Bounds

Traffic intensity

Vehicle Type

Pollutants

Road Type

Fuel Types

Figure Source EPA US Environmental Protection Agency 2012- Moves 2010b Model

EPA Moves 2014a The modeling used input factors divided into six section

parameters On-Road Inventory local data input

Geographic Domains CountyNonattainment Area

Vehicle-Miles Traveled (VMT) is the total number of miles driven by all vehicles withina given time period and geographic area

Average speed range from 25 miles per

hour to 65 miles per hour

Vehicle Classes Motorcycle PassengerCarTruks light-duty Commercial Truck(6001-8500 lbs) Buses heave-duty trucksRefuse trucks School Bus Single UnitShort Haul-truck Single Unit Long Haul-truck Long Haul Truck Heavy-DutyVehicles (26001-33000 lbs)

Pollutants

Road TypeRural restricted Acces(Freeways and interstates) Rural and Restricted Acces Urban Restricted Acces Off-Network

Fuel Types Gasoline Diesel Fuel

Specific Road Types

Two road types for running emission from the MOVES can be

selected

(freeways and interstates)

Interior urban Urban

Figure Source EPA US Environmental Protection Agency 2012- Moves 2010b Model

VehiclesEquipment

This panel show which on-road vehicles will be modeled

Figure Source EPA US Environmental Protection Agency 2012- Moves 2010b Model

Long haul truck Short haul truck Inercity bus Ligth comercial truck

Passenger car Passenger truck Refuse truck

School bus Single unit long haul-truck

Single unit short haul-truck

Transit bus

Motor home

Motorcycle

Based on Department of Transportation Highway MOVES will Estimates Traffic

Emissions from Cars Trucks amp Motorcycles

Output Data Moves 2014a

Inventories of PM 10 25 Mobile Emission from all

on-Road Traffic

Exhaust Emission PM 10 25 gramsmile

Brake Wear Emission PM 10 25 gramsmile

Tire wear Emission PM 10 25 gramsmile

Date of Vehicle miles traveled (VMT) for

Day Week Month Year

Total Vehicle population

Vehicle age distribution

Simulation of Mobile Emission in the El PdN Region Zip Code 79905

Figure Total Emissions from road traffic in El Paso TX Area were estimated for PM10

Exhaust and Non exhaust emission in kilogramsmonth (Source EPA MOVES 2014a)

0

10000

20000

30000

40000

50000

PM

10 k

gM

on

th

Months

Monthly PM 10 Exhaust and Non-Exhaust Mobile Emissions 2010

On-Road Urban Restricted Area Zip Code 79905

Primary Exhaust PM 10 (kg) Primary PM 10 Brakewear (kg)

Primary PM 10 Tirewear (kg)

05000

100001500020000250003000035000400004500050000

PM

25

kg

Mo

nth

Months

Monthly PM 25 Exhaust and Non-Exhaust Mobile Emission 2010

On-Road Urban Restricted Area Zip Code 79905

Primary Exhaust PM 25 (kg) Primary PM 25 Brakewear (kg) Primary PM 25Tirewear (kg)

Figure Total Emissions from road traffic in El Paso TX Area were estimated for PM25

Exhaust and Non exhaust emission in kilogramsmonth (Source EPA MOVES 2014a)

Total Emissions from Road Traffic in El Paso County PM1025 Exhaust and Non exhaust Emission in kilogramsmonth

Taking the interests to the health risks related to PM 1025 mobile emission were simulated

Exhaust and Non-exhaust emissions contribute almost equally to total traffic-related PM1025 Emissions (Querol et al 2004 Bukowiecki et al 2009a Amato et al 2011)

Monthly PM 10 25 Exhaust and Non-Exhaust (BrakewearTirewear) Mobile

Emission 2010 On-Road Urban Restricted Area Zip Code 79905

Figure Total Emissions from road traffic in El Paso TX Area were estimated for PM10 25 Exhaust and Non Exhaust mobile

emission in kilograms per month (Source EPA MOVES)

0

10000

20000

30000

40000

50000

January February March April May June July August September October November December

PM

10

25

(K

ilog

ram

s)

Months

Summary- Monthly PM 10 25 Exhaust and Non-Exhaust Mobile

Emission 2010 On-Road Urban Restricted Area Zip Code 79905

Primary Exhaust PM 10 Primary PM 10 Brakewear Primary PM 10 Tirewear

Primary Exhaust PM 25 Primary PM 25 Brakewear Primary PM 25Tirewear

Exhaust Emissions PM1025 is reaching maximum emission 48000-42000 thousand of Kgmonth followedby Brake wear 29000-5000 thousand kgmonth and Tire wear with 9000-2000 kgmonth The results showthat the emissions of PM derived mainly from Exhaust and Brake are significantly higher in Urban Area

Annual Contribution of Mobile Emission PM 1025 (Kg) Zip Code 79905 El

Paso County 2010

Total Primary

Exhaust _PM10

39

Total Primary

Exhaust _PM25

36

Brakewear

particulate_PM10

18

Tirewear

particulate_PM10

4

Brakewear

particulate_PM25

2

Tirewear

particulate_PM25

1

0

5

10

15

20

25

30

35

40

45

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53

Fig Annual Average PM10 Concentrations at the

Chamizal C41 Station and PM1025 mobile

Concentration Zip code 79905

PM10 TCEQ (μgm3) Total Mobile Emission PM10 (Ugm3)

Fig Exhaust Emission is Contributing Approximately 74 of total

PM1025 Mobile Emissions following of Brake wear with 20 and Tire

wear with 5

Annual Average PM1025 ugm3 Mobile Emissions (Moves) 26 Chamizal C41

Monitoring Station (TCEQ Chamizal Station )

Predicting Mobile Emission and VTM

Estimation The PdN Region 2010

44E+09

46E+09

48E+09

5E+09

52E+09

54E+09

56E+09

58E+09

6E+09

62E+09

0

50000

100000

150000

200000

250000

300000

350000

20

10

20

11

20

12

20

13

20

14

20

15

20

16

20

17

20

18

20

21

20

22

20

23

20

24

20

25

20

26

20

27

20

28

20

29

20

30

EX

HA

US

T

EM

ISS

ION

MO

BIL

E (

KG

YE

AR

)

YEARS

Predict ing Mobile Exhaust Emission and VTM

Estimation

2010 - 2030 e l PdN Area

Total_ Exhaust PM10 Total_ Exhaust PM25 Distance (Miles)

Fig Predicting Mobile Exhaust PM1025 (kgMonth) Emission and VTM Estimation 2010

- 2030 el PdN Area

44E+09

46E+09

48E+09

5E+09

52E+09

54E+09

56E+09

58E+09

6E+09

62E+09

0

5000000

10000000

15000000

20000000

25000000

30000000

20

10

20

11

20

12

20

13

20

14

20

15

20

16

20

17

20

18

20

21

20

22

20

23

20

24

20

25

20

26

20

27

20

28

20

29

20

30

EX

HA

US

T

EM

ISS

ION

MO

BIL

E (

KG

YE

AR

)

YEARS

Predict ing Mobile Exhaust Emission and

VTM Estimation

2010 - 2030 e l PdN Area

CO NO2 NO NOx Distance

Fig Predicting Mobile Exhaust Emission and VTM Estimation

2010 - 2030 el PdN Area in El Paso TX Area were estimated for

Total CO NOx NO2 NO emission in kilograms per year

(Source EPA MOVES 2014a model)

The simulated Exhaust emissions in the future years shows a trend of reduction of this type of emissions in the

future years one factor should be the new hybrid technology is increasing by 476 since 2010 to 2015 and

use of catalytic converters diesel particulate filters and improved fuels and engines Non-exhaustive sources

will increase in the coming years because there is no control in the material of manufacture composed by Fe

Cu and Mn also not to be able to reduce the number of events of braking (Accelerations and decelerations)

45E+09

5E+09

55E+09

6E+09

65E+09

0

50000

100000

150000

200000

250000

201

0

201

1

201

2

201

3

201

4

201

5

201

6

201

7

201

8

202

1

202

2

202

3

202

4

202

5

202

6

202

7

202

8

202

9

203

0

NO

N-

EX

HA

US

T

EM

ISS

ION

MO

BIL

E

(KG

YE

AR

)

YEARS

Predicting Non Exhaust Mobile

Emission and VTM Estimation

2010 - 2030 el PdN Area

Brake_PM10 Tire_PM10 Distance (Miles)

Fig Predicting Mobile Exhaust PM1025 (kgMonth) Emission and VTM

Estimation 2010 - 2030 el PdN Area

Daily Avg PM1025

Levels of PM Mobile Emission Non-Exhaust -Rush Hour Periods Fall 2010 Zip Code

79905

00

100

200

300

400

500

600

Mo

bil

e P

M1

0 (k

g)

Rush Hours

Daily Avg PM10

Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush Hours

Periods 2010 Zip Code 79905

Total Primary Exhaust

_PM10 WinterSpring

Brakewear

particulate_PM10

WinterSpringTirewear particulate_PM10

WinterSpring

Total Primary Exhaust

_PM10 Summer

Brakewear

particulate_PM10 Summer

Tirewear Particulate_PM10

Summer

Total Primary Exhaust

_PM10 Fall

Brakewear

particulate_PM10 Fall

Tirewear particulate_PM10

Fall

00

50

100

150

200

250

300

350

Mo

bil

e P

M2

5 (k

g)

Rush hours

Daily Avg PM25

Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush

Hours Periods 2010 Zip Code 79905

Total Primary Exhaust _PM25

WinterSpring

Brakewear Particulate_PM25

WinterSpring

Tirewear particulate_PM25

WinterSpring

Total Primary Exhaust _PM25

Summer

Brakewear particulate_PM25

Summer

Tirewear particulate_PM25

Summer

Total Primary Exhaust _PM25

Fall

Brakewear particulate_PM25

Fall

Tirewear particulate_PM25

Fall

Figure Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush Hours Figure Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush Hours

GIS EMISSIONS INVENTORY SYSTEM A geographic information system (GIS) was used to established geographic scenarios with processed images of seasonal mobile

emissions in the PdN region Seasonal mapping is visualized for different types of pollutants Brakewear Exhaust and Tyrewear

Fg Graphics of GIS and Seasonal mobile Emission of particulate matter emission inventory Seasonal emission simulations were performed in kilograms and five contributing inputs factors were identified for

modeling 1) On the composition of the particulate material from different sources such as Exhaust and Non exhaust (Brake wear Tirewear) 2) The Vehicles Equipment clasification were selected according to

the use of gasoline and diesel fuel (motorcycle passenger car Light Duty Vehicles Trucks refuse truck Light Duty Vehicles Light Commercial Truck Light Duty Vehicles School Bus)

Winter Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

120354 67860 19065

Spring Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

139767 86702 24463

Summer Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

94747 62481 17630

Fall Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

75510 45542 12596

251 Descriptive Statistics Data Analysis

Weekly Correlation Analysis of Mobile Emission PM10 (Exhaust-Non-Exhaust) and Respiratory

Diagnoses WinterSpring Summer and Fall 2010

0

2

4

6

8

10

0

50

100

150

200

250

300

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21

Mo

rbid

ity

Dis

ch

arg

e

for

all R

esp

ira

tory

Dis

ea

se

ICD

-9

(A

sth

ma

-Bro

nc

hitis

)

WinterSpring Week

Weekly Avg Mobile PM10 Concentrations during

WinterSpring 2010 and its Influence on Respiratory

Diagnoses

Zip Code 79905

Total Medical data ZIP Code 79902

Total Mobile Emission PM10 (Ugm3)

0

1

2

3

4

5

6

7

0

20

40

60

80

100

Mo

rbid

ity

Dis

ch

arg

e

for

all R

esp

ira

tory

Dis

ea

se

ICD

-9

(Ast

hm

aB

ron

ch

itis

)

Weekly Avg Mobile PM10 Concentrations during

Summer 2010 and its Influence on Respiratory

Diagnoses

Summer 2010 Zip Code 79905

Total Mobile Emission PM10

Hospital Admission (Asthma-Bronchitis)

0

2

4

6

8

10

12

0

20

40

60

80

100

120

140

160

180

200

Mo

rbid

ity

dis

ch

arg

es

for

all r

esp

ira

tory

dis

ea

se

Weekly Avg Mobile PM10 Concentrations

during Fall 2010 and its Influence on Respiratory

Diagnoses

Zip Code 79905

Total Medical data ZIP Code 79902

Total Mobile Emission PM10 (Ugm3)

Mobile(Exhaust-Non-

Exhaust) PM10 and

Asthma-Bronchitis)

Linear R

Square

WinterSpring 734 ndash 39

Summer 614 ndash 32

Fall 548 -29

PM10 Mobile emission (Exhaust-Non-Exhaust)contributed significantly

association to the incidence of RD

Weekly Correlation Analysis of PM 25 Mobile Emission (Exhaust-Non-Exhaust)

and Cardiovascular Diagnoses WinterSpring Summer and Fall 2010

0010203040

00500

100015002000

Wee

k 1

Wee

k 2

Wee

k 3

Wee

k 4

Wee

k 5

Wee

k 6

Wee

k 7

Wee

k 8

Wee

k 9

Wee

k 1

0

Wee

k 1

1

Wee

k 1

2

Wee

k 1

3

Wee

k 1

4

Wee

k 1

5

Wee

k 1

6

Wee

k 1

7

Wee

k 1

8

Wee

k 1

9

Wee

k 2

0

Wee

k 2

1

Morb

idit

y d

isch

arg

es f

or

all

card

iovasc

ula

r d

isea

se

Weekly Avg PM25 Mobile Concentrations during

WinterSpring 2010 and its Influence on all Heart

Diagnoses

Zip Code 79905

Total All Heart Disease PM 25 mobile (μgm3)

0010203040

00

500

1000

1500

Mo

rbid

ity

dis

ch

arg

es

for

all

ca

rdio

va

scu

lar

dis

ea

se

Weeks

CORRELATION BETWEEN MOBILE PM25 ugm3

EXPOSURE TO HEART DISEASES SYMPTOMS

SUMMER SEASON 2010

Total All Heart Disease PM 25 mobile (μgm3)

Figure Statistical Analyses of the Relationship Between PM25 Caused by Traffic Emission( 26 of total Emission) with Heart diseases Source Hospital Admissions for Asthma Acute Bronchitis and Heart diseases in El Paso County zip code 79905 from Texas Health Care

Information Council in Austin Texas (Texas Health Care Information Council 2000)

00

10

20

30

40

0

50

100

150

We

ek 3

6

We

ek 3

7

We

ek 3

8

We

ek 3

9

We

ek 4

0

We

ek 4

1

We

ek 4

2

We

ek 4

3

We

ek 4

4

We

ek 4

5

We

ek 4

6

We

ek 4

7

We

ek 4

8

We

ek 4

9

We

ek 5

0

We

ek 5

1

We

ek 5

2

We

ek 5

3

Mo

rbid

ity

dis

ch

arg

es

for

all

ca

rdio

va

scu

lar

dis

ea

se

CORRELATION BETWEEN MOBILE PM25 ugm3

EXPOSURE TO HEART DISEASES SYMPTOMS FALL

SEASON 2010

Total All Heart Disease PM 25 mobile (μgm3)

Mobile(Exhaust-

Non-Exhaust)

PM10 and

Asthma-

Bronchitis)

Linear R

Square

WinterSpring 833 -42

Summer 620 -32

Fall 501-26

PM10 Mobile

emission (Exhaust-

Non-

Exhaust)contribut

ed significantly

association to the

incidence of CVD

Diseases

Monthly Brake Mobile Emission PM1025 kg During year 2010 and its Influence on

Respiratory Diagnoses Zip Code 79905

00200040006000800010000

010000200003000040000

PM

10

Mo

bile

(K

g)

Months

Monthly Brake Mobile Emission PM10 kg during year

2010 and its Influence on Respiratory Diagnoses

Zip Code 79905

Primary PM 10

Brakewear 00100020003000400050006000

0

1000

2000

3000

4000

PM

25

Mo

bil

e(K

g)

Months

Monthly Brake Mobile Emission PM25 during

year 2010 and its Influence on Heart Diagnoses

Zip Code 79905

Primary PM 25

Brakewear

Heart Diseases

Hospital

Admission

Brake Mobile Emission

PM10 kg Asthma-

Bronchitis)

Brake Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=969 Linear Square R=856

Monthly Mobile Exhaust Emission PM1025 During year 2010 and its Influence on

Respiratory Diagnoses Zip Code 79905

0

200

400

600

800

1000

0

10000

20000

30000

40000

50000

1 3 5 7 9 11

PM

10

(K

g m

on

th)

Months

Monthly Mobile Exhaust Emission PM10 during

year 2010 and its Influence on Respiratory

Diagnoses

Zip Code 79905

Primary Exhaust

PM 10

Respiratory Disease

(Asthma

Bronchitis) Hospital

Admission

0

100

200

300

400

500

600

0

10000

20000

30000

40000

50000

1 2 3 4 5 6 7 8 9 101112

PM

25

(K

g m

on

th)

Months

Monthly Exhaust Mobile Emission PM25 during

year 2010 and its Influence on Heart Diagnoses

Zip Code 79905

Primary Exhaust PM

25

Heart Diseases

Hospital Admission

Exhaust Mobile Emission

PM10 kg Asthma-

Bronchitis)

Exhaust Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=929 Linear Square R=831

Monthly Tire wear Mobile Emission PM1025 During year 2010 and its Influence on Heart

Diagnoses Zip Code 79905

0

100

200

300

400

500

600

700

800

900

0

1000

2000

3000

4000

5000

6000

7000

8000

9000

1 2 3 4 5 6 7 8 9 10 11 12

PM

10

(K

g m

on

th)

Months

Monthly Tirewear Mobile Emission PM10 during year 2010

and its Influence on Heart Diagnoses

Zip Code 79905

Primary PM 10 Tirewear

Mobile Emission

Respiratory Disease

(Asthma Bronchitis)

Hospital Admission

0

100

200

300

400

500

600

0

200

400

600

800

1000

1200

1400

1 2 3 4 5 6 7 8 9 10 11 12

PM

25

(K

g m

on

th)

Months

Monthly Tirewear Mobile Emission PM25 during year 2010

and its Influence on Respiratory Diagnoses

Zip Code 79905

Primary PM 25Tirewear

Mobile Emission

Heart Diseases Hospital

Admission

Exhaust Mobile Emission

PM10 kg Asthma-

Bronchitis)

Exhaust Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=769 Linear Square R=715

Dona Ana County Zip Codes

88021880278807288048

Primary

Exhaust

PM 10 Zip

code

79905

Total

Primary

Exhaust

PM10

Dona Ana

Primary

Exhaust

PM 25 Zip

Code

79905

Total

Primary

Exhaust

PM25

Dona Ana

Series1 430378 111773 391915 102123

0

100000

200000

300000

400000

500000

AX

IS T

ITLE

Annual Comparison of the Mobile

Exhaust Emissions El Paso County

and Dona Ana 2010

Primary

PM 10

Brakewea

r Zip code

79905

Brakewea

r

particulat

e_PM10

Dona Ana

Primary

PM 10

Tirewear

Zip code

79905

Tirewear

particulat

e_PM10

Dona Ana

Series1 262585 48573 73754 11864

050000

100000150000200000250000300000

AX

IS T

ITLE

Annual Comparison of the Mobile

Brakewear Emissions El Paso County

and Dona Ana 2010

Figure Comparison of the Annual Mobile Emissions

of Primary PM10 Non-Exhauts (Brake ) from Dona

Ana County New Mexico and El Paso Texas Units

in KgMonth

Figure Comparison of the Annual Mobile Emissions

of Primary PM10-Exhauts Emission from Dona Ana

County New Mexico and El Paso Texas Units in

KgMonth

Primary

PM 25

Brakewe

ar Ziphellip

Brakewe

ar

particula

te_PMhellip

Primary

PM

25Tirewe

ar Ziphellip

Tirewear

particula

te_PM25

Donahellip

Series1 32645 6071 10919 1779

0

10000

20000

30000

40000

AX

IS T

ITLE

Annual Comparison of the

Mobile Exhaust Emissions El Paso

County and Dona Ana 2010

Figure Comparison of the Annual Mobile Emissions

of Primary PM10-Exhauts Emission from Dona Ana

County New Mexico and El Paso Texas Units in

KgMonth

Monthly Mobile Emission PM1025 kg During year 2006

and its Influence on Respiratory Diagnoses Dona Ana

County Zip Code 880218802788072

0

100

200

300

0

5000

10000

15000

Axi

s Ti

tle

Axis Title

Monthly Mobile Exhaust Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Total PrimaryMobile Exhaust_PM10

All Respiratory ICD-9 (AsthmaBronchitis)

050100150200250300

010002000300040005000

Axi

s Ti

tle

Axis Title

Monthly Mobile Brake Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Brakewearparticulate_PM10

All RespiratoryICD -9 (AsthmaBronchitis)

050100150200250300

0200400600800

10001200

Axi

s Ti

tle

Axis Title

Monthly Mobile Tirewear Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Tirewearparticulate_PM10

All Respiratory ICD -9 (AsthmaBronchitis)

Mobile Exhauts

Emission PM10

kg Asthma-

Bronchitis)

Brake Mobile

Emission PM10

kg and Heart

Diagnoses

Tirewear Mobile

Emission PM10

kg and Heart

Diagnoses

Linear Square

R= 951

Linear Square

R=625

Linear Square

R=525

Mobile Exhauts

Emission PM25

kg Asthma-

Bronchitis)

Brake Mobile

Emission PM25

kg and Heart

Diagnoses

Tirewear Mobile

Emission PM25

kg and Heart

Diagnoses

Linear Square

R= 986

Linear Square

R=691

Linear Square

R=601

Results

The results showed that mobile PM emissions in the urban areas close to urban Road and highways is putting at risk public health

and the proportion of diseases attributable to this exposure is potentially large

Brake wear emissions is much lower in freeways due to significantly reduced number of braking events while tire wear is much

higher in areas where studded tires are used The emission of exhaust gases are much higher in areas where there is a high

vehicular traffic

Brake Mobile

Emission PM10 kg

Asthma-Bronchitis)

Brake Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square

R=969

Linear Square

R=856

Exhaust Mobile

Emission PM10 kg

Asthma-Bronchitis)

Exhaust Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square

R=929

Linear Square

R=831

Tirewear Mobile

Emission PM10 kg

Asthma-Bronchitis)

Tirewear Mobile

Emission PM25 kg

and Heart Diagnoses

Linear Square R=769 Linear Square R=715

Brake Mobile

Emission PM10 kg

and Heart

Diagnoses

Brake Mobile

Emission PM25 kg

and Heart

Diagnoses

Exhaust Mobile

Emission PM10 kg

Asthma-Bronchitis)

Linear Square

R=625

Linear Square

R=691

Linear Square R=

951

Exhaust Mobile

Emission PM25 kg

Asthma-

Bronchitis)

Tire wear Mobile

Emission PM10 kg and

Heart Diagnoses

Tirewear Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square R=

986

Linear Square R=525 Linear Square

R=601

El Paso County

Dona Ana

County

BenMAP-CE

In this analysis the Program of Mapping and Analysis of Environmental Benefits-Community Edition

(BenMAP-CE) was used to Estimate the number and economic value of health impacts resulting from changes

in air pollution PM 25 Ugm3 in The El Paso Area

Health and Economic Benefits associated with the Response of PM25 Emission between

Base Year 2010

Number of Mortalities in 2010 Base Year Based on El Paso County Texas Department of State Health Services

Number of Mortalities in 2010 Base Year Based on El Paso County Texas

Department of State Health Services

cause of death

year

2010

Populatio

n

Affected

Backgro

und

Concentr

ation Pollutant

Rollback

Type

Avoided

Deaths

(

Populatio

n)

alzheimers disease 2010 40716 125 PM25

25

microgmAcircsup3

Rollback 9

diseases of the

heart 2010 15834 125 PM25

25

microgmAcircsup3

Rollback 35

influenza and

neumonia 2010 81432 125 PM25

25

microgmAcircsup3

Rollback 18

acute bronchitis

and bronchiolitis 2010 117624 125 PM25

25

microgmAcircsup3

Rollback 26

chronic lower

respiratory diseases 2010 54288 125 PM25

25

microgmAcircsup3

Rollback 12

The Basin-wide decrease in 4 ugm3 PM25 concentration after this

reduction control

Cause of death year 2010

Populatio

n

Affected

Background

Concentrati

on

Reduc

cion

scena

rio Polluta

nt

Rollback

Type

Avoi

ded

Deat

hs

(

Pop

ulati

on)

economic

benefits

analysis $

Alzheimers

disease 2010 121 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 9 12000

Diseases of the

heart 2010 470 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 35 35000

Influenza and

neumonia 2010 242 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 18 42500

Acute bronchitis

and bronchiolitis 2010 349 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 26 95000

Chronic lower

respiratory

diseases 2010 161 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 12 4500

$1 295000

PM25-related Mortalities Based on BenMAP-CE Estimate in 2010 Base Year with change in the concentrations levels

Health and Economic Benefits associated with the Response of PM25 Emission between

Base Year 2010 Increasing 7 Ugm3

Cause of death year 2010

Population

Affected

Deaths

avoided by

attaining 195

μgm3

standard

Background

Concentrati

on

Pollut

ant

Rollback

Type

Avoided

Deaths (

Populatio

n)

econo

mic

Unben

efits

analysi

s

Alzheimers

disease 2010 4524 195 PM25

25

microgmAcircsup3

Rollback 19 150000

Diseases of the

heart 2010 20358 195 PM25

25

microgmAcircsup3

Rollback 135 450000

Influenza and

neumonia 2010 126672 195 PM25

25

microgmAcircsup3

Rollback 38 525000

Acute bronchitis

and bronchiolitis 2010 162864 195 PM25

25

microgmAcircsup3

Rollback 36 122000

Chronic lower

respiratory

diseases 2010 99528 195 PM25

25

microgmAcircsup3

Rollback 12 650000

Conclusions

An excellent Pearson Correlation was established to analyze the relationship in the relative risks of hospitalization of Respiratory(RD) and cardiovascular (CVD) associated with ambient exposure caused by traffic emission in relation to their size andspecific sources of emission on different scenarios interior a border Urban Rural Urban restricted access (freeways andinterstates)

A significant correlation of PM1025 exposure from mobile emission and hospital admissions for selected Respiratory (RD) andcardiovascular (CVD) diagnoses was established The results showed that PM emissions in urban restricted access (freeways andinterstates) is mainly caused by traffic Therefore people living close to highways are more exposed higher vehicular emissions

Conclusions

We found statistically significant associations between mobile PM25 caused by traffic emission with Respiratory and Cardiovascular Diseases in the study areaSubsequently a correlation between cardio-respiratory mortality is established

A significant correlation of PM1025 exposure from mobile emission and hospital admissions for selected Respiratory (RD) and cardiovascular (CVD) diagnoses isestablished The results showed that PM emissions in urban restricted access (freeways and interstates) is mainly caused by traffic Therefore people living close tohighways receive higher vehicular emissions

The table shows the percentage of PM mobile exposure in the analyzed areas contributing to increase the risk of Respiratory and Cardiovascular Diseases

An examination was conducted of the synoptic and local meteorology for the June 2006 ozone episode using the WRF model to determine how meteorological parametersinfluence the formation transport and dispersion of ozone in the PdN The predominant synoptic feature of the ozone event day was the expansion intensification and slowprogression of an upper-level ridge of high pressure The high ozone episodes are associated with highly stable atmospheres strong temperature inversions with low mixingheights and therefore low mixing volumes Under these conditions emissions such as NOx lead to highly polluted conditions that favor ozone formation

BenMAP Conclusions

We have estimated the number and economic value of health impacts resulting

from changes in air pollution concentrations of PM 25 in the PdN region

Reduction of Pm 25 4 UGm3= Avoided 213 cases respiratory cardiovascular

diseses and Economic Benefits associated with the Response of PM25 Emission + $

1295000

Increase of PM25 7 ugm3 = increasing Dies= 326 economic Unbenefits= 2345000$

Bibliography

1 Dockery DW Pope CAI Xu X Spengler JD Ware JH Fay ME Ferris BG Speizer FE An association between air pollution and mortality in six US cities N Engl J Med 3291753ndash1759 (1993)

2 Samet JM Dominici F Curriero FC Coursac I Zeger SL Fine particulate air pollution and mortality in 20 US cities 1987ndash1994 N Engl J Med 3431742ndash1749 (2000)

3 Nel AE Diaz-Sanchez D Li N The role of particulate pollutants in pulmonary inflammation and asthma evidence for the involvement of organic chemicals and oxidative stress Curr Opin Pulm Med 20017 20ndash26

4 Westerholm R Karl-Erik E Exhaust emissions from lightand heavy-duty vehicles chemical composition impact of exhaust after treatment and fuel parameters Environ Health Perspect 102(suppl 4)13ndash23 (1994)

5 Bascom R Bromberg P Costa D Delvin R Dockery D Frampton M Lambert W Samet J Speizer F Utell

6 Health effects of outdoor air pollution Am J Respir Crit Care Med 1533ndash50 (1996)

7 Chow JC Watson JG Frazier CA Egami RT Goodrich A Ralph C Spatial and temporal source contributions to

8 PM10 and PM25 in Reno NV In PM-10 Implementation of Standards Transactions An APCAEPA International Speciality Conference San Francisco CA (Mathal CV Stonefield DH eds) PittsburghAPCA 1988439ndash457

9 overview In Particulate Matter Health and Regulatory Issues VIP-49 Proceedings of an International Specialty Conference 4ndash6 April 1995 Pittsburgh PA PittsburghAir and Waste Management Association 1995577ndash598

10 Kunzli N Kaiser R Medina S Studnicka M Chanel O

11 Filliger P Herry M Horak F Jr Puybonnieux-Texier V Quenel P et al Public-health impact of outdoor and traffic- related air pollution a European assessment Lancet 356795ndash801 (2000)

Bibliography

1 Sioutas C Delfino RJ Singh M Exposure assessment for atmospheric ultrafine particles (UFP) and implications in epidemiological research Environ Health Perspect 2005113947ndash955

2 Mosleh M Blau PJ Dumitrescu D (2004) Characteristics and morphology of wear particles from laboratory testing of disc brake materials Wear 2561128ndash1134

3 Kuumlnzli N et al (2000) Public-health impact of outdoor and traffi c-related air pollution a European assessment Lancet 356(9232)795ndash801

4 Dora C Phillips M eds (2000) Transport environment and health Copenhagen WHO Regional Office for Europe (WHO Regional Publications European Series No 89 httpwwweurowhointdocumente72015pdf accessed 26 November 2004)

5 Westerholm R Karl-Erik E Exhaust emissions from lightand

6 heavy-duty vehicles chemical composition impact of exhaust after treatment and fuel parameters Environ Health Perspect 102(suppl 4)13ndash23 (1994)

7 Fauser Tjell Mosbaek pigegaard Quantification of tire-Tread particles using extractable Organic Zinc as a Tracer Rubber Chemistry and Technology 1999 969Table shows some literature estimates of the contribution of tire wear to PM10 in air (Panko et al 2013) Gustafsson M Blomqvist G Gudmundsson A Dahl A Swietlicki E Bohgard M Lindbom J Ljungman A

8 Chen Y Shah N Huggins FE and Huffman GP (2006) Microanalysis of Ambient Particles from Lexington Ky by Electron Microscopy Atmos Environ 40 651ndash663

9 Donaldson K Tran CL Jimenez LA Duffin R Newby DE and Mills N (2005) Combustion-derived Nanoparticles A Review of Their Toxicology Following Inhalation Exposure Part Fibre Toxicol 2 10ndash23

10 Su D Serafino A Muller JO Jentoft RE Schlogl R and Fiorito S (2008) Cytotoxicity and Inflammatory Potential of Soot Particles of Low-emission Diesel Engines Environ Sci Technol 42 1761ndash1765

11 Maier KL Alessandrini F Beck-Speier I Hofer TPJ Diabatґe S Bitterle E Stoger T and Jakob T (2008) Health Effects of Ambient Particulate Matter-Biological Mechanisms and Inflammatory Responses to in Vitroand in Vivo Particle Exposures Inhalation Toxicol 20 319ndash337

Page 25: Studies of Air Pollutants and their Impact on Respiratory and ...€¦ · Ascarate Park C37 Monitoring Station: The National Ambient Air Quality Standard (NAAQS) for PM 10 and 2.5

EPA MOVES Model for Estimating Emission

Inventories

Motor Vehicle Emission Simulator (MOVES 2010b) will be configuredin The El Paso North Region for Calculate five categories of PM10

PM25 total Emission inventories from all on-road traffic over a

variety of scales within periods of time selected weeks months

and years

Moves (Motor Vehicle Emission

Simulator)

The emission model is develop using the current equation to calculate direct traffic emissions from

vehicles in the form of PM is

Eext annual emissions are measured in grams of miles traveled by the vehicle (gVMT )

SL is the road surface loading in (gm2)

W is the average weight in tons of the vehicles on the road

K is the particle size multiplier for particle size range (eg gVMT for PM10 when using grams and miles)

P is the 7 number of wet days with at least 0254 mm of precipitation during the averaging period

N is the number of years considered in the averaging period

C is the particle size specific emissions factor in units of interest vehicle direct exhaust brake wear and tirewear

Modeling Simulation Domain and Emissions Scenarios

For simulations of mobile air quality emission inventories a motor vehicle emission simulator EPA (MOVES 2014a) was used

The modeling use input factors divided into seven section

parameters

On-Road Inventory local data

input

Scale

Geographic Bounds

Traffic intensity

Vehicle Type

Pollutants

Road Type

Fuel Types

Figure Source EPA US Environmental Protection Agency 2012- Moves 2010b Model

EPA Moves 2014a The modeling used input factors divided into six section

parameters On-Road Inventory local data input

Geographic Domains CountyNonattainment Area

Vehicle-Miles Traveled (VMT) is the total number of miles driven by all vehicles withina given time period and geographic area

Average speed range from 25 miles per

hour to 65 miles per hour

Vehicle Classes Motorcycle PassengerCarTruks light-duty Commercial Truck(6001-8500 lbs) Buses heave-duty trucksRefuse trucks School Bus Single UnitShort Haul-truck Single Unit Long Haul-truck Long Haul Truck Heavy-DutyVehicles (26001-33000 lbs)

Pollutants

Road TypeRural restricted Acces(Freeways and interstates) Rural and Restricted Acces Urban Restricted Acces Off-Network

Fuel Types Gasoline Diesel Fuel

Specific Road Types

Two road types for running emission from the MOVES can be

selected

(freeways and interstates)

Interior urban Urban

Figure Source EPA US Environmental Protection Agency 2012- Moves 2010b Model

VehiclesEquipment

This panel show which on-road vehicles will be modeled

Figure Source EPA US Environmental Protection Agency 2012- Moves 2010b Model

Long haul truck Short haul truck Inercity bus Ligth comercial truck

Passenger car Passenger truck Refuse truck

School bus Single unit long haul-truck

Single unit short haul-truck

Transit bus

Motor home

Motorcycle

Based on Department of Transportation Highway MOVES will Estimates Traffic

Emissions from Cars Trucks amp Motorcycles

Output Data Moves 2014a

Inventories of PM 10 25 Mobile Emission from all

on-Road Traffic

Exhaust Emission PM 10 25 gramsmile

Brake Wear Emission PM 10 25 gramsmile

Tire wear Emission PM 10 25 gramsmile

Date of Vehicle miles traveled (VMT) for

Day Week Month Year

Total Vehicle population

Vehicle age distribution

Simulation of Mobile Emission in the El PdN Region Zip Code 79905

Figure Total Emissions from road traffic in El Paso TX Area were estimated for PM10

Exhaust and Non exhaust emission in kilogramsmonth (Source EPA MOVES 2014a)

0

10000

20000

30000

40000

50000

PM

10 k

gM

on

th

Months

Monthly PM 10 Exhaust and Non-Exhaust Mobile Emissions 2010

On-Road Urban Restricted Area Zip Code 79905

Primary Exhaust PM 10 (kg) Primary PM 10 Brakewear (kg)

Primary PM 10 Tirewear (kg)

05000

100001500020000250003000035000400004500050000

PM

25

kg

Mo

nth

Months

Monthly PM 25 Exhaust and Non-Exhaust Mobile Emission 2010

On-Road Urban Restricted Area Zip Code 79905

Primary Exhaust PM 25 (kg) Primary PM 25 Brakewear (kg) Primary PM 25Tirewear (kg)

Figure Total Emissions from road traffic in El Paso TX Area were estimated for PM25

Exhaust and Non exhaust emission in kilogramsmonth (Source EPA MOVES 2014a)

Total Emissions from Road Traffic in El Paso County PM1025 Exhaust and Non exhaust Emission in kilogramsmonth

Taking the interests to the health risks related to PM 1025 mobile emission were simulated

Exhaust and Non-exhaust emissions contribute almost equally to total traffic-related PM1025 Emissions (Querol et al 2004 Bukowiecki et al 2009a Amato et al 2011)

Monthly PM 10 25 Exhaust and Non-Exhaust (BrakewearTirewear) Mobile

Emission 2010 On-Road Urban Restricted Area Zip Code 79905

Figure Total Emissions from road traffic in El Paso TX Area were estimated for PM10 25 Exhaust and Non Exhaust mobile

emission in kilograms per month (Source EPA MOVES)

0

10000

20000

30000

40000

50000

January February March April May June July August September October November December

PM

10

25

(K

ilog

ram

s)

Months

Summary- Monthly PM 10 25 Exhaust and Non-Exhaust Mobile

Emission 2010 On-Road Urban Restricted Area Zip Code 79905

Primary Exhaust PM 10 Primary PM 10 Brakewear Primary PM 10 Tirewear

Primary Exhaust PM 25 Primary PM 25 Brakewear Primary PM 25Tirewear

Exhaust Emissions PM1025 is reaching maximum emission 48000-42000 thousand of Kgmonth followedby Brake wear 29000-5000 thousand kgmonth and Tire wear with 9000-2000 kgmonth The results showthat the emissions of PM derived mainly from Exhaust and Brake are significantly higher in Urban Area

Annual Contribution of Mobile Emission PM 1025 (Kg) Zip Code 79905 El

Paso County 2010

Total Primary

Exhaust _PM10

39

Total Primary

Exhaust _PM25

36

Brakewear

particulate_PM10

18

Tirewear

particulate_PM10

4

Brakewear

particulate_PM25

2

Tirewear

particulate_PM25

1

0

5

10

15

20

25

30

35

40

45

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53

Fig Annual Average PM10 Concentrations at the

Chamizal C41 Station and PM1025 mobile

Concentration Zip code 79905

PM10 TCEQ (μgm3) Total Mobile Emission PM10 (Ugm3)

Fig Exhaust Emission is Contributing Approximately 74 of total

PM1025 Mobile Emissions following of Brake wear with 20 and Tire

wear with 5

Annual Average PM1025 ugm3 Mobile Emissions (Moves) 26 Chamizal C41

Monitoring Station (TCEQ Chamizal Station )

Predicting Mobile Emission and VTM

Estimation The PdN Region 2010

44E+09

46E+09

48E+09

5E+09

52E+09

54E+09

56E+09

58E+09

6E+09

62E+09

0

50000

100000

150000

200000

250000

300000

350000

20

10

20

11

20

12

20

13

20

14

20

15

20

16

20

17

20

18

20

21

20

22

20

23

20

24

20

25

20

26

20

27

20

28

20

29

20

30

EX

HA

US

T

EM

ISS

ION

MO

BIL

E (

KG

YE

AR

)

YEARS

Predict ing Mobile Exhaust Emission and VTM

Estimation

2010 - 2030 e l PdN Area

Total_ Exhaust PM10 Total_ Exhaust PM25 Distance (Miles)

Fig Predicting Mobile Exhaust PM1025 (kgMonth) Emission and VTM Estimation 2010

- 2030 el PdN Area

44E+09

46E+09

48E+09

5E+09

52E+09

54E+09

56E+09

58E+09

6E+09

62E+09

0

5000000

10000000

15000000

20000000

25000000

30000000

20

10

20

11

20

12

20

13

20

14

20

15

20

16

20

17

20

18

20

21

20

22

20

23

20

24

20

25

20

26

20

27

20

28

20

29

20

30

EX

HA

US

T

EM

ISS

ION

MO

BIL

E (

KG

YE

AR

)

YEARS

Predict ing Mobile Exhaust Emission and

VTM Estimation

2010 - 2030 e l PdN Area

CO NO2 NO NOx Distance

Fig Predicting Mobile Exhaust Emission and VTM Estimation

2010 - 2030 el PdN Area in El Paso TX Area were estimated for

Total CO NOx NO2 NO emission in kilograms per year

(Source EPA MOVES 2014a model)

The simulated Exhaust emissions in the future years shows a trend of reduction of this type of emissions in the

future years one factor should be the new hybrid technology is increasing by 476 since 2010 to 2015 and

use of catalytic converters diesel particulate filters and improved fuels and engines Non-exhaustive sources

will increase in the coming years because there is no control in the material of manufacture composed by Fe

Cu and Mn also not to be able to reduce the number of events of braking (Accelerations and decelerations)

45E+09

5E+09

55E+09

6E+09

65E+09

0

50000

100000

150000

200000

250000

201

0

201

1

201

2

201

3

201

4

201

5

201

6

201

7

201

8

202

1

202

2

202

3

202

4

202

5

202

6

202

7

202

8

202

9

203

0

NO

N-

EX

HA

US

T

EM

ISS

ION

MO

BIL

E

(KG

YE

AR

)

YEARS

Predicting Non Exhaust Mobile

Emission and VTM Estimation

2010 - 2030 el PdN Area

Brake_PM10 Tire_PM10 Distance (Miles)

Fig Predicting Mobile Exhaust PM1025 (kgMonth) Emission and VTM

Estimation 2010 - 2030 el PdN Area

Daily Avg PM1025

Levels of PM Mobile Emission Non-Exhaust -Rush Hour Periods Fall 2010 Zip Code

79905

00

100

200

300

400

500

600

Mo

bil

e P

M1

0 (k

g)

Rush Hours

Daily Avg PM10

Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush Hours

Periods 2010 Zip Code 79905

Total Primary Exhaust

_PM10 WinterSpring

Brakewear

particulate_PM10

WinterSpringTirewear particulate_PM10

WinterSpring

Total Primary Exhaust

_PM10 Summer

Brakewear

particulate_PM10 Summer

Tirewear Particulate_PM10

Summer

Total Primary Exhaust

_PM10 Fall

Brakewear

particulate_PM10 Fall

Tirewear particulate_PM10

Fall

00

50

100

150

200

250

300

350

Mo

bil

e P

M2

5 (k

g)

Rush hours

Daily Avg PM25

Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush

Hours Periods 2010 Zip Code 79905

Total Primary Exhaust _PM25

WinterSpring

Brakewear Particulate_PM25

WinterSpring

Tirewear particulate_PM25

WinterSpring

Total Primary Exhaust _PM25

Summer

Brakewear particulate_PM25

Summer

Tirewear particulate_PM25

Summer

Total Primary Exhaust _PM25

Fall

Brakewear particulate_PM25

Fall

Tirewear particulate_PM25

Fall

Figure Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush Hours Figure Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush Hours

GIS EMISSIONS INVENTORY SYSTEM A geographic information system (GIS) was used to established geographic scenarios with processed images of seasonal mobile

emissions in the PdN region Seasonal mapping is visualized for different types of pollutants Brakewear Exhaust and Tyrewear

Fg Graphics of GIS and Seasonal mobile Emission of particulate matter emission inventory Seasonal emission simulations were performed in kilograms and five contributing inputs factors were identified for

modeling 1) On the composition of the particulate material from different sources such as Exhaust and Non exhaust (Brake wear Tirewear) 2) The Vehicles Equipment clasification were selected according to

the use of gasoline and diesel fuel (motorcycle passenger car Light Duty Vehicles Trucks refuse truck Light Duty Vehicles Light Commercial Truck Light Duty Vehicles School Bus)

Winter Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

120354 67860 19065

Spring Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

139767 86702 24463

Summer Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

94747 62481 17630

Fall Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

75510 45542 12596

251 Descriptive Statistics Data Analysis

Weekly Correlation Analysis of Mobile Emission PM10 (Exhaust-Non-Exhaust) and Respiratory

Diagnoses WinterSpring Summer and Fall 2010

0

2

4

6

8

10

0

50

100

150

200

250

300

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21

Mo

rbid

ity

Dis

ch

arg

e

for

all R

esp

ira

tory

Dis

ea

se

ICD

-9

(A

sth

ma

-Bro

nc

hitis

)

WinterSpring Week

Weekly Avg Mobile PM10 Concentrations during

WinterSpring 2010 and its Influence on Respiratory

Diagnoses

Zip Code 79905

Total Medical data ZIP Code 79902

Total Mobile Emission PM10 (Ugm3)

0

1

2

3

4

5

6

7

0

20

40

60

80

100

Mo

rbid

ity

Dis

ch

arg

e

for

all R

esp

ira

tory

Dis

ea

se

ICD

-9

(Ast

hm

aB

ron

ch

itis

)

Weekly Avg Mobile PM10 Concentrations during

Summer 2010 and its Influence on Respiratory

Diagnoses

Summer 2010 Zip Code 79905

Total Mobile Emission PM10

Hospital Admission (Asthma-Bronchitis)

0

2

4

6

8

10

12

0

20

40

60

80

100

120

140

160

180

200

Mo

rbid

ity

dis

ch

arg

es

for

all r

esp

ira

tory

dis

ea

se

Weekly Avg Mobile PM10 Concentrations

during Fall 2010 and its Influence on Respiratory

Diagnoses

Zip Code 79905

Total Medical data ZIP Code 79902

Total Mobile Emission PM10 (Ugm3)

Mobile(Exhaust-Non-

Exhaust) PM10 and

Asthma-Bronchitis)

Linear R

Square

WinterSpring 734 ndash 39

Summer 614 ndash 32

Fall 548 -29

PM10 Mobile emission (Exhaust-Non-Exhaust)contributed significantly

association to the incidence of RD

Weekly Correlation Analysis of PM 25 Mobile Emission (Exhaust-Non-Exhaust)

and Cardiovascular Diagnoses WinterSpring Summer and Fall 2010

0010203040

00500

100015002000

Wee

k 1

Wee

k 2

Wee

k 3

Wee

k 4

Wee

k 5

Wee

k 6

Wee

k 7

Wee

k 8

Wee

k 9

Wee

k 1

0

Wee

k 1

1

Wee

k 1

2

Wee

k 1

3

Wee

k 1

4

Wee

k 1

5

Wee

k 1

6

Wee

k 1

7

Wee

k 1

8

Wee

k 1

9

Wee

k 2

0

Wee

k 2

1

Morb

idit

y d

isch

arg

es f

or

all

card

iovasc

ula

r d

isea

se

Weekly Avg PM25 Mobile Concentrations during

WinterSpring 2010 and its Influence on all Heart

Diagnoses

Zip Code 79905

Total All Heart Disease PM 25 mobile (μgm3)

0010203040

00

500

1000

1500

Mo

rbid

ity

dis

ch

arg

es

for

all

ca

rdio

va

scu

lar

dis

ea

se

Weeks

CORRELATION BETWEEN MOBILE PM25 ugm3

EXPOSURE TO HEART DISEASES SYMPTOMS

SUMMER SEASON 2010

Total All Heart Disease PM 25 mobile (μgm3)

Figure Statistical Analyses of the Relationship Between PM25 Caused by Traffic Emission( 26 of total Emission) with Heart diseases Source Hospital Admissions for Asthma Acute Bronchitis and Heart diseases in El Paso County zip code 79905 from Texas Health Care

Information Council in Austin Texas (Texas Health Care Information Council 2000)

00

10

20

30

40

0

50

100

150

We

ek 3

6

We

ek 3

7

We

ek 3

8

We

ek 3

9

We

ek 4

0

We

ek 4

1

We

ek 4

2

We

ek 4

3

We

ek 4

4

We

ek 4

5

We

ek 4

6

We

ek 4

7

We

ek 4

8

We

ek 4

9

We

ek 5

0

We

ek 5

1

We

ek 5

2

We

ek 5

3

Mo

rbid

ity

dis

ch

arg

es

for

all

ca

rdio

va

scu

lar

dis

ea

se

CORRELATION BETWEEN MOBILE PM25 ugm3

EXPOSURE TO HEART DISEASES SYMPTOMS FALL

SEASON 2010

Total All Heart Disease PM 25 mobile (μgm3)

Mobile(Exhaust-

Non-Exhaust)

PM10 and

Asthma-

Bronchitis)

Linear R

Square

WinterSpring 833 -42

Summer 620 -32

Fall 501-26

PM10 Mobile

emission (Exhaust-

Non-

Exhaust)contribut

ed significantly

association to the

incidence of CVD

Diseases

Monthly Brake Mobile Emission PM1025 kg During year 2010 and its Influence on

Respiratory Diagnoses Zip Code 79905

00200040006000800010000

010000200003000040000

PM

10

Mo

bile

(K

g)

Months

Monthly Brake Mobile Emission PM10 kg during year

2010 and its Influence on Respiratory Diagnoses

Zip Code 79905

Primary PM 10

Brakewear 00100020003000400050006000

0

1000

2000

3000

4000

PM

25

Mo

bil

e(K

g)

Months

Monthly Brake Mobile Emission PM25 during

year 2010 and its Influence on Heart Diagnoses

Zip Code 79905

Primary PM 25

Brakewear

Heart Diseases

Hospital

Admission

Brake Mobile Emission

PM10 kg Asthma-

Bronchitis)

Brake Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=969 Linear Square R=856

Monthly Mobile Exhaust Emission PM1025 During year 2010 and its Influence on

Respiratory Diagnoses Zip Code 79905

0

200

400

600

800

1000

0

10000

20000

30000

40000

50000

1 3 5 7 9 11

PM

10

(K

g m

on

th)

Months

Monthly Mobile Exhaust Emission PM10 during

year 2010 and its Influence on Respiratory

Diagnoses

Zip Code 79905

Primary Exhaust

PM 10

Respiratory Disease

(Asthma

Bronchitis) Hospital

Admission

0

100

200

300

400

500

600

0

10000

20000

30000

40000

50000

1 2 3 4 5 6 7 8 9 101112

PM

25

(K

g m

on

th)

Months

Monthly Exhaust Mobile Emission PM25 during

year 2010 and its Influence on Heart Diagnoses

Zip Code 79905

Primary Exhaust PM

25

Heart Diseases

Hospital Admission

Exhaust Mobile Emission

PM10 kg Asthma-

Bronchitis)

Exhaust Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=929 Linear Square R=831

Monthly Tire wear Mobile Emission PM1025 During year 2010 and its Influence on Heart

Diagnoses Zip Code 79905

0

100

200

300

400

500

600

700

800

900

0

1000

2000

3000

4000

5000

6000

7000

8000

9000

1 2 3 4 5 6 7 8 9 10 11 12

PM

10

(K

g m

on

th)

Months

Monthly Tirewear Mobile Emission PM10 during year 2010

and its Influence on Heart Diagnoses

Zip Code 79905

Primary PM 10 Tirewear

Mobile Emission

Respiratory Disease

(Asthma Bronchitis)

Hospital Admission

0

100

200

300

400

500

600

0

200

400

600

800

1000

1200

1400

1 2 3 4 5 6 7 8 9 10 11 12

PM

25

(K

g m

on

th)

Months

Monthly Tirewear Mobile Emission PM25 during year 2010

and its Influence on Respiratory Diagnoses

Zip Code 79905

Primary PM 25Tirewear

Mobile Emission

Heart Diseases Hospital

Admission

Exhaust Mobile Emission

PM10 kg Asthma-

Bronchitis)

Exhaust Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=769 Linear Square R=715

Dona Ana County Zip Codes

88021880278807288048

Primary

Exhaust

PM 10 Zip

code

79905

Total

Primary

Exhaust

PM10

Dona Ana

Primary

Exhaust

PM 25 Zip

Code

79905

Total

Primary

Exhaust

PM25

Dona Ana

Series1 430378 111773 391915 102123

0

100000

200000

300000

400000

500000

AX

IS T

ITLE

Annual Comparison of the Mobile

Exhaust Emissions El Paso County

and Dona Ana 2010

Primary

PM 10

Brakewea

r Zip code

79905

Brakewea

r

particulat

e_PM10

Dona Ana

Primary

PM 10

Tirewear

Zip code

79905

Tirewear

particulat

e_PM10

Dona Ana

Series1 262585 48573 73754 11864

050000

100000150000200000250000300000

AX

IS T

ITLE

Annual Comparison of the Mobile

Brakewear Emissions El Paso County

and Dona Ana 2010

Figure Comparison of the Annual Mobile Emissions

of Primary PM10 Non-Exhauts (Brake ) from Dona

Ana County New Mexico and El Paso Texas Units

in KgMonth

Figure Comparison of the Annual Mobile Emissions

of Primary PM10-Exhauts Emission from Dona Ana

County New Mexico and El Paso Texas Units in

KgMonth

Primary

PM 25

Brakewe

ar Ziphellip

Brakewe

ar

particula

te_PMhellip

Primary

PM

25Tirewe

ar Ziphellip

Tirewear

particula

te_PM25

Donahellip

Series1 32645 6071 10919 1779

0

10000

20000

30000

40000

AX

IS T

ITLE

Annual Comparison of the

Mobile Exhaust Emissions El Paso

County and Dona Ana 2010

Figure Comparison of the Annual Mobile Emissions

of Primary PM10-Exhauts Emission from Dona Ana

County New Mexico and El Paso Texas Units in

KgMonth

Monthly Mobile Emission PM1025 kg During year 2006

and its Influence on Respiratory Diagnoses Dona Ana

County Zip Code 880218802788072

0

100

200

300

0

5000

10000

15000

Axi

s Ti

tle

Axis Title

Monthly Mobile Exhaust Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Total PrimaryMobile Exhaust_PM10

All Respiratory ICD-9 (AsthmaBronchitis)

050100150200250300

010002000300040005000

Axi

s Ti

tle

Axis Title

Monthly Mobile Brake Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Brakewearparticulate_PM10

All RespiratoryICD -9 (AsthmaBronchitis)

050100150200250300

0200400600800

10001200

Axi

s Ti

tle

Axis Title

Monthly Mobile Tirewear Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Tirewearparticulate_PM10

All Respiratory ICD -9 (AsthmaBronchitis)

Mobile Exhauts

Emission PM10

kg Asthma-

Bronchitis)

Brake Mobile

Emission PM10

kg and Heart

Diagnoses

Tirewear Mobile

Emission PM10

kg and Heart

Diagnoses

Linear Square

R= 951

Linear Square

R=625

Linear Square

R=525

Mobile Exhauts

Emission PM25

kg Asthma-

Bronchitis)

Brake Mobile

Emission PM25

kg and Heart

Diagnoses

Tirewear Mobile

Emission PM25

kg and Heart

Diagnoses

Linear Square

R= 986

Linear Square

R=691

Linear Square

R=601

Results

The results showed that mobile PM emissions in the urban areas close to urban Road and highways is putting at risk public health

and the proportion of diseases attributable to this exposure is potentially large

Brake wear emissions is much lower in freeways due to significantly reduced number of braking events while tire wear is much

higher in areas where studded tires are used The emission of exhaust gases are much higher in areas where there is a high

vehicular traffic

Brake Mobile

Emission PM10 kg

Asthma-Bronchitis)

Brake Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square

R=969

Linear Square

R=856

Exhaust Mobile

Emission PM10 kg

Asthma-Bronchitis)

Exhaust Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square

R=929

Linear Square

R=831

Tirewear Mobile

Emission PM10 kg

Asthma-Bronchitis)

Tirewear Mobile

Emission PM25 kg

and Heart Diagnoses

Linear Square R=769 Linear Square R=715

Brake Mobile

Emission PM10 kg

and Heart

Diagnoses

Brake Mobile

Emission PM25 kg

and Heart

Diagnoses

Exhaust Mobile

Emission PM10 kg

Asthma-Bronchitis)

Linear Square

R=625

Linear Square

R=691

Linear Square R=

951

Exhaust Mobile

Emission PM25 kg

Asthma-

Bronchitis)

Tire wear Mobile

Emission PM10 kg and

Heart Diagnoses

Tirewear Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square R=

986

Linear Square R=525 Linear Square

R=601

El Paso County

Dona Ana

County

BenMAP-CE

In this analysis the Program of Mapping and Analysis of Environmental Benefits-Community Edition

(BenMAP-CE) was used to Estimate the number and economic value of health impacts resulting from changes

in air pollution PM 25 Ugm3 in The El Paso Area

Health and Economic Benefits associated with the Response of PM25 Emission between

Base Year 2010

Number of Mortalities in 2010 Base Year Based on El Paso County Texas Department of State Health Services

Number of Mortalities in 2010 Base Year Based on El Paso County Texas

Department of State Health Services

cause of death

year

2010

Populatio

n

Affected

Backgro

und

Concentr

ation Pollutant

Rollback

Type

Avoided

Deaths

(

Populatio

n)

alzheimers disease 2010 40716 125 PM25

25

microgmAcircsup3

Rollback 9

diseases of the

heart 2010 15834 125 PM25

25

microgmAcircsup3

Rollback 35

influenza and

neumonia 2010 81432 125 PM25

25

microgmAcircsup3

Rollback 18

acute bronchitis

and bronchiolitis 2010 117624 125 PM25

25

microgmAcircsup3

Rollback 26

chronic lower

respiratory diseases 2010 54288 125 PM25

25

microgmAcircsup3

Rollback 12

The Basin-wide decrease in 4 ugm3 PM25 concentration after this

reduction control

Cause of death year 2010

Populatio

n

Affected

Background

Concentrati

on

Reduc

cion

scena

rio Polluta

nt

Rollback

Type

Avoi

ded

Deat

hs

(

Pop

ulati

on)

economic

benefits

analysis $

Alzheimers

disease 2010 121 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 9 12000

Diseases of the

heart 2010 470 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 35 35000

Influenza and

neumonia 2010 242 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 18 42500

Acute bronchitis

and bronchiolitis 2010 349 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 26 95000

Chronic lower

respiratory

diseases 2010 161 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 12 4500

$1 295000

PM25-related Mortalities Based on BenMAP-CE Estimate in 2010 Base Year with change in the concentrations levels

Health and Economic Benefits associated with the Response of PM25 Emission between

Base Year 2010 Increasing 7 Ugm3

Cause of death year 2010

Population

Affected

Deaths

avoided by

attaining 195

μgm3

standard

Background

Concentrati

on

Pollut

ant

Rollback

Type

Avoided

Deaths (

Populatio

n)

econo

mic

Unben

efits

analysi

s

Alzheimers

disease 2010 4524 195 PM25

25

microgmAcircsup3

Rollback 19 150000

Diseases of the

heart 2010 20358 195 PM25

25

microgmAcircsup3

Rollback 135 450000

Influenza and

neumonia 2010 126672 195 PM25

25

microgmAcircsup3

Rollback 38 525000

Acute bronchitis

and bronchiolitis 2010 162864 195 PM25

25

microgmAcircsup3

Rollback 36 122000

Chronic lower

respiratory

diseases 2010 99528 195 PM25

25

microgmAcircsup3

Rollback 12 650000

Conclusions

An excellent Pearson Correlation was established to analyze the relationship in the relative risks of hospitalization of Respiratory(RD) and cardiovascular (CVD) associated with ambient exposure caused by traffic emission in relation to their size andspecific sources of emission on different scenarios interior a border Urban Rural Urban restricted access (freeways andinterstates)

A significant correlation of PM1025 exposure from mobile emission and hospital admissions for selected Respiratory (RD) andcardiovascular (CVD) diagnoses was established The results showed that PM emissions in urban restricted access (freeways andinterstates) is mainly caused by traffic Therefore people living close to highways are more exposed higher vehicular emissions

Conclusions

We found statistically significant associations between mobile PM25 caused by traffic emission with Respiratory and Cardiovascular Diseases in the study areaSubsequently a correlation between cardio-respiratory mortality is established

A significant correlation of PM1025 exposure from mobile emission and hospital admissions for selected Respiratory (RD) and cardiovascular (CVD) diagnoses isestablished The results showed that PM emissions in urban restricted access (freeways and interstates) is mainly caused by traffic Therefore people living close tohighways receive higher vehicular emissions

The table shows the percentage of PM mobile exposure in the analyzed areas contributing to increase the risk of Respiratory and Cardiovascular Diseases

An examination was conducted of the synoptic and local meteorology for the June 2006 ozone episode using the WRF model to determine how meteorological parametersinfluence the formation transport and dispersion of ozone in the PdN The predominant synoptic feature of the ozone event day was the expansion intensification and slowprogression of an upper-level ridge of high pressure The high ozone episodes are associated with highly stable atmospheres strong temperature inversions with low mixingheights and therefore low mixing volumes Under these conditions emissions such as NOx lead to highly polluted conditions that favor ozone formation

BenMAP Conclusions

We have estimated the number and economic value of health impacts resulting

from changes in air pollution concentrations of PM 25 in the PdN region

Reduction of Pm 25 4 UGm3= Avoided 213 cases respiratory cardiovascular

diseses and Economic Benefits associated with the Response of PM25 Emission + $

1295000

Increase of PM25 7 ugm3 = increasing Dies= 326 economic Unbenefits= 2345000$

Bibliography

1 Dockery DW Pope CAI Xu X Spengler JD Ware JH Fay ME Ferris BG Speizer FE An association between air pollution and mortality in six US cities N Engl J Med 3291753ndash1759 (1993)

2 Samet JM Dominici F Curriero FC Coursac I Zeger SL Fine particulate air pollution and mortality in 20 US cities 1987ndash1994 N Engl J Med 3431742ndash1749 (2000)

3 Nel AE Diaz-Sanchez D Li N The role of particulate pollutants in pulmonary inflammation and asthma evidence for the involvement of organic chemicals and oxidative stress Curr Opin Pulm Med 20017 20ndash26

4 Westerholm R Karl-Erik E Exhaust emissions from lightand heavy-duty vehicles chemical composition impact of exhaust after treatment and fuel parameters Environ Health Perspect 102(suppl 4)13ndash23 (1994)

5 Bascom R Bromberg P Costa D Delvin R Dockery D Frampton M Lambert W Samet J Speizer F Utell

6 Health effects of outdoor air pollution Am J Respir Crit Care Med 1533ndash50 (1996)

7 Chow JC Watson JG Frazier CA Egami RT Goodrich A Ralph C Spatial and temporal source contributions to

8 PM10 and PM25 in Reno NV In PM-10 Implementation of Standards Transactions An APCAEPA International Speciality Conference San Francisco CA (Mathal CV Stonefield DH eds) PittsburghAPCA 1988439ndash457

9 overview In Particulate Matter Health and Regulatory Issues VIP-49 Proceedings of an International Specialty Conference 4ndash6 April 1995 Pittsburgh PA PittsburghAir and Waste Management Association 1995577ndash598

10 Kunzli N Kaiser R Medina S Studnicka M Chanel O

11 Filliger P Herry M Horak F Jr Puybonnieux-Texier V Quenel P et al Public-health impact of outdoor and traffic- related air pollution a European assessment Lancet 356795ndash801 (2000)

Bibliography

1 Sioutas C Delfino RJ Singh M Exposure assessment for atmospheric ultrafine particles (UFP) and implications in epidemiological research Environ Health Perspect 2005113947ndash955

2 Mosleh M Blau PJ Dumitrescu D (2004) Characteristics and morphology of wear particles from laboratory testing of disc brake materials Wear 2561128ndash1134

3 Kuumlnzli N et al (2000) Public-health impact of outdoor and traffi c-related air pollution a European assessment Lancet 356(9232)795ndash801

4 Dora C Phillips M eds (2000) Transport environment and health Copenhagen WHO Regional Office for Europe (WHO Regional Publications European Series No 89 httpwwweurowhointdocumente72015pdf accessed 26 November 2004)

5 Westerholm R Karl-Erik E Exhaust emissions from lightand

6 heavy-duty vehicles chemical composition impact of exhaust after treatment and fuel parameters Environ Health Perspect 102(suppl 4)13ndash23 (1994)

7 Fauser Tjell Mosbaek pigegaard Quantification of tire-Tread particles using extractable Organic Zinc as a Tracer Rubber Chemistry and Technology 1999 969Table shows some literature estimates of the contribution of tire wear to PM10 in air (Panko et al 2013) Gustafsson M Blomqvist G Gudmundsson A Dahl A Swietlicki E Bohgard M Lindbom J Ljungman A

8 Chen Y Shah N Huggins FE and Huffman GP (2006) Microanalysis of Ambient Particles from Lexington Ky by Electron Microscopy Atmos Environ 40 651ndash663

9 Donaldson K Tran CL Jimenez LA Duffin R Newby DE and Mills N (2005) Combustion-derived Nanoparticles A Review of Their Toxicology Following Inhalation Exposure Part Fibre Toxicol 2 10ndash23

10 Su D Serafino A Muller JO Jentoft RE Schlogl R and Fiorito S (2008) Cytotoxicity and Inflammatory Potential of Soot Particles of Low-emission Diesel Engines Environ Sci Technol 42 1761ndash1765

11 Maier KL Alessandrini F Beck-Speier I Hofer TPJ Diabatґe S Bitterle E Stoger T and Jakob T (2008) Health Effects of Ambient Particulate Matter-Biological Mechanisms and Inflammatory Responses to in Vitroand in Vivo Particle Exposures Inhalation Toxicol 20 319ndash337

Page 26: Studies of Air Pollutants and their Impact on Respiratory and ...€¦ · Ascarate Park C37 Monitoring Station: The National Ambient Air Quality Standard (NAAQS) for PM 10 and 2.5

Moves (Motor Vehicle Emission

Simulator)

The emission model is develop using the current equation to calculate direct traffic emissions from

vehicles in the form of PM is

Eext annual emissions are measured in grams of miles traveled by the vehicle (gVMT )

SL is the road surface loading in (gm2)

W is the average weight in tons of the vehicles on the road

K is the particle size multiplier for particle size range (eg gVMT for PM10 when using grams and miles)

P is the 7 number of wet days with at least 0254 mm of precipitation during the averaging period

N is the number of years considered in the averaging period

C is the particle size specific emissions factor in units of interest vehicle direct exhaust brake wear and tirewear

Modeling Simulation Domain and Emissions Scenarios

For simulations of mobile air quality emission inventories a motor vehicle emission simulator EPA (MOVES 2014a) was used

The modeling use input factors divided into seven section

parameters

On-Road Inventory local data

input

Scale

Geographic Bounds

Traffic intensity

Vehicle Type

Pollutants

Road Type

Fuel Types

Figure Source EPA US Environmental Protection Agency 2012- Moves 2010b Model

EPA Moves 2014a The modeling used input factors divided into six section

parameters On-Road Inventory local data input

Geographic Domains CountyNonattainment Area

Vehicle-Miles Traveled (VMT) is the total number of miles driven by all vehicles withina given time period and geographic area

Average speed range from 25 miles per

hour to 65 miles per hour

Vehicle Classes Motorcycle PassengerCarTruks light-duty Commercial Truck(6001-8500 lbs) Buses heave-duty trucksRefuse trucks School Bus Single UnitShort Haul-truck Single Unit Long Haul-truck Long Haul Truck Heavy-DutyVehicles (26001-33000 lbs)

Pollutants

Road TypeRural restricted Acces(Freeways and interstates) Rural and Restricted Acces Urban Restricted Acces Off-Network

Fuel Types Gasoline Diesel Fuel

Specific Road Types

Two road types for running emission from the MOVES can be

selected

(freeways and interstates)

Interior urban Urban

Figure Source EPA US Environmental Protection Agency 2012- Moves 2010b Model

VehiclesEquipment

This panel show which on-road vehicles will be modeled

Figure Source EPA US Environmental Protection Agency 2012- Moves 2010b Model

Long haul truck Short haul truck Inercity bus Ligth comercial truck

Passenger car Passenger truck Refuse truck

School bus Single unit long haul-truck

Single unit short haul-truck

Transit bus

Motor home

Motorcycle

Based on Department of Transportation Highway MOVES will Estimates Traffic

Emissions from Cars Trucks amp Motorcycles

Output Data Moves 2014a

Inventories of PM 10 25 Mobile Emission from all

on-Road Traffic

Exhaust Emission PM 10 25 gramsmile

Brake Wear Emission PM 10 25 gramsmile

Tire wear Emission PM 10 25 gramsmile

Date of Vehicle miles traveled (VMT) for

Day Week Month Year

Total Vehicle population

Vehicle age distribution

Simulation of Mobile Emission in the El PdN Region Zip Code 79905

Figure Total Emissions from road traffic in El Paso TX Area were estimated for PM10

Exhaust and Non exhaust emission in kilogramsmonth (Source EPA MOVES 2014a)

0

10000

20000

30000

40000

50000

PM

10 k

gM

on

th

Months

Monthly PM 10 Exhaust and Non-Exhaust Mobile Emissions 2010

On-Road Urban Restricted Area Zip Code 79905

Primary Exhaust PM 10 (kg) Primary PM 10 Brakewear (kg)

Primary PM 10 Tirewear (kg)

05000

100001500020000250003000035000400004500050000

PM

25

kg

Mo

nth

Months

Monthly PM 25 Exhaust and Non-Exhaust Mobile Emission 2010

On-Road Urban Restricted Area Zip Code 79905

Primary Exhaust PM 25 (kg) Primary PM 25 Brakewear (kg) Primary PM 25Tirewear (kg)

Figure Total Emissions from road traffic in El Paso TX Area were estimated for PM25

Exhaust and Non exhaust emission in kilogramsmonth (Source EPA MOVES 2014a)

Total Emissions from Road Traffic in El Paso County PM1025 Exhaust and Non exhaust Emission in kilogramsmonth

Taking the interests to the health risks related to PM 1025 mobile emission were simulated

Exhaust and Non-exhaust emissions contribute almost equally to total traffic-related PM1025 Emissions (Querol et al 2004 Bukowiecki et al 2009a Amato et al 2011)

Monthly PM 10 25 Exhaust and Non-Exhaust (BrakewearTirewear) Mobile

Emission 2010 On-Road Urban Restricted Area Zip Code 79905

Figure Total Emissions from road traffic in El Paso TX Area were estimated for PM10 25 Exhaust and Non Exhaust mobile

emission in kilograms per month (Source EPA MOVES)

0

10000

20000

30000

40000

50000

January February March April May June July August September October November December

PM

10

25

(K

ilog

ram

s)

Months

Summary- Monthly PM 10 25 Exhaust and Non-Exhaust Mobile

Emission 2010 On-Road Urban Restricted Area Zip Code 79905

Primary Exhaust PM 10 Primary PM 10 Brakewear Primary PM 10 Tirewear

Primary Exhaust PM 25 Primary PM 25 Brakewear Primary PM 25Tirewear

Exhaust Emissions PM1025 is reaching maximum emission 48000-42000 thousand of Kgmonth followedby Brake wear 29000-5000 thousand kgmonth and Tire wear with 9000-2000 kgmonth The results showthat the emissions of PM derived mainly from Exhaust and Brake are significantly higher in Urban Area

Annual Contribution of Mobile Emission PM 1025 (Kg) Zip Code 79905 El

Paso County 2010

Total Primary

Exhaust _PM10

39

Total Primary

Exhaust _PM25

36

Brakewear

particulate_PM10

18

Tirewear

particulate_PM10

4

Brakewear

particulate_PM25

2

Tirewear

particulate_PM25

1

0

5

10

15

20

25

30

35

40

45

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53

Fig Annual Average PM10 Concentrations at the

Chamizal C41 Station and PM1025 mobile

Concentration Zip code 79905

PM10 TCEQ (μgm3) Total Mobile Emission PM10 (Ugm3)

Fig Exhaust Emission is Contributing Approximately 74 of total

PM1025 Mobile Emissions following of Brake wear with 20 and Tire

wear with 5

Annual Average PM1025 ugm3 Mobile Emissions (Moves) 26 Chamizal C41

Monitoring Station (TCEQ Chamizal Station )

Predicting Mobile Emission and VTM

Estimation The PdN Region 2010

44E+09

46E+09

48E+09

5E+09

52E+09

54E+09

56E+09

58E+09

6E+09

62E+09

0

50000

100000

150000

200000

250000

300000

350000

20

10

20

11

20

12

20

13

20

14

20

15

20

16

20

17

20

18

20

21

20

22

20

23

20

24

20

25

20

26

20

27

20

28

20

29

20

30

EX

HA

US

T

EM

ISS

ION

MO

BIL

E (

KG

YE

AR

)

YEARS

Predict ing Mobile Exhaust Emission and VTM

Estimation

2010 - 2030 e l PdN Area

Total_ Exhaust PM10 Total_ Exhaust PM25 Distance (Miles)

Fig Predicting Mobile Exhaust PM1025 (kgMonth) Emission and VTM Estimation 2010

- 2030 el PdN Area

44E+09

46E+09

48E+09

5E+09

52E+09

54E+09

56E+09

58E+09

6E+09

62E+09

0

5000000

10000000

15000000

20000000

25000000

30000000

20

10

20

11

20

12

20

13

20

14

20

15

20

16

20

17

20

18

20

21

20

22

20

23

20

24

20

25

20

26

20

27

20

28

20

29

20

30

EX

HA

US

T

EM

ISS

ION

MO

BIL

E (

KG

YE

AR

)

YEARS

Predict ing Mobile Exhaust Emission and

VTM Estimation

2010 - 2030 e l PdN Area

CO NO2 NO NOx Distance

Fig Predicting Mobile Exhaust Emission and VTM Estimation

2010 - 2030 el PdN Area in El Paso TX Area were estimated for

Total CO NOx NO2 NO emission in kilograms per year

(Source EPA MOVES 2014a model)

The simulated Exhaust emissions in the future years shows a trend of reduction of this type of emissions in the

future years one factor should be the new hybrid technology is increasing by 476 since 2010 to 2015 and

use of catalytic converters diesel particulate filters and improved fuels and engines Non-exhaustive sources

will increase in the coming years because there is no control in the material of manufacture composed by Fe

Cu and Mn also not to be able to reduce the number of events of braking (Accelerations and decelerations)

45E+09

5E+09

55E+09

6E+09

65E+09

0

50000

100000

150000

200000

250000

201

0

201

1

201

2

201

3

201

4

201

5

201

6

201

7

201

8

202

1

202

2

202

3

202

4

202

5

202

6

202

7

202

8

202

9

203

0

NO

N-

EX

HA

US

T

EM

ISS

ION

MO

BIL

E

(KG

YE

AR

)

YEARS

Predicting Non Exhaust Mobile

Emission and VTM Estimation

2010 - 2030 el PdN Area

Brake_PM10 Tire_PM10 Distance (Miles)

Fig Predicting Mobile Exhaust PM1025 (kgMonth) Emission and VTM

Estimation 2010 - 2030 el PdN Area

Daily Avg PM1025

Levels of PM Mobile Emission Non-Exhaust -Rush Hour Periods Fall 2010 Zip Code

79905

00

100

200

300

400

500

600

Mo

bil

e P

M1

0 (k

g)

Rush Hours

Daily Avg PM10

Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush Hours

Periods 2010 Zip Code 79905

Total Primary Exhaust

_PM10 WinterSpring

Brakewear

particulate_PM10

WinterSpringTirewear particulate_PM10

WinterSpring

Total Primary Exhaust

_PM10 Summer

Brakewear

particulate_PM10 Summer

Tirewear Particulate_PM10

Summer

Total Primary Exhaust

_PM10 Fall

Brakewear

particulate_PM10 Fall

Tirewear particulate_PM10

Fall

00

50

100

150

200

250

300

350

Mo

bil

e P

M2

5 (k

g)

Rush hours

Daily Avg PM25

Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush

Hours Periods 2010 Zip Code 79905

Total Primary Exhaust _PM25

WinterSpring

Brakewear Particulate_PM25

WinterSpring

Tirewear particulate_PM25

WinterSpring

Total Primary Exhaust _PM25

Summer

Brakewear particulate_PM25

Summer

Tirewear particulate_PM25

Summer

Total Primary Exhaust _PM25

Fall

Brakewear particulate_PM25

Fall

Tirewear particulate_PM25

Fall

Figure Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush Hours Figure Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush Hours

GIS EMISSIONS INVENTORY SYSTEM A geographic information system (GIS) was used to established geographic scenarios with processed images of seasonal mobile

emissions in the PdN region Seasonal mapping is visualized for different types of pollutants Brakewear Exhaust and Tyrewear

Fg Graphics of GIS and Seasonal mobile Emission of particulate matter emission inventory Seasonal emission simulations were performed in kilograms and five contributing inputs factors were identified for

modeling 1) On the composition of the particulate material from different sources such as Exhaust and Non exhaust (Brake wear Tirewear) 2) The Vehicles Equipment clasification were selected according to

the use of gasoline and diesel fuel (motorcycle passenger car Light Duty Vehicles Trucks refuse truck Light Duty Vehicles Light Commercial Truck Light Duty Vehicles School Bus)

Winter Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

120354 67860 19065

Spring Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

139767 86702 24463

Summer Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

94747 62481 17630

Fall Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

75510 45542 12596

251 Descriptive Statistics Data Analysis

Weekly Correlation Analysis of Mobile Emission PM10 (Exhaust-Non-Exhaust) and Respiratory

Diagnoses WinterSpring Summer and Fall 2010

0

2

4

6

8

10

0

50

100

150

200

250

300

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21

Mo

rbid

ity

Dis

ch

arg

e

for

all R

esp

ira

tory

Dis

ea

se

ICD

-9

(A

sth

ma

-Bro

nc

hitis

)

WinterSpring Week

Weekly Avg Mobile PM10 Concentrations during

WinterSpring 2010 and its Influence on Respiratory

Diagnoses

Zip Code 79905

Total Medical data ZIP Code 79902

Total Mobile Emission PM10 (Ugm3)

0

1

2

3

4

5

6

7

0

20

40

60

80

100

Mo

rbid

ity

Dis

ch

arg

e

for

all R

esp

ira

tory

Dis

ea

se

ICD

-9

(Ast

hm

aB

ron

ch

itis

)

Weekly Avg Mobile PM10 Concentrations during

Summer 2010 and its Influence on Respiratory

Diagnoses

Summer 2010 Zip Code 79905

Total Mobile Emission PM10

Hospital Admission (Asthma-Bronchitis)

0

2

4

6

8

10

12

0

20

40

60

80

100

120

140

160

180

200

Mo

rbid

ity

dis

ch

arg

es

for

all r

esp

ira

tory

dis

ea

se

Weekly Avg Mobile PM10 Concentrations

during Fall 2010 and its Influence on Respiratory

Diagnoses

Zip Code 79905

Total Medical data ZIP Code 79902

Total Mobile Emission PM10 (Ugm3)

Mobile(Exhaust-Non-

Exhaust) PM10 and

Asthma-Bronchitis)

Linear R

Square

WinterSpring 734 ndash 39

Summer 614 ndash 32

Fall 548 -29

PM10 Mobile emission (Exhaust-Non-Exhaust)contributed significantly

association to the incidence of RD

Weekly Correlation Analysis of PM 25 Mobile Emission (Exhaust-Non-Exhaust)

and Cardiovascular Diagnoses WinterSpring Summer and Fall 2010

0010203040

00500

100015002000

Wee

k 1

Wee

k 2

Wee

k 3

Wee

k 4

Wee

k 5

Wee

k 6

Wee

k 7

Wee

k 8

Wee

k 9

Wee

k 1

0

Wee

k 1

1

Wee

k 1

2

Wee

k 1

3

Wee

k 1

4

Wee

k 1

5

Wee

k 1

6

Wee

k 1

7

Wee

k 1

8

Wee

k 1

9

Wee

k 2

0

Wee

k 2

1

Morb

idit

y d

isch

arg

es f

or

all

card

iovasc

ula

r d

isea

se

Weekly Avg PM25 Mobile Concentrations during

WinterSpring 2010 and its Influence on all Heart

Diagnoses

Zip Code 79905

Total All Heart Disease PM 25 mobile (μgm3)

0010203040

00

500

1000

1500

Mo

rbid

ity

dis

ch

arg

es

for

all

ca

rdio

va

scu

lar

dis

ea

se

Weeks

CORRELATION BETWEEN MOBILE PM25 ugm3

EXPOSURE TO HEART DISEASES SYMPTOMS

SUMMER SEASON 2010

Total All Heart Disease PM 25 mobile (μgm3)

Figure Statistical Analyses of the Relationship Between PM25 Caused by Traffic Emission( 26 of total Emission) with Heart diseases Source Hospital Admissions for Asthma Acute Bronchitis and Heart diseases in El Paso County zip code 79905 from Texas Health Care

Information Council in Austin Texas (Texas Health Care Information Council 2000)

00

10

20

30

40

0

50

100

150

We

ek 3

6

We

ek 3

7

We

ek 3

8

We

ek 3

9

We

ek 4

0

We

ek 4

1

We

ek 4

2

We

ek 4

3

We

ek 4

4

We

ek 4

5

We

ek 4

6

We

ek 4

7

We

ek 4

8

We

ek 4

9

We

ek 5

0

We

ek 5

1

We

ek 5

2

We

ek 5

3

Mo

rbid

ity

dis

ch

arg

es

for

all

ca

rdio

va

scu

lar

dis

ea

se

CORRELATION BETWEEN MOBILE PM25 ugm3

EXPOSURE TO HEART DISEASES SYMPTOMS FALL

SEASON 2010

Total All Heart Disease PM 25 mobile (μgm3)

Mobile(Exhaust-

Non-Exhaust)

PM10 and

Asthma-

Bronchitis)

Linear R

Square

WinterSpring 833 -42

Summer 620 -32

Fall 501-26

PM10 Mobile

emission (Exhaust-

Non-

Exhaust)contribut

ed significantly

association to the

incidence of CVD

Diseases

Monthly Brake Mobile Emission PM1025 kg During year 2010 and its Influence on

Respiratory Diagnoses Zip Code 79905

00200040006000800010000

010000200003000040000

PM

10

Mo

bile

(K

g)

Months

Monthly Brake Mobile Emission PM10 kg during year

2010 and its Influence on Respiratory Diagnoses

Zip Code 79905

Primary PM 10

Brakewear 00100020003000400050006000

0

1000

2000

3000

4000

PM

25

Mo

bil

e(K

g)

Months

Monthly Brake Mobile Emission PM25 during

year 2010 and its Influence on Heart Diagnoses

Zip Code 79905

Primary PM 25

Brakewear

Heart Diseases

Hospital

Admission

Brake Mobile Emission

PM10 kg Asthma-

Bronchitis)

Brake Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=969 Linear Square R=856

Monthly Mobile Exhaust Emission PM1025 During year 2010 and its Influence on

Respiratory Diagnoses Zip Code 79905

0

200

400

600

800

1000

0

10000

20000

30000

40000

50000

1 3 5 7 9 11

PM

10

(K

g m

on

th)

Months

Monthly Mobile Exhaust Emission PM10 during

year 2010 and its Influence on Respiratory

Diagnoses

Zip Code 79905

Primary Exhaust

PM 10

Respiratory Disease

(Asthma

Bronchitis) Hospital

Admission

0

100

200

300

400

500

600

0

10000

20000

30000

40000

50000

1 2 3 4 5 6 7 8 9 101112

PM

25

(K

g m

on

th)

Months

Monthly Exhaust Mobile Emission PM25 during

year 2010 and its Influence on Heart Diagnoses

Zip Code 79905

Primary Exhaust PM

25

Heart Diseases

Hospital Admission

Exhaust Mobile Emission

PM10 kg Asthma-

Bronchitis)

Exhaust Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=929 Linear Square R=831

Monthly Tire wear Mobile Emission PM1025 During year 2010 and its Influence on Heart

Diagnoses Zip Code 79905

0

100

200

300

400

500

600

700

800

900

0

1000

2000

3000

4000

5000

6000

7000

8000

9000

1 2 3 4 5 6 7 8 9 10 11 12

PM

10

(K

g m

on

th)

Months

Monthly Tirewear Mobile Emission PM10 during year 2010

and its Influence on Heart Diagnoses

Zip Code 79905

Primary PM 10 Tirewear

Mobile Emission

Respiratory Disease

(Asthma Bronchitis)

Hospital Admission

0

100

200

300

400

500

600

0

200

400

600

800

1000

1200

1400

1 2 3 4 5 6 7 8 9 10 11 12

PM

25

(K

g m

on

th)

Months

Monthly Tirewear Mobile Emission PM25 during year 2010

and its Influence on Respiratory Diagnoses

Zip Code 79905

Primary PM 25Tirewear

Mobile Emission

Heart Diseases Hospital

Admission

Exhaust Mobile Emission

PM10 kg Asthma-

Bronchitis)

Exhaust Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=769 Linear Square R=715

Dona Ana County Zip Codes

88021880278807288048

Primary

Exhaust

PM 10 Zip

code

79905

Total

Primary

Exhaust

PM10

Dona Ana

Primary

Exhaust

PM 25 Zip

Code

79905

Total

Primary

Exhaust

PM25

Dona Ana

Series1 430378 111773 391915 102123

0

100000

200000

300000

400000

500000

AX

IS T

ITLE

Annual Comparison of the Mobile

Exhaust Emissions El Paso County

and Dona Ana 2010

Primary

PM 10

Brakewea

r Zip code

79905

Brakewea

r

particulat

e_PM10

Dona Ana

Primary

PM 10

Tirewear

Zip code

79905

Tirewear

particulat

e_PM10

Dona Ana

Series1 262585 48573 73754 11864

050000

100000150000200000250000300000

AX

IS T

ITLE

Annual Comparison of the Mobile

Brakewear Emissions El Paso County

and Dona Ana 2010

Figure Comparison of the Annual Mobile Emissions

of Primary PM10 Non-Exhauts (Brake ) from Dona

Ana County New Mexico and El Paso Texas Units

in KgMonth

Figure Comparison of the Annual Mobile Emissions

of Primary PM10-Exhauts Emission from Dona Ana

County New Mexico and El Paso Texas Units in

KgMonth

Primary

PM 25

Brakewe

ar Ziphellip

Brakewe

ar

particula

te_PMhellip

Primary

PM

25Tirewe

ar Ziphellip

Tirewear

particula

te_PM25

Donahellip

Series1 32645 6071 10919 1779

0

10000

20000

30000

40000

AX

IS T

ITLE

Annual Comparison of the

Mobile Exhaust Emissions El Paso

County and Dona Ana 2010

Figure Comparison of the Annual Mobile Emissions

of Primary PM10-Exhauts Emission from Dona Ana

County New Mexico and El Paso Texas Units in

KgMonth

Monthly Mobile Emission PM1025 kg During year 2006

and its Influence on Respiratory Diagnoses Dona Ana

County Zip Code 880218802788072

0

100

200

300

0

5000

10000

15000

Axi

s Ti

tle

Axis Title

Monthly Mobile Exhaust Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Total PrimaryMobile Exhaust_PM10

All Respiratory ICD-9 (AsthmaBronchitis)

050100150200250300

010002000300040005000

Axi

s Ti

tle

Axis Title

Monthly Mobile Brake Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Brakewearparticulate_PM10

All RespiratoryICD -9 (AsthmaBronchitis)

050100150200250300

0200400600800

10001200

Axi

s Ti

tle

Axis Title

Monthly Mobile Tirewear Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Tirewearparticulate_PM10

All Respiratory ICD -9 (AsthmaBronchitis)

Mobile Exhauts

Emission PM10

kg Asthma-

Bronchitis)

Brake Mobile

Emission PM10

kg and Heart

Diagnoses

Tirewear Mobile

Emission PM10

kg and Heart

Diagnoses

Linear Square

R= 951

Linear Square

R=625

Linear Square

R=525

Mobile Exhauts

Emission PM25

kg Asthma-

Bronchitis)

Brake Mobile

Emission PM25

kg and Heart

Diagnoses

Tirewear Mobile

Emission PM25

kg and Heart

Diagnoses

Linear Square

R= 986

Linear Square

R=691

Linear Square

R=601

Results

The results showed that mobile PM emissions in the urban areas close to urban Road and highways is putting at risk public health

and the proportion of diseases attributable to this exposure is potentially large

Brake wear emissions is much lower in freeways due to significantly reduced number of braking events while tire wear is much

higher in areas where studded tires are used The emission of exhaust gases are much higher in areas where there is a high

vehicular traffic

Brake Mobile

Emission PM10 kg

Asthma-Bronchitis)

Brake Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square

R=969

Linear Square

R=856

Exhaust Mobile

Emission PM10 kg

Asthma-Bronchitis)

Exhaust Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square

R=929

Linear Square

R=831

Tirewear Mobile

Emission PM10 kg

Asthma-Bronchitis)

Tirewear Mobile

Emission PM25 kg

and Heart Diagnoses

Linear Square R=769 Linear Square R=715

Brake Mobile

Emission PM10 kg

and Heart

Diagnoses

Brake Mobile

Emission PM25 kg

and Heart

Diagnoses

Exhaust Mobile

Emission PM10 kg

Asthma-Bronchitis)

Linear Square

R=625

Linear Square

R=691

Linear Square R=

951

Exhaust Mobile

Emission PM25 kg

Asthma-

Bronchitis)

Tire wear Mobile

Emission PM10 kg and

Heart Diagnoses

Tirewear Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square R=

986

Linear Square R=525 Linear Square

R=601

El Paso County

Dona Ana

County

BenMAP-CE

In this analysis the Program of Mapping and Analysis of Environmental Benefits-Community Edition

(BenMAP-CE) was used to Estimate the number and economic value of health impacts resulting from changes

in air pollution PM 25 Ugm3 in The El Paso Area

Health and Economic Benefits associated with the Response of PM25 Emission between

Base Year 2010

Number of Mortalities in 2010 Base Year Based on El Paso County Texas Department of State Health Services

Number of Mortalities in 2010 Base Year Based on El Paso County Texas

Department of State Health Services

cause of death

year

2010

Populatio

n

Affected

Backgro

und

Concentr

ation Pollutant

Rollback

Type

Avoided

Deaths

(

Populatio

n)

alzheimers disease 2010 40716 125 PM25

25

microgmAcircsup3

Rollback 9

diseases of the

heart 2010 15834 125 PM25

25

microgmAcircsup3

Rollback 35

influenza and

neumonia 2010 81432 125 PM25

25

microgmAcircsup3

Rollback 18

acute bronchitis

and bronchiolitis 2010 117624 125 PM25

25

microgmAcircsup3

Rollback 26

chronic lower

respiratory diseases 2010 54288 125 PM25

25

microgmAcircsup3

Rollback 12

The Basin-wide decrease in 4 ugm3 PM25 concentration after this

reduction control

Cause of death year 2010

Populatio

n

Affected

Background

Concentrati

on

Reduc

cion

scena

rio Polluta

nt

Rollback

Type

Avoi

ded

Deat

hs

(

Pop

ulati

on)

economic

benefits

analysis $

Alzheimers

disease 2010 121 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 9 12000

Diseases of the

heart 2010 470 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 35 35000

Influenza and

neumonia 2010 242 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 18 42500

Acute bronchitis

and bronchiolitis 2010 349 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 26 95000

Chronic lower

respiratory

diseases 2010 161 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 12 4500

$1 295000

PM25-related Mortalities Based on BenMAP-CE Estimate in 2010 Base Year with change in the concentrations levels

Health and Economic Benefits associated with the Response of PM25 Emission between

Base Year 2010 Increasing 7 Ugm3

Cause of death year 2010

Population

Affected

Deaths

avoided by

attaining 195

μgm3

standard

Background

Concentrati

on

Pollut

ant

Rollback

Type

Avoided

Deaths (

Populatio

n)

econo

mic

Unben

efits

analysi

s

Alzheimers

disease 2010 4524 195 PM25

25

microgmAcircsup3

Rollback 19 150000

Diseases of the

heart 2010 20358 195 PM25

25

microgmAcircsup3

Rollback 135 450000

Influenza and

neumonia 2010 126672 195 PM25

25

microgmAcircsup3

Rollback 38 525000

Acute bronchitis

and bronchiolitis 2010 162864 195 PM25

25

microgmAcircsup3

Rollback 36 122000

Chronic lower

respiratory

diseases 2010 99528 195 PM25

25

microgmAcircsup3

Rollback 12 650000

Conclusions

An excellent Pearson Correlation was established to analyze the relationship in the relative risks of hospitalization of Respiratory(RD) and cardiovascular (CVD) associated with ambient exposure caused by traffic emission in relation to their size andspecific sources of emission on different scenarios interior a border Urban Rural Urban restricted access (freeways andinterstates)

A significant correlation of PM1025 exposure from mobile emission and hospital admissions for selected Respiratory (RD) andcardiovascular (CVD) diagnoses was established The results showed that PM emissions in urban restricted access (freeways andinterstates) is mainly caused by traffic Therefore people living close to highways are more exposed higher vehicular emissions

Conclusions

We found statistically significant associations between mobile PM25 caused by traffic emission with Respiratory and Cardiovascular Diseases in the study areaSubsequently a correlation between cardio-respiratory mortality is established

A significant correlation of PM1025 exposure from mobile emission and hospital admissions for selected Respiratory (RD) and cardiovascular (CVD) diagnoses isestablished The results showed that PM emissions in urban restricted access (freeways and interstates) is mainly caused by traffic Therefore people living close tohighways receive higher vehicular emissions

The table shows the percentage of PM mobile exposure in the analyzed areas contributing to increase the risk of Respiratory and Cardiovascular Diseases

An examination was conducted of the synoptic and local meteorology for the June 2006 ozone episode using the WRF model to determine how meteorological parametersinfluence the formation transport and dispersion of ozone in the PdN The predominant synoptic feature of the ozone event day was the expansion intensification and slowprogression of an upper-level ridge of high pressure The high ozone episodes are associated with highly stable atmospheres strong temperature inversions with low mixingheights and therefore low mixing volumes Under these conditions emissions such as NOx lead to highly polluted conditions that favor ozone formation

BenMAP Conclusions

We have estimated the number and economic value of health impacts resulting

from changes in air pollution concentrations of PM 25 in the PdN region

Reduction of Pm 25 4 UGm3= Avoided 213 cases respiratory cardiovascular

diseses and Economic Benefits associated with the Response of PM25 Emission + $

1295000

Increase of PM25 7 ugm3 = increasing Dies= 326 economic Unbenefits= 2345000$

Bibliography

1 Dockery DW Pope CAI Xu X Spengler JD Ware JH Fay ME Ferris BG Speizer FE An association between air pollution and mortality in six US cities N Engl J Med 3291753ndash1759 (1993)

2 Samet JM Dominici F Curriero FC Coursac I Zeger SL Fine particulate air pollution and mortality in 20 US cities 1987ndash1994 N Engl J Med 3431742ndash1749 (2000)

3 Nel AE Diaz-Sanchez D Li N The role of particulate pollutants in pulmonary inflammation and asthma evidence for the involvement of organic chemicals and oxidative stress Curr Opin Pulm Med 20017 20ndash26

4 Westerholm R Karl-Erik E Exhaust emissions from lightand heavy-duty vehicles chemical composition impact of exhaust after treatment and fuel parameters Environ Health Perspect 102(suppl 4)13ndash23 (1994)

5 Bascom R Bromberg P Costa D Delvin R Dockery D Frampton M Lambert W Samet J Speizer F Utell

6 Health effects of outdoor air pollution Am J Respir Crit Care Med 1533ndash50 (1996)

7 Chow JC Watson JG Frazier CA Egami RT Goodrich A Ralph C Spatial and temporal source contributions to

8 PM10 and PM25 in Reno NV In PM-10 Implementation of Standards Transactions An APCAEPA International Speciality Conference San Francisco CA (Mathal CV Stonefield DH eds) PittsburghAPCA 1988439ndash457

9 overview In Particulate Matter Health and Regulatory Issues VIP-49 Proceedings of an International Specialty Conference 4ndash6 April 1995 Pittsburgh PA PittsburghAir and Waste Management Association 1995577ndash598

10 Kunzli N Kaiser R Medina S Studnicka M Chanel O

11 Filliger P Herry M Horak F Jr Puybonnieux-Texier V Quenel P et al Public-health impact of outdoor and traffic- related air pollution a European assessment Lancet 356795ndash801 (2000)

Bibliography

1 Sioutas C Delfino RJ Singh M Exposure assessment for atmospheric ultrafine particles (UFP) and implications in epidemiological research Environ Health Perspect 2005113947ndash955

2 Mosleh M Blau PJ Dumitrescu D (2004) Characteristics and morphology of wear particles from laboratory testing of disc brake materials Wear 2561128ndash1134

3 Kuumlnzli N et al (2000) Public-health impact of outdoor and traffi c-related air pollution a European assessment Lancet 356(9232)795ndash801

4 Dora C Phillips M eds (2000) Transport environment and health Copenhagen WHO Regional Office for Europe (WHO Regional Publications European Series No 89 httpwwweurowhointdocumente72015pdf accessed 26 November 2004)

5 Westerholm R Karl-Erik E Exhaust emissions from lightand

6 heavy-duty vehicles chemical composition impact of exhaust after treatment and fuel parameters Environ Health Perspect 102(suppl 4)13ndash23 (1994)

7 Fauser Tjell Mosbaek pigegaard Quantification of tire-Tread particles using extractable Organic Zinc as a Tracer Rubber Chemistry and Technology 1999 969Table shows some literature estimates of the contribution of tire wear to PM10 in air (Panko et al 2013) Gustafsson M Blomqvist G Gudmundsson A Dahl A Swietlicki E Bohgard M Lindbom J Ljungman A

8 Chen Y Shah N Huggins FE and Huffman GP (2006) Microanalysis of Ambient Particles from Lexington Ky by Electron Microscopy Atmos Environ 40 651ndash663

9 Donaldson K Tran CL Jimenez LA Duffin R Newby DE and Mills N (2005) Combustion-derived Nanoparticles A Review of Their Toxicology Following Inhalation Exposure Part Fibre Toxicol 2 10ndash23

10 Su D Serafino A Muller JO Jentoft RE Schlogl R and Fiorito S (2008) Cytotoxicity and Inflammatory Potential of Soot Particles of Low-emission Diesel Engines Environ Sci Technol 42 1761ndash1765

11 Maier KL Alessandrini F Beck-Speier I Hofer TPJ Diabatґe S Bitterle E Stoger T and Jakob T (2008) Health Effects of Ambient Particulate Matter-Biological Mechanisms and Inflammatory Responses to in Vitroand in Vivo Particle Exposures Inhalation Toxicol 20 319ndash337

Page 27: Studies of Air Pollutants and their Impact on Respiratory and ...€¦ · Ascarate Park C37 Monitoring Station: The National Ambient Air Quality Standard (NAAQS) for PM 10 and 2.5

Modeling Simulation Domain and Emissions Scenarios

For simulations of mobile air quality emission inventories a motor vehicle emission simulator EPA (MOVES 2014a) was used

The modeling use input factors divided into seven section

parameters

On-Road Inventory local data

input

Scale

Geographic Bounds

Traffic intensity

Vehicle Type

Pollutants

Road Type

Fuel Types

Figure Source EPA US Environmental Protection Agency 2012- Moves 2010b Model

EPA Moves 2014a The modeling used input factors divided into six section

parameters On-Road Inventory local data input

Geographic Domains CountyNonattainment Area

Vehicle-Miles Traveled (VMT) is the total number of miles driven by all vehicles withina given time period and geographic area

Average speed range from 25 miles per

hour to 65 miles per hour

Vehicle Classes Motorcycle PassengerCarTruks light-duty Commercial Truck(6001-8500 lbs) Buses heave-duty trucksRefuse trucks School Bus Single UnitShort Haul-truck Single Unit Long Haul-truck Long Haul Truck Heavy-DutyVehicles (26001-33000 lbs)

Pollutants

Road TypeRural restricted Acces(Freeways and interstates) Rural and Restricted Acces Urban Restricted Acces Off-Network

Fuel Types Gasoline Diesel Fuel

Specific Road Types

Two road types for running emission from the MOVES can be

selected

(freeways and interstates)

Interior urban Urban

Figure Source EPA US Environmental Protection Agency 2012- Moves 2010b Model

VehiclesEquipment

This panel show which on-road vehicles will be modeled

Figure Source EPA US Environmental Protection Agency 2012- Moves 2010b Model

Long haul truck Short haul truck Inercity bus Ligth comercial truck

Passenger car Passenger truck Refuse truck

School bus Single unit long haul-truck

Single unit short haul-truck

Transit bus

Motor home

Motorcycle

Based on Department of Transportation Highway MOVES will Estimates Traffic

Emissions from Cars Trucks amp Motorcycles

Output Data Moves 2014a

Inventories of PM 10 25 Mobile Emission from all

on-Road Traffic

Exhaust Emission PM 10 25 gramsmile

Brake Wear Emission PM 10 25 gramsmile

Tire wear Emission PM 10 25 gramsmile

Date of Vehicle miles traveled (VMT) for

Day Week Month Year

Total Vehicle population

Vehicle age distribution

Simulation of Mobile Emission in the El PdN Region Zip Code 79905

Figure Total Emissions from road traffic in El Paso TX Area were estimated for PM10

Exhaust and Non exhaust emission in kilogramsmonth (Source EPA MOVES 2014a)

0

10000

20000

30000

40000

50000

PM

10 k

gM

on

th

Months

Monthly PM 10 Exhaust and Non-Exhaust Mobile Emissions 2010

On-Road Urban Restricted Area Zip Code 79905

Primary Exhaust PM 10 (kg) Primary PM 10 Brakewear (kg)

Primary PM 10 Tirewear (kg)

05000

100001500020000250003000035000400004500050000

PM

25

kg

Mo

nth

Months

Monthly PM 25 Exhaust and Non-Exhaust Mobile Emission 2010

On-Road Urban Restricted Area Zip Code 79905

Primary Exhaust PM 25 (kg) Primary PM 25 Brakewear (kg) Primary PM 25Tirewear (kg)

Figure Total Emissions from road traffic in El Paso TX Area were estimated for PM25

Exhaust and Non exhaust emission in kilogramsmonth (Source EPA MOVES 2014a)

Total Emissions from Road Traffic in El Paso County PM1025 Exhaust and Non exhaust Emission in kilogramsmonth

Taking the interests to the health risks related to PM 1025 mobile emission were simulated

Exhaust and Non-exhaust emissions contribute almost equally to total traffic-related PM1025 Emissions (Querol et al 2004 Bukowiecki et al 2009a Amato et al 2011)

Monthly PM 10 25 Exhaust and Non-Exhaust (BrakewearTirewear) Mobile

Emission 2010 On-Road Urban Restricted Area Zip Code 79905

Figure Total Emissions from road traffic in El Paso TX Area were estimated for PM10 25 Exhaust and Non Exhaust mobile

emission in kilograms per month (Source EPA MOVES)

0

10000

20000

30000

40000

50000

January February March April May June July August September October November December

PM

10

25

(K

ilog

ram

s)

Months

Summary- Monthly PM 10 25 Exhaust and Non-Exhaust Mobile

Emission 2010 On-Road Urban Restricted Area Zip Code 79905

Primary Exhaust PM 10 Primary PM 10 Brakewear Primary PM 10 Tirewear

Primary Exhaust PM 25 Primary PM 25 Brakewear Primary PM 25Tirewear

Exhaust Emissions PM1025 is reaching maximum emission 48000-42000 thousand of Kgmonth followedby Brake wear 29000-5000 thousand kgmonth and Tire wear with 9000-2000 kgmonth The results showthat the emissions of PM derived mainly from Exhaust and Brake are significantly higher in Urban Area

Annual Contribution of Mobile Emission PM 1025 (Kg) Zip Code 79905 El

Paso County 2010

Total Primary

Exhaust _PM10

39

Total Primary

Exhaust _PM25

36

Brakewear

particulate_PM10

18

Tirewear

particulate_PM10

4

Brakewear

particulate_PM25

2

Tirewear

particulate_PM25

1

0

5

10

15

20

25

30

35

40

45

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53

Fig Annual Average PM10 Concentrations at the

Chamizal C41 Station and PM1025 mobile

Concentration Zip code 79905

PM10 TCEQ (μgm3) Total Mobile Emission PM10 (Ugm3)

Fig Exhaust Emission is Contributing Approximately 74 of total

PM1025 Mobile Emissions following of Brake wear with 20 and Tire

wear with 5

Annual Average PM1025 ugm3 Mobile Emissions (Moves) 26 Chamizal C41

Monitoring Station (TCEQ Chamizal Station )

Predicting Mobile Emission and VTM

Estimation The PdN Region 2010

44E+09

46E+09

48E+09

5E+09

52E+09

54E+09

56E+09

58E+09

6E+09

62E+09

0

50000

100000

150000

200000

250000

300000

350000

20

10

20

11

20

12

20

13

20

14

20

15

20

16

20

17

20

18

20

21

20

22

20

23

20

24

20

25

20

26

20

27

20

28

20

29

20

30

EX

HA

US

T

EM

ISS

ION

MO

BIL

E (

KG

YE

AR

)

YEARS

Predict ing Mobile Exhaust Emission and VTM

Estimation

2010 - 2030 e l PdN Area

Total_ Exhaust PM10 Total_ Exhaust PM25 Distance (Miles)

Fig Predicting Mobile Exhaust PM1025 (kgMonth) Emission and VTM Estimation 2010

- 2030 el PdN Area

44E+09

46E+09

48E+09

5E+09

52E+09

54E+09

56E+09

58E+09

6E+09

62E+09

0

5000000

10000000

15000000

20000000

25000000

30000000

20

10

20

11

20

12

20

13

20

14

20

15

20

16

20

17

20

18

20

21

20

22

20

23

20

24

20

25

20

26

20

27

20

28

20

29

20

30

EX

HA

US

T

EM

ISS

ION

MO

BIL

E (

KG

YE

AR

)

YEARS

Predict ing Mobile Exhaust Emission and

VTM Estimation

2010 - 2030 e l PdN Area

CO NO2 NO NOx Distance

Fig Predicting Mobile Exhaust Emission and VTM Estimation

2010 - 2030 el PdN Area in El Paso TX Area were estimated for

Total CO NOx NO2 NO emission in kilograms per year

(Source EPA MOVES 2014a model)

The simulated Exhaust emissions in the future years shows a trend of reduction of this type of emissions in the

future years one factor should be the new hybrid technology is increasing by 476 since 2010 to 2015 and

use of catalytic converters diesel particulate filters and improved fuels and engines Non-exhaustive sources

will increase in the coming years because there is no control in the material of manufacture composed by Fe

Cu and Mn also not to be able to reduce the number of events of braking (Accelerations and decelerations)

45E+09

5E+09

55E+09

6E+09

65E+09

0

50000

100000

150000

200000

250000

201

0

201

1

201

2

201

3

201

4

201

5

201

6

201

7

201

8

202

1

202

2

202

3

202

4

202

5

202

6

202

7

202

8

202

9

203

0

NO

N-

EX

HA

US

T

EM

ISS

ION

MO

BIL

E

(KG

YE

AR

)

YEARS

Predicting Non Exhaust Mobile

Emission and VTM Estimation

2010 - 2030 el PdN Area

Brake_PM10 Tire_PM10 Distance (Miles)

Fig Predicting Mobile Exhaust PM1025 (kgMonth) Emission and VTM

Estimation 2010 - 2030 el PdN Area

Daily Avg PM1025

Levels of PM Mobile Emission Non-Exhaust -Rush Hour Periods Fall 2010 Zip Code

79905

00

100

200

300

400

500

600

Mo

bil

e P

M1

0 (k

g)

Rush Hours

Daily Avg PM10

Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush Hours

Periods 2010 Zip Code 79905

Total Primary Exhaust

_PM10 WinterSpring

Brakewear

particulate_PM10

WinterSpringTirewear particulate_PM10

WinterSpring

Total Primary Exhaust

_PM10 Summer

Brakewear

particulate_PM10 Summer

Tirewear Particulate_PM10

Summer

Total Primary Exhaust

_PM10 Fall

Brakewear

particulate_PM10 Fall

Tirewear particulate_PM10

Fall

00

50

100

150

200

250

300

350

Mo

bil

e P

M2

5 (k

g)

Rush hours

Daily Avg PM25

Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush

Hours Periods 2010 Zip Code 79905

Total Primary Exhaust _PM25

WinterSpring

Brakewear Particulate_PM25

WinterSpring

Tirewear particulate_PM25

WinterSpring

Total Primary Exhaust _PM25

Summer

Brakewear particulate_PM25

Summer

Tirewear particulate_PM25

Summer

Total Primary Exhaust _PM25

Fall

Brakewear particulate_PM25

Fall

Tirewear particulate_PM25

Fall

Figure Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush Hours Figure Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush Hours

GIS EMISSIONS INVENTORY SYSTEM A geographic information system (GIS) was used to established geographic scenarios with processed images of seasonal mobile

emissions in the PdN region Seasonal mapping is visualized for different types of pollutants Brakewear Exhaust and Tyrewear

Fg Graphics of GIS and Seasonal mobile Emission of particulate matter emission inventory Seasonal emission simulations were performed in kilograms and five contributing inputs factors were identified for

modeling 1) On the composition of the particulate material from different sources such as Exhaust and Non exhaust (Brake wear Tirewear) 2) The Vehicles Equipment clasification were selected according to

the use of gasoline and diesel fuel (motorcycle passenger car Light Duty Vehicles Trucks refuse truck Light Duty Vehicles Light Commercial Truck Light Duty Vehicles School Bus)

Winter Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

120354 67860 19065

Spring Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

139767 86702 24463

Summer Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

94747 62481 17630

Fall Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

75510 45542 12596

251 Descriptive Statistics Data Analysis

Weekly Correlation Analysis of Mobile Emission PM10 (Exhaust-Non-Exhaust) and Respiratory

Diagnoses WinterSpring Summer and Fall 2010

0

2

4

6

8

10

0

50

100

150

200

250

300

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21

Mo

rbid

ity

Dis

ch

arg

e

for

all R

esp

ira

tory

Dis

ea

se

ICD

-9

(A

sth

ma

-Bro

nc

hitis

)

WinterSpring Week

Weekly Avg Mobile PM10 Concentrations during

WinterSpring 2010 and its Influence on Respiratory

Diagnoses

Zip Code 79905

Total Medical data ZIP Code 79902

Total Mobile Emission PM10 (Ugm3)

0

1

2

3

4

5

6

7

0

20

40

60

80

100

Mo

rbid

ity

Dis

ch

arg

e

for

all R

esp

ira

tory

Dis

ea

se

ICD

-9

(Ast

hm

aB

ron

ch

itis

)

Weekly Avg Mobile PM10 Concentrations during

Summer 2010 and its Influence on Respiratory

Diagnoses

Summer 2010 Zip Code 79905

Total Mobile Emission PM10

Hospital Admission (Asthma-Bronchitis)

0

2

4

6

8

10

12

0

20

40

60

80

100

120

140

160

180

200

Mo

rbid

ity

dis

ch

arg

es

for

all r

esp

ira

tory

dis

ea

se

Weekly Avg Mobile PM10 Concentrations

during Fall 2010 and its Influence on Respiratory

Diagnoses

Zip Code 79905

Total Medical data ZIP Code 79902

Total Mobile Emission PM10 (Ugm3)

Mobile(Exhaust-Non-

Exhaust) PM10 and

Asthma-Bronchitis)

Linear R

Square

WinterSpring 734 ndash 39

Summer 614 ndash 32

Fall 548 -29

PM10 Mobile emission (Exhaust-Non-Exhaust)contributed significantly

association to the incidence of RD

Weekly Correlation Analysis of PM 25 Mobile Emission (Exhaust-Non-Exhaust)

and Cardiovascular Diagnoses WinterSpring Summer and Fall 2010

0010203040

00500

100015002000

Wee

k 1

Wee

k 2

Wee

k 3

Wee

k 4

Wee

k 5

Wee

k 6

Wee

k 7

Wee

k 8

Wee

k 9

Wee

k 1

0

Wee

k 1

1

Wee

k 1

2

Wee

k 1

3

Wee

k 1

4

Wee

k 1

5

Wee

k 1

6

Wee

k 1

7

Wee

k 1

8

Wee

k 1

9

Wee

k 2

0

Wee

k 2

1

Morb

idit

y d

isch

arg

es f

or

all

card

iovasc

ula

r d

isea

se

Weekly Avg PM25 Mobile Concentrations during

WinterSpring 2010 and its Influence on all Heart

Diagnoses

Zip Code 79905

Total All Heart Disease PM 25 mobile (μgm3)

0010203040

00

500

1000

1500

Mo

rbid

ity

dis

ch

arg

es

for

all

ca

rdio

va

scu

lar

dis

ea

se

Weeks

CORRELATION BETWEEN MOBILE PM25 ugm3

EXPOSURE TO HEART DISEASES SYMPTOMS

SUMMER SEASON 2010

Total All Heart Disease PM 25 mobile (μgm3)

Figure Statistical Analyses of the Relationship Between PM25 Caused by Traffic Emission( 26 of total Emission) with Heart diseases Source Hospital Admissions for Asthma Acute Bronchitis and Heart diseases in El Paso County zip code 79905 from Texas Health Care

Information Council in Austin Texas (Texas Health Care Information Council 2000)

00

10

20

30

40

0

50

100

150

We

ek 3

6

We

ek 3

7

We

ek 3

8

We

ek 3

9

We

ek 4

0

We

ek 4

1

We

ek 4

2

We

ek 4

3

We

ek 4

4

We

ek 4

5

We

ek 4

6

We

ek 4

7

We

ek 4

8

We

ek 4

9

We

ek 5

0

We

ek 5

1

We

ek 5

2

We

ek 5

3

Mo

rbid

ity

dis

ch

arg

es

for

all

ca

rdio

va

scu

lar

dis

ea

se

CORRELATION BETWEEN MOBILE PM25 ugm3

EXPOSURE TO HEART DISEASES SYMPTOMS FALL

SEASON 2010

Total All Heart Disease PM 25 mobile (μgm3)

Mobile(Exhaust-

Non-Exhaust)

PM10 and

Asthma-

Bronchitis)

Linear R

Square

WinterSpring 833 -42

Summer 620 -32

Fall 501-26

PM10 Mobile

emission (Exhaust-

Non-

Exhaust)contribut

ed significantly

association to the

incidence of CVD

Diseases

Monthly Brake Mobile Emission PM1025 kg During year 2010 and its Influence on

Respiratory Diagnoses Zip Code 79905

00200040006000800010000

010000200003000040000

PM

10

Mo

bile

(K

g)

Months

Monthly Brake Mobile Emission PM10 kg during year

2010 and its Influence on Respiratory Diagnoses

Zip Code 79905

Primary PM 10

Brakewear 00100020003000400050006000

0

1000

2000

3000

4000

PM

25

Mo

bil

e(K

g)

Months

Monthly Brake Mobile Emission PM25 during

year 2010 and its Influence on Heart Diagnoses

Zip Code 79905

Primary PM 25

Brakewear

Heart Diseases

Hospital

Admission

Brake Mobile Emission

PM10 kg Asthma-

Bronchitis)

Brake Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=969 Linear Square R=856

Monthly Mobile Exhaust Emission PM1025 During year 2010 and its Influence on

Respiratory Diagnoses Zip Code 79905

0

200

400

600

800

1000

0

10000

20000

30000

40000

50000

1 3 5 7 9 11

PM

10

(K

g m

on

th)

Months

Monthly Mobile Exhaust Emission PM10 during

year 2010 and its Influence on Respiratory

Diagnoses

Zip Code 79905

Primary Exhaust

PM 10

Respiratory Disease

(Asthma

Bronchitis) Hospital

Admission

0

100

200

300

400

500

600

0

10000

20000

30000

40000

50000

1 2 3 4 5 6 7 8 9 101112

PM

25

(K

g m

on

th)

Months

Monthly Exhaust Mobile Emission PM25 during

year 2010 and its Influence on Heart Diagnoses

Zip Code 79905

Primary Exhaust PM

25

Heart Diseases

Hospital Admission

Exhaust Mobile Emission

PM10 kg Asthma-

Bronchitis)

Exhaust Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=929 Linear Square R=831

Monthly Tire wear Mobile Emission PM1025 During year 2010 and its Influence on Heart

Diagnoses Zip Code 79905

0

100

200

300

400

500

600

700

800

900

0

1000

2000

3000

4000

5000

6000

7000

8000

9000

1 2 3 4 5 6 7 8 9 10 11 12

PM

10

(K

g m

on

th)

Months

Monthly Tirewear Mobile Emission PM10 during year 2010

and its Influence on Heart Diagnoses

Zip Code 79905

Primary PM 10 Tirewear

Mobile Emission

Respiratory Disease

(Asthma Bronchitis)

Hospital Admission

0

100

200

300

400

500

600

0

200

400

600

800

1000

1200

1400

1 2 3 4 5 6 7 8 9 10 11 12

PM

25

(K

g m

on

th)

Months

Monthly Tirewear Mobile Emission PM25 during year 2010

and its Influence on Respiratory Diagnoses

Zip Code 79905

Primary PM 25Tirewear

Mobile Emission

Heart Diseases Hospital

Admission

Exhaust Mobile Emission

PM10 kg Asthma-

Bronchitis)

Exhaust Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=769 Linear Square R=715

Dona Ana County Zip Codes

88021880278807288048

Primary

Exhaust

PM 10 Zip

code

79905

Total

Primary

Exhaust

PM10

Dona Ana

Primary

Exhaust

PM 25 Zip

Code

79905

Total

Primary

Exhaust

PM25

Dona Ana

Series1 430378 111773 391915 102123

0

100000

200000

300000

400000

500000

AX

IS T

ITLE

Annual Comparison of the Mobile

Exhaust Emissions El Paso County

and Dona Ana 2010

Primary

PM 10

Brakewea

r Zip code

79905

Brakewea

r

particulat

e_PM10

Dona Ana

Primary

PM 10

Tirewear

Zip code

79905

Tirewear

particulat

e_PM10

Dona Ana

Series1 262585 48573 73754 11864

050000

100000150000200000250000300000

AX

IS T

ITLE

Annual Comparison of the Mobile

Brakewear Emissions El Paso County

and Dona Ana 2010

Figure Comparison of the Annual Mobile Emissions

of Primary PM10 Non-Exhauts (Brake ) from Dona

Ana County New Mexico and El Paso Texas Units

in KgMonth

Figure Comparison of the Annual Mobile Emissions

of Primary PM10-Exhauts Emission from Dona Ana

County New Mexico and El Paso Texas Units in

KgMonth

Primary

PM 25

Brakewe

ar Ziphellip

Brakewe

ar

particula

te_PMhellip

Primary

PM

25Tirewe

ar Ziphellip

Tirewear

particula

te_PM25

Donahellip

Series1 32645 6071 10919 1779

0

10000

20000

30000

40000

AX

IS T

ITLE

Annual Comparison of the

Mobile Exhaust Emissions El Paso

County and Dona Ana 2010

Figure Comparison of the Annual Mobile Emissions

of Primary PM10-Exhauts Emission from Dona Ana

County New Mexico and El Paso Texas Units in

KgMonth

Monthly Mobile Emission PM1025 kg During year 2006

and its Influence on Respiratory Diagnoses Dona Ana

County Zip Code 880218802788072

0

100

200

300

0

5000

10000

15000

Axi

s Ti

tle

Axis Title

Monthly Mobile Exhaust Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Total PrimaryMobile Exhaust_PM10

All Respiratory ICD-9 (AsthmaBronchitis)

050100150200250300

010002000300040005000

Axi

s Ti

tle

Axis Title

Monthly Mobile Brake Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Brakewearparticulate_PM10

All RespiratoryICD -9 (AsthmaBronchitis)

050100150200250300

0200400600800

10001200

Axi

s Ti

tle

Axis Title

Monthly Mobile Tirewear Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Tirewearparticulate_PM10

All Respiratory ICD -9 (AsthmaBronchitis)

Mobile Exhauts

Emission PM10

kg Asthma-

Bronchitis)

Brake Mobile

Emission PM10

kg and Heart

Diagnoses

Tirewear Mobile

Emission PM10

kg and Heart

Diagnoses

Linear Square

R= 951

Linear Square

R=625

Linear Square

R=525

Mobile Exhauts

Emission PM25

kg Asthma-

Bronchitis)

Brake Mobile

Emission PM25

kg and Heart

Diagnoses

Tirewear Mobile

Emission PM25

kg and Heart

Diagnoses

Linear Square

R= 986

Linear Square

R=691

Linear Square

R=601

Results

The results showed that mobile PM emissions in the urban areas close to urban Road and highways is putting at risk public health

and the proportion of diseases attributable to this exposure is potentially large

Brake wear emissions is much lower in freeways due to significantly reduced number of braking events while tire wear is much

higher in areas where studded tires are used The emission of exhaust gases are much higher in areas where there is a high

vehicular traffic

Brake Mobile

Emission PM10 kg

Asthma-Bronchitis)

Brake Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square

R=969

Linear Square

R=856

Exhaust Mobile

Emission PM10 kg

Asthma-Bronchitis)

Exhaust Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square

R=929

Linear Square

R=831

Tirewear Mobile

Emission PM10 kg

Asthma-Bronchitis)

Tirewear Mobile

Emission PM25 kg

and Heart Diagnoses

Linear Square R=769 Linear Square R=715

Brake Mobile

Emission PM10 kg

and Heart

Diagnoses

Brake Mobile

Emission PM25 kg

and Heart

Diagnoses

Exhaust Mobile

Emission PM10 kg

Asthma-Bronchitis)

Linear Square

R=625

Linear Square

R=691

Linear Square R=

951

Exhaust Mobile

Emission PM25 kg

Asthma-

Bronchitis)

Tire wear Mobile

Emission PM10 kg and

Heart Diagnoses

Tirewear Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square R=

986

Linear Square R=525 Linear Square

R=601

El Paso County

Dona Ana

County

BenMAP-CE

In this analysis the Program of Mapping and Analysis of Environmental Benefits-Community Edition

(BenMAP-CE) was used to Estimate the number and economic value of health impacts resulting from changes

in air pollution PM 25 Ugm3 in The El Paso Area

Health and Economic Benefits associated with the Response of PM25 Emission between

Base Year 2010

Number of Mortalities in 2010 Base Year Based on El Paso County Texas Department of State Health Services

Number of Mortalities in 2010 Base Year Based on El Paso County Texas

Department of State Health Services

cause of death

year

2010

Populatio

n

Affected

Backgro

und

Concentr

ation Pollutant

Rollback

Type

Avoided

Deaths

(

Populatio

n)

alzheimers disease 2010 40716 125 PM25

25

microgmAcircsup3

Rollback 9

diseases of the

heart 2010 15834 125 PM25

25

microgmAcircsup3

Rollback 35

influenza and

neumonia 2010 81432 125 PM25

25

microgmAcircsup3

Rollback 18

acute bronchitis

and bronchiolitis 2010 117624 125 PM25

25

microgmAcircsup3

Rollback 26

chronic lower

respiratory diseases 2010 54288 125 PM25

25

microgmAcircsup3

Rollback 12

The Basin-wide decrease in 4 ugm3 PM25 concentration after this

reduction control

Cause of death year 2010

Populatio

n

Affected

Background

Concentrati

on

Reduc

cion

scena

rio Polluta

nt

Rollback

Type

Avoi

ded

Deat

hs

(

Pop

ulati

on)

economic

benefits

analysis $

Alzheimers

disease 2010 121 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 9 12000

Diseases of the

heart 2010 470 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 35 35000

Influenza and

neumonia 2010 242 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 18 42500

Acute bronchitis

and bronchiolitis 2010 349 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 26 95000

Chronic lower

respiratory

diseases 2010 161 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 12 4500

$1 295000

PM25-related Mortalities Based on BenMAP-CE Estimate in 2010 Base Year with change in the concentrations levels

Health and Economic Benefits associated with the Response of PM25 Emission between

Base Year 2010 Increasing 7 Ugm3

Cause of death year 2010

Population

Affected

Deaths

avoided by

attaining 195

μgm3

standard

Background

Concentrati

on

Pollut

ant

Rollback

Type

Avoided

Deaths (

Populatio

n)

econo

mic

Unben

efits

analysi

s

Alzheimers

disease 2010 4524 195 PM25

25

microgmAcircsup3

Rollback 19 150000

Diseases of the

heart 2010 20358 195 PM25

25

microgmAcircsup3

Rollback 135 450000

Influenza and

neumonia 2010 126672 195 PM25

25

microgmAcircsup3

Rollback 38 525000

Acute bronchitis

and bronchiolitis 2010 162864 195 PM25

25

microgmAcircsup3

Rollback 36 122000

Chronic lower

respiratory

diseases 2010 99528 195 PM25

25

microgmAcircsup3

Rollback 12 650000

Conclusions

An excellent Pearson Correlation was established to analyze the relationship in the relative risks of hospitalization of Respiratory(RD) and cardiovascular (CVD) associated with ambient exposure caused by traffic emission in relation to their size andspecific sources of emission on different scenarios interior a border Urban Rural Urban restricted access (freeways andinterstates)

A significant correlation of PM1025 exposure from mobile emission and hospital admissions for selected Respiratory (RD) andcardiovascular (CVD) diagnoses was established The results showed that PM emissions in urban restricted access (freeways andinterstates) is mainly caused by traffic Therefore people living close to highways are more exposed higher vehicular emissions

Conclusions

We found statistically significant associations between mobile PM25 caused by traffic emission with Respiratory and Cardiovascular Diseases in the study areaSubsequently a correlation between cardio-respiratory mortality is established

A significant correlation of PM1025 exposure from mobile emission and hospital admissions for selected Respiratory (RD) and cardiovascular (CVD) diagnoses isestablished The results showed that PM emissions in urban restricted access (freeways and interstates) is mainly caused by traffic Therefore people living close tohighways receive higher vehicular emissions

The table shows the percentage of PM mobile exposure in the analyzed areas contributing to increase the risk of Respiratory and Cardiovascular Diseases

An examination was conducted of the synoptic and local meteorology for the June 2006 ozone episode using the WRF model to determine how meteorological parametersinfluence the formation transport and dispersion of ozone in the PdN The predominant synoptic feature of the ozone event day was the expansion intensification and slowprogression of an upper-level ridge of high pressure The high ozone episodes are associated with highly stable atmospheres strong temperature inversions with low mixingheights and therefore low mixing volumes Under these conditions emissions such as NOx lead to highly polluted conditions that favor ozone formation

BenMAP Conclusions

We have estimated the number and economic value of health impacts resulting

from changes in air pollution concentrations of PM 25 in the PdN region

Reduction of Pm 25 4 UGm3= Avoided 213 cases respiratory cardiovascular

diseses and Economic Benefits associated with the Response of PM25 Emission + $

1295000

Increase of PM25 7 ugm3 = increasing Dies= 326 economic Unbenefits= 2345000$

Bibliography

1 Dockery DW Pope CAI Xu X Spengler JD Ware JH Fay ME Ferris BG Speizer FE An association between air pollution and mortality in six US cities N Engl J Med 3291753ndash1759 (1993)

2 Samet JM Dominici F Curriero FC Coursac I Zeger SL Fine particulate air pollution and mortality in 20 US cities 1987ndash1994 N Engl J Med 3431742ndash1749 (2000)

3 Nel AE Diaz-Sanchez D Li N The role of particulate pollutants in pulmonary inflammation and asthma evidence for the involvement of organic chemicals and oxidative stress Curr Opin Pulm Med 20017 20ndash26

4 Westerholm R Karl-Erik E Exhaust emissions from lightand heavy-duty vehicles chemical composition impact of exhaust after treatment and fuel parameters Environ Health Perspect 102(suppl 4)13ndash23 (1994)

5 Bascom R Bromberg P Costa D Delvin R Dockery D Frampton M Lambert W Samet J Speizer F Utell

6 Health effects of outdoor air pollution Am J Respir Crit Care Med 1533ndash50 (1996)

7 Chow JC Watson JG Frazier CA Egami RT Goodrich A Ralph C Spatial and temporal source contributions to

8 PM10 and PM25 in Reno NV In PM-10 Implementation of Standards Transactions An APCAEPA International Speciality Conference San Francisco CA (Mathal CV Stonefield DH eds) PittsburghAPCA 1988439ndash457

9 overview In Particulate Matter Health and Regulatory Issues VIP-49 Proceedings of an International Specialty Conference 4ndash6 April 1995 Pittsburgh PA PittsburghAir and Waste Management Association 1995577ndash598

10 Kunzli N Kaiser R Medina S Studnicka M Chanel O

11 Filliger P Herry M Horak F Jr Puybonnieux-Texier V Quenel P et al Public-health impact of outdoor and traffic- related air pollution a European assessment Lancet 356795ndash801 (2000)

Bibliography

1 Sioutas C Delfino RJ Singh M Exposure assessment for atmospheric ultrafine particles (UFP) and implications in epidemiological research Environ Health Perspect 2005113947ndash955

2 Mosleh M Blau PJ Dumitrescu D (2004) Characteristics and morphology of wear particles from laboratory testing of disc brake materials Wear 2561128ndash1134

3 Kuumlnzli N et al (2000) Public-health impact of outdoor and traffi c-related air pollution a European assessment Lancet 356(9232)795ndash801

4 Dora C Phillips M eds (2000) Transport environment and health Copenhagen WHO Regional Office for Europe (WHO Regional Publications European Series No 89 httpwwweurowhointdocumente72015pdf accessed 26 November 2004)

5 Westerholm R Karl-Erik E Exhaust emissions from lightand

6 heavy-duty vehicles chemical composition impact of exhaust after treatment and fuel parameters Environ Health Perspect 102(suppl 4)13ndash23 (1994)

7 Fauser Tjell Mosbaek pigegaard Quantification of tire-Tread particles using extractable Organic Zinc as a Tracer Rubber Chemistry and Technology 1999 969Table shows some literature estimates of the contribution of tire wear to PM10 in air (Panko et al 2013) Gustafsson M Blomqvist G Gudmundsson A Dahl A Swietlicki E Bohgard M Lindbom J Ljungman A

8 Chen Y Shah N Huggins FE and Huffman GP (2006) Microanalysis of Ambient Particles from Lexington Ky by Electron Microscopy Atmos Environ 40 651ndash663

9 Donaldson K Tran CL Jimenez LA Duffin R Newby DE and Mills N (2005) Combustion-derived Nanoparticles A Review of Their Toxicology Following Inhalation Exposure Part Fibre Toxicol 2 10ndash23

10 Su D Serafino A Muller JO Jentoft RE Schlogl R and Fiorito S (2008) Cytotoxicity and Inflammatory Potential of Soot Particles of Low-emission Diesel Engines Environ Sci Technol 42 1761ndash1765

11 Maier KL Alessandrini F Beck-Speier I Hofer TPJ Diabatґe S Bitterle E Stoger T and Jakob T (2008) Health Effects of Ambient Particulate Matter-Biological Mechanisms and Inflammatory Responses to in Vitroand in Vivo Particle Exposures Inhalation Toxicol 20 319ndash337

Page 28: Studies of Air Pollutants and their Impact on Respiratory and ...€¦ · Ascarate Park C37 Monitoring Station: The National Ambient Air Quality Standard (NAAQS) for PM 10 and 2.5

The modeling use input factors divided into seven section

parameters

On-Road Inventory local data

input

Scale

Geographic Bounds

Traffic intensity

Vehicle Type

Pollutants

Road Type

Fuel Types

Figure Source EPA US Environmental Protection Agency 2012- Moves 2010b Model

EPA Moves 2014a The modeling used input factors divided into six section

parameters On-Road Inventory local data input

Geographic Domains CountyNonattainment Area

Vehicle-Miles Traveled (VMT) is the total number of miles driven by all vehicles withina given time period and geographic area

Average speed range from 25 miles per

hour to 65 miles per hour

Vehicle Classes Motorcycle PassengerCarTruks light-duty Commercial Truck(6001-8500 lbs) Buses heave-duty trucksRefuse trucks School Bus Single UnitShort Haul-truck Single Unit Long Haul-truck Long Haul Truck Heavy-DutyVehicles (26001-33000 lbs)

Pollutants

Road TypeRural restricted Acces(Freeways and interstates) Rural and Restricted Acces Urban Restricted Acces Off-Network

Fuel Types Gasoline Diesel Fuel

Specific Road Types

Two road types for running emission from the MOVES can be

selected

(freeways and interstates)

Interior urban Urban

Figure Source EPA US Environmental Protection Agency 2012- Moves 2010b Model

VehiclesEquipment

This panel show which on-road vehicles will be modeled

Figure Source EPA US Environmental Protection Agency 2012- Moves 2010b Model

Long haul truck Short haul truck Inercity bus Ligth comercial truck

Passenger car Passenger truck Refuse truck

School bus Single unit long haul-truck

Single unit short haul-truck

Transit bus

Motor home

Motorcycle

Based on Department of Transportation Highway MOVES will Estimates Traffic

Emissions from Cars Trucks amp Motorcycles

Output Data Moves 2014a

Inventories of PM 10 25 Mobile Emission from all

on-Road Traffic

Exhaust Emission PM 10 25 gramsmile

Brake Wear Emission PM 10 25 gramsmile

Tire wear Emission PM 10 25 gramsmile

Date of Vehicle miles traveled (VMT) for

Day Week Month Year

Total Vehicle population

Vehicle age distribution

Simulation of Mobile Emission in the El PdN Region Zip Code 79905

Figure Total Emissions from road traffic in El Paso TX Area were estimated for PM10

Exhaust and Non exhaust emission in kilogramsmonth (Source EPA MOVES 2014a)

0

10000

20000

30000

40000

50000

PM

10 k

gM

on

th

Months

Monthly PM 10 Exhaust and Non-Exhaust Mobile Emissions 2010

On-Road Urban Restricted Area Zip Code 79905

Primary Exhaust PM 10 (kg) Primary PM 10 Brakewear (kg)

Primary PM 10 Tirewear (kg)

05000

100001500020000250003000035000400004500050000

PM

25

kg

Mo

nth

Months

Monthly PM 25 Exhaust and Non-Exhaust Mobile Emission 2010

On-Road Urban Restricted Area Zip Code 79905

Primary Exhaust PM 25 (kg) Primary PM 25 Brakewear (kg) Primary PM 25Tirewear (kg)

Figure Total Emissions from road traffic in El Paso TX Area were estimated for PM25

Exhaust and Non exhaust emission in kilogramsmonth (Source EPA MOVES 2014a)

Total Emissions from Road Traffic in El Paso County PM1025 Exhaust and Non exhaust Emission in kilogramsmonth

Taking the interests to the health risks related to PM 1025 mobile emission were simulated

Exhaust and Non-exhaust emissions contribute almost equally to total traffic-related PM1025 Emissions (Querol et al 2004 Bukowiecki et al 2009a Amato et al 2011)

Monthly PM 10 25 Exhaust and Non-Exhaust (BrakewearTirewear) Mobile

Emission 2010 On-Road Urban Restricted Area Zip Code 79905

Figure Total Emissions from road traffic in El Paso TX Area were estimated for PM10 25 Exhaust and Non Exhaust mobile

emission in kilograms per month (Source EPA MOVES)

0

10000

20000

30000

40000

50000

January February March April May June July August September October November December

PM

10

25

(K

ilog

ram

s)

Months

Summary- Monthly PM 10 25 Exhaust and Non-Exhaust Mobile

Emission 2010 On-Road Urban Restricted Area Zip Code 79905

Primary Exhaust PM 10 Primary PM 10 Brakewear Primary PM 10 Tirewear

Primary Exhaust PM 25 Primary PM 25 Brakewear Primary PM 25Tirewear

Exhaust Emissions PM1025 is reaching maximum emission 48000-42000 thousand of Kgmonth followedby Brake wear 29000-5000 thousand kgmonth and Tire wear with 9000-2000 kgmonth The results showthat the emissions of PM derived mainly from Exhaust and Brake are significantly higher in Urban Area

Annual Contribution of Mobile Emission PM 1025 (Kg) Zip Code 79905 El

Paso County 2010

Total Primary

Exhaust _PM10

39

Total Primary

Exhaust _PM25

36

Brakewear

particulate_PM10

18

Tirewear

particulate_PM10

4

Brakewear

particulate_PM25

2

Tirewear

particulate_PM25

1

0

5

10

15

20

25

30

35

40

45

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53

Fig Annual Average PM10 Concentrations at the

Chamizal C41 Station and PM1025 mobile

Concentration Zip code 79905

PM10 TCEQ (μgm3) Total Mobile Emission PM10 (Ugm3)

Fig Exhaust Emission is Contributing Approximately 74 of total

PM1025 Mobile Emissions following of Brake wear with 20 and Tire

wear with 5

Annual Average PM1025 ugm3 Mobile Emissions (Moves) 26 Chamizal C41

Monitoring Station (TCEQ Chamizal Station )

Predicting Mobile Emission and VTM

Estimation The PdN Region 2010

44E+09

46E+09

48E+09

5E+09

52E+09

54E+09

56E+09

58E+09

6E+09

62E+09

0

50000

100000

150000

200000

250000

300000

350000

20

10

20

11

20

12

20

13

20

14

20

15

20

16

20

17

20

18

20

21

20

22

20

23

20

24

20

25

20

26

20

27

20

28

20

29

20

30

EX

HA

US

T

EM

ISS

ION

MO

BIL

E (

KG

YE

AR

)

YEARS

Predict ing Mobile Exhaust Emission and VTM

Estimation

2010 - 2030 e l PdN Area

Total_ Exhaust PM10 Total_ Exhaust PM25 Distance (Miles)

Fig Predicting Mobile Exhaust PM1025 (kgMonth) Emission and VTM Estimation 2010

- 2030 el PdN Area

44E+09

46E+09

48E+09

5E+09

52E+09

54E+09

56E+09

58E+09

6E+09

62E+09

0

5000000

10000000

15000000

20000000

25000000

30000000

20

10

20

11

20

12

20

13

20

14

20

15

20

16

20

17

20

18

20

21

20

22

20

23

20

24

20

25

20

26

20

27

20

28

20

29

20

30

EX

HA

US

T

EM

ISS

ION

MO

BIL

E (

KG

YE

AR

)

YEARS

Predict ing Mobile Exhaust Emission and

VTM Estimation

2010 - 2030 e l PdN Area

CO NO2 NO NOx Distance

Fig Predicting Mobile Exhaust Emission and VTM Estimation

2010 - 2030 el PdN Area in El Paso TX Area were estimated for

Total CO NOx NO2 NO emission in kilograms per year

(Source EPA MOVES 2014a model)

The simulated Exhaust emissions in the future years shows a trend of reduction of this type of emissions in the

future years one factor should be the new hybrid technology is increasing by 476 since 2010 to 2015 and

use of catalytic converters diesel particulate filters and improved fuels and engines Non-exhaustive sources

will increase in the coming years because there is no control in the material of manufacture composed by Fe

Cu and Mn also not to be able to reduce the number of events of braking (Accelerations and decelerations)

45E+09

5E+09

55E+09

6E+09

65E+09

0

50000

100000

150000

200000

250000

201

0

201

1

201

2

201

3

201

4

201

5

201

6

201

7

201

8

202

1

202

2

202

3

202

4

202

5

202

6

202

7

202

8

202

9

203

0

NO

N-

EX

HA

US

T

EM

ISS

ION

MO

BIL

E

(KG

YE

AR

)

YEARS

Predicting Non Exhaust Mobile

Emission and VTM Estimation

2010 - 2030 el PdN Area

Brake_PM10 Tire_PM10 Distance (Miles)

Fig Predicting Mobile Exhaust PM1025 (kgMonth) Emission and VTM

Estimation 2010 - 2030 el PdN Area

Daily Avg PM1025

Levels of PM Mobile Emission Non-Exhaust -Rush Hour Periods Fall 2010 Zip Code

79905

00

100

200

300

400

500

600

Mo

bil

e P

M1

0 (k

g)

Rush Hours

Daily Avg PM10

Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush Hours

Periods 2010 Zip Code 79905

Total Primary Exhaust

_PM10 WinterSpring

Brakewear

particulate_PM10

WinterSpringTirewear particulate_PM10

WinterSpring

Total Primary Exhaust

_PM10 Summer

Brakewear

particulate_PM10 Summer

Tirewear Particulate_PM10

Summer

Total Primary Exhaust

_PM10 Fall

Brakewear

particulate_PM10 Fall

Tirewear particulate_PM10

Fall

00

50

100

150

200

250

300

350

Mo

bil

e P

M2

5 (k

g)

Rush hours

Daily Avg PM25

Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush

Hours Periods 2010 Zip Code 79905

Total Primary Exhaust _PM25

WinterSpring

Brakewear Particulate_PM25

WinterSpring

Tirewear particulate_PM25

WinterSpring

Total Primary Exhaust _PM25

Summer

Brakewear particulate_PM25

Summer

Tirewear particulate_PM25

Summer

Total Primary Exhaust _PM25

Fall

Brakewear particulate_PM25

Fall

Tirewear particulate_PM25

Fall

Figure Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush Hours Figure Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush Hours

GIS EMISSIONS INVENTORY SYSTEM A geographic information system (GIS) was used to established geographic scenarios with processed images of seasonal mobile

emissions in the PdN region Seasonal mapping is visualized for different types of pollutants Brakewear Exhaust and Tyrewear

Fg Graphics of GIS and Seasonal mobile Emission of particulate matter emission inventory Seasonal emission simulations were performed in kilograms and five contributing inputs factors were identified for

modeling 1) On the composition of the particulate material from different sources such as Exhaust and Non exhaust (Brake wear Tirewear) 2) The Vehicles Equipment clasification were selected according to

the use of gasoline and diesel fuel (motorcycle passenger car Light Duty Vehicles Trucks refuse truck Light Duty Vehicles Light Commercial Truck Light Duty Vehicles School Bus)

Winter Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

120354 67860 19065

Spring Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

139767 86702 24463

Summer Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

94747 62481 17630

Fall Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

75510 45542 12596

251 Descriptive Statistics Data Analysis

Weekly Correlation Analysis of Mobile Emission PM10 (Exhaust-Non-Exhaust) and Respiratory

Diagnoses WinterSpring Summer and Fall 2010

0

2

4

6

8

10

0

50

100

150

200

250

300

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21

Mo

rbid

ity

Dis

ch

arg

e

for

all R

esp

ira

tory

Dis

ea

se

ICD

-9

(A

sth

ma

-Bro

nc

hitis

)

WinterSpring Week

Weekly Avg Mobile PM10 Concentrations during

WinterSpring 2010 and its Influence on Respiratory

Diagnoses

Zip Code 79905

Total Medical data ZIP Code 79902

Total Mobile Emission PM10 (Ugm3)

0

1

2

3

4

5

6

7

0

20

40

60

80

100

Mo

rbid

ity

Dis

ch

arg

e

for

all R

esp

ira

tory

Dis

ea

se

ICD

-9

(Ast

hm

aB

ron

ch

itis

)

Weekly Avg Mobile PM10 Concentrations during

Summer 2010 and its Influence on Respiratory

Diagnoses

Summer 2010 Zip Code 79905

Total Mobile Emission PM10

Hospital Admission (Asthma-Bronchitis)

0

2

4

6

8

10

12

0

20

40

60

80

100

120

140

160

180

200

Mo

rbid

ity

dis

ch

arg

es

for

all r

esp

ira

tory

dis

ea

se

Weekly Avg Mobile PM10 Concentrations

during Fall 2010 and its Influence on Respiratory

Diagnoses

Zip Code 79905

Total Medical data ZIP Code 79902

Total Mobile Emission PM10 (Ugm3)

Mobile(Exhaust-Non-

Exhaust) PM10 and

Asthma-Bronchitis)

Linear R

Square

WinterSpring 734 ndash 39

Summer 614 ndash 32

Fall 548 -29

PM10 Mobile emission (Exhaust-Non-Exhaust)contributed significantly

association to the incidence of RD

Weekly Correlation Analysis of PM 25 Mobile Emission (Exhaust-Non-Exhaust)

and Cardiovascular Diagnoses WinterSpring Summer and Fall 2010

0010203040

00500

100015002000

Wee

k 1

Wee

k 2

Wee

k 3

Wee

k 4

Wee

k 5

Wee

k 6

Wee

k 7

Wee

k 8

Wee

k 9

Wee

k 1

0

Wee

k 1

1

Wee

k 1

2

Wee

k 1

3

Wee

k 1

4

Wee

k 1

5

Wee

k 1

6

Wee

k 1

7

Wee

k 1

8

Wee

k 1

9

Wee

k 2

0

Wee

k 2

1

Morb

idit

y d

isch

arg

es f

or

all

card

iovasc

ula

r d

isea

se

Weekly Avg PM25 Mobile Concentrations during

WinterSpring 2010 and its Influence on all Heart

Diagnoses

Zip Code 79905

Total All Heart Disease PM 25 mobile (μgm3)

0010203040

00

500

1000

1500

Mo

rbid

ity

dis

ch

arg

es

for

all

ca

rdio

va

scu

lar

dis

ea

se

Weeks

CORRELATION BETWEEN MOBILE PM25 ugm3

EXPOSURE TO HEART DISEASES SYMPTOMS

SUMMER SEASON 2010

Total All Heart Disease PM 25 mobile (μgm3)

Figure Statistical Analyses of the Relationship Between PM25 Caused by Traffic Emission( 26 of total Emission) with Heart diseases Source Hospital Admissions for Asthma Acute Bronchitis and Heart diseases in El Paso County zip code 79905 from Texas Health Care

Information Council in Austin Texas (Texas Health Care Information Council 2000)

00

10

20

30

40

0

50

100

150

We

ek 3

6

We

ek 3

7

We

ek 3

8

We

ek 3

9

We

ek 4

0

We

ek 4

1

We

ek 4

2

We

ek 4

3

We

ek 4

4

We

ek 4

5

We

ek 4

6

We

ek 4

7

We

ek 4

8

We

ek 4

9

We

ek 5

0

We

ek 5

1

We

ek 5

2

We

ek 5

3

Mo

rbid

ity

dis

ch

arg

es

for

all

ca

rdio

va

scu

lar

dis

ea

se

CORRELATION BETWEEN MOBILE PM25 ugm3

EXPOSURE TO HEART DISEASES SYMPTOMS FALL

SEASON 2010

Total All Heart Disease PM 25 mobile (μgm3)

Mobile(Exhaust-

Non-Exhaust)

PM10 and

Asthma-

Bronchitis)

Linear R

Square

WinterSpring 833 -42

Summer 620 -32

Fall 501-26

PM10 Mobile

emission (Exhaust-

Non-

Exhaust)contribut

ed significantly

association to the

incidence of CVD

Diseases

Monthly Brake Mobile Emission PM1025 kg During year 2010 and its Influence on

Respiratory Diagnoses Zip Code 79905

00200040006000800010000

010000200003000040000

PM

10

Mo

bile

(K

g)

Months

Monthly Brake Mobile Emission PM10 kg during year

2010 and its Influence on Respiratory Diagnoses

Zip Code 79905

Primary PM 10

Brakewear 00100020003000400050006000

0

1000

2000

3000

4000

PM

25

Mo

bil

e(K

g)

Months

Monthly Brake Mobile Emission PM25 during

year 2010 and its Influence on Heart Diagnoses

Zip Code 79905

Primary PM 25

Brakewear

Heart Diseases

Hospital

Admission

Brake Mobile Emission

PM10 kg Asthma-

Bronchitis)

Brake Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=969 Linear Square R=856

Monthly Mobile Exhaust Emission PM1025 During year 2010 and its Influence on

Respiratory Diagnoses Zip Code 79905

0

200

400

600

800

1000

0

10000

20000

30000

40000

50000

1 3 5 7 9 11

PM

10

(K

g m

on

th)

Months

Monthly Mobile Exhaust Emission PM10 during

year 2010 and its Influence on Respiratory

Diagnoses

Zip Code 79905

Primary Exhaust

PM 10

Respiratory Disease

(Asthma

Bronchitis) Hospital

Admission

0

100

200

300

400

500

600

0

10000

20000

30000

40000

50000

1 2 3 4 5 6 7 8 9 101112

PM

25

(K

g m

on

th)

Months

Monthly Exhaust Mobile Emission PM25 during

year 2010 and its Influence on Heart Diagnoses

Zip Code 79905

Primary Exhaust PM

25

Heart Diseases

Hospital Admission

Exhaust Mobile Emission

PM10 kg Asthma-

Bronchitis)

Exhaust Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=929 Linear Square R=831

Monthly Tire wear Mobile Emission PM1025 During year 2010 and its Influence on Heart

Diagnoses Zip Code 79905

0

100

200

300

400

500

600

700

800

900

0

1000

2000

3000

4000

5000

6000

7000

8000

9000

1 2 3 4 5 6 7 8 9 10 11 12

PM

10

(K

g m

on

th)

Months

Monthly Tirewear Mobile Emission PM10 during year 2010

and its Influence on Heart Diagnoses

Zip Code 79905

Primary PM 10 Tirewear

Mobile Emission

Respiratory Disease

(Asthma Bronchitis)

Hospital Admission

0

100

200

300

400

500

600

0

200

400

600

800

1000

1200

1400

1 2 3 4 5 6 7 8 9 10 11 12

PM

25

(K

g m

on

th)

Months

Monthly Tirewear Mobile Emission PM25 during year 2010

and its Influence on Respiratory Diagnoses

Zip Code 79905

Primary PM 25Tirewear

Mobile Emission

Heart Diseases Hospital

Admission

Exhaust Mobile Emission

PM10 kg Asthma-

Bronchitis)

Exhaust Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=769 Linear Square R=715

Dona Ana County Zip Codes

88021880278807288048

Primary

Exhaust

PM 10 Zip

code

79905

Total

Primary

Exhaust

PM10

Dona Ana

Primary

Exhaust

PM 25 Zip

Code

79905

Total

Primary

Exhaust

PM25

Dona Ana

Series1 430378 111773 391915 102123

0

100000

200000

300000

400000

500000

AX

IS T

ITLE

Annual Comparison of the Mobile

Exhaust Emissions El Paso County

and Dona Ana 2010

Primary

PM 10

Brakewea

r Zip code

79905

Brakewea

r

particulat

e_PM10

Dona Ana

Primary

PM 10

Tirewear

Zip code

79905

Tirewear

particulat

e_PM10

Dona Ana

Series1 262585 48573 73754 11864

050000

100000150000200000250000300000

AX

IS T

ITLE

Annual Comparison of the Mobile

Brakewear Emissions El Paso County

and Dona Ana 2010

Figure Comparison of the Annual Mobile Emissions

of Primary PM10 Non-Exhauts (Brake ) from Dona

Ana County New Mexico and El Paso Texas Units

in KgMonth

Figure Comparison of the Annual Mobile Emissions

of Primary PM10-Exhauts Emission from Dona Ana

County New Mexico and El Paso Texas Units in

KgMonth

Primary

PM 25

Brakewe

ar Ziphellip

Brakewe

ar

particula

te_PMhellip

Primary

PM

25Tirewe

ar Ziphellip

Tirewear

particula

te_PM25

Donahellip

Series1 32645 6071 10919 1779

0

10000

20000

30000

40000

AX

IS T

ITLE

Annual Comparison of the

Mobile Exhaust Emissions El Paso

County and Dona Ana 2010

Figure Comparison of the Annual Mobile Emissions

of Primary PM10-Exhauts Emission from Dona Ana

County New Mexico and El Paso Texas Units in

KgMonth

Monthly Mobile Emission PM1025 kg During year 2006

and its Influence on Respiratory Diagnoses Dona Ana

County Zip Code 880218802788072

0

100

200

300

0

5000

10000

15000

Axi

s Ti

tle

Axis Title

Monthly Mobile Exhaust Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Total PrimaryMobile Exhaust_PM10

All Respiratory ICD-9 (AsthmaBronchitis)

050100150200250300

010002000300040005000

Axi

s Ti

tle

Axis Title

Monthly Mobile Brake Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Brakewearparticulate_PM10

All RespiratoryICD -9 (AsthmaBronchitis)

050100150200250300

0200400600800

10001200

Axi

s Ti

tle

Axis Title

Monthly Mobile Tirewear Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Tirewearparticulate_PM10

All Respiratory ICD -9 (AsthmaBronchitis)

Mobile Exhauts

Emission PM10

kg Asthma-

Bronchitis)

Brake Mobile

Emission PM10

kg and Heart

Diagnoses

Tirewear Mobile

Emission PM10

kg and Heart

Diagnoses

Linear Square

R= 951

Linear Square

R=625

Linear Square

R=525

Mobile Exhauts

Emission PM25

kg Asthma-

Bronchitis)

Brake Mobile

Emission PM25

kg and Heart

Diagnoses

Tirewear Mobile

Emission PM25

kg and Heart

Diagnoses

Linear Square

R= 986

Linear Square

R=691

Linear Square

R=601

Results

The results showed that mobile PM emissions in the urban areas close to urban Road and highways is putting at risk public health

and the proportion of diseases attributable to this exposure is potentially large

Brake wear emissions is much lower in freeways due to significantly reduced number of braking events while tire wear is much

higher in areas where studded tires are used The emission of exhaust gases are much higher in areas where there is a high

vehicular traffic

Brake Mobile

Emission PM10 kg

Asthma-Bronchitis)

Brake Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square

R=969

Linear Square

R=856

Exhaust Mobile

Emission PM10 kg

Asthma-Bronchitis)

Exhaust Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square

R=929

Linear Square

R=831

Tirewear Mobile

Emission PM10 kg

Asthma-Bronchitis)

Tirewear Mobile

Emission PM25 kg

and Heart Diagnoses

Linear Square R=769 Linear Square R=715

Brake Mobile

Emission PM10 kg

and Heart

Diagnoses

Brake Mobile

Emission PM25 kg

and Heart

Diagnoses

Exhaust Mobile

Emission PM10 kg

Asthma-Bronchitis)

Linear Square

R=625

Linear Square

R=691

Linear Square R=

951

Exhaust Mobile

Emission PM25 kg

Asthma-

Bronchitis)

Tire wear Mobile

Emission PM10 kg and

Heart Diagnoses

Tirewear Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square R=

986

Linear Square R=525 Linear Square

R=601

El Paso County

Dona Ana

County

BenMAP-CE

In this analysis the Program of Mapping and Analysis of Environmental Benefits-Community Edition

(BenMAP-CE) was used to Estimate the number and economic value of health impacts resulting from changes

in air pollution PM 25 Ugm3 in The El Paso Area

Health and Economic Benefits associated with the Response of PM25 Emission between

Base Year 2010

Number of Mortalities in 2010 Base Year Based on El Paso County Texas Department of State Health Services

Number of Mortalities in 2010 Base Year Based on El Paso County Texas

Department of State Health Services

cause of death

year

2010

Populatio

n

Affected

Backgro

und

Concentr

ation Pollutant

Rollback

Type

Avoided

Deaths

(

Populatio

n)

alzheimers disease 2010 40716 125 PM25

25

microgmAcircsup3

Rollback 9

diseases of the

heart 2010 15834 125 PM25

25

microgmAcircsup3

Rollback 35

influenza and

neumonia 2010 81432 125 PM25

25

microgmAcircsup3

Rollback 18

acute bronchitis

and bronchiolitis 2010 117624 125 PM25

25

microgmAcircsup3

Rollback 26

chronic lower

respiratory diseases 2010 54288 125 PM25

25

microgmAcircsup3

Rollback 12

The Basin-wide decrease in 4 ugm3 PM25 concentration after this

reduction control

Cause of death year 2010

Populatio

n

Affected

Background

Concentrati

on

Reduc

cion

scena

rio Polluta

nt

Rollback

Type

Avoi

ded

Deat

hs

(

Pop

ulati

on)

economic

benefits

analysis $

Alzheimers

disease 2010 121 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 9 12000

Diseases of the

heart 2010 470 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 35 35000

Influenza and

neumonia 2010 242 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 18 42500

Acute bronchitis

and bronchiolitis 2010 349 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 26 95000

Chronic lower

respiratory

diseases 2010 161 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 12 4500

$1 295000

PM25-related Mortalities Based on BenMAP-CE Estimate in 2010 Base Year with change in the concentrations levels

Health and Economic Benefits associated with the Response of PM25 Emission between

Base Year 2010 Increasing 7 Ugm3

Cause of death year 2010

Population

Affected

Deaths

avoided by

attaining 195

μgm3

standard

Background

Concentrati

on

Pollut

ant

Rollback

Type

Avoided

Deaths (

Populatio

n)

econo

mic

Unben

efits

analysi

s

Alzheimers

disease 2010 4524 195 PM25

25

microgmAcircsup3

Rollback 19 150000

Diseases of the

heart 2010 20358 195 PM25

25

microgmAcircsup3

Rollback 135 450000

Influenza and

neumonia 2010 126672 195 PM25

25

microgmAcircsup3

Rollback 38 525000

Acute bronchitis

and bronchiolitis 2010 162864 195 PM25

25

microgmAcircsup3

Rollback 36 122000

Chronic lower

respiratory

diseases 2010 99528 195 PM25

25

microgmAcircsup3

Rollback 12 650000

Conclusions

An excellent Pearson Correlation was established to analyze the relationship in the relative risks of hospitalization of Respiratory(RD) and cardiovascular (CVD) associated with ambient exposure caused by traffic emission in relation to their size andspecific sources of emission on different scenarios interior a border Urban Rural Urban restricted access (freeways andinterstates)

A significant correlation of PM1025 exposure from mobile emission and hospital admissions for selected Respiratory (RD) andcardiovascular (CVD) diagnoses was established The results showed that PM emissions in urban restricted access (freeways andinterstates) is mainly caused by traffic Therefore people living close to highways are more exposed higher vehicular emissions

Conclusions

We found statistically significant associations between mobile PM25 caused by traffic emission with Respiratory and Cardiovascular Diseases in the study areaSubsequently a correlation between cardio-respiratory mortality is established

A significant correlation of PM1025 exposure from mobile emission and hospital admissions for selected Respiratory (RD) and cardiovascular (CVD) diagnoses isestablished The results showed that PM emissions in urban restricted access (freeways and interstates) is mainly caused by traffic Therefore people living close tohighways receive higher vehicular emissions

The table shows the percentage of PM mobile exposure in the analyzed areas contributing to increase the risk of Respiratory and Cardiovascular Diseases

An examination was conducted of the synoptic and local meteorology for the June 2006 ozone episode using the WRF model to determine how meteorological parametersinfluence the formation transport and dispersion of ozone in the PdN The predominant synoptic feature of the ozone event day was the expansion intensification and slowprogression of an upper-level ridge of high pressure The high ozone episodes are associated with highly stable atmospheres strong temperature inversions with low mixingheights and therefore low mixing volumes Under these conditions emissions such as NOx lead to highly polluted conditions that favor ozone formation

BenMAP Conclusions

We have estimated the number and economic value of health impacts resulting

from changes in air pollution concentrations of PM 25 in the PdN region

Reduction of Pm 25 4 UGm3= Avoided 213 cases respiratory cardiovascular

diseses and Economic Benefits associated with the Response of PM25 Emission + $

1295000

Increase of PM25 7 ugm3 = increasing Dies= 326 economic Unbenefits= 2345000$

Bibliography

1 Dockery DW Pope CAI Xu X Spengler JD Ware JH Fay ME Ferris BG Speizer FE An association between air pollution and mortality in six US cities N Engl J Med 3291753ndash1759 (1993)

2 Samet JM Dominici F Curriero FC Coursac I Zeger SL Fine particulate air pollution and mortality in 20 US cities 1987ndash1994 N Engl J Med 3431742ndash1749 (2000)

3 Nel AE Diaz-Sanchez D Li N The role of particulate pollutants in pulmonary inflammation and asthma evidence for the involvement of organic chemicals and oxidative stress Curr Opin Pulm Med 20017 20ndash26

4 Westerholm R Karl-Erik E Exhaust emissions from lightand heavy-duty vehicles chemical composition impact of exhaust after treatment and fuel parameters Environ Health Perspect 102(suppl 4)13ndash23 (1994)

5 Bascom R Bromberg P Costa D Delvin R Dockery D Frampton M Lambert W Samet J Speizer F Utell

6 Health effects of outdoor air pollution Am J Respir Crit Care Med 1533ndash50 (1996)

7 Chow JC Watson JG Frazier CA Egami RT Goodrich A Ralph C Spatial and temporal source contributions to

8 PM10 and PM25 in Reno NV In PM-10 Implementation of Standards Transactions An APCAEPA International Speciality Conference San Francisco CA (Mathal CV Stonefield DH eds) PittsburghAPCA 1988439ndash457

9 overview In Particulate Matter Health and Regulatory Issues VIP-49 Proceedings of an International Specialty Conference 4ndash6 April 1995 Pittsburgh PA PittsburghAir and Waste Management Association 1995577ndash598

10 Kunzli N Kaiser R Medina S Studnicka M Chanel O

11 Filliger P Herry M Horak F Jr Puybonnieux-Texier V Quenel P et al Public-health impact of outdoor and traffic- related air pollution a European assessment Lancet 356795ndash801 (2000)

Bibliography

1 Sioutas C Delfino RJ Singh M Exposure assessment for atmospheric ultrafine particles (UFP) and implications in epidemiological research Environ Health Perspect 2005113947ndash955

2 Mosleh M Blau PJ Dumitrescu D (2004) Characteristics and morphology of wear particles from laboratory testing of disc brake materials Wear 2561128ndash1134

3 Kuumlnzli N et al (2000) Public-health impact of outdoor and traffi c-related air pollution a European assessment Lancet 356(9232)795ndash801

4 Dora C Phillips M eds (2000) Transport environment and health Copenhagen WHO Regional Office for Europe (WHO Regional Publications European Series No 89 httpwwweurowhointdocumente72015pdf accessed 26 November 2004)

5 Westerholm R Karl-Erik E Exhaust emissions from lightand

6 heavy-duty vehicles chemical composition impact of exhaust after treatment and fuel parameters Environ Health Perspect 102(suppl 4)13ndash23 (1994)

7 Fauser Tjell Mosbaek pigegaard Quantification of tire-Tread particles using extractable Organic Zinc as a Tracer Rubber Chemistry and Technology 1999 969Table shows some literature estimates of the contribution of tire wear to PM10 in air (Panko et al 2013) Gustafsson M Blomqvist G Gudmundsson A Dahl A Swietlicki E Bohgard M Lindbom J Ljungman A

8 Chen Y Shah N Huggins FE and Huffman GP (2006) Microanalysis of Ambient Particles from Lexington Ky by Electron Microscopy Atmos Environ 40 651ndash663

9 Donaldson K Tran CL Jimenez LA Duffin R Newby DE and Mills N (2005) Combustion-derived Nanoparticles A Review of Their Toxicology Following Inhalation Exposure Part Fibre Toxicol 2 10ndash23

10 Su D Serafino A Muller JO Jentoft RE Schlogl R and Fiorito S (2008) Cytotoxicity and Inflammatory Potential of Soot Particles of Low-emission Diesel Engines Environ Sci Technol 42 1761ndash1765

11 Maier KL Alessandrini F Beck-Speier I Hofer TPJ Diabatґe S Bitterle E Stoger T and Jakob T (2008) Health Effects of Ambient Particulate Matter-Biological Mechanisms and Inflammatory Responses to in Vitroand in Vivo Particle Exposures Inhalation Toxicol 20 319ndash337

Page 29: Studies of Air Pollutants and their Impact on Respiratory and ...€¦ · Ascarate Park C37 Monitoring Station: The National Ambient Air Quality Standard (NAAQS) for PM 10 and 2.5

EPA Moves 2014a The modeling used input factors divided into six section

parameters On-Road Inventory local data input

Geographic Domains CountyNonattainment Area

Vehicle-Miles Traveled (VMT) is the total number of miles driven by all vehicles withina given time period and geographic area

Average speed range from 25 miles per

hour to 65 miles per hour

Vehicle Classes Motorcycle PassengerCarTruks light-duty Commercial Truck(6001-8500 lbs) Buses heave-duty trucksRefuse trucks School Bus Single UnitShort Haul-truck Single Unit Long Haul-truck Long Haul Truck Heavy-DutyVehicles (26001-33000 lbs)

Pollutants

Road TypeRural restricted Acces(Freeways and interstates) Rural and Restricted Acces Urban Restricted Acces Off-Network

Fuel Types Gasoline Diesel Fuel

Specific Road Types

Two road types for running emission from the MOVES can be

selected

(freeways and interstates)

Interior urban Urban

Figure Source EPA US Environmental Protection Agency 2012- Moves 2010b Model

VehiclesEquipment

This panel show which on-road vehicles will be modeled

Figure Source EPA US Environmental Protection Agency 2012- Moves 2010b Model

Long haul truck Short haul truck Inercity bus Ligth comercial truck

Passenger car Passenger truck Refuse truck

School bus Single unit long haul-truck

Single unit short haul-truck

Transit bus

Motor home

Motorcycle

Based on Department of Transportation Highway MOVES will Estimates Traffic

Emissions from Cars Trucks amp Motorcycles

Output Data Moves 2014a

Inventories of PM 10 25 Mobile Emission from all

on-Road Traffic

Exhaust Emission PM 10 25 gramsmile

Brake Wear Emission PM 10 25 gramsmile

Tire wear Emission PM 10 25 gramsmile

Date of Vehicle miles traveled (VMT) for

Day Week Month Year

Total Vehicle population

Vehicle age distribution

Simulation of Mobile Emission in the El PdN Region Zip Code 79905

Figure Total Emissions from road traffic in El Paso TX Area were estimated for PM10

Exhaust and Non exhaust emission in kilogramsmonth (Source EPA MOVES 2014a)

0

10000

20000

30000

40000

50000

PM

10 k

gM

on

th

Months

Monthly PM 10 Exhaust and Non-Exhaust Mobile Emissions 2010

On-Road Urban Restricted Area Zip Code 79905

Primary Exhaust PM 10 (kg) Primary PM 10 Brakewear (kg)

Primary PM 10 Tirewear (kg)

05000

100001500020000250003000035000400004500050000

PM

25

kg

Mo

nth

Months

Monthly PM 25 Exhaust and Non-Exhaust Mobile Emission 2010

On-Road Urban Restricted Area Zip Code 79905

Primary Exhaust PM 25 (kg) Primary PM 25 Brakewear (kg) Primary PM 25Tirewear (kg)

Figure Total Emissions from road traffic in El Paso TX Area were estimated for PM25

Exhaust and Non exhaust emission in kilogramsmonth (Source EPA MOVES 2014a)

Total Emissions from Road Traffic in El Paso County PM1025 Exhaust and Non exhaust Emission in kilogramsmonth

Taking the interests to the health risks related to PM 1025 mobile emission were simulated

Exhaust and Non-exhaust emissions contribute almost equally to total traffic-related PM1025 Emissions (Querol et al 2004 Bukowiecki et al 2009a Amato et al 2011)

Monthly PM 10 25 Exhaust and Non-Exhaust (BrakewearTirewear) Mobile

Emission 2010 On-Road Urban Restricted Area Zip Code 79905

Figure Total Emissions from road traffic in El Paso TX Area were estimated for PM10 25 Exhaust and Non Exhaust mobile

emission in kilograms per month (Source EPA MOVES)

0

10000

20000

30000

40000

50000

January February March April May June July August September October November December

PM

10

25

(K

ilog

ram

s)

Months

Summary- Monthly PM 10 25 Exhaust and Non-Exhaust Mobile

Emission 2010 On-Road Urban Restricted Area Zip Code 79905

Primary Exhaust PM 10 Primary PM 10 Brakewear Primary PM 10 Tirewear

Primary Exhaust PM 25 Primary PM 25 Brakewear Primary PM 25Tirewear

Exhaust Emissions PM1025 is reaching maximum emission 48000-42000 thousand of Kgmonth followedby Brake wear 29000-5000 thousand kgmonth and Tire wear with 9000-2000 kgmonth The results showthat the emissions of PM derived mainly from Exhaust and Brake are significantly higher in Urban Area

Annual Contribution of Mobile Emission PM 1025 (Kg) Zip Code 79905 El

Paso County 2010

Total Primary

Exhaust _PM10

39

Total Primary

Exhaust _PM25

36

Brakewear

particulate_PM10

18

Tirewear

particulate_PM10

4

Brakewear

particulate_PM25

2

Tirewear

particulate_PM25

1

0

5

10

15

20

25

30

35

40

45

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53

Fig Annual Average PM10 Concentrations at the

Chamizal C41 Station and PM1025 mobile

Concentration Zip code 79905

PM10 TCEQ (μgm3) Total Mobile Emission PM10 (Ugm3)

Fig Exhaust Emission is Contributing Approximately 74 of total

PM1025 Mobile Emissions following of Brake wear with 20 and Tire

wear with 5

Annual Average PM1025 ugm3 Mobile Emissions (Moves) 26 Chamizal C41

Monitoring Station (TCEQ Chamizal Station )

Predicting Mobile Emission and VTM

Estimation The PdN Region 2010

44E+09

46E+09

48E+09

5E+09

52E+09

54E+09

56E+09

58E+09

6E+09

62E+09

0

50000

100000

150000

200000

250000

300000

350000

20

10

20

11

20

12

20

13

20

14

20

15

20

16

20

17

20

18

20

21

20

22

20

23

20

24

20

25

20

26

20

27

20

28

20

29

20

30

EX

HA

US

T

EM

ISS

ION

MO

BIL

E (

KG

YE

AR

)

YEARS

Predict ing Mobile Exhaust Emission and VTM

Estimation

2010 - 2030 e l PdN Area

Total_ Exhaust PM10 Total_ Exhaust PM25 Distance (Miles)

Fig Predicting Mobile Exhaust PM1025 (kgMonth) Emission and VTM Estimation 2010

- 2030 el PdN Area

44E+09

46E+09

48E+09

5E+09

52E+09

54E+09

56E+09

58E+09

6E+09

62E+09

0

5000000

10000000

15000000

20000000

25000000

30000000

20

10

20

11

20

12

20

13

20

14

20

15

20

16

20

17

20

18

20

21

20

22

20

23

20

24

20

25

20

26

20

27

20

28

20

29

20

30

EX

HA

US

T

EM

ISS

ION

MO

BIL

E (

KG

YE

AR

)

YEARS

Predict ing Mobile Exhaust Emission and

VTM Estimation

2010 - 2030 e l PdN Area

CO NO2 NO NOx Distance

Fig Predicting Mobile Exhaust Emission and VTM Estimation

2010 - 2030 el PdN Area in El Paso TX Area were estimated for

Total CO NOx NO2 NO emission in kilograms per year

(Source EPA MOVES 2014a model)

The simulated Exhaust emissions in the future years shows a trend of reduction of this type of emissions in the

future years one factor should be the new hybrid technology is increasing by 476 since 2010 to 2015 and

use of catalytic converters diesel particulate filters and improved fuels and engines Non-exhaustive sources

will increase in the coming years because there is no control in the material of manufacture composed by Fe

Cu and Mn also not to be able to reduce the number of events of braking (Accelerations and decelerations)

45E+09

5E+09

55E+09

6E+09

65E+09

0

50000

100000

150000

200000

250000

201

0

201

1

201

2

201

3

201

4

201

5

201

6

201

7

201

8

202

1

202

2

202

3

202

4

202

5

202

6

202

7

202

8

202

9

203

0

NO

N-

EX

HA

US

T

EM

ISS

ION

MO

BIL

E

(KG

YE

AR

)

YEARS

Predicting Non Exhaust Mobile

Emission and VTM Estimation

2010 - 2030 el PdN Area

Brake_PM10 Tire_PM10 Distance (Miles)

Fig Predicting Mobile Exhaust PM1025 (kgMonth) Emission and VTM

Estimation 2010 - 2030 el PdN Area

Daily Avg PM1025

Levels of PM Mobile Emission Non-Exhaust -Rush Hour Periods Fall 2010 Zip Code

79905

00

100

200

300

400

500

600

Mo

bil

e P

M1

0 (k

g)

Rush Hours

Daily Avg PM10

Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush Hours

Periods 2010 Zip Code 79905

Total Primary Exhaust

_PM10 WinterSpring

Brakewear

particulate_PM10

WinterSpringTirewear particulate_PM10

WinterSpring

Total Primary Exhaust

_PM10 Summer

Brakewear

particulate_PM10 Summer

Tirewear Particulate_PM10

Summer

Total Primary Exhaust

_PM10 Fall

Brakewear

particulate_PM10 Fall

Tirewear particulate_PM10

Fall

00

50

100

150

200

250

300

350

Mo

bil

e P

M2

5 (k

g)

Rush hours

Daily Avg PM25

Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush

Hours Periods 2010 Zip Code 79905

Total Primary Exhaust _PM25

WinterSpring

Brakewear Particulate_PM25

WinterSpring

Tirewear particulate_PM25

WinterSpring

Total Primary Exhaust _PM25

Summer

Brakewear particulate_PM25

Summer

Tirewear particulate_PM25

Summer

Total Primary Exhaust _PM25

Fall

Brakewear particulate_PM25

Fall

Tirewear particulate_PM25

Fall

Figure Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush Hours Figure Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush Hours

GIS EMISSIONS INVENTORY SYSTEM A geographic information system (GIS) was used to established geographic scenarios with processed images of seasonal mobile

emissions in the PdN region Seasonal mapping is visualized for different types of pollutants Brakewear Exhaust and Tyrewear

Fg Graphics of GIS and Seasonal mobile Emission of particulate matter emission inventory Seasonal emission simulations were performed in kilograms and five contributing inputs factors were identified for

modeling 1) On the composition of the particulate material from different sources such as Exhaust and Non exhaust (Brake wear Tirewear) 2) The Vehicles Equipment clasification were selected according to

the use of gasoline and diesel fuel (motorcycle passenger car Light Duty Vehicles Trucks refuse truck Light Duty Vehicles Light Commercial Truck Light Duty Vehicles School Bus)

Winter Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

120354 67860 19065

Spring Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

139767 86702 24463

Summer Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

94747 62481 17630

Fall Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

75510 45542 12596

251 Descriptive Statistics Data Analysis

Weekly Correlation Analysis of Mobile Emission PM10 (Exhaust-Non-Exhaust) and Respiratory

Diagnoses WinterSpring Summer and Fall 2010

0

2

4

6

8

10

0

50

100

150

200

250

300

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21

Mo

rbid

ity

Dis

ch

arg

e

for

all R

esp

ira

tory

Dis

ea

se

ICD

-9

(A

sth

ma

-Bro

nc

hitis

)

WinterSpring Week

Weekly Avg Mobile PM10 Concentrations during

WinterSpring 2010 and its Influence on Respiratory

Diagnoses

Zip Code 79905

Total Medical data ZIP Code 79902

Total Mobile Emission PM10 (Ugm3)

0

1

2

3

4

5

6

7

0

20

40

60

80

100

Mo

rbid

ity

Dis

ch

arg

e

for

all R

esp

ira

tory

Dis

ea

se

ICD

-9

(Ast

hm

aB

ron

ch

itis

)

Weekly Avg Mobile PM10 Concentrations during

Summer 2010 and its Influence on Respiratory

Diagnoses

Summer 2010 Zip Code 79905

Total Mobile Emission PM10

Hospital Admission (Asthma-Bronchitis)

0

2

4

6

8

10

12

0

20

40

60

80

100

120

140

160

180

200

Mo

rbid

ity

dis

ch

arg

es

for

all r

esp

ira

tory

dis

ea

se

Weekly Avg Mobile PM10 Concentrations

during Fall 2010 and its Influence on Respiratory

Diagnoses

Zip Code 79905

Total Medical data ZIP Code 79902

Total Mobile Emission PM10 (Ugm3)

Mobile(Exhaust-Non-

Exhaust) PM10 and

Asthma-Bronchitis)

Linear R

Square

WinterSpring 734 ndash 39

Summer 614 ndash 32

Fall 548 -29

PM10 Mobile emission (Exhaust-Non-Exhaust)contributed significantly

association to the incidence of RD

Weekly Correlation Analysis of PM 25 Mobile Emission (Exhaust-Non-Exhaust)

and Cardiovascular Diagnoses WinterSpring Summer and Fall 2010

0010203040

00500

100015002000

Wee

k 1

Wee

k 2

Wee

k 3

Wee

k 4

Wee

k 5

Wee

k 6

Wee

k 7

Wee

k 8

Wee

k 9

Wee

k 1

0

Wee

k 1

1

Wee

k 1

2

Wee

k 1

3

Wee

k 1

4

Wee

k 1

5

Wee

k 1

6

Wee

k 1

7

Wee

k 1

8

Wee

k 1

9

Wee

k 2

0

Wee

k 2

1

Morb

idit

y d

isch

arg

es f

or

all

card

iovasc

ula

r d

isea

se

Weekly Avg PM25 Mobile Concentrations during

WinterSpring 2010 and its Influence on all Heart

Diagnoses

Zip Code 79905

Total All Heart Disease PM 25 mobile (μgm3)

0010203040

00

500

1000

1500

Mo

rbid

ity

dis

ch

arg

es

for

all

ca

rdio

va

scu

lar

dis

ea

se

Weeks

CORRELATION BETWEEN MOBILE PM25 ugm3

EXPOSURE TO HEART DISEASES SYMPTOMS

SUMMER SEASON 2010

Total All Heart Disease PM 25 mobile (μgm3)

Figure Statistical Analyses of the Relationship Between PM25 Caused by Traffic Emission( 26 of total Emission) with Heart diseases Source Hospital Admissions for Asthma Acute Bronchitis and Heart diseases in El Paso County zip code 79905 from Texas Health Care

Information Council in Austin Texas (Texas Health Care Information Council 2000)

00

10

20

30

40

0

50

100

150

We

ek 3

6

We

ek 3

7

We

ek 3

8

We

ek 3

9

We

ek 4

0

We

ek 4

1

We

ek 4

2

We

ek 4

3

We

ek 4

4

We

ek 4

5

We

ek 4

6

We

ek 4

7

We

ek 4

8

We

ek 4

9

We

ek 5

0

We

ek 5

1

We

ek 5

2

We

ek 5

3

Mo

rbid

ity

dis

ch

arg

es

for

all

ca

rdio

va

scu

lar

dis

ea

se

CORRELATION BETWEEN MOBILE PM25 ugm3

EXPOSURE TO HEART DISEASES SYMPTOMS FALL

SEASON 2010

Total All Heart Disease PM 25 mobile (μgm3)

Mobile(Exhaust-

Non-Exhaust)

PM10 and

Asthma-

Bronchitis)

Linear R

Square

WinterSpring 833 -42

Summer 620 -32

Fall 501-26

PM10 Mobile

emission (Exhaust-

Non-

Exhaust)contribut

ed significantly

association to the

incidence of CVD

Diseases

Monthly Brake Mobile Emission PM1025 kg During year 2010 and its Influence on

Respiratory Diagnoses Zip Code 79905

00200040006000800010000

010000200003000040000

PM

10

Mo

bile

(K

g)

Months

Monthly Brake Mobile Emission PM10 kg during year

2010 and its Influence on Respiratory Diagnoses

Zip Code 79905

Primary PM 10

Brakewear 00100020003000400050006000

0

1000

2000

3000

4000

PM

25

Mo

bil

e(K

g)

Months

Monthly Brake Mobile Emission PM25 during

year 2010 and its Influence on Heart Diagnoses

Zip Code 79905

Primary PM 25

Brakewear

Heart Diseases

Hospital

Admission

Brake Mobile Emission

PM10 kg Asthma-

Bronchitis)

Brake Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=969 Linear Square R=856

Monthly Mobile Exhaust Emission PM1025 During year 2010 and its Influence on

Respiratory Diagnoses Zip Code 79905

0

200

400

600

800

1000

0

10000

20000

30000

40000

50000

1 3 5 7 9 11

PM

10

(K

g m

on

th)

Months

Monthly Mobile Exhaust Emission PM10 during

year 2010 and its Influence on Respiratory

Diagnoses

Zip Code 79905

Primary Exhaust

PM 10

Respiratory Disease

(Asthma

Bronchitis) Hospital

Admission

0

100

200

300

400

500

600

0

10000

20000

30000

40000

50000

1 2 3 4 5 6 7 8 9 101112

PM

25

(K

g m

on

th)

Months

Monthly Exhaust Mobile Emission PM25 during

year 2010 and its Influence on Heart Diagnoses

Zip Code 79905

Primary Exhaust PM

25

Heart Diseases

Hospital Admission

Exhaust Mobile Emission

PM10 kg Asthma-

Bronchitis)

Exhaust Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=929 Linear Square R=831

Monthly Tire wear Mobile Emission PM1025 During year 2010 and its Influence on Heart

Diagnoses Zip Code 79905

0

100

200

300

400

500

600

700

800

900

0

1000

2000

3000

4000

5000

6000

7000

8000

9000

1 2 3 4 5 6 7 8 9 10 11 12

PM

10

(K

g m

on

th)

Months

Monthly Tirewear Mobile Emission PM10 during year 2010

and its Influence on Heart Diagnoses

Zip Code 79905

Primary PM 10 Tirewear

Mobile Emission

Respiratory Disease

(Asthma Bronchitis)

Hospital Admission

0

100

200

300

400

500

600

0

200

400

600

800

1000

1200

1400

1 2 3 4 5 6 7 8 9 10 11 12

PM

25

(K

g m

on

th)

Months

Monthly Tirewear Mobile Emission PM25 during year 2010

and its Influence on Respiratory Diagnoses

Zip Code 79905

Primary PM 25Tirewear

Mobile Emission

Heart Diseases Hospital

Admission

Exhaust Mobile Emission

PM10 kg Asthma-

Bronchitis)

Exhaust Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=769 Linear Square R=715

Dona Ana County Zip Codes

88021880278807288048

Primary

Exhaust

PM 10 Zip

code

79905

Total

Primary

Exhaust

PM10

Dona Ana

Primary

Exhaust

PM 25 Zip

Code

79905

Total

Primary

Exhaust

PM25

Dona Ana

Series1 430378 111773 391915 102123

0

100000

200000

300000

400000

500000

AX

IS T

ITLE

Annual Comparison of the Mobile

Exhaust Emissions El Paso County

and Dona Ana 2010

Primary

PM 10

Brakewea

r Zip code

79905

Brakewea

r

particulat

e_PM10

Dona Ana

Primary

PM 10

Tirewear

Zip code

79905

Tirewear

particulat

e_PM10

Dona Ana

Series1 262585 48573 73754 11864

050000

100000150000200000250000300000

AX

IS T

ITLE

Annual Comparison of the Mobile

Brakewear Emissions El Paso County

and Dona Ana 2010

Figure Comparison of the Annual Mobile Emissions

of Primary PM10 Non-Exhauts (Brake ) from Dona

Ana County New Mexico and El Paso Texas Units

in KgMonth

Figure Comparison of the Annual Mobile Emissions

of Primary PM10-Exhauts Emission from Dona Ana

County New Mexico and El Paso Texas Units in

KgMonth

Primary

PM 25

Brakewe

ar Ziphellip

Brakewe

ar

particula

te_PMhellip

Primary

PM

25Tirewe

ar Ziphellip

Tirewear

particula

te_PM25

Donahellip

Series1 32645 6071 10919 1779

0

10000

20000

30000

40000

AX

IS T

ITLE

Annual Comparison of the

Mobile Exhaust Emissions El Paso

County and Dona Ana 2010

Figure Comparison of the Annual Mobile Emissions

of Primary PM10-Exhauts Emission from Dona Ana

County New Mexico and El Paso Texas Units in

KgMonth

Monthly Mobile Emission PM1025 kg During year 2006

and its Influence on Respiratory Diagnoses Dona Ana

County Zip Code 880218802788072

0

100

200

300

0

5000

10000

15000

Axi

s Ti

tle

Axis Title

Monthly Mobile Exhaust Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Total PrimaryMobile Exhaust_PM10

All Respiratory ICD-9 (AsthmaBronchitis)

050100150200250300

010002000300040005000

Axi

s Ti

tle

Axis Title

Monthly Mobile Brake Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Brakewearparticulate_PM10

All RespiratoryICD -9 (AsthmaBronchitis)

050100150200250300

0200400600800

10001200

Axi

s Ti

tle

Axis Title

Monthly Mobile Tirewear Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Tirewearparticulate_PM10

All Respiratory ICD -9 (AsthmaBronchitis)

Mobile Exhauts

Emission PM10

kg Asthma-

Bronchitis)

Brake Mobile

Emission PM10

kg and Heart

Diagnoses

Tirewear Mobile

Emission PM10

kg and Heart

Diagnoses

Linear Square

R= 951

Linear Square

R=625

Linear Square

R=525

Mobile Exhauts

Emission PM25

kg Asthma-

Bronchitis)

Brake Mobile

Emission PM25

kg and Heart

Diagnoses

Tirewear Mobile

Emission PM25

kg and Heart

Diagnoses

Linear Square

R= 986

Linear Square

R=691

Linear Square

R=601

Results

The results showed that mobile PM emissions in the urban areas close to urban Road and highways is putting at risk public health

and the proportion of diseases attributable to this exposure is potentially large

Brake wear emissions is much lower in freeways due to significantly reduced number of braking events while tire wear is much

higher in areas where studded tires are used The emission of exhaust gases are much higher in areas where there is a high

vehicular traffic

Brake Mobile

Emission PM10 kg

Asthma-Bronchitis)

Brake Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square

R=969

Linear Square

R=856

Exhaust Mobile

Emission PM10 kg

Asthma-Bronchitis)

Exhaust Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square

R=929

Linear Square

R=831

Tirewear Mobile

Emission PM10 kg

Asthma-Bronchitis)

Tirewear Mobile

Emission PM25 kg

and Heart Diagnoses

Linear Square R=769 Linear Square R=715

Brake Mobile

Emission PM10 kg

and Heart

Diagnoses

Brake Mobile

Emission PM25 kg

and Heart

Diagnoses

Exhaust Mobile

Emission PM10 kg

Asthma-Bronchitis)

Linear Square

R=625

Linear Square

R=691

Linear Square R=

951

Exhaust Mobile

Emission PM25 kg

Asthma-

Bronchitis)

Tire wear Mobile

Emission PM10 kg and

Heart Diagnoses

Tirewear Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square R=

986

Linear Square R=525 Linear Square

R=601

El Paso County

Dona Ana

County

BenMAP-CE

In this analysis the Program of Mapping and Analysis of Environmental Benefits-Community Edition

(BenMAP-CE) was used to Estimate the number and economic value of health impacts resulting from changes

in air pollution PM 25 Ugm3 in The El Paso Area

Health and Economic Benefits associated with the Response of PM25 Emission between

Base Year 2010

Number of Mortalities in 2010 Base Year Based on El Paso County Texas Department of State Health Services

Number of Mortalities in 2010 Base Year Based on El Paso County Texas

Department of State Health Services

cause of death

year

2010

Populatio

n

Affected

Backgro

und

Concentr

ation Pollutant

Rollback

Type

Avoided

Deaths

(

Populatio

n)

alzheimers disease 2010 40716 125 PM25

25

microgmAcircsup3

Rollback 9

diseases of the

heart 2010 15834 125 PM25

25

microgmAcircsup3

Rollback 35

influenza and

neumonia 2010 81432 125 PM25

25

microgmAcircsup3

Rollback 18

acute bronchitis

and bronchiolitis 2010 117624 125 PM25

25

microgmAcircsup3

Rollback 26

chronic lower

respiratory diseases 2010 54288 125 PM25

25

microgmAcircsup3

Rollback 12

The Basin-wide decrease in 4 ugm3 PM25 concentration after this

reduction control

Cause of death year 2010

Populatio

n

Affected

Background

Concentrati

on

Reduc

cion

scena

rio Polluta

nt

Rollback

Type

Avoi

ded

Deat

hs

(

Pop

ulati

on)

economic

benefits

analysis $

Alzheimers

disease 2010 121 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 9 12000

Diseases of the

heart 2010 470 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 35 35000

Influenza and

neumonia 2010 242 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 18 42500

Acute bronchitis

and bronchiolitis 2010 349 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 26 95000

Chronic lower

respiratory

diseases 2010 161 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 12 4500

$1 295000

PM25-related Mortalities Based on BenMAP-CE Estimate in 2010 Base Year with change in the concentrations levels

Health and Economic Benefits associated with the Response of PM25 Emission between

Base Year 2010 Increasing 7 Ugm3

Cause of death year 2010

Population

Affected

Deaths

avoided by

attaining 195

μgm3

standard

Background

Concentrati

on

Pollut

ant

Rollback

Type

Avoided

Deaths (

Populatio

n)

econo

mic

Unben

efits

analysi

s

Alzheimers

disease 2010 4524 195 PM25

25

microgmAcircsup3

Rollback 19 150000

Diseases of the

heart 2010 20358 195 PM25

25

microgmAcircsup3

Rollback 135 450000

Influenza and

neumonia 2010 126672 195 PM25

25

microgmAcircsup3

Rollback 38 525000

Acute bronchitis

and bronchiolitis 2010 162864 195 PM25

25

microgmAcircsup3

Rollback 36 122000

Chronic lower

respiratory

diseases 2010 99528 195 PM25

25

microgmAcircsup3

Rollback 12 650000

Conclusions

An excellent Pearson Correlation was established to analyze the relationship in the relative risks of hospitalization of Respiratory(RD) and cardiovascular (CVD) associated with ambient exposure caused by traffic emission in relation to their size andspecific sources of emission on different scenarios interior a border Urban Rural Urban restricted access (freeways andinterstates)

A significant correlation of PM1025 exposure from mobile emission and hospital admissions for selected Respiratory (RD) andcardiovascular (CVD) diagnoses was established The results showed that PM emissions in urban restricted access (freeways andinterstates) is mainly caused by traffic Therefore people living close to highways are more exposed higher vehicular emissions

Conclusions

We found statistically significant associations between mobile PM25 caused by traffic emission with Respiratory and Cardiovascular Diseases in the study areaSubsequently a correlation between cardio-respiratory mortality is established

A significant correlation of PM1025 exposure from mobile emission and hospital admissions for selected Respiratory (RD) and cardiovascular (CVD) diagnoses isestablished The results showed that PM emissions in urban restricted access (freeways and interstates) is mainly caused by traffic Therefore people living close tohighways receive higher vehicular emissions

The table shows the percentage of PM mobile exposure in the analyzed areas contributing to increase the risk of Respiratory and Cardiovascular Diseases

An examination was conducted of the synoptic and local meteorology for the June 2006 ozone episode using the WRF model to determine how meteorological parametersinfluence the formation transport and dispersion of ozone in the PdN The predominant synoptic feature of the ozone event day was the expansion intensification and slowprogression of an upper-level ridge of high pressure The high ozone episodes are associated with highly stable atmospheres strong temperature inversions with low mixingheights and therefore low mixing volumes Under these conditions emissions such as NOx lead to highly polluted conditions that favor ozone formation

BenMAP Conclusions

We have estimated the number and economic value of health impacts resulting

from changes in air pollution concentrations of PM 25 in the PdN region

Reduction of Pm 25 4 UGm3= Avoided 213 cases respiratory cardiovascular

diseses and Economic Benefits associated with the Response of PM25 Emission + $

1295000

Increase of PM25 7 ugm3 = increasing Dies= 326 economic Unbenefits= 2345000$

Bibliography

1 Dockery DW Pope CAI Xu X Spengler JD Ware JH Fay ME Ferris BG Speizer FE An association between air pollution and mortality in six US cities N Engl J Med 3291753ndash1759 (1993)

2 Samet JM Dominici F Curriero FC Coursac I Zeger SL Fine particulate air pollution and mortality in 20 US cities 1987ndash1994 N Engl J Med 3431742ndash1749 (2000)

3 Nel AE Diaz-Sanchez D Li N The role of particulate pollutants in pulmonary inflammation and asthma evidence for the involvement of organic chemicals and oxidative stress Curr Opin Pulm Med 20017 20ndash26

4 Westerholm R Karl-Erik E Exhaust emissions from lightand heavy-duty vehicles chemical composition impact of exhaust after treatment and fuel parameters Environ Health Perspect 102(suppl 4)13ndash23 (1994)

5 Bascom R Bromberg P Costa D Delvin R Dockery D Frampton M Lambert W Samet J Speizer F Utell

6 Health effects of outdoor air pollution Am J Respir Crit Care Med 1533ndash50 (1996)

7 Chow JC Watson JG Frazier CA Egami RT Goodrich A Ralph C Spatial and temporal source contributions to

8 PM10 and PM25 in Reno NV In PM-10 Implementation of Standards Transactions An APCAEPA International Speciality Conference San Francisco CA (Mathal CV Stonefield DH eds) PittsburghAPCA 1988439ndash457

9 overview In Particulate Matter Health and Regulatory Issues VIP-49 Proceedings of an International Specialty Conference 4ndash6 April 1995 Pittsburgh PA PittsburghAir and Waste Management Association 1995577ndash598

10 Kunzli N Kaiser R Medina S Studnicka M Chanel O

11 Filliger P Herry M Horak F Jr Puybonnieux-Texier V Quenel P et al Public-health impact of outdoor and traffic- related air pollution a European assessment Lancet 356795ndash801 (2000)

Bibliography

1 Sioutas C Delfino RJ Singh M Exposure assessment for atmospheric ultrafine particles (UFP) and implications in epidemiological research Environ Health Perspect 2005113947ndash955

2 Mosleh M Blau PJ Dumitrescu D (2004) Characteristics and morphology of wear particles from laboratory testing of disc brake materials Wear 2561128ndash1134

3 Kuumlnzli N et al (2000) Public-health impact of outdoor and traffi c-related air pollution a European assessment Lancet 356(9232)795ndash801

4 Dora C Phillips M eds (2000) Transport environment and health Copenhagen WHO Regional Office for Europe (WHO Regional Publications European Series No 89 httpwwweurowhointdocumente72015pdf accessed 26 November 2004)

5 Westerholm R Karl-Erik E Exhaust emissions from lightand

6 heavy-duty vehicles chemical composition impact of exhaust after treatment and fuel parameters Environ Health Perspect 102(suppl 4)13ndash23 (1994)

7 Fauser Tjell Mosbaek pigegaard Quantification of tire-Tread particles using extractable Organic Zinc as a Tracer Rubber Chemistry and Technology 1999 969Table shows some literature estimates of the contribution of tire wear to PM10 in air (Panko et al 2013) Gustafsson M Blomqvist G Gudmundsson A Dahl A Swietlicki E Bohgard M Lindbom J Ljungman A

8 Chen Y Shah N Huggins FE and Huffman GP (2006) Microanalysis of Ambient Particles from Lexington Ky by Electron Microscopy Atmos Environ 40 651ndash663

9 Donaldson K Tran CL Jimenez LA Duffin R Newby DE and Mills N (2005) Combustion-derived Nanoparticles A Review of Their Toxicology Following Inhalation Exposure Part Fibre Toxicol 2 10ndash23

10 Su D Serafino A Muller JO Jentoft RE Schlogl R and Fiorito S (2008) Cytotoxicity and Inflammatory Potential of Soot Particles of Low-emission Diesel Engines Environ Sci Technol 42 1761ndash1765

11 Maier KL Alessandrini F Beck-Speier I Hofer TPJ Diabatґe S Bitterle E Stoger T and Jakob T (2008) Health Effects of Ambient Particulate Matter-Biological Mechanisms and Inflammatory Responses to in Vitroand in Vivo Particle Exposures Inhalation Toxicol 20 319ndash337

Page 30: Studies of Air Pollutants and their Impact on Respiratory and ...€¦ · Ascarate Park C37 Monitoring Station: The National Ambient Air Quality Standard (NAAQS) for PM 10 and 2.5

Specific Road Types

Two road types for running emission from the MOVES can be

selected

(freeways and interstates)

Interior urban Urban

Figure Source EPA US Environmental Protection Agency 2012- Moves 2010b Model

VehiclesEquipment

This panel show which on-road vehicles will be modeled

Figure Source EPA US Environmental Protection Agency 2012- Moves 2010b Model

Long haul truck Short haul truck Inercity bus Ligth comercial truck

Passenger car Passenger truck Refuse truck

School bus Single unit long haul-truck

Single unit short haul-truck

Transit bus

Motor home

Motorcycle

Based on Department of Transportation Highway MOVES will Estimates Traffic

Emissions from Cars Trucks amp Motorcycles

Output Data Moves 2014a

Inventories of PM 10 25 Mobile Emission from all

on-Road Traffic

Exhaust Emission PM 10 25 gramsmile

Brake Wear Emission PM 10 25 gramsmile

Tire wear Emission PM 10 25 gramsmile

Date of Vehicle miles traveled (VMT) for

Day Week Month Year

Total Vehicle population

Vehicle age distribution

Simulation of Mobile Emission in the El PdN Region Zip Code 79905

Figure Total Emissions from road traffic in El Paso TX Area were estimated for PM10

Exhaust and Non exhaust emission in kilogramsmonth (Source EPA MOVES 2014a)

0

10000

20000

30000

40000

50000

PM

10 k

gM

on

th

Months

Monthly PM 10 Exhaust and Non-Exhaust Mobile Emissions 2010

On-Road Urban Restricted Area Zip Code 79905

Primary Exhaust PM 10 (kg) Primary PM 10 Brakewear (kg)

Primary PM 10 Tirewear (kg)

05000

100001500020000250003000035000400004500050000

PM

25

kg

Mo

nth

Months

Monthly PM 25 Exhaust and Non-Exhaust Mobile Emission 2010

On-Road Urban Restricted Area Zip Code 79905

Primary Exhaust PM 25 (kg) Primary PM 25 Brakewear (kg) Primary PM 25Tirewear (kg)

Figure Total Emissions from road traffic in El Paso TX Area were estimated for PM25

Exhaust and Non exhaust emission in kilogramsmonth (Source EPA MOVES 2014a)

Total Emissions from Road Traffic in El Paso County PM1025 Exhaust and Non exhaust Emission in kilogramsmonth

Taking the interests to the health risks related to PM 1025 mobile emission were simulated

Exhaust and Non-exhaust emissions contribute almost equally to total traffic-related PM1025 Emissions (Querol et al 2004 Bukowiecki et al 2009a Amato et al 2011)

Monthly PM 10 25 Exhaust and Non-Exhaust (BrakewearTirewear) Mobile

Emission 2010 On-Road Urban Restricted Area Zip Code 79905

Figure Total Emissions from road traffic in El Paso TX Area were estimated for PM10 25 Exhaust and Non Exhaust mobile

emission in kilograms per month (Source EPA MOVES)

0

10000

20000

30000

40000

50000

January February March April May June July August September October November December

PM

10

25

(K

ilog

ram

s)

Months

Summary- Monthly PM 10 25 Exhaust and Non-Exhaust Mobile

Emission 2010 On-Road Urban Restricted Area Zip Code 79905

Primary Exhaust PM 10 Primary PM 10 Brakewear Primary PM 10 Tirewear

Primary Exhaust PM 25 Primary PM 25 Brakewear Primary PM 25Tirewear

Exhaust Emissions PM1025 is reaching maximum emission 48000-42000 thousand of Kgmonth followedby Brake wear 29000-5000 thousand kgmonth and Tire wear with 9000-2000 kgmonth The results showthat the emissions of PM derived mainly from Exhaust and Brake are significantly higher in Urban Area

Annual Contribution of Mobile Emission PM 1025 (Kg) Zip Code 79905 El

Paso County 2010

Total Primary

Exhaust _PM10

39

Total Primary

Exhaust _PM25

36

Brakewear

particulate_PM10

18

Tirewear

particulate_PM10

4

Brakewear

particulate_PM25

2

Tirewear

particulate_PM25

1

0

5

10

15

20

25

30

35

40

45

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53

Fig Annual Average PM10 Concentrations at the

Chamizal C41 Station and PM1025 mobile

Concentration Zip code 79905

PM10 TCEQ (μgm3) Total Mobile Emission PM10 (Ugm3)

Fig Exhaust Emission is Contributing Approximately 74 of total

PM1025 Mobile Emissions following of Brake wear with 20 and Tire

wear with 5

Annual Average PM1025 ugm3 Mobile Emissions (Moves) 26 Chamizal C41

Monitoring Station (TCEQ Chamizal Station )

Predicting Mobile Emission and VTM

Estimation The PdN Region 2010

44E+09

46E+09

48E+09

5E+09

52E+09

54E+09

56E+09

58E+09

6E+09

62E+09

0

50000

100000

150000

200000

250000

300000

350000

20

10

20

11

20

12

20

13

20

14

20

15

20

16

20

17

20

18

20

21

20

22

20

23

20

24

20

25

20

26

20

27

20

28

20

29

20

30

EX

HA

US

T

EM

ISS

ION

MO

BIL

E (

KG

YE

AR

)

YEARS

Predict ing Mobile Exhaust Emission and VTM

Estimation

2010 - 2030 e l PdN Area

Total_ Exhaust PM10 Total_ Exhaust PM25 Distance (Miles)

Fig Predicting Mobile Exhaust PM1025 (kgMonth) Emission and VTM Estimation 2010

- 2030 el PdN Area

44E+09

46E+09

48E+09

5E+09

52E+09

54E+09

56E+09

58E+09

6E+09

62E+09

0

5000000

10000000

15000000

20000000

25000000

30000000

20

10

20

11

20

12

20

13

20

14

20

15

20

16

20

17

20

18

20

21

20

22

20

23

20

24

20

25

20

26

20

27

20

28

20

29

20

30

EX

HA

US

T

EM

ISS

ION

MO

BIL

E (

KG

YE

AR

)

YEARS

Predict ing Mobile Exhaust Emission and

VTM Estimation

2010 - 2030 e l PdN Area

CO NO2 NO NOx Distance

Fig Predicting Mobile Exhaust Emission and VTM Estimation

2010 - 2030 el PdN Area in El Paso TX Area were estimated for

Total CO NOx NO2 NO emission in kilograms per year

(Source EPA MOVES 2014a model)

The simulated Exhaust emissions in the future years shows a trend of reduction of this type of emissions in the

future years one factor should be the new hybrid technology is increasing by 476 since 2010 to 2015 and

use of catalytic converters diesel particulate filters and improved fuels and engines Non-exhaustive sources

will increase in the coming years because there is no control in the material of manufacture composed by Fe

Cu and Mn also not to be able to reduce the number of events of braking (Accelerations and decelerations)

45E+09

5E+09

55E+09

6E+09

65E+09

0

50000

100000

150000

200000

250000

201

0

201

1

201

2

201

3

201

4

201

5

201

6

201

7

201

8

202

1

202

2

202

3

202

4

202

5

202

6

202

7

202

8

202

9

203

0

NO

N-

EX

HA

US

T

EM

ISS

ION

MO

BIL

E

(KG

YE

AR

)

YEARS

Predicting Non Exhaust Mobile

Emission and VTM Estimation

2010 - 2030 el PdN Area

Brake_PM10 Tire_PM10 Distance (Miles)

Fig Predicting Mobile Exhaust PM1025 (kgMonth) Emission and VTM

Estimation 2010 - 2030 el PdN Area

Daily Avg PM1025

Levels of PM Mobile Emission Non-Exhaust -Rush Hour Periods Fall 2010 Zip Code

79905

00

100

200

300

400

500

600

Mo

bil

e P

M1

0 (k

g)

Rush Hours

Daily Avg PM10

Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush Hours

Periods 2010 Zip Code 79905

Total Primary Exhaust

_PM10 WinterSpring

Brakewear

particulate_PM10

WinterSpringTirewear particulate_PM10

WinterSpring

Total Primary Exhaust

_PM10 Summer

Brakewear

particulate_PM10 Summer

Tirewear Particulate_PM10

Summer

Total Primary Exhaust

_PM10 Fall

Brakewear

particulate_PM10 Fall

Tirewear particulate_PM10

Fall

00

50

100

150

200

250

300

350

Mo

bil

e P

M2

5 (k

g)

Rush hours

Daily Avg PM25

Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush

Hours Periods 2010 Zip Code 79905

Total Primary Exhaust _PM25

WinterSpring

Brakewear Particulate_PM25

WinterSpring

Tirewear particulate_PM25

WinterSpring

Total Primary Exhaust _PM25

Summer

Brakewear particulate_PM25

Summer

Tirewear particulate_PM25

Summer

Total Primary Exhaust _PM25

Fall

Brakewear particulate_PM25

Fall

Tirewear particulate_PM25

Fall

Figure Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush Hours Figure Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush Hours

GIS EMISSIONS INVENTORY SYSTEM A geographic information system (GIS) was used to established geographic scenarios with processed images of seasonal mobile

emissions in the PdN region Seasonal mapping is visualized for different types of pollutants Brakewear Exhaust and Tyrewear

Fg Graphics of GIS and Seasonal mobile Emission of particulate matter emission inventory Seasonal emission simulations were performed in kilograms and five contributing inputs factors were identified for

modeling 1) On the composition of the particulate material from different sources such as Exhaust and Non exhaust (Brake wear Tirewear) 2) The Vehicles Equipment clasification were selected according to

the use of gasoline and diesel fuel (motorcycle passenger car Light Duty Vehicles Trucks refuse truck Light Duty Vehicles Light Commercial Truck Light Duty Vehicles School Bus)

Winter Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

120354 67860 19065

Spring Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

139767 86702 24463

Summer Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

94747 62481 17630

Fall Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

75510 45542 12596

251 Descriptive Statistics Data Analysis

Weekly Correlation Analysis of Mobile Emission PM10 (Exhaust-Non-Exhaust) and Respiratory

Diagnoses WinterSpring Summer and Fall 2010

0

2

4

6

8

10

0

50

100

150

200

250

300

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21

Mo

rbid

ity

Dis

ch

arg

e

for

all R

esp

ira

tory

Dis

ea

se

ICD

-9

(A

sth

ma

-Bro

nc

hitis

)

WinterSpring Week

Weekly Avg Mobile PM10 Concentrations during

WinterSpring 2010 and its Influence on Respiratory

Diagnoses

Zip Code 79905

Total Medical data ZIP Code 79902

Total Mobile Emission PM10 (Ugm3)

0

1

2

3

4

5

6

7

0

20

40

60

80

100

Mo

rbid

ity

Dis

ch

arg

e

for

all R

esp

ira

tory

Dis

ea

se

ICD

-9

(Ast

hm

aB

ron

ch

itis

)

Weekly Avg Mobile PM10 Concentrations during

Summer 2010 and its Influence on Respiratory

Diagnoses

Summer 2010 Zip Code 79905

Total Mobile Emission PM10

Hospital Admission (Asthma-Bronchitis)

0

2

4

6

8

10

12

0

20

40

60

80

100

120

140

160

180

200

Mo

rbid

ity

dis

ch

arg

es

for

all r

esp

ira

tory

dis

ea

se

Weekly Avg Mobile PM10 Concentrations

during Fall 2010 and its Influence on Respiratory

Diagnoses

Zip Code 79905

Total Medical data ZIP Code 79902

Total Mobile Emission PM10 (Ugm3)

Mobile(Exhaust-Non-

Exhaust) PM10 and

Asthma-Bronchitis)

Linear R

Square

WinterSpring 734 ndash 39

Summer 614 ndash 32

Fall 548 -29

PM10 Mobile emission (Exhaust-Non-Exhaust)contributed significantly

association to the incidence of RD

Weekly Correlation Analysis of PM 25 Mobile Emission (Exhaust-Non-Exhaust)

and Cardiovascular Diagnoses WinterSpring Summer and Fall 2010

0010203040

00500

100015002000

Wee

k 1

Wee

k 2

Wee

k 3

Wee

k 4

Wee

k 5

Wee

k 6

Wee

k 7

Wee

k 8

Wee

k 9

Wee

k 1

0

Wee

k 1

1

Wee

k 1

2

Wee

k 1

3

Wee

k 1

4

Wee

k 1

5

Wee

k 1

6

Wee

k 1

7

Wee

k 1

8

Wee

k 1

9

Wee

k 2

0

Wee

k 2

1

Morb

idit

y d

isch

arg

es f

or

all

card

iovasc

ula

r d

isea

se

Weekly Avg PM25 Mobile Concentrations during

WinterSpring 2010 and its Influence on all Heart

Diagnoses

Zip Code 79905

Total All Heart Disease PM 25 mobile (μgm3)

0010203040

00

500

1000

1500

Mo

rbid

ity

dis

ch

arg

es

for

all

ca

rdio

va

scu

lar

dis

ea

se

Weeks

CORRELATION BETWEEN MOBILE PM25 ugm3

EXPOSURE TO HEART DISEASES SYMPTOMS

SUMMER SEASON 2010

Total All Heart Disease PM 25 mobile (μgm3)

Figure Statistical Analyses of the Relationship Between PM25 Caused by Traffic Emission( 26 of total Emission) with Heart diseases Source Hospital Admissions for Asthma Acute Bronchitis and Heart diseases in El Paso County zip code 79905 from Texas Health Care

Information Council in Austin Texas (Texas Health Care Information Council 2000)

00

10

20

30

40

0

50

100

150

We

ek 3

6

We

ek 3

7

We

ek 3

8

We

ek 3

9

We

ek 4

0

We

ek 4

1

We

ek 4

2

We

ek 4

3

We

ek 4

4

We

ek 4

5

We

ek 4

6

We

ek 4

7

We

ek 4

8

We

ek 4

9

We

ek 5

0

We

ek 5

1

We

ek 5

2

We

ek 5

3

Mo

rbid

ity

dis

ch

arg

es

for

all

ca

rdio

va

scu

lar

dis

ea

se

CORRELATION BETWEEN MOBILE PM25 ugm3

EXPOSURE TO HEART DISEASES SYMPTOMS FALL

SEASON 2010

Total All Heart Disease PM 25 mobile (μgm3)

Mobile(Exhaust-

Non-Exhaust)

PM10 and

Asthma-

Bronchitis)

Linear R

Square

WinterSpring 833 -42

Summer 620 -32

Fall 501-26

PM10 Mobile

emission (Exhaust-

Non-

Exhaust)contribut

ed significantly

association to the

incidence of CVD

Diseases

Monthly Brake Mobile Emission PM1025 kg During year 2010 and its Influence on

Respiratory Diagnoses Zip Code 79905

00200040006000800010000

010000200003000040000

PM

10

Mo

bile

(K

g)

Months

Monthly Brake Mobile Emission PM10 kg during year

2010 and its Influence on Respiratory Diagnoses

Zip Code 79905

Primary PM 10

Brakewear 00100020003000400050006000

0

1000

2000

3000

4000

PM

25

Mo

bil

e(K

g)

Months

Monthly Brake Mobile Emission PM25 during

year 2010 and its Influence on Heart Diagnoses

Zip Code 79905

Primary PM 25

Brakewear

Heart Diseases

Hospital

Admission

Brake Mobile Emission

PM10 kg Asthma-

Bronchitis)

Brake Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=969 Linear Square R=856

Monthly Mobile Exhaust Emission PM1025 During year 2010 and its Influence on

Respiratory Diagnoses Zip Code 79905

0

200

400

600

800

1000

0

10000

20000

30000

40000

50000

1 3 5 7 9 11

PM

10

(K

g m

on

th)

Months

Monthly Mobile Exhaust Emission PM10 during

year 2010 and its Influence on Respiratory

Diagnoses

Zip Code 79905

Primary Exhaust

PM 10

Respiratory Disease

(Asthma

Bronchitis) Hospital

Admission

0

100

200

300

400

500

600

0

10000

20000

30000

40000

50000

1 2 3 4 5 6 7 8 9 101112

PM

25

(K

g m

on

th)

Months

Monthly Exhaust Mobile Emission PM25 during

year 2010 and its Influence on Heart Diagnoses

Zip Code 79905

Primary Exhaust PM

25

Heart Diseases

Hospital Admission

Exhaust Mobile Emission

PM10 kg Asthma-

Bronchitis)

Exhaust Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=929 Linear Square R=831

Monthly Tire wear Mobile Emission PM1025 During year 2010 and its Influence on Heart

Diagnoses Zip Code 79905

0

100

200

300

400

500

600

700

800

900

0

1000

2000

3000

4000

5000

6000

7000

8000

9000

1 2 3 4 5 6 7 8 9 10 11 12

PM

10

(K

g m

on

th)

Months

Monthly Tirewear Mobile Emission PM10 during year 2010

and its Influence on Heart Diagnoses

Zip Code 79905

Primary PM 10 Tirewear

Mobile Emission

Respiratory Disease

(Asthma Bronchitis)

Hospital Admission

0

100

200

300

400

500

600

0

200

400

600

800

1000

1200

1400

1 2 3 4 5 6 7 8 9 10 11 12

PM

25

(K

g m

on

th)

Months

Monthly Tirewear Mobile Emission PM25 during year 2010

and its Influence on Respiratory Diagnoses

Zip Code 79905

Primary PM 25Tirewear

Mobile Emission

Heart Diseases Hospital

Admission

Exhaust Mobile Emission

PM10 kg Asthma-

Bronchitis)

Exhaust Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=769 Linear Square R=715

Dona Ana County Zip Codes

88021880278807288048

Primary

Exhaust

PM 10 Zip

code

79905

Total

Primary

Exhaust

PM10

Dona Ana

Primary

Exhaust

PM 25 Zip

Code

79905

Total

Primary

Exhaust

PM25

Dona Ana

Series1 430378 111773 391915 102123

0

100000

200000

300000

400000

500000

AX

IS T

ITLE

Annual Comparison of the Mobile

Exhaust Emissions El Paso County

and Dona Ana 2010

Primary

PM 10

Brakewea

r Zip code

79905

Brakewea

r

particulat

e_PM10

Dona Ana

Primary

PM 10

Tirewear

Zip code

79905

Tirewear

particulat

e_PM10

Dona Ana

Series1 262585 48573 73754 11864

050000

100000150000200000250000300000

AX

IS T

ITLE

Annual Comparison of the Mobile

Brakewear Emissions El Paso County

and Dona Ana 2010

Figure Comparison of the Annual Mobile Emissions

of Primary PM10 Non-Exhauts (Brake ) from Dona

Ana County New Mexico and El Paso Texas Units

in KgMonth

Figure Comparison of the Annual Mobile Emissions

of Primary PM10-Exhauts Emission from Dona Ana

County New Mexico and El Paso Texas Units in

KgMonth

Primary

PM 25

Brakewe

ar Ziphellip

Brakewe

ar

particula

te_PMhellip

Primary

PM

25Tirewe

ar Ziphellip

Tirewear

particula

te_PM25

Donahellip

Series1 32645 6071 10919 1779

0

10000

20000

30000

40000

AX

IS T

ITLE

Annual Comparison of the

Mobile Exhaust Emissions El Paso

County and Dona Ana 2010

Figure Comparison of the Annual Mobile Emissions

of Primary PM10-Exhauts Emission from Dona Ana

County New Mexico and El Paso Texas Units in

KgMonth

Monthly Mobile Emission PM1025 kg During year 2006

and its Influence on Respiratory Diagnoses Dona Ana

County Zip Code 880218802788072

0

100

200

300

0

5000

10000

15000

Axi

s Ti

tle

Axis Title

Monthly Mobile Exhaust Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Total PrimaryMobile Exhaust_PM10

All Respiratory ICD-9 (AsthmaBronchitis)

050100150200250300

010002000300040005000

Axi

s Ti

tle

Axis Title

Monthly Mobile Brake Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Brakewearparticulate_PM10

All RespiratoryICD -9 (AsthmaBronchitis)

050100150200250300

0200400600800

10001200

Axi

s Ti

tle

Axis Title

Monthly Mobile Tirewear Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Tirewearparticulate_PM10

All Respiratory ICD -9 (AsthmaBronchitis)

Mobile Exhauts

Emission PM10

kg Asthma-

Bronchitis)

Brake Mobile

Emission PM10

kg and Heart

Diagnoses

Tirewear Mobile

Emission PM10

kg and Heart

Diagnoses

Linear Square

R= 951

Linear Square

R=625

Linear Square

R=525

Mobile Exhauts

Emission PM25

kg Asthma-

Bronchitis)

Brake Mobile

Emission PM25

kg and Heart

Diagnoses

Tirewear Mobile

Emission PM25

kg and Heart

Diagnoses

Linear Square

R= 986

Linear Square

R=691

Linear Square

R=601

Results

The results showed that mobile PM emissions in the urban areas close to urban Road and highways is putting at risk public health

and the proportion of diseases attributable to this exposure is potentially large

Brake wear emissions is much lower in freeways due to significantly reduced number of braking events while tire wear is much

higher in areas where studded tires are used The emission of exhaust gases are much higher in areas where there is a high

vehicular traffic

Brake Mobile

Emission PM10 kg

Asthma-Bronchitis)

Brake Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square

R=969

Linear Square

R=856

Exhaust Mobile

Emission PM10 kg

Asthma-Bronchitis)

Exhaust Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square

R=929

Linear Square

R=831

Tirewear Mobile

Emission PM10 kg

Asthma-Bronchitis)

Tirewear Mobile

Emission PM25 kg

and Heart Diagnoses

Linear Square R=769 Linear Square R=715

Brake Mobile

Emission PM10 kg

and Heart

Diagnoses

Brake Mobile

Emission PM25 kg

and Heart

Diagnoses

Exhaust Mobile

Emission PM10 kg

Asthma-Bronchitis)

Linear Square

R=625

Linear Square

R=691

Linear Square R=

951

Exhaust Mobile

Emission PM25 kg

Asthma-

Bronchitis)

Tire wear Mobile

Emission PM10 kg and

Heart Diagnoses

Tirewear Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square R=

986

Linear Square R=525 Linear Square

R=601

El Paso County

Dona Ana

County

BenMAP-CE

In this analysis the Program of Mapping and Analysis of Environmental Benefits-Community Edition

(BenMAP-CE) was used to Estimate the number and economic value of health impacts resulting from changes

in air pollution PM 25 Ugm3 in The El Paso Area

Health and Economic Benefits associated with the Response of PM25 Emission between

Base Year 2010

Number of Mortalities in 2010 Base Year Based on El Paso County Texas Department of State Health Services

Number of Mortalities in 2010 Base Year Based on El Paso County Texas

Department of State Health Services

cause of death

year

2010

Populatio

n

Affected

Backgro

und

Concentr

ation Pollutant

Rollback

Type

Avoided

Deaths

(

Populatio

n)

alzheimers disease 2010 40716 125 PM25

25

microgmAcircsup3

Rollback 9

diseases of the

heart 2010 15834 125 PM25

25

microgmAcircsup3

Rollback 35

influenza and

neumonia 2010 81432 125 PM25

25

microgmAcircsup3

Rollback 18

acute bronchitis

and bronchiolitis 2010 117624 125 PM25

25

microgmAcircsup3

Rollback 26

chronic lower

respiratory diseases 2010 54288 125 PM25

25

microgmAcircsup3

Rollback 12

The Basin-wide decrease in 4 ugm3 PM25 concentration after this

reduction control

Cause of death year 2010

Populatio

n

Affected

Background

Concentrati

on

Reduc

cion

scena

rio Polluta

nt

Rollback

Type

Avoi

ded

Deat

hs

(

Pop

ulati

on)

economic

benefits

analysis $

Alzheimers

disease 2010 121 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 9 12000

Diseases of the

heart 2010 470 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 35 35000

Influenza and

neumonia 2010 242 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 18 42500

Acute bronchitis

and bronchiolitis 2010 349 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 26 95000

Chronic lower

respiratory

diseases 2010 161 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 12 4500

$1 295000

PM25-related Mortalities Based on BenMAP-CE Estimate in 2010 Base Year with change in the concentrations levels

Health and Economic Benefits associated with the Response of PM25 Emission between

Base Year 2010 Increasing 7 Ugm3

Cause of death year 2010

Population

Affected

Deaths

avoided by

attaining 195

μgm3

standard

Background

Concentrati

on

Pollut

ant

Rollback

Type

Avoided

Deaths (

Populatio

n)

econo

mic

Unben

efits

analysi

s

Alzheimers

disease 2010 4524 195 PM25

25

microgmAcircsup3

Rollback 19 150000

Diseases of the

heart 2010 20358 195 PM25

25

microgmAcircsup3

Rollback 135 450000

Influenza and

neumonia 2010 126672 195 PM25

25

microgmAcircsup3

Rollback 38 525000

Acute bronchitis

and bronchiolitis 2010 162864 195 PM25

25

microgmAcircsup3

Rollback 36 122000

Chronic lower

respiratory

diseases 2010 99528 195 PM25

25

microgmAcircsup3

Rollback 12 650000

Conclusions

An excellent Pearson Correlation was established to analyze the relationship in the relative risks of hospitalization of Respiratory(RD) and cardiovascular (CVD) associated with ambient exposure caused by traffic emission in relation to their size andspecific sources of emission on different scenarios interior a border Urban Rural Urban restricted access (freeways andinterstates)

A significant correlation of PM1025 exposure from mobile emission and hospital admissions for selected Respiratory (RD) andcardiovascular (CVD) diagnoses was established The results showed that PM emissions in urban restricted access (freeways andinterstates) is mainly caused by traffic Therefore people living close to highways are more exposed higher vehicular emissions

Conclusions

We found statistically significant associations between mobile PM25 caused by traffic emission with Respiratory and Cardiovascular Diseases in the study areaSubsequently a correlation between cardio-respiratory mortality is established

A significant correlation of PM1025 exposure from mobile emission and hospital admissions for selected Respiratory (RD) and cardiovascular (CVD) diagnoses isestablished The results showed that PM emissions in urban restricted access (freeways and interstates) is mainly caused by traffic Therefore people living close tohighways receive higher vehicular emissions

The table shows the percentage of PM mobile exposure in the analyzed areas contributing to increase the risk of Respiratory and Cardiovascular Diseases

An examination was conducted of the synoptic and local meteorology for the June 2006 ozone episode using the WRF model to determine how meteorological parametersinfluence the formation transport and dispersion of ozone in the PdN The predominant synoptic feature of the ozone event day was the expansion intensification and slowprogression of an upper-level ridge of high pressure The high ozone episodes are associated with highly stable atmospheres strong temperature inversions with low mixingheights and therefore low mixing volumes Under these conditions emissions such as NOx lead to highly polluted conditions that favor ozone formation

BenMAP Conclusions

We have estimated the number and economic value of health impacts resulting

from changes in air pollution concentrations of PM 25 in the PdN region

Reduction of Pm 25 4 UGm3= Avoided 213 cases respiratory cardiovascular

diseses and Economic Benefits associated with the Response of PM25 Emission + $

1295000

Increase of PM25 7 ugm3 = increasing Dies= 326 economic Unbenefits= 2345000$

Bibliography

1 Dockery DW Pope CAI Xu X Spengler JD Ware JH Fay ME Ferris BG Speizer FE An association between air pollution and mortality in six US cities N Engl J Med 3291753ndash1759 (1993)

2 Samet JM Dominici F Curriero FC Coursac I Zeger SL Fine particulate air pollution and mortality in 20 US cities 1987ndash1994 N Engl J Med 3431742ndash1749 (2000)

3 Nel AE Diaz-Sanchez D Li N The role of particulate pollutants in pulmonary inflammation and asthma evidence for the involvement of organic chemicals and oxidative stress Curr Opin Pulm Med 20017 20ndash26

4 Westerholm R Karl-Erik E Exhaust emissions from lightand heavy-duty vehicles chemical composition impact of exhaust after treatment and fuel parameters Environ Health Perspect 102(suppl 4)13ndash23 (1994)

5 Bascom R Bromberg P Costa D Delvin R Dockery D Frampton M Lambert W Samet J Speizer F Utell

6 Health effects of outdoor air pollution Am J Respir Crit Care Med 1533ndash50 (1996)

7 Chow JC Watson JG Frazier CA Egami RT Goodrich A Ralph C Spatial and temporal source contributions to

8 PM10 and PM25 in Reno NV In PM-10 Implementation of Standards Transactions An APCAEPA International Speciality Conference San Francisco CA (Mathal CV Stonefield DH eds) PittsburghAPCA 1988439ndash457

9 overview In Particulate Matter Health and Regulatory Issues VIP-49 Proceedings of an International Specialty Conference 4ndash6 April 1995 Pittsburgh PA PittsburghAir and Waste Management Association 1995577ndash598

10 Kunzli N Kaiser R Medina S Studnicka M Chanel O

11 Filliger P Herry M Horak F Jr Puybonnieux-Texier V Quenel P et al Public-health impact of outdoor and traffic- related air pollution a European assessment Lancet 356795ndash801 (2000)

Bibliography

1 Sioutas C Delfino RJ Singh M Exposure assessment for atmospheric ultrafine particles (UFP) and implications in epidemiological research Environ Health Perspect 2005113947ndash955

2 Mosleh M Blau PJ Dumitrescu D (2004) Characteristics and morphology of wear particles from laboratory testing of disc brake materials Wear 2561128ndash1134

3 Kuumlnzli N et al (2000) Public-health impact of outdoor and traffi c-related air pollution a European assessment Lancet 356(9232)795ndash801

4 Dora C Phillips M eds (2000) Transport environment and health Copenhagen WHO Regional Office for Europe (WHO Regional Publications European Series No 89 httpwwweurowhointdocumente72015pdf accessed 26 November 2004)

5 Westerholm R Karl-Erik E Exhaust emissions from lightand

6 heavy-duty vehicles chemical composition impact of exhaust after treatment and fuel parameters Environ Health Perspect 102(suppl 4)13ndash23 (1994)

7 Fauser Tjell Mosbaek pigegaard Quantification of tire-Tread particles using extractable Organic Zinc as a Tracer Rubber Chemistry and Technology 1999 969Table shows some literature estimates of the contribution of tire wear to PM10 in air (Panko et al 2013) Gustafsson M Blomqvist G Gudmundsson A Dahl A Swietlicki E Bohgard M Lindbom J Ljungman A

8 Chen Y Shah N Huggins FE and Huffman GP (2006) Microanalysis of Ambient Particles from Lexington Ky by Electron Microscopy Atmos Environ 40 651ndash663

9 Donaldson K Tran CL Jimenez LA Duffin R Newby DE and Mills N (2005) Combustion-derived Nanoparticles A Review of Their Toxicology Following Inhalation Exposure Part Fibre Toxicol 2 10ndash23

10 Su D Serafino A Muller JO Jentoft RE Schlogl R and Fiorito S (2008) Cytotoxicity and Inflammatory Potential of Soot Particles of Low-emission Diesel Engines Environ Sci Technol 42 1761ndash1765

11 Maier KL Alessandrini F Beck-Speier I Hofer TPJ Diabatґe S Bitterle E Stoger T and Jakob T (2008) Health Effects of Ambient Particulate Matter-Biological Mechanisms and Inflammatory Responses to in Vitroand in Vivo Particle Exposures Inhalation Toxicol 20 319ndash337

Page 31: Studies of Air Pollutants and their Impact on Respiratory and ...€¦ · Ascarate Park C37 Monitoring Station: The National Ambient Air Quality Standard (NAAQS) for PM 10 and 2.5

VehiclesEquipment

This panel show which on-road vehicles will be modeled

Figure Source EPA US Environmental Protection Agency 2012- Moves 2010b Model

Long haul truck Short haul truck Inercity bus Ligth comercial truck

Passenger car Passenger truck Refuse truck

School bus Single unit long haul-truck

Single unit short haul-truck

Transit bus

Motor home

Motorcycle

Based on Department of Transportation Highway MOVES will Estimates Traffic

Emissions from Cars Trucks amp Motorcycles

Output Data Moves 2014a

Inventories of PM 10 25 Mobile Emission from all

on-Road Traffic

Exhaust Emission PM 10 25 gramsmile

Brake Wear Emission PM 10 25 gramsmile

Tire wear Emission PM 10 25 gramsmile

Date of Vehicle miles traveled (VMT) for

Day Week Month Year

Total Vehicle population

Vehicle age distribution

Simulation of Mobile Emission in the El PdN Region Zip Code 79905

Figure Total Emissions from road traffic in El Paso TX Area were estimated for PM10

Exhaust and Non exhaust emission in kilogramsmonth (Source EPA MOVES 2014a)

0

10000

20000

30000

40000

50000

PM

10 k

gM

on

th

Months

Monthly PM 10 Exhaust and Non-Exhaust Mobile Emissions 2010

On-Road Urban Restricted Area Zip Code 79905

Primary Exhaust PM 10 (kg) Primary PM 10 Brakewear (kg)

Primary PM 10 Tirewear (kg)

05000

100001500020000250003000035000400004500050000

PM

25

kg

Mo

nth

Months

Monthly PM 25 Exhaust and Non-Exhaust Mobile Emission 2010

On-Road Urban Restricted Area Zip Code 79905

Primary Exhaust PM 25 (kg) Primary PM 25 Brakewear (kg) Primary PM 25Tirewear (kg)

Figure Total Emissions from road traffic in El Paso TX Area were estimated for PM25

Exhaust and Non exhaust emission in kilogramsmonth (Source EPA MOVES 2014a)

Total Emissions from Road Traffic in El Paso County PM1025 Exhaust and Non exhaust Emission in kilogramsmonth

Taking the interests to the health risks related to PM 1025 mobile emission were simulated

Exhaust and Non-exhaust emissions contribute almost equally to total traffic-related PM1025 Emissions (Querol et al 2004 Bukowiecki et al 2009a Amato et al 2011)

Monthly PM 10 25 Exhaust and Non-Exhaust (BrakewearTirewear) Mobile

Emission 2010 On-Road Urban Restricted Area Zip Code 79905

Figure Total Emissions from road traffic in El Paso TX Area were estimated for PM10 25 Exhaust and Non Exhaust mobile

emission in kilograms per month (Source EPA MOVES)

0

10000

20000

30000

40000

50000

January February March April May June July August September October November December

PM

10

25

(K

ilog

ram

s)

Months

Summary- Monthly PM 10 25 Exhaust and Non-Exhaust Mobile

Emission 2010 On-Road Urban Restricted Area Zip Code 79905

Primary Exhaust PM 10 Primary PM 10 Brakewear Primary PM 10 Tirewear

Primary Exhaust PM 25 Primary PM 25 Brakewear Primary PM 25Tirewear

Exhaust Emissions PM1025 is reaching maximum emission 48000-42000 thousand of Kgmonth followedby Brake wear 29000-5000 thousand kgmonth and Tire wear with 9000-2000 kgmonth The results showthat the emissions of PM derived mainly from Exhaust and Brake are significantly higher in Urban Area

Annual Contribution of Mobile Emission PM 1025 (Kg) Zip Code 79905 El

Paso County 2010

Total Primary

Exhaust _PM10

39

Total Primary

Exhaust _PM25

36

Brakewear

particulate_PM10

18

Tirewear

particulate_PM10

4

Brakewear

particulate_PM25

2

Tirewear

particulate_PM25

1

0

5

10

15

20

25

30

35

40

45

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53

Fig Annual Average PM10 Concentrations at the

Chamizal C41 Station and PM1025 mobile

Concentration Zip code 79905

PM10 TCEQ (μgm3) Total Mobile Emission PM10 (Ugm3)

Fig Exhaust Emission is Contributing Approximately 74 of total

PM1025 Mobile Emissions following of Brake wear with 20 and Tire

wear with 5

Annual Average PM1025 ugm3 Mobile Emissions (Moves) 26 Chamizal C41

Monitoring Station (TCEQ Chamizal Station )

Predicting Mobile Emission and VTM

Estimation The PdN Region 2010

44E+09

46E+09

48E+09

5E+09

52E+09

54E+09

56E+09

58E+09

6E+09

62E+09

0

50000

100000

150000

200000

250000

300000

350000

20

10

20

11

20

12

20

13

20

14

20

15

20

16

20

17

20

18

20

21

20

22

20

23

20

24

20

25

20

26

20

27

20

28

20

29

20

30

EX

HA

US

T

EM

ISS

ION

MO

BIL

E (

KG

YE

AR

)

YEARS

Predict ing Mobile Exhaust Emission and VTM

Estimation

2010 - 2030 e l PdN Area

Total_ Exhaust PM10 Total_ Exhaust PM25 Distance (Miles)

Fig Predicting Mobile Exhaust PM1025 (kgMonth) Emission and VTM Estimation 2010

- 2030 el PdN Area

44E+09

46E+09

48E+09

5E+09

52E+09

54E+09

56E+09

58E+09

6E+09

62E+09

0

5000000

10000000

15000000

20000000

25000000

30000000

20

10

20

11

20

12

20

13

20

14

20

15

20

16

20

17

20

18

20

21

20

22

20

23

20

24

20

25

20

26

20

27

20

28

20

29

20

30

EX

HA

US

T

EM

ISS

ION

MO

BIL

E (

KG

YE

AR

)

YEARS

Predict ing Mobile Exhaust Emission and

VTM Estimation

2010 - 2030 e l PdN Area

CO NO2 NO NOx Distance

Fig Predicting Mobile Exhaust Emission and VTM Estimation

2010 - 2030 el PdN Area in El Paso TX Area were estimated for

Total CO NOx NO2 NO emission in kilograms per year

(Source EPA MOVES 2014a model)

The simulated Exhaust emissions in the future years shows a trend of reduction of this type of emissions in the

future years one factor should be the new hybrid technology is increasing by 476 since 2010 to 2015 and

use of catalytic converters diesel particulate filters and improved fuels and engines Non-exhaustive sources

will increase in the coming years because there is no control in the material of manufacture composed by Fe

Cu and Mn also not to be able to reduce the number of events of braking (Accelerations and decelerations)

45E+09

5E+09

55E+09

6E+09

65E+09

0

50000

100000

150000

200000

250000

201

0

201

1

201

2

201

3

201

4

201

5

201

6

201

7

201

8

202

1

202

2

202

3

202

4

202

5

202

6

202

7

202

8

202

9

203

0

NO

N-

EX

HA

US

T

EM

ISS

ION

MO

BIL

E

(KG

YE

AR

)

YEARS

Predicting Non Exhaust Mobile

Emission and VTM Estimation

2010 - 2030 el PdN Area

Brake_PM10 Tire_PM10 Distance (Miles)

Fig Predicting Mobile Exhaust PM1025 (kgMonth) Emission and VTM

Estimation 2010 - 2030 el PdN Area

Daily Avg PM1025

Levels of PM Mobile Emission Non-Exhaust -Rush Hour Periods Fall 2010 Zip Code

79905

00

100

200

300

400

500

600

Mo

bil

e P

M1

0 (k

g)

Rush Hours

Daily Avg PM10

Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush Hours

Periods 2010 Zip Code 79905

Total Primary Exhaust

_PM10 WinterSpring

Brakewear

particulate_PM10

WinterSpringTirewear particulate_PM10

WinterSpring

Total Primary Exhaust

_PM10 Summer

Brakewear

particulate_PM10 Summer

Tirewear Particulate_PM10

Summer

Total Primary Exhaust

_PM10 Fall

Brakewear

particulate_PM10 Fall

Tirewear particulate_PM10

Fall

00

50

100

150

200

250

300

350

Mo

bil

e P

M2

5 (k

g)

Rush hours

Daily Avg PM25

Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush

Hours Periods 2010 Zip Code 79905

Total Primary Exhaust _PM25

WinterSpring

Brakewear Particulate_PM25

WinterSpring

Tirewear particulate_PM25

WinterSpring

Total Primary Exhaust _PM25

Summer

Brakewear particulate_PM25

Summer

Tirewear particulate_PM25

Summer

Total Primary Exhaust _PM25

Fall

Brakewear particulate_PM25

Fall

Tirewear particulate_PM25

Fall

Figure Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush Hours Figure Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush Hours

GIS EMISSIONS INVENTORY SYSTEM A geographic information system (GIS) was used to established geographic scenarios with processed images of seasonal mobile

emissions in the PdN region Seasonal mapping is visualized for different types of pollutants Brakewear Exhaust and Tyrewear

Fg Graphics of GIS and Seasonal mobile Emission of particulate matter emission inventory Seasonal emission simulations were performed in kilograms and five contributing inputs factors were identified for

modeling 1) On the composition of the particulate material from different sources such as Exhaust and Non exhaust (Brake wear Tirewear) 2) The Vehicles Equipment clasification were selected according to

the use of gasoline and diesel fuel (motorcycle passenger car Light Duty Vehicles Trucks refuse truck Light Duty Vehicles Light Commercial Truck Light Duty Vehicles School Bus)

Winter Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

120354 67860 19065

Spring Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

139767 86702 24463

Summer Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

94747 62481 17630

Fall Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

75510 45542 12596

251 Descriptive Statistics Data Analysis

Weekly Correlation Analysis of Mobile Emission PM10 (Exhaust-Non-Exhaust) and Respiratory

Diagnoses WinterSpring Summer and Fall 2010

0

2

4

6

8

10

0

50

100

150

200

250

300

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21

Mo

rbid

ity

Dis

ch

arg

e

for

all R

esp

ira

tory

Dis

ea

se

ICD

-9

(A

sth

ma

-Bro

nc

hitis

)

WinterSpring Week

Weekly Avg Mobile PM10 Concentrations during

WinterSpring 2010 and its Influence on Respiratory

Diagnoses

Zip Code 79905

Total Medical data ZIP Code 79902

Total Mobile Emission PM10 (Ugm3)

0

1

2

3

4

5

6

7

0

20

40

60

80

100

Mo

rbid

ity

Dis

ch

arg

e

for

all R

esp

ira

tory

Dis

ea

se

ICD

-9

(Ast

hm

aB

ron

ch

itis

)

Weekly Avg Mobile PM10 Concentrations during

Summer 2010 and its Influence on Respiratory

Diagnoses

Summer 2010 Zip Code 79905

Total Mobile Emission PM10

Hospital Admission (Asthma-Bronchitis)

0

2

4

6

8

10

12

0

20

40

60

80

100

120

140

160

180

200

Mo

rbid

ity

dis

ch

arg

es

for

all r

esp

ira

tory

dis

ea

se

Weekly Avg Mobile PM10 Concentrations

during Fall 2010 and its Influence on Respiratory

Diagnoses

Zip Code 79905

Total Medical data ZIP Code 79902

Total Mobile Emission PM10 (Ugm3)

Mobile(Exhaust-Non-

Exhaust) PM10 and

Asthma-Bronchitis)

Linear R

Square

WinterSpring 734 ndash 39

Summer 614 ndash 32

Fall 548 -29

PM10 Mobile emission (Exhaust-Non-Exhaust)contributed significantly

association to the incidence of RD

Weekly Correlation Analysis of PM 25 Mobile Emission (Exhaust-Non-Exhaust)

and Cardiovascular Diagnoses WinterSpring Summer and Fall 2010

0010203040

00500

100015002000

Wee

k 1

Wee

k 2

Wee

k 3

Wee

k 4

Wee

k 5

Wee

k 6

Wee

k 7

Wee

k 8

Wee

k 9

Wee

k 1

0

Wee

k 1

1

Wee

k 1

2

Wee

k 1

3

Wee

k 1

4

Wee

k 1

5

Wee

k 1

6

Wee

k 1

7

Wee

k 1

8

Wee

k 1

9

Wee

k 2

0

Wee

k 2

1

Morb

idit

y d

isch

arg

es f

or

all

card

iovasc

ula

r d

isea

se

Weekly Avg PM25 Mobile Concentrations during

WinterSpring 2010 and its Influence on all Heart

Diagnoses

Zip Code 79905

Total All Heart Disease PM 25 mobile (μgm3)

0010203040

00

500

1000

1500

Mo

rbid

ity

dis

ch

arg

es

for

all

ca

rdio

va

scu

lar

dis

ea

se

Weeks

CORRELATION BETWEEN MOBILE PM25 ugm3

EXPOSURE TO HEART DISEASES SYMPTOMS

SUMMER SEASON 2010

Total All Heart Disease PM 25 mobile (μgm3)

Figure Statistical Analyses of the Relationship Between PM25 Caused by Traffic Emission( 26 of total Emission) with Heart diseases Source Hospital Admissions for Asthma Acute Bronchitis and Heart diseases in El Paso County zip code 79905 from Texas Health Care

Information Council in Austin Texas (Texas Health Care Information Council 2000)

00

10

20

30

40

0

50

100

150

We

ek 3

6

We

ek 3

7

We

ek 3

8

We

ek 3

9

We

ek 4

0

We

ek 4

1

We

ek 4

2

We

ek 4

3

We

ek 4

4

We

ek 4

5

We

ek 4

6

We

ek 4

7

We

ek 4

8

We

ek 4

9

We

ek 5

0

We

ek 5

1

We

ek 5

2

We

ek 5

3

Mo

rbid

ity

dis

ch

arg

es

for

all

ca

rdio

va

scu

lar

dis

ea

se

CORRELATION BETWEEN MOBILE PM25 ugm3

EXPOSURE TO HEART DISEASES SYMPTOMS FALL

SEASON 2010

Total All Heart Disease PM 25 mobile (μgm3)

Mobile(Exhaust-

Non-Exhaust)

PM10 and

Asthma-

Bronchitis)

Linear R

Square

WinterSpring 833 -42

Summer 620 -32

Fall 501-26

PM10 Mobile

emission (Exhaust-

Non-

Exhaust)contribut

ed significantly

association to the

incidence of CVD

Diseases

Monthly Brake Mobile Emission PM1025 kg During year 2010 and its Influence on

Respiratory Diagnoses Zip Code 79905

00200040006000800010000

010000200003000040000

PM

10

Mo

bile

(K

g)

Months

Monthly Brake Mobile Emission PM10 kg during year

2010 and its Influence on Respiratory Diagnoses

Zip Code 79905

Primary PM 10

Brakewear 00100020003000400050006000

0

1000

2000

3000

4000

PM

25

Mo

bil

e(K

g)

Months

Monthly Brake Mobile Emission PM25 during

year 2010 and its Influence on Heart Diagnoses

Zip Code 79905

Primary PM 25

Brakewear

Heart Diseases

Hospital

Admission

Brake Mobile Emission

PM10 kg Asthma-

Bronchitis)

Brake Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=969 Linear Square R=856

Monthly Mobile Exhaust Emission PM1025 During year 2010 and its Influence on

Respiratory Diagnoses Zip Code 79905

0

200

400

600

800

1000

0

10000

20000

30000

40000

50000

1 3 5 7 9 11

PM

10

(K

g m

on

th)

Months

Monthly Mobile Exhaust Emission PM10 during

year 2010 and its Influence on Respiratory

Diagnoses

Zip Code 79905

Primary Exhaust

PM 10

Respiratory Disease

(Asthma

Bronchitis) Hospital

Admission

0

100

200

300

400

500

600

0

10000

20000

30000

40000

50000

1 2 3 4 5 6 7 8 9 101112

PM

25

(K

g m

on

th)

Months

Monthly Exhaust Mobile Emission PM25 during

year 2010 and its Influence on Heart Diagnoses

Zip Code 79905

Primary Exhaust PM

25

Heart Diseases

Hospital Admission

Exhaust Mobile Emission

PM10 kg Asthma-

Bronchitis)

Exhaust Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=929 Linear Square R=831

Monthly Tire wear Mobile Emission PM1025 During year 2010 and its Influence on Heart

Diagnoses Zip Code 79905

0

100

200

300

400

500

600

700

800

900

0

1000

2000

3000

4000

5000

6000

7000

8000

9000

1 2 3 4 5 6 7 8 9 10 11 12

PM

10

(K

g m

on

th)

Months

Monthly Tirewear Mobile Emission PM10 during year 2010

and its Influence on Heart Diagnoses

Zip Code 79905

Primary PM 10 Tirewear

Mobile Emission

Respiratory Disease

(Asthma Bronchitis)

Hospital Admission

0

100

200

300

400

500

600

0

200

400

600

800

1000

1200

1400

1 2 3 4 5 6 7 8 9 10 11 12

PM

25

(K

g m

on

th)

Months

Monthly Tirewear Mobile Emission PM25 during year 2010

and its Influence on Respiratory Diagnoses

Zip Code 79905

Primary PM 25Tirewear

Mobile Emission

Heart Diseases Hospital

Admission

Exhaust Mobile Emission

PM10 kg Asthma-

Bronchitis)

Exhaust Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=769 Linear Square R=715

Dona Ana County Zip Codes

88021880278807288048

Primary

Exhaust

PM 10 Zip

code

79905

Total

Primary

Exhaust

PM10

Dona Ana

Primary

Exhaust

PM 25 Zip

Code

79905

Total

Primary

Exhaust

PM25

Dona Ana

Series1 430378 111773 391915 102123

0

100000

200000

300000

400000

500000

AX

IS T

ITLE

Annual Comparison of the Mobile

Exhaust Emissions El Paso County

and Dona Ana 2010

Primary

PM 10

Brakewea

r Zip code

79905

Brakewea

r

particulat

e_PM10

Dona Ana

Primary

PM 10

Tirewear

Zip code

79905

Tirewear

particulat

e_PM10

Dona Ana

Series1 262585 48573 73754 11864

050000

100000150000200000250000300000

AX

IS T

ITLE

Annual Comparison of the Mobile

Brakewear Emissions El Paso County

and Dona Ana 2010

Figure Comparison of the Annual Mobile Emissions

of Primary PM10 Non-Exhauts (Brake ) from Dona

Ana County New Mexico and El Paso Texas Units

in KgMonth

Figure Comparison of the Annual Mobile Emissions

of Primary PM10-Exhauts Emission from Dona Ana

County New Mexico and El Paso Texas Units in

KgMonth

Primary

PM 25

Brakewe

ar Ziphellip

Brakewe

ar

particula

te_PMhellip

Primary

PM

25Tirewe

ar Ziphellip

Tirewear

particula

te_PM25

Donahellip

Series1 32645 6071 10919 1779

0

10000

20000

30000

40000

AX

IS T

ITLE

Annual Comparison of the

Mobile Exhaust Emissions El Paso

County and Dona Ana 2010

Figure Comparison of the Annual Mobile Emissions

of Primary PM10-Exhauts Emission from Dona Ana

County New Mexico and El Paso Texas Units in

KgMonth

Monthly Mobile Emission PM1025 kg During year 2006

and its Influence on Respiratory Diagnoses Dona Ana

County Zip Code 880218802788072

0

100

200

300

0

5000

10000

15000

Axi

s Ti

tle

Axis Title

Monthly Mobile Exhaust Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Total PrimaryMobile Exhaust_PM10

All Respiratory ICD-9 (AsthmaBronchitis)

050100150200250300

010002000300040005000

Axi

s Ti

tle

Axis Title

Monthly Mobile Brake Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Brakewearparticulate_PM10

All RespiratoryICD -9 (AsthmaBronchitis)

050100150200250300

0200400600800

10001200

Axi

s Ti

tle

Axis Title

Monthly Mobile Tirewear Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Tirewearparticulate_PM10

All Respiratory ICD -9 (AsthmaBronchitis)

Mobile Exhauts

Emission PM10

kg Asthma-

Bronchitis)

Brake Mobile

Emission PM10

kg and Heart

Diagnoses

Tirewear Mobile

Emission PM10

kg and Heart

Diagnoses

Linear Square

R= 951

Linear Square

R=625

Linear Square

R=525

Mobile Exhauts

Emission PM25

kg Asthma-

Bronchitis)

Brake Mobile

Emission PM25

kg and Heart

Diagnoses

Tirewear Mobile

Emission PM25

kg and Heart

Diagnoses

Linear Square

R= 986

Linear Square

R=691

Linear Square

R=601

Results

The results showed that mobile PM emissions in the urban areas close to urban Road and highways is putting at risk public health

and the proportion of diseases attributable to this exposure is potentially large

Brake wear emissions is much lower in freeways due to significantly reduced number of braking events while tire wear is much

higher in areas where studded tires are used The emission of exhaust gases are much higher in areas where there is a high

vehicular traffic

Brake Mobile

Emission PM10 kg

Asthma-Bronchitis)

Brake Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square

R=969

Linear Square

R=856

Exhaust Mobile

Emission PM10 kg

Asthma-Bronchitis)

Exhaust Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square

R=929

Linear Square

R=831

Tirewear Mobile

Emission PM10 kg

Asthma-Bronchitis)

Tirewear Mobile

Emission PM25 kg

and Heart Diagnoses

Linear Square R=769 Linear Square R=715

Brake Mobile

Emission PM10 kg

and Heart

Diagnoses

Brake Mobile

Emission PM25 kg

and Heart

Diagnoses

Exhaust Mobile

Emission PM10 kg

Asthma-Bronchitis)

Linear Square

R=625

Linear Square

R=691

Linear Square R=

951

Exhaust Mobile

Emission PM25 kg

Asthma-

Bronchitis)

Tire wear Mobile

Emission PM10 kg and

Heart Diagnoses

Tirewear Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square R=

986

Linear Square R=525 Linear Square

R=601

El Paso County

Dona Ana

County

BenMAP-CE

In this analysis the Program of Mapping and Analysis of Environmental Benefits-Community Edition

(BenMAP-CE) was used to Estimate the number and economic value of health impacts resulting from changes

in air pollution PM 25 Ugm3 in The El Paso Area

Health and Economic Benefits associated with the Response of PM25 Emission between

Base Year 2010

Number of Mortalities in 2010 Base Year Based on El Paso County Texas Department of State Health Services

Number of Mortalities in 2010 Base Year Based on El Paso County Texas

Department of State Health Services

cause of death

year

2010

Populatio

n

Affected

Backgro

und

Concentr

ation Pollutant

Rollback

Type

Avoided

Deaths

(

Populatio

n)

alzheimers disease 2010 40716 125 PM25

25

microgmAcircsup3

Rollback 9

diseases of the

heart 2010 15834 125 PM25

25

microgmAcircsup3

Rollback 35

influenza and

neumonia 2010 81432 125 PM25

25

microgmAcircsup3

Rollback 18

acute bronchitis

and bronchiolitis 2010 117624 125 PM25

25

microgmAcircsup3

Rollback 26

chronic lower

respiratory diseases 2010 54288 125 PM25

25

microgmAcircsup3

Rollback 12

The Basin-wide decrease in 4 ugm3 PM25 concentration after this

reduction control

Cause of death year 2010

Populatio

n

Affected

Background

Concentrati

on

Reduc

cion

scena

rio Polluta

nt

Rollback

Type

Avoi

ded

Deat

hs

(

Pop

ulati

on)

economic

benefits

analysis $

Alzheimers

disease 2010 121 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 9 12000

Diseases of the

heart 2010 470 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 35 35000

Influenza and

neumonia 2010 242 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 18 42500

Acute bronchitis

and bronchiolitis 2010 349 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 26 95000

Chronic lower

respiratory

diseases 2010 161 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 12 4500

$1 295000

PM25-related Mortalities Based on BenMAP-CE Estimate in 2010 Base Year with change in the concentrations levels

Health and Economic Benefits associated with the Response of PM25 Emission between

Base Year 2010 Increasing 7 Ugm3

Cause of death year 2010

Population

Affected

Deaths

avoided by

attaining 195

μgm3

standard

Background

Concentrati

on

Pollut

ant

Rollback

Type

Avoided

Deaths (

Populatio

n)

econo

mic

Unben

efits

analysi

s

Alzheimers

disease 2010 4524 195 PM25

25

microgmAcircsup3

Rollback 19 150000

Diseases of the

heart 2010 20358 195 PM25

25

microgmAcircsup3

Rollback 135 450000

Influenza and

neumonia 2010 126672 195 PM25

25

microgmAcircsup3

Rollback 38 525000

Acute bronchitis

and bronchiolitis 2010 162864 195 PM25

25

microgmAcircsup3

Rollback 36 122000

Chronic lower

respiratory

diseases 2010 99528 195 PM25

25

microgmAcircsup3

Rollback 12 650000

Conclusions

An excellent Pearson Correlation was established to analyze the relationship in the relative risks of hospitalization of Respiratory(RD) and cardiovascular (CVD) associated with ambient exposure caused by traffic emission in relation to their size andspecific sources of emission on different scenarios interior a border Urban Rural Urban restricted access (freeways andinterstates)

A significant correlation of PM1025 exposure from mobile emission and hospital admissions for selected Respiratory (RD) andcardiovascular (CVD) diagnoses was established The results showed that PM emissions in urban restricted access (freeways andinterstates) is mainly caused by traffic Therefore people living close to highways are more exposed higher vehicular emissions

Conclusions

We found statistically significant associations between mobile PM25 caused by traffic emission with Respiratory and Cardiovascular Diseases in the study areaSubsequently a correlation between cardio-respiratory mortality is established

A significant correlation of PM1025 exposure from mobile emission and hospital admissions for selected Respiratory (RD) and cardiovascular (CVD) diagnoses isestablished The results showed that PM emissions in urban restricted access (freeways and interstates) is mainly caused by traffic Therefore people living close tohighways receive higher vehicular emissions

The table shows the percentage of PM mobile exposure in the analyzed areas contributing to increase the risk of Respiratory and Cardiovascular Diseases

An examination was conducted of the synoptic and local meteorology for the June 2006 ozone episode using the WRF model to determine how meteorological parametersinfluence the formation transport and dispersion of ozone in the PdN The predominant synoptic feature of the ozone event day was the expansion intensification and slowprogression of an upper-level ridge of high pressure The high ozone episodes are associated with highly stable atmospheres strong temperature inversions with low mixingheights and therefore low mixing volumes Under these conditions emissions such as NOx lead to highly polluted conditions that favor ozone formation

BenMAP Conclusions

We have estimated the number and economic value of health impacts resulting

from changes in air pollution concentrations of PM 25 in the PdN region

Reduction of Pm 25 4 UGm3= Avoided 213 cases respiratory cardiovascular

diseses and Economic Benefits associated with the Response of PM25 Emission + $

1295000

Increase of PM25 7 ugm3 = increasing Dies= 326 economic Unbenefits= 2345000$

Bibliography

1 Dockery DW Pope CAI Xu X Spengler JD Ware JH Fay ME Ferris BG Speizer FE An association between air pollution and mortality in six US cities N Engl J Med 3291753ndash1759 (1993)

2 Samet JM Dominici F Curriero FC Coursac I Zeger SL Fine particulate air pollution and mortality in 20 US cities 1987ndash1994 N Engl J Med 3431742ndash1749 (2000)

3 Nel AE Diaz-Sanchez D Li N The role of particulate pollutants in pulmonary inflammation and asthma evidence for the involvement of organic chemicals and oxidative stress Curr Opin Pulm Med 20017 20ndash26

4 Westerholm R Karl-Erik E Exhaust emissions from lightand heavy-duty vehicles chemical composition impact of exhaust after treatment and fuel parameters Environ Health Perspect 102(suppl 4)13ndash23 (1994)

5 Bascom R Bromberg P Costa D Delvin R Dockery D Frampton M Lambert W Samet J Speizer F Utell

6 Health effects of outdoor air pollution Am J Respir Crit Care Med 1533ndash50 (1996)

7 Chow JC Watson JG Frazier CA Egami RT Goodrich A Ralph C Spatial and temporal source contributions to

8 PM10 and PM25 in Reno NV In PM-10 Implementation of Standards Transactions An APCAEPA International Speciality Conference San Francisco CA (Mathal CV Stonefield DH eds) PittsburghAPCA 1988439ndash457

9 overview In Particulate Matter Health and Regulatory Issues VIP-49 Proceedings of an International Specialty Conference 4ndash6 April 1995 Pittsburgh PA PittsburghAir and Waste Management Association 1995577ndash598

10 Kunzli N Kaiser R Medina S Studnicka M Chanel O

11 Filliger P Herry M Horak F Jr Puybonnieux-Texier V Quenel P et al Public-health impact of outdoor and traffic- related air pollution a European assessment Lancet 356795ndash801 (2000)

Bibliography

1 Sioutas C Delfino RJ Singh M Exposure assessment for atmospheric ultrafine particles (UFP) and implications in epidemiological research Environ Health Perspect 2005113947ndash955

2 Mosleh M Blau PJ Dumitrescu D (2004) Characteristics and morphology of wear particles from laboratory testing of disc brake materials Wear 2561128ndash1134

3 Kuumlnzli N et al (2000) Public-health impact of outdoor and traffi c-related air pollution a European assessment Lancet 356(9232)795ndash801

4 Dora C Phillips M eds (2000) Transport environment and health Copenhagen WHO Regional Office for Europe (WHO Regional Publications European Series No 89 httpwwweurowhointdocumente72015pdf accessed 26 November 2004)

5 Westerholm R Karl-Erik E Exhaust emissions from lightand

6 heavy-duty vehicles chemical composition impact of exhaust after treatment and fuel parameters Environ Health Perspect 102(suppl 4)13ndash23 (1994)

7 Fauser Tjell Mosbaek pigegaard Quantification of tire-Tread particles using extractable Organic Zinc as a Tracer Rubber Chemistry and Technology 1999 969Table shows some literature estimates of the contribution of tire wear to PM10 in air (Panko et al 2013) Gustafsson M Blomqvist G Gudmundsson A Dahl A Swietlicki E Bohgard M Lindbom J Ljungman A

8 Chen Y Shah N Huggins FE and Huffman GP (2006) Microanalysis of Ambient Particles from Lexington Ky by Electron Microscopy Atmos Environ 40 651ndash663

9 Donaldson K Tran CL Jimenez LA Duffin R Newby DE and Mills N (2005) Combustion-derived Nanoparticles A Review of Their Toxicology Following Inhalation Exposure Part Fibre Toxicol 2 10ndash23

10 Su D Serafino A Muller JO Jentoft RE Schlogl R and Fiorito S (2008) Cytotoxicity and Inflammatory Potential of Soot Particles of Low-emission Diesel Engines Environ Sci Technol 42 1761ndash1765

11 Maier KL Alessandrini F Beck-Speier I Hofer TPJ Diabatґe S Bitterle E Stoger T and Jakob T (2008) Health Effects of Ambient Particulate Matter-Biological Mechanisms and Inflammatory Responses to in Vitroand in Vivo Particle Exposures Inhalation Toxicol 20 319ndash337

Page 32: Studies of Air Pollutants and their Impact on Respiratory and ...€¦ · Ascarate Park C37 Monitoring Station: The National Ambient Air Quality Standard (NAAQS) for PM 10 and 2.5

Long haul truck Short haul truck Inercity bus Ligth comercial truck

Passenger car Passenger truck Refuse truck

School bus Single unit long haul-truck

Single unit short haul-truck

Transit bus

Motor home

Motorcycle

Based on Department of Transportation Highway MOVES will Estimates Traffic

Emissions from Cars Trucks amp Motorcycles

Output Data Moves 2014a

Inventories of PM 10 25 Mobile Emission from all

on-Road Traffic

Exhaust Emission PM 10 25 gramsmile

Brake Wear Emission PM 10 25 gramsmile

Tire wear Emission PM 10 25 gramsmile

Date of Vehicle miles traveled (VMT) for

Day Week Month Year

Total Vehicle population

Vehicle age distribution

Simulation of Mobile Emission in the El PdN Region Zip Code 79905

Figure Total Emissions from road traffic in El Paso TX Area were estimated for PM10

Exhaust and Non exhaust emission in kilogramsmonth (Source EPA MOVES 2014a)

0

10000

20000

30000

40000

50000

PM

10 k

gM

on

th

Months

Monthly PM 10 Exhaust and Non-Exhaust Mobile Emissions 2010

On-Road Urban Restricted Area Zip Code 79905

Primary Exhaust PM 10 (kg) Primary PM 10 Brakewear (kg)

Primary PM 10 Tirewear (kg)

05000

100001500020000250003000035000400004500050000

PM

25

kg

Mo

nth

Months

Monthly PM 25 Exhaust and Non-Exhaust Mobile Emission 2010

On-Road Urban Restricted Area Zip Code 79905

Primary Exhaust PM 25 (kg) Primary PM 25 Brakewear (kg) Primary PM 25Tirewear (kg)

Figure Total Emissions from road traffic in El Paso TX Area were estimated for PM25

Exhaust and Non exhaust emission in kilogramsmonth (Source EPA MOVES 2014a)

Total Emissions from Road Traffic in El Paso County PM1025 Exhaust and Non exhaust Emission in kilogramsmonth

Taking the interests to the health risks related to PM 1025 mobile emission were simulated

Exhaust and Non-exhaust emissions contribute almost equally to total traffic-related PM1025 Emissions (Querol et al 2004 Bukowiecki et al 2009a Amato et al 2011)

Monthly PM 10 25 Exhaust and Non-Exhaust (BrakewearTirewear) Mobile

Emission 2010 On-Road Urban Restricted Area Zip Code 79905

Figure Total Emissions from road traffic in El Paso TX Area were estimated for PM10 25 Exhaust and Non Exhaust mobile

emission in kilograms per month (Source EPA MOVES)

0

10000

20000

30000

40000

50000

January February March April May June July August September October November December

PM

10

25

(K

ilog

ram

s)

Months

Summary- Monthly PM 10 25 Exhaust and Non-Exhaust Mobile

Emission 2010 On-Road Urban Restricted Area Zip Code 79905

Primary Exhaust PM 10 Primary PM 10 Brakewear Primary PM 10 Tirewear

Primary Exhaust PM 25 Primary PM 25 Brakewear Primary PM 25Tirewear

Exhaust Emissions PM1025 is reaching maximum emission 48000-42000 thousand of Kgmonth followedby Brake wear 29000-5000 thousand kgmonth and Tire wear with 9000-2000 kgmonth The results showthat the emissions of PM derived mainly from Exhaust and Brake are significantly higher in Urban Area

Annual Contribution of Mobile Emission PM 1025 (Kg) Zip Code 79905 El

Paso County 2010

Total Primary

Exhaust _PM10

39

Total Primary

Exhaust _PM25

36

Brakewear

particulate_PM10

18

Tirewear

particulate_PM10

4

Brakewear

particulate_PM25

2

Tirewear

particulate_PM25

1

0

5

10

15

20

25

30

35

40

45

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53

Fig Annual Average PM10 Concentrations at the

Chamizal C41 Station and PM1025 mobile

Concentration Zip code 79905

PM10 TCEQ (μgm3) Total Mobile Emission PM10 (Ugm3)

Fig Exhaust Emission is Contributing Approximately 74 of total

PM1025 Mobile Emissions following of Brake wear with 20 and Tire

wear with 5

Annual Average PM1025 ugm3 Mobile Emissions (Moves) 26 Chamizal C41

Monitoring Station (TCEQ Chamizal Station )

Predicting Mobile Emission and VTM

Estimation The PdN Region 2010

44E+09

46E+09

48E+09

5E+09

52E+09

54E+09

56E+09

58E+09

6E+09

62E+09

0

50000

100000

150000

200000

250000

300000

350000

20

10

20

11

20

12

20

13

20

14

20

15

20

16

20

17

20

18

20

21

20

22

20

23

20

24

20

25

20

26

20

27

20

28

20

29

20

30

EX

HA

US

T

EM

ISS

ION

MO

BIL

E (

KG

YE

AR

)

YEARS

Predict ing Mobile Exhaust Emission and VTM

Estimation

2010 - 2030 e l PdN Area

Total_ Exhaust PM10 Total_ Exhaust PM25 Distance (Miles)

Fig Predicting Mobile Exhaust PM1025 (kgMonth) Emission and VTM Estimation 2010

- 2030 el PdN Area

44E+09

46E+09

48E+09

5E+09

52E+09

54E+09

56E+09

58E+09

6E+09

62E+09

0

5000000

10000000

15000000

20000000

25000000

30000000

20

10

20

11

20

12

20

13

20

14

20

15

20

16

20

17

20

18

20

21

20

22

20

23

20

24

20

25

20

26

20

27

20

28

20

29

20

30

EX

HA

US

T

EM

ISS

ION

MO

BIL

E (

KG

YE

AR

)

YEARS

Predict ing Mobile Exhaust Emission and

VTM Estimation

2010 - 2030 e l PdN Area

CO NO2 NO NOx Distance

Fig Predicting Mobile Exhaust Emission and VTM Estimation

2010 - 2030 el PdN Area in El Paso TX Area were estimated for

Total CO NOx NO2 NO emission in kilograms per year

(Source EPA MOVES 2014a model)

The simulated Exhaust emissions in the future years shows a trend of reduction of this type of emissions in the

future years one factor should be the new hybrid technology is increasing by 476 since 2010 to 2015 and

use of catalytic converters diesel particulate filters and improved fuels and engines Non-exhaustive sources

will increase in the coming years because there is no control in the material of manufacture composed by Fe

Cu and Mn also not to be able to reduce the number of events of braking (Accelerations and decelerations)

45E+09

5E+09

55E+09

6E+09

65E+09

0

50000

100000

150000

200000

250000

201

0

201

1

201

2

201

3

201

4

201

5

201

6

201

7

201

8

202

1

202

2

202

3

202

4

202

5

202

6

202

7

202

8

202

9

203

0

NO

N-

EX

HA

US

T

EM

ISS

ION

MO

BIL

E

(KG

YE

AR

)

YEARS

Predicting Non Exhaust Mobile

Emission and VTM Estimation

2010 - 2030 el PdN Area

Brake_PM10 Tire_PM10 Distance (Miles)

Fig Predicting Mobile Exhaust PM1025 (kgMonth) Emission and VTM

Estimation 2010 - 2030 el PdN Area

Daily Avg PM1025

Levels of PM Mobile Emission Non-Exhaust -Rush Hour Periods Fall 2010 Zip Code

79905

00

100

200

300

400

500

600

Mo

bil

e P

M1

0 (k

g)

Rush Hours

Daily Avg PM10

Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush Hours

Periods 2010 Zip Code 79905

Total Primary Exhaust

_PM10 WinterSpring

Brakewear

particulate_PM10

WinterSpringTirewear particulate_PM10

WinterSpring

Total Primary Exhaust

_PM10 Summer

Brakewear

particulate_PM10 Summer

Tirewear Particulate_PM10

Summer

Total Primary Exhaust

_PM10 Fall

Brakewear

particulate_PM10 Fall

Tirewear particulate_PM10

Fall

00

50

100

150

200

250

300

350

Mo

bil

e P

M2

5 (k

g)

Rush hours

Daily Avg PM25

Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush

Hours Periods 2010 Zip Code 79905

Total Primary Exhaust _PM25

WinterSpring

Brakewear Particulate_PM25

WinterSpring

Tirewear particulate_PM25

WinterSpring

Total Primary Exhaust _PM25

Summer

Brakewear particulate_PM25

Summer

Tirewear particulate_PM25

Summer

Total Primary Exhaust _PM25

Fall

Brakewear particulate_PM25

Fall

Tirewear particulate_PM25

Fall

Figure Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush Hours Figure Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush Hours

GIS EMISSIONS INVENTORY SYSTEM A geographic information system (GIS) was used to established geographic scenarios with processed images of seasonal mobile

emissions in the PdN region Seasonal mapping is visualized for different types of pollutants Brakewear Exhaust and Tyrewear

Fg Graphics of GIS and Seasonal mobile Emission of particulate matter emission inventory Seasonal emission simulations were performed in kilograms and five contributing inputs factors were identified for

modeling 1) On the composition of the particulate material from different sources such as Exhaust and Non exhaust (Brake wear Tirewear) 2) The Vehicles Equipment clasification were selected according to

the use of gasoline and diesel fuel (motorcycle passenger car Light Duty Vehicles Trucks refuse truck Light Duty Vehicles Light Commercial Truck Light Duty Vehicles School Bus)

Winter Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

120354 67860 19065

Spring Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

139767 86702 24463

Summer Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

94747 62481 17630

Fall Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

75510 45542 12596

251 Descriptive Statistics Data Analysis

Weekly Correlation Analysis of Mobile Emission PM10 (Exhaust-Non-Exhaust) and Respiratory

Diagnoses WinterSpring Summer and Fall 2010

0

2

4

6

8

10

0

50

100

150

200

250

300

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21

Mo

rbid

ity

Dis

ch

arg

e

for

all R

esp

ira

tory

Dis

ea

se

ICD

-9

(A

sth

ma

-Bro

nc

hitis

)

WinterSpring Week

Weekly Avg Mobile PM10 Concentrations during

WinterSpring 2010 and its Influence on Respiratory

Diagnoses

Zip Code 79905

Total Medical data ZIP Code 79902

Total Mobile Emission PM10 (Ugm3)

0

1

2

3

4

5

6

7

0

20

40

60

80

100

Mo

rbid

ity

Dis

ch

arg

e

for

all R

esp

ira

tory

Dis

ea

se

ICD

-9

(Ast

hm

aB

ron

ch

itis

)

Weekly Avg Mobile PM10 Concentrations during

Summer 2010 and its Influence on Respiratory

Diagnoses

Summer 2010 Zip Code 79905

Total Mobile Emission PM10

Hospital Admission (Asthma-Bronchitis)

0

2

4

6

8

10

12

0

20

40

60

80

100

120

140

160

180

200

Mo

rbid

ity

dis

ch

arg

es

for

all r

esp

ira

tory

dis

ea

se

Weekly Avg Mobile PM10 Concentrations

during Fall 2010 and its Influence on Respiratory

Diagnoses

Zip Code 79905

Total Medical data ZIP Code 79902

Total Mobile Emission PM10 (Ugm3)

Mobile(Exhaust-Non-

Exhaust) PM10 and

Asthma-Bronchitis)

Linear R

Square

WinterSpring 734 ndash 39

Summer 614 ndash 32

Fall 548 -29

PM10 Mobile emission (Exhaust-Non-Exhaust)contributed significantly

association to the incidence of RD

Weekly Correlation Analysis of PM 25 Mobile Emission (Exhaust-Non-Exhaust)

and Cardiovascular Diagnoses WinterSpring Summer and Fall 2010

0010203040

00500

100015002000

Wee

k 1

Wee

k 2

Wee

k 3

Wee

k 4

Wee

k 5

Wee

k 6

Wee

k 7

Wee

k 8

Wee

k 9

Wee

k 1

0

Wee

k 1

1

Wee

k 1

2

Wee

k 1

3

Wee

k 1

4

Wee

k 1

5

Wee

k 1

6

Wee

k 1

7

Wee

k 1

8

Wee

k 1

9

Wee

k 2

0

Wee

k 2

1

Morb

idit

y d

isch

arg

es f

or

all

card

iovasc

ula

r d

isea

se

Weekly Avg PM25 Mobile Concentrations during

WinterSpring 2010 and its Influence on all Heart

Diagnoses

Zip Code 79905

Total All Heart Disease PM 25 mobile (μgm3)

0010203040

00

500

1000

1500

Mo

rbid

ity

dis

ch

arg

es

for

all

ca

rdio

va

scu

lar

dis

ea

se

Weeks

CORRELATION BETWEEN MOBILE PM25 ugm3

EXPOSURE TO HEART DISEASES SYMPTOMS

SUMMER SEASON 2010

Total All Heart Disease PM 25 mobile (μgm3)

Figure Statistical Analyses of the Relationship Between PM25 Caused by Traffic Emission( 26 of total Emission) with Heart diseases Source Hospital Admissions for Asthma Acute Bronchitis and Heart diseases in El Paso County zip code 79905 from Texas Health Care

Information Council in Austin Texas (Texas Health Care Information Council 2000)

00

10

20

30

40

0

50

100

150

We

ek 3

6

We

ek 3

7

We

ek 3

8

We

ek 3

9

We

ek 4

0

We

ek 4

1

We

ek 4

2

We

ek 4

3

We

ek 4

4

We

ek 4

5

We

ek 4

6

We

ek 4

7

We

ek 4

8

We

ek 4

9

We

ek 5

0

We

ek 5

1

We

ek 5

2

We

ek 5

3

Mo

rbid

ity

dis

ch

arg

es

for

all

ca

rdio

va

scu

lar

dis

ea

se

CORRELATION BETWEEN MOBILE PM25 ugm3

EXPOSURE TO HEART DISEASES SYMPTOMS FALL

SEASON 2010

Total All Heart Disease PM 25 mobile (μgm3)

Mobile(Exhaust-

Non-Exhaust)

PM10 and

Asthma-

Bronchitis)

Linear R

Square

WinterSpring 833 -42

Summer 620 -32

Fall 501-26

PM10 Mobile

emission (Exhaust-

Non-

Exhaust)contribut

ed significantly

association to the

incidence of CVD

Diseases

Monthly Brake Mobile Emission PM1025 kg During year 2010 and its Influence on

Respiratory Diagnoses Zip Code 79905

00200040006000800010000

010000200003000040000

PM

10

Mo

bile

(K

g)

Months

Monthly Brake Mobile Emission PM10 kg during year

2010 and its Influence on Respiratory Diagnoses

Zip Code 79905

Primary PM 10

Brakewear 00100020003000400050006000

0

1000

2000

3000

4000

PM

25

Mo

bil

e(K

g)

Months

Monthly Brake Mobile Emission PM25 during

year 2010 and its Influence on Heart Diagnoses

Zip Code 79905

Primary PM 25

Brakewear

Heart Diseases

Hospital

Admission

Brake Mobile Emission

PM10 kg Asthma-

Bronchitis)

Brake Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=969 Linear Square R=856

Monthly Mobile Exhaust Emission PM1025 During year 2010 and its Influence on

Respiratory Diagnoses Zip Code 79905

0

200

400

600

800

1000

0

10000

20000

30000

40000

50000

1 3 5 7 9 11

PM

10

(K

g m

on

th)

Months

Monthly Mobile Exhaust Emission PM10 during

year 2010 and its Influence on Respiratory

Diagnoses

Zip Code 79905

Primary Exhaust

PM 10

Respiratory Disease

(Asthma

Bronchitis) Hospital

Admission

0

100

200

300

400

500

600

0

10000

20000

30000

40000

50000

1 2 3 4 5 6 7 8 9 101112

PM

25

(K

g m

on

th)

Months

Monthly Exhaust Mobile Emission PM25 during

year 2010 and its Influence on Heart Diagnoses

Zip Code 79905

Primary Exhaust PM

25

Heart Diseases

Hospital Admission

Exhaust Mobile Emission

PM10 kg Asthma-

Bronchitis)

Exhaust Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=929 Linear Square R=831

Monthly Tire wear Mobile Emission PM1025 During year 2010 and its Influence on Heart

Diagnoses Zip Code 79905

0

100

200

300

400

500

600

700

800

900

0

1000

2000

3000

4000

5000

6000

7000

8000

9000

1 2 3 4 5 6 7 8 9 10 11 12

PM

10

(K

g m

on

th)

Months

Monthly Tirewear Mobile Emission PM10 during year 2010

and its Influence on Heart Diagnoses

Zip Code 79905

Primary PM 10 Tirewear

Mobile Emission

Respiratory Disease

(Asthma Bronchitis)

Hospital Admission

0

100

200

300

400

500

600

0

200

400

600

800

1000

1200

1400

1 2 3 4 5 6 7 8 9 10 11 12

PM

25

(K

g m

on

th)

Months

Monthly Tirewear Mobile Emission PM25 during year 2010

and its Influence on Respiratory Diagnoses

Zip Code 79905

Primary PM 25Tirewear

Mobile Emission

Heart Diseases Hospital

Admission

Exhaust Mobile Emission

PM10 kg Asthma-

Bronchitis)

Exhaust Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=769 Linear Square R=715

Dona Ana County Zip Codes

88021880278807288048

Primary

Exhaust

PM 10 Zip

code

79905

Total

Primary

Exhaust

PM10

Dona Ana

Primary

Exhaust

PM 25 Zip

Code

79905

Total

Primary

Exhaust

PM25

Dona Ana

Series1 430378 111773 391915 102123

0

100000

200000

300000

400000

500000

AX

IS T

ITLE

Annual Comparison of the Mobile

Exhaust Emissions El Paso County

and Dona Ana 2010

Primary

PM 10

Brakewea

r Zip code

79905

Brakewea

r

particulat

e_PM10

Dona Ana

Primary

PM 10

Tirewear

Zip code

79905

Tirewear

particulat

e_PM10

Dona Ana

Series1 262585 48573 73754 11864

050000

100000150000200000250000300000

AX

IS T

ITLE

Annual Comparison of the Mobile

Brakewear Emissions El Paso County

and Dona Ana 2010

Figure Comparison of the Annual Mobile Emissions

of Primary PM10 Non-Exhauts (Brake ) from Dona

Ana County New Mexico and El Paso Texas Units

in KgMonth

Figure Comparison of the Annual Mobile Emissions

of Primary PM10-Exhauts Emission from Dona Ana

County New Mexico and El Paso Texas Units in

KgMonth

Primary

PM 25

Brakewe

ar Ziphellip

Brakewe

ar

particula

te_PMhellip

Primary

PM

25Tirewe

ar Ziphellip

Tirewear

particula

te_PM25

Donahellip

Series1 32645 6071 10919 1779

0

10000

20000

30000

40000

AX

IS T

ITLE

Annual Comparison of the

Mobile Exhaust Emissions El Paso

County and Dona Ana 2010

Figure Comparison of the Annual Mobile Emissions

of Primary PM10-Exhauts Emission from Dona Ana

County New Mexico and El Paso Texas Units in

KgMonth

Monthly Mobile Emission PM1025 kg During year 2006

and its Influence on Respiratory Diagnoses Dona Ana

County Zip Code 880218802788072

0

100

200

300

0

5000

10000

15000

Axi

s Ti

tle

Axis Title

Monthly Mobile Exhaust Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Total PrimaryMobile Exhaust_PM10

All Respiratory ICD-9 (AsthmaBronchitis)

050100150200250300

010002000300040005000

Axi

s Ti

tle

Axis Title

Monthly Mobile Brake Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Brakewearparticulate_PM10

All RespiratoryICD -9 (AsthmaBronchitis)

050100150200250300

0200400600800

10001200

Axi

s Ti

tle

Axis Title

Monthly Mobile Tirewear Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Tirewearparticulate_PM10

All Respiratory ICD -9 (AsthmaBronchitis)

Mobile Exhauts

Emission PM10

kg Asthma-

Bronchitis)

Brake Mobile

Emission PM10

kg and Heart

Diagnoses

Tirewear Mobile

Emission PM10

kg and Heart

Diagnoses

Linear Square

R= 951

Linear Square

R=625

Linear Square

R=525

Mobile Exhauts

Emission PM25

kg Asthma-

Bronchitis)

Brake Mobile

Emission PM25

kg and Heart

Diagnoses

Tirewear Mobile

Emission PM25

kg and Heart

Diagnoses

Linear Square

R= 986

Linear Square

R=691

Linear Square

R=601

Results

The results showed that mobile PM emissions in the urban areas close to urban Road and highways is putting at risk public health

and the proportion of diseases attributable to this exposure is potentially large

Brake wear emissions is much lower in freeways due to significantly reduced number of braking events while tire wear is much

higher in areas where studded tires are used The emission of exhaust gases are much higher in areas where there is a high

vehicular traffic

Brake Mobile

Emission PM10 kg

Asthma-Bronchitis)

Brake Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square

R=969

Linear Square

R=856

Exhaust Mobile

Emission PM10 kg

Asthma-Bronchitis)

Exhaust Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square

R=929

Linear Square

R=831

Tirewear Mobile

Emission PM10 kg

Asthma-Bronchitis)

Tirewear Mobile

Emission PM25 kg

and Heart Diagnoses

Linear Square R=769 Linear Square R=715

Brake Mobile

Emission PM10 kg

and Heart

Diagnoses

Brake Mobile

Emission PM25 kg

and Heart

Diagnoses

Exhaust Mobile

Emission PM10 kg

Asthma-Bronchitis)

Linear Square

R=625

Linear Square

R=691

Linear Square R=

951

Exhaust Mobile

Emission PM25 kg

Asthma-

Bronchitis)

Tire wear Mobile

Emission PM10 kg and

Heart Diagnoses

Tirewear Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square R=

986

Linear Square R=525 Linear Square

R=601

El Paso County

Dona Ana

County

BenMAP-CE

In this analysis the Program of Mapping and Analysis of Environmental Benefits-Community Edition

(BenMAP-CE) was used to Estimate the number and economic value of health impacts resulting from changes

in air pollution PM 25 Ugm3 in The El Paso Area

Health and Economic Benefits associated with the Response of PM25 Emission between

Base Year 2010

Number of Mortalities in 2010 Base Year Based on El Paso County Texas Department of State Health Services

Number of Mortalities in 2010 Base Year Based on El Paso County Texas

Department of State Health Services

cause of death

year

2010

Populatio

n

Affected

Backgro

und

Concentr

ation Pollutant

Rollback

Type

Avoided

Deaths

(

Populatio

n)

alzheimers disease 2010 40716 125 PM25

25

microgmAcircsup3

Rollback 9

diseases of the

heart 2010 15834 125 PM25

25

microgmAcircsup3

Rollback 35

influenza and

neumonia 2010 81432 125 PM25

25

microgmAcircsup3

Rollback 18

acute bronchitis

and bronchiolitis 2010 117624 125 PM25

25

microgmAcircsup3

Rollback 26

chronic lower

respiratory diseases 2010 54288 125 PM25

25

microgmAcircsup3

Rollback 12

The Basin-wide decrease in 4 ugm3 PM25 concentration after this

reduction control

Cause of death year 2010

Populatio

n

Affected

Background

Concentrati

on

Reduc

cion

scena

rio Polluta

nt

Rollback

Type

Avoi

ded

Deat

hs

(

Pop

ulati

on)

economic

benefits

analysis $

Alzheimers

disease 2010 121 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 9 12000

Diseases of the

heart 2010 470 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 35 35000

Influenza and

neumonia 2010 242 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 18 42500

Acute bronchitis

and bronchiolitis 2010 349 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 26 95000

Chronic lower

respiratory

diseases 2010 161 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 12 4500

$1 295000

PM25-related Mortalities Based on BenMAP-CE Estimate in 2010 Base Year with change in the concentrations levels

Health and Economic Benefits associated with the Response of PM25 Emission between

Base Year 2010 Increasing 7 Ugm3

Cause of death year 2010

Population

Affected

Deaths

avoided by

attaining 195

μgm3

standard

Background

Concentrati

on

Pollut

ant

Rollback

Type

Avoided

Deaths (

Populatio

n)

econo

mic

Unben

efits

analysi

s

Alzheimers

disease 2010 4524 195 PM25

25

microgmAcircsup3

Rollback 19 150000

Diseases of the

heart 2010 20358 195 PM25

25

microgmAcircsup3

Rollback 135 450000

Influenza and

neumonia 2010 126672 195 PM25

25

microgmAcircsup3

Rollback 38 525000

Acute bronchitis

and bronchiolitis 2010 162864 195 PM25

25

microgmAcircsup3

Rollback 36 122000

Chronic lower

respiratory

diseases 2010 99528 195 PM25

25

microgmAcircsup3

Rollback 12 650000

Conclusions

An excellent Pearson Correlation was established to analyze the relationship in the relative risks of hospitalization of Respiratory(RD) and cardiovascular (CVD) associated with ambient exposure caused by traffic emission in relation to their size andspecific sources of emission on different scenarios interior a border Urban Rural Urban restricted access (freeways andinterstates)

A significant correlation of PM1025 exposure from mobile emission and hospital admissions for selected Respiratory (RD) andcardiovascular (CVD) diagnoses was established The results showed that PM emissions in urban restricted access (freeways andinterstates) is mainly caused by traffic Therefore people living close to highways are more exposed higher vehicular emissions

Conclusions

We found statistically significant associations between mobile PM25 caused by traffic emission with Respiratory and Cardiovascular Diseases in the study areaSubsequently a correlation between cardio-respiratory mortality is established

A significant correlation of PM1025 exposure from mobile emission and hospital admissions for selected Respiratory (RD) and cardiovascular (CVD) diagnoses isestablished The results showed that PM emissions in urban restricted access (freeways and interstates) is mainly caused by traffic Therefore people living close tohighways receive higher vehicular emissions

The table shows the percentage of PM mobile exposure in the analyzed areas contributing to increase the risk of Respiratory and Cardiovascular Diseases

An examination was conducted of the synoptic and local meteorology for the June 2006 ozone episode using the WRF model to determine how meteorological parametersinfluence the formation transport and dispersion of ozone in the PdN The predominant synoptic feature of the ozone event day was the expansion intensification and slowprogression of an upper-level ridge of high pressure The high ozone episodes are associated with highly stable atmospheres strong temperature inversions with low mixingheights and therefore low mixing volumes Under these conditions emissions such as NOx lead to highly polluted conditions that favor ozone formation

BenMAP Conclusions

We have estimated the number and economic value of health impacts resulting

from changes in air pollution concentrations of PM 25 in the PdN region

Reduction of Pm 25 4 UGm3= Avoided 213 cases respiratory cardiovascular

diseses and Economic Benefits associated with the Response of PM25 Emission + $

1295000

Increase of PM25 7 ugm3 = increasing Dies= 326 economic Unbenefits= 2345000$

Bibliography

1 Dockery DW Pope CAI Xu X Spengler JD Ware JH Fay ME Ferris BG Speizer FE An association between air pollution and mortality in six US cities N Engl J Med 3291753ndash1759 (1993)

2 Samet JM Dominici F Curriero FC Coursac I Zeger SL Fine particulate air pollution and mortality in 20 US cities 1987ndash1994 N Engl J Med 3431742ndash1749 (2000)

3 Nel AE Diaz-Sanchez D Li N The role of particulate pollutants in pulmonary inflammation and asthma evidence for the involvement of organic chemicals and oxidative stress Curr Opin Pulm Med 20017 20ndash26

4 Westerholm R Karl-Erik E Exhaust emissions from lightand heavy-duty vehicles chemical composition impact of exhaust after treatment and fuel parameters Environ Health Perspect 102(suppl 4)13ndash23 (1994)

5 Bascom R Bromberg P Costa D Delvin R Dockery D Frampton M Lambert W Samet J Speizer F Utell

6 Health effects of outdoor air pollution Am J Respir Crit Care Med 1533ndash50 (1996)

7 Chow JC Watson JG Frazier CA Egami RT Goodrich A Ralph C Spatial and temporal source contributions to

8 PM10 and PM25 in Reno NV In PM-10 Implementation of Standards Transactions An APCAEPA International Speciality Conference San Francisco CA (Mathal CV Stonefield DH eds) PittsburghAPCA 1988439ndash457

9 overview In Particulate Matter Health and Regulatory Issues VIP-49 Proceedings of an International Specialty Conference 4ndash6 April 1995 Pittsburgh PA PittsburghAir and Waste Management Association 1995577ndash598

10 Kunzli N Kaiser R Medina S Studnicka M Chanel O

11 Filliger P Herry M Horak F Jr Puybonnieux-Texier V Quenel P et al Public-health impact of outdoor and traffic- related air pollution a European assessment Lancet 356795ndash801 (2000)

Bibliography

1 Sioutas C Delfino RJ Singh M Exposure assessment for atmospheric ultrafine particles (UFP) and implications in epidemiological research Environ Health Perspect 2005113947ndash955

2 Mosleh M Blau PJ Dumitrescu D (2004) Characteristics and morphology of wear particles from laboratory testing of disc brake materials Wear 2561128ndash1134

3 Kuumlnzli N et al (2000) Public-health impact of outdoor and traffi c-related air pollution a European assessment Lancet 356(9232)795ndash801

4 Dora C Phillips M eds (2000) Transport environment and health Copenhagen WHO Regional Office for Europe (WHO Regional Publications European Series No 89 httpwwweurowhointdocumente72015pdf accessed 26 November 2004)

5 Westerholm R Karl-Erik E Exhaust emissions from lightand

6 heavy-duty vehicles chemical composition impact of exhaust after treatment and fuel parameters Environ Health Perspect 102(suppl 4)13ndash23 (1994)

7 Fauser Tjell Mosbaek pigegaard Quantification of tire-Tread particles using extractable Organic Zinc as a Tracer Rubber Chemistry and Technology 1999 969Table shows some literature estimates of the contribution of tire wear to PM10 in air (Panko et al 2013) Gustafsson M Blomqvist G Gudmundsson A Dahl A Swietlicki E Bohgard M Lindbom J Ljungman A

8 Chen Y Shah N Huggins FE and Huffman GP (2006) Microanalysis of Ambient Particles from Lexington Ky by Electron Microscopy Atmos Environ 40 651ndash663

9 Donaldson K Tran CL Jimenez LA Duffin R Newby DE and Mills N (2005) Combustion-derived Nanoparticles A Review of Their Toxicology Following Inhalation Exposure Part Fibre Toxicol 2 10ndash23

10 Su D Serafino A Muller JO Jentoft RE Schlogl R and Fiorito S (2008) Cytotoxicity and Inflammatory Potential of Soot Particles of Low-emission Diesel Engines Environ Sci Technol 42 1761ndash1765

11 Maier KL Alessandrini F Beck-Speier I Hofer TPJ Diabatґe S Bitterle E Stoger T and Jakob T (2008) Health Effects of Ambient Particulate Matter-Biological Mechanisms and Inflammatory Responses to in Vitroand in Vivo Particle Exposures Inhalation Toxicol 20 319ndash337

Page 33: Studies of Air Pollutants and their Impact on Respiratory and ...€¦ · Ascarate Park C37 Monitoring Station: The National Ambient Air Quality Standard (NAAQS) for PM 10 and 2.5

Output Data Moves 2014a

Inventories of PM 10 25 Mobile Emission from all

on-Road Traffic

Exhaust Emission PM 10 25 gramsmile

Brake Wear Emission PM 10 25 gramsmile

Tire wear Emission PM 10 25 gramsmile

Date of Vehicle miles traveled (VMT) for

Day Week Month Year

Total Vehicle population

Vehicle age distribution

Simulation of Mobile Emission in the El PdN Region Zip Code 79905

Figure Total Emissions from road traffic in El Paso TX Area were estimated for PM10

Exhaust and Non exhaust emission in kilogramsmonth (Source EPA MOVES 2014a)

0

10000

20000

30000

40000

50000

PM

10 k

gM

on

th

Months

Monthly PM 10 Exhaust and Non-Exhaust Mobile Emissions 2010

On-Road Urban Restricted Area Zip Code 79905

Primary Exhaust PM 10 (kg) Primary PM 10 Brakewear (kg)

Primary PM 10 Tirewear (kg)

05000

100001500020000250003000035000400004500050000

PM

25

kg

Mo

nth

Months

Monthly PM 25 Exhaust and Non-Exhaust Mobile Emission 2010

On-Road Urban Restricted Area Zip Code 79905

Primary Exhaust PM 25 (kg) Primary PM 25 Brakewear (kg) Primary PM 25Tirewear (kg)

Figure Total Emissions from road traffic in El Paso TX Area were estimated for PM25

Exhaust and Non exhaust emission in kilogramsmonth (Source EPA MOVES 2014a)

Total Emissions from Road Traffic in El Paso County PM1025 Exhaust and Non exhaust Emission in kilogramsmonth

Taking the interests to the health risks related to PM 1025 mobile emission were simulated

Exhaust and Non-exhaust emissions contribute almost equally to total traffic-related PM1025 Emissions (Querol et al 2004 Bukowiecki et al 2009a Amato et al 2011)

Monthly PM 10 25 Exhaust and Non-Exhaust (BrakewearTirewear) Mobile

Emission 2010 On-Road Urban Restricted Area Zip Code 79905

Figure Total Emissions from road traffic in El Paso TX Area were estimated for PM10 25 Exhaust and Non Exhaust mobile

emission in kilograms per month (Source EPA MOVES)

0

10000

20000

30000

40000

50000

January February March April May June July August September October November December

PM

10

25

(K

ilog

ram

s)

Months

Summary- Monthly PM 10 25 Exhaust and Non-Exhaust Mobile

Emission 2010 On-Road Urban Restricted Area Zip Code 79905

Primary Exhaust PM 10 Primary PM 10 Brakewear Primary PM 10 Tirewear

Primary Exhaust PM 25 Primary PM 25 Brakewear Primary PM 25Tirewear

Exhaust Emissions PM1025 is reaching maximum emission 48000-42000 thousand of Kgmonth followedby Brake wear 29000-5000 thousand kgmonth and Tire wear with 9000-2000 kgmonth The results showthat the emissions of PM derived mainly from Exhaust and Brake are significantly higher in Urban Area

Annual Contribution of Mobile Emission PM 1025 (Kg) Zip Code 79905 El

Paso County 2010

Total Primary

Exhaust _PM10

39

Total Primary

Exhaust _PM25

36

Brakewear

particulate_PM10

18

Tirewear

particulate_PM10

4

Brakewear

particulate_PM25

2

Tirewear

particulate_PM25

1

0

5

10

15

20

25

30

35

40

45

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53

Fig Annual Average PM10 Concentrations at the

Chamizal C41 Station and PM1025 mobile

Concentration Zip code 79905

PM10 TCEQ (μgm3) Total Mobile Emission PM10 (Ugm3)

Fig Exhaust Emission is Contributing Approximately 74 of total

PM1025 Mobile Emissions following of Brake wear with 20 and Tire

wear with 5

Annual Average PM1025 ugm3 Mobile Emissions (Moves) 26 Chamizal C41

Monitoring Station (TCEQ Chamizal Station )

Predicting Mobile Emission and VTM

Estimation The PdN Region 2010

44E+09

46E+09

48E+09

5E+09

52E+09

54E+09

56E+09

58E+09

6E+09

62E+09

0

50000

100000

150000

200000

250000

300000

350000

20

10

20

11

20

12

20

13

20

14

20

15

20

16

20

17

20

18

20

21

20

22

20

23

20

24

20

25

20

26

20

27

20

28

20

29

20

30

EX

HA

US

T

EM

ISS

ION

MO

BIL

E (

KG

YE

AR

)

YEARS

Predict ing Mobile Exhaust Emission and VTM

Estimation

2010 - 2030 e l PdN Area

Total_ Exhaust PM10 Total_ Exhaust PM25 Distance (Miles)

Fig Predicting Mobile Exhaust PM1025 (kgMonth) Emission and VTM Estimation 2010

- 2030 el PdN Area

44E+09

46E+09

48E+09

5E+09

52E+09

54E+09

56E+09

58E+09

6E+09

62E+09

0

5000000

10000000

15000000

20000000

25000000

30000000

20

10

20

11

20

12

20

13

20

14

20

15

20

16

20

17

20

18

20

21

20

22

20

23

20

24

20

25

20

26

20

27

20

28

20

29

20

30

EX

HA

US

T

EM

ISS

ION

MO

BIL

E (

KG

YE

AR

)

YEARS

Predict ing Mobile Exhaust Emission and

VTM Estimation

2010 - 2030 e l PdN Area

CO NO2 NO NOx Distance

Fig Predicting Mobile Exhaust Emission and VTM Estimation

2010 - 2030 el PdN Area in El Paso TX Area were estimated for

Total CO NOx NO2 NO emission in kilograms per year

(Source EPA MOVES 2014a model)

The simulated Exhaust emissions in the future years shows a trend of reduction of this type of emissions in the

future years one factor should be the new hybrid technology is increasing by 476 since 2010 to 2015 and

use of catalytic converters diesel particulate filters and improved fuels and engines Non-exhaustive sources

will increase in the coming years because there is no control in the material of manufacture composed by Fe

Cu and Mn also not to be able to reduce the number of events of braking (Accelerations and decelerations)

45E+09

5E+09

55E+09

6E+09

65E+09

0

50000

100000

150000

200000

250000

201

0

201

1

201

2

201

3

201

4

201

5

201

6

201

7

201

8

202

1

202

2

202

3

202

4

202

5

202

6

202

7

202

8

202

9

203

0

NO

N-

EX

HA

US

T

EM

ISS

ION

MO

BIL

E

(KG

YE

AR

)

YEARS

Predicting Non Exhaust Mobile

Emission and VTM Estimation

2010 - 2030 el PdN Area

Brake_PM10 Tire_PM10 Distance (Miles)

Fig Predicting Mobile Exhaust PM1025 (kgMonth) Emission and VTM

Estimation 2010 - 2030 el PdN Area

Daily Avg PM1025

Levels of PM Mobile Emission Non-Exhaust -Rush Hour Periods Fall 2010 Zip Code

79905

00

100

200

300

400

500

600

Mo

bil

e P

M1

0 (k

g)

Rush Hours

Daily Avg PM10

Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush Hours

Periods 2010 Zip Code 79905

Total Primary Exhaust

_PM10 WinterSpring

Brakewear

particulate_PM10

WinterSpringTirewear particulate_PM10

WinterSpring

Total Primary Exhaust

_PM10 Summer

Brakewear

particulate_PM10 Summer

Tirewear Particulate_PM10

Summer

Total Primary Exhaust

_PM10 Fall

Brakewear

particulate_PM10 Fall

Tirewear particulate_PM10

Fall

00

50

100

150

200

250

300

350

Mo

bil

e P

M2

5 (k

g)

Rush hours

Daily Avg PM25

Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush

Hours Periods 2010 Zip Code 79905

Total Primary Exhaust _PM25

WinterSpring

Brakewear Particulate_PM25

WinterSpring

Tirewear particulate_PM25

WinterSpring

Total Primary Exhaust _PM25

Summer

Brakewear particulate_PM25

Summer

Tirewear particulate_PM25

Summer

Total Primary Exhaust _PM25

Fall

Brakewear particulate_PM25

Fall

Tirewear particulate_PM25

Fall

Figure Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush Hours Figure Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush Hours

GIS EMISSIONS INVENTORY SYSTEM A geographic information system (GIS) was used to established geographic scenarios with processed images of seasonal mobile

emissions in the PdN region Seasonal mapping is visualized for different types of pollutants Brakewear Exhaust and Tyrewear

Fg Graphics of GIS and Seasonal mobile Emission of particulate matter emission inventory Seasonal emission simulations were performed in kilograms and five contributing inputs factors were identified for

modeling 1) On the composition of the particulate material from different sources such as Exhaust and Non exhaust (Brake wear Tirewear) 2) The Vehicles Equipment clasification were selected according to

the use of gasoline and diesel fuel (motorcycle passenger car Light Duty Vehicles Trucks refuse truck Light Duty Vehicles Light Commercial Truck Light Duty Vehicles School Bus)

Winter Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

120354 67860 19065

Spring Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

139767 86702 24463

Summer Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

94747 62481 17630

Fall Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

75510 45542 12596

251 Descriptive Statistics Data Analysis

Weekly Correlation Analysis of Mobile Emission PM10 (Exhaust-Non-Exhaust) and Respiratory

Diagnoses WinterSpring Summer and Fall 2010

0

2

4

6

8

10

0

50

100

150

200

250

300

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21

Mo

rbid

ity

Dis

ch

arg

e

for

all R

esp

ira

tory

Dis

ea

se

ICD

-9

(A

sth

ma

-Bro

nc

hitis

)

WinterSpring Week

Weekly Avg Mobile PM10 Concentrations during

WinterSpring 2010 and its Influence on Respiratory

Diagnoses

Zip Code 79905

Total Medical data ZIP Code 79902

Total Mobile Emission PM10 (Ugm3)

0

1

2

3

4

5

6

7

0

20

40

60

80

100

Mo

rbid

ity

Dis

ch

arg

e

for

all R

esp

ira

tory

Dis

ea

se

ICD

-9

(Ast

hm

aB

ron

ch

itis

)

Weekly Avg Mobile PM10 Concentrations during

Summer 2010 and its Influence on Respiratory

Diagnoses

Summer 2010 Zip Code 79905

Total Mobile Emission PM10

Hospital Admission (Asthma-Bronchitis)

0

2

4

6

8

10

12

0

20

40

60

80

100

120

140

160

180

200

Mo

rbid

ity

dis

ch

arg

es

for

all r

esp

ira

tory

dis

ea

se

Weekly Avg Mobile PM10 Concentrations

during Fall 2010 and its Influence on Respiratory

Diagnoses

Zip Code 79905

Total Medical data ZIP Code 79902

Total Mobile Emission PM10 (Ugm3)

Mobile(Exhaust-Non-

Exhaust) PM10 and

Asthma-Bronchitis)

Linear R

Square

WinterSpring 734 ndash 39

Summer 614 ndash 32

Fall 548 -29

PM10 Mobile emission (Exhaust-Non-Exhaust)contributed significantly

association to the incidence of RD

Weekly Correlation Analysis of PM 25 Mobile Emission (Exhaust-Non-Exhaust)

and Cardiovascular Diagnoses WinterSpring Summer and Fall 2010

0010203040

00500

100015002000

Wee

k 1

Wee

k 2

Wee

k 3

Wee

k 4

Wee

k 5

Wee

k 6

Wee

k 7

Wee

k 8

Wee

k 9

Wee

k 1

0

Wee

k 1

1

Wee

k 1

2

Wee

k 1

3

Wee

k 1

4

Wee

k 1

5

Wee

k 1

6

Wee

k 1

7

Wee

k 1

8

Wee

k 1

9

Wee

k 2

0

Wee

k 2

1

Morb

idit

y d

isch

arg

es f

or

all

card

iovasc

ula

r d

isea

se

Weekly Avg PM25 Mobile Concentrations during

WinterSpring 2010 and its Influence on all Heart

Diagnoses

Zip Code 79905

Total All Heart Disease PM 25 mobile (μgm3)

0010203040

00

500

1000

1500

Mo

rbid

ity

dis

ch

arg

es

for

all

ca

rdio

va

scu

lar

dis

ea

se

Weeks

CORRELATION BETWEEN MOBILE PM25 ugm3

EXPOSURE TO HEART DISEASES SYMPTOMS

SUMMER SEASON 2010

Total All Heart Disease PM 25 mobile (μgm3)

Figure Statistical Analyses of the Relationship Between PM25 Caused by Traffic Emission( 26 of total Emission) with Heart diseases Source Hospital Admissions for Asthma Acute Bronchitis and Heart diseases in El Paso County zip code 79905 from Texas Health Care

Information Council in Austin Texas (Texas Health Care Information Council 2000)

00

10

20

30

40

0

50

100

150

We

ek 3

6

We

ek 3

7

We

ek 3

8

We

ek 3

9

We

ek 4

0

We

ek 4

1

We

ek 4

2

We

ek 4

3

We

ek 4

4

We

ek 4

5

We

ek 4

6

We

ek 4

7

We

ek 4

8

We

ek 4

9

We

ek 5

0

We

ek 5

1

We

ek 5

2

We

ek 5

3

Mo

rbid

ity

dis

ch

arg

es

for

all

ca

rdio

va

scu

lar

dis

ea

se

CORRELATION BETWEEN MOBILE PM25 ugm3

EXPOSURE TO HEART DISEASES SYMPTOMS FALL

SEASON 2010

Total All Heart Disease PM 25 mobile (μgm3)

Mobile(Exhaust-

Non-Exhaust)

PM10 and

Asthma-

Bronchitis)

Linear R

Square

WinterSpring 833 -42

Summer 620 -32

Fall 501-26

PM10 Mobile

emission (Exhaust-

Non-

Exhaust)contribut

ed significantly

association to the

incidence of CVD

Diseases

Monthly Brake Mobile Emission PM1025 kg During year 2010 and its Influence on

Respiratory Diagnoses Zip Code 79905

00200040006000800010000

010000200003000040000

PM

10

Mo

bile

(K

g)

Months

Monthly Brake Mobile Emission PM10 kg during year

2010 and its Influence on Respiratory Diagnoses

Zip Code 79905

Primary PM 10

Brakewear 00100020003000400050006000

0

1000

2000

3000

4000

PM

25

Mo

bil

e(K

g)

Months

Monthly Brake Mobile Emission PM25 during

year 2010 and its Influence on Heart Diagnoses

Zip Code 79905

Primary PM 25

Brakewear

Heart Diseases

Hospital

Admission

Brake Mobile Emission

PM10 kg Asthma-

Bronchitis)

Brake Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=969 Linear Square R=856

Monthly Mobile Exhaust Emission PM1025 During year 2010 and its Influence on

Respiratory Diagnoses Zip Code 79905

0

200

400

600

800

1000

0

10000

20000

30000

40000

50000

1 3 5 7 9 11

PM

10

(K

g m

on

th)

Months

Monthly Mobile Exhaust Emission PM10 during

year 2010 and its Influence on Respiratory

Diagnoses

Zip Code 79905

Primary Exhaust

PM 10

Respiratory Disease

(Asthma

Bronchitis) Hospital

Admission

0

100

200

300

400

500

600

0

10000

20000

30000

40000

50000

1 2 3 4 5 6 7 8 9 101112

PM

25

(K

g m

on

th)

Months

Monthly Exhaust Mobile Emission PM25 during

year 2010 and its Influence on Heart Diagnoses

Zip Code 79905

Primary Exhaust PM

25

Heart Diseases

Hospital Admission

Exhaust Mobile Emission

PM10 kg Asthma-

Bronchitis)

Exhaust Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=929 Linear Square R=831

Monthly Tire wear Mobile Emission PM1025 During year 2010 and its Influence on Heart

Diagnoses Zip Code 79905

0

100

200

300

400

500

600

700

800

900

0

1000

2000

3000

4000

5000

6000

7000

8000

9000

1 2 3 4 5 6 7 8 9 10 11 12

PM

10

(K

g m

on

th)

Months

Monthly Tirewear Mobile Emission PM10 during year 2010

and its Influence on Heart Diagnoses

Zip Code 79905

Primary PM 10 Tirewear

Mobile Emission

Respiratory Disease

(Asthma Bronchitis)

Hospital Admission

0

100

200

300

400

500

600

0

200

400

600

800

1000

1200

1400

1 2 3 4 5 6 7 8 9 10 11 12

PM

25

(K

g m

on

th)

Months

Monthly Tirewear Mobile Emission PM25 during year 2010

and its Influence on Respiratory Diagnoses

Zip Code 79905

Primary PM 25Tirewear

Mobile Emission

Heart Diseases Hospital

Admission

Exhaust Mobile Emission

PM10 kg Asthma-

Bronchitis)

Exhaust Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=769 Linear Square R=715

Dona Ana County Zip Codes

88021880278807288048

Primary

Exhaust

PM 10 Zip

code

79905

Total

Primary

Exhaust

PM10

Dona Ana

Primary

Exhaust

PM 25 Zip

Code

79905

Total

Primary

Exhaust

PM25

Dona Ana

Series1 430378 111773 391915 102123

0

100000

200000

300000

400000

500000

AX

IS T

ITLE

Annual Comparison of the Mobile

Exhaust Emissions El Paso County

and Dona Ana 2010

Primary

PM 10

Brakewea

r Zip code

79905

Brakewea

r

particulat

e_PM10

Dona Ana

Primary

PM 10

Tirewear

Zip code

79905

Tirewear

particulat

e_PM10

Dona Ana

Series1 262585 48573 73754 11864

050000

100000150000200000250000300000

AX

IS T

ITLE

Annual Comparison of the Mobile

Brakewear Emissions El Paso County

and Dona Ana 2010

Figure Comparison of the Annual Mobile Emissions

of Primary PM10 Non-Exhauts (Brake ) from Dona

Ana County New Mexico and El Paso Texas Units

in KgMonth

Figure Comparison of the Annual Mobile Emissions

of Primary PM10-Exhauts Emission from Dona Ana

County New Mexico and El Paso Texas Units in

KgMonth

Primary

PM 25

Brakewe

ar Ziphellip

Brakewe

ar

particula

te_PMhellip

Primary

PM

25Tirewe

ar Ziphellip

Tirewear

particula

te_PM25

Donahellip

Series1 32645 6071 10919 1779

0

10000

20000

30000

40000

AX

IS T

ITLE

Annual Comparison of the

Mobile Exhaust Emissions El Paso

County and Dona Ana 2010

Figure Comparison of the Annual Mobile Emissions

of Primary PM10-Exhauts Emission from Dona Ana

County New Mexico and El Paso Texas Units in

KgMonth

Monthly Mobile Emission PM1025 kg During year 2006

and its Influence on Respiratory Diagnoses Dona Ana

County Zip Code 880218802788072

0

100

200

300

0

5000

10000

15000

Axi

s Ti

tle

Axis Title

Monthly Mobile Exhaust Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Total PrimaryMobile Exhaust_PM10

All Respiratory ICD-9 (AsthmaBronchitis)

050100150200250300

010002000300040005000

Axi

s Ti

tle

Axis Title

Monthly Mobile Brake Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Brakewearparticulate_PM10

All RespiratoryICD -9 (AsthmaBronchitis)

050100150200250300

0200400600800

10001200

Axi

s Ti

tle

Axis Title

Monthly Mobile Tirewear Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Tirewearparticulate_PM10

All Respiratory ICD -9 (AsthmaBronchitis)

Mobile Exhauts

Emission PM10

kg Asthma-

Bronchitis)

Brake Mobile

Emission PM10

kg and Heart

Diagnoses

Tirewear Mobile

Emission PM10

kg and Heart

Diagnoses

Linear Square

R= 951

Linear Square

R=625

Linear Square

R=525

Mobile Exhauts

Emission PM25

kg Asthma-

Bronchitis)

Brake Mobile

Emission PM25

kg and Heart

Diagnoses

Tirewear Mobile

Emission PM25

kg and Heart

Diagnoses

Linear Square

R= 986

Linear Square

R=691

Linear Square

R=601

Results

The results showed that mobile PM emissions in the urban areas close to urban Road and highways is putting at risk public health

and the proportion of diseases attributable to this exposure is potentially large

Brake wear emissions is much lower in freeways due to significantly reduced number of braking events while tire wear is much

higher in areas where studded tires are used The emission of exhaust gases are much higher in areas where there is a high

vehicular traffic

Brake Mobile

Emission PM10 kg

Asthma-Bronchitis)

Brake Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square

R=969

Linear Square

R=856

Exhaust Mobile

Emission PM10 kg

Asthma-Bronchitis)

Exhaust Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square

R=929

Linear Square

R=831

Tirewear Mobile

Emission PM10 kg

Asthma-Bronchitis)

Tirewear Mobile

Emission PM25 kg

and Heart Diagnoses

Linear Square R=769 Linear Square R=715

Brake Mobile

Emission PM10 kg

and Heart

Diagnoses

Brake Mobile

Emission PM25 kg

and Heart

Diagnoses

Exhaust Mobile

Emission PM10 kg

Asthma-Bronchitis)

Linear Square

R=625

Linear Square

R=691

Linear Square R=

951

Exhaust Mobile

Emission PM25 kg

Asthma-

Bronchitis)

Tire wear Mobile

Emission PM10 kg and

Heart Diagnoses

Tirewear Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square R=

986

Linear Square R=525 Linear Square

R=601

El Paso County

Dona Ana

County

BenMAP-CE

In this analysis the Program of Mapping and Analysis of Environmental Benefits-Community Edition

(BenMAP-CE) was used to Estimate the number and economic value of health impacts resulting from changes

in air pollution PM 25 Ugm3 in The El Paso Area

Health and Economic Benefits associated with the Response of PM25 Emission between

Base Year 2010

Number of Mortalities in 2010 Base Year Based on El Paso County Texas Department of State Health Services

Number of Mortalities in 2010 Base Year Based on El Paso County Texas

Department of State Health Services

cause of death

year

2010

Populatio

n

Affected

Backgro

und

Concentr

ation Pollutant

Rollback

Type

Avoided

Deaths

(

Populatio

n)

alzheimers disease 2010 40716 125 PM25

25

microgmAcircsup3

Rollback 9

diseases of the

heart 2010 15834 125 PM25

25

microgmAcircsup3

Rollback 35

influenza and

neumonia 2010 81432 125 PM25

25

microgmAcircsup3

Rollback 18

acute bronchitis

and bronchiolitis 2010 117624 125 PM25

25

microgmAcircsup3

Rollback 26

chronic lower

respiratory diseases 2010 54288 125 PM25

25

microgmAcircsup3

Rollback 12

The Basin-wide decrease in 4 ugm3 PM25 concentration after this

reduction control

Cause of death year 2010

Populatio

n

Affected

Background

Concentrati

on

Reduc

cion

scena

rio Polluta

nt

Rollback

Type

Avoi

ded

Deat

hs

(

Pop

ulati

on)

economic

benefits

analysis $

Alzheimers

disease 2010 121 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 9 12000

Diseases of the

heart 2010 470 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 35 35000

Influenza and

neumonia 2010 242 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 18 42500

Acute bronchitis

and bronchiolitis 2010 349 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 26 95000

Chronic lower

respiratory

diseases 2010 161 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 12 4500

$1 295000

PM25-related Mortalities Based on BenMAP-CE Estimate in 2010 Base Year with change in the concentrations levels

Health and Economic Benefits associated with the Response of PM25 Emission between

Base Year 2010 Increasing 7 Ugm3

Cause of death year 2010

Population

Affected

Deaths

avoided by

attaining 195

μgm3

standard

Background

Concentrati

on

Pollut

ant

Rollback

Type

Avoided

Deaths (

Populatio

n)

econo

mic

Unben

efits

analysi

s

Alzheimers

disease 2010 4524 195 PM25

25

microgmAcircsup3

Rollback 19 150000

Diseases of the

heart 2010 20358 195 PM25

25

microgmAcircsup3

Rollback 135 450000

Influenza and

neumonia 2010 126672 195 PM25

25

microgmAcircsup3

Rollback 38 525000

Acute bronchitis

and bronchiolitis 2010 162864 195 PM25

25

microgmAcircsup3

Rollback 36 122000

Chronic lower

respiratory

diseases 2010 99528 195 PM25

25

microgmAcircsup3

Rollback 12 650000

Conclusions

An excellent Pearson Correlation was established to analyze the relationship in the relative risks of hospitalization of Respiratory(RD) and cardiovascular (CVD) associated with ambient exposure caused by traffic emission in relation to their size andspecific sources of emission on different scenarios interior a border Urban Rural Urban restricted access (freeways andinterstates)

A significant correlation of PM1025 exposure from mobile emission and hospital admissions for selected Respiratory (RD) andcardiovascular (CVD) diagnoses was established The results showed that PM emissions in urban restricted access (freeways andinterstates) is mainly caused by traffic Therefore people living close to highways are more exposed higher vehicular emissions

Conclusions

We found statistically significant associations between mobile PM25 caused by traffic emission with Respiratory and Cardiovascular Diseases in the study areaSubsequently a correlation between cardio-respiratory mortality is established

A significant correlation of PM1025 exposure from mobile emission and hospital admissions for selected Respiratory (RD) and cardiovascular (CVD) diagnoses isestablished The results showed that PM emissions in urban restricted access (freeways and interstates) is mainly caused by traffic Therefore people living close tohighways receive higher vehicular emissions

The table shows the percentage of PM mobile exposure in the analyzed areas contributing to increase the risk of Respiratory and Cardiovascular Diseases

An examination was conducted of the synoptic and local meteorology for the June 2006 ozone episode using the WRF model to determine how meteorological parametersinfluence the formation transport and dispersion of ozone in the PdN The predominant synoptic feature of the ozone event day was the expansion intensification and slowprogression of an upper-level ridge of high pressure The high ozone episodes are associated with highly stable atmospheres strong temperature inversions with low mixingheights and therefore low mixing volumes Under these conditions emissions such as NOx lead to highly polluted conditions that favor ozone formation

BenMAP Conclusions

We have estimated the number and economic value of health impacts resulting

from changes in air pollution concentrations of PM 25 in the PdN region

Reduction of Pm 25 4 UGm3= Avoided 213 cases respiratory cardiovascular

diseses and Economic Benefits associated with the Response of PM25 Emission + $

1295000

Increase of PM25 7 ugm3 = increasing Dies= 326 economic Unbenefits= 2345000$

Bibliography

1 Dockery DW Pope CAI Xu X Spengler JD Ware JH Fay ME Ferris BG Speizer FE An association between air pollution and mortality in six US cities N Engl J Med 3291753ndash1759 (1993)

2 Samet JM Dominici F Curriero FC Coursac I Zeger SL Fine particulate air pollution and mortality in 20 US cities 1987ndash1994 N Engl J Med 3431742ndash1749 (2000)

3 Nel AE Diaz-Sanchez D Li N The role of particulate pollutants in pulmonary inflammation and asthma evidence for the involvement of organic chemicals and oxidative stress Curr Opin Pulm Med 20017 20ndash26

4 Westerholm R Karl-Erik E Exhaust emissions from lightand heavy-duty vehicles chemical composition impact of exhaust after treatment and fuel parameters Environ Health Perspect 102(suppl 4)13ndash23 (1994)

5 Bascom R Bromberg P Costa D Delvin R Dockery D Frampton M Lambert W Samet J Speizer F Utell

6 Health effects of outdoor air pollution Am J Respir Crit Care Med 1533ndash50 (1996)

7 Chow JC Watson JG Frazier CA Egami RT Goodrich A Ralph C Spatial and temporal source contributions to

8 PM10 and PM25 in Reno NV In PM-10 Implementation of Standards Transactions An APCAEPA International Speciality Conference San Francisco CA (Mathal CV Stonefield DH eds) PittsburghAPCA 1988439ndash457

9 overview In Particulate Matter Health and Regulatory Issues VIP-49 Proceedings of an International Specialty Conference 4ndash6 April 1995 Pittsburgh PA PittsburghAir and Waste Management Association 1995577ndash598

10 Kunzli N Kaiser R Medina S Studnicka M Chanel O

11 Filliger P Herry M Horak F Jr Puybonnieux-Texier V Quenel P et al Public-health impact of outdoor and traffic- related air pollution a European assessment Lancet 356795ndash801 (2000)

Bibliography

1 Sioutas C Delfino RJ Singh M Exposure assessment for atmospheric ultrafine particles (UFP) and implications in epidemiological research Environ Health Perspect 2005113947ndash955

2 Mosleh M Blau PJ Dumitrescu D (2004) Characteristics and morphology of wear particles from laboratory testing of disc brake materials Wear 2561128ndash1134

3 Kuumlnzli N et al (2000) Public-health impact of outdoor and traffi c-related air pollution a European assessment Lancet 356(9232)795ndash801

4 Dora C Phillips M eds (2000) Transport environment and health Copenhagen WHO Regional Office for Europe (WHO Regional Publications European Series No 89 httpwwweurowhointdocumente72015pdf accessed 26 November 2004)

5 Westerholm R Karl-Erik E Exhaust emissions from lightand

6 heavy-duty vehicles chemical composition impact of exhaust after treatment and fuel parameters Environ Health Perspect 102(suppl 4)13ndash23 (1994)

7 Fauser Tjell Mosbaek pigegaard Quantification of tire-Tread particles using extractable Organic Zinc as a Tracer Rubber Chemistry and Technology 1999 969Table shows some literature estimates of the contribution of tire wear to PM10 in air (Panko et al 2013) Gustafsson M Blomqvist G Gudmundsson A Dahl A Swietlicki E Bohgard M Lindbom J Ljungman A

8 Chen Y Shah N Huggins FE and Huffman GP (2006) Microanalysis of Ambient Particles from Lexington Ky by Electron Microscopy Atmos Environ 40 651ndash663

9 Donaldson K Tran CL Jimenez LA Duffin R Newby DE and Mills N (2005) Combustion-derived Nanoparticles A Review of Their Toxicology Following Inhalation Exposure Part Fibre Toxicol 2 10ndash23

10 Su D Serafino A Muller JO Jentoft RE Schlogl R and Fiorito S (2008) Cytotoxicity and Inflammatory Potential of Soot Particles of Low-emission Diesel Engines Environ Sci Technol 42 1761ndash1765

11 Maier KL Alessandrini F Beck-Speier I Hofer TPJ Diabatґe S Bitterle E Stoger T and Jakob T (2008) Health Effects of Ambient Particulate Matter-Biological Mechanisms and Inflammatory Responses to in Vitroand in Vivo Particle Exposures Inhalation Toxicol 20 319ndash337

Page 34: Studies of Air Pollutants and their Impact on Respiratory and ...€¦ · Ascarate Park C37 Monitoring Station: The National Ambient Air Quality Standard (NAAQS) for PM 10 and 2.5

Simulation of Mobile Emission in the El PdN Region Zip Code 79905

Figure Total Emissions from road traffic in El Paso TX Area were estimated for PM10

Exhaust and Non exhaust emission in kilogramsmonth (Source EPA MOVES 2014a)

0

10000

20000

30000

40000

50000

PM

10 k

gM

on

th

Months

Monthly PM 10 Exhaust and Non-Exhaust Mobile Emissions 2010

On-Road Urban Restricted Area Zip Code 79905

Primary Exhaust PM 10 (kg) Primary PM 10 Brakewear (kg)

Primary PM 10 Tirewear (kg)

05000

100001500020000250003000035000400004500050000

PM

25

kg

Mo

nth

Months

Monthly PM 25 Exhaust and Non-Exhaust Mobile Emission 2010

On-Road Urban Restricted Area Zip Code 79905

Primary Exhaust PM 25 (kg) Primary PM 25 Brakewear (kg) Primary PM 25Tirewear (kg)

Figure Total Emissions from road traffic in El Paso TX Area were estimated for PM25

Exhaust and Non exhaust emission in kilogramsmonth (Source EPA MOVES 2014a)

Total Emissions from Road Traffic in El Paso County PM1025 Exhaust and Non exhaust Emission in kilogramsmonth

Taking the interests to the health risks related to PM 1025 mobile emission were simulated

Exhaust and Non-exhaust emissions contribute almost equally to total traffic-related PM1025 Emissions (Querol et al 2004 Bukowiecki et al 2009a Amato et al 2011)

Monthly PM 10 25 Exhaust and Non-Exhaust (BrakewearTirewear) Mobile

Emission 2010 On-Road Urban Restricted Area Zip Code 79905

Figure Total Emissions from road traffic in El Paso TX Area were estimated for PM10 25 Exhaust and Non Exhaust mobile

emission in kilograms per month (Source EPA MOVES)

0

10000

20000

30000

40000

50000

January February March April May June July August September October November December

PM

10

25

(K

ilog

ram

s)

Months

Summary- Monthly PM 10 25 Exhaust and Non-Exhaust Mobile

Emission 2010 On-Road Urban Restricted Area Zip Code 79905

Primary Exhaust PM 10 Primary PM 10 Brakewear Primary PM 10 Tirewear

Primary Exhaust PM 25 Primary PM 25 Brakewear Primary PM 25Tirewear

Exhaust Emissions PM1025 is reaching maximum emission 48000-42000 thousand of Kgmonth followedby Brake wear 29000-5000 thousand kgmonth and Tire wear with 9000-2000 kgmonth The results showthat the emissions of PM derived mainly from Exhaust and Brake are significantly higher in Urban Area

Annual Contribution of Mobile Emission PM 1025 (Kg) Zip Code 79905 El

Paso County 2010

Total Primary

Exhaust _PM10

39

Total Primary

Exhaust _PM25

36

Brakewear

particulate_PM10

18

Tirewear

particulate_PM10

4

Brakewear

particulate_PM25

2

Tirewear

particulate_PM25

1

0

5

10

15

20

25

30

35

40

45

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53

Fig Annual Average PM10 Concentrations at the

Chamizal C41 Station and PM1025 mobile

Concentration Zip code 79905

PM10 TCEQ (μgm3) Total Mobile Emission PM10 (Ugm3)

Fig Exhaust Emission is Contributing Approximately 74 of total

PM1025 Mobile Emissions following of Brake wear with 20 and Tire

wear with 5

Annual Average PM1025 ugm3 Mobile Emissions (Moves) 26 Chamizal C41

Monitoring Station (TCEQ Chamizal Station )

Predicting Mobile Emission and VTM

Estimation The PdN Region 2010

44E+09

46E+09

48E+09

5E+09

52E+09

54E+09

56E+09

58E+09

6E+09

62E+09

0

50000

100000

150000

200000

250000

300000

350000

20

10

20

11

20

12

20

13

20

14

20

15

20

16

20

17

20

18

20

21

20

22

20

23

20

24

20

25

20

26

20

27

20

28

20

29

20

30

EX

HA

US

T

EM

ISS

ION

MO

BIL

E (

KG

YE

AR

)

YEARS

Predict ing Mobile Exhaust Emission and VTM

Estimation

2010 - 2030 e l PdN Area

Total_ Exhaust PM10 Total_ Exhaust PM25 Distance (Miles)

Fig Predicting Mobile Exhaust PM1025 (kgMonth) Emission and VTM Estimation 2010

- 2030 el PdN Area

44E+09

46E+09

48E+09

5E+09

52E+09

54E+09

56E+09

58E+09

6E+09

62E+09

0

5000000

10000000

15000000

20000000

25000000

30000000

20

10

20

11

20

12

20

13

20

14

20

15

20

16

20

17

20

18

20

21

20

22

20

23

20

24

20

25

20

26

20

27

20

28

20

29

20

30

EX

HA

US

T

EM

ISS

ION

MO

BIL

E (

KG

YE

AR

)

YEARS

Predict ing Mobile Exhaust Emission and

VTM Estimation

2010 - 2030 e l PdN Area

CO NO2 NO NOx Distance

Fig Predicting Mobile Exhaust Emission and VTM Estimation

2010 - 2030 el PdN Area in El Paso TX Area were estimated for

Total CO NOx NO2 NO emission in kilograms per year

(Source EPA MOVES 2014a model)

The simulated Exhaust emissions in the future years shows a trend of reduction of this type of emissions in the

future years one factor should be the new hybrid technology is increasing by 476 since 2010 to 2015 and

use of catalytic converters diesel particulate filters and improved fuels and engines Non-exhaustive sources

will increase in the coming years because there is no control in the material of manufacture composed by Fe

Cu and Mn also not to be able to reduce the number of events of braking (Accelerations and decelerations)

45E+09

5E+09

55E+09

6E+09

65E+09

0

50000

100000

150000

200000

250000

201

0

201

1

201

2

201

3

201

4

201

5

201

6

201

7

201

8

202

1

202

2

202

3

202

4

202

5

202

6

202

7

202

8

202

9

203

0

NO

N-

EX

HA

US

T

EM

ISS

ION

MO

BIL

E

(KG

YE

AR

)

YEARS

Predicting Non Exhaust Mobile

Emission and VTM Estimation

2010 - 2030 el PdN Area

Brake_PM10 Tire_PM10 Distance (Miles)

Fig Predicting Mobile Exhaust PM1025 (kgMonth) Emission and VTM

Estimation 2010 - 2030 el PdN Area

Daily Avg PM1025

Levels of PM Mobile Emission Non-Exhaust -Rush Hour Periods Fall 2010 Zip Code

79905

00

100

200

300

400

500

600

Mo

bil

e P

M1

0 (k

g)

Rush Hours

Daily Avg PM10

Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush Hours

Periods 2010 Zip Code 79905

Total Primary Exhaust

_PM10 WinterSpring

Brakewear

particulate_PM10

WinterSpringTirewear particulate_PM10

WinterSpring

Total Primary Exhaust

_PM10 Summer

Brakewear

particulate_PM10 Summer

Tirewear Particulate_PM10

Summer

Total Primary Exhaust

_PM10 Fall

Brakewear

particulate_PM10 Fall

Tirewear particulate_PM10

Fall

00

50

100

150

200

250

300

350

Mo

bil

e P

M2

5 (k

g)

Rush hours

Daily Avg PM25

Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush

Hours Periods 2010 Zip Code 79905

Total Primary Exhaust _PM25

WinterSpring

Brakewear Particulate_PM25

WinterSpring

Tirewear particulate_PM25

WinterSpring

Total Primary Exhaust _PM25

Summer

Brakewear particulate_PM25

Summer

Tirewear particulate_PM25

Summer

Total Primary Exhaust _PM25

Fall

Brakewear particulate_PM25

Fall

Tirewear particulate_PM25

Fall

Figure Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush Hours Figure Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush Hours

GIS EMISSIONS INVENTORY SYSTEM A geographic information system (GIS) was used to established geographic scenarios with processed images of seasonal mobile

emissions in the PdN region Seasonal mapping is visualized for different types of pollutants Brakewear Exhaust and Tyrewear

Fg Graphics of GIS and Seasonal mobile Emission of particulate matter emission inventory Seasonal emission simulations were performed in kilograms and five contributing inputs factors were identified for

modeling 1) On the composition of the particulate material from different sources such as Exhaust and Non exhaust (Brake wear Tirewear) 2) The Vehicles Equipment clasification were selected according to

the use of gasoline and diesel fuel (motorcycle passenger car Light Duty Vehicles Trucks refuse truck Light Duty Vehicles Light Commercial Truck Light Duty Vehicles School Bus)

Winter Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

120354 67860 19065

Spring Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

139767 86702 24463

Summer Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

94747 62481 17630

Fall Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

75510 45542 12596

251 Descriptive Statistics Data Analysis

Weekly Correlation Analysis of Mobile Emission PM10 (Exhaust-Non-Exhaust) and Respiratory

Diagnoses WinterSpring Summer and Fall 2010

0

2

4

6

8

10

0

50

100

150

200

250

300

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21

Mo

rbid

ity

Dis

ch

arg

e

for

all R

esp

ira

tory

Dis

ea

se

ICD

-9

(A

sth

ma

-Bro

nc

hitis

)

WinterSpring Week

Weekly Avg Mobile PM10 Concentrations during

WinterSpring 2010 and its Influence on Respiratory

Diagnoses

Zip Code 79905

Total Medical data ZIP Code 79902

Total Mobile Emission PM10 (Ugm3)

0

1

2

3

4

5

6

7

0

20

40

60

80

100

Mo

rbid

ity

Dis

ch

arg

e

for

all R

esp

ira

tory

Dis

ea

se

ICD

-9

(Ast

hm

aB

ron

ch

itis

)

Weekly Avg Mobile PM10 Concentrations during

Summer 2010 and its Influence on Respiratory

Diagnoses

Summer 2010 Zip Code 79905

Total Mobile Emission PM10

Hospital Admission (Asthma-Bronchitis)

0

2

4

6

8

10

12

0

20

40

60

80

100

120

140

160

180

200

Mo

rbid

ity

dis

ch

arg

es

for

all r

esp

ira

tory

dis

ea

se

Weekly Avg Mobile PM10 Concentrations

during Fall 2010 and its Influence on Respiratory

Diagnoses

Zip Code 79905

Total Medical data ZIP Code 79902

Total Mobile Emission PM10 (Ugm3)

Mobile(Exhaust-Non-

Exhaust) PM10 and

Asthma-Bronchitis)

Linear R

Square

WinterSpring 734 ndash 39

Summer 614 ndash 32

Fall 548 -29

PM10 Mobile emission (Exhaust-Non-Exhaust)contributed significantly

association to the incidence of RD

Weekly Correlation Analysis of PM 25 Mobile Emission (Exhaust-Non-Exhaust)

and Cardiovascular Diagnoses WinterSpring Summer and Fall 2010

0010203040

00500

100015002000

Wee

k 1

Wee

k 2

Wee

k 3

Wee

k 4

Wee

k 5

Wee

k 6

Wee

k 7

Wee

k 8

Wee

k 9

Wee

k 1

0

Wee

k 1

1

Wee

k 1

2

Wee

k 1

3

Wee

k 1

4

Wee

k 1

5

Wee

k 1

6

Wee

k 1

7

Wee

k 1

8

Wee

k 1

9

Wee

k 2

0

Wee

k 2

1

Morb

idit

y d

isch

arg

es f

or

all

card

iovasc

ula

r d

isea

se

Weekly Avg PM25 Mobile Concentrations during

WinterSpring 2010 and its Influence on all Heart

Diagnoses

Zip Code 79905

Total All Heart Disease PM 25 mobile (μgm3)

0010203040

00

500

1000

1500

Mo

rbid

ity

dis

ch

arg

es

for

all

ca

rdio

va

scu

lar

dis

ea

se

Weeks

CORRELATION BETWEEN MOBILE PM25 ugm3

EXPOSURE TO HEART DISEASES SYMPTOMS

SUMMER SEASON 2010

Total All Heart Disease PM 25 mobile (μgm3)

Figure Statistical Analyses of the Relationship Between PM25 Caused by Traffic Emission( 26 of total Emission) with Heart diseases Source Hospital Admissions for Asthma Acute Bronchitis and Heart diseases in El Paso County zip code 79905 from Texas Health Care

Information Council in Austin Texas (Texas Health Care Information Council 2000)

00

10

20

30

40

0

50

100

150

We

ek 3

6

We

ek 3

7

We

ek 3

8

We

ek 3

9

We

ek 4

0

We

ek 4

1

We

ek 4

2

We

ek 4

3

We

ek 4

4

We

ek 4

5

We

ek 4

6

We

ek 4

7

We

ek 4

8

We

ek 4

9

We

ek 5

0

We

ek 5

1

We

ek 5

2

We

ek 5

3

Mo

rbid

ity

dis

ch

arg

es

for

all

ca

rdio

va

scu

lar

dis

ea

se

CORRELATION BETWEEN MOBILE PM25 ugm3

EXPOSURE TO HEART DISEASES SYMPTOMS FALL

SEASON 2010

Total All Heart Disease PM 25 mobile (μgm3)

Mobile(Exhaust-

Non-Exhaust)

PM10 and

Asthma-

Bronchitis)

Linear R

Square

WinterSpring 833 -42

Summer 620 -32

Fall 501-26

PM10 Mobile

emission (Exhaust-

Non-

Exhaust)contribut

ed significantly

association to the

incidence of CVD

Diseases

Monthly Brake Mobile Emission PM1025 kg During year 2010 and its Influence on

Respiratory Diagnoses Zip Code 79905

00200040006000800010000

010000200003000040000

PM

10

Mo

bile

(K

g)

Months

Monthly Brake Mobile Emission PM10 kg during year

2010 and its Influence on Respiratory Diagnoses

Zip Code 79905

Primary PM 10

Brakewear 00100020003000400050006000

0

1000

2000

3000

4000

PM

25

Mo

bil

e(K

g)

Months

Monthly Brake Mobile Emission PM25 during

year 2010 and its Influence on Heart Diagnoses

Zip Code 79905

Primary PM 25

Brakewear

Heart Diseases

Hospital

Admission

Brake Mobile Emission

PM10 kg Asthma-

Bronchitis)

Brake Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=969 Linear Square R=856

Monthly Mobile Exhaust Emission PM1025 During year 2010 and its Influence on

Respiratory Diagnoses Zip Code 79905

0

200

400

600

800

1000

0

10000

20000

30000

40000

50000

1 3 5 7 9 11

PM

10

(K

g m

on

th)

Months

Monthly Mobile Exhaust Emission PM10 during

year 2010 and its Influence on Respiratory

Diagnoses

Zip Code 79905

Primary Exhaust

PM 10

Respiratory Disease

(Asthma

Bronchitis) Hospital

Admission

0

100

200

300

400

500

600

0

10000

20000

30000

40000

50000

1 2 3 4 5 6 7 8 9 101112

PM

25

(K

g m

on

th)

Months

Monthly Exhaust Mobile Emission PM25 during

year 2010 and its Influence on Heart Diagnoses

Zip Code 79905

Primary Exhaust PM

25

Heart Diseases

Hospital Admission

Exhaust Mobile Emission

PM10 kg Asthma-

Bronchitis)

Exhaust Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=929 Linear Square R=831

Monthly Tire wear Mobile Emission PM1025 During year 2010 and its Influence on Heart

Diagnoses Zip Code 79905

0

100

200

300

400

500

600

700

800

900

0

1000

2000

3000

4000

5000

6000

7000

8000

9000

1 2 3 4 5 6 7 8 9 10 11 12

PM

10

(K

g m

on

th)

Months

Monthly Tirewear Mobile Emission PM10 during year 2010

and its Influence on Heart Diagnoses

Zip Code 79905

Primary PM 10 Tirewear

Mobile Emission

Respiratory Disease

(Asthma Bronchitis)

Hospital Admission

0

100

200

300

400

500

600

0

200

400

600

800

1000

1200

1400

1 2 3 4 5 6 7 8 9 10 11 12

PM

25

(K

g m

on

th)

Months

Monthly Tirewear Mobile Emission PM25 during year 2010

and its Influence on Respiratory Diagnoses

Zip Code 79905

Primary PM 25Tirewear

Mobile Emission

Heart Diseases Hospital

Admission

Exhaust Mobile Emission

PM10 kg Asthma-

Bronchitis)

Exhaust Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=769 Linear Square R=715

Dona Ana County Zip Codes

88021880278807288048

Primary

Exhaust

PM 10 Zip

code

79905

Total

Primary

Exhaust

PM10

Dona Ana

Primary

Exhaust

PM 25 Zip

Code

79905

Total

Primary

Exhaust

PM25

Dona Ana

Series1 430378 111773 391915 102123

0

100000

200000

300000

400000

500000

AX

IS T

ITLE

Annual Comparison of the Mobile

Exhaust Emissions El Paso County

and Dona Ana 2010

Primary

PM 10

Brakewea

r Zip code

79905

Brakewea

r

particulat

e_PM10

Dona Ana

Primary

PM 10

Tirewear

Zip code

79905

Tirewear

particulat

e_PM10

Dona Ana

Series1 262585 48573 73754 11864

050000

100000150000200000250000300000

AX

IS T

ITLE

Annual Comparison of the Mobile

Brakewear Emissions El Paso County

and Dona Ana 2010

Figure Comparison of the Annual Mobile Emissions

of Primary PM10 Non-Exhauts (Brake ) from Dona

Ana County New Mexico and El Paso Texas Units

in KgMonth

Figure Comparison of the Annual Mobile Emissions

of Primary PM10-Exhauts Emission from Dona Ana

County New Mexico and El Paso Texas Units in

KgMonth

Primary

PM 25

Brakewe

ar Ziphellip

Brakewe

ar

particula

te_PMhellip

Primary

PM

25Tirewe

ar Ziphellip

Tirewear

particula

te_PM25

Donahellip

Series1 32645 6071 10919 1779

0

10000

20000

30000

40000

AX

IS T

ITLE

Annual Comparison of the

Mobile Exhaust Emissions El Paso

County and Dona Ana 2010

Figure Comparison of the Annual Mobile Emissions

of Primary PM10-Exhauts Emission from Dona Ana

County New Mexico and El Paso Texas Units in

KgMonth

Monthly Mobile Emission PM1025 kg During year 2006

and its Influence on Respiratory Diagnoses Dona Ana

County Zip Code 880218802788072

0

100

200

300

0

5000

10000

15000

Axi

s Ti

tle

Axis Title

Monthly Mobile Exhaust Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Total PrimaryMobile Exhaust_PM10

All Respiratory ICD-9 (AsthmaBronchitis)

050100150200250300

010002000300040005000

Axi

s Ti

tle

Axis Title

Monthly Mobile Brake Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Brakewearparticulate_PM10

All RespiratoryICD -9 (AsthmaBronchitis)

050100150200250300

0200400600800

10001200

Axi

s Ti

tle

Axis Title

Monthly Mobile Tirewear Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Tirewearparticulate_PM10

All Respiratory ICD -9 (AsthmaBronchitis)

Mobile Exhauts

Emission PM10

kg Asthma-

Bronchitis)

Brake Mobile

Emission PM10

kg and Heart

Diagnoses

Tirewear Mobile

Emission PM10

kg and Heart

Diagnoses

Linear Square

R= 951

Linear Square

R=625

Linear Square

R=525

Mobile Exhauts

Emission PM25

kg Asthma-

Bronchitis)

Brake Mobile

Emission PM25

kg and Heart

Diagnoses

Tirewear Mobile

Emission PM25

kg and Heart

Diagnoses

Linear Square

R= 986

Linear Square

R=691

Linear Square

R=601

Results

The results showed that mobile PM emissions in the urban areas close to urban Road and highways is putting at risk public health

and the proportion of diseases attributable to this exposure is potentially large

Brake wear emissions is much lower in freeways due to significantly reduced number of braking events while tire wear is much

higher in areas where studded tires are used The emission of exhaust gases are much higher in areas where there is a high

vehicular traffic

Brake Mobile

Emission PM10 kg

Asthma-Bronchitis)

Brake Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square

R=969

Linear Square

R=856

Exhaust Mobile

Emission PM10 kg

Asthma-Bronchitis)

Exhaust Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square

R=929

Linear Square

R=831

Tirewear Mobile

Emission PM10 kg

Asthma-Bronchitis)

Tirewear Mobile

Emission PM25 kg

and Heart Diagnoses

Linear Square R=769 Linear Square R=715

Brake Mobile

Emission PM10 kg

and Heart

Diagnoses

Brake Mobile

Emission PM25 kg

and Heart

Diagnoses

Exhaust Mobile

Emission PM10 kg

Asthma-Bronchitis)

Linear Square

R=625

Linear Square

R=691

Linear Square R=

951

Exhaust Mobile

Emission PM25 kg

Asthma-

Bronchitis)

Tire wear Mobile

Emission PM10 kg and

Heart Diagnoses

Tirewear Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square R=

986

Linear Square R=525 Linear Square

R=601

El Paso County

Dona Ana

County

BenMAP-CE

In this analysis the Program of Mapping and Analysis of Environmental Benefits-Community Edition

(BenMAP-CE) was used to Estimate the number and economic value of health impacts resulting from changes

in air pollution PM 25 Ugm3 in The El Paso Area

Health and Economic Benefits associated with the Response of PM25 Emission between

Base Year 2010

Number of Mortalities in 2010 Base Year Based on El Paso County Texas Department of State Health Services

Number of Mortalities in 2010 Base Year Based on El Paso County Texas

Department of State Health Services

cause of death

year

2010

Populatio

n

Affected

Backgro

und

Concentr

ation Pollutant

Rollback

Type

Avoided

Deaths

(

Populatio

n)

alzheimers disease 2010 40716 125 PM25

25

microgmAcircsup3

Rollback 9

diseases of the

heart 2010 15834 125 PM25

25

microgmAcircsup3

Rollback 35

influenza and

neumonia 2010 81432 125 PM25

25

microgmAcircsup3

Rollback 18

acute bronchitis

and bronchiolitis 2010 117624 125 PM25

25

microgmAcircsup3

Rollback 26

chronic lower

respiratory diseases 2010 54288 125 PM25

25

microgmAcircsup3

Rollback 12

The Basin-wide decrease in 4 ugm3 PM25 concentration after this

reduction control

Cause of death year 2010

Populatio

n

Affected

Background

Concentrati

on

Reduc

cion

scena

rio Polluta

nt

Rollback

Type

Avoi

ded

Deat

hs

(

Pop

ulati

on)

economic

benefits

analysis $

Alzheimers

disease 2010 121 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 9 12000

Diseases of the

heart 2010 470 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 35 35000

Influenza and

neumonia 2010 242 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 18 42500

Acute bronchitis

and bronchiolitis 2010 349 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 26 95000

Chronic lower

respiratory

diseases 2010 161 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 12 4500

$1 295000

PM25-related Mortalities Based on BenMAP-CE Estimate in 2010 Base Year with change in the concentrations levels

Health and Economic Benefits associated with the Response of PM25 Emission between

Base Year 2010 Increasing 7 Ugm3

Cause of death year 2010

Population

Affected

Deaths

avoided by

attaining 195

μgm3

standard

Background

Concentrati

on

Pollut

ant

Rollback

Type

Avoided

Deaths (

Populatio

n)

econo

mic

Unben

efits

analysi

s

Alzheimers

disease 2010 4524 195 PM25

25

microgmAcircsup3

Rollback 19 150000

Diseases of the

heart 2010 20358 195 PM25

25

microgmAcircsup3

Rollback 135 450000

Influenza and

neumonia 2010 126672 195 PM25

25

microgmAcircsup3

Rollback 38 525000

Acute bronchitis

and bronchiolitis 2010 162864 195 PM25

25

microgmAcircsup3

Rollback 36 122000

Chronic lower

respiratory

diseases 2010 99528 195 PM25

25

microgmAcircsup3

Rollback 12 650000

Conclusions

An excellent Pearson Correlation was established to analyze the relationship in the relative risks of hospitalization of Respiratory(RD) and cardiovascular (CVD) associated with ambient exposure caused by traffic emission in relation to their size andspecific sources of emission on different scenarios interior a border Urban Rural Urban restricted access (freeways andinterstates)

A significant correlation of PM1025 exposure from mobile emission and hospital admissions for selected Respiratory (RD) andcardiovascular (CVD) diagnoses was established The results showed that PM emissions in urban restricted access (freeways andinterstates) is mainly caused by traffic Therefore people living close to highways are more exposed higher vehicular emissions

Conclusions

We found statistically significant associations between mobile PM25 caused by traffic emission with Respiratory and Cardiovascular Diseases in the study areaSubsequently a correlation between cardio-respiratory mortality is established

A significant correlation of PM1025 exposure from mobile emission and hospital admissions for selected Respiratory (RD) and cardiovascular (CVD) diagnoses isestablished The results showed that PM emissions in urban restricted access (freeways and interstates) is mainly caused by traffic Therefore people living close tohighways receive higher vehicular emissions

The table shows the percentage of PM mobile exposure in the analyzed areas contributing to increase the risk of Respiratory and Cardiovascular Diseases

An examination was conducted of the synoptic and local meteorology for the June 2006 ozone episode using the WRF model to determine how meteorological parametersinfluence the formation transport and dispersion of ozone in the PdN The predominant synoptic feature of the ozone event day was the expansion intensification and slowprogression of an upper-level ridge of high pressure The high ozone episodes are associated with highly stable atmospheres strong temperature inversions with low mixingheights and therefore low mixing volumes Under these conditions emissions such as NOx lead to highly polluted conditions that favor ozone formation

BenMAP Conclusions

We have estimated the number and economic value of health impacts resulting

from changes in air pollution concentrations of PM 25 in the PdN region

Reduction of Pm 25 4 UGm3= Avoided 213 cases respiratory cardiovascular

diseses and Economic Benefits associated with the Response of PM25 Emission + $

1295000

Increase of PM25 7 ugm3 = increasing Dies= 326 economic Unbenefits= 2345000$

Bibliography

1 Dockery DW Pope CAI Xu X Spengler JD Ware JH Fay ME Ferris BG Speizer FE An association between air pollution and mortality in six US cities N Engl J Med 3291753ndash1759 (1993)

2 Samet JM Dominici F Curriero FC Coursac I Zeger SL Fine particulate air pollution and mortality in 20 US cities 1987ndash1994 N Engl J Med 3431742ndash1749 (2000)

3 Nel AE Diaz-Sanchez D Li N The role of particulate pollutants in pulmonary inflammation and asthma evidence for the involvement of organic chemicals and oxidative stress Curr Opin Pulm Med 20017 20ndash26

4 Westerholm R Karl-Erik E Exhaust emissions from lightand heavy-duty vehicles chemical composition impact of exhaust after treatment and fuel parameters Environ Health Perspect 102(suppl 4)13ndash23 (1994)

5 Bascom R Bromberg P Costa D Delvin R Dockery D Frampton M Lambert W Samet J Speizer F Utell

6 Health effects of outdoor air pollution Am J Respir Crit Care Med 1533ndash50 (1996)

7 Chow JC Watson JG Frazier CA Egami RT Goodrich A Ralph C Spatial and temporal source contributions to

8 PM10 and PM25 in Reno NV In PM-10 Implementation of Standards Transactions An APCAEPA International Speciality Conference San Francisco CA (Mathal CV Stonefield DH eds) PittsburghAPCA 1988439ndash457

9 overview In Particulate Matter Health and Regulatory Issues VIP-49 Proceedings of an International Specialty Conference 4ndash6 April 1995 Pittsburgh PA PittsburghAir and Waste Management Association 1995577ndash598

10 Kunzli N Kaiser R Medina S Studnicka M Chanel O

11 Filliger P Herry M Horak F Jr Puybonnieux-Texier V Quenel P et al Public-health impact of outdoor and traffic- related air pollution a European assessment Lancet 356795ndash801 (2000)

Bibliography

1 Sioutas C Delfino RJ Singh M Exposure assessment for atmospheric ultrafine particles (UFP) and implications in epidemiological research Environ Health Perspect 2005113947ndash955

2 Mosleh M Blau PJ Dumitrescu D (2004) Characteristics and morphology of wear particles from laboratory testing of disc brake materials Wear 2561128ndash1134

3 Kuumlnzli N et al (2000) Public-health impact of outdoor and traffi c-related air pollution a European assessment Lancet 356(9232)795ndash801

4 Dora C Phillips M eds (2000) Transport environment and health Copenhagen WHO Regional Office for Europe (WHO Regional Publications European Series No 89 httpwwweurowhointdocumente72015pdf accessed 26 November 2004)

5 Westerholm R Karl-Erik E Exhaust emissions from lightand

6 heavy-duty vehicles chemical composition impact of exhaust after treatment and fuel parameters Environ Health Perspect 102(suppl 4)13ndash23 (1994)

7 Fauser Tjell Mosbaek pigegaard Quantification of tire-Tread particles using extractable Organic Zinc as a Tracer Rubber Chemistry and Technology 1999 969Table shows some literature estimates of the contribution of tire wear to PM10 in air (Panko et al 2013) Gustafsson M Blomqvist G Gudmundsson A Dahl A Swietlicki E Bohgard M Lindbom J Ljungman A

8 Chen Y Shah N Huggins FE and Huffman GP (2006) Microanalysis of Ambient Particles from Lexington Ky by Electron Microscopy Atmos Environ 40 651ndash663

9 Donaldson K Tran CL Jimenez LA Duffin R Newby DE and Mills N (2005) Combustion-derived Nanoparticles A Review of Their Toxicology Following Inhalation Exposure Part Fibre Toxicol 2 10ndash23

10 Su D Serafino A Muller JO Jentoft RE Schlogl R and Fiorito S (2008) Cytotoxicity and Inflammatory Potential of Soot Particles of Low-emission Diesel Engines Environ Sci Technol 42 1761ndash1765

11 Maier KL Alessandrini F Beck-Speier I Hofer TPJ Diabatґe S Bitterle E Stoger T and Jakob T (2008) Health Effects of Ambient Particulate Matter-Biological Mechanisms and Inflammatory Responses to in Vitroand in Vivo Particle Exposures Inhalation Toxicol 20 319ndash337

Page 35: Studies of Air Pollutants and their Impact on Respiratory and ...€¦ · Ascarate Park C37 Monitoring Station: The National Ambient Air Quality Standard (NAAQS) for PM 10 and 2.5

Monthly PM 10 25 Exhaust and Non-Exhaust (BrakewearTirewear) Mobile

Emission 2010 On-Road Urban Restricted Area Zip Code 79905

Figure Total Emissions from road traffic in El Paso TX Area were estimated for PM10 25 Exhaust and Non Exhaust mobile

emission in kilograms per month (Source EPA MOVES)

0

10000

20000

30000

40000

50000

January February March April May June July August September October November December

PM

10

25

(K

ilog

ram

s)

Months

Summary- Monthly PM 10 25 Exhaust and Non-Exhaust Mobile

Emission 2010 On-Road Urban Restricted Area Zip Code 79905

Primary Exhaust PM 10 Primary PM 10 Brakewear Primary PM 10 Tirewear

Primary Exhaust PM 25 Primary PM 25 Brakewear Primary PM 25Tirewear

Exhaust Emissions PM1025 is reaching maximum emission 48000-42000 thousand of Kgmonth followedby Brake wear 29000-5000 thousand kgmonth and Tire wear with 9000-2000 kgmonth The results showthat the emissions of PM derived mainly from Exhaust and Brake are significantly higher in Urban Area

Annual Contribution of Mobile Emission PM 1025 (Kg) Zip Code 79905 El

Paso County 2010

Total Primary

Exhaust _PM10

39

Total Primary

Exhaust _PM25

36

Brakewear

particulate_PM10

18

Tirewear

particulate_PM10

4

Brakewear

particulate_PM25

2

Tirewear

particulate_PM25

1

0

5

10

15

20

25

30

35

40

45

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53

Fig Annual Average PM10 Concentrations at the

Chamizal C41 Station and PM1025 mobile

Concentration Zip code 79905

PM10 TCEQ (μgm3) Total Mobile Emission PM10 (Ugm3)

Fig Exhaust Emission is Contributing Approximately 74 of total

PM1025 Mobile Emissions following of Brake wear with 20 and Tire

wear with 5

Annual Average PM1025 ugm3 Mobile Emissions (Moves) 26 Chamizal C41

Monitoring Station (TCEQ Chamizal Station )

Predicting Mobile Emission and VTM

Estimation The PdN Region 2010

44E+09

46E+09

48E+09

5E+09

52E+09

54E+09

56E+09

58E+09

6E+09

62E+09

0

50000

100000

150000

200000

250000

300000

350000

20

10

20

11

20

12

20

13

20

14

20

15

20

16

20

17

20

18

20

21

20

22

20

23

20

24

20

25

20

26

20

27

20

28

20

29

20

30

EX

HA

US

T

EM

ISS

ION

MO

BIL

E (

KG

YE

AR

)

YEARS

Predict ing Mobile Exhaust Emission and VTM

Estimation

2010 - 2030 e l PdN Area

Total_ Exhaust PM10 Total_ Exhaust PM25 Distance (Miles)

Fig Predicting Mobile Exhaust PM1025 (kgMonth) Emission and VTM Estimation 2010

- 2030 el PdN Area

44E+09

46E+09

48E+09

5E+09

52E+09

54E+09

56E+09

58E+09

6E+09

62E+09

0

5000000

10000000

15000000

20000000

25000000

30000000

20

10

20

11

20

12

20

13

20

14

20

15

20

16

20

17

20

18

20

21

20

22

20

23

20

24

20

25

20

26

20

27

20

28

20

29

20

30

EX

HA

US

T

EM

ISS

ION

MO

BIL

E (

KG

YE

AR

)

YEARS

Predict ing Mobile Exhaust Emission and

VTM Estimation

2010 - 2030 e l PdN Area

CO NO2 NO NOx Distance

Fig Predicting Mobile Exhaust Emission and VTM Estimation

2010 - 2030 el PdN Area in El Paso TX Area were estimated for

Total CO NOx NO2 NO emission in kilograms per year

(Source EPA MOVES 2014a model)

The simulated Exhaust emissions in the future years shows a trend of reduction of this type of emissions in the

future years one factor should be the new hybrid technology is increasing by 476 since 2010 to 2015 and

use of catalytic converters diesel particulate filters and improved fuels and engines Non-exhaustive sources

will increase in the coming years because there is no control in the material of manufacture composed by Fe

Cu and Mn also not to be able to reduce the number of events of braking (Accelerations and decelerations)

45E+09

5E+09

55E+09

6E+09

65E+09

0

50000

100000

150000

200000

250000

201

0

201

1

201

2

201

3

201

4

201

5

201

6

201

7

201

8

202

1

202

2

202

3

202

4

202

5

202

6

202

7

202

8

202

9

203

0

NO

N-

EX

HA

US

T

EM

ISS

ION

MO

BIL

E

(KG

YE

AR

)

YEARS

Predicting Non Exhaust Mobile

Emission and VTM Estimation

2010 - 2030 el PdN Area

Brake_PM10 Tire_PM10 Distance (Miles)

Fig Predicting Mobile Exhaust PM1025 (kgMonth) Emission and VTM

Estimation 2010 - 2030 el PdN Area

Daily Avg PM1025

Levels of PM Mobile Emission Non-Exhaust -Rush Hour Periods Fall 2010 Zip Code

79905

00

100

200

300

400

500

600

Mo

bil

e P

M1

0 (k

g)

Rush Hours

Daily Avg PM10

Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush Hours

Periods 2010 Zip Code 79905

Total Primary Exhaust

_PM10 WinterSpring

Brakewear

particulate_PM10

WinterSpringTirewear particulate_PM10

WinterSpring

Total Primary Exhaust

_PM10 Summer

Brakewear

particulate_PM10 Summer

Tirewear Particulate_PM10

Summer

Total Primary Exhaust

_PM10 Fall

Brakewear

particulate_PM10 Fall

Tirewear particulate_PM10

Fall

00

50

100

150

200

250

300

350

Mo

bil

e P

M2

5 (k

g)

Rush hours

Daily Avg PM25

Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush

Hours Periods 2010 Zip Code 79905

Total Primary Exhaust _PM25

WinterSpring

Brakewear Particulate_PM25

WinterSpring

Tirewear particulate_PM25

WinterSpring

Total Primary Exhaust _PM25

Summer

Brakewear particulate_PM25

Summer

Tirewear particulate_PM25

Summer

Total Primary Exhaust _PM25

Fall

Brakewear particulate_PM25

Fall

Tirewear particulate_PM25

Fall

Figure Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush Hours Figure Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush Hours

GIS EMISSIONS INVENTORY SYSTEM A geographic information system (GIS) was used to established geographic scenarios with processed images of seasonal mobile

emissions in the PdN region Seasonal mapping is visualized for different types of pollutants Brakewear Exhaust and Tyrewear

Fg Graphics of GIS and Seasonal mobile Emission of particulate matter emission inventory Seasonal emission simulations were performed in kilograms and five contributing inputs factors were identified for

modeling 1) On the composition of the particulate material from different sources such as Exhaust and Non exhaust (Brake wear Tirewear) 2) The Vehicles Equipment clasification were selected according to

the use of gasoline and diesel fuel (motorcycle passenger car Light Duty Vehicles Trucks refuse truck Light Duty Vehicles Light Commercial Truck Light Duty Vehicles School Bus)

Winter Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

120354 67860 19065

Spring Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

139767 86702 24463

Summer Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

94747 62481 17630

Fall Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

75510 45542 12596

251 Descriptive Statistics Data Analysis

Weekly Correlation Analysis of Mobile Emission PM10 (Exhaust-Non-Exhaust) and Respiratory

Diagnoses WinterSpring Summer and Fall 2010

0

2

4

6

8

10

0

50

100

150

200

250

300

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21

Mo

rbid

ity

Dis

ch

arg

e

for

all R

esp

ira

tory

Dis

ea

se

ICD

-9

(A

sth

ma

-Bro

nc

hitis

)

WinterSpring Week

Weekly Avg Mobile PM10 Concentrations during

WinterSpring 2010 and its Influence on Respiratory

Diagnoses

Zip Code 79905

Total Medical data ZIP Code 79902

Total Mobile Emission PM10 (Ugm3)

0

1

2

3

4

5

6

7

0

20

40

60

80

100

Mo

rbid

ity

Dis

ch

arg

e

for

all R

esp

ira

tory

Dis

ea

se

ICD

-9

(Ast

hm

aB

ron

ch

itis

)

Weekly Avg Mobile PM10 Concentrations during

Summer 2010 and its Influence on Respiratory

Diagnoses

Summer 2010 Zip Code 79905

Total Mobile Emission PM10

Hospital Admission (Asthma-Bronchitis)

0

2

4

6

8

10

12

0

20

40

60

80

100

120

140

160

180

200

Mo

rbid

ity

dis

ch

arg

es

for

all r

esp

ira

tory

dis

ea

se

Weekly Avg Mobile PM10 Concentrations

during Fall 2010 and its Influence on Respiratory

Diagnoses

Zip Code 79905

Total Medical data ZIP Code 79902

Total Mobile Emission PM10 (Ugm3)

Mobile(Exhaust-Non-

Exhaust) PM10 and

Asthma-Bronchitis)

Linear R

Square

WinterSpring 734 ndash 39

Summer 614 ndash 32

Fall 548 -29

PM10 Mobile emission (Exhaust-Non-Exhaust)contributed significantly

association to the incidence of RD

Weekly Correlation Analysis of PM 25 Mobile Emission (Exhaust-Non-Exhaust)

and Cardiovascular Diagnoses WinterSpring Summer and Fall 2010

0010203040

00500

100015002000

Wee

k 1

Wee

k 2

Wee

k 3

Wee

k 4

Wee

k 5

Wee

k 6

Wee

k 7

Wee

k 8

Wee

k 9

Wee

k 1

0

Wee

k 1

1

Wee

k 1

2

Wee

k 1

3

Wee

k 1

4

Wee

k 1

5

Wee

k 1

6

Wee

k 1

7

Wee

k 1

8

Wee

k 1

9

Wee

k 2

0

Wee

k 2

1

Morb

idit

y d

isch

arg

es f

or

all

card

iovasc

ula

r d

isea

se

Weekly Avg PM25 Mobile Concentrations during

WinterSpring 2010 and its Influence on all Heart

Diagnoses

Zip Code 79905

Total All Heart Disease PM 25 mobile (μgm3)

0010203040

00

500

1000

1500

Mo

rbid

ity

dis

ch

arg

es

for

all

ca

rdio

va

scu

lar

dis

ea

se

Weeks

CORRELATION BETWEEN MOBILE PM25 ugm3

EXPOSURE TO HEART DISEASES SYMPTOMS

SUMMER SEASON 2010

Total All Heart Disease PM 25 mobile (μgm3)

Figure Statistical Analyses of the Relationship Between PM25 Caused by Traffic Emission( 26 of total Emission) with Heart diseases Source Hospital Admissions for Asthma Acute Bronchitis and Heart diseases in El Paso County zip code 79905 from Texas Health Care

Information Council in Austin Texas (Texas Health Care Information Council 2000)

00

10

20

30

40

0

50

100

150

We

ek 3

6

We

ek 3

7

We

ek 3

8

We

ek 3

9

We

ek 4

0

We

ek 4

1

We

ek 4

2

We

ek 4

3

We

ek 4

4

We

ek 4

5

We

ek 4

6

We

ek 4

7

We

ek 4

8

We

ek 4

9

We

ek 5

0

We

ek 5

1

We

ek 5

2

We

ek 5

3

Mo

rbid

ity

dis

ch

arg

es

for

all

ca

rdio

va

scu

lar

dis

ea

se

CORRELATION BETWEEN MOBILE PM25 ugm3

EXPOSURE TO HEART DISEASES SYMPTOMS FALL

SEASON 2010

Total All Heart Disease PM 25 mobile (μgm3)

Mobile(Exhaust-

Non-Exhaust)

PM10 and

Asthma-

Bronchitis)

Linear R

Square

WinterSpring 833 -42

Summer 620 -32

Fall 501-26

PM10 Mobile

emission (Exhaust-

Non-

Exhaust)contribut

ed significantly

association to the

incidence of CVD

Diseases

Monthly Brake Mobile Emission PM1025 kg During year 2010 and its Influence on

Respiratory Diagnoses Zip Code 79905

00200040006000800010000

010000200003000040000

PM

10

Mo

bile

(K

g)

Months

Monthly Brake Mobile Emission PM10 kg during year

2010 and its Influence on Respiratory Diagnoses

Zip Code 79905

Primary PM 10

Brakewear 00100020003000400050006000

0

1000

2000

3000

4000

PM

25

Mo

bil

e(K

g)

Months

Monthly Brake Mobile Emission PM25 during

year 2010 and its Influence on Heart Diagnoses

Zip Code 79905

Primary PM 25

Brakewear

Heart Diseases

Hospital

Admission

Brake Mobile Emission

PM10 kg Asthma-

Bronchitis)

Brake Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=969 Linear Square R=856

Monthly Mobile Exhaust Emission PM1025 During year 2010 and its Influence on

Respiratory Diagnoses Zip Code 79905

0

200

400

600

800

1000

0

10000

20000

30000

40000

50000

1 3 5 7 9 11

PM

10

(K

g m

on

th)

Months

Monthly Mobile Exhaust Emission PM10 during

year 2010 and its Influence on Respiratory

Diagnoses

Zip Code 79905

Primary Exhaust

PM 10

Respiratory Disease

(Asthma

Bronchitis) Hospital

Admission

0

100

200

300

400

500

600

0

10000

20000

30000

40000

50000

1 2 3 4 5 6 7 8 9 101112

PM

25

(K

g m

on

th)

Months

Monthly Exhaust Mobile Emission PM25 during

year 2010 and its Influence on Heart Diagnoses

Zip Code 79905

Primary Exhaust PM

25

Heart Diseases

Hospital Admission

Exhaust Mobile Emission

PM10 kg Asthma-

Bronchitis)

Exhaust Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=929 Linear Square R=831

Monthly Tire wear Mobile Emission PM1025 During year 2010 and its Influence on Heart

Diagnoses Zip Code 79905

0

100

200

300

400

500

600

700

800

900

0

1000

2000

3000

4000

5000

6000

7000

8000

9000

1 2 3 4 5 6 7 8 9 10 11 12

PM

10

(K

g m

on

th)

Months

Monthly Tirewear Mobile Emission PM10 during year 2010

and its Influence on Heart Diagnoses

Zip Code 79905

Primary PM 10 Tirewear

Mobile Emission

Respiratory Disease

(Asthma Bronchitis)

Hospital Admission

0

100

200

300

400

500

600

0

200

400

600

800

1000

1200

1400

1 2 3 4 5 6 7 8 9 10 11 12

PM

25

(K

g m

on

th)

Months

Monthly Tirewear Mobile Emission PM25 during year 2010

and its Influence on Respiratory Diagnoses

Zip Code 79905

Primary PM 25Tirewear

Mobile Emission

Heart Diseases Hospital

Admission

Exhaust Mobile Emission

PM10 kg Asthma-

Bronchitis)

Exhaust Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=769 Linear Square R=715

Dona Ana County Zip Codes

88021880278807288048

Primary

Exhaust

PM 10 Zip

code

79905

Total

Primary

Exhaust

PM10

Dona Ana

Primary

Exhaust

PM 25 Zip

Code

79905

Total

Primary

Exhaust

PM25

Dona Ana

Series1 430378 111773 391915 102123

0

100000

200000

300000

400000

500000

AX

IS T

ITLE

Annual Comparison of the Mobile

Exhaust Emissions El Paso County

and Dona Ana 2010

Primary

PM 10

Brakewea

r Zip code

79905

Brakewea

r

particulat

e_PM10

Dona Ana

Primary

PM 10

Tirewear

Zip code

79905

Tirewear

particulat

e_PM10

Dona Ana

Series1 262585 48573 73754 11864

050000

100000150000200000250000300000

AX

IS T

ITLE

Annual Comparison of the Mobile

Brakewear Emissions El Paso County

and Dona Ana 2010

Figure Comparison of the Annual Mobile Emissions

of Primary PM10 Non-Exhauts (Brake ) from Dona

Ana County New Mexico and El Paso Texas Units

in KgMonth

Figure Comparison of the Annual Mobile Emissions

of Primary PM10-Exhauts Emission from Dona Ana

County New Mexico and El Paso Texas Units in

KgMonth

Primary

PM 25

Brakewe

ar Ziphellip

Brakewe

ar

particula

te_PMhellip

Primary

PM

25Tirewe

ar Ziphellip

Tirewear

particula

te_PM25

Donahellip

Series1 32645 6071 10919 1779

0

10000

20000

30000

40000

AX

IS T

ITLE

Annual Comparison of the

Mobile Exhaust Emissions El Paso

County and Dona Ana 2010

Figure Comparison of the Annual Mobile Emissions

of Primary PM10-Exhauts Emission from Dona Ana

County New Mexico and El Paso Texas Units in

KgMonth

Monthly Mobile Emission PM1025 kg During year 2006

and its Influence on Respiratory Diagnoses Dona Ana

County Zip Code 880218802788072

0

100

200

300

0

5000

10000

15000

Axi

s Ti

tle

Axis Title

Monthly Mobile Exhaust Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Total PrimaryMobile Exhaust_PM10

All Respiratory ICD-9 (AsthmaBronchitis)

050100150200250300

010002000300040005000

Axi

s Ti

tle

Axis Title

Monthly Mobile Brake Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Brakewearparticulate_PM10

All RespiratoryICD -9 (AsthmaBronchitis)

050100150200250300

0200400600800

10001200

Axi

s Ti

tle

Axis Title

Monthly Mobile Tirewear Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Tirewearparticulate_PM10

All Respiratory ICD -9 (AsthmaBronchitis)

Mobile Exhauts

Emission PM10

kg Asthma-

Bronchitis)

Brake Mobile

Emission PM10

kg and Heart

Diagnoses

Tirewear Mobile

Emission PM10

kg and Heart

Diagnoses

Linear Square

R= 951

Linear Square

R=625

Linear Square

R=525

Mobile Exhauts

Emission PM25

kg Asthma-

Bronchitis)

Brake Mobile

Emission PM25

kg and Heart

Diagnoses

Tirewear Mobile

Emission PM25

kg and Heart

Diagnoses

Linear Square

R= 986

Linear Square

R=691

Linear Square

R=601

Results

The results showed that mobile PM emissions in the urban areas close to urban Road and highways is putting at risk public health

and the proportion of diseases attributable to this exposure is potentially large

Brake wear emissions is much lower in freeways due to significantly reduced number of braking events while tire wear is much

higher in areas where studded tires are used The emission of exhaust gases are much higher in areas where there is a high

vehicular traffic

Brake Mobile

Emission PM10 kg

Asthma-Bronchitis)

Brake Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square

R=969

Linear Square

R=856

Exhaust Mobile

Emission PM10 kg

Asthma-Bronchitis)

Exhaust Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square

R=929

Linear Square

R=831

Tirewear Mobile

Emission PM10 kg

Asthma-Bronchitis)

Tirewear Mobile

Emission PM25 kg

and Heart Diagnoses

Linear Square R=769 Linear Square R=715

Brake Mobile

Emission PM10 kg

and Heart

Diagnoses

Brake Mobile

Emission PM25 kg

and Heart

Diagnoses

Exhaust Mobile

Emission PM10 kg

Asthma-Bronchitis)

Linear Square

R=625

Linear Square

R=691

Linear Square R=

951

Exhaust Mobile

Emission PM25 kg

Asthma-

Bronchitis)

Tire wear Mobile

Emission PM10 kg and

Heart Diagnoses

Tirewear Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square R=

986

Linear Square R=525 Linear Square

R=601

El Paso County

Dona Ana

County

BenMAP-CE

In this analysis the Program of Mapping and Analysis of Environmental Benefits-Community Edition

(BenMAP-CE) was used to Estimate the number and economic value of health impacts resulting from changes

in air pollution PM 25 Ugm3 in The El Paso Area

Health and Economic Benefits associated with the Response of PM25 Emission between

Base Year 2010

Number of Mortalities in 2010 Base Year Based on El Paso County Texas Department of State Health Services

Number of Mortalities in 2010 Base Year Based on El Paso County Texas

Department of State Health Services

cause of death

year

2010

Populatio

n

Affected

Backgro

und

Concentr

ation Pollutant

Rollback

Type

Avoided

Deaths

(

Populatio

n)

alzheimers disease 2010 40716 125 PM25

25

microgmAcircsup3

Rollback 9

diseases of the

heart 2010 15834 125 PM25

25

microgmAcircsup3

Rollback 35

influenza and

neumonia 2010 81432 125 PM25

25

microgmAcircsup3

Rollback 18

acute bronchitis

and bronchiolitis 2010 117624 125 PM25

25

microgmAcircsup3

Rollback 26

chronic lower

respiratory diseases 2010 54288 125 PM25

25

microgmAcircsup3

Rollback 12

The Basin-wide decrease in 4 ugm3 PM25 concentration after this

reduction control

Cause of death year 2010

Populatio

n

Affected

Background

Concentrati

on

Reduc

cion

scena

rio Polluta

nt

Rollback

Type

Avoi

ded

Deat

hs

(

Pop

ulati

on)

economic

benefits

analysis $

Alzheimers

disease 2010 121 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 9 12000

Diseases of the

heart 2010 470 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 35 35000

Influenza and

neumonia 2010 242 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 18 42500

Acute bronchitis

and bronchiolitis 2010 349 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 26 95000

Chronic lower

respiratory

diseases 2010 161 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 12 4500

$1 295000

PM25-related Mortalities Based on BenMAP-CE Estimate in 2010 Base Year with change in the concentrations levels

Health and Economic Benefits associated with the Response of PM25 Emission between

Base Year 2010 Increasing 7 Ugm3

Cause of death year 2010

Population

Affected

Deaths

avoided by

attaining 195

μgm3

standard

Background

Concentrati

on

Pollut

ant

Rollback

Type

Avoided

Deaths (

Populatio

n)

econo

mic

Unben

efits

analysi

s

Alzheimers

disease 2010 4524 195 PM25

25

microgmAcircsup3

Rollback 19 150000

Diseases of the

heart 2010 20358 195 PM25

25

microgmAcircsup3

Rollback 135 450000

Influenza and

neumonia 2010 126672 195 PM25

25

microgmAcircsup3

Rollback 38 525000

Acute bronchitis

and bronchiolitis 2010 162864 195 PM25

25

microgmAcircsup3

Rollback 36 122000

Chronic lower

respiratory

diseases 2010 99528 195 PM25

25

microgmAcircsup3

Rollback 12 650000

Conclusions

An excellent Pearson Correlation was established to analyze the relationship in the relative risks of hospitalization of Respiratory(RD) and cardiovascular (CVD) associated with ambient exposure caused by traffic emission in relation to their size andspecific sources of emission on different scenarios interior a border Urban Rural Urban restricted access (freeways andinterstates)

A significant correlation of PM1025 exposure from mobile emission and hospital admissions for selected Respiratory (RD) andcardiovascular (CVD) diagnoses was established The results showed that PM emissions in urban restricted access (freeways andinterstates) is mainly caused by traffic Therefore people living close to highways are more exposed higher vehicular emissions

Conclusions

We found statistically significant associations between mobile PM25 caused by traffic emission with Respiratory and Cardiovascular Diseases in the study areaSubsequently a correlation between cardio-respiratory mortality is established

A significant correlation of PM1025 exposure from mobile emission and hospital admissions for selected Respiratory (RD) and cardiovascular (CVD) diagnoses isestablished The results showed that PM emissions in urban restricted access (freeways and interstates) is mainly caused by traffic Therefore people living close tohighways receive higher vehicular emissions

The table shows the percentage of PM mobile exposure in the analyzed areas contributing to increase the risk of Respiratory and Cardiovascular Diseases

An examination was conducted of the synoptic and local meteorology for the June 2006 ozone episode using the WRF model to determine how meteorological parametersinfluence the formation transport and dispersion of ozone in the PdN The predominant synoptic feature of the ozone event day was the expansion intensification and slowprogression of an upper-level ridge of high pressure The high ozone episodes are associated with highly stable atmospheres strong temperature inversions with low mixingheights and therefore low mixing volumes Under these conditions emissions such as NOx lead to highly polluted conditions that favor ozone formation

BenMAP Conclusions

We have estimated the number and economic value of health impacts resulting

from changes in air pollution concentrations of PM 25 in the PdN region

Reduction of Pm 25 4 UGm3= Avoided 213 cases respiratory cardiovascular

diseses and Economic Benefits associated with the Response of PM25 Emission + $

1295000

Increase of PM25 7 ugm3 = increasing Dies= 326 economic Unbenefits= 2345000$

Bibliography

1 Dockery DW Pope CAI Xu X Spengler JD Ware JH Fay ME Ferris BG Speizer FE An association between air pollution and mortality in six US cities N Engl J Med 3291753ndash1759 (1993)

2 Samet JM Dominici F Curriero FC Coursac I Zeger SL Fine particulate air pollution and mortality in 20 US cities 1987ndash1994 N Engl J Med 3431742ndash1749 (2000)

3 Nel AE Diaz-Sanchez D Li N The role of particulate pollutants in pulmonary inflammation and asthma evidence for the involvement of organic chemicals and oxidative stress Curr Opin Pulm Med 20017 20ndash26

4 Westerholm R Karl-Erik E Exhaust emissions from lightand heavy-duty vehicles chemical composition impact of exhaust after treatment and fuel parameters Environ Health Perspect 102(suppl 4)13ndash23 (1994)

5 Bascom R Bromberg P Costa D Delvin R Dockery D Frampton M Lambert W Samet J Speizer F Utell

6 Health effects of outdoor air pollution Am J Respir Crit Care Med 1533ndash50 (1996)

7 Chow JC Watson JG Frazier CA Egami RT Goodrich A Ralph C Spatial and temporal source contributions to

8 PM10 and PM25 in Reno NV In PM-10 Implementation of Standards Transactions An APCAEPA International Speciality Conference San Francisco CA (Mathal CV Stonefield DH eds) PittsburghAPCA 1988439ndash457

9 overview In Particulate Matter Health and Regulatory Issues VIP-49 Proceedings of an International Specialty Conference 4ndash6 April 1995 Pittsburgh PA PittsburghAir and Waste Management Association 1995577ndash598

10 Kunzli N Kaiser R Medina S Studnicka M Chanel O

11 Filliger P Herry M Horak F Jr Puybonnieux-Texier V Quenel P et al Public-health impact of outdoor and traffic- related air pollution a European assessment Lancet 356795ndash801 (2000)

Bibliography

1 Sioutas C Delfino RJ Singh M Exposure assessment for atmospheric ultrafine particles (UFP) and implications in epidemiological research Environ Health Perspect 2005113947ndash955

2 Mosleh M Blau PJ Dumitrescu D (2004) Characteristics and morphology of wear particles from laboratory testing of disc brake materials Wear 2561128ndash1134

3 Kuumlnzli N et al (2000) Public-health impact of outdoor and traffi c-related air pollution a European assessment Lancet 356(9232)795ndash801

4 Dora C Phillips M eds (2000) Transport environment and health Copenhagen WHO Regional Office for Europe (WHO Regional Publications European Series No 89 httpwwweurowhointdocumente72015pdf accessed 26 November 2004)

5 Westerholm R Karl-Erik E Exhaust emissions from lightand

6 heavy-duty vehicles chemical composition impact of exhaust after treatment and fuel parameters Environ Health Perspect 102(suppl 4)13ndash23 (1994)

7 Fauser Tjell Mosbaek pigegaard Quantification of tire-Tread particles using extractable Organic Zinc as a Tracer Rubber Chemistry and Technology 1999 969Table shows some literature estimates of the contribution of tire wear to PM10 in air (Panko et al 2013) Gustafsson M Blomqvist G Gudmundsson A Dahl A Swietlicki E Bohgard M Lindbom J Ljungman A

8 Chen Y Shah N Huggins FE and Huffman GP (2006) Microanalysis of Ambient Particles from Lexington Ky by Electron Microscopy Atmos Environ 40 651ndash663

9 Donaldson K Tran CL Jimenez LA Duffin R Newby DE and Mills N (2005) Combustion-derived Nanoparticles A Review of Their Toxicology Following Inhalation Exposure Part Fibre Toxicol 2 10ndash23

10 Su D Serafino A Muller JO Jentoft RE Schlogl R and Fiorito S (2008) Cytotoxicity and Inflammatory Potential of Soot Particles of Low-emission Diesel Engines Environ Sci Technol 42 1761ndash1765

11 Maier KL Alessandrini F Beck-Speier I Hofer TPJ Diabatґe S Bitterle E Stoger T and Jakob T (2008) Health Effects of Ambient Particulate Matter-Biological Mechanisms and Inflammatory Responses to in Vitroand in Vivo Particle Exposures Inhalation Toxicol 20 319ndash337

Page 36: Studies of Air Pollutants and their Impact on Respiratory and ...€¦ · Ascarate Park C37 Monitoring Station: The National Ambient Air Quality Standard (NAAQS) for PM 10 and 2.5

Annual Contribution of Mobile Emission PM 1025 (Kg) Zip Code 79905 El

Paso County 2010

Total Primary

Exhaust _PM10

39

Total Primary

Exhaust _PM25

36

Brakewear

particulate_PM10

18

Tirewear

particulate_PM10

4

Brakewear

particulate_PM25

2

Tirewear

particulate_PM25

1

0

5

10

15

20

25

30

35

40

45

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53

Fig Annual Average PM10 Concentrations at the

Chamizal C41 Station and PM1025 mobile

Concentration Zip code 79905

PM10 TCEQ (μgm3) Total Mobile Emission PM10 (Ugm3)

Fig Exhaust Emission is Contributing Approximately 74 of total

PM1025 Mobile Emissions following of Brake wear with 20 and Tire

wear with 5

Annual Average PM1025 ugm3 Mobile Emissions (Moves) 26 Chamizal C41

Monitoring Station (TCEQ Chamizal Station )

Predicting Mobile Emission and VTM

Estimation The PdN Region 2010

44E+09

46E+09

48E+09

5E+09

52E+09

54E+09

56E+09

58E+09

6E+09

62E+09

0

50000

100000

150000

200000

250000

300000

350000

20

10

20

11

20

12

20

13

20

14

20

15

20

16

20

17

20

18

20

21

20

22

20

23

20

24

20

25

20

26

20

27

20

28

20

29

20

30

EX

HA

US

T

EM

ISS

ION

MO

BIL

E (

KG

YE

AR

)

YEARS

Predict ing Mobile Exhaust Emission and VTM

Estimation

2010 - 2030 e l PdN Area

Total_ Exhaust PM10 Total_ Exhaust PM25 Distance (Miles)

Fig Predicting Mobile Exhaust PM1025 (kgMonth) Emission and VTM Estimation 2010

- 2030 el PdN Area

44E+09

46E+09

48E+09

5E+09

52E+09

54E+09

56E+09

58E+09

6E+09

62E+09

0

5000000

10000000

15000000

20000000

25000000

30000000

20

10

20

11

20

12

20

13

20

14

20

15

20

16

20

17

20

18

20

21

20

22

20

23

20

24

20

25

20

26

20

27

20

28

20

29

20

30

EX

HA

US

T

EM

ISS

ION

MO

BIL

E (

KG

YE

AR

)

YEARS

Predict ing Mobile Exhaust Emission and

VTM Estimation

2010 - 2030 e l PdN Area

CO NO2 NO NOx Distance

Fig Predicting Mobile Exhaust Emission and VTM Estimation

2010 - 2030 el PdN Area in El Paso TX Area were estimated for

Total CO NOx NO2 NO emission in kilograms per year

(Source EPA MOVES 2014a model)

The simulated Exhaust emissions in the future years shows a trend of reduction of this type of emissions in the

future years one factor should be the new hybrid technology is increasing by 476 since 2010 to 2015 and

use of catalytic converters diesel particulate filters and improved fuels and engines Non-exhaustive sources

will increase in the coming years because there is no control in the material of manufacture composed by Fe

Cu and Mn also not to be able to reduce the number of events of braking (Accelerations and decelerations)

45E+09

5E+09

55E+09

6E+09

65E+09

0

50000

100000

150000

200000

250000

201

0

201

1

201

2

201

3

201

4

201

5

201

6

201

7

201

8

202

1

202

2

202

3

202

4

202

5

202

6

202

7

202

8

202

9

203

0

NO

N-

EX

HA

US

T

EM

ISS

ION

MO

BIL

E

(KG

YE

AR

)

YEARS

Predicting Non Exhaust Mobile

Emission and VTM Estimation

2010 - 2030 el PdN Area

Brake_PM10 Tire_PM10 Distance (Miles)

Fig Predicting Mobile Exhaust PM1025 (kgMonth) Emission and VTM

Estimation 2010 - 2030 el PdN Area

Daily Avg PM1025

Levels of PM Mobile Emission Non-Exhaust -Rush Hour Periods Fall 2010 Zip Code

79905

00

100

200

300

400

500

600

Mo

bil

e P

M1

0 (k

g)

Rush Hours

Daily Avg PM10

Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush Hours

Periods 2010 Zip Code 79905

Total Primary Exhaust

_PM10 WinterSpring

Brakewear

particulate_PM10

WinterSpringTirewear particulate_PM10

WinterSpring

Total Primary Exhaust

_PM10 Summer

Brakewear

particulate_PM10 Summer

Tirewear Particulate_PM10

Summer

Total Primary Exhaust

_PM10 Fall

Brakewear

particulate_PM10 Fall

Tirewear particulate_PM10

Fall

00

50

100

150

200

250

300

350

Mo

bil

e P

M2

5 (k

g)

Rush hours

Daily Avg PM25

Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush

Hours Periods 2010 Zip Code 79905

Total Primary Exhaust _PM25

WinterSpring

Brakewear Particulate_PM25

WinterSpring

Tirewear particulate_PM25

WinterSpring

Total Primary Exhaust _PM25

Summer

Brakewear particulate_PM25

Summer

Tirewear particulate_PM25

Summer

Total Primary Exhaust _PM25

Fall

Brakewear particulate_PM25

Fall

Tirewear particulate_PM25

Fall

Figure Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush Hours Figure Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush Hours

GIS EMISSIONS INVENTORY SYSTEM A geographic information system (GIS) was used to established geographic scenarios with processed images of seasonal mobile

emissions in the PdN region Seasonal mapping is visualized for different types of pollutants Brakewear Exhaust and Tyrewear

Fg Graphics of GIS and Seasonal mobile Emission of particulate matter emission inventory Seasonal emission simulations were performed in kilograms and five contributing inputs factors were identified for

modeling 1) On the composition of the particulate material from different sources such as Exhaust and Non exhaust (Brake wear Tirewear) 2) The Vehicles Equipment clasification were selected according to

the use of gasoline and diesel fuel (motorcycle passenger car Light Duty Vehicles Trucks refuse truck Light Duty Vehicles Light Commercial Truck Light Duty Vehicles School Bus)

Winter Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

120354 67860 19065

Spring Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

139767 86702 24463

Summer Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

94747 62481 17630

Fall Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

75510 45542 12596

251 Descriptive Statistics Data Analysis

Weekly Correlation Analysis of Mobile Emission PM10 (Exhaust-Non-Exhaust) and Respiratory

Diagnoses WinterSpring Summer and Fall 2010

0

2

4

6

8

10

0

50

100

150

200

250

300

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21

Mo

rbid

ity

Dis

ch

arg

e

for

all R

esp

ira

tory

Dis

ea

se

ICD

-9

(A

sth

ma

-Bro

nc

hitis

)

WinterSpring Week

Weekly Avg Mobile PM10 Concentrations during

WinterSpring 2010 and its Influence on Respiratory

Diagnoses

Zip Code 79905

Total Medical data ZIP Code 79902

Total Mobile Emission PM10 (Ugm3)

0

1

2

3

4

5

6

7

0

20

40

60

80

100

Mo

rbid

ity

Dis

ch

arg

e

for

all R

esp

ira

tory

Dis

ea

se

ICD

-9

(Ast

hm

aB

ron

ch

itis

)

Weekly Avg Mobile PM10 Concentrations during

Summer 2010 and its Influence on Respiratory

Diagnoses

Summer 2010 Zip Code 79905

Total Mobile Emission PM10

Hospital Admission (Asthma-Bronchitis)

0

2

4

6

8

10

12

0

20

40

60

80

100

120

140

160

180

200

Mo

rbid

ity

dis

ch

arg

es

for

all r

esp

ira

tory

dis

ea

se

Weekly Avg Mobile PM10 Concentrations

during Fall 2010 and its Influence on Respiratory

Diagnoses

Zip Code 79905

Total Medical data ZIP Code 79902

Total Mobile Emission PM10 (Ugm3)

Mobile(Exhaust-Non-

Exhaust) PM10 and

Asthma-Bronchitis)

Linear R

Square

WinterSpring 734 ndash 39

Summer 614 ndash 32

Fall 548 -29

PM10 Mobile emission (Exhaust-Non-Exhaust)contributed significantly

association to the incidence of RD

Weekly Correlation Analysis of PM 25 Mobile Emission (Exhaust-Non-Exhaust)

and Cardiovascular Diagnoses WinterSpring Summer and Fall 2010

0010203040

00500

100015002000

Wee

k 1

Wee

k 2

Wee

k 3

Wee

k 4

Wee

k 5

Wee

k 6

Wee

k 7

Wee

k 8

Wee

k 9

Wee

k 1

0

Wee

k 1

1

Wee

k 1

2

Wee

k 1

3

Wee

k 1

4

Wee

k 1

5

Wee

k 1

6

Wee

k 1

7

Wee

k 1

8

Wee

k 1

9

Wee

k 2

0

Wee

k 2

1

Morb

idit

y d

isch

arg

es f

or

all

card

iovasc

ula

r d

isea

se

Weekly Avg PM25 Mobile Concentrations during

WinterSpring 2010 and its Influence on all Heart

Diagnoses

Zip Code 79905

Total All Heart Disease PM 25 mobile (μgm3)

0010203040

00

500

1000

1500

Mo

rbid

ity

dis

ch

arg

es

for

all

ca

rdio

va

scu

lar

dis

ea

se

Weeks

CORRELATION BETWEEN MOBILE PM25 ugm3

EXPOSURE TO HEART DISEASES SYMPTOMS

SUMMER SEASON 2010

Total All Heart Disease PM 25 mobile (μgm3)

Figure Statistical Analyses of the Relationship Between PM25 Caused by Traffic Emission( 26 of total Emission) with Heart diseases Source Hospital Admissions for Asthma Acute Bronchitis and Heart diseases in El Paso County zip code 79905 from Texas Health Care

Information Council in Austin Texas (Texas Health Care Information Council 2000)

00

10

20

30

40

0

50

100

150

We

ek 3

6

We

ek 3

7

We

ek 3

8

We

ek 3

9

We

ek 4

0

We

ek 4

1

We

ek 4

2

We

ek 4

3

We

ek 4

4

We

ek 4

5

We

ek 4

6

We

ek 4

7

We

ek 4

8

We

ek 4

9

We

ek 5

0

We

ek 5

1

We

ek 5

2

We

ek 5

3

Mo

rbid

ity

dis

ch

arg

es

for

all

ca

rdio

va

scu

lar

dis

ea

se

CORRELATION BETWEEN MOBILE PM25 ugm3

EXPOSURE TO HEART DISEASES SYMPTOMS FALL

SEASON 2010

Total All Heart Disease PM 25 mobile (μgm3)

Mobile(Exhaust-

Non-Exhaust)

PM10 and

Asthma-

Bronchitis)

Linear R

Square

WinterSpring 833 -42

Summer 620 -32

Fall 501-26

PM10 Mobile

emission (Exhaust-

Non-

Exhaust)contribut

ed significantly

association to the

incidence of CVD

Diseases

Monthly Brake Mobile Emission PM1025 kg During year 2010 and its Influence on

Respiratory Diagnoses Zip Code 79905

00200040006000800010000

010000200003000040000

PM

10

Mo

bile

(K

g)

Months

Monthly Brake Mobile Emission PM10 kg during year

2010 and its Influence on Respiratory Diagnoses

Zip Code 79905

Primary PM 10

Brakewear 00100020003000400050006000

0

1000

2000

3000

4000

PM

25

Mo

bil

e(K

g)

Months

Monthly Brake Mobile Emission PM25 during

year 2010 and its Influence on Heart Diagnoses

Zip Code 79905

Primary PM 25

Brakewear

Heart Diseases

Hospital

Admission

Brake Mobile Emission

PM10 kg Asthma-

Bronchitis)

Brake Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=969 Linear Square R=856

Monthly Mobile Exhaust Emission PM1025 During year 2010 and its Influence on

Respiratory Diagnoses Zip Code 79905

0

200

400

600

800

1000

0

10000

20000

30000

40000

50000

1 3 5 7 9 11

PM

10

(K

g m

on

th)

Months

Monthly Mobile Exhaust Emission PM10 during

year 2010 and its Influence on Respiratory

Diagnoses

Zip Code 79905

Primary Exhaust

PM 10

Respiratory Disease

(Asthma

Bronchitis) Hospital

Admission

0

100

200

300

400

500

600

0

10000

20000

30000

40000

50000

1 2 3 4 5 6 7 8 9 101112

PM

25

(K

g m

on

th)

Months

Monthly Exhaust Mobile Emission PM25 during

year 2010 and its Influence on Heart Diagnoses

Zip Code 79905

Primary Exhaust PM

25

Heart Diseases

Hospital Admission

Exhaust Mobile Emission

PM10 kg Asthma-

Bronchitis)

Exhaust Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=929 Linear Square R=831

Monthly Tire wear Mobile Emission PM1025 During year 2010 and its Influence on Heart

Diagnoses Zip Code 79905

0

100

200

300

400

500

600

700

800

900

0

1000

2000

3000

4000

5000

6000

7000

8000

9000

1 2 3 4 5 6 7 8 9 10 11 12

PM

10

(K

g m

on

th)

Months

Monthly Tirewear Mobile Emission PM10 during year 2010

and its Influence on Heart Diagnoses

Zip Code 79905

Primary PM 10 Tirewear

Mobile Emission

Respiratory Disease

(Asthma Bronchitis)

Hospital Admission

0

100

200

300

400

500

600

0

200

400

600

800

1000

1200

1400

1 2 3 4 5 6 7 8 9 10 11 12

PM

25

(K

g m

on

th)

Months

Monthly Tirewear Mobile Emission PM25 during year 2010

and its Influence on Respiratory Diagnoses

Zip Code 79905

Primary PM 25Tirewear

Mobile Emission

Heart Diseases Hospital

Admission

Exhaust Mobile Emission

PM10 kg Asthma-

Bronchitis)

Exhaust Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=769 Linear Square R=715

Dona Ana County Zip Codes

88021880278807288048

Primary

Exhaust

PM 10 Zip

code

79905

Total

Primary

Exhaust

PM10

Dona Ana

Primary

Exhaust

PM 25 Zip

Code

79905

Total

Primary

Exhaust

PM25

Dona Ana

Series1 430378 111773 391915 102123

0

100000

200000

300000

400000

500000

AX

IS T

ITLE

Annual Comparison of the Mobile

Exhaust Emissions El Paso County

and Dona Ana 2010

Primary

PM 10

Brakewea

r Zip code

79905

Brakewea

r

particulat

e_PM10

Dona Ana

Primary

PM 10

Tirewear

Zip code

79905

Tirewear

particulat

e_PM10

Dona Ana

Series1 262585 48573 73754 11864

050000

100000150000200000250000300000

AX

IS T

ITLE

Annual Comparison of the Mobile

Brakewear Emissions El Paso County

and Dona Ana 2010

Figure Comparison of the Annual Mobile Emissions

of Primary PM10 Non-Exhauts (Brake ) from Dona

Ana County New Mexico and El Paso Texas Units

in KgMonth

Figure Comparison of the Annual Mobile Emissions

of Primary PM10-Exhauts Emission from Dona Ana

County New Mexico and El Paso Texas Units in

KgMonth

Primary

PM 25

Brakewe

ar Ziphellip

Brakewe

ar

particula

te_PMhellip

Primary

PM

25Tirewe

ar Ziphellip

Tirewear

particula

te_PM25

Donahellip

Series1 32645 6071 10919 1779

0

10000

20000

30000

40000

AX

IS T

ITLE

Annual Comparison of the

Mobile Exhaust Emissions El Paso

County and Dona Ana 2010

Figure Comparison of the Annual Mobile Emissions

of Primary PM10-Exhauts Emission from Dona Ana

County New Mexico and El Paso Texas Units in

KgMonth

Monthly Mobile Emission PM1025 kg During year 2006

and its Influence on Respiratory Diagnoses Dona Ana

County Zip Code 880218802788072

0

100

200

300

0

5000

10000

15000

Axi

s Ti

tle

Axis Title

Monthly Mobile Exhaust Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Total PrimaryMobile Exhaust_PM10

All Respiratory ICD-9 (AsthmaBronchitis)

050100150200250300

010002000300040005000

Axi

s Ti

tle

Axis Title

Monthly Mobile Brake Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Brakewearparticulate_PM10

All RespiratoryICD -9 (AsthmaBronchitis)

050100150200250300

0200400600800

10001200

Axi

s Ti

tle

Axis Title

Monthly Mobile Tirewear Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Tirewearparticulate_PM10

All Respiratory ICD -9 (AsthmaBronchitis)

Mobile Exhauts

Emission PM10

kg Asthma-

Bronchitis)

Brake Mobile

Emission PM10

kg and Heart

Diagnoses

Tirewear Mobile

Emission PM10

kg and Heart

Diagnoses

Linear Square

R= 951

Linear Square

R=625

Linear Square

R=525

Mobile Exhauts

Emission PM25

kg Asthma-

Bronchitis)

Brake Mobile

Emission PM25

kg and Heart

Diagnoses

Tirewear Mobile

Emission PM25

kg and Heart

Diagnoses

Linear Square

R= 986

Linear Square

R=691

Linear Square

R=601

Results

The results showed that mobile PM emissions in the urban areas close to urban Road and highways is putting at risk public health

and the proportion of diseases attributable to this exposure is potentially large

Brake wear emissions is much lower in freeways due to significantly reduced number of braking events while tire wear is much

higher in areas where studded tires are used The emission of exhaust gases are much higher in areas where there is a high

vehicular traffic

Brake Mobile

Emission PM10 kg

Asthma-Bronchitis)

Brake Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square

R=969

Linear Square

R=856

Exhaust Mobile

Emission PM10 kg

Asthma-Bronchitis)

Exhaust Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square

R=929

Linear Square

R=831

Tirewear Mobile

Emission PM10 kg

Asthma-Bronchitis)

Tirewear Mobile

Emission PM25 kg

and Heart Diagnoses

Linear Square R=769 Linear Square R=715

Brake Mobile

Emission PM10 kg

and Heart

Diagnoses

Brake Mobile

Emission PM25 kg

and Heart

Diagnoses

Exhaust Mobile

Emission PM10 kg

Asthma-Bronchitis)

Linear Square

R=625

Linear Square

R=691

Linear Square R=

951

Exhaust Mobile

Emission PM25 kg

Asthma-

Bronchitis)

Tire wear Mobile

Emission PM10 kg and

Heart Diagnoses

Tirewear Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square R=

986

Linear Square R=525 Linear Square

R=601

El Paso County

Dona Ana

County

BenMAP-CE

In this analysis the Program of Mapping and Analysis of Environmental Benefits-Community Edition

(BenMAP-CE) was used to Estimate the number and economic value of health impacts resulting from changes

in air pollution PM 25 Ugm3 in The El Paso Area

Health and Economic Benefits associated with the Response of PM25 Emission between

Base Year 2010

Number of Mortalities in 2010 Base Year Based on El Paso County Texas Department of State Health Services

Number of Mortalities in 2010 Base Year Based on El Paso County Texas

Department of State Health Services

cause of death

year

2010

Populatio

n

Affected

Backgro

und

Concentr

ation Pollutant

Rollback

Type

Avoided

Deaths

(

Populatio

n)

alzheimers disease 2010 40716 125 PM25

25

microgmAcircsup3

Rollback 9

diseases of the

heart 2010 15834 125 PM25

25

microgmAcircsup3

Rollback 35

influenza and

neumonia 2010 81432 125 PM25

25

microgmAcircsup3

Rollback 18

acute bronchitis

and bronchiolitis 2010 117624 125 PM25

25

microgmAcircsup3

Rollback 26

chronic lower

respiratory diseases 2010 54288 125 PM25

25

microgmAcircsup3

Rollback 12

The Basin-wide decrease in 4 ugm3 PM25 concentration after this

reduction control

Cause of death year 2010

Populatio

n

Affected

Background

Concentrati

on

Reduc

cion

scena

rio Polluta

nt

Rollback

Type

Avoi

ded

Deat

hs

(

Pop

ulati

on)

economic

benefits

analysis $

Alzheimers

disease 2010 121 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 9 12000

Diseases of the

heart 2010 470 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 35 35000

Influenza and

neumonia 2010 242 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 18 42500

Acute bronchitis

and bronchiolitis 2010 349 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 26 95000

Chronic lower

respiratory

diseases 2010 161 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 12 4500

$1 295000

PM25-related Mortalities Based on BenMAP-CE Estimate in 2010 Base Year with change in the concentrations levels

Health and Economic Benefits associated with the Response of PM25 Emission between

Base Year 2010 Increasing 7 Ugm3

Cause of death year 2010

Population

Affected

Deaths

avoided by

attaining 195

μgm3

standard

Background

Concentrati

on

Pollut

ant

Rollback

Type

Avoided

Deaths (

Populatio

n)

econo

mic

Unben

efits

analysi

s

Alzheimers

disease 2010 4524 195 PM25

25

microgmAcircsup3

Rollback 19 150000

Diseases of the

heart 2010 20358 195 PM25

25

microgmAcircsup3

Rollback 135 450000

Influenza and

neumonia 2010 126672 195 PM25

25

microgmAcircsup3

Rollback 38 525000

Acute bronchitis

and bronchiolitis 2010 162864 195 PM25

25

microgmAcircsup3

Rollback 36 122000

Chronic lower

respiratory

diseases 2010 99528 195 PM25

25

microgmAcircsup3

Rollback 12 650000

Conclusions

An excellent Pearson Correlation was established to analyze the relationship in the relative risks of hospitalization of Respiratory(RD) and cardiovascular (CVD) associated with ambient exposure caused by traffic emission in relation to their size andspecific sources of emission on different scenarios interior a border Urban Rural Urban restricted access (freeways andinterstates)

A significant correlation of PM1025 exposure from mobile emission and hospital admissions for selected Respiratory (RD) andcardiovascular (CVD) diagnoses was established The results showed that PM emissions in urban restricted access (freeways andinterstates) is mainly caused by traffic Therefore people living close to highways are more exposed higher vehicular emissions

Conclusions

We found statistically significant associations between mobile PM25 caused by traffic emission with Respiratory and Cardiovascular Diseases in the study areaSubsequently a correlation between cardio-respiratory mortality is established

A significant correlation of PM1025 exposure from mobile emission and hospital admissions for selected Respiratory (RD) and cardiovascular (CVD) diagnoses isestablished The results showed that PM emissions in urban restricted access (freeways and interstates) is mainly caused by traffic Therefore people living close tohighways receive higher vehicular emissions

The table shows the percentage of PM mobile exposure in the analyzed areas contributing to increase the risk of Respiratory and Cardiovascular Diseases

An examination was conducted of the synoptic and local meteorology for the June 2006 ozone episode using the WRF model to determine how meteorological parametersinfluence the formation transport and dispersion of ozone in the PdN The predominant synoptic feature of the ozone event day was the expansion intensification and slowprogression of an upper-level ridge of high pressure The high ozone episodes are associated with highly stable atmospheres strong temperature inversions with low mixingheights and therefore low mixing volumes Under these conditions emissions such as NOx lead to highly polluted conditions that favor ozone formation

BenMAP Conclusions

We have estimated the number and economic value of health impacts resulting

from changes in air pollution concentrations of PM 25 in the PdN region

Reduction of Pm 25 4 UGm3= Avoided 213 cases respiratory cardiovascular

diseses and Economic Benefits associated with the Response of PM25 Emission + $

1295000

Increase of PM25 7 ugm3 = increasing Dies= 326 economic Unbenefits= 2345000$

Bibliography

1 Dockery DW Pope CAI Xu X Spengler JD Ware JH Fay ME Ferris BG Speizer FE An association between air pollution and mortality in six US cities N Engl J Med 3291753ndash1759 (1993)

2 Samet JM Dominici F Curriero FC Coursac I Zeger SL Fine particulate air pollution and mortality in 20 US cities 1987ndash1994 N Engl J Med 3431742ndash1749 (2000)

3 Nel AE Diaz-Sanchez D Li N The role of particulate pollutants in pulmonary inflammation and asthma evidence for the involvement of organic chemicals and oxidative stress Curr Opin Pulm Med 20017 20ndash26

4 Westerholm R Karl-Erik E Exhaust emissions from lightand heavy-duty vehicles chemical composition impact of exhaust after treatment and fuel parameters Environ Health Perspect 102(suppl 4)13ndash23 (1994)

5 Bascom R Bromberg P Costa D Delvin R Dockery D Frampton M Lambert W Samet J Speizer F Utell

6 Health effects of outdoor air pollution Am J Respir Crit Care Med 1533ndash50 (1996)

7 Chow JC Watson JG Frazier CA Egami RT Goodrich A Ralph C Spatial and temporal source contributions to

8 PM10 and PM25 in Reno NV In PM-10 Implementation of Standards Transactions An APCAEPA International Speciality Conference San Francisco CA (Mathal CV Stonefield DH eds) PittsburghAPCA 1988439ndash457

9 overview In Particulate Matter Health and Regulatory Issues VIP-49 Proceedings of an International Specialty Conference 4ndash6 April 1995 Pittsburgh PA PittsburghAir and Waste Management Association 1995577ndash598

10 Kunzli N Kaiser R Medina S Studnicka M Chanel O

11 Filliger P Herry M Horak F Jr Puybonnieux-Texier V Quenel P et al Public-health impact of outdoor and traffic- related air pollution a European assessment Lancet 356795ndash801 (2000)

Bibliography

1 Sioutas C Delfino RJ Singh M Exposure assessment for atmospheric ultrafine particles (UFP) and implications in epidemiological research Environ Health Perspect 2005113947ndash955

2 Mosleh M Blau PJ Dumitrescu D (2004) Characteristics and morphology of wear particles from laboratory testing of disc brake materials Wear 2561128ndash1134

3 Kuumlnzli N et al (2000) Public-health impact of outdoor and traffi c-related air pollution a European assessment Lancet 356(9232)795ndash801

4 Dora C Phillips M eds (2000) Transport environment and health Copenhagen WHO Regional Office for Europe (WHO Regional Publications European Series No 89 httpwwweurowhointdocumente72015pdf accessed 26 November 2004)

5 Westerholm R Karl-Erik E Exhaust emissions from lightand

6 heavy-duty vehicles chemical composition impact of exhaust after treatment and fuel parameters Environ Health Perspect 102(suppl 4)13ndash23 (1994)

7 Fauser Tjell Mosbaek pigegaard Quantification of tire-Tread particles using extractable Organic Zinc as a Tracer Rubber Chemistry and Technology 1999 969Table shows some literature estimates of the contribution of tire wear to PM10 in air (Panko et al 2013) Gustafsson M Blomqvist G Gudmundsson A Dahl A Swietlicki E Bohgard M Lindbom J Ljungman A

8 Chen Y Shah N Huggins FE and Huffman GP (2006) Microanalysis of Ambient Particles from Lexington Ky by Electron Microscopy Atmos Environ 40 651ndash663

9 Donaldson K Tran CL Jimenez LA Duffin R Newby DE and Mills N (2005) Combustion-derived Nanoparticles A Review of Their Toxicology Following Inhalation Exposure Part Fibre Toxicol 2 10ndash23

10 Su D Serafino A Muller JO Jentoft RE Schlogl R and Fiorito S (2008) Cytotoxicity and Inflammatory Potential of Soot Particles of Low-emission Diesel Engines Environ Sci Technol 42 1761ndash1765

11 Maier KL Alessandrini F Beck-Speier I Hofer TPJ Diabatґe S Bitterle E Stoger T and Jakob T (2008) Health Effects of Ambient Particulate Matter-Biological Mechanisms and Inflammatory Responses to in Vitroand in Vivo Particle Exposures Inhalation Toxicol 20 319ndash337

Page 37: Studies of Air Pollutants and their Impact on Respiratory and ...€¦ · Ascarate Park C37 Monitoring Station: The National Ambient Air Quality Standard (NAAQS) for PM 10 and 2.5

Predicting Mobile Emission and VTM

Estimation The PdN Region 2010

44E+09

46E+09

48E+09

5E+09

52E+09

54E+09

56E+09

58E+09

6E+09

62E+09

0

50000

100000

150000

200000

250000

300000

350000

20

10

20

11

20

12

20

13

20

14

20

15

20

16

20

17

20

18

20

21

20

22

20

23

20

24

20

25

20

26

20

27

20

28

20

29

20

30

EX

HA

US

T

EM

ISS

ION

MO

BIL

E (

KG

YE

AR

)

YEARS

Predict ing Mobile Exhaust Emission and VTM

Estimation

2010 - 2030 e l PdN Area

Total_ Exhaust PM10 Total_ Exhaust PM25 Distance (Miles)

Fig Predicting Mobile Exhaust PM1025 (kgMonth) Emission and VTM Estimation 2010

- 2030 el PdN Area

44E+09

46E+09

48E+09

5E+09

52E+09

54E+09

56E+09

58E+09

6E+09

62E+09

0

5000000

10000000

15000000

20000000

25000000

30000000

20

10

20

11

20

12

20

13

20

14

20

15

20

16

20

17

20

18

20

21

20

22

20

23

20

24

20

25

20

26

20

27

20

28

20

29

20

30

EX

HA

US

T

EM

ISS

ION

MO

BIL

E (

KG

YE

AR

)

YEARS

Predict ing Mobile Exhaust Emission and

VTM Estimation

2010 - 2030 e l PdN Area

CO NO2 NO NOx Distance

Fig Predicting Mobile Exhaust Emission and VTM Estimation

2010 - 2030 el PdN Area in El Paso TX Area were estimated for

Total CO NOx NO2 NO emission in kilograms per year

(Source EPA MOVES 2014a model)

The simulated Exhaust emissions in the future years shows a trend of reduction of this type of emissions in the

future years one factor should be the new hybrid technology is increasing by 476 since 2010 to 2015 and

use of catalytic converters diesel particulate filters and improved fuels and engines Non-exhaustive sources

will increase in the coming years because there is no control in the material of manufacture composed by Fe

Cu and Mn also not to be able to reduce the number of events of braking (Accelerations and decelerations)

45E+09

5E+09

55E+09

6E+09

65E+09

0

50000

100000

150000

200000

250000

201

0

201

1

201

2

201

3

201

4

201

5

201

6

201

7

201

8

202

1

202

2

202

3

202

4

202

5

202

6

202

7

202

8

202

9

203

0

NO

N-

EX

HA

US

T

EM

ISS

ION

MO

BIL

E

(KG

YE

AR

)

YEARS

Predicting Non Exhaust Mobile

Emission and VTM Estimation

2010 - 2030 el PdN Area

Brake_PM10 Tire_PM10 Distance (Miles)

Fig Predicting Mobile Exhaust PM1025 (kgMonth) Emission and VTM

Estimation 2010 - 2030 el PdN Area

Daily Avg PM1025

Levels of PM Mobile Emission Non-Exhaust -Rush Hour Periods Fall 2010 Zip Code

79905

00

100

200

300

400

500

600

Mo

bil

e P

M1

0 (k

g)

Rush Hours

Daily Avg PM10

Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush Hours

Periods 2010 Zip Code 79905

Total Primary Exhaust

_PM10 WinterSpring

Brakewear

particulate_PM10

WinterSpringTirewear particulate_PM10

WinterSpring

Total Primary Exhaust

_PM10 Summer

Brakewear

particulate_PM10 Summer

Tirewear Particulate_PM10

Summer

Total Primary Exhaust

_PM10 Fall

Brakewear

particulate_PM10 Fall

Tirewear particulate_PM10

Fall

00

50

100

150

200

250

300

350

Mo

bil

e P

M2

5 (k

g)

Rush hours

Daily Avg PM25

Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush

Hours Periods 2010 Zip Code 79905

Total Primary Exhaust _PM25

WinterSpring

Brakewear Particulate_PM25

WinterSpring

Tirewear particulate_PM25

WinterSpring

Total Primary Exhaust _PM25

Summer

Brakewear particulate_PM25

Summer

Tirewear particulate_PM25

Summer

Total Primary Exhaust _PM25

Fall

Brakewear particulate_PM25

Fall

Tirewear particulate_PM25

Fall

Figure Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush Hours Figure Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush Hours

GIS EMISSIONS INVENTORY SYSTEM A geographic information system (GIS) was used to established geographic scenarios with processed images of seasonal mobile

emissions in the PdN region Seasonal mapping is visualized for different types of pollutants Brakewear Exhaust and Tyrewear

Fg Graphics of GIS and Seasonal mobile Emission of particulate matter emission inventory Seasonal emission simulations were performed in kilograms and five contributing inputs factors were identified for

modeling 1) On the composition of the particulate material from different sources such as Exhaust and Non exhaust (Brake wear Tirewear) 2) The Vehicles Equipment clasification were selected according to

the use of gasoline and diesel fuel (motorcycle passenger car Light Duty Vehicles Trucks refuse truck Light Duty Vehicles Light Commercial Truck Light Duty Vehicles School Bus)

Winter Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

120354 67860 19065

Spring Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

139767 86702 24463

Summer Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

94747 62481 17630

Fall Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

75510 45542 12596

251 Descriptive Statistics Data Analysis

Weekly Correlation Analysis of Mobile Emission PM10 (Exhaust-Non-Exhaust) and Respiratory

Diagnoses WinterSpring Summer and Fall 2010

0

2

4

6

8

10

0

50

100

150

200

250

300

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21

Mo

rbid

ity

Dis

ch

arg

e

for

all R

esp

ira

tory

Dis

ea

se

ICD

-9

(A

sth

ma

-Bro

nc

hitis

)

WinterSpring Week

Weekly Avg Mobile PM10 Concentrations during

WinterSpring 2010 and its Influence on Respiratory

Diagnoses

Zip Code 79905

Total Medical data ZIP Code 79902

Total Mobile Emission PM10 (Ugm3)

0

1

2

3

4

5

6

7

0

20

40

60

80

100

Mo

rbid

ity

Dis

ch

arg

e

for

all R

esp

ira

tory

Dis

ea

se

ICD

-9

(Ast

hm

aB

ron

ch

itis

)

Weekly Avg Mobile PM10 Concentrations during

Summer 2010 and its Influence on Respiratory

Diagnoses

Summer 2010 Zip Code 79905

Total Mobile Emission PM10

Hospital Admission (Asthma-Bronchitis)

0

2

4

6

8

10

12

0

20

40

60

80

100

120

140

160

180

200

Mo

rbid

ity

dis

ch

arg

es

for

all r

esp

ira

tory

dis

ea

se

Weekly Avg Mobile PM10 Concentrations

during Fall 2010 and its Influence on Respiratory

Diagnoses

Zip Code 79905

Total Medical data ZIP Code 79902

Total Mobile Emission PM10 (Ugm3)

Mobile(Exhaust-Non-

Exhaust) PM10 and

Asthma-Bronchitis)

Linear R

Square

WinterSpring 734 ndash 39

Summer 614 ndash 32

Fall 548 -29

PM10 Mobile emission (Exhaust-Non-Exhaust)contributed significantly

association to the incidence of RD

Weekly Correlation Analysis of PM 25 Mobile Emission (Exhaust-Non-Exhaust)

and Cardiovascular Diagnoses WinterSpring Summer and Fall 2010

0010203040

00500

100015002000

Wee

k 1

Wee

k 2

Wee

k 3

Wee

k 4

Wee

k 5

Wee

k 6

Wee

k 7

Wee

k 8

Wee

k 9

Wee

k 1

0

Wee

k 1

1

Wee

k 1

2

Wee

k 1

3

Wee

k 1

4

Wee

k 1

5

Wee

k 1

6

Wee

k 1

7

Wee

k 1

8

Wee

k 1

9

Wee

k 2

0

Wee

k 2

1

Morb

idit

y d

isch

arg

es f

or

all

card

iovasc

ula

r d

isea

se

Weekly Avg PM25 Mobile Concentrations during

WinterSpring 2010 and its Influence on all Heart

Diagnoses

Zip Code 79905

Total All Heart Disease PM 25 mobile (μgm3)

0010203040

00

500

1000

1500

Mo

rbid

ity

dis

ch

arg

es

for

all

ca

rdio

va

scu

lar

dis

ea

se

Weeks

CORRELATION BETWEEN MOBILE PM25 ugm3

EXPOSURE TO HEART DISEASES SYMPTOMS

SUMMER SEASON 2010

Total All Heart Disease PM 25 mobile (μgm3)

Figure Statistical Analyses of the Relationship Between PM25 Caused by Traffic Emission( 26 of total Emission) with Heart diseases Source Hospital Admissions for Asthma Acute Bronchitis and Heart diseases in El Paso County zip code 79905 from Texas Health Care

Information Council in Austin Texas (Texas Health Care Information Council 2000)

00

10

20

30

40

0

50

100

150

We

ek 3

6

We

ek 3

7

We

ek 3

8

We

ek 3

9

We

ek 4

0

We

ek 4

1

We

ek 4

2

We

ek 4

3

We

ek 4

4

We

ek 4

5

We

ek 4

6

We

ek 4

7

We

ek 4

8

We

ek 4

9

We

ek 5

0

We

ek 5

1

We

ek 5

2

We

ek 5

3

Mo

rbid

ity

dis

ch

arg

es

for

all

ca

rdio

va

scu

lar

dis

ea

se

CORRELATION BETWEEN MOBILE PM25 ugm3

EXPOSURE TO HEART DISEASES SYMPTOMS FALL

SEASON 2010

Total All Heart Disease PM 25 mobile (μgm3)

Mobile(Exhaust-

Non-Exhaust)

PM10 and

Asthma-

Bronchitis)

Linear R

Square

WinterSpring 833 -42

Summer 620 -32

Fall 501-26

PM10 Mobile

emission (Exhaust-

Non-

Exhaust)contribut

ed significantly

association to the

incidence of CVD

Diseases

Monthly Brake Mobile Emission PM1025 kg During year 2010 and its Influence on

Respiratory Diagnoses Zip Code 79905

00200040006000800010000

010000200003000040000

PM

10

Mo

bile

(K

g)

Months

Monthly Brake Mobile Emission PM10 kg during year

2010 and its Influence on Respiratory Diagnoses

Zip Code 79905

Primary PM 10

Brakewear 00100020003000400050006000

0

1000

2000

3000

4000

PM

25

Mo

bil

e(K

g)

Months

Monthly Brake Mobile Emission PM25 during

year 2010 and its Influence on Heart Diagnoses

Zip Code 79905

Primary PM 25

Brakewear

Heart Diseases

Hospital

Admission

Brake Mobile Emission

PM10 kg Asthma-

Bronchitis)

Brake Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=969 Linear Square R=856

Monthly Mobile Exhaust Emission PM1025 During year 2010 and its Influence on

Respiratory Diagnoses Zip Code 79905

0

200

400

600

800

1000

0

10000

20000

30000

40000

50000

1 3 5 7 9 11

PM

10

(K

g m

on

th)

Months

Monthly Mobile Exhaust Emission PM10 during

year 2010 and its Influence on Respiratory

Diagnoses

Zip Code 79905

Primary Exhaust

PM 10

Respiratory Disease

(Asthma

Bronchitis) Hospital

Admission

0

100

200

300

400

500

600

0

10000

20000

30000

40000

50000

1 2 3 4 5 6 7 8 9 101112

PM

25

(K

g m

on

th)

Months

Monthly Exhaust Mobile Emission PM25 during

year 2010 and its Influence on Heart Diagnoses

Zip Code 79905

Primary Exhaust PM

25

Heart Diseases

Hospital Admission

Exhaust Mobile Emission

PM10 kg Asthma-

Bronchitis)

Exhaust Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=929 Linear Square R=831

Monthly Tire wear Mobile Emission PM1025 During year 2010 and its Influence on Heart

Diagnoses Zip Code 79905

0

100

200

300

400

500

600

700

800

900

0

1000

2000

3000

4000

5000

6000

7000

8000

9000

1 2 3 4 5 6 7 8 9 10 11 12

PM

10

(K

g m

on

th)

Months

Monthly Tirewear Mobile Emission PM10 during year 2010

and its Influence on Heart Diagnoses

Zip Code 79905

Primary PM 10 Tirewear

Mobile Emission

Respiratory Disease

(Asthma Bronchitis)

Hospital Admission

0

100

200

300

400

500

600

0

200

400

600

800

1000

1200

1400

1 2 3 4 5 6 7 8 9 10 11 12

PM

25

(K

g m

on

th)

Months

Monthly Tirewear Mobile Emission PM25 during year 2010

and its Influence on Respiratory Diagnoses

Zip Code 79905

Primary PM 25Tirewear

Mobile Emission

Heart Diseases Hospital

Admission

Exhaust Mobile Emission

PM10 kg Asthma-

Bronchitis)

Exhaust Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=769 Linear Square R=715

Dona Ana County Zip Codes

88021880278807288048

Primary

Exhaust

PM 10 Zip

code

79905

Total

Primary

Exhaust

PM10

Dona Ana

Primary

Exhaust

PM 25 Zip

Code

79905

Total

Primary

Exhaust

PM25

Dona Ana

Series1 430378 111773 391915 102123

0

100000

200000

300000

400000

500000

AX

IS T

ITLE

Annual Comparison of the Mobile

Exhaust Emissions El Paso County

and Dona Ana 2010

Primary

PM 10

Brakewea

r Zip code

79905

Brakewea

r

particulat

e_PM10

Dona Ana

Primary

PM 10

Tirewear

Zip code

79905

Tirewear

particulat

e_PM10

Dona Ana

Series1 262585 48573 73754 11864

050000

100000150000200000250000300000

AX

IS T

ITLE

Annual Comparison of the Mobile

Brakewear Emissions El Paso County

and Dona Ana 2010

Figure Comparison of the Annual Mobile Emissions

of Primary PM10 Non-Exhauts (Brake ) from Dona

Ana County New Mexico and El Paso Texas Units

in KgMonth

Figure Comparison of the Annual Mobile Emissions

of Primary PM10-Exhauts Emission from Dona Ana

County New Mexico and El Paso Texas Units in

KgMonth

Primary

PM 25

Brakewe

ar Ziphellip

Brakewe

ar

particula

te_PMhellip

Primary

PM

25Tirewe

ar Ziphellip

Tirewear

particula

te_PM25

Donahellip

Series1 32645 6071 10919 1779

0

10000

20000

30000

40000

AX

IS T

ITLE

Annual Comparison of the

Mobile Exhaust Emissions El Paso

County and Dona Ana 2010

Figure Comparison of the Annual Mobile Emissions

of Primary PM10-Exhauts Emission from Dona Ana

County New Mexico and El Paso Texas Units in

KgMonth

Monthly Mobile Emission PM1025 kg During year 2006

and its Influence on Respiratory Diagnoses Dona Ana

County Zip Code 880218802788072

0

100

200

300

0

5000

10000

15000

Axi

s Ti

tle

Axis Title

Monthly Mobile Exhaust Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Total PrimaryMobile Exhaust_PM10

All Respiratory ICD-9 (AsthmaBronchitis)

050100150200250300

010002000300040005000

Axi

s Ti

tle

Axis Title

Monthly Mobile Brake Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Brakewearparticulate_PM10

All RespiratoryICD -9 (AsthmaBronchitis)

050100150200250300

0200400600800

10001200

Axi

s Ti

tle

Axis Title

Monthly Mobile Tirewear Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Tirewearparticulate_PM10

All Respiratory ICD -9 (AsthmaBronchitis)

Mobile Exhauts

Emission PM10

kg Asthma-

Bronchitis)

Brake Mobile

Emission PM10

kg and Heart

Diagnoses

Tirewear Mobile

Emission PM10

kg and Heart

Diagnoses

Linear Square

R= 951

Linear Square

R=625

Linear Square

R=525

Mobile Exhauts

Emission PM25

kg Asthma-

Bronchitis)

Brake Mobile

Emission PM25

kg and Heart

Diagnoses

Tirewear Mobile

Emission PM25

kg and Heart

Diagnoses

Linear Square

R= 986

Linear Square

R=691

Linear Square

R=601

Results

The results showed that mobile PM emissions in the urban areas close to urban Road and highways is putting at risk public health

and the proportion of diseases attributable to this exposure is potentially large

Brake wear emissions is much lower in freeways due to significantly reduced number of braking events while tire wear is much

higher in areas where studded tires are used The emission of exhaust gases are much higher in areas where there is a high

vehicular traffic

Brake Mobile

Emission PM10 kg

Asthma-Bronchitis)

Brake Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square

R=969

Linear Square

R=856

Exhaust Mobile

Emission PM10 kg

Asthma-Bronchitis)

Exhaust Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square

R=929

Linear Square

R=831

Tirewear Mobile

Emission PM10 kg

Asthma-Bronchitis)

Tirewear Mobile

Emission PM25 kg

and Heart Diagnoses

Linear Square R=769 Linear Square R=715

Brake Mobile

Emission PM10 kg

and Heart

Diagnoses

Brake Mobile

Emission PM25 kg

and Heart

Diagnoses

Exhaust Mobile

Emission PM10 kg

Asthma-Bronchitis)

Linear Square

R=625

Linear Square

R=691

Linear Square R=

951

Exhaust Mobile

Emission PM25 kg

Asthma-

Bronchitis)

Tire wear Mobile

Emission PM10 kg and

Heart Diagnoses

Tirewear Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square R=

986

Linear Square R=525 Linear Square

R=601

El Paso County

Dona Ana

County

BenMAP-CE

In this analysis the Program of Mapping and Analysis of Environmental Benefits-Community Edition

(BenMAP-CE) was used to Estimate the number and economic value of health impacts resulting from changes

in air pollution PM 25 Ugm3 in The El Paso Area

Health and Economic Benefits associated with the Response of PM25 Emission between

Base Year 2010

Number of Mortalities in 2010 Base Year Based on El Paso County Texas Department of State Health Services

Number of Mortalities in 2010 Base Year Based on El Paso County Texas

Department of State Health Services

cause of death

year

2010

Populatio

n

Affected

Backgro

und

Concentr

ation Pollutant

Rollback

Type

Avoided

Deaths

(

Populatio

n)

alzheimers disease 2010 40716 125 PM25

25

microgmAcircsup3

Rollback 9

diseases of the

heart 2010 15834 125 PM25

25

microgmAcircsup3

Rollback 35

influenza and

neumonia 2010 81432 125 PM25

25

microgmAcircsup3

Rollback 18

acute bronchitis

and bronchiolitis 2010 117624 125 PM25

25

microgmAcircsup3

Rollback 26

chronic lower

respiratory diseases 2010 54288 125 PM25

25

microgmAcircsup3

Rollback 12

The Basin-wide decrease in 4 ugm3 PM25 concentration after this

reduction control

Cause of death year 2010

Populatio

n

Affected

Background

Concentrati

on

Reduc

cion

scena

rio Polluta

nt

Rollback

Type

Avoi

ded

Deat

hs

(

Pop

ulati

on)

economic

benefits

analysis $

Alzheimers

disease 2010 121 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 9 12000

Diseases of the

heart 2010 470 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 35 35000

Influenza and

neumonia 2010 242 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 18 42500

Acute bronchitis

and bronchiolitis 2010 349 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 26 95000

Chronic lower

respiratory

diseases 2010 161 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 12 4500

$1 295000

PM25-related Mortalities Based on BenMAP-CE Estimate in 2010 Base Year with change in the concentrations levels

Health and Economic Benefits associated with the Response of PM25 Emission between

Base Year 2010 Increasing 7 Ugm3

Cause of death year 2010

Population

Affected

Deaths

avoided by

attaining 195

μgm3

standard

Background

Concentrati

on

Pollut

ant

Rollback

Type

Avoided

Deaths (

Populatio

n)

econo

mic

Unben

efits

analysi

s

Alzheimers

disease 2010 4524 195 PM25

25

microgmAcircsup3

Rollback 19 150000

Diseases of the

heart 2010 20358 195 PM25

25

microgmAcircsup3

Rollback 135 450000

Influenza and

neumonia 2010 126672 195 PM25

25

microgmAcircsup3

Rollback 38 525000

Acute bronchitis

and bronchiolitis 2010 162864 195 PM25

25

microgmAcircsup3

Rollback 36 122000

Chronic lower

respiratory

diseases 2010 99528 195 PM25

25

microgmAcircsup3

Rollback 12 650000

Conclusions

An excellent Pearson Correlation was established to analyze the relationship in the relative risks of hospitalization of Respiratory(RD) and cardiovascular (CVD) associated with ambient exposure caused by traffic emission in relation to their size andspecific sources of emission on different scenarios interior a border Urban Rural Urban restricted access (freeways andinterstates)

A significant correlation of PM1025 exposure from mobile emission and hospital admissions for selected Respiratory (RD) andcardiovascular (CVD) diagnoses was established The results showed that PM emissions in urban restricted access (freeways andinterstates) is mainly caused by traffic Therefore people living close to highways are more exposed higher vehicular emissions

Conclusions

We found statistically significant associations between mobile PM25 caused by traffic emission with Respiratory and Cardiovascular Diseases in the study areaSubsequently a correlation between cardio-respiratory mortality is established

A significant correlation of PM1025 exposure from mobile emission and hospital admissions for selected Respiratory (RD) and cardiovascular (CVD) diagnoses isestablished The results showed that PM emissions in urban restricted access (freeways and interstates) is mainly caused by traffic Therefore people living close tohighways receive higher vehicular emissions

The table shows the percentage of PM mobile exposure in the analyzed areas contributing to increase the risk of Respiratory and Cardiovascular Diseases

An examination was conducted of the synoptic and local meteorology for the June 2006 ozone episode using the WRF model to determine how meteorological parametersinfluence the formation transport and dispersion of ozone in the PdN The predominant synoptic feature of the ozone event day was the expansion intensification and slowprogression of an upper-level ridge of high pressure The high ozone episodes are associated with highly stable atmospheres strong temperature inversions with low mixingheights and therefore low mixing volumes Under these conditions emissions such as NOx lead to highly polluted conditions that favor ozone formation

BenMAP Conclusions

We have estimated the number and economic value of health impacts resulting

from changes in air pollution concentrations of PM 25 in the PdN region

Reduction of Pm 25 4 UGm3= Avoided 213 cases respiratory cardiovascular

diseses and Economic Benefits associated with the Response of PM25 Emission + $

1295000

Increase of PM25 7 ugm3 = increasing Dies= 326 economic Unbenefits= 2345000$

Bibliography

1 Dockery DW Pope CAI Xu X Spengler JD Ware JH Fay ME Ferris BG Speizer FE An association between air pollution and mortality in six US cities N Engl J Med 3291753ndash1759 (1993)

2 Samet JM Dominici F Curriero FC Coursac I Zeger SL Fine particulate air pollution and mortality in 20 US cities 1987ndash1994 N Engl J Med 3431742ndash1749 (2000)

3 Nel AE Diaz-Sanchez D Li N The role of particulate pollutants in pulmonary inflammation and asthma evidence for the involvement of organic chemicals and oxidative stress Curr Opin Pulm Med 20017 20ndash26

4 Westerholm R Karl-Erik E Exhaust emissions from lightand heavy-duty vehicles chemical composition impact of exhaust after treatment and fuel parameters Environ Health Perspect 102(suppl 4)13ndash23 (1994)

5 Bascom R Bromberg P Costa D Delvin R Dockery D Frampton M Lambert W Samet J Speizer F Utell

6 Health effects of outdoor air pollution Am J Respir Crit Care Med 1533ndash50 (1996)

7 Chow JC Watson JG Frazier CA Egami RT Goodrich A Ralph C Spatial and temporal source contributions to

8 PM10 and PM25 in Reno NV In PM-10 Implementation of Standards Transactions An APCAEPA International Speciality Conference San Francisco CA (Mathal CV Stonefield DH eds) PittsburghAPCA 1988439ndash457

9 overview In Particulate Matter Health and Regulatory Issues VIP-49 Proceedings of an International Specialty Conference 4ndash6 April 1995 Pittsburgh PA PittsburghAir and Waste Management Association 1995577ndash598

10 Kunzli N Kaiser R Medina S Studnicka M Chanel O

11 Filliger P Herry M Horak F Jr Puybonnieux-Texier V Quenel P et al Public-health impact of outdoor and traffic- related air pollution a European assessment Lancet 356795ndash801 (2000)

Bibliography

1 Sioutas C Delfino RJ Singh M Exposure assessment for atmospheric ultrafine particles (UFP) and implications in epidemiological research Environ Health Perspect 2005113947ndash955

2 Mosleh M Blau PJ Dumitrescu D (2004) Characteristics and morphology of wear particles from laboratory testing of disc brake materials Wear 2561128ndash1134

3 Kuumlnzli N et al (2000) Public-health impact of outdoor and traffi c-related air pollution a European assessment Lancet 356(9232)795ndash801

4 Dora C Phillips M eds (2000) Transport environment and health Copenhagen WHO Regional Office for Europe (WHO Regional Publications European Series No 89 httpwwweurowhointdocumente72015pdf accessed 26 November 2004)

5 Westerholm R Karl-Erik E Exhaust emissions from lightand

6 heavy-duty vehicles chemical composition impact of exhaust after treatment and fuel parameters Environ Health Perspect 102(suppl 4)13ndash23 (1994)

7 Fauser Tjell Mosbaek pigegaard Quantification of tire-Tread particles using extractable Organic Zinc as a Tracer Rubber Chemistry and Technology 1999 969Table shows some literature estimates of the contribution of tire wear to PM10 in air (Panko et al 2013) Gustafsson M Blomqvist G Gudmundsson A Dahl A Swietlicki E Bohgard M Lindbom J Ljungman A

8 Chen Y Shah N Huggins FE and Huffman GP (2006) Microanalysis of Ambient Particles from Lexington Ky by Electron Microscopy Atmos Environ 40 651ndash663

9 Donaldson K Tran CL Jimenez LA Duffin R Newby DE and Mills N (2005) Combustion-derived Nanoparticles A Review of Their Toxicology Following Inhalation Exposure Part Fibre Toxicol 2 10ndash23

10 Su D Serafino A Muller JO Jentoft RE Schlogl R and Fiorito S (2008) Cytotoxicity and Inflammatory Potential of Soot Particles of Low-emission Diesel Engines Environ Sci Technol 42 1761ndash1765

11 Maier KL Alessandrini F Beck-Speier I Hofer TPJ Diabatґe S Bitterle E Stoger T and Jakob T (2008) Health Effects of Ambient Particulate Matter-Biological Mechanisms and Inflammatory Responses to in Vitroand in Vivo Particle Exposures Inhalation Toxicol 20 319ndash337

Page 38: Studies of Air Pollutants and their Impact on Respiratory and ...€¦ · Ascarate Park C37 Monitoring Station: The National Ambient Air Quality Standard (NAAQS) for PM 10 and 2.5

Daily Avg PM1025

Levels of PM Mobile Emission Non-Exhaust -Rush Hour Periods Fall 2010 Zip Code

79905

00

100

200

300

400

500

600

Mo

bil

e P

M1

0 (k

g)

Rush Hours

Daily Avg PM10

Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush Hours

Periods 2010 Zip Code 79905

Total Primary Exhaust

_PM10 WinterSpring

Brakewear

particulate_PM10

WinterSpringTirewear particulate_PM10

WinterSpring

Total Primary Exhaust

_PM10 Summer

Brakewear

particulate_PM10 Summer

Tirewear Particulate_PM10

Summer

Total Primary Exhaust

_PM10 Fall

Brakewear

particulate_PM10 Fall

Tirewear particulate_PM10

Fall

00

50

100

150

200

250

300

350

Mo

bil

e P

M2

5 (k

g)

Rush hours

Daily Avg PM25

Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush

Hours Periods 2010 Zip Code 79905

Total Primary Exhaust _PM25

WinterSpring

Brakewear Particulate_PM25

WinterSpring

Tirewear particulate_PM25

WinterSpring

Total Primary Exhaust _PM25

Summer

Brakewear particulate_PM25

Summer

Tirewear particulate_PM25

Summer

Total Primary Exhaust _PM25

Fall

Brakewear particulate_PM25

Fall

Tirewear particulate_PM25

Fall

Figure Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush Hours Figure Seasonal Levels of PM25 from Mobile Emission Non-Exhaust -Rush Hours

GIS EMISSIONS INVENTORY SYSTEM A geographic information system (GIS) was used to established geographic scenarios with processed images of seasonal mobile

emissions in the PdN region Seasonal mapping is visualized for different types of pollutants Brakewear Exhaust and Tyrewear

Fg Graphics of GIS and Seasonal mobile Emission of particulate matter emission inventory Seasonal emission simulations were performed in kilograms and five contributing inputs factors were identified for

modeling 1) On the composition of the particulate material from different sources such as Exhaust and Non exhaust (Brake wear Tirewear) 2) The Vehicles Equipment clasification were selected according to

the use of gasoline and diesel fuel (motorcycle passenger car Light Duty Vehicles Trucks refuse truck Light Duty Vehicles Light Commercial Truck Light Duty Vehicles School Bus)

Winter Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

120354 67860 19065

Spring Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

139767 86702 24463

Summer Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

94747 62481 17630

Fall Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

75510 45542 12596

251 Descriptive Statistics Data Analysis

Weekly Correlation Analysis of Mobile Emission PM10 (Exhaust-Non-Exhaust) and Respiratory

Diagnoses WinterSpring Summer and Fall 2010

0

2

4

6

8

10

0

50

100

150

200

250

300

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21

Mo

rbid

ity

Dis

ch

arg

e

for

all R

esp

ira

tory

Dis

ea

se

ICD

-9

(A

sth

ma

-Bro

nc

hitis

)

WinterSpring Week

Weekly Avg Mobile PM10 Concentrations during

WinterSpring 2010 and its Influence on Respiratory

Diagnoses

Zip Code 79905

Total Medical data ZIP Code 79902

Total Mobile Emission PM10 (Ugm3)

0

1

2

3

4

5

6

7

0

20

40

60

80

100

Mo

rbid

ity

Dis

ch

arg

e

for

all R

esp

ira

tory

Dis

ea

se

ICD

-9

(Ast

hm

aB

ron

ch

itis

)

Weekly Avg Mobile PM10 Concentrations during

Summer 2010 and its Influence on Respiratory

Diagnoses

Summer 2010 Zip Code 79905

Total Mobile Emission PM10

Hospital Admission (Asthma-Bronchitis)

0

2

4

6

8

10

12

0

20

40

60

80

100

120

140

160

180

200

Mo

rbid

ity

dis

ch

arg

es

for

all r

esp

ira

tory

dis

ea

se

Weekly Avg Mobile PM10 Concentrations

during Fall 2010 and its Influence on Respiratory

Diagnoses

Zip Code 79905

Total Medical data ZIP Code 79902

Total Mobile Emission PM10 (Ugm3)

Mobile(Exhaust-Non-

Exhaust) PM10 and

Asthma-Bronchitis)

Linear R

Square

WinterSpring 734 ndash 39

Summer 614 ndash 32

Fall 548 -29

PM10 Mobile emission (Exhaust-Non-Exhaust)contributed significantly

association to the incidence of RD

Weekly Correlation Analysis of PM 25 Mobile Emission (Exhaust-Non-Exhaust)

and Cardiovascular Diagnoses WinterSpring Summer and Fall 2010

0010203040

00500

100015002000

Wee

k 1

Wee

k 2

Wee

k 3

Wee

k 4

Wee

k 5

Wee

k 6

Wee

k 7

Wee

k 8

Wee

k 9

Wee

k 1

0

Wee

k 1

1

Wee

k 1

2

Wee

k 1

3

Wee

k 1

4

Wee

k 1

5

Wee

k 1

6

Wee

k 1

7

Wee

k 1

8

Wee

k 1

9

Wee

k 2

0

Wee

k 2

1

Morb

idit

y d

isch

arg

es f

or

all

card

iovasc

ula

r d

isea

se

Weekly Avg PM25 Mobile Concentrations during

WinterSpring 2010 and its Influence on all Heart

Diagnoses

Zip Code 79905

Total All Heart Disease PM 25 mobile (μgm3)

0010203040

00

500

1000

1500

Mo

rbid

ity

dis

ch

arg

es

for

all

ca

rdio

va

scu

lar

dis

ea

se

Weeks

CORRELATION BETWEEN MOBILE PM25 ugm3

EXPOSURE TO HEART DISEASES SYMPTOMS

SUMMER SEASON 2010

Total All Heart Disease PM 25 mobile (μgm3)

Figure Statistical Analyses of the Relationship Between PM25 Caused by Traffic Emission( 26 of total Emission) with Heart diseases Source Hospital Admissions for Asthma Acute Bronchitis and Heart diseases in El Paso County zip code 79905 from Texas Health Care

Information Council in Austin Texas (Texas Health Care Information Council 2000)

00

10

20

30

40

0

50

100

150

We

ek 3

6

We

ek 3

7

We

ek 3

8

We

ek 3

9

We

ek 4

0

We

ek 4

1

We

ek 4

2

We

ek 4

3

We

ek 4

4

We

ek 4

5

We

ek 4

6

We

ek 4

7

We

ek 4

8

We

ek 4

9

We

ek 5

0

We

ek 5

1

We

ek 5

2

We

ek 5

3

Mo

rbid

ity

dis

ch

arg

es

for

all

ca

rdio

va

scu

lar

dis

ea

se

CORRELATION BETWEEN MOBILE PM25 ugm3

EXPOSURE TO HEART DISEASES SYMPTOMS FALL

SEASON 2010

Total All Heart Disease PM 25 mobile (μgm3)

Mobile(Exhaust-

Non-Exhaust)

PM10 and

Asthma-

Bronchitis)

Linear R

Square

WinterSpring 833 -42

Summer 620 -32

Fall 501-26

PM10 Mobile

emission (Exhaust-

Non-

Exhaust)contribut

ed significantly

association to the

incidence of CVD

Diseases

Monthly Brake Mobile Emission PM1025 kg During year 2010 and its Influence on

Respiratory Diagnoses Zip Code 79905

00200040006000800010000

010000200003000040000

PM

10

Mo

bile

(K

g)

Months

Monthly Brake Mobile Emission PM10 kg during year

2010 and its Influence on Respiratory Diagnoses

Zip Code 79905

Primary PM 10

Brakewear 00100020003000400050006000

0

1000

2000

3000

4000

PM

25

Mo

bil

e(K

g)

Months

Monthly Brake Mobile Emission PM25 during

year 2010 and its Influence on Heart Diagnoses

Zip Code 79905

Primary PM 25

Brakewear

Heart Diseases

Hospital

Admission

Brake Mobile Emission

PM10 kg Asthma-

Bronchitis)

Brake Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=969 Linear Square R=856

Monthly Mobile Exhaust Emission PM1025 During year 2010 and its Influence on

Respiratory Diagnoses Zip Code 79905

0

200

400

600

800

1000

0

10000

20000

30000

40000

50000

1 3 5 7 9 11

PM

10

(K

g m

on

th)

Months

Monthly Mobile Exhaust Emission PM10 during

year 2010 and its Influence on Respiratory

Diagnoses

Zip Code 79905

Primary Exhaust

PM 10

Respiratory Disease

(Asthma

Bronchitis) Hospital

Admission

0

100

200

300

400

500

600

0

10000

20000

30000

40000

50000

1 2 3 4 5 6 7 8 9 101112

PM

25

(K

g m

on

th)

Months

Monthly Exhaust Mobile Emission PM25 during

year 2010 and its Influence on Heart Diagnoses

Zip Code 79905

Primary Exhaust PM

25

Heart Diseases

Hospital Admission

Exhaust Mobile Emission

PM10 kg Asthma-

Bronchitis)

Exhaust Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=929 Linear Square R=831

Monthly Tire wear Mobile Emission PM1025 During year 2010 and its Influence on Heart

Diagnoses Zip Code 79905

0

100

200

300

400

500

600

700

800

900

0

1000

2000

3000

4000

5000

6000

7000

8000

9000

1 2 3 4 5 6 7 8 9 10 11 12

PM

10

(K

g m

on

th)

Months

Monthly Tirewear Mobile Emission PM10 during year 2010

and its Influence on Heart Diagnoses

Zip Code 79905

Primary PM 10 Tirewear

Mobile Emission

Respiratory Disease

(Asthma Bronchitis)

Hospital Admission

0

100

200

300

400

500

600

0

200

400

600

800

1000

1200

1400

1 2 3 4 5 6 7 8 9 10 11 12

PM

25

(K

g m

on

th)

Months

Monthly Tirewear Mobile Emission PM25 during year 2010

and its Influence on Respiratory Diagnoses

Zip Code 79905

Primary PM 25Tirewear

Mobile Emission

Heart Diseases Hospital

Admission

Exhaust Mobile Emission

PM10 kg Asthma-

Bronchitis)

Exhaust Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=769 Linear Square R=715

Dona Ana County Zip Codes

88021880278807288048

Primary

Exhaust

PM 10 Zip

code

79905

Total

Primary

Exhaust

PM10

Dona Ana

Primary

Exhaust

PM 25 Zip

Code

79905

Total

Primary

Exhaust

PM25

Dona Ana

Series1 430378 111773 391915 102123

0

100000

200000

300000

400000

500000

AX

IS T

ITLE

Annual Comparison of the Mobile

Exhaust Emissions El Paso County

and Dona Ana 2010

Primary

PM 10

Brakewea

r Zip code

79905

Brakewea

r

particulat

e_PM10

Dona Ana

Primary

PM 10

Tirewear

Zip code

79905

Tirewear

particulat

e_PM10

Dona Ana

Series1 262585 48573 73754 11864

050000

100000150000200000250000300000

AX

IS T

ITLE

Annual Comparison of the Mobile

Brakewear Emissions El Paso County

and Dona Ana 2010

Figure Comparison of the Annual Mobile Emissions

of Primary PM10 Non-Exhauts (Brake ) from Dona

Ana County New Mexico and El Paso Texas Units

in KgMonth

Figure Comparison of the Annual Mobile Emissions

of Primary PM10-Exhauts Emission from Dona Ana

County New Mexico and El Paso Texas Units in

KgMonth

Primary

PM 25

Brakewe

ar Ziphellip

Brakewe

ar

particula

te_PMhellip

Primary

PM

25Tirewe

ar Ziphellip

Tirewear

particula

te_PM25

Donahellip

Series1 32645 6071 10919 1779

0

10000

20000

30000

40000

AX

IS T

ITLE

Annual Comparison of the

Mobile Exhaust Emissions El Paso

County and Dona Ana 2010

Figure Comparison of the Annual Mobile Emissions

of Primary PM10-Exhauts Emission from Dona Ana

County New Mexico and El Paso Texas Units in

KgMonth

Monthly Mobile Emission PM1025 kg During year 2006

and its Influence on Respiratory Diagnoses Dona Ana

County Zip Code 880218802788072

0

100

200

300

0

5000

10000

15000

Axi

s Ti

tle

Axis Title

Monthly Mobile Exhaust Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Total PrimaryMobile Exhaust_PM10

All Respiratory ICD-9 (AsthmaBronchitis)

050100150200250300

010002000300040005000

Axi

s Ti

tle

Axis Title

Monthly Mobile Brake Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Brakewearparticulate_PM10

All RespiratoryICD -9 (AsthmaBronchitis)

050100150200250300

0200400600800

10001200

Axi

s Ti

tle

Axis Title

Monthly Mobile Tirewear Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Tirewearparticulate_PM10

All Respiratory ICD -9 (AsthmaBronchitis)

Mobile Exhauts

Emission PM10

kg Asthma-

Bronchitis)

Brake Mobile

Emission PM10

kg and Heart

Diagnoses

Tirewear Mobile

Emission PM10

kg and Heart

Diagnoses

Linear Square

R= 951

Linear Square

R=625

Linear Square

R=525

Mobile Exhauts

Emission PM25

kg Asthma-

Bronchitis)

Brake Mobile

Emission PM25

kg and Heart

Diagnoses

Tirewear Mobile

Emission PM25

kg and Heart

Diagnoses

Linear Square

R= 986

Linear Square

R=691

Linear Square

R=601

Results

The results showed that mobile PM emissions in the urban areas close to urban Road and highways is putting at risk public health

and the proportion of diseases attributable to this exposure is potentially large

Brake wear emissions is much lower in freeways due to significantly reduced number of braking events while tire wear is much

higher in areas where studded tires are used The emission of exhaust gases are much higher in areas where there is a high

vehicular traffic

Brake Mobile

Emission PM10 kg

Asthma-Bronchitis)

Brake Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square

R=969

Linear Square

R=856

Exhaust Mobile

Emission PM10 kg

Asthma-Bronchitis)

Exhaust Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square

R=929

Linear Square

R=831

Tirewear Mobile

Emission PM10 kg

Asthma-Bronchitis)

Tirewear Mobile

Emission PM25 kg

and Heart Diagnoses

Linear Square R=769 Linear Square R=715

Brake Mobile

Emission PM10 kg

and Heart

Diagnoses

Brake Mobile

Emission PM25 kg

and Heart

Diagnoses

Exhaust Mobile

Emission PM10 kg

Asthma-Bronchitis)

Linear Square

R=625

Linear Square

R=691

Linear Square R=

951

Exhaust Mobile

Emission PM25 kg

Asthma-

Bronchitis)

Tire wear Mobile

Emission PM10 kg and

Heart Diagnoses

Tirewear Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square R=

986

Linear Square R=525 Linear Square

R=601

El Paso County

Dona Ana

County

BenMAP-CE

In this analysis the Program of Mapping and Analysis of Environmental Benefits-Community Edition

(BenMAP-CE) was used to Estimate the number and economic value of health impacts resulting from changes

in air pollution PM 25 Ugm3 in The El Paso Area

Health and Economic Benefits associated with the Response of PM25 Emission between

Base Year 2010

Number of Mortalities in 2010 Base Year Based on El Paso County Texas Department of State Health Services

Number of Mortalities in 2010 Base Year Based on El Paso County Texas

Department of State Health Services

cause of death

year

2010

Populatio

n

Affected

Backgro

und

Concentr

ation Pollutant

Rollback

Type

Avoided

Deaths

(

Populatio

n)

alzheimers disease 2010 40716 125 PM25

25

microgmAcircsup3

Rollback 9

diseases of the

heart 2010 15834 125 PM25

25

microgmAcircsup3

Rollback 35

influenza and

neumonia 2010 81432 125 PM25

25

microgmAcircsup3

Rollback 18

acute bronchitis

and bronchiolitis 2010 117624 125 PM25

25

microgmAcircsup3

Rollback 26

chronic lower

respiratory diseases 2010 54288 125 PM25

25

microgmAcircsup3

Rollback 12

The Basin-wide decrease in 4 ugm3 PM25 concentration after this

reduction control

Cause of death year 2010

Populatio

n

Affected

Background

Concentrati

on

Reduc

cion

scena

rio Polluta

nt

Rollback

Type

Avoi

ded

Deat

hs

(

Pop

ulati

on)

economic

benefits

analysis $

Alzheimers

disease 2010 121 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 9 12000

Diseases of the

heart 2010 470 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 35 35000

Influenza and

neumonia 2010 242 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 18 42500

Acute bronchitis

and bronchiolitis 2010 349 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 26 95000

Chronic lower

respiratory

diseases 2010 161 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 12 4500

$1 295000

PM25-related Mortalities Based on BenMAP-CE Estimate in 2010 Base Year with change in the concentrations levels

Health and Economic Benefits associated with the Response of PM25 Emission between

Base Year 2010 Increasing 7 Ugm3

Cause of death year 2010

Population

Affected

Deaths

avoided by

attaining 195

μgm3

standard

Background

Concentrati

on

Pollut

ant

Rollback

Type

Avoided

Deaths (

Populatio

n)

econo

mic

Unben

efits

analysi

s

Alzheimers

disease 2010 4524 195 PM25

25

microgmAcircsup3

Rollback 19 150000

Diseases of the

heart 2010 20358 195 PM25

25

microgmAcircsup3

Rollback 135 450000

Influenza and

neumonia 2010 126672 195 PM25

25

microgmAcircsup3

Rollback 38 525000

Acute bronchitis

and bronchiolitis 2010 162864 195 PM25

25

microgmAcircsup3

Rollback 36 122000

Chronic lower

respiratory

diseases 2010 99528 195 PM25

25

microgmAcircsup3

Rollback 12 650000

Conclusions

An excellent Pearson Correlation was established to analyze the relationship in the relative risks of hospitalization of Respiratory(RD) and cardiovascular (CVD) associated with ambient exposure caused by traffic emission in relation to their size andspecific sources of emission on different scenarios interior a border Urban Rural Urban restricted access (freeways andinterstates)

A significant correlation of PM1025 exposure from mobile emission and hospital admissions for selected Respiratory (RD) andcardiovascular (CVD) diagnoses was established The results showed that PM emissions in urban restricted access (freeways andinterstates) is mainly caused by traffic Therefore people living close to highways are more exposed higher vehicular emissions

Conclusions

We found statistically significant associations between mobile PM25 caused by traffic emission with Respiratory and Cardiovascular Diseases in the study areaSubsequently a correlation between cardio-respiratory mortality is established

A significant correlation of PM1025 exposure from mobile emission and hospital admissions for selected Respiratory (RD) and cardiovascular (CVD) diagnoses isestablished The results showed that PM emissions in urban restricted access (freeways and interstates) is mainly caused by traffic Therefore people living close tohighways receive higher vehicular emissions

The table shows the percentage of PM mobile exposure in the analyzed areas contributing to increase the risk of Respiratory and Cardiovascular Diseases

An examination was conducted of the synoptic and local meteorology for the June 2006 ozone episode using the WRF model to determine how meteorological parametersinfluence the formation transport and dispersion of ozone in the PdN The predominant synoptic feature of the ozone event day was the expansion intensification and slowprogression of an upper-level ridge of high pressure The high ozone episodes are associated with highly stable atmospheres strong temperature inversions with low mixingheights and therefore low mixing volumes Under these conditions emissions such as NOx lead to highly polluted conditions that favor ozone formation

BenMAP Conclusions

We have estimated the number and economic value of health impacts resulting

from changes in air pollution concentrations of PM 25 in the PdN region

Reduction of Pm 25 4 UGm3= Avoided 213 cases respiratory cardiovascular

diseses and Economic Benefits associated with the Response of PM25 Emission + $

1295000

Increase of PM25 7 ugm3 = increasing Dies= 326 economic Unbenefits= 2345000$

Bibliography

1 Dockery DW Pope CAI Xu X Spengler JD Ware JH Fay ME Ferris BG Speizer FE An association between air pollution and mortality in six US cities N Engl J Med 3291753ndash1759 (1993)

2 Samet JM Dominici F Curriero FC Coursac I Zeger SL Fine particulate air pollution and mortality in 20 US cities 1987ndash1994 N Engl J Med 3431742ndash1749 (2000)

3 Nel AE Diaz-Sanchez D Li N The role of particulate pollutants in pulmonary inflammation and asthma evidence for the involvement of organic chemicals and oxidative stress Curr Opin Pulm Med 20017 20ndash26

4 Westerholm R Karl-Erik E Exhaust emissions from lightand heavy-duty vehicles chemical composition impact of exhaust after treatment and fuel parameters Environ Health Perspect 102(suppl 4)13ndash23 (1994)

5 Bascom R Bromberg P Costa D Delvin R Dockery D Frampton M Lambert W Samet J Speizer F Utell

6 Health effects of outdoor air pollution Am J Respir Crit Care Med 1533ndash50 (1996)

7 Chow JC Watson JG Frazier CA Egami RT Goodrich A Ralph C Spatial and temporal source contributions to

8 PM10 and PM25 in Reno NV In PM-10 Implementation of Standards Transactions An APCAEPA International Speciality Conference San Francisco CA (Mathal CV Stonefield DH eds) PittsburghAPCA 1988439ndash457

9 overview In Particulate Matter Health and Regulatory Issues VIP-49 Proceedings of an International Specialty Conference 4ndash6 April 1995 Pittsburgh PA PittsburghAir and Waste Management Association 1995577ndash598

10 Kunzli N Kaiser R Medina S Studnicka M Chanel O

11 Filliger P Herry M Horak F Jr Puybonnieux-Texier V Quenel P et al Public-health impact of outdoor and traffic- related air pollution a European assessment Lancet 356795ndash801 (2000)

Bibliography

1 Sioutas C Delfino RJ Singh M Exposure assessment for atmospheric ultrafine particles (UFP) and implications in epidemiological research Environ Health Perspect 2005113947ndash955

2 Mosleh M Blau PJ Dumitrescu D (2004) Characteristics and morphology of wear particles from laboratory testing of disc brake materials Wear 2561128ndash1134

3 Kuumlnzli N et al (2000) Public-health impact of outdoor and traffi c-related air pollution a European assessment Lancet 356(9232)795ndash801

4 Dora C Phillips M eds (2000) Transport environment and health Copenhagen WHO Regional Office for Europe (WHO Regional Publications European Series No 89 httpwwweurowhointdocumente72015pdf accessed 26 November 2004)

5 Westerholm R Karl-Erik E Exhaust emissions from lightand

6 heavy-duty vehicles chemical composition impact of exhaust after treatment and fuel parameters Environ Health Perspect 102(suppl 4)13ndash23 (1994)

7 Fauser Tjell Mosbaek pigegaard Quantification of tire-Tread particles using extractable Organic Zinc as a Tracer Rubber Chemistry and Technology 1999 969Table shows some literature estimates of the contribution of tire wear to PM10 in air (Panko et al 2013) Gustafsson M Blomqvist G Gudmundsson A Dahl A Swietlicki E Bohgard M Lindbom J Ljungman A

8 Chen Y Shah N Huggins FE and Huffman GP (2006) Microanalysis of Ambient Particles from Lexington Ky by Electron Microscopy Atmos Environ 40 651ndash663

9 Donaldson K Tran CL Jimenez LA Duffin R Newby DE and Mills N (2005) Combustion-derived Nanoparticles A Review of Their Toxicology Following Inhalation Exposure Part Fibre Toxicol 2 10ndash23

10 Su D Serafino A Muller JO Jentoft RE Schlogl R and Fiorito S (2008) Cytotoxicity and Inflammatory Potential of Soot Particles of Low-emission Diesel Engines Environ Sci Technol 42 1761ndash1765

11 Maier KL Alessandrini F Beck-Speier I Hofer TPJ Diabatґe S Bitterle E Stoger T and Jakob T (2008) Health Effects of Ambient Particulate Matter-Biological Mechanisms and Inflammatory Responses to in Vitroand in Vivo Particle Exposures Inhalation Toxicol 20 319ndash337

Page 39: Studies of Air Pollutants and their Impact on Respiratory and ...€¦ · Ascarate Park C37 Monitoring Station: The National Ambient Air Quality Standard (NAAQS) for PM 10 and 2.5

GIS EMISSIONS INVENTORY SYSTEM A geographic information system (GIS) was used to established geographic scenarios with processed images of seasonal mobile

emissions in the PdN region Seasonal mapping is visualized for different types of pollutants Brakewear Exhaust and Tyrewear

Fg Graphics of GIS and Seasonal mobile Emission of particulate matter emission inventory Seasonal emission simulations were performed in kilograms and five contributing inputs factors were identified for

modeling 1) On the composition of the particulate material from different sources such as Exhaust and Non exhaust (Brake wear Tirewear) 2) The Vehicles Equipment clasification were selected according to

the use of gasoline and diesel fuel (motorcycle passenger car Light Duty Vehicles Trucks refuse truck Light Duty Vehicles Light Commercial Truck Light Duty Vehicles School Bus)

Winter Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

120354 67860 19065

Spring Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

139767 86702 24463

Summer Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

94747 62481 17630

Fall Primary Exhaust PM 10 (kg)Primary PM 10 Brakewear

(kg) Primary PM 10 Tirewear (kg)

75510 45542 12596

251 Descriptive Statistics Data Analysis

Weekly Correlation Analysis of Mobile Emission PM10 (Exhaust-Non-Exhaust) and Respiratory

Diagnoses WinterSpring Summer and Fall 2010

0

2

4

6

8

10

0

50

100

150

200

250

300

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21

Mo

rbid

ity

Dis

ch

arg

e

for

all R

esp

ira

tory

Dis

ea

se

ICD

-9

(A

sth

ma

-Bro

nc

hitis

)

WinterSpring Week

Weekly Avg Mobile PM10 Concentrations during

WinterSpring 2010 and its Influence on Respiratory

Diagnoses

Zip Code 79905

Total Medical data ZIP Code 79902

Total Mobile Emission PM10 (Ugm3)

0

1

2

3

4

5

6

7

0

20

40

60

80

100

Mo

rbid

ity

Dis

ch

arg

e

for

all R

esp

ira

tory

Dis

ea

se

ICD

-9

(Ast

hm

aB

ron

ch

itis

)

Weekly Avg Mobile PM10 Concentrations during

Summer 2010 and its Influence on Respiratory

Diagnoses

Summer 2010 Zip Code 79905

Total Mobile Emission PM10

Hospital Admission (Asthma-Bronchitis)

0

2

4

6

8

10

12

0

20

40

60

80

100

120

140

160

180

200

Mo

rbid

ity

dis

ch

arg

es

for

all r

esp

ira

tory

dis

ea

se

Weekly Avg Mobile PM10 Concentrations

during Fall 2010 and its Influence on Respiratory

Diagnoses

Zip Code 79905

Total Medical data ZIP Code 79902

Total Mobile Emission PM10 (Ugm3)

Mobile(Exhaust-Non-

Exhaust) PM10 and

Asthma-Bronchitis)

Linear R

Square

WinterSpring 734 ndash 39

Summer 614 ndash 32

Fall 548 -29

PM10 Mobile emission (Exhaust-Non-Exhaust)contributed significantly

association to the incidence of RD

Weekly Correlation Analysis of PM 25 Mobile Emission (Exhaust-Non-Exhaust)

and Cardiovascular Diagnoses WinterSpring Summer and Fall 2010

0010203040

00500

100015002000

Wee

k 1

Wee

k 2

Wee

k 3

Wee

k 4

Wee

k 5

Wee

k 6

Wee

k 7

Wee

k 8

Wee

k 9

Wee

k 1

0

Wee

k 1

1

Wee

k 1

2

Wee

k 1

3

Wee

k 1

4

Wee

k 1

5

Wee

k 1

6

Wee

k 1

7

Wee

k 1

8

Wee

k 1

9

Wee

k 2

0

Wee

k 2

1

Morb

idit

y d

isch

arg

es f

or

all

card

iovasc

ula

r d

isea

se

Weekly Avg PM25 Mobile Concentrations during

WinterSpring 2010 and its Influence on all Heart

Diagnoses

Zip Code 79905

Total All Heart Disease PM 25 mobile (μgm3)

0010203040

00

500

1000

1500

Mo

rbid

ity

dis

ch

arg

es

for

all

ca

rdio

va

scu

lar

dis

ea

se

Weeks

CORRELATION BETWEEN MOBILE PM25 ugm3

EXPOSURE TO HEART DISEASES SYMPTOMS

SUMMER SEASON 2010

Total All Heart Disease PM 25 mobile (μgm3)

Figure Statistical Analyses of the Relationship Between PM25 Caused by Traffic Emission( 26 of total Emission) with Heart diseases Source Hospital Admissions for Asthma Acute Bronchitis and Heart diseases in El Paso County zip code 79905 from Texas Health Care

Information Council in Austin Texas (Texas Health Care Information Council 2000)

00

10

20

30

40

0

50

100

150

We

ek 3

6

We

ek 3

7

We

ek 3

8

We

ek 3

9

We

ek 4

0

We

ek 4

1

We

ek 4

2

We

ek 4

3

We

ek 4

4

We

ek 4

5

We

ek 4

6

We

ek 4

7

We

ek 4

8

We

ek 4

9

We

ek 5

0

We

ek 5

1

We

ek 5

2

We

ek 5

3

Mo

rbid

ity

dis

ch

arg

es

for

all

ca

rdio

va

scu

lar

dis

ea

se

CORRELATION BETWEEN MOBILE PM25 ugm3

EXPOSURE TO HEART DISEASES SYMPTOMS FALL

SEASON 2010

Total All Heart Disease PM 25 mobile (μgm3)

Mobile(Exhaust-

Non-Exhaust)

PM10 and

Asthma-

Bronchitis)

Linear R

Square

WinterSpring 833 -42

Summer 620 -32

Fall 501-26

PM10 Mobile

emission (Exhaust-

Non-

Exhaust)contribut

ed significantly

association to the

incidence of CVD

Diseases

Monthly Brake Mobile Emission PM1025 kg During year 2010 and its Influence on

Respiratory Diagnoses Zip Code 79905

00200040006000800010000

010000200003000040000

PM

10

Mo

bile

(K

g)

Months

Monthly Brake Mobile Emission PM10 kg during year

2010 and its Influence on Respiratory Diagnoses

Zip Code 79905

Primary PM 10

Brakewear 00100020003000400050006000

0

1000

2000

3000

4000

PM

25

Mo

bil

e(K

g)

Months

Monthly Brake Mobile Emission PM25 during

year 2010 and its Influence on Heart Diagnoses

Zip Code 79905

Primary PM 25

Brakewear

Heart Diseases

Hospital

Admission

Brake Mobile Emission

PM10 kg Asthma-

Bronchitis)

Brake Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=969 Linear Square R=856

Monthly Mobile Exhaust Emission PM1025 During year 2010 and its Influence on

Respiratory Diagnoses Zip Code 79905

0

200

400

600

800

1000

0

10000

20000

30000

40000

50000

1 3 5 7 9 11

PM

10

(K

g m

on

th)

Months

Monthly Mobile Exhaust Emission PM10 during

year 2010 and its Influence on Respiratory

Diagnoses

Zip Code 79905

Primary Exhaust

PM 10

Respiratory Disease

(Asthma

Bronchitis) Hospital

Admission

0

100

200

300

400

500

600

0

10000

20000

30000

40000

50000

1 2 3 4 5 6 7 8 9 101112

PM

25

(K

g m

on

th)

Months

Monthly Exhaust Mobile Emission PM25 during

year 2010 and its Influence on Heart Diagnoses

Zip Code 79905

Primary Exhaust PM

25

Heart Diseases

Hospital Admission

Exhaust Mobile Emission

PM10 kg Asthma-

Bronchitis)

Exhaust Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=929 Linear Square R=831

Monthly Tire wear Mobile Emission PM1025 During year 2010 and its Influence on Heart

Diagnoses Zip Code 79905

0

100

200

300

400

500

600

700

800

900

0

1000

2000

3000

4000

5000

6000

7000

8000

9000

1 2 3 4 5 6 7 8 9 10 11 12

PM

10

(K

g m

on

th)

Months

Monthly Tirewear Mobile Emission PM10 during year 2010

and its Influence on Heart Diagnoses

Zip Code 79905

Primary PM 10 Tirewear

Mobile Emission

Respiratory Disease

(Asthma Bronchitis)

Hospital Admission

0

100

200

300

400

500

600

0

200

400

600

800

1000

1200

1400

1 2 3 4 5 6 7 8 9 10 11 12

PM

25

(K

g m

on

th)

Months

Monthly Tirewear Mobile Emission PM25 during year 2010

and its Influence on Respiratory Diagnoses

Zip Code 79905

Primary PM 25Tirewear

Mobile Emission

Heart Diseases Hospital

Admission

Exhaust Mobile Emission

PM10 kg Asthma-

Bronchitis)

Exhaust Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=769 Linear Square R=715

Dona Ana County Zip Codes

88021880278807288048

Primary

Exhaust

PM 10 Zip

code

79905

Total

Primary

Exhaust

PM10

Dona Ana

Primary

Exhaust

PM 25 Zip

Code

79905

Total

Primary

Exhaust

PM25

Dona Ana

Series1 430378 111773 391915 102123

0

100000

200000

300000

400000

500000

AX

IS T

ITLE

Annual Comparison of the Mobile

Exhaust Emissions El Paso County

and Dona Ana 2010

Primary

PM 10

Brakewea

r Zip code

79905

Brakewea

r

particulat

e_PM10

Dona Ana

Primary

PM 10

Tirewear

Zip code

79905

Tirewear

particulat

e_PM10

Dona Ana

Series1 262585 48573 73754 11864

050000

100000150000200000250000300000

AX

IS T

ITLE

Annual Comparison of the Mobile

Brakewear Emissions El Paso County

and Dona Ana 2010

Figure Comparison of the Annual Mobile Emissions

of Primary PM10 Non-Exhauts (Brake ) from Dona

Ana County New Mexico and El Paso Texas Units

in KgMonth

Figure Comparison of the Annual Mobile Emissions

of Primary PM10-Exhauts Emission from Dona Ana

County New Mexico and El Paso Texas Units in

KgMonth

Primary

PM 25

Brakewe

ar Ziphellip

Brakewe

ar

particula

te_PMhellip

Primary

PM

25Tirewe

ar Ziphellip

Tirewear

particula

te_PM25

Donahellip

Series1 32645 6071 10919 1779

0

10000

20000

30000

40000

AX

IS T

ITLE

Annual Comparison of the

Mobile Exhaust Emissions El Paso

County and Dona Ana 2010

Figure Comparison of the Annual Mobile Emissions

of Primary PM10-Exhauts Emission from Dona Ana

County New Mexico and El Paso Texas Units in

KgMonth

Monthly Mobile Emission PM1025 kg During year 2006

and its Influence on Respiratory Diagnoses Dona Ana

County Zip Code 880218802788072

0

100

200

300

0

5000

10000

15000

Axi

s Ti

tle

Axis Title

Monthly Mobile Exhaust Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Total PrimaryMobile Exhaust_PM10

All Respiratory ICD-9 (AsthmaBronchitis)

050100150200250300

010002000300040005000

Axi

s Ti

tle

Axis Title

Monthly Mobile Brake Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Brakewearparticulate_PM10

All RespiratoryICD -9 (AsthmaBronchitis)

050100150200250300

0200400600800

10001200

Axi

s Ti

tle

Axis Title

Monthly Mobile Tirewear Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Tirewearparticulate_PM10

All Respiratory ICD -9 (AsthmaBronchitis)

Mobile Exhauts

Emission PM10

kg Asthma-

Bronchitis)

Brake Mobile

Emission PM10

kg and Heart

Diagnoses

Tirewear Mobile

Emission PM10

kg and Heart

Diagnoses

Linear Square

R= 951

Linear Square

R=625

Linear Square

R=525

Mobile Exhauts

Emission PM25

kg Asthma-

Bronchitis)

Brake Mobile

Emission PM25

kg and Heart

Diagnoses

Tirewear Mobile

Emission PM25

kg and Heart

Diagnoses

Linear Square

R= 986

Linear Square

R=691

Linear Square

R=601

Results

The results showed that mobile PM emissions in the urban areas close to urban Road and highways is putting at risk public health

and the proportion of diseases attributable to this exposure is potentially large

Brake wear emissions is much lower in freeways due to significantly reduced number of braking events while tire wear is much

higher in areas where studded tires are used The emission of exhaust gases are much higher in areas where there is a high

vehicular traffic

Brake Mobile

Emission PM10 kg

Asthma-Bronchitis)

Brake Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square

R=969

Linear Square

R=856

Exhaust Mobile

Emission PM10 kg

Asthma-Bronchitis)

Exhaust Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square

R=929

Linear Square

R=831

Tirewear Mobile

Emission PM10 kg

Asthma-Bronchitis)

Tirewear Mobile

Emission PM25 kg

and Heart Diagnoses

Linear Square R=769 Linear Square R=715

Brake Mobile

Emission PM10 kg

and Heart

Diagnoses

Brake Mobile

Emission PM25 kg

and Heart

Diagnoses

Exhaust Mobile

Emission PM10 kg

Asthma-Bronchitis)

Linear Square

R=625

Linear Square

R=691

Linear Square R=

951

Exhaust Mobile

Emission PM25 kg

Asthma-

Bronchitis)

Tire wear Mobile

Emission PM10 kg and

Heart Diagnoses

Tirewear Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square R=

986

Linear Square R=525 Linear Square

R=601

El Paso County

Dona Ana

County

BenMAP-CE

In this analysis the Program of Mapping and Analysis of Environmental Benefits-Community Edition

(BenMAP-CE) was used to Estimate the number and economic value of health impacts resulting from changes

in air pollution PM 25 Ugm3 in The El Paso Area

Health and Economic Benefits associated with the Response of PM25 Emission between

Base Year 2010

Number of Mortalities in 2010 Base Year Based on El Paso County Texas Department of State Health Services

Number of Mortalities in 2010 Base Year Based on El Paso County Texas

Department of State Health Services

cause of death

year

2010

Populatio

n

Affected

Backgro

und

Concentr

ation Pollutant

Rollback

Type

Avoided

Deaths

(

Populatio

n)

alzheimers disease 2010 40716 125 PM25

25

microgmAcircsup3

Rollback 9

diseases of the

heart 2010 15834 125 PM25

25

microgmAcircsup3

Rollback 35

influenza and

neumonia 2010 81432 125 PM25

25

microgmAcircsup3

Rollback 18

acute bronchitis

and bronchiolitis 2010 117624 125 PM25

25

microgmAcircsup3

Rollback 26

chronic lower

respiratory diseases 2010 54288 125 PM25

25

microgmAcircsup3

Rollback 12

The Basin-wide decrease in 4 ugm3 PM25 concentration after this

reduction control

Cause of death year 2010

Populatio

n

Affected

Background

Concentrati

on

Reduc

cion

scena

rio Polluta

nt

Rollback

Type

Avoi

ded

Deat

hs

(

Pop

ulati

on)

economic

benefits

analysis $

Alzheimers

disease 2010 121 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 9 12000

Diseases of the

heart 2010 470 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 35 35000

Influenza and

neumonia 2010 242 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 18 42500

Acute bronchitis

and bronchiolitis 2010 349 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 26 95000

Chronic lower

respiratory

diseases 2010 161 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 12 4500

$1 295000

PM25-related Mortalities Based on BenMAP-CE Estimate in 2010 Base Year with change in the concentrations levels

Health and Economic Benefits associated with the Response of PM25 Emission between

Base Year 2010 Increasing 7 Ugm3

Cause of death year 2010

Population

Affected

Deaths

avoided by

attaining 195

μgm3

standard

Background

Concentrati

on

Pollut

ant

Rollback

Type

Avoided

Deaths (

Populatio

n)

econo

mic

Unben

efits

analysi

s

Alzheimers

disease 2010 4524 195 PM25

25

microgmAcircsup3

Rollback 19 150000

Diseases of the

heart 2010 20358 195 PM25

25

microgmAcircsup3

Rollback 135 450000

Influenza and

neumonia 2010 126672 195 PM25

25

microgmAcircsup3

Rollback 38 525000

Acute bronchitis

and bronchiolitis 2010 162864 195 PM25

25

microgmAcircsup3

Rollback 36 122000

Chronic lower

respiratory

diseases 2010 99528 195 PM25

25

microgmAcircsup3

Rollback 12 650000

Conclusions

An excellent Pearson Correlation was established to analyze the relationship in the relative risks of hospitalization of Respiratory(RD) and cardiovascular (CVD) associated with ambient exposure caused by traffic emission in relation to their size andspecific sources of emission on different scenarios interior a border Urban Rural Urban restricted access (freeways andinterstates)

A significant correlation of PM1025 exposure from mobile emission and hospital admissions for selected Respiratory (RD) andcardiovascular (CVD) diagnoses was established The results showed that PM emissions in urban restricted access (freeways andinterstates) is mainly caused by traffic Therefore people living close to highways are more exposed higher vehicular emissions

Conclusions

We found statistically significant associations between mobile PM25 caused by traffic emission with Respiratory and Cardiovascular Diseases in the study areaSubsequently a correlation between cardio-respiratory mortality is established

A significant correlation of PM1025 exposure from mobile emission and hospital admissions for selected Respiratory (RD) and cardiovascular (CVD) diagnoses isestablished The results showed that PM emissions in urban restricted access (freeways and interstates) is mainly caused by traffic Therefore people living close tohighways receive higher vehicular emissions

The table shows the percentage of PM mobile exposure in the analyzed areas contributing to increase the risk of Respiratory and Cardiovascular Diseases

An examination was conducted of the synoptic and local meteorology for the June 2006 ozone episode using the WRF model to determine how meteorological parametersinfluence the formation transport and dispersion of ozone in the PdN The predominant synoptic feature of the ozone event day was the expansion intensification and slowprogression of an upper-level ridge of high pressure The high ozone episodes are associated with highly stable atmospheres strong temperature inversions with low mixingheights and therefore low mixing volumes Under these conditions emissions such as NOx lead to highly polluted conditions that favor ozone formation

BenMAP Conclusions

We have estimated the number and economic value of health impacts resulting

from changes in air pollution concentrations of PM 25 in the PdN region

Reduction of Pm 25 4 UGm3= Avoided 213 cases respiratory cardiovascular

diseses and Economic Benefits associated with the Response of PM25 Emission + $

1295000

Increase of PM25 7 ugm3 = increasing Dies= 326 economic Unbenefits= 2345000$

Bibliography

1 Dockery DW Pope CAI Xu X Spengler JD Ware JH Fay ME Ferris BG Speizer FE An association between air pollution and mortality in six US cities N Engl J Med 3291753ndash1759 (1993)

2 Samet JM Dominici F Curriero FC Coursac I Zeger SL Fine particulate air pollution and mortality in 20 US cities 1987ndash1994 N Engl J Med 3431742ndash1749 (2000)

3 Nel AE Diaz-Sanchez D Li N The role of particulate pollutants in pulmonary inflammation and asthma evidence for the involvement of organic chemicals and oxidative stress Curr Opin Pulm Med 20017 20ndash26

4 Westerholm R Karl-Erik E Exhaust emissions from lightand heavy-duty vehicles chemical composition impact of exhaust after treatment and fuel parameters Environ Health Perspect 102(suppl 4)13ndash23 (1994)

5 Bascom R Bromberg P Costa D Delvin R Dockery D Frampton M Lambert W Samet J Speizer F Utell

6 Health effects of outdoor air pollution Am J Respir Crit Care Med 1533ndash50 (1996)

7 Chow JC Watson JG Frazier CA Egami RT Goodrich A Ralph C Spatial and temporal source contributions to

8 PM10 and PM25 in Reno NV In PM-10 Implementation of Standards Transactions An APCAEPA International Speciality Conference San Francisco CA (Mathal CV Stonefield DH eds) PittsburghAPCA 1988439ndash457

9 overview In Particulate Matter Health and Regulatory Issues VIP-49 Proceedings of an International Specialty Conference 4ndash6 April 1995 Pittsburgh PA PittsburghAir and Waste Management Association 1995577ndash598

10 Kunzli N Kaiser R Medina S Studnicka M Chanel O

11 Filliger P Herry M Horak F Jr Puybonnieux-Texier V Quenel P et al Public-health impact of outdoor and traffic- related air pollution a European assessment Lancet 356795ndash801 (2000)

Bibliography

1 Sioutas C Delfino RJ Singh M Exposure assessment for atmospheric ultrafine particles (UFP) and implications in epidemiological research Environ Health Perspect 2005113947ndash955

2 Mosleh M Blau PJ Dumitrescu D (2004) Characteristics and morphology of wear particles from laboratory testing of disc brake materials Wear 2561128ndash1134

3 Kuumlnzli N et al (2000) Public-health impact of outdoor and traffi c-related air pollution a European assessment Lancet 356(9232)795ndash801

4 Dora C Phillips M eds (2000) Transport environment and health Copenhagen WHO Regional Office for Europe (WHO Regional Publications European Series No 89 httpwwweurowhointdocumente72015pdf accessed 26 November 2004)

5 Westerholm R Karl-Erik E Exhaust emissions from lightand

6 heavy-duty vehicles chemical composition impact of exhaust after treatment and fuel parameters Environ Health Perspect 102(suppl 4)13ndash23 (1994)

7 Fauser Tjell Mosbaek pigegaard Quantification of tire-Tread particles using extractable Organic Zinc as a Tracer Rubber Chemistry and Technology 1999 969Table shows some literature estimates of the contribution of tire wear to PM10 in air (Panko et al 2013) Gustafsson M Blomqvist G Gudmundsson A Dahl A Swietlicki E Bohgard M Lindbom J Ljungman A

8 Chen Y Shah N Huggins FE and Huffman GP (2006) Microanalysis of Ambient Particles from Lexington Ky by Electron Microscopy Atmos Environ 40 651ndash663

9 Donaldson K Tran CL Jimenez LA Duffin R Newby DE and Mills N (2005) Combustion-derived Nanoparticles A Review of Their Toxicology Following Inhalation Exposure Part Fibre Toxicol 2 10ndash23

10 Su D Serafino A Muller JO Jentoft RE Schlogl R and Fiorito S (2008) Cytotoxicity and Inflammatory Potential of Soot Particles of Low-emission Diesel Engines Environ Sci Technol 42 1761ndash1765

11 Maier KL Alessandrini F Beck-Speier I Hofer TPJ Diabatґe S Bitterle E Stoger T and Jakob T (2008) Health Effects of Ambient Particulate Matter-Biological Mechanisms and Inflammatory Responses to in Vitroand in Vivo Particle Exposures Inhalation Toxicol 20 319ndash337

Page 40: Studies of Air Pollutants and their Impact on Respiratory and ...€¦ · Ascarate Park C37 Monitoring Station: The National Ambient Air Quality Standard (NAAQS) for PM 10 and 2.5

251 Descriptive Statistics Data Analysis

Weekly Correlation Analysis of Mobile Emission PM10 (Exhaust-Non-Exhaust) and Respiratory

Diagnoses WinterSpring Summer and Fall 2010

0

2

4

6

8

10

0

50

100

150

200

250

300

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21

Mo

rbid

ity

Dis

ch

arg

e

for

all R

esp

ira

tory

Dis

ea

se

ICD

-9

(A

sth

ma

-Bro

nc

hitis

)

WinterSpring Week

Weekly Avg Mobile PM10 Concentrations during

WinterSpring 2010 and its Influence on Respiratory

Diagnoses

Zip Code 79905

Total Medical data ZIP Code 79902

Total Mobile Emission PM10 (Ugm3)

0

1

2

3

4

5

6

7

0

20

40

60

80

100

Mo

rbid

ity

Dis

ch

arg

e

for

all R

esp

ira

tory

Dis

ea

se

ICD

-9

(Ast

hm

aB

ron

ch

itis

)

Weekly Avg Mobile PM10 Concentrations during

Summer 2010 and its Influence on Respiratory

Diagnoses

Summer 2010 Zip Code 79905

Total Mobile Emission PM10

Hospital Admission (Asthma-Bronchitis)

0

2

4

6

8

10

12

0

20

40

60

80

100

120

140

160

180

200

Mo

rbid

ity

dis

ch

arg

es

for

all r

esp

ira

tory

dis

ea

se

Weekly Avg Mobile PM10 Concentrations

during Fall 2010 and its Influence on Respiratory

Diagnoses

Zip Code 79905

Total Medical data ZIP Code 79902

Total Mobile Emission PM10 (Ugm3)

Mobile(Exhaust-Non-

Exhaust) PM10 and

Asthma-Bronchitis)

Linear R

Square

WinterSpring 734 ndash 39

Summer 614 ndash 32

Fall 548 -29

PM10 Mobile emission (Exhaust-Non-Exhaust)contributed significantly

association to the incidence of RD

Weekly Correlation Analysis of PM 25 Mobile Emission (Exhaust-Non-Exhaust)

and Cardiovascular Diagnoses WinterSpring Summer and Fall 2010

0010203040

00500

100015002000

Wee

k 1

Wee

k 2

Wee

k 3

Wee

k 4

Wee

k 5

Wee

k 6

Wee

k 7

Wee

k 8

Wee

k 9

Wee

k 1

0

Wee

k 1

1

Wee

k 1

2

Wee

k 1

3

Wee

k 1

4

Wee

k 1

5

Wee

k 1

6

Wee

k 1

7

Wee

k 1

8

Wee

k 1

9

Wee

k 2

0

Wee

k 2

1

Morb

idit

y d

isch

arg

es f

or

all

card

iovasc

ula

r d

isea

se

Weekly Avg PM25 Mobile Concentrations during

WinterSpring 2010 and its Influence on all Heart

Diagnoses

Zip Code 79905

Total All Heart Disease PM 25 mobile (μgm3)

0010203040

00

500

1000

1500

Mo

rbid

ity

dis

ch

arg

es

for

all

ca

rdio

va

scu

lar

dis

ea

se

Weeks

CORRELATION BETWEEN MOBILE PM25 ugm3

EXPOSURE TO HEART DISEASES SYMPTOMS

SUMMER SEASON 2010

Total All Heart Disease PM 25 mobile (μgm3)

Figure Statistical Analyses of the Relationship Between PM25 Caused by Traffic Emission( 26 of total Emission) with Heart diseases Source Hospital Admissions for Asthma Acute Bronchitis and Heart diseases in El Paso County zip code 79905 from Texas Health Care

Information Council in Austin Texas (Texas Health Care Information Council 2000)

00

10

20

30

40

0

50

100

150

We

ek 3

6

We

ek 3

7

We

ek 3

8

We

ek 3

9

We

ek 4

0

We

ek 4

1

We

ek 4

2

We

ek 4

3

We

ek 4

4

We

ek 4

5

We

ek 4

6

We

ek 4

7

We

ek 4

8

We

ek 4

9

We

ek 5

0

We

ek 5

1

We

ek 5

2

We

ek 5

3

Mo

rbid

ity

dis

ch

arg

es

for

all

ca

rdio

va

scu

lar

dis

ea

se

CORRELATION BETWEEN MOBILE PM25 ugm3

EXPOSURE TO HEART DISEASES SYMPTOMS FALL

SEASON 2010

Total All Heart Disease PM 25 mobile (μgm3)

Mobile(Exhaust-

Non-Exhaust)

PM10 and

Asthma-

Bronchitis)

Linear R

Square

WinterSpring 833 -42

Summer 620 -32

Fall 501-26

PM10 Mobile

emission (Exhaust-

Non-

Exhaust)contribut

ed significantly

association to the

incidence of CVD

Diseases

Monthly Brake Mobile Emission PM1025 kg During year 2010 and its Influence on

Respiratory Diagnoses Zip Code 79905

00200040006000800010000

010000200003000040000

PM

10

Mo

bile

(K

g)

Months

Monthly Brake Mobile Emission PM10 kg during year

2010 and its Influence on Respiratory Diagnoses

Zip Code 79905

Primary PM 10

Brakewear 00100020003000400050006000

0

1000

2000

3000

4000

PM

25

Mo

bil

e(K

g)

Months

Monthly Brake Mobile Emission PM25 during

year 2010 and its Influence on Heart Diagnoses

Zip Code 79905

Primary PM 25

Brakewear

Heart Diseases

Hospital

Admission

Brake Mobile Emission

PM10 kg Asthma-

Bronchitis)

Brake Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=969 Linear Square R=856

Monthly Mobile Exhaust Emission PM1025 During year 2010 and its Influence on

Respiratory Diagnoses Zip Code 79905

0

200

400

600

800

1000

0

10000

20000

30000

40000

50000

1 3 5 7 9 11

PM

10

(K

g m

on

th)

Months

Monthly Mobile Exhaust Emission PM10 during

year 2010 and its Influence on Respiratory

Diagnoses

Zip Code 79905

Primary Exhaust

PM 10

Respiratory Disease

(Asthma

Bronchitis) Hospital

Admission

0

100

200

300

400

500

600

0

10000

20000

30000

40000

50000

1 2 3 4 5 6 7 8 9 101112

PM

25

(K

g m

on

th)

Months

Monthly Exhaust Mobile Emission PM25 during

year 2010 and its Influence on Heart Diagnoses

Zip Code 79905

Primary Exhaust PM

25

Heart Diseases

Hospital Admission

Exhaust Mobile Emission

PM10 kg Asthma-

Bronchitis)

Exhaust Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=929 Linear Square R=831

Monthly Tire wear Mobile Emission PM1025 During year 2010 and its Influence on Heart

Diagnoses Zip Code 79905

0

100

200

300

400

500

600

700

800

900

0

1000

2000

3000

4000

5000

6000

7000

8000

9000

1 2 3 4 5 6 7 8 9 10 11 12

PM

10

(K

g m

on

th)

Months

Monthly Tirewear Mobile Emission PM10 during year 2010

and its Influence on Heart Diagnoses

Zip Code 79905

Primary PM 10 Tirewear

Mobile Emission

Respiratory Disease

(Asthma Bronchitis)

Hospital Admission

0

100

200

300

400

500

600

0

200

400

600

800

1000

1200

1400

1 2 3 4 5 6 7 8 9 10 11 12

PM

25

(K

g m

on

th)

Months

Monthly Tirewear Mobile Emission PM25 during year 2010

and its Influence on Respiratory Diagnoses

Zip Code 79905

Primary PM 25Tirewear

Mobile Emission

Heart Diseases Hospital

Admission

Exhaust Mobile Emission

PM10 kg Asthma-

Bronchitis)

Exhaust Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=769 Linear Square R=715

Dona Ana County Zip Codes

88021880278807288048

Primary

Exhaust

PM 10 Zip

code

79905

Total

Primary

Exhaust

PM10

Dona Ana

Primary

Exhaust

PM 25 Zip

Code

79905

Total

Primary

Exhaust

PM25

Dona Ana

Series1 430378 111773 391915 102123

0

100000

200000

300000

400000

500000

AX

IS T

ITLE

Annual Comparison of the Mobile

Exhaust Emissions El Paso County

and Dona Ana 2010

Primary

PM 10

Brakewea

r Zip code

79905

Brakewea

r

particulat

e_PM10

Dona Ana

Primary

PM 10

Tirewear

Zip code

79905

Tirewear

particulat

e_PM10

Dona Ana

Series1 262585 48573 73754 11864

050000

100000150000200000250000300000

AX

IS T

ITLE

Annual Comparison of the Mobile

Brakewear Emissions El Paso County

and Dona Ana 2010

Figure Comparison of the Annual Mobile Emissions

of Primary PM10 Non-Exhauts (Brake ) from Dona

Ana County New Mexico and El Paso Texas Units

in KgMonth

Figure Comparison of the Annual Mobile Emissions

of Primary PM10-Exhauts Emission from Dona Ana

County New Mexico and El Paso Texas Units in

KgMonth

Primary

PM 25

Brakewe

ar Ziphellip

Brakewe

ar

particula

te_PMhellip

Primary

PM

25Tirewe

ar Ziphellip

Tirewear

particula

te_PM25

Donahellip

Series1 32645 6071 10919 1779

0

10000

20000

30000

40000

AX

IS T

ITLE

Annual Comparison of the

Mobile Exhaust Emissions El Paso

County and Dona Ana 2010

Figure Comparison of the Annual Mobile Emissions

of Primary PM10-Exhauts Emission from Dona Ana

County New Mexico and El Paso Texas Units in

KgMonth

Monthly Mobile Emission PM1025 kg During year 2006

and its Influence on Respiratory Diagnoses Dona Ana

County Zip Code 880218802788072

0

100

200

300

0

5000

10000

15000

Axi

s Ti

tle

Axis Title

Monthly Mobile Exhaust Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Total PrimaryMobile Exhaust_PM10

All Respiratory ICD-9 (AsthmaBronchitis)

050100150200250300

010002000300040005000

Axi

s Ti

tle

Axis Title

Monthly Mobile Brake Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Brakewearparticulate_PM10

All RespiratoryICD -9 (AsthmaBronchitis)

050100150200250300

0200400600800

10001200

Axi

s Ti

tle

Axis Title

Monthly Mobile Tirewear Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Tirewearparticulate_PM10

All Respiratory ICD -9 (AsthmaBronchitis)

Mobile Exhauts

Emission PM10

kg Asthma-

Bronchitis)

Brake Mobile

Emission PM10

kg and Heart

Diagnoses

Tirewear Mobile

Emission PM10

kg and Heart

Diagnoses

Linear Square

R= 951

Linear Square

R=625

Linear Square

R=525

Mobile Exhauts

Emission PM25

kg Asthma-

Bronchitis)

Brake Mobile

Emission PM25

kg and Heart

Diagnoses

Tirewear Mobile

Emission PM25

kg and Heart

Diagnoses

Linear Square

R= 986

Linear Square

R=691

Linear Square

R=601

Results

The results showed that mobile PM emissions in the urban areas close to urban Road and highways is putting at risk public health

and the proportion of diseases attributable to this exposure is potentially large

Brake wear emissions is much lower in freeways due to significantly reduced number of braking events while tire wear is much

higher in areas where studded tires are used The emission of exhaust gases are much higher in areas where there is a high

vehicular traffic

Brake Mobile

Emission PM10 kg

Asthma-Bronchitis)

Brake Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square

R=969

Linear Square

R=856

Exhaust Mobile

Emission PM10 kg

Asthma-Bronchitis)

Exhaust Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square

R=929

Linear Square

R=831

Tirewear Mobile

Emission PM10 kg

Asthma-Bronchitis)

Tirewear Mobile

Emission PM25 kg

and Heart Diagnoses

Linear Square R=769 Linear Square R=715

Brake Mobile

Emission PM10 kg

and Heart

Diagnoses

Brake Mobile

Emission PM25 kg

and Heart

Diagnoses

Exhaust Mobile

Emission PM10 kg

Asthma-Bronchitis)

Linear Square

R=625

Linear Square

R=691

Linear Square R=

951

Exhaust Mobile

Emission PM25 kg

Asthma-

Bronchitis)

Tire wear Mobile

Emission PM10 kg and

Heart Diagnoses

Tirewear Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square R=

986

Linear Square R=525 Linear Square

R=601

El Paso County

Dona Ana

County

BenMAP-CE

In this analysis the Program of Mapping and Analysis of Environmental Benefits-Community Edition

(BenMAP-CE) was used to Estimate the number and economic value of health impacts resulting from changes

in air pollution PM 25 Ugm3 in The El Paso Area

Health and Economic Benefits associated with the Response of PM25 Emission between

Base Year 2010

Number of Mortalities in 2010 Base Year Based on El Paso County Texas Department of State Health Services

Number of Mortalities in 2010 Base Year Based on El Paso County Texas

Department of State Health Services

cause of death

year

2010

Populatio

n

Affected

Backgro

und

Concentr

ation Pollutant

Rollback

Type

Avoided

Deaths

(

Populatio

n)

alzheimers disease 2010 40716 125 PM25

25

microgmAcircsup3

Rollback 9

diseases of the

heart 2010 15834 125 PM25

25

microgmAcircsup3

Rollback 35

influenza and

neumonia 2010 81432 125 PM25

25

microgmAcircsup3

Rollback 18

acute bronchitis

and bronchiolitis 2010 117624 125 PM25

25

microgmAcircsup3

Rollback 26

chronic lower

respiratory diseases 2010 54288 125 PM25

25

microgmAcircsup3

Rollback 12

The Basin-wide decrease in 4 ugm3 PM25 concentration after this

reduction control

Cause of death year 2010

Populatio

n

Affected

Background

Concentrati

on

Reduc

cion

scena

rio Polluta

nt

Rollback

Type

Avoi

ded

Deat

hs

(

Pop

ulati

on)

economic

benefits

analysis $

Alzheimers

disease 2010 121 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 9 12000

Diseases of the

heart 2010 470 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 35 35000

Influenza and

neumonia 2010 242 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 18 42500

Acute bronchitis

and bronchiolitis 2010 349 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 26 95000

Chronic lower

respiratory

diseases 2010 161 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 12 4500

$1 295000

PM25-related Mortalities Based on BenMAP-CE Estimate in 2010 Base Year with change in the concentrations levels

Health and Economic Benefits associated with the Response of PM25 Emission between

Base Year 2010 Increasing 7 Ugm3

Cause of death year 2010

Population

Affected

Deaths

avoided by

attaining 195

μgm3

standard

Background

Concentrati

on

Pollut

ant

Rollback

Type

Avoided

Deaths (

Populatio

n)

econo

mic

Unben

efits

analysi

s

Alzheimers

disease 2010 4524 195 PM25

25

microgmAcircsup3

Rollback 19 150000

Diseases of the

heart 2010 20358 195 PM25

25

microgmAcircsup3

Rollback 135 450000

Influenza and

neumonia 2010 126672 195 PM25

25

microgmAcircsup3

Rollback 38 525000

Acute bronchitis

and bronchiolitis 2010 162864 195 PM25

25

microgmAcircsup3

Rollback 36 122000

Chronic lower

respiratory

diseases 2010 99528 195 PM25

25

microgmAcircsup3

Rollback 12 650000

Conclusions

An excellent Pearson Correlation was established to analyze the relationship in the relative risks of hospitalization of Respiratory(RD) and cardiovascular (CVD) associated with ambient exposure caused by traffic emission in relation to their size andspecific sources of emission on different scenarios interior a border Urban Rural Urban restricted access (freeways andinterstates)

A significant correlation of PM1025 exposure from mobile emission and hospital admissions for selected Respiratory (RD) andcardiovascular (CVD) diagnoses was established The results showed that PM emissions in urban restricted access (freeways andinterstates) is mainly caused by traffic Therefore people living close to highways are more exposed higher vehicular emissions

Conclusions

We found statistically significant associations between mobile PM25 caused by traffic emission with Respiratory and Cardiovascular Diseases in the study areaSubsequently a correlation between cardio-respiratory mortality is established

A significant correlation of PM1025 exposure from mobile emission and hospital admissions for selected Respiratory (RD) and cardiovascular (CVD) diagnoses isestablished The results showed that PM emissions in urban restricted access (freeways and interstates) is mainly caused by traffic Therefore people living close tohighways receive higher vehicular emissions

The table shows the percentage of PM mobile exposure in the analyzed areas contributing to increase the risk of Respiratory and Cardiovascular Diseases

An examination was conducted of the synoptic and local meteorology for the June 2006 ozone episode using the WRF model to determine how meteorological parametersinfluence the formation transport and dispersion of ozone in the PdN The predominant synoptic feature of the ozone event day was the expansion intensification and slowprogression of an upper-level ridge of high pressure The high ozone episodes are associated with highly stable atmospheres strong temperature inversions with low mixingheights and therefore low mixing volumes Under these conditions emissions such as NOx lead to highly polluted conditions that favor ozone formation

BenMAP Conclusions

We have estimated the number and economic value of health impacts resulting

from changes in air pollution concentrations of PM 25 in the PdN region

Reduction of Pm 25 4 UGm3= Avoided 213 cases respiratory cardiovascular

diseses and Economic Benefits associated with the Response of PM25 Emission + $

1295000

Increase of PM25 7 ugm3 = increasing Dies= 326 economic Unbenefits= 2345000$

Bibliography

1 Dockery DW Pope CAI Xu X Spengler JD Ware JH Fay ME Ferris BG Speizer FE An association between air pollution and mortality in six US cities N Engl J Med 3291753ndash1759 (1993)

2 Samet JM Dominici F Curriero FC Coursac I Zeger SL Fine particulate air pollution and mortality in 20 US cities 1987ndash1994 N Engl J Med 3431742ndash1749 (2000)

3 Nel AE Diaz-Sanchez D Li N The role of particulate pollutants in pulmonary inflammation and asthma evidence for the involvement of organic chemicals and oxidative stress Curr Opin Pulm Med 20017 20ndash26

4 Westerholm R Karl-Erik E Exhaust emissions from lightand heavy-duty vehicles chemical composition impact of exhaust after treatment and fuel parameters Environ Health Perspect 102(suppl 4)13ndash23 (1994)

5 Bascom R Bromberg P Costa D Delvin R Dockery D Frampton M Lambert W Samet J Speizer F Utell

6 Health effects of outdoor air pollution Am J Respir Crit Care Med 1533ndash50 (1996)

7 Chow JC Watson JG Frazier CA Egami RT Goodrich A Ralph C Spatial and temporal source contributions to

8 PM10 and PM25 in Reno NV In PM-10 Implementation of Standards Transactions An APCAEPA International Speciality Conference San Francisco CA (Mathal CV Stonefield DH eds) PittsburghAPCA 1988439ndash457

9 overview In Particulate Matter Health and Regulatory Issues VIP-49 Proceedings of an International Specialty Conference 4ndash6 April 1995 Pittsburgh PA PittsburghAir and Waste Management Association 1995577ndash598

10 Kunzli N Kaiser R Medina S Studnicka M Chanel O

11 Filliger P Herry M Horak F Jr Puybonnieux-Texier V Quenel P et al Public-health impact of outdoor and traffic- related air pollution a European assessment Lancet 356795ndash801 (2000)

Bibliography

1 Sioutas C Delfino RJ Singh M Exposure assessment for atmospheric ultrafine particles (UFP) and implications in epidemiological research Environ Health Perspect 2005113947ndash955

2 Mosleh M Blau PJ Dumitrescu D (2004) Characteristics and morphology of wear particles from laboratory testing of disc brake materials Wear 2561128ndash1134

3 Kuumlnzli N et al (2000) Public-health impact of outdoor and traffi c-related air pollution a European assessment Lancet 356(9232)795ndash801

4 Dora C Phillips M eds (2000) Transport environment and health Copenhagen WHO Regional Office for Europe (WHO Regional Publications European Series No 89 httpwwweurowhointdocumente72015pdf accessed 26 November 2004)

5 Westerholm R Karl-Erik E Exhaust emissions from lightand

6 heavy-duty vehicles chemical composition impact of exhaust after treatment and fuel parameters Environ Health Perspect 102(suppl 4)13ndash23 (1994)

7 Fauser Tjell Mosbaek pigegaard Quantification of tire-Tread particles using extractable Organic Zinc as a Tracer Rubber Chemistry and Technology 1999 969Table shows some literature estimates of the contribution of tire wear to PM10 in air (Panko et al 2013) Gustafsson M Blomqvist G Gudmundsson A Dahl A Swietlicki E Bohgard M Lindbom J Ljungman A

8 Chen Y Shah N Huggins FE and Huffman GP (2006) Microanalysis of Ambient Particles from Lexington Ky by Electron Microscopy Atmos Environ 40 651ndash663

9 Donaldson K Tran CL Jimenez LA Duffin R Newby DE and Mills N (2005) Combustion-derived Nanoparticles A Review of Their Toxicology Following Inhalation Exposure Part Fibre Toxicol 2 10ndash23

10 Su D Serafino A Muller JO Jentoft RE Schlogl R and Fiorito S (2008) Cytotoxicity and Inflammatory Potential of Soot Particles of Low-emission Diesel Engines Environ Sci Technol 42 1761ndash1765

11 Maier KL Alessandrini F Beck-Speier I Hofer TPJ Diabatґe S Bitterle E Stoger T and Jakob T (2008) Health Effects of Ambient Particulate Matter-Biological Mechanisms and Inflammatory Responses to in Vitroand in Vivo Particle Exposures Inhalation Toxicol 20 319ndash337

Page 41: Studies of Air Pollutants and their Impact on Respiratory and ...€¦ · Ascarate Park C37 Monitoring Station: The National Ambient Air Quality Standard (NAAQS) for PM 10 and 2.5

Weekly Correlation Analysis of PM 25 Mobile Emission (Exhaust-Non-Exhaust)

and Cardiovascular Diagnoses WinterSpring Summer and Fall 2010

0010203040

00500

100015002000

Wee

k 1

Wee

k 2

Wee

k 3

Wee

k 4

Wee

k 5

Wee

k 6

Wee

k 7

Wee

k 8

Wee

k 9

Wee

k 1

0

Wee

k 1

1

Wee

k 1

2

Wee

k 1

3

Wee

k 1

4

Wee

k 1

5

Wee

k 1

6

Wee

k 1

7

Wee

k 1

8

Wee

k 1

9

Wee

k 2

0

Wee

k 2

1

Morb

idit

y d

isch

arg

es f

or

all

card

iovasc

ula

r d

isea

se

Weekly Avg PM25 Mobile Concentrations during

WinterSpring 2010 and its Influence on all Heart

Diagnoses

Zip Code 79905

Total All Heart Disease PM 25 mobile (μgm3)

0010203040

00

500

1000

1500

Mo

rbid

ity

dis

ch

arg

es

for

all

ca

rdio

va

scu

lar

dis

ea

se

Weeks

CORRELATION BETWEEN MOBILE PM25 ugm3

EXPOSURE TO HEART DISEASES SYMPTOMS

SUMMER SEASON 2010

Total All Heart Disease PM 25 mobile (μgm3)

Figure Statistical Analyses of the Relationship Between PM25 Caused by Traffic Emission( 26 of total Emission) with Heart diseases Source Hospital Admissions for Asthma Acute Bronchitis and Heart diseases in El Paso County zip code 79905 from Texas Health Care

Information Council in Austin Texas (Texas Health Care Information Council 2000)

00

10

20

30

40

0

50

100

150

We

ek 3

6

We

ek 3

7

We

ek 3

8

We

ek 3

9

We

ek 4

0

We

ek 4

1

We

ek 4

2

We

ek 4

3

We

ek 4

4

We

ek 4

5

We

ek 4

6

We

ek 4

7

We

ek 4

8

We

ek 4

9

We

ek 5

0

We

ek 5

1

We

ek 5

2

We

ek 5

3

Mo

rbid

ity

dis

ch

arg

es

for

all

ca

rdio

va

scu

lar

dis

ea

se

CORRELATION BETWEEN MOBILE PM25 ugm3

EXPOSURE TO HEART DISEASES SYMPTOMS FALL

SEASON 2010

Total All Heart Disease PM 25 mobile (μgm3)

Mobile(Exhaust-

Non-Exhaust)

PM10 and

Asthma-

Bronchitis)

Linear R

Square

WinterSpring 833 -42

Summer 620 -32

Fall 501-26

PM10 Mobile

emission (Exhaust-

Non-

Exhaust)contribut

ed significantly

association to the

incidence of CVD

Diseases

Monthly Brake Mobile Emission PM1025 kg During year 2010 and its Influence on

Respiratory Diagnoses Zip Code 79905

00200040006000800010000

010000200003000040000

PM

10

Mo

bile

(K

g)

Months

Monthly Brake Mobile Emission PM10 kg during year

2010 and its Influence on Respiratory Diagnoses

Zip Code 79905

Primary PM 10

Brakewear 00100020003000400050006000

0

1000

2000

3000

4000

PM

25

Mo

bil

e(K

g)

Months

Monthly Brake Mobile Emission PM25 during

year 2010 and its Influence on Heart Diagnoses

Zip Code 79905

Primary PM 25

Brakewear

Heart Diseases

Hospital

Admission

Brake Mobile Emission

PM10 kg Asthma-

Bronchitis)

Brake Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=969 Linear Square R=856

Monthly Mobile Exhaust Emission PM1025 During year 2010 and its Influence on

Respiratory Diagnoses Zip Code 79905

0

200

400

600

800

1000

0

10000

20000

30000

40000

50000

1 3 5 7 9 11

PM

10

(K

g m

on

th)

Months

Monthly Mobile Exhaust Emission PM10 during

year 2010 and its Influence on Respiratory

Diagnoses

Zip Code 79905

Primary Exhaust

PM 10

Respiratory Disease

(Asthma

Bronchitis) Hospital

Admission

0

100

200

300

400

500

600

0

10000

20000

30000

40000

50000

1 2 3 4 5 6 7 8 9 101112

PM

25

(K

g m

on

th)

Months

Monthly Exhaust Mobile Emission PM25 during

year 2010 and its Influence on Heart Diagnoses

Zip Code 79905

Primary Exhaust PM

25

Heart Diseases

Hospital Admission

Exhaust Mobile Emission

PM10 kg Asthma-

Bronchitis)

Exhaust Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=929 Linear Square R=831

Monthly Tire wear Mobile Emission PM1025 During year 2010 and its Influence on Heart

Diagnoses Zip Code 79905

0

100

200

300

400

500

600

700

800

900

0

1000

2000

3000

4000

5000

6000

7000

8000

9000

1 2 3 4 5 6 7 8 9 10 11 12

PM

10

(K

g m

on

th)

Months

Monthly Tirewear Mobile Emission PM10 during year 2010

and its Influence on Heart Diagnoses

Zip Code 79905

Primary PM 10 Tirewear

Mobile Emission

Respiratory Disease

(Asthma Bronchitis)

Hospital Admission

0

100

200

300

400

500

600

0

200

400

600

800

1000

1200

1400

1 2 3 4 5 6 7 8 9 10 11 12

PM

25

(K

g m

on

th)

Months

Monthly Tirewear Mobile Emission PM25 during year 2010

and its Influence on Respiratory Diagnoses

Zip Code 79905

Primary PM 25Tirewear

Mobile Emission

Heart Diseases Hospital

Admission

Exhaust Mobile Emission

PM10 kg Asthma-

Bronchitis)

Exhaust Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=769 Linear Square R=715

Dona Ana County Zip Codes

88021880278807288048

Primary

Exhaust

PM 10 Zip

code

79905

Total

Primary

Exhaust

PM10

Dona Ana

Primary

Exhaust

PM 25 Zip

Code

79905

Total

Primary

Exhaust

PM25

Dona Ana

Series1 430378 111773 391915 102123

0

100000

200000

300000

400000

500000

AX

IS T

ITLE

Annual Comparison of the Mobile

Exhaust Emissions El Paso County

and Dona Ana 2010

Primary

PM 10

Brakewea

r Zip code

79905

Brakewea

r

particulat

e_PM10

Dona Ana

Primary

PM 10

Tirewear

Zip code

79905

Tirewear

particulat

e_PM10

Dona Ana

Series1 262585 48573 73754 11864

050000

100000150000200000250000300000

AX

IS T

ITLE

Annual Comparison of the Mobile

Brakewear Emissions El Paso County

and Dona Ana 2010

Figure Comparison of the Annual Mobile Emissions

of Primary PM10 Non-Exhauts (Brake ) from Dona

Ana County New Mexico and El Paso Texas Units

in KgMonth

Figure Comparison of the Annual Mobile Emissions

of Primary PM10-Exhauts Emission from Dona Ana

County New Mexico and El Paso Texas Units in

KgMonth

Primary

PM 25

Brakewe

ar Ziphellip

Brakewe

ar

particula

te_PMhellip

Primary

PM

25Tirewe

ar Ziphellip

Tirewear

particula

te_PM25

Donahellip

Series1 32645 6071 10919 1779

0

10000

20000

30000

40000

AX

IS T

ITLE

Annual Comparison of the

Mobile Exhaust Emissions El Paso

County and Dona Ana 2010

Figure Comparison of the Annual Mobile Emissions

of Primary PM10-Exhauts Emission from Dona Ana

County New Mexico and El Paso Texas Units in

KgMonth

Monthly Mobile Emission PM1025 kg During year 2006

and its Influence on Respiratory Diagnoses Dona Ana

County Zip Code 880218802788072

0

100

200

300

0

5000

10000

15000

Axi

s Ti

tle

Axis Title

Monthly Mobile Exhaust Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Total PrimaryMobile Exhaust_PM10

All Respiratory ICD-9 (AsthmaBronchitis)

050100150200250300

010002000300040005000

Axi

s Ti

tle

Axis Title

Monthly Mobile Brake Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Brakewearparticulate_PM10

All RespiratoryICD -9 (AsthmaBronchitis)

050100150200250300

0200400600800

10001200

Axi

s Ti

tle

Axis Title

Monthly Mobile Tirewear Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Tirewearparticulate_PM10

All Respiratory ICD -9 (AsthmaBronchitis)

Mobile Exhauts

Emission PM10

kg Asthma-

Bronchitis)

Brake Mobile

Emission PM10

kg and Heart

Diagnoses

Tirewear Mobile

Emission PM10

kg and Heart

Diagnoses

Linear Square

R= 951

Linear Square

R=625

Linear Square

R=525

Mobile Exhauts

Emission PM25

kg Asthma-

Bronchitis)

Brake Mobile

Emission PM25

kg and Heart

Diagnoses

Tirewear Mobile

Emission PM25

kg and Heart

Diagnoses

Linear Square

R= 986

Linear Square

R=691

Linear Square

R=601

Results

The results showed that mobile PM emissions in the urban areas close to urban Road and highways is putting at risk public health

and the proportion of diseases attributable to this exposure is potentially large

Brake wear emissions is much lower in freeways due to significantly reduced number of braking events while tire wear is much

higher in areas where studded tires are used The emission of exhaust gases are much higher in areas where there is a high

vehicular traffic

Brake Mobile

Emission PM10 kg

Asthma-Bronchitis)

Brake Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square

R=969

Linear Square

R=856

Exhaust Mobile

Emission PM10 kg

Asthma-Bronchitis)

Exhaust Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square

R=929

Linear Square

R=831

Tirewear Mobile

Emission PM10 kg

Asthma-Bronchitis)

Tirewear Mobile

Emission PM25 kg

and Heart Diagnoses

Linear Square R=769 Linear Square R=715

Brake Mobile

Emission PM10 kg

and Heart

Diagnoses

Brake Mobile

Emission PM25 kg

and Heart

Diagnoses

Exhaust Mobile

Emission PM10 kg

Asthma-Bronchitis)

Linear Square

R=625

Linear Square

R=691

Linear Square R=

951

Exhaust Mobile

Emission PM25 kg

Asthma-

Bronchitis)

Tire wear Mobile

Emission PM10 kg and

Heart Diagnoses

Tirewear Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square R=

986

Linear Square R=525 Linear Square

R=601

El Paso County

Dona Ana

County

BenMAP-CE

In this analysis the Program of Mapping and Analysis of Environmental Benefits-Community Edition

(BenMAP-CE) was used to Estimate the number and economic value of health impacts resulting from changes

in air pollution PM 25 Ugm3 in The El Paso Area

Health and Economic Benefits associated with the Response of PM25 Emission between

Base Year 2010

Number of Mortalities in 2010 Base Year Based on El Paso County Texas Department of State Health Services

Number of Mortalities in 2010 Base Year Based on El Paso County Texas

Department of State Health Services

cause of death

year

2010

Populatio

n

Affected

Backgro

und

Concentr

ation Pollutant

Rollback

Type

Avoided

Deaths

(

Populatio

n)

alzheimers disease 2010 40716 125 PM25

25

microgmAcircsup3

Rollback 9

diseases of the

heart 2010 15834 125 PM25

25

microgmAcircsup3

Rollback 35

influenza and

neumonia 2010 81432 125 PM25

25

microgmAcircsup3

Rollback 18

acute bronchitis

and bronchiolitis 2010 117624 125 PM25

25

microgmAcircsup3

Rollback 26

chronic lower

respiratory diseases 2010 54288 125 PM25

25

microgmAcircsup3

Rollback 12

The Basin-wide decrease in 4 ugm3 PM25 concentration after this

reduction control

Cause of death year 2010

Populatio

n

Affected

Background

Concentrati

on

Reduc

cion

scena

rio Polluta

nt

Rollback

Type

Avoi

ded

Deat

hs

(

Pop

ulati

on)

economic

benefits

analysis $

Alzheimers

disease 2010 121 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 9 12000

Diseases of the

heart 2010 470 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 35 35000

Influenza and

neumonia 2010 242 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 18 42500

Acute bronchitis

and bronchiolitis 2010 349 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 26 95000

Chronic lower

respiratory

diseases 2010 161 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 12 4500

$1 295000

PM25-related Mortalities Based on BenMAP-CE Estimate in 2010 Base Year with change in the concentrations levels

Health and Economic Benefits associated with the Response of PM25 Emission between

Base Year 2010 Increasing 7 Ugm3

Cause of death year 2010

Population

Affected

Deaths

avoided by

attaining 195

μgm3

standard

Background

Concentrati

on

Pollut

ant

Rollback

Type

Avoided

Deaths (

Populatio

n)

econo

mic

Unben

efits

analysi

s

Alzheimers

disease 2010 4524 195 PM25

25

microgmAcircsup3

Rollback 19 150000

Diseases of the

heart 2010 20358 195 PM25

25

microgmAcircsup3

Rollback 135 450000

Influenza and

neumonia 2010 126672 195 PM25

25

microgmAcircsup3

Rollback 38 525000

Acute bronchitis

and bronchiolitis 2010 162864 195 PM25

25

microgmAcircsup3

Rollback 36 122000

Chronic lower

respiratory

diseases 2010 99528 195 PM25

25

microgmAcircsup3

Rollback 12 650000

Conclusions

An excellent Pearson Correlation was established to analyze the relationship in the relative risks of hospitalization of Respiratory(RD) and cardiovascular (CVD) associated with ambient exposure caused by traffic emission in relation to their size andspecific sources of emission on different scenarios interior a border Urban Rural Urban restricted access (freeways andinterstates)

A significant correlation of PM1025 exposure from mobile emission and hospital admissions for selected Respiratory (RD) andcardiovascular (CVD) diagnoses was established The results showed that PM emissions in urban restricted access (freeways andinterstates) is mainly caused by traffic Therefore people living close to highways are more exposed higher vehicular emissions

Conclusions

We found statistically significant associations between mobile PM25 caused by traffic emission with Respiratory and Cardiovascular Diseases in the study areaSubsequently a correlation between cardio-respiratory mortality is established

A significant correlation of PM1025 exposure from mobile emission and hospital admissions for selected Respiratory (RD) and cardiovascular (CVD) diagnoses isestablished The results showed that PM emissions in urban restricted access (freeways and interstates) is mainly caused by traffic Therefore people living close tohighways receive higher vehicular emissions

The table shows the percentage of PM mobile exposure in the analyzed areas contributing to increase the risk of Respiratory and Cardiovascular Diseases

An examination was conducted of the synoptic and local meteorology for the June 2006 ozone episode using the WRF model to determine how meteorological parametersinfluence the formation transport and dispersion of ozone in the PdN The predominant synoptic feature of the ozone event day was the expansion intensification and slowprogression of an upper-level ridge of high pressure The high ozone episodes are associated with highly stable atmospheres strong temperature inversions with low mixingheights and therefore low mixing volumes Under these conditions emissions such as NOx lead to highly polluted conditions that favor ozone formation

BenMAP Conclusions

We have estimated the number and economic value of health impacts resulting

from changes in air pollution concentrations of PM 25 in the PdN region

Reduction of Pm 25 4 UGm3= Avoided 213 cases respiratory cardiovascular

diseses and Economic Benefits associated with the Response of PM25 Emission + $

1295000

Increase of PM25 7 ugm3 = increasing Dies= 326 economic Unbenefits= 2345000$

Bibliography

1 Dockery DW Pope CAI Xu X Spengler JD Ware JH Fay ME Ferris BG Speizer FE An association between air pollution and mortality in six US cities N Engl J Med 3291753ndash1759 (1993)

2 Samet JM Dominici F Curriero FC Coursac I Zeger SL Fine particulate air pollution and mortality in 20 US cities 1987ndash1994 N Engl J Med 3431742ndash1749 (2000)

3 Nel AE Diaz-Sanchez D Li N The role of particulate pollutants in pulmonary inflammation and asthma evidence for the involvement of organic chemicals and oxidative stress Curr Opin Pulm Med 20017 20ndash26

4 Westerholm R Karl-Erik E Exhaust emissions from lightand heavy-duty vehicles chemical composition impact of exhaust after treatment and fuel parameters Environ Health Perspect 102(suppl 4)13ndash23 (1994)

5 Bascom R Bromberg P Costa D Delvin R Dockery D Frampton M Lambert W Samet J Speizer F Utell

6 Health effects of outdoor air pollution Am J Respir Crit Care Med 1533ndash50 (1996)

7 Chow JC Watson JG Frazier CA Egami RT Goodrich A Ralph C Spatial and temporal source contributions to

8 PM10 and PM25 in Reno NV In PM-10 Implementation of Standards Transactions An APCAEPA International Speciality Conference San Francisco CA (Mathal CV Stonefield DH eds) PittsburghAPCA 1988439ndash457

9 overview In Particulate Matter Health and Regulatory Issues VIP-49 Proceedings of an International Specialty Conference 4ndash6 April 1995 Pittsburgh PA PittsburghAir and Waste Management Association 1995577ndash598

10 Kunzli N Kaiser R Medina S Studnicka M Chanel O

11 Filliger P Herry M Horak F Jr Puybonnieux-Texier V Quenel P et al Public-health impact of outdoor and traffic- related air pollution a European assessment Lancet 356795ndash801 (2000)

Bibliography

1 Sioutas C Delfino RJ Singh M Exposure assessment for atmospheric ultrafine particles (UFP) and implications in epidemiological research Environ Health Perspect 2005113947ndash955

2 Mosleh M Blau PJ Dumitrescu D (2004) Characteristics and morphology of wear particles from laboratory testing of disc brake materials Wear 2561128ndash1134

3 Kuumlnzli N et al (2000) Public-health impact of outdoor and traffi c-related air pollution a European assessment Lancet 356(9232)795ndash801

4 Dora C Phillips M eds (2000) Transport environment and health Copenhagen WHO Regional Office for Europe (WHO Regional Publications European Series No 89 httpwwweurowhointdocumente72015pdf accessed 26 November 2004)

5 Westerholm R Karl-Erik E Exhaust emissions from lightand

6 heavy-duty vehicles chemical composition impact of exhaust after treatment and fuel parameters Environ Health Perspect 102(suppl 4)13ndash23 (1994)

7 Fauser Tjell Mosbaek pigegaard Quantification of tire-Tread particles using extractable Organic Zinc as a Tracer Rubber Chemistry and Technology 1999 969Table shows some literature estimates of the contribution of tire wear to PM10 in air (Panko et al 2013) Gustafsson M Blomqvist G Gudmundsson A Dahl A Swietlicki E Bohgard M Lindbom J Ljungman A

8 Chen Y Shah N Huggins FE and Huffman GP (2006) Microanalysis of Ambient Particles from Lexington Ky by Electron Microscopy Atmos Environ 40 651ndash663

9 Donaldson K Tran CL Jimenez LA Duffin R Newby DE and Mills N (2005) Combustion-derived Nanoparticles A Review of Their Toxicology Following Inhalation Exposure Part Fibre Toxicol 2 10ndash23

10 Su D Serafino A Muller JO Jentoft RE Schlogl R and Fiorito S (2008) Cytotoxicity and Inflammatory Potential of Soot Particles of Low-emission Diesel Engines Environ Sci Technol 42 1761ndash1765

11 Maier KL Alessandrini F Beck-Speier I Hofer TPJ Diabatґe S Bitterle E Stoger T and Jakob T (2008) Health Effects of Ambient Particulate Matter-Biological Mechanisms and Inflammatory Responses to in Vitroand in Vivo Particle Exposures Inhalation Toxicol 20 319ndash337

Page 42: Studies of Air Pollutants and their Impact on Respiratory and ...€¦ · Ascarate Park C37 Monitoring Station: The National Ambient Air Quality Standard (NAAQS) for PM 10 and 2.5

Monthly Brake Mobile Emission PM1025 kg During year 2010 and its Influence on

Respiratory Diagnoses Zip Code 79905

00200040006000800010000

010000200003000040000

PM

10

Mo

bile

(K

g)

Months

Monthly Brake Mobile Emission PM10 kg during year

2010 and its Influence on Respiratory Diagnoses

Zip Code 79905

Primary PM 10

Brakewear 00100020003000400050006000

0

1000

2000

3000

4000

PM

25

Mo

bil

e(K

g)

Months

Monthly Brake Mobile Emission PM25 during

year 2010 and its Influence on Heart Diagnoses

Zip Code 79905

Primary PM 25

Brakewear

Heart Diseases

Hospital

Admission

Brake Mobile Emission

PM10 kg Asthma-

Bronchitis)

Brake Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=969 Linear Square R=856

Monthly Mobile Exhaust Emission PM1025 During year 2010 and its Influence on

Respiratory Diagnoses Zip Code 79905

0

200

400

600

800

1000

0

10000

20000

30000

40000

50000

1 3 5 7 9 11

PM

10

(K

g m

on

th)

Months

Monthly Mobile Exhaust Emission PM10 during

year 2010 and its Influence on Respiratory

Diagnoses

Zip Code 79905

Primary Exhaust

PM 10

Respiratory Disease

(Asthma

Bronchitis) Hospital

Admission

0

100

200

300

400

500

600

0

10000

20000

30000

40000

50000

1 2 3 4 5 6 7 8 9 101112

PM

25

(K

g m

on

th)

Months

Monthly Exhaust Mobile Emission PM25 during

year 2010 and its Influence on Heart Diagnoses

Zip Code 79905

Primary Exhaust PM

25

Heart Diseases

Hospital Admission

Exhaust Mobile Emission

PM10 kg Asthma-

Bronchitis)

Exhaust Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=929 Linear Square R=831

Monthly Tire wear Mobile Emission PM1025 During year 2010 and its Influence on Heart

Diagnoses Zip Code 79905

0

100

200

300

400

500

600

700

800

900

0

1000

2000

3000

4000

5000

6000

7000

8000

9000

1 2 3 4 5 6 7 8 9 10 11 12

PM

10

(K

g m

on

th)

Months

Monthly Tirewear Mobile Emission PM10 during year 2010

and its Influence on Heart Diagnoses

Zip Code 79905

Primary PM 10 Tirewear

Mobile Emission

Respiratory Disease

(Asthma Bronchitis)

Hospital Admission

0

100

200

300

400

500

600

0

200

400

600

800

1000

1200

1400

1 2 3 4 5 6 7 8 9 10 11 12

PM

25

(K

g m

on

th)

Months

Monthly Tirewear Mobile Emission PM25 during year 2010

and its Influence on Respiratory Diagnoses

Zip Code 79905

Primary PM 25Tirewear

Mobile Emission

Heart Diseases Hospital

Admission

Exhaust Mobile Emission

PM10 kg Asthma-

Bronchitis)

Exhaust Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=769 Linear Square R=715

Dona Ana County Zip Codes

88021880278807288048

Primary

Exhaust

PM 10 Zip

code

79905

Total

Primary

Exhaust

PM10

Dona Ana

Primary

Exhaust

PM 25 Zip

Code

79905

Total

Primary

Exhaust

PM25

Dona Ana

Series1 430378 111773 391915 102123

0

100000

200000

300000

400000

500000

AX

IS T

ITLE

Annual Comparison of the Mobile

Exhaust Emissions El Paso County

and Dona Ana 2010

Primary

PM 10

Brakewea

r Zip code

79905

Brakewea

r

particulat

e_PM10

Dona Ana

Primary

PM 10

Tirewear

Zip code

79905

Tirewear

particulat

e_PM10

Dona Ana

Series1 262585 48573 73754 11864

050000

100000150000200000250000300000

AX

IS T

ITLE

Annual Comparison of the Mobile

Brakewear Emissions El Paso County

and Dona Ana 2010

Figure Comparison of the Annual Mobile Emissions

of Primary PM10 Non-Exhauts (Brake ) from Dona

Ana County New Mexico and El Paso Texas Units

in KgMonth

Figure Comparison of the Annual Mobile Emissions

of Primary PM10-Exhauts Emission from Dona Ana

County New Mexico and El Paso Texas Units in

KgMonth

Primary

PM 25

Brakewe

ar Ziphellip

Brakewe

ar

particula

te_PMhellip

Primary

PM

25Tirewe

ar Ziphellip

Tirewear

particula

te_PM25

Donahellip

Series1 32645 6071 10919 1779

0

10000

20000

30000

40000

AX

IS T

ITLE

Annual Comparison of the

Mobile Exhaust Emissions El Paso

County and Dona Ana 2010

Figure Comparison of the Annual Mobile Emissions

of Primary PM10-Exhauts Emission from Dona Ana

County New Mexico and El Paso Texas Units in

KgMonth

Monthly Mobile Emission PM1025 kg During year 2006

and its Influence on Respiratory Diagnoses Dona Ana

County Zip Code 880218802788072

0

100

200

300

0

5000

10000

15000

Axi

s Ti

tle

Axis Title

Monthly Mobile Exhaust Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Total PrimaryMobile Exhaust_PM10

All Respiratory ICD-9 (AsthmaBronchitis)

050100150200250300

010002000300040005000

Axi

s Ti

tle

Axis Title

Monthly Mobile Brake Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Brakewearparticulate_PM10

All RespiratoryICD -9 (AsthmaBronchitis)

050100150200250300

0200400600800

10001200

Axi

s Ti

tle

Axis Title

Monthly Mobile Tirewear Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Tirewearparticulate_PM10

All Respiratory ICD -9 (AsthmaBronchitis)

Mobile Exhauts

Emission PM10

kg Asthma-

Bronchitis)

Brake Mobile

Emission PM10

kg and Heart

Diagnoses

Tirewear Mobile

Emission PM10

kg and Heart

Diagnoses

Linear Square

R= 951

Linear Square

R=625

Linear Square

R=525

Mobile Exhauts

Emission PM25

kg Asthma-

Bronchitis)

Brake Mobile

Emission PM25

kg and Heart

Diagnoses

Tirewear Mobile

Emission PM25

kg and Heart

Diagnoses

Linear Square

R= 986

Linear Square

R=691

Linear Square

R=601

Results

The results showed that mobile PM emissions in the urban areas close to urban Road and highways is putting at risk public health

and the proportion of diseases attributable to this exposure is potentially large

Brake wear emissions is much lower in freeways due to significantly reduced number of braking events while tire wear is much

higher in areas where studded tires are used The emission of exhaust gases are much higher in areas where there is a high

vehicular traffic

Brake Mobile

Emission PM10 kg

Asthma-Bronchitis)

Brake Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square

R=969

Linear Square

R=856

Exhaust Mobile

Emission PM10 kg

Asthma-Bronchitis)

Exhaust Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square

R=929

Linear Square

R=831

Tirewear Mobile

Emission PM10 kg

Asthma-Bronchitis)

Tirewear Mobile

Emission PM25 kg

and Heart Diagnoses

Linear Square R=769 Linear Square R=715

Brake Mobile

Emission PM10 kg

and Heart

Diagnoses

Brake Mobile

Emission PM25 kg

and Heart

Diagnoses

Exhaust Mobile

Emission PM10 kg

Asthma-Bronchitis)

Linear Square

R=625

Linear Square

R=691

Linear Square R=

951

Exhaust Mobile

Emission PM25 kg

Asthma-

Bronchitis)

Tire wear Mobile

Emission PM10 kg and

Heart Diagnoses

Tirewear Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square R=

986

Linear Square R=525 Linear Square

R=601

El Paso County

Dona Ana

County

BenMAP-CE

In this analysis the Program of Mapping and Analysis of Environmental Benefits-Community Edition

(BenMAP-CE) was used to Estimate the number and economic value of health impacts resulting from changes

in air pollution PM 25 Ugm3 in The El Paso Area

Health and Economic Benefits associated with the Response of PM25 Emission between

Base Year 2010

Number of Mortalities in 2010 Base Year Based on El Paso County Texas Department of State Health Services

Number of Mortalities in 2010 Base Year Based on El Paso County Texas

Department of State Health Services

cause of death

year

2010

Populatio

n

Affected

Backgro

und

Concentr

ation Pollutant

Rollback

Type

Avoided

Deaths

(

Populatio

n)

alzheimers disease 2010 40716 125 PM25

25

microgmAcircsup3

Rollback 9

diseases of the

heart 2010 15834 125 PM25

25

microgmAcircsup3

Rollback 35

influenza and

neumonia 2010 81432 125 PM25

25

microgmAcircsup3

Rollback 18

acute bronchitis

and bronchiolitis 2010 117624 125 PM25

25

microgmAcircsup3

Rollback 26

chronic lower

respiratory diseases 2010 54288 125 PM25

25

microgmAcircsup3

Rollback 12

The Basin-wide decrease in 4 ugm3 PM25 concentration after this

reduction control

Cause of death year 2010

Populatio

n

Affected

Background

Concentrati

on

Reduc

cion

scena

rio Polluta

nt

Rollback

Type

Avoi

ded

Deat

hs

(

Pop

ulati

on)

economic

benefits

analysis $

Alzheimers

disease 2010 121 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 9 12000

Diseases of the

heart 2010 470 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 35 35000

Influenza and

neumonia 2010 242 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 18 42500

Acute bronchitis

and bronchiolitis 2010 349 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 26 95000

Chronic lower

respiratory

diseases 2010 161 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 12 4500

$1 295000

PM25-related Mortalities Based on BenMAP-CE Estimate in 2010 Base Year with change in the concentrations levels

Health and Economic Benefits associated with the Response of PM25 Emission between

Base Year 2010 Increasing 7 Ugm3

Cause of death year 2010

Population

Affected

Deaths

avoided by

attaining 195

μgm3

standard

Background

Concentrati

on

Pollut

ant

Rollback

Type

Avoided

Deaths (

Populatio

n)

econo

mic

Unben

efits

analysi

s

Alzheimers

disease 2010 4524 195 PM25

25

microgmAcircsup3

Rollback 19 150000

Diseases of the

heart 2010 20358 195 PM25

25

microgmAcircsup3

Rollback 135 450000

Influenza and

neumonia 2010 126672 195 PM25

25

microgmAcircsup3

Rollback 38 525000

Acute bronchitis

and bronchiolitis 2010 162864 195 PM25

25

microgmAcircsup3

Rollback 36 122000

Chronic lower

respiratory

diseases 2010 99528 195 PM25

25

microgmAcircsup3

Rollback 12 650000

Conclusions

An excellent Pearson Correlation was established to analyze the relationship in the relative risks of hospitalization of Respiratory(RD) and cardiovascular (CVD) associated with ambient exposure caused by traffic emission in relation to their size andspecific sources of emission on different scenarios interior a border Urban Rural Urban restricted access (freeways andinterstates)

A significant correlation of PM1025 exposure from mobile emission and hospital admissions for selected Respiratory (RD) andcardiovascular (CVD) diagnoses was established The results showed that PM emissions in urban restricted access (freeways andinterstates) is mainly caused by traffic Therefore people living close to highways are more exposed higher vehicular emissions

Conclusions

We found statistically significant associations between mobile PM25 caused by traffic emission with Respiratory and Cardiovascular Diseases in the study areaSubsequently a correlation between cardio-respiratory mortality is established

A significant correlation of PM1025 exposure from mobile emission and hospital admissions for selected Respiratory (RD) and cardiovascular (CVD) diagnoses isestablished The results showed that PM emissions in urban restricted access (freeways and interstates) is mainly caused by traffic Therefore people living close tohighways receive higher vehicular emissions

The table shows the percentage of PM mobile exposure in the analyzed areas contributing to increase the risk of Respiratory and Cardiovascular Diseases

An examination was conducted of the synoptic and local meteorology for the June 2006 ozone episode using the WRF model to determine how meteorological parametersinfluence the formation transport and dispersion of ozone in the PdN The predominant synoptic feature of the ozone event day was the expansion intensification and slowprogression of an upper-level ridge of high pressure The high ozone episodes are associated with highly stable atmospheres strong temperature inversions with low mixingheights and therefore low mixing volumes Under these conditions emissions such as NOx lead to highly polluted conditions that favor ozone formation

BenMAP Conclusions

We have estimated the number and economic value of health impacts resulting

from changes in air pollution concentrations of PM 25 in the PdN region

Reduction of Pm 25 4 UGm3= Avoided 213 cases respiratory cardiovascular

diseses and Economic Benefits associated with the Response of PM25 Emission + $

1295000

Increase of PM25 7 ugm3 = increasing Dies= 326 economic Unbenefits= 2345000$

Bibliography

1 Dockery DW Pope CAI Xu X Spengler JD Ware JH Fay ME Ferris BG Speizer FE An association between air pollution and mortality in six US cities N Engl J Med 3291753ndash1759 (1993)

2 Samet JM Dominici F Curriero FC Coursac I Zeger SL Fine particulate air pollution and mortality in 20 US cities 1987ndash1994 N Engl J Med 3431742ndash1749 (2000)

3 Nel AE Diaz-Sanchez D Li N The role of particulate pollutants in pulmonary inflammation and asthma evidence for the involvement of organic chemicals and oxidative stress Curr Opin Pulm Med 20017 20ndash26

4 Westerholm R Karl-Erik E Exhaust emissions from lightand heavy-duty vehicles chemical composition impact of exhaust after treatment and fuel parameters Environ Health Perspect 102(suppl 4)13ndash23 (1994)

5 Bascom R Bromberg P Costa D Delvin R Dockery D Frampton M Lambert W Samet J Speizer F Utell

6 Health effects of outdoor air pollution Am J Respir Crit Care Med 1533ndash50 (1996)

7 Chow JC Watson JG Frazier CA Egami RT Goodrich A Ralph C Spatial and temporal source contributions to

8 PM10 and PM25 in Reno NV In PM-10 Implementation of Standards Transactions An APCAEPA International Speciality Conference San Francisco CA (Mathal CV Stonefield DH eds) PittsburghAPCA 1988439ndash457

9 overview In Particulate Matter Health and Regulatory Issues VIP-49 Proceedings of an International Specialty Conference 4ndash6 April 1995 Pittsburgh PA PittsburghAir and Waste Management Association 1995577ndash598

10 Kunzli N Kaiser R Medina S Studnicka M Chanel O

11 Filliger P Herry M Horak F Jr Puybonnieux-Texier V Quenel P et al Public-health impact of outdoor and traffic- related air pollution a European assessment Lancet 356795ndash801 (2000)

Bibliography

1 Sioutas C Delfino RJ Singh M Exposure assessment for atmospheric ultrafine particles (UFP) and implications in epidemiological research Environ Health Perspect 2005113947ndash955

2 Mosleh M Blau PJ Dumitrescu D (2004) Characteristics and morphology of wear particles from laboratory testing of disc brake materials Wear 2561128ndash1134

3 Kuumlnzli N et al (2000) Public-health impact of outdoor and traffi c-related air pollution a European assessment Lancet 356(9232)795ndash801

4 Dora C Phillips M eds (2000) Transport environment and health Copenhagen WHO Regional Office for Europe (WHO Regional Publications European Series No 89 httpwwweurowhointdocumente72015pdf accessed 26 November 2004)

5 Westerholm R Karl-Erik E Exhaust emissions from lightand

6 heavy-duty vehicles chemical composition impact of exhaust after treatment and fuel parameters Environ Health Perspect 102(suppl 4)13ndash23 (1994)

7 Fauser Tjell Mosbaek pigegaard Quantification of tire-Tread particles using extractable Organic Zinc as a Tracer Rubber Chemistry and Technology 1999 969Table shows some literature estimates of the contribution of tire wear to PM10 in air (Panko et al 2013) Gustafsson M Blomqvist G Gudmundsson A Dahl A Swietlicki E Bohgard M Lindbom J Ljungman A

8 Chen Y Shah N Huggins FE and Huffman GP (2006) Microanalysis of Ambient Particles from Lexington Ky by Electron Microscopy Atmos Environ 40 651ndash663

9 Donaldson K Tran CL Jimenez LA Duffin R Newby DE and Mills N (2005) Combustion-derived Nanoparticles A Review of Their Toxicology Following Inhalation Exposure Part Fibre Toxicol 2 10ndash23

10 Su D Serafino A Muller JO Jentoft RE Schlogl R and Fiorito S (2008) Cytotoxicity and Inflammatory Potential of Soot Particles of Low-emission Diesel Engines Environ Sci Technol 42 1761ndash1765

11 Maier KL Alessandrini F Beck-Speier I Hofer TPJ Diabatґe S Bitterle E Stoger T and Jakob T (2008) Health Effects of Ambient Particulate Matter-Biological Mechanisms and Inflammatory Responses to in Vitroand in Vivo Particle Exposures Inhalation Toxicol 20 319ndash337

Page 43: Studies of Air Pollutants and their Impact on Respiratory and ...€¦ · Ascarate Park C37 Monitoring Station: The National Ambient Air Quality Standard (NAAQS) for PM 10 and 2.5

Monthly Mobile Exhaust Emission PM1025 During year 2010 and its Influence on

Respiratory Diagnoses Zip Code 79905

0

200

400

600

800

1000

0

10000

20000

30000

40000

50000

1 3 5 7 9 11

PM

10

(K

g m

on

th)

Months

Monthly Mobile Exhaust Emission PM10 during

year 2010 and its Influence on Respiratory

Diagnoses

Zip Code 79905

Primary Exhaust

PM 10

Respiratory Disease

(Asthma

Bronchitis) Hospital

Admission

0

100

200

300

400

500

600

0

10000

20000

30000

40000

50000

1 2 3 4 5 6 7 8 9 101112

PM

25

(K

g m

on

th)

Months

Monthly Exhaust Mobile Emission PM25 during

year 2010 and its Influence on Heart Diagnoses

Zip Code 79905

Primary Exhaust PM

25

Heart Diseases

Hospital Admission

Exhaust Mobile Emission

PM10 kg Asthma-

Bronchitis)

Exhaust Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=929 Linear Square R=831

Monthly Tire wear Mobile Emission PM1025 During year 2010 and its Influence on Heart

Diagnoses Zip Code 79905

0

100

200

300

400

500

600

700

800

900

0

1000

2000

3000

4000

5000

6000

7000

8000

9000

1 2 3 4 5 6 7 8 9 10 11 12

PM

10

(K

g m

on

th)

Months

Monthly Tirewear Mobile Emission PM10 during year 2010

and its Influence on Heart Diagnoses

Zip Code 79905

Primary PM 10 Tirewear

Mobile Emission

Respiratory Disease

(Asthma Bronchitis)

Hospital Admission

0

100

200

300

400

500

600

0

200

400

600

800

1000

1200

1400

1 2 3 4 5 6 7 8 9 10 11 12

PM

25

(K

g m

on

th)

Months

Monthly Tirewear Mobile Emission PM25 during year 2010

and its Influence on Respiratory Diagnoses

Zip Code 79905

Primary PM 25Tirewear

Mobile Emission

Heart Diseases Hospital

Admission

Exhaust Mobile Emission

PM10 kg Asthma-

Bronchitis)

Exhaust Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=769 Linear Square R=715

Dona Ana County Zip Codes

88021880278807288048

Primary

Exhaust

PM 10 Zip

code

79905

Total

Primary

Exhaust

PM10

Dona Ana

Primary

Exhaust

PM 25 Zip

Code

79905

Total

Primary

Exhaust

PM25

Dona Ana

Series1 430378 111773 391915 102123

0

100000

200000

300000

400000

500000

AX

IS T

ITLE

Annual Comparison of the Mobile

Exhaust Emissions El Paso County

and Dona Ana 2010

Primary

PM 10

Brakewea

r Zip code

79905

Brakewea

r

particulat

e_PM10

Dona Ana

Primary

PM 10

Tirewear

Zip code

79905

Tirewear

particulat

e_PM10

Dona Ana

Series1 262585 48573 73754 11864

050000

100000150000200000250000300000

AX

IS T

ITLE

Annual Comparison of the Mobile

Brakewear Emissions El Paso County

and Dona Ana 2010

Figure Comparison of the Annual Mobile Emissions

of Primary PM10 Non-Exhauts (Brake ) from Dona

Ana County New Mexico and El Paso Texas Units

in KgMonth

Figure Comparison of the Annual Mobile Emissions

of Primary PM10-Exhauts Emission from Dona Ana

County New Mexico and El Paso Texas Units in

KgMonth

Primary

PM 25

Brakewe

ar Ziphellip

Brakewe

ar

particula

te_PMhellip

Primary

PM

25Tirewe

ar Ziphellip

Tirewear

particula

te_PM25

Donahellip

Series1 32645 6071 10919 1779

0

10000

20000

30000

40000

AX

IS T

ITLE

Annual Comparison of the

Mobile Exhaust Emissions El Paso

County and Dona Ana 2010

Figure Comparison of the Annual Mobile Emissions

of Primary PM10-Exhauts Emission from Dona Ana

County New Mexico and El Paso Texas Units in

KgMonth

Monthly Mobile Emission PM1025 kg During year 2006

and its Influence on Respiratory Diagnoses Dona Ana

County Zip Code 880218802788072

0

100

200

300

0

5000

10000

15000

Axi

s Ti

tle

Axis Title

Monthly Mobile Exhaust Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Total PrimaryMobile Exhaust_PM10

All Respiratory ICD-9 (AsthmaBronchitis)

050100150200250300

010002000300040005000

Axi

s Ti

tle

Axis Title

Monthly Mobile Brake Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Brakewearparticulate_PM10

All RespiratoryICD -9 (AsthmaBronchitis)

050100150200250300

0200400600800

10001200

Axi

s Ti

tle

Axis Title

Monthly Mobile Tirewear Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Tirewearparticulate_PM10

All Respiratory ICD -9 (AsthmaBronchitis)

Mobile Exhauts

Emission PM10

kg Asthma-

Bronchitis)

Brake Mobile

Emission PM10

kg and Heart

Diagnoses

Tirewear Mobile

Emission PM10

kg and Heart

Diagnoses

Linear Square

R= 951

Linear Square

R=625

Linear Square

R=525

Mobile Exhauts

Emission PM25

kg Asthma-

Bronchitis)

Brake Mobile

Emission PM25

kg and Heart

Diagnoses

Tirewear Mobile

Emission PM25

kg and Heart

Diagnoses

Linear Square

R= 986

Linear Square

R=691

Linear Square

R=601

Results

The results showed that mobile PM emissions in the urban areas close to urban Road and highways is putting at risk public health

and the proportion of diseases attributable to this exposure is potentially large

Brake wear emissions is much lower in freeways due to significantly reduced number of braking events while tire wear is much

higher in areas where studded tires are used The emission of exhaust gases are much higher in areas where there is a high

vehicular traffic

Brake Mobile

Emission PM10 kg

Asthma-Bronchitis)

Brake Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square

R=969

Linear Square

R=856

Exhaust Mobile

Emission PM10 kg

Asthma-Bronchitis)

Exhaust Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square

R=929

Linear Square

R=831

Tirewear Mobile

Emission PM10 kg

Asthma-Bronchitis)

Tirewear Mobile

Emission PM25 kg

and Heart Diagnoses

Linear Square R=769 Linear Square R=715

Brake Mobile

Emission PM10 kg

and Heart

Diagnoses

Brake Mobile

Emission PM25 kg

and Heart

Diagnoses

Exhaust Mobile

Emission PM10 kg

Asthma-Bronchitis)

Linear Square

R=625

Linear Square

R=691

Linear Square R=

951

Exhaust Mobile

Emission PM25 kg

Asthma-

Bronchitis)

Tire wear Mobile

Emission PM10 kg and

Heart Diagnoses

Tirewear Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square R=

986

Linear Square R=525 Linear Square

R=601

El Paso County

Dona Ana

County

BenMAP-CE

In this analysis the Program of Mapping and Analysis of Environmental Benefits-Community Edition

(BenMAP-CE) was used to Estimate the number and economic value of health impacts resulting from changes

in air pollution PM 25 Ugm3 in The El Paso Area

Health and Economic Benefits associated with the Response of PM25 Emission between

Base Year 2010

Number of Mortalities in 2010 Base Year Based on El Paso County Texas Department of State Health Services

Number of Mortalities in 2010 Base Year Based on El Paso County Texas

Department of State Health Services

cause of death

year

2010

Populatio

n

Affected

Backgro

und

Concentr

ation Pollutant

Rollback

Type

Avoided

Deaths

(

Populatio

n)

alzheimers disease 2010 40716 125 PM25

25

microgmAcircsup3

Rollback 9

diseases of the

heart 2010 15834 125 PM25

25

microgmAcircsup3

Rollback 35

influenza and

neumonia 2010 81432 125 PM25

25

microgmAcircsup3

Rollback 18

acute bronchitis

and bronchiolitis 2010 117624 125 PM25

25

microgmAcircsup3

Rollback 26

chronic lower

respiratory diseases 2010 54288 125 PM25

25

microgmAcircsup3

Rollback 12

The Basin-wide decrease in 4 ugm3 PM25 concentration after this

reduction control

Cause of death year 2010

Populatio

n

Affected

Background

Concentrati

on

Reduc

cion

scena

rio Polluta

nt

Rollback

Type

Avoi

ded

Deat

hs

(

Pop

ulati

on)

economic

benefits

analysis $

Alzheimers

disease 2010 121 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 9 12000

Diseases of the

heart 2010 470 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 35 35000

Influenza and

neumonia 2010 242 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 18 42500

Acute bronchitis

and bronchiolitis 2010 349 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 26 95000

Chronic lower

respiratory

diseases 2010 161 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 12 4500

$1 295000

PM25-related Mortalities Based on BenMAP-CE Estimate in 2010 Base Year with change in the concentrations levels

Health and Economic Benefits associated with the Response of PM25 Emission between

Base Year 2010 Increasing 7 Ugm3

Cause of death year 2010

Population

Affected

Deaths

avoided by

attaining 195

μgm3

standard

Background

Concentrati

on

Pollut

ant

Rollback

Type

Avoided

Deaths (

Populatio

n)

econo

mic

Unben

efits

analysi

s

Alzheimers

disease 2010 4524 195 PM25

25

microgmAcircsup3

Rollback 19 150000

Diseases of the

heart 2010 20358 195 PM25

25

microgmAcircsup3

Rollback 135 450000

Influenza and

neumonia 2010 126672 195 PM25

25

microgmAcircsup3

Rollback 38 525000

Acute bronchitis

and bronchiolitis 2010 162864 195 PM25

25

microgmAcircsup3

Rollback 36 122000

Chronic lower

respiratory

diseases 2010 99528 195 PM25

25

microgmAcircsup3

Rollback 12 650000

Conclusions

An excellent Pearson Correlation was established to analyze the relationship in the relative risks of hospitalization of Respiratory(RD) and cardiovascular (CVD) associated with ambient exposure caused by traffic emission in relation to their size andspecific sources of emission on different scenarios interior a border Urban Rural Urban restricted access (freeways andinterstates)

A significant correlation of PM1025 exposure from mobile emission and hospital admissions for selected Respiratory (RD) andcardiovascular (CVD) diagnoses was established The results showed that PM emissions in urban restricted access (freeways andinterstates) is mainly caused by traffic Therefore people living close to highways are more exposed higher vehicular emissions

Conclusions

We found statistically significant associations between mobile PM25 caused by traffic emission with Respiratory and Cardiovascular Diseases in the study areaSubsequently a correlation between cardio-respiratory mortality is established

A significant correlation of PM1025 exposure from mobile emission and hospital admissions for selected Respiratory (RD) and cardiovascular (CVD) diagnoses isestablished The results showed that PM emissions in urban restricted access (freeways and interstates) is mainly caused by traffic Therefore people living close tohighways receive higher vehicular emissions

The table shows the percentage of PM mobile exposure in the analyzed areas contributing to increase the risk of Respiratory and Cardiovascular Diseases

An examination was conducted of the synoptic and local meteorology for the June 2006 ozone episode using the WRF model to determine how meteorological parametersinfluence the formation transport and dispersion of ozone in the PdN The predominant synoptic feature of the ozone event day was the expansion intensification and slowprogression of an upper-level ridge of high pressure The high ozone episodes are associated with highly stable atmospheres strong temperature inversions with low mixingheights and therefore low mixing volumes Under these conditions emissions such as NOx lead to highly polluted conditions that favor ozone formation

BenMAP Conclusions

We have estimated the number and economic value of health impacts resulting

from changes in air pollution concentrations of PM 25 in the PdN region

Reduction of Pm 25 4 UGm3= Avoided 213 cases respiratory cardiovascular

diseses and Economic Benefits associated with the Response of PM25 Emission + $

1295000

Increase of PM25 7 ugm3 = increasing Dies= 326 economic Unbenefits= 2345000$

Bibliography

1 Dockery DW Pope CAI Xu X Spengler JD Ware JH Fay ME Ferris BG Speizer FE An association between air pollution and mortality in six US cities N Engl J Med 3291753ndash1759 (1993)

2 Samet JM Dominici F Curriero FC Coursac I Zeger SL Fine particulate air pollution and mortality in 20 US cities 1987ndash1994 N Engl J Med 3431742ndash1749 (2000)

3 Nel AE Diaz-Sanchez D Li N The role of particulate pollutants in pulmonary inflammation and asthma evidence for the involvement of organic chemicals and oxidative stress Curr Opin Pulm Med 20017 20ndash26

4 Westerholm R Karl-Erik E Exhaust emissions from lightand heavy-duty vehicles chemical composition impact of exhaust after treatment and fuel parameters Environ Health Perspect 102(suppl 4)13ndash23 (1994)

5 Bascom R Bromberg P Costa D Delvin R Dockery D Frampton M Lambert W Samet J Speizer F Utell

6 Health effects of outdoor air pollution Am J Respir Crit Care Med 1533ndash50 (1996)

7 Chow JC Watson JG Frazier CA Egami RT Goodrich A Ralph C Spatial and temporal source contributions to

8 PM10 and PM25 in Reno NV In PM-10 Implementation of Standards Transactions An APCAEPA International Speciality Conference San Francisco CA (Mathal CV Stonefield DH eds) PittsburghAPCA 1988439ndash457

9 overview In Particulate Matter Health and Regulatory Issues VIP-49 Proceedings of an International Specialty Conference 4ndash6 April 1995 Pittsburgh PA PittsburghAir and Waste Management Association 1995577ndash598

10 Kunzli N Kaiser R Medina S Studnicka M Chanel O

11 Filliger P Herry M Horak F Jr Puybonnieux-Texier V Quenel P et al Public-health impact of outdoor and traffic- related air pollution a European assessment Lancet 356795ndash801 (2000)

Bibliography

1 Sioutas C Delfino RJ Singh M Exposure assessment for atmospheric ultrafine particles (UFP) and implications in epidemiological research Environ Health Perspect 2005113947ndash955

2 Mosleh M Blau PJ Dumitrescu D (2004) Characteristics and morphology of wear particles from laboratory testing of disc brake materials Wear 2561128ndash1134

3 Kuumlnzli N et al (2000) Public-health impact of outdoor and traffi c-related air pollution a European assessment Lancet 356(9232)795ndash801

4 Dora C Phillips M eds (2000) Transport environment and health Copenhagen WHO Regional Office for Europe (WHO Regional Publications European Series No 89 httpwwweurowhointdocumente72015pdf accessed 26 November 2004)

5 Westerholm R Karl-Erik E Exhaust emissions from lightand

6 heavy-duty vehicles chemical composition impact of exhaust after treatment and fuel parameters Environ Health Perspect 102(suppl 4)13ndash23 (1994)

7 Fauser Tjell Mosbaek pigegaard Quantification of tire-Tread particles using extractable Organic Zinc as a Tracer Rubber Chemistry and Technology 1999 969Table shows some literature estimates of the contribution of tire wear to PM10 in air (Panko et al 2013) Gustafsson M Blomqvist G Gudmundsson A Dahl A Swietlicki E Bohgard M Lindbom J Ljungman A

8 Chen Y Shah N Huggins FE and Huffman GP (2006) Microanalysis of Ambient Particles from Lexington Ky by Electron Microscopy Atmos Environ 40 651ndash663

9 Donaldson K Tran CL Jimenez LA Duffin R Newby DE and Mills N (2005) Combustion-derived Nanoparticles A Review of Their Toxicology Following Inhalation Exposure Part Fibre Toxicol 2 10ndash23

10 Su D Serafino A Muller JO Jentoft RE Schlogl R and Fiorito S (2008) Cytotoxicity and Inflammatory Potential of Soot Particles of Low-emission Diesel Engines Environ Sci Technol 42 1761ndash1765

11 Maier KL Alessandrini F Beck-Speier I Hofer TPJ Diabatґe S Bitterle E Stoger T and Jakob T (2008) Health Effects of Ambient Particulate Matter-Biological Mechanisms and Inflammatory Responses to in Vitroand in Vivo Particle Exposures Inhalation Toxicol 20 319ndash337

Page 44: Studies of Air Pollutants and their Impact on Respiratory and ...€¦ · Ascarate Park C37 Monitoring Station: The National Ambient Air Quality Standard (NAAQS) for PM 10 and 2.5

Monthly Tire wear Mobile Emission PM1025 During year 2010 and its Influence on Heart

Diagnoses Zip Code 79905

0

100

200

300

400

500

600

700

800

900

0

1000

2000

3000

4000

5000

6000

7000

8000

9000

1 2 3 4 5 6 7 8 9 10 11 12

PM

10

(K

g m

on

th)

Months

Monthly Tirewear Mobile Emission PM10 during year 2010

and its Influence on Heart Diagnoses

Zip Code 79905

Primary PM 10 Tirewear

Mobile Emission

Respiratory Disease

(Asthma Bronchitis)

Hospital Admission

0

100

200

300

400

500

600

0

200

400

600

800

1000

1200

1400

1 2 3 4 5 6 7 8 9 10 11 12

PM

25

(K

g m

on

th)

Months

Monthly Tirewear Mobile Emission PM25 during year 2010

and its Influence on Respiratory Diagnoses

Zip Code 79905

Primary PM 25Tirewear

Mobile Emission

Heart Diseases Hospital

Admission

Exhaust Mobile Emission

PM10 kg Asthma-

Bronchitis)

Exhaust Mobile Emission

PM25 kg and Heart

Diagnoses

Linear Square R=769 Linear Square R=715

Dona Ana County Zip Codes

88021880278807288048

Primary

Exhaust

PM 10 Zip

code

79905

Total

Primary

Exhaust

PM10

Dona Ana

Primary

Exhaust

PM 25 Zip

Code

79905

Total

Primary

Exhaust

PM25

Dona Ana

Series1 430378 111773 391915 102123

0

100000

200000

300000

400000

500000

AX

IS T

ITLE

Annual Comparison of the Mobile

Exhaust Emissions El Paso County

and Dona Ana 2010

Primary

PM 10

Brakewea

r Zip code

79905

Brakewea

r

particulat

e_PM10

Dona Ana

Primary

PM 10

Tirewear

Zip code

79905

Tirewear

particulat

e_PM10

Dona Ana

Series1 262585 48573 73754 11864

050000

100000150000200000250000300000

AX

IS T

ITLE

Annual Comparison of the Mobile

Brakewear Emissions El Paso County

and Dona Ana 2010

Figure Comparison of the Annual Mobile Emissions

of Primary PM10 Non-Exhauts (Brake ) from Dona

Ana County New Mexico and El Paso Texas Units

in KgMonth

Figure Comparison of the Annual Mobile Emissions

of Primary PM10-Exhauts Emission from Dona Ana

County New Mexico and El Paso Texas Units in

KgMonth

Primary

PM 25

Brakewe

ar Ziphellip

Brakewe

ar

particula

te_PMhellip

Primary

PM

25Tirewe

ar Ziphellip

Tirewear

particula

te_PM25

Donahellip

Series1 32645 6071 10919 1779

0

10000

20000

30000

40000

AX

IS T

ITLE

Annual Comparison of the

Mobile Exhaust Emissions El Paso

County and Dona Ana 2010

Figure Comparison of the Annual Mobile Emissions

of Primary PM10-Exhauts Emission from Dona Ana

County New Mexico and El Paso Texas Units in

KgMonth

Monthly Mobile Emission PM1025 kg During year 2006

and its Influence on Respiratory Diagnoses Dona Ana

County Zip Code 880218802788072

0

100

200

300

0

5000

10000

15000

Axi

s Ti

tle

Axis Title

Monthly Mobile Exhaust Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Total PrimaryMobile Exhaust_PM10

All Respiratory ICD-9 (AsthmaBronchitis)

050100150200250300

010002000300040005000

Axi

s Ti

tle

Axis Title

Monthly Mobile Brake Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Brakewearparticulate_PM10

All RespiratoryICD -9 (AsthmaBronchitis)

050100150200250300

0200400600800

10001200

Axi

s Ti

tle

Axis Title

Monthly Mobile Tirewear Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Tirewearparticulate_PM10

All Respiratory ICD -9 (AsthmaBronchitis)

Mobile Exhauts

Emission PM10

kg Asthma-

Bronchitis)

Brake Mobile

Emission PM10

kg and Heart

Diagnoses

Tirewear Mobile

Emission PM10

kg and Heart

Diagnoses

Linear Square

R= 951

Linear Square

R=625

Linear Square

R=525

Mobile Exhauts

Emission PM25

kg Asthma-

Bronchitis)

Brake Mobile

Emission PM25

kg and Heart

Diagnoses

Tirewear Mobile

Emission PM25

kg and Heart

Diagnoses

Linear Square

R= 986

Linear Square

R=691

Linear Square

R=601

Results

The results showed that mobile PM emissions in the urban areas close to urban Road and highways is putting at risk public health

and the proportion of diseases attributable to this exposure is potentially large

Brake wear emissions is much lower in freeways due to significantly reduced number of braking events while tire wear is much

higher in areas where studded tires are used The emission of exhaust gases are much higher in areas where there is a high

vehicular traffic

Brake Mobile

Emission PM10 kg

Asthma-Bronchitis)

Brake Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square

R=969

Linear Square

R=856

Exhaust Mobile

Emission PM10 kg

Asthma-Bronchitis)

Exhaust Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square

R=929

Linear Square

R=831

Tirewear Mobile

Emission PM10 kg

Asthma-Bronchitis)

Tirewear Mobile

Emission PM25 kg

and Heart Diagnoses

Linear Square R=769 Linear Square R=715

Brake Mobile

Emission PM10 kg

and Heart

Diagnoses

Brake Mobile

Emission PM25 kg

and Heart

Diagnoses

Exhaust Mobile

Emission PM10 kg

Asthma-Bronchitis)

Linear Square

R=625

Linear Square

R=691

Linear Square R=

951

Exhaust Mobile

Emission PM25 kg

Asthma-

Bronchitis)

Tire wear Mobile

Emission PM10 kg and

Heart Diagnoses

Tirewear Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square R=

986

Linear Square R=525 Linear Square

R=601

El Paso County

Dona Ana

County

BenMAP-CE

In this analysis the Program of Mapping and Analysis of Environmental Benefits-Community Edition

(BenMAP-CE) was used to Estimate the number and economic value of health impacts resulting from changes

in air pollution PM 25 Ugm3 in The El Paso Area

Health and Economic Benefits associated with the Response of PM25 Emission between

Base Year 2010

Number of Mortalities in 2010 Base Year Based on El Paso County Texas Department of State Health Services

Number of Mortalities in 2010 Base Year Based on El Paso County Texas

Department of State Health Services

cause of death

year

2010

Populatio

n

Affected

Backgro

und

Concentr

ation Pollutant

Rollback

Type

Avoided

Deaths

(

Populatio

n)

alzheimers disease 2010 40716 125 PM25

25

microgmAcircsup3

Rollback 9

diseases of the

heart 2010 15834 125 PM25

25

microgmAcircsup3

Rollback 35

influenza and

neumonia 2010 81432 125 PM25

25

microgmAcircsup3

Rollback 18

acute bronchitis

and bronchiolitis 2010 117624 125 PM25

25

microgmAcircsup3

Rollback 26

chronic lower

respiratory diseases 2010 54288 125 PM25

25

microgmAcircsup3

Rollback 12

The Basin-wide decrease in 4 ugm3 PM25 concentration after this

reduction control

Cause of death year 2010

Populatio

n

Affected

Background

Concentrati

on

Reduc

cion

scena

rio Polluta

nt

Rollback

Type

Avoi

ded

Deat

hs

(

Pop

ulati

on)

economic

benefits

analysis $

Alzheimers

disease 2010 121 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 9 12000

Diseases of the

heart 2010 470 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 35 35000

Influenza and

neumonia 2010 242 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 18 42500

Acute bronchitis

and bronchiolitis 2010 349 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 26 95000

Chronic lower

respiratory

diseases 2010 161 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 12 4500

$1 295000

PM25-related Mortalities Based on BenMAP-CE Estimate in 2010 Base Year with change in the concentrations levels

Health and Economic Benefits associated with the Response of PM25 Emission between

Base Year 2010 Increasing 7 Ugm3

Cause of death year 2010

Population

Affected

Deaths

avoided by

attaining 195

μgm3

standard

Background

Concentrati

on

Pollut

ant

Rollback

Type

Avoided

Deaths (

Populatio

n)

econo

mic

Unben

efits

analysi

s

Alzheimers

disease 2010 4524 195 PM25

25

microgmAcircsup3

Rollback 19 150000

Diseases of the

heart 2010 20358 195 PM25

25

microgmAcircsup3

Rollback 135 450000

Influenza and

neumonia 2010 126672 195 PM25

25

microgmAcircsup3

Rollback 38 525000

Acute bronchitis

and bronchiolitis 2010 162864 195 PM25

25

microgmAcircsup3

Rollback 36 122000

Chronic lower

respiratory

diseases 2010 99528 195 PM25

25

microgmAcircsup3

Rollback 12 650000

Conclusions

An excellent Pearson Correlation was established to analyze the relationship in the relative risks of hospitalization of Respiratory(RD) and cardiovascular (CVD) associated with ambient exposure caused by traffic emission in relation to their size andspecific sources of emission on different scenarios interior a border Urban Rural Urban restricted access (freeways andinterstates)

A significant correlation of PM1025 exposure from mobile emission and hospital admissions for selected Respiratory (RD) andcardiovascular (CVD) diagnoses was established The results showed that PM emissions in urban restricted access (freeways andinterstates) is mainly caused by traffic Therefore people living close to highways are more exposed higher vehicular emissions

Conclusions

We found statistically significant associations between mobile PM25 caused by traffic emission with Respiratory and Cardiovascular Diseases in the study areaSubsequently a correlation between cardio-respiratory mortality is established

A significant correlation of PM1025 exposure from mobile emission and hospital admissions for selected Respiratory (RD) and cardiovascular (CVD) diagnoses isestablished The results showed that PM emissions in urban restricted access (freeways and interstates) is mainly caused by traffic Therefore people living close tohighways receive higher vehicular emissions

The table shows the percentage of PM mobile exposure in the analyzed areas contributing to increase the risk of Respiratory and Cardiovascular Diseases

An examination was conducted of the synoptic and local meteorology for the June 2006 ozone episode using the WRF model to determine how meteorological parametersinfluence the formation transport and dispersion of ozone in the PdN The predominant synoptic feature of the ozone event day was the expansion intensification and slowprogression of an upper-level ridge of high pressure The high ozone episodes are associated with highly stable atmospheres strong temperature inversions with low mixingheights and therefore low mixing volumes Under these conditions emissions such as NOx lead to highly polluted conditions that favor ozone formation

BenMAP Conclusions

We have estimated the number and economic value of health impacts resulting

from changes in air pollution concentrations of PM 25 in the PdN region

Reduction of Pm 25 4 UGm3= Avoided 213 cases respiratory cardiovascular

diseses and Economic Benefits associated with the Response of PM25 Emission + $

1295000

Increase of PM25 7 ugm3 = increasing Dies= 326 economic Unbenefits= 2345000$

Bibliography

1 Dockery DW Pope CAI Xu X Spengler JD Ware JH Fay ME Ferris BG Speizer FE An association between air pollution and mortality in six US cities N Engl J Med 3291753ndash1759 (1993)

2 Samet JM Dominici F Curriero FC Coursac I Zeger SL Fine particulate air pollution and mortality in 20 US cities 1987ndash1994 N Engl J Med 3431742ndash1749 (2000)

3 Nel AE Diaz-Sanchez D Li N The role of particulate pollutants in pulmonary inflammation and asthma evidence for the involvement of organic chemicals and oxidative stress Curr Opin Pulm Med 20017 20ndash26

4 Westerholm R Karl-Erik E Exhaust emissions from lightand heavy-duty vehicles chemical composition impact of exhaust after treatment and fuel parameters Environ Health Perspect 102(suppl 4)13ndash23 (1994)

5 Bascom R Bromberg P Costa D Delvin R Dockery D Frampton M Lambert W Samet J Speizer F Utell

6 Health effects of outdoor air pollution Am J Respir Crit Care Med 1533ndash50 (1996)

7 Chow JC Watson JG Frazier CA Egami RT Goodrich A Ralph C Spatial and temporal source contributions to

8 PM10 and PM25 in Reno NV In PM-10 Implementation of Standards Transactions An APCAEPA International Speciality Conference San Francisco CA (Mathal CV Stonefield DH eds) PittsburghAPCA 1988439ndash457

9 overview In Particulate Matter Health and Regulatory Issues VIP-49 Proceedings of an International Specialty Conference 4ndash6 April 1995 Pittsburgh PA PittsburghAir and Waste Management Association 1995577ndash598

10 Kunzli N Kaiser R Medina S Studnicka M Chanel O

11 Filliger P Herry M Horak F Jr Puybonnieux-Texier V Quenel P et al Public-health impact of outdoor and traffic- related air pollution a European assessment Lancet 356795ndash801 (2000)

Bibliography

1 Sioutas C Delfino RJ Singh M Exposure assessment for atmospheric ultrafine particles (UFP) and implications in epidemiological research Environ Health Perspect 2005113947ndash955

2 Mosleh M Blau PJ Dumitrescu D (2004) Characteristics and morphology of wear particles from laboratory testing of disc brake materials Wear 2561128ndash1134

3 Kuumlnzli N et al (2000) Public-health impact of outdoor and traffi c-related air pollution a European assessment Lancet 356(9232)795ndash801

4 Dora C Phillips M eds (2000) Transport environment and health Copenhagen WHO Regional Office for Europe (WHO Regional Publications European Series No 89 httpwwweurowhointdocumente72015pdf accessed 26 November 2004)

5 Westerholm R Karl-Erik E Exhaust emissions from lightand

6 heavy-duty vehicles chemical composition impact of exhaust after treatment and fuel parameters Environ Health Perspect 102(suppl 4)13ndash23 (1994)

7 Fauser Tjell Mosbaek pigegaard Quantification of tire-Tread particles using extractable Organic Zinc as a Tracer Rubber Chemistry and Technology 1999 969Table shows some literature estimates of the contribution of tire wear to PM10 in air (Panko et al 2013) Gustafsson M Blomqvist G Gudmundsson A Dahl A Swietlicki E Bohgard M Lindbom J Ljungman A

8 Chen Y Shah N Huggins FE and Huffman GP (2006) Microanalysis of Ambient Particles from Lexington Ky by Electron Microscopy Atmos Environ 40 651ndash663

9 Donaldson K Tran CL Jimenez LA Duffin R Newby DE and Mills N (2005) Combustion-derived Nanoparticles A Review of Their Toxicology Following Inhalation Exposure Part Fibre Toxicol 2 10ndash23

10 Su D Serafino A Muller JO Jentoft RE Schlogl R and Fiorito S (2008) Cytotoxicity and Inflammatory Potential of Soot Particles of Low-emission Diesel Engines Environ Sci Technol 42 1761ndash1765

11 Maier KL Alessandrini F Beck-Speier I Hofer TPJ Diabatґe S Bitterle E Stoger T and Jakob T (2008) Health Effects of Ambient Particulate Matter-Biological Mechanisms and Inflammatory Responses to in Vitroand in Vivo Particle Exposures Inhalation Toxicol 20 319ndash337

Page 45: Studies of Air Pollutants and their Impact on Respiratory and ...€¦ · Ascarate Park C37 Monitoring Station: The National Ambient Air Quality Standard (NAAQS) for PM 10 and 2.5

Dona Ana County Zip Codes

88021880278807288048

Primary

Exhaust

PM 10 Zip

code

79905

Total

Primary

Exhaust

PM10

Dona Ana

Primary

Exhaust

PM 25 Zip

Code

79905

Total

Primary

Exhaust

PM25

Dona Ana

Series1 430378 111773 391915 102123

0

100000

200000

300000

400000

500000

AX

IS T

ITLE

Annual Comparison of the Mobile

Exhaust Emissions El Paso County

and Dona Ana 2010

Primary

PM 10

Brakewea

r Zip code

79905

Brakewea

r

particulat

e_PM10

Dona Ana

Primary

PM 10

Tirewear

Zip code

79905

Tirewear

particulat

e_PM10

Dona Ana

Series1 262585 48573 73754 11864

050000

100000150000200000250000300000

AX

IS T

ITLE

Annual Comparison of the Mobile

Brakewear Emissions El Paso County

and Dona Ana 2010

Figure Comparison of the Annual Mobile Emissions

of Primary PM10 Non-Exhauts (Brake ) from Dona

Ana County New Mexico and El Paso Texas Units

in KgMonth

Figure Comparison of the Annual Mobile Emissions

of Primary PM10-Exhauts Emission from Dona Ana

County New Mexico and El Paso Texas Units in

KgMonth

Primary

PM 25

Brakewe

ar Ziphellip

Brakewe

ar

particula

te_PMhellip

Primary

PM

25Tirewe

ar Ziphellip

Tirewear

particula

te_PM25

Donahellip

Series1 32645 6071 10919 1779

0

10000

20000

30000

40000

AX

IS T

ITLE

Annual Comparison of the

Mobile Exhaust Emissions El Paso

County and Dona Ana 2010

Figure Comparison of the Annual Mobile Emissions

of Primary PM10-Exhauts Emission from Dona Ana

County New Mexico and El Paso Texas Units in

KgMonth

Monthly Mobile Emission PM1025 kg During year 2006

and its Influence on Respiratory Diagnoses Dona Ana

County Zip Code 880218802788072

0

100

200

300

0

5000

10000

15000

Axi

s Ti

tle

Axis Title

Monthly Mobile Exhaust Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Total PrimaryMobile Exhaust_PM10

All Respiratory ICD-9 (AsthmaBronchitis)

050100150200250300

010002000300040005000

Axi

s Ti

tle

Axis Title

Monthly Mobile Brake Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Brakewearparticulate_PM10

All RespiratoryICD -9 (AsthmaBronchitis)

050100150200250300

0200400600800

10001200

Axi

s Ti

tle

Axis Title

Monthly Mobile Tirewear Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Tirewearparticulate_PM10

All Respiratory ICD -9 (AsthmaBronchitis)

Mobile Exhauts

Emission PM10

kg Asthma-

Bronchitis)

Brake Mobile

Emission PM10

kg and Heart

Diagnoses

Tirewear Mobile

Emission PM10

kg and Heart

Diagnoses

Linear Square

R= 951

Linear Square

R=625

Linear Square

R=525

Mobile Exhauts

Emission PM25

kg Asthma-

Bronchitis)

Brake Mobile

Emission PM25

kg and Heart

Diagnoses

Tirewear Mobile

Emission PM25

kg and Heart

Diagnoses

Linear Square

R= 986

Linear Square

R=691

Linear Square

R=601

Results

The results showed that mobile PM emissions in the urban areas close to urban Road and highways is putting at risk public health

and the proportion of diseases attributable to this exposure is potentially large

Brake wear emissions is much lower in freeways due to significantly reduced number of braking events while tire wear is much

higher in areas where studded tires are used The emission of exhaust gases are much higher in areas where there is a high

vehicular traffic

Brake Mobile

Emission PM10 kg

Asthma-Bronchitis)

Brake Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square

R=969

Linear Square

R=856

Exhaust Mobile

Emission PM10 kg

Asthma-Bronchitis)

Exhaust Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square

R=929

Linear Square

R=831

Tirewear Mobile

Emission PM10 kg

Asthma-Bronchitis)

Tirewear Mobile

Emission PM25 kg

and Heart Diagnoses

Linear Square R=769 Linear Square R=715

Brake Mobile

Emission PM10 kg

and Heart

Diagnoses

Brake Mobile

Emission PM25 kg

and Heart

Diagnoses

Exhaust Mobile

Emission PM10 kg

Asthma-Bronchitis)

Linear Square

R=625

Linear Square

R=691

Linear Square R=

951

Exhaust Mobile

Emission PM25 kg

Asthma-

Bronchitis)

Tire wear Mobile

Emission PM10 kg and

Heart Diagnoses

Tirewear Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square R=

986

Linear Square R=525 Linear Square

R=601

El Paso County

Dona Ana

County

BenMAP-CE

In this analysis the Program of Mapping and Analysis of Environmental Benefits-Community Edition

(BenMAP-CE) was used to Estimate the number and economic value of health impacts resulting from changes

in air pollution PM 25 Ugm3 in The El Paso Area

Health and Economic Benefits associated with the Response of PM25 Emission between

Base Year 2010

Number of Mortalities in 2010 Base Year Based on El Paso County Texas Department of State Health Services

Number of Mortalities in 2010 Base Year Based on El Paso County Texas

Department of State Health Services

cause of death

year

2010

Populatio

n

Affected

Backgro

und

Concentr

ation Pollutant

Rollback

Type

Avoided

Deaths

(

Populatio

n)

alzheimers disease 2010 40716 125 PM25

25

microgmAcircsup3

Rollback 9

diseases of the

heart 2010 15834 125 PM25

25

microgmAcircsup3

Rollback 35

influenza and

neumonia 2010 81432 125 PM25

25

microgmAcircsup3

Rollback 18

acute bronchitis

and bronchiolitis 2010 117624 125 PM25

25

microgmAcircsup3

Rollback 26

chronic lower

respiratory diseases 2010 54288 125 PM25

25

microgmAcircsup3

Rollback 12

The Basin-wide decrease in 4 ugm3 PM25 concentration after this

reduction control

Cause of death year 2010

Populatio

n

Affected

Background

Concentrati

on

Reduc

cion

scena

rio Polluta

nt

Rollback

Type

Avoi

ded

Deat

hs

(

Pop

ulati

on)

economic

benefits

analysis $

Alzheimers

disease 2010 121 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 9 12000

Diseases of the

heart 2010 470 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 35 35000

Influenza and

neumonia 2010 242 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 18 42500

Acute bronchitis

and bronchiolitis 2010 349 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 26 95000

Chronic lower

respiratory

diseases 2010 161 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 12 4500

$1 295000

PM25-related Mortalities Based on BenMAP-CE Estimate in 2010 Base Year with change in the concentrations levels

Health and Economic Benefits associated with the Response of PM25 Emission between

Base Year 2010 Increasing 7 Ugm3

Cause of death year 2010

Population

Affected

Deaths

avoided by

attaining 195

μgm3

standard

Background

Concentrati

on

Pollut

ant

Rollback

Type

Avoided

Deaths (

Populatio

n)

econo

mic

Unben

efits

analysi

s

Alzheimers

disease 2010 4524 195 PM25

25

microgmAcircsup3

Rollback 19 150000

Diseases of the

heart 2010 20358 195 PM25

25

microgmAcircsup3

Rollback 135 450000

Influenza and

neumonia 2010 126672 195 PM25

25

microgmAcircsup3

Rollback 38 525000

Acute bronchitis

and bronchiolitis 2010 162864 195 PM25

25

microgmAcircsup3

Rollback 36 122000

Chronic lower

respiratory

diseases 2010 99528 195 PM25

25

microgmAcircsup3

Rollback 12 650000

Conclusions

An excellent Pearson Correlation was established to analyze the relationship in the relative risks of hospitalization of Respiratory(RD) and cardiovascular (CVD) associated with ambient exposure caused by traffic emission in relation to their size andspecific sources of emission on different scenarios interior a border Urban Rural Urban restricted access (freeways andinterstates)

A significant correlation of PM1025 exposure from mobile emission and hospital admissions for selected Respiratory (RD) andcardiovascular (CVD) diagnoses was established The results showed that PM emissions in urban restricted access (freeways andinterstates) is mainly caused by traffic Therefore people living close to highways are more exposed higher vehicular emissions

Conclusions

We found statistically significant associations between mobile PM25 caused by traffic emission with Respiratory and Cardiovascular Diseases in the study areaSubsequently a correlation between cardio-respiratory mortality is established

A significant correlation of PM1025 exposure from mobile emission and hospital admissions for selected Respiratory (RD) and cardiovascular (CVD) diagnoses isestablished The results showed that PM emissions in urban restricted access (freeways and interstates) is mainly caused by traffic Therefore people living close tohighways receive higher vehicular emissions

The table shows the percentage of PM mobile exposure in the analyzed areas contributing to increase the risk of Respiratory and Cardiovascular Diseases

An examination was conducted of the synoptic and local meteorology for the June 2006 ozone episode using the WRF model to determine how meteorological parametersinfluence the formation transport and dispersion of ozone in the PdN The predominant synoptic feature of the ozone event day was the expansion intensification and slowprogression of an upper-level ridge of high pressure The high ozone episodes are associated with highly stable atmospheres strong temperature inversions with low mixingheights and therefore low mixing volumes Under these conditions emissions such as NOx lead to highly polluted conditions that favor ozone formation

BenMAP Conclusions

We have estimated the number and economic value of health impacts resulting

from changes in air pollution concentrations of PM 25 in the PdN region

Reduction of Pm 25 4 UGm3= Avoided 213 cases respiratory cardiovascular

diseses and Economic Benefits associated with the Response of PM25 Emission + $

1295000

Increase of PM25 7 ugm3 = increasing Dies= 326 economic Unbenefits= 2345000$

Bibliography

1 Dockery DW Pope CAI Xu X Spengler JD Ware JH Fay ME Ferris BG Speizer FE An association between air pollution and mortality in six US cities N Engl J Med 3291753ndash1759 (1993)

2 Samet JM Dominici F Curriero FC Coursac I Zeger SL Fine particulate air pollution and mortality in 20 US cities 1987ndash1994 N Engl J Med 3431742ndash1749 (2000)

3 Nel AE Diaz-Sanchez D Li N The role of particulate pollutants in pulmonary inflammation and asthma evidence for the involvement of organic chemicals and oxidative stress Curr Opin Pulm Med 20017 20ndash26

4 Westerholm R Karl-Erik E Exhaust emissions from lightand heavy-duty vehicles chemical composition impact of exhaust after treatment and fuel parameters Environ Health Perspect 102(suppl 4)13ndash23 (1994)

5 Bascom R Bromberg P Costa D Delvin R Dockery D Frampton M Lambert W Samet J Speizer F Utell

6 Health effects of outdoor air pollution Am J Respir Crit Care Med 1533ndash50 (1996)

7 Chow JC Watson JG Frazier CA Egami RT Goodrich A Ralph C Spatial and temporal source contributions to

8 PM10 and PM25 in Reno NV In PM-10 Implementation of Standards Transactions An APCAEPA International Speciality Conference San Francisco CA (Mathal CV Stonefield DH eds) PittsburghAPCA 1988439ndash457

9 overview In Particulate Matter Health and Regulatory Issues VIP-49 Proceedings of an International Specialty Conference 4ndash6 April 1995 Pittsburgh PA PittsburghAir and Waste Management Association 1995577ndash598

10 Kunzli N Kaiser R Medina S Studnicka M Chanel O

11 Filliger P Herry M Horak F Jr Puybonnieux-Texier V Quenel P et al Public-health impact of outdoor and traffic- related air pollution a European assessment Lancet 356795ndash801 (2000)

Bibliography

1 Sioutas C Delfino RJ Singh M Exposure assessment for atmospheric ultrafine particles (UFP) and implications in epidemiological research Environ Health Perspect 2005113947ndash955

2 Mosleh M Blau PJ Dumitrescu D (2004) Characteristics and morphology of wear particles from laboratory testing of disc brake materials Wear 2561128ndash1134

3 Kuumlnzli N et al (2000) Public-health impact of outdoor and traffi c-related air pollution a European assessment Lancet 356(9232)795ndash801

4 Dora C Phillips M eds (2000) Transport environment and health Copenhagen WHO Regional Office for Europe (WHO Regional Publications European Series No 89 httpwwweurowhointdocumente72015pdf accessed 26 November 2004)

5 Westerholm R Karl-Erik E Exhaust emissions from lightand

6 heavy-duty vehicles chemical composition impact of exhaust after treatment and fuel parameters Environ Health Perspect 102(suppl 4)13ndash23 (1994)

7 Fauser Tjell Mosbaek pigegaard Quantification of tire-Tread particles using extractable Organic Zinc as a Tracer Rubber Chemistry and Technology 1999 969Table shows some literature estimates of the contribution of tire wear to PM10 in air (Panko et al 2013) Gustafsson M Blomqvist G Gudmundsson A Dahl A Swietlicki E Bohgard M Lindbom J Ljungman A

8 Chen Y Shah N Huggins FE and Huffman GP (2006) Microanalysis of Ambient Particles from Lexington Ky by Electron Microscopy Atmos Environ 40 651ndash663

9 Donaldson K Tran CL Jimenez LA Duffin R Newby DE and Mills N (2005) Combustion-derived Nanoparticles A Review of Their Toxicology Following Inhalation Exposure Part Fibre Toxicol 2 10ndash23

10 Su D Serafino A Muller JO Jentoft RE Schlogl R and Fiorito S (2008) Cytotoxicity and Inflammatory Potential of Soot Particles of Low-emission Diesel Engines Environ Sci Technol 42 1761ndash1765

11 Maier KL Alessandrini F Beck-Speier I Hofer TPJ Diabatґe S Bitterle E Stoger T and Jakob T (2008) Health Effects of Ambient Particulate Matter-Biological Mechanisms and Inflammatory Responses to in Vitroand in Vivo Particle Exposures Inhalation Toxicol 20 319ndash337

Page 46: Studies of Air Pollutants and their Impact on Respiratory and ...€¦ · Ascarate Park C37 Monitoring Station: The National Ambient Air Quality Standard (NAAQS) for PM 10 and 2.5

Monthly Mobile Emission PM1025 kg During year 2006

and its Influence on Respiratory Diagnoses Dona Ana

County Zip Code 880218802788072

0

100

200

300

0

5000

10000

15000

Axi

s Ti

tle

Axis Title

Monthly Mobile Exhaust Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Total PrimaryMobile Exhaust_PM10

All Respiratory ICD-9 (AsthmaBronchitis)

050100150200250300

010002000300040005000

Axi

s Ti

tle

Axis Title

Monthly Mobile Brake Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Brakewearparticulate_PM10

All RespiratoryICD -9 (AsthmaBronchitis)

050100150200250300

0200400600800

10001200

Axi

s Ti

tle

Axis Title

Monthly Mobile Tirewear Emission PM10 during year 2006 and its Influence on Respiratory Diagnoses

Zip Code 880218802788072

Tirewearparticulate_PM10

All Respiratory ICD -9 (AsthmaBronchitis)

Mobile Exhauts

Emission PM10

kg Asthma-

Bronchitis)

Brake Mobile

Emission PM10

kg and Heart

Diagnoses

Tirewear Mobile

Emission PM10

kg and Heart

Diagnoses

Linear Square

R= 951

Linear Square

R=625

Linear Square

R=525

Mobile Exhauts

Emission PM25

kg Asthma-

Bronchitis)

Brake Mobile

Emission PM25

kg and Heart

Diagnoses

Tirewear Mobile

Emission PM25

kg and Heart

Diagnoses

Linear Square

R= 986

Linear Square

R=691

Linear Square

R=601

Results

The results showed that mobile PM emissions in the urban areas close to urban Road and highways is putting at risk public health

and the proportion of diseases attributable to this exposure is potentially large

Brake wear emissions is much lower in freeways due to significantly reduced number of braking events while tire wear is much

higher in areas where studded tires are used The emission of exhaust gases are much higher in areas where there is a high

vehicular traffic

Brake Mobile

Emission PM10 kg

Asthma-Bronchitis)

Brake Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square

R=969

Linear Square

R=856

Exhaust Mobile

Emission PM10 kg

Asthma-Bronchitis)

Exhaust Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square

R=929

Linear Square

R=831

Tirewear Mobile

Emission PM10 kg

Asthma-Bronchitis)

Tirewear Mobile

Emission PM25 kg

and Heart Diagnoses

Linear Square R=769 Linear Square R=715

Brake Mobile

Emission PM10 kg

and Heart

Diagnoses

Brake Mobile

Emission PM25 kg

and Heart

Diagnoses

Exhaust Mobile

Emission PM10 kg

Asthma-Bronchitis)

Linear Square

R=625

Linear Square

R=691

Linear Square R=

951

Exhaust Mobile

Emission PM25 kg

Asthma-

Bronchitis)

Tire wear Mobile

Emission PM10 kg and

Heart Diagnoses

Tirewear Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square R=

986

Linear Square R=525 Linear Square

R=601

El Paso County

Dona Ana

County

BenMAP-CE

In this analysis the Program of Mapping and Analysis of Environmental Benefits-Community Edition

(BenMAP-CE) was used to Estimate the number and economic value of health impacts resulting from changes

in air pollution PM 25 Ugm3 in The El Paso Area

Health and Economic Benefits associated with the Response of PM25 Emission between

Base Year 2010

Number of Mortalities in 2010 Base Year Based on El Paso County Texas Department of State Health Services

Number of Mortalities in 2010 Base Year Based on El Paso County Texas

Department of State Health Services

cause of death

year

2010

Populatio

n

Affected

Backgro

und

Concentr

ation Pollutant

Rollback

Type

Avoided

Deaths

(

Populatio

n)

alzheimers disease 2010 40716 125 PM25

25

microgmAcircsup3

Rollback 9

diseases of the

heart 2010 15834 125 PM25

25

microgmAcircsup3

Rollback 35

influenza and

neumonia 2010 81432 125 PM25

25

microgmAcircsup3

Rollback 18

acute bronchitis

and bronchiolitis 2010 117624 125 PM25

25

microgmAcircsup3

Rollback 26

chronic lower

respiratory diseases 2010 54288 125 PM25

25

microgmAcircsup3

Rollback 12

The Basin-wide decrease in 4 ugm3 PM25 concentration after this

reduction control

Cause of death year 2010

Populatio

n

Affected

Background

Concentrati

on

Reduc

cion

scena

rio Polluta

nt

Rollback

Type

Avoi

ded

Deat

hs

(

Pop

ulati

on)

economic

benefits

analysis $

Alzheimers

disease 2010 121 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 9 12000

Diseases of the

heart 2010 470 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 35 35000

Influenza and

neumonia 2010 242 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 18 42500

Acute bronchitis

and bronchiolitis 2010 349 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 26 95000

Chronic lower

respiratory

diseases 2010 161 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 12 4500

$1 295000

PM25-related Mortalities Based on BenMAP-CE Estimate in 2010 Base Year with change in the concentrations levels

Health and Economic Benefits associated with the Response of PM25 Emission between

Base Year 2010 Increasing 7 Ugm3

Cause of death year 2010

Population

Affected

Deaths

avoided by

attaining 195

μgm3

standard

Background

Concentrati

on

Pollut

ant

Rollback

Type

Avoided

Deaths (

Populatio

n)

econo

mic

Unben

efits

analysi

s

Alzheimers

disease 2010 4524 195 PM25

25

microgmAcircsup3

Rollback 19 150000

Diseases of the

heart 2010 20358 195 PM25

25

microgmAcircsup3

Rollback 135 450000

Influenza and

neumonia 2010 126672 195 PM25

25

microgmAcircsup3

Rollback 38 525000

Acute bronchitis

and bronchiolitis 2010 162864 195 PM25

25

microgmAcircsup3

Rollback 36 122000

Chronic lower

respiratory

diseases 2010 99528 195 PM25

25

microgmAcircsup3

Rollback 12 650000

Conclusions

An excellent Pearson Correlation was established to analyze the relationship in the relative risks of hospitalization of Respiratory(RD) and cardiovascular (CVD) associated with ambient exposure caused by traffic emission in relation to their size andspecific sources of emission on different scenarios interior a border Urban Rural Urban restricted access (freeways andinterstates)

A significant correlation of PM1025 exposure from mobile emission and hospital admissions for selected Respiratory (RD) andcardiovascular (CVD) diagnoses was established The results showed that PM emissions in urban restricted access (freeways andinterstates) is mainly caused by traffic Therefore people living close to highways are more exposed higher vehicular emissions

Conclusions

We found statistically significant associations between mobile PM25 caused by traffic emission with Respiratory and Cardiovascular Diseases in the study areaSubsequently a correlation between cardio-respiratory mortality is established

A significant correlation of PM1025 exposure from mobile emission and hospital admissions for selected Respiratory (RD) and cardiovascular (CVD) diagnoses isestablished The results showed that PM emissions in urban restricted access (freeways and interstates) is mainly caused by traffic Therefore people living close tohighways receive higher vehicular emissions

The table shows the percentage of PM mobile exposure in the analyzed areas contributing to increase the risk of Respiratory and Cardiovascular Diseases

An examination was conducted of the synoptic and local meteorology for the June 2006 ozone episode using the WRF model to determine how meteorological parametersinfluence the formation transport and dispersion of ozone in the PdN The predominant synoptic feature of the ozone event day was the expansion intensification and slowprogression of an upper-level ridge of high pressure The high ozone episodes are associated with highly stable atmospheres strong temperature inversions with low mixingheights and therefore low mixing volumes Under these conditions emissions such as NOx lead to highly polluted conditions that favor ozone formation

BenMAP Conclusions

We have estimated the number and economic value of health impacts resulting

from changes in air pollution concentrations of PM 25 in the PdN region

Reduction of Pm 25 4 UGm3= Avoided 213 cases respiratory cardiovascular

diseses and Economic Benefits associated with the Response of PM25 Emission + $

1295000

Increase of PM25 7 ugm3 = increasing Dies= 326 economic Unbenefits= 2345000$

Bibliography

1 Dockery DW Pope CAI Xu X Spengler JD Ware JH Fay ME Ferris BG Speizer FE An association between air pollution and mortality in six US cities N Engl J Med 3291753ndash1759 (1993)

2 Samet JM Dominici F Curriero FC Coursac I Zeger SL Fine particulate air pollution and mortality in 20 US cities 1987ndash1994 N Engl J Med 3431742ndash1749 (2000)

3 Nel AE Diaz-Sanchez D Li N The role of particulate pollutants in pulmonary inflammation and asthma evidence for the involvement of organic chemicals and oxidative stress Curr Opin Pulm Med 20017 20ndash26

4 Westerholm R Karl-Erik E Exhaust emissions from lightand heavy-duty vehicles chemical composition impact of exhaust after treatment and fuel parameters Environ Health Perspect 102(suppl 4)13ndash23 (1994)

5 Bascom R Bromberg P Costa D Delvin R Dockery D Frampton M Lambert W Samet J Speizer F Utell

6 Health effects of outdoor air pollution Am J Respir Crit Care Med 1533ndash50 (1996)

7 Chow JC Watson JG Frazier CA Egami RT Goodrich A Ralph C Spatial and temporal source contributions to

8 PM10 and PM25 in Reno NV In PM-10 Implementation of Standards Transactions An APCAEPA International Speciality Conference San Francisco CA (Mathal CV Stonefield DH eds) PittsburghAPCA 1988439ndash457

9 overview In Particulate Matter Health and Regulatory Issues VIP-49 Proceedings of an International Specialty Conference 4ndash6 April 1995 Pittsburgh PA PittsburghAir and Waste Management Association 1995577ndash598

10 Kunzli N Kaiser R Medina S Studnicka M Chanel O

11 Filliger P Herry M Horak F Jr Puybonnieux-Texier V Quenel P et al Public-health impact of outdoor and traffic- related air pollution a European assessment Lancet 356795ndash801 (2000)

Bibliography

1 Sioutas C Delfino RJ Singh M Exposure assessment for atmospheric ultrafine particles (UFP) and implications in epidemiological research Environ Health Perspect 2005113947ndash955

2 Mosleh M Blau PJ Dumitrescu D (2004) Characteristics and morphology of wear particles from laboratory testing of disc brake materials Wear 2561128ndash1134

3 Kuumlnzli N et al (2000) Public-health impact of outdoor and traffi c-related air pollution a European assessment Lancet 356(9232)795ndash801

4 Dora C Phillips M eds (2000) Transport environment and health Copenhagen WHO Regional Office for Europe (WHO Regional Publications European Series No 89 httpwwweurowhointdocumente72015pdf accessed 26 November 2004)

5 Westerholm R Karl-Erik E Exhaust emissions from lightand

6 heavy-duty vehicles chemical composition impact of exhaust after treatment and fuel parameters Environ Health Perspect 102(suppl 4)13ndash23 (1994)

7 Fauser Tjell Mosbaek pigegaard Quantification of tire-Tread particles using extractable Organic Zinc as a Tracer Rubber Chemistry and Technology 1999 969Table shows some literature estimates of the contribution of tire wear to PM10 in air (Panko et al 2013) Gustafsson M Blomqvist G Gudmundsson A Dahl A Swietlicki E Bohgard M Lindbom J Ljungman A

8 Chen Y Shah N Huggins FE and Huffman GP (2006) Microanalysis of Ambient Particles from Lexington Ky by Electron Microscopy Atmos Environ 40 651ndash663

9 Donaldson K Tran CL Jimenez LA Duffin R Newby DE and Mills N (2005) Combustion-derived Nanoparticles A Review of Their Toxicology Following Inhalation Exposure Part Fibre Toxicol 2 10ndash23

10 Su D Serafino A Muller JO Jentoft RE Schlogl R and Fiorito S (2008) Cytotoxicity and Inflammatory Potential of Soot Particles of Low-emission Diesel Engines Environ Sci Technol 42 1761ndash1765

11 Maier KL Alessandrini F Beck-Speier I Hofer TPJ Diabatґe S Bitterle E Stoger T and Jakob T (2008) Health Effects of Ambient Particulate Matter-Biological Mechanisms and Inflammatory Responses to in Vitroand in Vivo Particle Exposures Inhalation Toxicol 20 319ndash337

Page 47: Studies of Air Pollutants and their Impact on Respiratory and ...€¦ · Ascarate Park C37 Monitoring Station: The National Ambient Air Quality Standard (NAAQS) for PM 10 and 2.5

Results

The results showed that mobile PM emissions in the urban areas close to urban Road and highways is putting at risk public health

and the proportion of diseases attributable to this exposure is potentially large

Brake wear emissions is much lower in freeways due to significantly reduced number of braking events while tire wear is much

higher in areas where studded tires are used The emission of exhaust gases are much higher in areas where there is a high

vehicular traffic

Brake Mobile

Emission PM10 kg

Asthma-Bronchitis)

Brake Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square

R=969

Linear Square

R=856

Exhaust Mobile

Emission PM10 kg

Asthma-Bronchitis)

Exhaust Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square

R=929

Linear Square

R=831

Tirewear Mobile

Emission PM10 kg

Asthma-Bronchitis)

Tirewear Mobile

Emission PM25 kg

and Heart Diagnoses

Linear Square R=769 Linear Square R=715

Brake Mobile

Emission PM10 kg

and Heart

Diagnoses

Brake Mobile

Emission PM25 kg

and Heart

Diagnoses

Exhaust Mobile

Emission PM10 kg

Asthma-Bronchitis)

Linear Square

R=625

Linear Square

R=691

Linear Square R=

951

Exhaust Mobile

Emission PM25 kg

Asthma-

Bronchitis)

Tire wear Mobile

Emission PM10 kg and

Heart Diagnoses

Tirewear Mobile

Emission PM25 kg

and Heart

Diagnoses

Linear Square R=

986

Linear Square R=525 Linear Square

R=601

El Paso County

Dona Ana

County

BenMAP-CE

In this analysis the Program of Mapping and Analysis of Environmental Benefits-Community Edition

(BenMAP-CE) was used to Estimate the number and economic value of health impacts resulting from changes

in air pollution PM 25 Ugm3 in The El Paso Area

Health and Economic Benefits associated with the Response of PM25 Emission between

Base Year 2010

Number of Mortalities in 2010 Base Year Based on El Paso County Texas Department of State Health Services

Number of Mortalities in 2010 Base Year Based on El Paso County Texas

Department of State Health Services

cause of death

year

2010

Populatio

n

Affected

Backgro

und

Concentr

ation Pollutant

Rollback

Type

Avoided

Deaths

(

Populatio

n)

alzheimers disease 2010 40716 125 PM25

25

microgmAcircsup3

Rollback 9

diseases of the

heart 2010 15834 125 PM25

25

microgmAcircsup3

Rollback 35

influenza and

neumonia 2010 81432 125 PM25

25

microgmAcircsup3

Rollback 18

acute bronchitis

and bronchiolitis 2010 117624 125 PM25

25

microgmAcircsup3

Rollback 26

chronic lower

respiratory diseases 2010 54288 125 PM25

25

microgmAcircsup3

Rollback 12

The Basin-wide decrease in 4 ugm3 PM25 concentration after this

reduction control

Cause of death year 2010

Populatio

n

Affected

Background

Concentrati

on

Reduc

cion

scena

rio Polluta

nt

Rollback

Type

Avoi

ded

Deat

hs

(

Pop

ulati

on)

economic

benefits

analysis $

Alzheimers

disease 2010 121 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 9 12000

Diseases of the

heart 2010 470 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 35 35000

Influenza and

neumonia 2010 242 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 18 42500

Acute bronchitis

and bronchiolitis 2010 349 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 26 95000

Chronic lower

respiratory

diseases 2010 161 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 12 4500

$1 295000

PM25-related Mortalities Based on BenMAP-CE Estimate in 2010 Base Year with change in the concentrations levels

Health and Economic Benefits associated with the Response of PM25 Emission between

Base Year 2010 Increasing 7 Ugm3

Cause of death year 2010

Population

Affected

Deaths

avoided by

attaining 195

μgm3

standard

Background

Concentrati

on

Pollut

ant

Rollback

Type

Avoided

Deaths (

Populatio

n)

econo

mic

Unben

efits

analysi

s

Alzheimers

disease 2010 4524 195 PM25

25

microgmAcircsup3

Rollback 19 150000

Diseases of the

heart 2010 20358 195 PM25

25

microgmAcircsup3

Rollback 135 450000

Influenza and

neumonia 2010 126672 195 PM25

25

microgmAcircsup3

Rollback 38 525000

Acute bronchitis

and bronchiolitis 2010 162864 195 PM25

25

microgmAcircsup3

Rollback 36 122000

Chronic lower

respiratory

diseases 2010 99528 195 PM25

25

microgmAcircsup3

Rollback 12 650000

Conclusions

An excellent Pearson Correlation was established to analyze the relationship in the relative risks of hospitalization of Respiratory(RD) and cardiovascular (CVD) associated with ambient exposure caused by traffic emission in relation to their size andspecific sources of emission on different scenarios interior a border Urban Rural Urban restricted access (freeways andinterstates)

A significant correlation of PM1025 exposure from mobile emission and hospital admissions for selected Respiratory (RD) andcardiovascular (CVD) diagnoses was established The results showed that PM emissions in urban restricted access (freeways andinterstates) is mainly caused by traffic Therefore people living close to highways are more exposed higher vehicular emissions

Conclusions

We found statistically significant associations between mobile PM25 caused by traffic emission with Respiratory and Cardiovascular Diseases in the study areaSubsequently a correlation between cardio-respiratory mortality is established

A significant correlation of PM1025 exposure from mobile emission and hospital admissions for selected Respiratory (RD) and cardiovascular (CVD) diagnoses isestablished The results showed that PM emissions in urban restricted access (freeways and interstates) is mainly caused by traffic Therefore people living close tohighways receive higher vehicular emissions

The table shows the percentage of PM mobile exposure in the analyzed areas contributing to increase the risk of Respiratory and Cardiovascular Diseases

An examination was conducted of the synoptic and local meteorology for the June 2006 ozone episode using the WRF model to determine how meteorological parametersinfluence the formation transport and dispersion of ozone in the PdN The predominant synoptic feature of the ozone event day was the expansion intensification and slowprogression of an upper-level ridge of high pressure The high ozone episodes are associated with highly stable atmospheres strong temperature inversions with low mixingheights and therefore low mixing volumes Under these conditions emissions such as NOx lead to highly polluted conditions that favor ozone formation

BenMAP Conclusions

We have estimated the number and economic value of health impacts resulting

from changes in air pollution concentrations of PM 25 in the PdN region

Reduction of Pm 25 4 UGm3= Avoided 213 cases respiratory cardiovascular

diseses and Economic Benefits associated with the Response of PM25 Emission + $

1295000

Increase of PM25 7 ugm3 = increasing Dies= 326 economic Unbenefits= 2345000$

Bibliography

1 Dockery DW Pope CAI Xu X Spengler JD Ware JH Fay ME Ferris BG Speizer FE An association between air pollution and mortality in six US cities N Engl J Med 3291753ndash1759 (1993)

2 Samet JM Dominici F Curriero FC Coursac I Zeger SL Fine particulate air pollution and mortality in 20 US cities 1987ndash1994 N Engl J Med 3431742ndash1749 (2000)

3 Nel AE Diaz-Sanchez D Li N The role of particulate pollutants in pulmonary inflammation and asthma evidence for the involvement of organic chemicals and oxidative stress Curr Opin Pulm Med 20017 20ndash26

4 Westerholm R Karl-Erik E Exhaust emissions from lightand heavy-duty vehicles chemical composition impact of exhaust after treatment and fuel parameters Environ Health Perspect 102(suppl 4)13ndash23 (1994)

5 Bascom R Bromberg P Costa D Delvin R Dockery D Frampton M Lambert W Samet J Speizer F Utell

6 Health effects of outdoor air pollution Am J Respir Crit Care Med 1533ndash50 (1996)

7 Chow JC Watson JG Frazier CA Egami RT Goodrich A Ralph C Spatial and temporal source contributions to

8 PM10 and PM25 in Reno NV In PM-10 Implementation of Standards Transactions An APCAEPA International Speciality Conference San Francisco CA (Mathal CV Stonefield DH eds) PittsburghAPCA 1988439ndash457

9 overview In Particulate Matter Health and Regulatory Issues VIP-49 Proceedings of an International Specialty Conference 4ndash6 April 1995 Pittsburgh PA PittsburghAir and Waste Management Association 1995577ndash598

10 Kunzli N Kaiser R Medina S Studnicka M Chanel O

11 Filliger P Herry M Horak F Jr Puybonnieux-Texier V Quenel P et al Public-health impact of outdoor and traffic- related air pollution a European assessment Lancet 356795ndash801 (2000)

Bibliography

1 Sioutas C Delfino RJ Singh M Exposure assessment for atmospheric ultrafine particles (UFP) and implications in epidemiological research Environ Health Perspect 2005113947ndash955

2 Mosleh M Blau PJ Dumitrescu D (2004) Characteristics and morphology of wear particles from laboratory testing of disc brake materials Wear 2561128ndash1134

3 Kuumlnzli N et al (2000) Public-health impact of outdoor and traffi c-related air pollution a European assessment Lancet 356(9232)795ndash801

4 Dora C Phillips M eds (2000) Transport environment and health Copenhagen WHO Regional Office for Europe (WHO Regional Publications European Series No 89 httpwwweurowhointdocumente72015pdf accessed 26 November 2004)

5 Westerholm R Karl-Erik E Exhaust emissions from lightand

6 heavy-duty vehicles chemical composition impact of exhaust after treatment and fuel parameters Environ Health Perspect 102(suppl 4)13ndash23 (1994)

7 Fauser Tjell Mosbaek pigegaard Quantification of tire-Tread particles using extractable Organic Zinc as a Tracer Rubber Chemistry and Technology 1999 969Table shows some literature estimates of the contribution of tire wear to PM10 in air (Panko et al 2013) Gustafsson M Blomqvist G Gudmundsson A Dahl A Swietlicki E Bohgard M Lindbom J Ljungman A

8 Chen Y Shah N Huggins FE and Huffman GP (2006) Microanalysis of Ambient Particles from Lexington Ky by Electron Microscopy Atmos Environ 40 651ndash663

9 Donaldson K Tran CL Jimenez LA Duffin R Newby DE and Mills N (2005) Combustion-derived Nanoparticles A Review of Their Toxicology Following Inhalation Exposure Part Fibre Toxicol 2 10ndash23

10 Su D Serafino A Muller JO Jentoft RE Schlogl R and Fiorito S (2008) Cytotoxicity and Inflammatory Potential of Soot Particles of Low-emission Diesel Engines Environ Sci Technol 42 1761ndash1765

11 Maier KL Alessandrini F Beck-Speier I Hofer TPJ Diabatґe S Bitterle E Stoger T and Jakob T (2008) Health Effects of Ambient Particulate Matter-Biological Mechanisms and Inflammatory Responses to in Vitroand in Vivo Particle Exposures Inhalation Toxicol 20 319ndash337

Page 48: Studies of Air Pollutants and their Impact on Respiratory and ...€¦ · Ascarate Park C37 Monitoring Station: The National Ambient Air Quality Standard (NAAQS) for PM 10 and 2.5

BenMAP-CE

In this analysis the Program of Mapping and Analysis of Environmental Benefits-Community Edition

(BenMAP-CE) was used to Estimate the number and economic value of health impacts resulting from changes

in air pollution PM 25 Ugm3 in The El Paso Area

Health and Economic Benefits associated with the Response of PM25 Emission between

Base Year 2010

Number of Mortalities in 2010 Base Year Based on El Paso County Texas Department of State Health Services

Number of Mortalities in 2010 Base Year Based on El Paso County Texas

Department of State Health Services

cause of death

year

2010

Populatio

n

Affected

Backgro

und

Concentr

ation Pollutant

Rollback

Type

Avoided

Deaths

(

Populatio

n)

alzheimers disease 2010 40716 125 PM25

25

microgmAcircsup3

Rollback 9

diseases of the

heart 2010 15834 125 PM25

25

microgmAcircsup3

Rollback 35

influenza and

neumonia 2010 81432 125 PM25

25

microgmAcircsup3

Rollback 18

acute bronchitis

and bronchiolitis 2010 117624 125 PM25

25

microgmAcircsup3

Rollback 26

chronic lower

respiratory diseases 2010 54288 125 PM25

25

microgmAcircsup3

Rollback 12

The Basin-wide decrease in 4 ugm3 PM25 concentration after this

reduction control

Cause of death year 2010

Populatio

n

Affected

Background

Concentrati

on

Reduc

cion

scena

rio Polluta

nt

Rollback

Type

Avoi

ded

Deat

hs

(

Pop

ulati

on)

economic

benefits

analysis $

Alzheimers

disease 2010 121 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 9 12000

Diseases of the

heart 2010 470 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 35 35000

Influenza and

neumonia 2010 242 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 18 42500

Acute bronchitis

and bronchiolitis 2010 349 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 26 95000

Chronic lower

respiratory

diseases 2010 161 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 12 4500

$1 295000

PM25-related Mortalities Based on BenMAP-CE Estimate in 2010 Base Year with change in the concentrations levels

Health and Economic Benefits associated with the Response of PM25 Emission between

Base Year 2010 Increasing 7 Ugm3

Cause of death year 2010

Population

Affected

Deaths

avoided by

attaining 195

μgm3

standard

Background

Concentrati

on

Pollut

ant

Rollback

Type

Avoided

Deaths (

Populatio

n)

econo

mic

Unben

efits

analysi

s

Alzheimers

disease 2010 4524 195 PM25

25

microgmAcircsup3

Rollback 19 150000

Diseases of the

heart 2010 20358 195 PM25

25

microgmAcircsup3

Rollback 135 450000

Influenza and

neumonia 2010 126672 195 PM25

25

microgmAcircsup3

Rollback 38 525000

Acute bronchitis

and bronchiolitis 2010 162864 195 PM25

25

microgmAcircsup3

Rollback 36 122000

Chronic lower

respiratory

diseases 2010 99528 195 PM25

25

microgmAcircsup3

Rollback 12 650000

Conclusions

An excellent Pearson Correlation was established to analyze the relationship in the relative risks of hospitalization of Respiratory(RD) and cardiovascular (CVD) associated with ambient exposure caused by traffic emission in relation to their size andspecific sources of emission on different scenarios interior a border Urban Rural Urban restricted access (freeways andinterstates)

A significant correlation of PM1025 exposure from mobile emission and hospital admissions for selected Respiratory (RD) andcardiovascular (CVD) diagnoses was established The results showed that PM emissions in urban restricted access (freeways andinterstates) is mainly caused by traffic Therefore people living close to highways are more exposed higher vehicular emissions

Conclusions

We found statistically significant associations between mobile PM25 caused by traffic emission with Respiratory and Cardiovascular Diseases in the study areaSubsequently a correlation between cardio-respiratory mortality is established

A significant correlation of PM1025 exposure from mobile emission and hospital admissions for selected Respiratory (RD) and cardiovascular (CVD) diagnoses isestablished The results showed that PM emissions in urban restricted access (freeways and interstates) is mainly caused by traffic Therefore people living close tohighways receive higher vehicular emissions

The table shows the percentage of PM mobile exposure in the analyzed areas contributing to increase the risk of Respiratory and Cardiovascular Diseases

An examination was conducted of the synoptic and local meteorology for the June 2006 ozone episode using the WRF model to determine how meteorological parametersinfluence the formation transport and dispersion of ozone in the PdN The predominant synoptic feature of the ozone event day was the expansion intensification and slowprogression of an upper-level ridge of high pressure The high ozone episodes are associated with highly stable atmospheres strong temperature inversions with low mixingheights and therefore low mixing volumes Under these conditions emissions such as NOx lead to highly polluted conditions that favor ozone formation

BenMAP Conclusions

We have estimated the number and economic value of health impacts resulting

from changes in air pollution concentrations of PM 25 in the PdN region

Reduction of Pm 25 4 UGm3= Avoided 213 cases respiratory cardiovascular

diseses and Economic Benefits associated with the Response of PM25 Emission + $

1295000

Increase of PM25 7 ugm3 = increasing Dies= 326 economic Unbenefits= 2345000$

Bibliography

1 Dockery DW Pope CAI Xu X Spengler JD Ware JH Fay ME Ferris BG Speizer FE An association between air pollution and mortality in six US cities N Engl J Med 3291753ndash1759 (1993)

2 Samet JM Dominici F Curriero FC Coursac I Zeger SL Fine particulate air pollution and mortality in 20 US cities 1987ndash1994 N Engl J Med 3431742ndash1749 (2000)

3 Nel AE Diaz-Sanchez D Li N The role of particulate pollutants in pulmonary inflammation and asthma evidence for the involvement of organic chemicals and oxidative stress Curr Opin Pulm Med 20017 20ndash26

4 Westerholm R Karl-Erik E Exhaust emissions from lightand heavy-duty vehicles chemical composition impact of exhaust after treatment and fuel parameters Environ Health Perspect 102(suppl 4)13ndash23 (1994)

5 Bascom R Bromberg P Costa D Delvin R Dockery D Frampton M Lambert W Samet J Speizer F Utell

6 Health effects of outdoor air pollution Am J Respir Crit Care Med 1533ndash50 (1996)

7 Chow JC Watson JG Frazier CA Egami RT Goodrich A Ralph C Spatial and temporal source contributions to

8 PM10 and PM25 in Reno NV In PM-10 Implementation of Standards Transactions An APCAEPA International Speciality Conference San Francisco CA (Mathal CV Stonefield DH eds) PittsburghAPCA 1988439ndash457

9 overview In Particulate Matter Health and Regulatory Issues VIP-49 Proceedings of an International Specialty Conference 4ndash6 April 1995 Pittsburgh PA PittsburghAir and Waste Management Association 1995577ndash598

10 Kunzli N Kaiser R Medina S Studnicka M Chanel O

11 Filliger P Herry M Horak F Jr Puybonnieux-Texier V Quenel P et al Public-health impact of outdoor and traffic- related air pollution a European assessment Lancet 356795ndash801 (2000)

Bibliography

1 Sioutas C Delfino RJ Singh M Exposure assessment for atmospheric ultrafine particles (UFP) and implications in epidemiological research Environ Health Perspect 2005113947ndash955

2 Mosleh M Blau PJ Dumitrescu D (2004) Characteristics and morphology of wear particles from laboratory testing of disc brake materials Wear 2561128ndash1134

3 Kuumlnzli N et al (2000) Public-health impact of outdoor and traffi c-related air pollution a European assessment Lancet 356(9232)795ndash801

4 Dora C Phillips M eds (2000) Transport environment and health Copenhagen WHO Regional Office for Europe (WHO Regional Publications European Series No 89 httpwwweurowhointdocumente72015pdf accessed 26 November 2004)

5 Westerholm R Karl-Erik E Exhaust emissions from lightand

6 heavy-duty vehicles chemical composition impact of exhaust after treatment and fuel parameters Environ Health Perspect 102(suppl 4)13ndash23 (1994)

7 Fauser Tjell Mosbaek pigegaard Quantification of tire-Tread particles using extractable Organic Zinc as a Tracer Rubber Chemistry and Technology 1999 969Table shows some literature estimates of the contribution of tire wear to PM10 in air (Panko et al 2013) Gustafsson M Blomqvist G Gudmundsson A Dahl A Swietlicki E Bohgard M Lindbom J Ljungman A

8 Chen Y Shah N Huggins FE and Huffman GP (2006) Microanalysis of Ambient Particles from Lexington Ky by Electron Microscopy Atmos Environ 40 651ndash663

9 Donaldson K Tran CL Jimenez LA Duffin R Newby DE and Mills N (2005) Combustion-derived Nanoparticles A Review of Their Toxicology Following Inhalation Exposure Part Fibre Toxicol 2 10ndash23

10 Su D Serafino A Muller JO Jentoft RE Schlogl R and Fiorito S (2008) Cytotoxicity and Inflammatory Potential of Soot Particles of Low-emission Diesel Engines Environ Sci Technol 42 1761ndash1765

11 Maier KL Alessandrini F Beck-Speier I Hofer TPJ Diabatґe S Bitterle E Stoger T and Jakob T (2008) Health Effects of Ambient Particulate Matter-Biological Mechanisms and Inflammatory Responses to in Vitroand in Vivo Particle Exposures Inhalation Toxicol 20 319ndash337

Page 49: Studies of Air Pollutants and their Impact on Respiratory and ...€¦ · Ascarate Park C37 Monitoring Station: The National Ambient Air Quality Standard (NAAQS) for PM 10 and 2.5

Health and Economic Benefits associated with the Response of PM25 Emission between

Base Year 2010

Number of Mortalities in 2010 Base Year Based on El Paso County Texas Department of State Health Services

Number of Mortalities in 2010 Base Year Based on El Paso County Texas

Department of State Health Services

cause of death

year

2010

Populatio

n

Affected

Backgro

und

Concentr

ation Pollutant

Rollback

Type

Avoided

Deaths

(

Populatio

n)

alzheimers disease 2010 40716 125 PM25

25

microgmAcircsup3

Rollback 9

diseases of the

heart 2010 15834 125 PM25

25

microgmAcircsup3

Rollback 35

influenza and

neumonia 2010 81432 125 PM25

25

microgmAcircsup3

Rollback 18

acute bronchitis

and bronchiolitis 2010 117624 125 PM25

25

microgmAcircsup3

Rollback 26

chronic lower

respiratory diseases 2010 54288 125 PM25

25

microgmAcircsup3

Rollback 12

The Basin-wide decrease in 4 ugm3 PM25 concentration after this

reduction control

Cause of death year 2010

Populatio

n

Affected

Background

Concentrati

on

Reduc

cion

scena

rio Polluta

nt

Rollback

Type

Avoi

ded

Deat

hs

(

Pop

ulati

on)

economic

benefits

analysis $

Alzheimers

disease 2010 121 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 9 12000

Diseases of the

heart 2010 470 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 35 35000

Influenza and

neumonia 2010 242 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 18 42500

Acute bronchitis

and bronchiolitis 2010 349 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 26 95000

Chronic lower

respiratory

diseases 2010 161 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 12 4500

$1 295000

PM25-related Mortalities Based on BenMAP-CE Estimate in 2010 Base Year with change in the concentrations levels

Health and Economic Benefits associated with the Response of PM25 Emission between

Base Year 2010 Increasing 7 Ugm3

Cause of death year 2010

Population

Affected

Deaths

avoided by

attaining 195

μgm3

standard

Background

Concentrati

on

Pollut

ant

Rollback

Type

Avoided

Deaths (

Populatio

n)

econo

mic

Unben

efits

analysi

s

Alzheimers

disease 2010 4524 195 PM25

25

microgmAcircsup3

Rollback 19 150000

Diseases of the

heart 2010 20358 195 PM25

25

microgmAcircsup3

Rollback 135 450000

Influenza and

neumonia 2010 126672 195 PM25

25

microgmAcircsup3

Rollback 38 525000

Acute bronchitis

and bronchiolitis 2010 162864 195 PM25

25

microgmAcircsup3

Rollback 36 122000

Chronic lower

respiratory

diseases 2010 99528 195 PM25

25

microgmAcircsup3

Rollback 12 650000

Conclusions

An excellent Pearson Correlation was established to analyze the relationship in the relative risks of hospitalization of Respiratory(RD) and cardiovascular (CVD) associated with ambient exposure caused by traffic emission in relation to their size andspecific sources of emission on different scenarios interior a border Urban Rural Urban restricted access (freeways andinterstates)

A significant correlation of PM1025 exposure from mobile emission and hospital admissions for selected Respiratory (RD) andcardiovascular (CVD) diagnoses was established The results showed that PM emissions in urban restricted access (freeways andinterstates) is mainly caused by traffic Therefore people living close to highways are more exposed higher vehicular emissions

Conclusions

We found statistically significant associations between mobile PM25 caused by traffic emission with Respiratory and Cardiovascular Diseases in the study areaSubsequently a correlation between cardio-respiratory mortality is established

A significant correlation of PM1025 exposure from mobile emission and hospital admissions for selected Respiratory (RD) and cardiovascular (CVD) diagnoses isestablished The results showed that PM emissions in urban restricted access (freeways and interstates) is mainly caused by traffic Therefore people living close tohighways receive higher vehicular emissions

The table shows the percentage of PM mobile exposure in the analyzed areas contributing to increase the risk of Respiratory and Cardiovascular Diseases

An examination was conducted of the synoptic and local meteorology for the June 2006 ozone episode using the WRF model to determine how meteorological parametersinfluence the formation transport and dispersion of ozone in the PdN The predominant synoptic feature of the ozone event day was the expansion intensification and slowprogression of an upper-level ridge of high pressure The high ozone episodes are associated with highly stable atmospheres strong temperature inversions with low mixingheights and therefore low mixing volumes Under these conditions emissions such as NOx lead to highly polluted conditions that favor ozone formation

BenMAP Conclusions

We have estimated the number and economic value of health impacts resulting

from changes in air pollution concentrations of PM 25 in the PdN region

Reduction of Pm 25 4 UGm3= Avoided 213 cases respiratory cardiovascular

diseses and Economic Benefits associated with the Response of PM25 Emission + $

1295000

Increase of PM25 7 ugm3 = increasing Dies= 326 economic Unbenefits= 2345000$

Bibliography

1 Dockery DW Pope CAI Xu X Spengler JD Ware JH Fay ME Ferris BG Speizer FE An association between air pollution and mortality in six US cities N Engl J Med 3291753ndash1759 (1993)

2 Samet JM Dominici F Curriero FC Coursac I Zeger SL Fine particulate air pollution and mortality in 20 US cities 1987ndash1994 N Engl J Med 3431742ndash1749 (2000)

3 Nel AE Diaz-Sanchez D Li N The role of particulate pollutants in pulmonary inflammation and asthma evidence for the involvement of organic chemicals and oxidative stress Curr Opin Pulm Med 20017 20ndash26

4 Westerholm R Karl-Erik E Exhaust emissions from lightand heavy-duty vehicles chemical composition impact of exhaust after treatment and fuel parameters Environ Health Perspect 102(suppl 4)13ndash23 (1994)

5 Bascom R Bromberg P Costa D Delvin R Dockery D Frampton M Lambert W Samet J Speizer F Utell

6 Health effects of outdoor air pollution Am J Respir Crit Care Med 1533ndash50 (1996)

7 Chow JC Watson JG Frazier CA Egami RT Goodrich A Ralph C Spatial and temporal source contributions to

8 PM10 and PM25 in Reno NV In PM-10 Implementation of Standards Transactions An APCAEPA International Speciality Conference San Francisco CA (Mathal CV Stonefield DH eds) PittsburghAPCA 1988439ndash457

9 overview In Particulate Matter Health and Regulatory Issues VIP-49 Proceedings of an International Specialty Conference 4ndash6 April 1995 Pittsburgh PA PittsburghAir and Waste Management Association 1995577ndash598

10 Kunzli N Kaiser R Medina S Studnicka M Chanel O

11 Filliger P Herry M Horak F Jr Puybonnieux-Texier V Quenel P et al Public-health impact of outdoor and traffic- related air pollution a European assessment Lancet 356795ndash801 (2000)

Bibliography

1 Sioutas C Delfino RJ Singh M Exposure assessment for atmospheric ultrafine particles (UFP) and implications in epidemiological research Environ Health Perspect 2005113947ndash955

2 Mosleh M Blau PJ Dumitrescu D (2004) Characteristics and morphology of wear particles from laboratory testing of disc brake materials Wear 2561128ndash1134

3 Kuumlnzli N et al (2000) Public-health impact of outdoor and traffi c-related air pollution a European assessment Lancet 356(9232)795ndash801

4 Dora C Phillips M eds (2000) Transport environment and health Copenhagen WHO Regional Office for Europe (WHO Regional Publications European Series No 89 httpwwweurowhointdocumente72015pdf accessed 26 November 2004)

5 Westerholm R Karl-Erik E Exhaust emissions from lightand

6 heavy-duty vehicles chemical composition impact of exhaust after treatment and fuel parameters Environ Health Perspect 102(suppl 4)13ndash23 (1994)

7 Fauser Tjell Mosbaek pigegaard Quantification of tire-Tread particles using extractable Organic Zinc as a Tracer Rubber Chemistry and Technology 1999 969Table shows some literature estimates of the contribution of tire wear to PM10 in air (Panko et al 2013) Gustafsson M Blomqvist G Gudmundsson A Dahl A Swietlicki E Bohgard M Lindbom J Ljungman A

8 Chen Y Shah N Huggins FE and Huffman GP (2006) Microanalysis of Ambient Particles from Lexington Ky by Electron Microscopy Atmos Environ 40 651ndash663

9 Donaldson K Tran CL Jimenez LA Duffin R Newby DE and Mills N (2005) Combustion-derived Nanoparticles A Review of Their Toxicology Following Inhalation Exposure Part Fibre Toxicol 2 10ndash23

10 Su D Serafino A Muller JO Jentoft RE Schlogl R and Fiorito S (2008) Cytotoxicity and Inflammatory Potential of Soot Particles of Low-emission Diesel Engines Environ Sci Technol 42 1761ndash1765

11 Maier KL Alessandrini F Beck-Speier I Hofer TPJ Diabatґe S Bitterle E Stoger T and Jakob T (2008) Health Effects of Ambient Particulate Matter-Biological Mechanisms and Inflammatory Responses to in Vitroand in Vivo Particle Exposures Inhalation Toxicol 20 319ndash337

Page 50: Studies of Air Pollutants and their Impact on Respiratory and ...€¦ · Ascarate Park C37 Monitoring Station: The National Ambient Air Quality Standard (NAAQS) for PM 10 and 2.5

The Basin-wide decrease in 4 ugm3 PM25 concentration after this

reduction control

Cause of death year 2010

Populatio

n

Affected

Background

Concentrati

on

Reduc

cion

scena

rio Polluta

nt

Rollback

Type

Avoi

ded

Deat

hs

(

Pop

ulati

on)

economic

benefits

analysis $

Alzheimers

disease 2010 121 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 9 12000

Diseases of the

heart 2010 470 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 35 35000

Influenza and

neumonia 2010 242 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 18 42500

Acute bronchitis

and bronchiolitis 2010 349 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 26 95000

Chronic lower

respiratory

diseases 2010 161 125

25

ugm

3 PM25

25

microgmAcircsup3

Rollback 12 4500

$1 295000

PM25-related Mortalities Based on BenMAP-CE Estimate in 2010 Base Year with change in the concentrations levels

Health and Economic Benefits associated with the Response of PM25 Emission between

Base Year 2010 Increasing 7 Ugm3

Cause of death year 2010

Population

Affected

Deaths

avoided by

attaining 195

μgm3

standard

Background

Concentrati

on

Pollut

ant

Rollback

Type

Avoided

Deaths (

Populatio

n)

econo

mic

Unben

efits

analysi

s

Alzheimers

disease 2010 4524 195 PM25

25

microgmAcircsup3

Rollback 19 150000

Diseases of the

heart 2010 20358 195 PM25

25

microgmAcircsup3

Rollback 135 450000

Influenza and

neumonia 2010 126672 195 PM25

25

microgmAcircsup3

Rollback 38 525000

Acute bronchitis

and bronchiolitis 2010 162864 195 PM25

25

microgmAcircsup3

Rollback 36 122000

Chronic lower

respiratory

diseases 2010 99528 195 PM25

25

microgmAcircsup3

Rollback 12 650000

Conclusions

An excellent Pearson Correlation was established to analyze the relationship in the relative risks of hospitalization of Respiratory(RD) and cardiovascular (CVD) associated with ambient exposure caused by traffic emission in relation to their size andspecific sources of emission on different scenarios interior a border Urban Rural Urban restricted access (freeways andinterstates)

A significant correlation of PM1025 exposure from mobile emission and hospital admissions for selected Respiratory (RD) andcardiovascular (CVD) diagnoses was established The results showed that PM emissions in urban restricted access (freeways andinterstates) is mainly caused by traffic Therefore people living close to highways are more exposed higher vehicular emissions

Conclusions

We found statistically significant associations between mobile PM25 caused by traffic emission with Respiratory and Cardiovascular Diseases in the study areaSubsequently a correlation between cardio-respiratory mortality is established

A significant correlation of PM1025 exposure from mobile emission and hospital admissions for selected Respiratory (RD) and cardiovascular (CVD) diagnoses isestablished The results showed that PM emissions in urban restricted access (freeways and interstates) is mainly caused by traffic Therefore people living close tohighways receive higher vehicular emissions

The table shows the percentage of PM mobile exposure in the analyzed areas contributing to increase the risk of Respiratory and Cardiovascular Diseases

An examination was conducted of the synoptic and local meteorology for the June 2006 ozone episode using the WRF model to determine how meteorological parametersinfluence the formation transport and dispersion of ozone in the PdN The predominant synoptic feature of the ozone event day was the expansion intensification and slowprogression of an upper-level ridge of high pressure The high ozone episodes are associated with highly stable atmospheres strong temperature inversions with low mixingheights and therefore low mixing volumes Under these conditions emissions such as NOx lead to highly polluted conditions that favor ozone formation

BenMAP Conclusions

We have estimated the number and economic value of health impacts resulting

from changes in air pollution concentrations of PM 25 in the PdN region

Reduction of Pm 25 4 UGm3= Avoided 213 cases respiratory cardiovascular

diseses and Economic Benefits associated with the Response of PM25 Emission + $

1295000

Increase of PM25 7 ugm3 = increasing Dies= 326 economic Unbenefits= 2345000$

Bibliography

1 Dockery DW Pope CAI Xu X Spengler JD Ware JH Fay ME Ferris BG Speizer FE An association between air pollution and mortality in six US cities N Engl J Med 3291753ndash1759 (1993)

2 Samet JM Dominici F Curriero FC Coursac I Zeger SL Fine particulate air pollution and mortality in 20 US cities 1987ndash1994 N Engl J Med 3431742ndash1749 (2000)

3 Nel AE Diaz-Sanchez D Li N The role of particulate pollutants in pulmonary inflammation and asthma evidence for the involvement of organic chemicals and oxidative stress Curr Opin Pulm Med 20017 20ndash26

4 Westerholm R Karl-Erik E Exhaust emissions from lightand heavy-duty vehicles chemical composition impact of exhaust after treatment and fuel parameters Environ Health Perspect 102(suppl 4)13ndash23 (1994)

5 Bascom R Bromberg P Costa D Delvin R Dockery D Frampton M Lambert W Samet J Speizer F Utell

6 Health effects of outdoor air pollution Am J Respir Crit Care Med 1533ndash50 (1996)

7 Chow JC Watson JG Frazier CA Egami RT Goodrich A Ralph C Spatial and temporal source contributions to

8 PM10 and PM25 in Reno NV In PM-10 Implementation of Standards Transactions An APCAEPA International Speciality Conference San Francisco CA (Mathal CV Stonefield DH eds) PittsburghAPCA 1988439ndash457

9 overview In Particulate Matter Health and Regulatory Issues VIP-49 Proceedings of an International Specialty Conference 4ndash6 April 1995 Pittsburgh PA PittsburghAir and Waste Management Association 1995577ndash598

10 Kunzli N Kaiser R Medina S Studnicka M Chanel O

11 Filliger P Herry M Horak F Jr Puybonnieux-Texier V Quenel P et al Public-health impact of outdoor and traffic- related air pollution a European assessment Lancet 356795ndash801 (2000)

Bibliography

1 Sioutas C Delfino RJ Singh M Exposure assessment for atmospheric ultrafine particles (UFP) and implications in epidemiological research Environ Health Perspect 2005113947ndash955

2 Mosleh M Blau PJ Dumitrescu D (2004) Characteristics and morphology of wear particles from laboratory testing of disc brake materials Wear 2561128ndash1134

3 Kuumlnzli N et al (2000) Public-health impact of outdoor and traffi c-related air pollution a European assessment Lancet 356(9232)795ndash801

4 Dora C Phillips M eds (2000) Transport environment and health Copenhagen WHO Regional Office for Europe (WHO Regional Publications European Series No 89 httpwwweurowhointdocumente72015pdf accessed 26 November 2004)

5 Westerholm R Karl-Erik E Exhaust emissions from lightand

6 heavy-duty vehicles chemical composition impact of exhaust after treatment and fuel parameters Environ Health Perspect 102(suppl 4)13ndash23 (1994)

7 Fauser Tjell Mosbaek pigegaard Quantification of tire-Tread particles using extractable Organic Zinc as a Tracer Rubber Chemistry and Technology 1999 969Table shows some literature estimates of the contribution of tire wear to PM10 in air (Panko et al 2013) Gustafsson M Blomqvist G Gudmundsson A Dahl A Swietlicki E Bohgard M Lindbom J Ljungman A

8 Chen Y Shah N Huggins FE and Huffman GP (2006) Microanalysis of Ambient Particles from Lexington Ky by Electron Microscopy Atmos Environ 40 651ndash663

9 Donaldson K Tran CL Jimenez LA Duffin R Newby DE and Mills N (2005) Combustion-derived Nanoparticles A Review of Their Toxicology Following Inhalation Exposure Part Fibre Toxicol 2 10ndash23

10 Su D Serafino A Muller JO Jentoft RE Schlogl R and Fiorito S (2008) Cytotoxicity and Inflammatory Potential of Soot Particles of Low-emission Diesel Engines Environ Sci Technol 42 1761ndash1765

11 Maier KL Alessandrini F Beck-Speier I Hofer TPJ Diabatґe S Bitterle E Stoger T and Jakob T (2008) Health Effects of Ambient Particulate Matter-Biological Mechanisms and Inflammatory Responses to in Vitroand in Vivo Particle Exposures Inhalation Toxicol 20 319ndash337

Page 51: Studies of Air Pollutants and their Impact on Respiratory and ...€¦ · Ascarate Park C37 Monitoring Station: The National Ambient Air Quality Standard (NAAQS) for PM 10 and 2.5

Health and Economic Benefits associated with the Response of PM25 Emission between

Base Year 2010 Increasing 7 Ugm3

Cause of death year 2010

Population

Affected

Deaths

avoided by

attaining 195

μgm3

standard

Background

Concentrati

on

Pollut

ant

Rollback

Type

Avoided

Deaths (

Populatio

n)

econo

mic

Unben

efits

analysi

s

Alzheimers

disease 2010 4524 195 PM25

25

microgmAcircsup3

Rollback 19 150000

Diseases of the

heart 2010 20358 195 PM25

25

microgmAcircsup3

Rollback 135 450000

Influenza and

neumonia 2010 126672 195 PM25

25

microgmAcircsup3

Rollback 38 525000

Acute bronchitis

and bronchiolitis 2010 162864 195 PM25

25

microgmAcircsup3

Rollback 36 122000

Chronic lower

respiratory

diseases 2010 99528 195 PM25

25

microgmAcircsup3

Rollback 12 650000

Conclusions

An excellent Pearson Correlation was established to analyze the relationship in the relative risks of hospitalization of Respiratory(RD) and cardiovascular (CVD) associated with ambient exposure caused by traffic emission in relation to their size andspecific sources of emission on different scenarios interior a border Urban Rural Urban restricted access (freeways andinterstates)

A significant correlation of PM1025 exposure from mobile emission and hospital admissions for selected Respiratory (RD) andcardiovascular (CVD) diagnoses was established The results showed that PM emissions in urban restricted access (freeways andinterstates) is mainly caused by traffic Therefore people living close to highways are more exposed higher vehicular emissions

Conclusions

We found statistically significant associations between mobile PM25 caused by traffic emission with Respiratory and Cardiovascular Diseases in the study areaSubsequently a correlation between cardio-respiratory mortality is established

A significant correlation of PM1025 exposure from mobile emission and hospital admissions for selected Respiratory (RD) and cardiovascular (CVD) diagnoses isestablished The results showed that PM emissions in urban restricted access (freeways and interstates) is mainly caused by traffic Therefore people living close tohighways receive higher vehicular emissions

The table shows the percentage of PM mobile exposure in the analyzed areas contributing to increase the risk of Respiratory and Cardiovascular Diseases

An examination was conducted of the synoptic and local meteorology for the June 2006 ozone episode using the WRF model to determine how meteorological parametersinfluence the formation transport and dispersion of ozone in the PdN The predominant synoptic feature of the ozone event day was the expansion intensification and slowprogression of an upper-level ridge of high pressure The high ozone episodes are associated with highly stable atmospheres strong temperature inversions with low mixingheights and therefore low mixing volumes Under these conditions emissions such as NOx lead to highly polluted conditions that favor ozone formation

BenMAP Conclusions

We have estimated the number and economic value of health impacts resulting

from changes in air pollution concentrations of PM 25 in the PdN region

Reduction of Pm 25 4 UGm3= Avoided 213 cases respiratory cardiovascular

diseses and Economic Benefits associated with the Response of PM25 Emission + $

1295000

Increase of PM25 7 ugm3 = increasing Dies= 326 economic Unbenefits= 2345000$

Bibliography

1 Dockery DW Pope CAI Xu X Spengler JD Ware JH Fay ME Ferris BG Speizer FE An association between air pollution and mortality in six US cities N Engl J Med 3291753ndash1759 (1993)

2 Samet JM Dominici F Curriero FC Coursac I Zeger SL Fine particulate air pollution and mortality in 20 US cities 1987ndash1994 N Engl J Med 3431742ndash1749 (2000)

3 Nel AE Diaz-Sanchez D Li N The role of particulate pollutants in pulmonary inflammation and asthma evidence for the involvement of organic chemicals and oxidative stress Curr Opin Pulm Med 20017 20ndash26

4 Westerholm R Karl-Erik E Exhaust emissions from lightand heavy-duty vehicles chemical composition impact of exhaust after treatment and fuel parameters Environ Health Perspect 102(suppl 4)13ndash23 (1994)

5 Bascom R Bromberg P Costa D Delvin R Dockery D Frampton M Lambert W Samet J Speizer F Utell

6 Health effects of outdoor air pollution Am J Respir Crit Care Med 1533ndash50 (1996)

7 Chow JC Watson JG Frazier CA Egami RT Goodrich A Ralph C Spatial and temporal source contributions to

8 PM10 and PM25 in Reno NV In PM-10 Implementation of Standards Transactions An APCAEPA International Speciality Conference San Francisco CA (Mathal CV Stonefield DH eds) PittsburghAPCA 1988439ndash457

9 overview In Particulate Matter Health and Regulatory Issues VIP-49 Proceedings of an International Specialty Conference 4ndash6 April 1995 Pittsburgh PA PittsburghAir and Waste Management Association 1995577ndash598

10 Kunzli N Kaiser R Medina S Studnicka M Chanel O

11 Filliger P Herry M Horak F Jr Puybonnieux-Texier V Quenel P et al Public-health impact of outdoor and traffic- related air pollution a European assessment Lancet 356795ndash801 (2000)

Bibliography

1 Sioutas C Delfino RJ Singh M Exposure assessment for atmospheric ultrafine particles (UFP) and implications in epidemiological research Environ Health Perspect 2005113947ndash955

2 Mosleh M Blau PJ Dumitrescu D (2004) Characteristics and morphology of wear particles from laboratory testing of disc brake materials Wear 2561128ndash1134

3 Kuumlnzli N et al (2000) Public-health impact of outdoor and traffi c-related air pollution a European assessment Lancet 356(9232)795ndash801

4 Dora C Phillips M eds (2000) Transport environment and health Copenhagen WHO Regional Office for Europe (WHO Regional Publications European Series No 89 httpwwweurowhointdocumente72015pdf accessed 26 November 2004)

5 Westerholm R Karl-Erik E Exhaust emissions from lightand

6 heavy-duty vehicles chemical composition impact of exhaust after treatment and fuel parameters Environ Health Perspect 102(suppl 4)13ndash23 (1994)

7 Fauser Tjell Mosbaek pigegaard Quantification of tire-Tread particles using extractable Organic Zinc as a Tracer Rubber Chemistry and Technology 1999 969Table shows some literature estimates of the contribution of tire wear to PM10 in air (Panko et al 2013) Gustafsson M Blomqvist G Gudmundsson A Dahl A Swietlicki E Bohgard M Lindbom J Ljungman A

8 Chen Y Shah N Huggins FE and Huffman GP (2006) Microanalysis of Ambient Particles from Lexington Ky by Electron Microscopy Atmos Environ 40 651ndash663

9 Donaldson K Tran CL Jimenez LA Duffin R Newby DE and Mills N (2005) Combustion-derived Nanoparticles A Review of Their Toxicology Following Inhalation Exposure Part Fibre Toxicol 2 10ndash23

10 Su D Serafino A Muller JO Jentoft RE Schlogl R and Fiorito S (2008) Cytotoxicity and Inflammatory Potential of Soot Particles of Low-emission Diesel Engines Environ Sci Technol 42 1761ndash1765

11 Maier KL Alessandrini F Beck-Speier I Hofer TPJ Diabatґe S Bitterle E Stoger T and Jakob T (2008) Health Effects of Ambient Particulate Matter-Biological Mechanisms and Inflammatory Responses to in Vitroand in Vivo Particle Exposures Inhalation Toxicol 20 319ndash337

Page 52: Studies of Air Pollutants and their Impact on Respiratory and ...€¦ · Ascarate Park C37 Monitoring Station: The National Ambient Air Quality Standard (NAAQS) for PM 10 and 2.5

Conclusions

An excellent Pearson Correlation was established to analyze the relationship in the relative risks of hospitalization of Respiratory(RD) and cardiovascular (CVD) associated with ambient exposure caused by traffic emission in relation to their size andspecific sources of emission on different scenarios interior a border Urban Rural Urban restricted access (freeways andinterstates)

A significant correlation of PM1025 exposure from mobile emission and hospital admissions for selected Respiratory (RD) andcardiovascular (CVD) diagnoses was established The results showed that PM emissions in urban restricted access (freeways andinterstates) is mainly caused by traffic Therefore people living close to highways are more exposed higher vehicular emissions

Conclusions

We found statistically significant associations between mobile PM25 caused by traffic emission with Respiratory and Cardiovascular Diseases in the study areaSubsequently a correlation between cardio-respiratory mortality is established

A significant correlation of PM1025 exposure from mobile emission and hospital admissions for selected Respiratory (RD) and cardiovascular (CVD) diagnoses isestablished The results showed that PM emissions in urban restricted access (freeways and interstates) is mainly caused by traffic Therefore people living close tohighways receive higher vehicular emissions

The table shows the percentage of PM mobile exposure in the analyzed areas contributing to increase the risk of Respiratory and Cardiovascular Diseases

An examination was conducted of the synoptic and local meteorology for the June 2006 ozone episode using the WRF model to determine how meteorological parametersinfluence the formation transport and dispersion of ozone in the PdN The predominant synoptic feature of the ozone event day was the expansion intensification and slowprogression of an upper-level ridge of high pressure The high ozone episodes are associated with highly stable atmospheres strong temperature inversions with low mixingheights and therefore low mixing volumes Under these conditions emissions such as NOx lead to highly polluted conditions that favor ozone formation

BenMAP Conclusions

We have estimated the number and economic value of health impacts resulting

from changes in air pollution concentrations of PM 25 in the PdN region

Reduction of Pm 25 4 UGm3= Avoided 213 cases respiratory cardiovascular

diseses and Economic Benefits associated with the Response of PM25 Emission + $

1295000

Increase of PM25 7 ugm3 = increasing Dies= 326 economic Unbenefits= 2345000$

Bibliography

1 Dockery DW Pope CAI Xu X Spengler JD Ware JH Fay ME Ferris BG Speizer FE An association between air pollution and mortality in six US cities N Engl J Med 3291753ndash1759 (1993)

2 Samet JM Dominici F Curriero FC Coursac I Zeger SL Fine particulate air pollution and mortality in 20 US cities 1987ndash1994 N Engl J Med 3431742ndash1749 (2000)

3 Nel AE Diaz-Sanchez D Li N The role of particulate pollutants in pulmonary inflammation and asthma evidence for the involvement of organic chemicals and oxidative stress Curr Opin Pulm Med 20017 20ndash26

4 Westerholm R Karl-Erik E Exhaust emissions from lightand heavy-duty vehicles chemical composition impact of exhaust after treatment and fuel parameters Environ Health Perspect 102(suppl 4)13ndash23 (1994)

5 Bascom R Bromberg P Costa D Delvin R Dockery D Frampton M Lambert W Samet J Speizer F Utell

6 Health effects of outdoor air pollution Am J Respir Crit Care Med 1533ndash50 (1996)

7 Chow JC Watson JG Frazier CA Egami RT Goodrich A Ralph C Spatial and temporal source contributions to

8 PM10 and PM25 in Reno NV In PM-10 Implementation of Standards Transactions An APCAEPA International Speciality Conference San Francisco CA (Mathal CV Stonefield DH eds) PittsburghAPCA 1988439ndash457

9 overview In Particulate Matter Health and Regulatory Issues VIP-49 Proceedings of an International Specialty Conference 4ndash6 April 1995 Pittsburgh PA PittsburghAir and Waste Management Association 1995577ndash598

10 Kunzli N Kaiser R Medina S Studnicka M Chanel O

11 Filliger P Herry M Horak F Jr Puybonnieux-Texier V Quenel P et al Public-health impact of outdoor and traffic- related air pollution a European assessment Lancet 356795ndash801 (2000)

Bibliography

1 Sioutas C Delfino RJ Singh M Exposure assessment for atmospheric ultrafine particles (UFP) and implications in epidemiological research Environ Health Perspect 2005113947ndash955

2 Mosleh M Blau PJ Dumitrescu D (2004) Characteristics and morphology of wear particles from laboratory testing of disc brake materials Wear 2561128ndash1134

3 Kuumlnzli N et al (2000) Public-health impact of outdoor and traffi c-related air pollution a European assessment Lancet 356(9232)795ndash801

4 Dora C Phillips M eds (2000) Transport environment and health Copenhagen WHO Regional Office for Europe (WHO Regional Publications European Series No 89 httpwwweurowhointdocumente72015pdf accessed 26 November 2004)

5 Westerholm R Karl-Erik E Exhaust emissions from lightand

6 heavy-duty vehicles chemical composition impact of exhaust after treatment and fuel parameters Environ Health Perspect 102(suppl 4)13ndash23 (1994)

7 Fauser Tjell Mosbaek pigegaard Quantification of tire-Tread particles using extractable Organic Zinc as a Tracer Rubber Chemistry and Technology 1999 969Table shows some literature estimates of the contribution of tire wear to PM10 in air (Panko et al 2013) Gustafsson M Blomqvist G Gudmundsson A Dahl A Swietlicki E Bohgard M Lindbom J Ljungman A

8 Chen Y Shah N Huggins FE and Huffman GP (2006) Microanalysis of Ambient Particles from Lexington Ky by Electron Microscopy Atmos Environ 40 651ndash663

9 Donaldson K Tran CL Jimenez LA Duffin R Newby DE and Mills N (2005) Combustion-derived Nanoparticles A Review of Their Toxicology Following Inhalation Exposure Part Fibre Toxicol 2 10ndash23

10 Su D Serafino A Muller JO Jentoft RE Schlogl R and Fiorito S (2008) Cytotoxicity and Inflammatory Potential of Soot Particles of Low-emission Diesel Engines Environ Sci Technol 42 1761ndash1765

11 Maier KL Alessandrini F Beck-Speier I Hofer TPJ Diabatґe S Bitterle E Stoger T and Jakob T (2008) Health Effects of Ambient Particulate Matter-Biological Mechanisms and Inflammatory Responses to in Vitroand in Vivo Particle Exposures Inhalation Toxicol 20 319ndash337

Page 53: Studies of Air Pollutants and their Impact on Respiratory and ...€¦ · Ascarate Park C37 Monitoring Station: The National Ambient Air Quality Standard (NAAQS) for PM 10 and 2.5

Conclusions

We found statistically significant associations between mobile PM25 caused by traffic emission with Respiratory and Cardiovascular Diseases in the study areaSubsequently a correlation between cardio-respiratory mortality is established

A significant correlation of PM1025 exposure from mobile emission and hospital admissions for selected Respiratory (RD) and cardiovascular (CVD) diagnoses isestablished The results showed that PM emissions in urban restricted access (freeways and interstates) is mainly caused by traffic Therefore people living close tohighways receive higher vehicular emissions

The table shows the percentage of PM mobile exposure in the analyzed areas contributing to increase the risk of Respiratory and Cardiovascular Diseases

An examination was conducted of the synoptic and local meteorology for the June 2006 ozone episode using the WRF model to determine how meteorological parametersinfluence the formation transport and dispersion of ozone in the PdN The predominant synoptic feature of the ozone event day was the expansion intensification and slowprogression of an upper-level ridge of high pressure The high ozone episodes are associated with highly stable atmospheres strong temperature inversions with low mixingheights and therefore low mixing volumes Under these conditions emissions such as NOx lead to highly polluted conditions that favor ozone formation

BenMAP Conclusions

We have estimated the number and economic value of health impacts resulting

from changes in air pollution concentrations of PM 25 in the PdN region

Reduction of Pm 25 4 UGm3= Avoided 213 cases respiratory cardiovascular

diseses and Economic Benefits associated with the Response of PM25 Emission + $

1295000

Increase of PM25 7 ugm3 = increasing Dies= 326 economic Unbenefits= 2345000$

Bibliography

1 Dockery DW Pope CAI Xu X Spengler JD Ware JH Fay ME Ferris BG Speizer FE An association between air pollution and mortality in six US cities N Engl J Med 3291753ndash1759 (1993)

2 Samet JM Dominici F Curriero FC Coursac I Zeger SL Fine particulate air pollution and mortality in 20 US cities 1987ndash1994 N Engl J Med 3431742ndash1749 (2000)

3 Nel AE Diaz-Sanchez D Li N The role of particulate pollutants in pulmonary inflammation and asthma evidence for the involvement of organic chemicals and oxidative stress Curr Opin Pulm Med 20017 20ndash26

4 Westerholm R Karl-Erik E Exhaust emissions from lightand heavy-duty vehicles chemical composition impact of exhaust after treatment and fuel parameters Environ Health Perspect 102(suppl 4)13ndash23 (1994)

5 Bascom R Bromberg P Costa D Delvin R Dockery D Frampton M Lambert W Samet J Speizer F Utell

6 Health effects of outdoor air pollution Am J Respir Crit Care Med 1533ndash50 (1996)

7 Chow JC Watson JG Frazier CA Egami RT Goodrich A Ralph C Spatial and temporal source contributions to

8 PM10 and PM25 in Reno NV In PM-10 Implementation of Standards Transactions An APCAEPA International Speciality Conference San Francisco CA (Mathal CV Stonefield DH eds) PittsburghAPCA 1988439ndash457

9 overview In Particulate Matter Health and Regulatory Issues VIP-49 Proceedings of an International Specialty Conference 4ndash6 April 1995 Pittsburgh PA PittsburghAir and Waste Management Association 1995577ndash598

10 Kunzli N Kaiser R Medina S Studnicka M Chanel O

11 Filliger P Herry M Horak F Jr Puybonnieux-Texier V Quenel P et al Public-health impact of outdoor and traffic- related air pollution a European assessment Lancet 356795ndash801 (2000)

Bibliography

1 Sioutas C Delfino RJ Singh M Exposure assessment for atmospheric ultrafine particles (UFP) and implications in epidemiological research Environ Health Perspect 2005113947ndash955

2 Mosleh M Blau PJ Dumitrescu D (2004) Characteristics and morphology of wear particles from laboratory testing of disc brake materials Wear 2561128ndash1134

3 Kuumlnzli N et al (2000) Public-health impact of outdoor and traffi c-related air pollution a European assessment Lancet 356(9232)795ndash801

4 Dora C Phillips M eds (2000) Transport environment and health Copenhagen WHO Regional Office for Europe (WHO Regional Publications European Series No 89 httpwwweurowhointdocumente72015pdf accessed 26 November 2004)

5 Westerholm R Karl-Erik E Exhaust emissions from lightand

6 heavy-duty vehicles chemical composition impact of exhaust after treatment and fuel parameters Environ Health Perspect 102(suppl 4)13ndash23 (1994)

7 Fauser Tjell Mosbaek pigegaard Quantification of tire-Tread particles using extractable Organic Zinc as a Tracer Rubber Chemistry and Technology 1999 969Table shows some literature estimates of the contribution of tire wear to PM10 in air (Panko et al 2013) Gustafsson M Blomqvist G Gudmundsson A Dahl A Swietlicki E Bohgard M Lindbom J Ljungman A

8 Chen Y Shah N Huggins FE and Huffman GP (2006) Microanalysis of Ambient Particles from Lexington Ky by Electron Microscopy Atmos Environ 40 651ndash663

9 Donaldson K Tran CL Jimenez LA Duffin R Newby DE and Mills N (2005) Combustion-derived Nanoparticles A Review of Their Toxicology Following Inhalation Exposure Part Fibre Toxicol 2 10ndash23

10 Su D Serafino A Muller JO Jentoft RE Schlogl R and Fiorito S (2008) Cytotoxicity and Inflammatory Potential of Soot Particles of Low-emission Diesel Engines Environ Sci Technol 42 1761ndash1765

11 Maier KL Alessandrini F Beck-Speier I Hofer TPJ Diabatґe S Bitterle E Stoger T and Jakob T (2008) Health Effects of Ambient Particulate Matter-Biological Mechanisms and Inflammatory Responses to in Vitroand in Vivo Particle Exposures Inhalation Toxicol 20 319ndash337

Page 54: Studies of Air Pollutants and their Impact on Respiratory and ...€¦ · Ascarate Park C37 Monitoring Station: The National Ambient Air Quality Standard (NAAQS) for PM 10 and 2.5

BenMAP Conclusions

We have estimated the number and economic value of health impacts resulting

from changes in air pollution concentrations of PM 25 in the PdN region

Reduction of Pm 25 4 UGm3= Avoided 213 cases respiratory cardiovascular

diseses and Economic Benefits associated with the Response of PM25 Emission + $

1295000

Increase of PM25 7 ugm3 = increasing Dies= 326 economic Unbenefits= 2345000$

Bibliography

1 Dockery DW Pope CAI Xu X Spengler JD Ware JH Fay ME Ferris BG Speizer FE An association between air pollution and mortality in six US cities N Engl J Med 3291753ndash1759 (1993)

2 Samet JM Dominici F Curriero FC Coursac I Zeger SL Fine particulate air pollution and mortality in 20 US cities 1987ndash1994 N Engl J Med 3431742ndash1749 (2000)

3 Nel AE Diaz-Sanchez D Li N The role of particulate pollutants in pulmonary inflammation and asthma evidence for the involvement of organic chemicals and oxidative stress Curr Opin Pulm Med 20017 20ndash26

4 Westerholm R Karl-Erik E Exhaust emissions from lightand heavy-duty vehicles chemical composition impact of exhaust after treatment and fuel parameters Environ Health Perspect 102(suppl 4)13ndash23 (1994)

5 Bascom R Bromberg P Costa D Delvin R Dockery D Frampton M Lambert W Samet J Speizer F Utell

6 Health effects of outdoor air pollution Am J Respir Crit Care Med 1533ndash50 (1996)

7 Chow JC Watson JG Frazier CA Egami RT Goodrich A Ralph C Spatial and temporal source contributions to

8 PM10 and PM25 in Reno NV In PM-10 Implementation of Standards Transactions An APCAEPA International Speciality Conference San Francisco CA (Mathal CV Stonefield DH eds) PittsburghAPCA 1988439ndash457

9 overview In Particulate Matter Health and Regulatory Issues VIP-49 Proceedings of an International Specialty Conference 4ndash6 April 1995 Pittsburgh PA PittsburghAir and Waste Management Association 1995577ndash598

10 Kunzli N Kaiser R Medina S Studnicka M Chanel O

11 Filliger P Herry M Horak F Jr Puybonnieux-Texier V Quenel P et al Public-health impact of outdoor and traffic- related air pollution a European assessment Lancet 356795ndash801 (2000)

Bibliography

1 Sioutas C Delfino RJ Singh M Exposure assessment for atmospheric ultrafine particles (UFP) and implications in epidemiological research Environ Health Perspect 2005113947ndash955

2 Mosleh M Blau PJ Dumitrescu D (2004) Characteristics and morphology of wear particles from laboratory testing of disc brake materials Wear 2561128ndash1134

3 Kuumlnzli N et al (2000) Public-health impact of outdoor and traffi c-related air pollution a European assessment Lancet 356(9232)795ndash801

4 Dora C Phillips M eds (2000) Transport environment and health Copenhagen WHO Regional Office for Europe (WHO Regional Publications European Series No 89 httpwwweurowhointdocumente72015pdf accessed 26 November 2004)

5 Westerholm R Karl-Erik E Exhaust emissions from lightand

6 heavy-duty vehicles chemical composition impact of exhaust after treatment and fuel parameters Environ Health Perspect 102(suppl 4)13ndash23 (1994)

7 Fauser Tjell Mosbaek pigegaard Quantification of tire-Tread particles using extractable Organic Zinc as a Tracer Rubber Chemistry and Technology 1999 969Table shows some literature estimates of the contribution of tire wear to PM10 in air (Panko et al 2013) Gustafsson M Blomqvist G Gudmundsson A Dahl A Swietlicki E Bohgard M Lindbom J Ljungman A

8 Chen Y Shah N Huggins FE and Huffman GP (2006) Microanalysis of Ambient Particles from Lexington Ky by Electron Microscopy Atmos Environ 40 651ndash663

9 Donaldson K Tran CL Jimenez LA Duffin R Newby DE and Mills N (2005) Combustion-derived Nanoparticles A Review of Their Toxicology Following Inhalation Exposure Part Fibre Toxicol 2 10ndash23

10 Su D Serafino A Muller JO Jentoft RE Schlogl R and Fiorito S (2008) Cytotoxicity and Inflammatory Potential of Soot Particles of Low-emission Diesel Engines Environ Sci Technol 42 1761ndash1765

11 Maier KL Alessandrini F Beck-Speier I Hofer TPJ Diabatґe S Bitterle E Stoger T and Jakob T (2008) Health Effects of Ambient Particulate Matter-Biological Mechanisms and Inflammatory Responses to in Vitroand in Vivo Particle Exposures Inhalation Toxicol 20 319ndash337

Page 55: Studies of Air Pollutants and their Impact on Respiratory and ...€¦ · Ascarate Park C37 Monitoring Station: The National Ambient Air Quality Standard (NAAQS) for PM 10 and 2.5

Bibliography

1 Dockery DW Pope CAI Xu X Spengler JD Ware JH Fay ME Ferris BG Speizer FE An association between air pollution and mortality in six US cities N Engl J Med 3291753ndash1759 (1993)

2 Samet JM Dominici F Curriero FC Coursac I Zeger SL Fine particulate air pollution and mortality in 20 US cities 1987ndash1994 N Engl J Med 3431742ndash1749 (2000)

3 Nel AE Diaz-Sanchez D Li N The role of particulate pollutants in pulmonary inflammation and asthma evidence for the involvement of organic chemicals and oxidative stress Curr Opin Pulm Med 20017 20ndash26

4 Westerholm R Karl-Erik E Exhaust emissions from lightand heavy-duty vehicles chemical composition impact of exhaust after treatment and fuel parameters Environ Health Perspect 102(suppl 4)13ndash23 (1994)

5 Bascom R Bromberg P Costa D Delvin R Dockery D Frampton M Lambert W Samet J Speizer F Utell

6 Health effects of outdoor air pollution Am J Respir Crit Care Med 1533ndash50 (1996)

7 Chow JC Watson JG Frazier CA Egami RT Goodrich A Ralph C Spatial and temporal source contributions to

8 PM10 and PM25 in Reno NV In PM-10 Implementation of Standards Transactions An APCAEPA International Speciality Conference San Francisco CA (Mathal CV Stonefield DH eds) PittsburghAPCA 1988439ndash457

9 overview In Particulate Matter Health and Regulatory Issues VIP-49 Proceedings of an International Specialty Conference 4ndash6 April 1995 Pittsburgh PA PittsburghAir and Waste Management Association 1995577ndash598

10 Kunzli N Kaiser R Medina S Studnicka M Chanel O

11 Filliger P Herry M Horak F Jr Puybonnieux-Texier V Quenel P et al Public-health impact of outdoor and traffic- related air pollution a European assessment Lancet 356795ndash801 (2000)

Bibliography

1 Sioutas C Delfino RJ Singh M Exposure assessment for atmospheric ultrafine particles (UFP) and implications in epidemiological research Environ Health Perspect 2005113947ndash955

2 Mosleh M Blau PJ Dumitrescu D (2004) Characteristics and morphology of wear particles from laboratory testing of disc brake materials Wear 2561128ndash1134

3 Kuumlnzli N et al (2000) Public-health impact of outdoor and traffi c-related air pollution a European assessment Lancet 356(9232)795ndash801

4 Dora C Phillips M eds (2000) Transport environment and health Copenhagen WHO Regional Office for Europe (WHO Regional Publications European Series No 89 httpwwweurowhointdocumente72015pdf accessed 26 November 2004)

5 Westerholm R Karl-Erik E Exhaust emissions from lightand

6 heavy-duty vehicles chemical composition impact of exhaust after treatment and fuel parameters Environ Health Perspect 102(suppl 4)13ndash23 (1994)

7 Fauser Tjell Mosbaek pigegaard Quantification of tire-Tread particles using extractable Organic Zinc as a Tracer Rubber Chemistry and Technology 1999 969Table shows some literature estimates of the contribution of tire wear to PM10 in air (Panko et al 2013) Gustafsson M Blomqvist G Gudmundsson A Dahl A Swietlicki E Bohgard M Lindbom J Ljungman A

8 Chen Y Shah N Huggins FE and Huffman GP (2006) Microanalysis of Ambient Particles from Lexington Ky by Electron Microscopy Atmos Environ 40 651ndash663

9 Donaldson K Tran CL Jimenez LA Duffin R Newby DE and Mills N (2005) Combustion-derived Nanoparticles A Review of Their Toxicology Following Inhalation Exposure Part Fibre Toxicol 2 10ndash23

10 Su D Serafino A Muller JO Jentoft RE Schlogl R and Fiorito S (2008) Cytotoxicity and Inflammatory Potential of Soot Particles of Low-emission Diesel Engines Environ Sci Technol 42 1761ndash1765

11 Maier KL Alessandrini F Beck-Speier I Hofer TPJ Diabatґe S Bitterle E Stoger T and Jakob T (2008) Health Effects of Ambient Particulate Matter-Biological Mechanisms and Inflammatory Responses to in Vitroand in Vivo Particle Exposures Inhalation Toxicol 20 319ndash337

Page 56: Studies of Air Pollutants and their Impact on Respiratory and ...€¦ · Ascarate Park C37 Monitoring Station: The National Ambient Air Quality Standard (NAAQS) for PM 10 and 2.5

Bibliography

1 Sioutas C Delfino RJ Singh M Exposure assessment for atmospheric ultrafine particles (UFP) and implications in epidemiological research Environ Health Perspect 2005113947ndash955

2 Mosleh M Blau PJ Dumitrescu D (2004) Characteristics and morphology of wear particles from laboratory testing of disc brake materials Wear 2561128ndash1134

3 Kuumlnzli N et al (2000) Public-health impact of outdoor and traffi c-related air pollution a European assessment Lancet 356(9232)795ndash801

4 Dora C Phillips M eds (2000) Transport environment and health Copenhagen WHO Regional Office for Europe (WHO Regional Publications European Series No 89 httpwwweurowhointdocumente72015pdf accessed 26 November 2004)

5 Westerholm R Karl-Erik E Exhaust emissions from lightand

6 heavy-duty vehicles chemical composition impact of exhaust after treatment and fuel parameters Environ Health Perspect 102(suppl 4)13ndash23 (1994)

7 Fauser Tjell Mosbaek pigegaard Quantification of tire-Tread particles using extractable Organic Zinc as a Tracer Rubber Chemistry and Technology 1999 969Table shows some literature estimates of the contribution of tire wear to PM10 in air (Panko et al 2013) Gustafsson M Blomqvist G Gudmundsson A Dahl A Swietlicki E Bohgard M Lindbom J Ljungman A

8 Chen Y Shah N Huggins FE and Huffman GP (2006) Microanalysis of Ambient Particles from Lexington Ky by Electron Microscopy Atmos Environ 40 651ndash663

9 Donaldson K Tran CL Jimenez LA Duffin R Newby DE and Mills N (2005) Combustion-derived Nanoparticles A Review of Their Toxicology Following Inhalation Exposure Part Fibre Toxicol 2 10ndash23

10 Su D Serafino A Muller JO Jentoft RE Schlogl R and Fiorito S (2008) Cytotoxicity and Inflammatory Potential of Soot Particles of Low-emission Diesel Engines Environ Sci Technol 42 1761ndash1765

11 Maier KL Alessandrini F Beck-Speier I Hofer TPJ Diabatґe S Bitterle E Stoger T and Jakob T (2008) Health Effects of Ambient Particulate Matter-Biological Mechanisms and Inflammatory Responses to in Vitroand in Vivo Particle Exposures Inhalation Toxicol 20 319ndash337