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Center for Environmental Research and Technology

University of California, RiversideBourns College of Engineering

Measurement of PMMeasurement of PM1010 Emission Rates Emission Rates from Roadways in Las Vegas, Nevada from Roadways in Las Vegas, Nevada

Using a SCAMPER Mobile Platform Using a SCAMPER Mobile Platform with Realwith Real--Time SensorsTime Sensors

Dennis R. Dennis R. FitzFitz, Kurt , Kurt BumillerBumillerUniversity of California, RiversideUniversity of California, Riverside

College of EngineeringCollege of Engineering--Center for Environmental Research Center for Environmental Research and Technologyand Technology

Vic Vic EtyemezianEtyemezian, Hampden , Hampden KuhnsKuhns, George , George NikolichNikolichDesert Research Institute, Division of Atmospheric Desert Research Institute, Division of Atmospheric

SciencesSciences



IntroductionIntroduction

•• Quantifying PM Emissions from Paved Roads Quantifying PM Emissions from Paved Roads are Important Because:are Important Because:

–– Significant contributor to exceeding standard in Significant contributor to exceeding standard in many air basinsmany air basins

–– Estimated inventories of geologic PM are higher Estimated inventories of geologic PM are higher than measured concentrationsthan measured concentrations

–– Emissions due to paved roads are a major Emissions due to paved roads are a major component of geologic emissionscomponent of geologic emissions



•• Emission Inventories are Difficult to Determine Emission Inventories are Difficult to Determine Because:Because:

–– Fugitive nature leads to high uncertainties for Fugitive nature leads to high uncertainties for emission factorsemission factors

–– Current inventories are based on an empirical Current inventories are based on an empirical equation derived from upwindequation derived from upwind--downwind sampling downwind sampling from primarily industrial roadsfrom primarily industrial roads

–– Modeling is required to determine emission factors Modeling is required to determine emission factors from upwindfrom upwind--downwind concentrationsdownwind concentrations

–– PM concentration differences are small between PM concentration differences are small between upwind and downwind locations for most roadsupwind and downwind locations for most roads



ObjectivesObjectives

•• Develop a More Accurate and CostDevelop a More Accurate and Cost--Effective Effective Approach for Measuring PMApproach for Measuring PM10 10 Emission Emission Factors for Paved RoadsFactors for Paved Roads

•• Determine PMDetermine PM1010 Emission Factors for Various Emission Factors for Various Roadway TypesRoadway Types



Approach InspirationApproach Inspiration



ApproachApproach•• Measure PM Directly in Front of and Behind a Measure PM Directly in Front of and Behind a

Test Vehicle with an Test Vehicle with an IsokineticIsokinetic Sampling Sampling ProbeProbe

•• Use RealUse Real--Time Sensors to Accumulate Large Time Sensors to Accumulate Large Amounts of PM Data QuicklyAmounts of PM Data Quickly

• Calibrate Real-time Sensors with Filter Collection.

•• Determine the Variability of PM behind the Determine the Variability of PM behind the Test VehicleTest Vehicle

•• Determine Emission Factors Based on the Determine Emission Factors Based on the Concentration Within the Vehicle’s WakeConcentration Within the Vehicle’s Wake



Experimental DesignExperimental Design•• DustTrakDustTrak PM Optical Scattering SensorsPM Optical Scattering Sensors•• IsokineticIsokinetic Sampling ProbeSampling Probe

–– Provide Provide isokineticisokinetic sampling from 0sampling from 0--60 mph60 mph–– Slow sample flow without creating a virtual Slow sample flow without creating a virtual

impactorimpactor•• Inlets Located in Front of Test Vehicle and on Inlets Located in Front of Test Vehicle and on

Small Trailer Towed Behind it Small Trailer Towed Behind it •• Low Volume PM10 Sample Collected Low Volume PM10 Sample Collected

SimultaneouslySimultaneously•• Approach Designated SCAMPER: Approach Designated SCAMPER: System of System of

Continuous Aerosol Monitoring of Particulate Continuous Aerosol Monitoring of Particulate Emissions from RoadwaysEmissions from Roadways



IsokineticIsokinetic Sampling ProbeSampling ProbeInlet

Pitot Static Tube

To DustTrak

Filter

PC Data AcquisitionSystem

Flow Control Valves

PressureTransducer

1 inch PVC Pipe

To Vacuum Pump

Solenoid Valves

Rotameters



Sampling Design for Wake Sampling Design for Wake CharacterizationCharacterization

4.26m

DustTrak #1 Inlet (1.98 or 2.59 m above ground)

DustTrak #2 & #3 Inlets (0.78 & 1.98 or 2.59 m above ground)

DustTrak 2 & Pump

DustTrak #1 & Pump

DustTrak 3 & Pump

0.49m

DAS

Batteries


University of California, RiversideBourns College of EngineeringIsokineticIsokinetic Sampling Probe Sampling Probe

Mounted on Front of Test Mounted on Front of Test VehicleVehicle



Test Trailer and Test Trailer and IsokineticIsokineticSampling ProbesSampling Probes



Wake CharacterizationWake Characterization

•• Test on Unused Deteriorating Paved Road to Test on Unused Deteriorating Paved Road to Provide High PM ConcentrationsProvide High PM Concentrations

•• Measured PM Concentrations at a Variety of Measured PM Concentrations at a Variety of Test Points On the Trailer Relative to a Test Points On the Trailer Relative to a Reference Test PointReference Test Point

•• Fully Characterized the Wake PM Fully Characterized the Wake PM Concentrations at Speeds from 10Concentrations at Speeds from 10--60 mph60 mph



Wake Characterization ResultsWake Characterization Results

0

1

2

3

4

5

6

7

8

20 30 40 50 60

Speed mi/hr

PM10

, mg/

m3

Probe 1, 1.98 m high, 1.22m left

Probe 2, 0.78m high, center

Probe 3, 1.98m high, center



Wake Characterization ResultsWake Characterization Results

0

2

4

6

8

10

12

20 30 40 50 60

Speed mi/hr

PM10

, mg/

m3

Probe 1, 2.60 mhigh, 1.22 m leftProbe 2, 0.78 m high, center

Probe 3, 2.59 m high, center



Wake Characterization ResultsWake Characterization Results•• The precision of the measurement (with three The precision of the measurement (with three

DustTraksDustTraks sampling from the same point).sampling from the same point).•• The homogeneity of the PM within the vehicle’s The homogeneity of the PM within the vehicle’s

wake with respect to the vehicle’s speed.wake with respect to the vehicle’s speed.•• The vertical and horizontal extent of the plume The vertical and horizontal extent of the plume

as a function of vehicle speed and cross wind.as a function of vehicle speed and cross wind.•• The optimum sampling position.The optimum sampling position.•• Exhaust PM10 could not be detectedExhaust PM10 could not be detected



Emission Factor MeasurementsEmission Factor Measurements•• Performed Repeated Measurements Over Test Performed Repeated Measurements Over Test

Loops in Southern California.Loops in Southern California.•• Tested All Types of Roadways and SpeedsTested All Types of Roadways and Speeds

–– FreewayFreeway–– ArterialArterial–– CollectorCollector–– LocalLocal

•• Calculated Emission Factors Based on Frontal Calculated Emission Factors Based on Frontal Area (Wake Size) For Various Road Type Area (Wake Size) For Various Road Type Segments.Segments.



Emission Factor CalculationEmission Factor Calculation

•• ER (mg/m) = (PM10ER (mg/m) = (PM10rr ––PM10PM10ff) * c *) * c *AAffwhere:where:ER = PM10 Emission RateER = PM10 Emission RatePM10PM10rr = PM10 concentration, rear = PM10 concentration, rear DustTrakDustTrakPM10PM10ff = PM10 concentration, front = PM10 concentration, front DustTrakDustTrakc = Calibration factor to relate c = Calibration factor to relate DustTrakDustTrak

response to filterresponse to filter--based PM10 mass based PM10 mass measurementmeasurement

AAff = Frontal area of the test vehicle= Frontal area of the test vehicle



Comparison With Other Studies Comparison With Other Studies Using Southern California DataUsing Southern California Data

Study Road Type Emission Factor(g/VKT)

Emission Factor(lbs/VMT)

This Study Freeway-local 0.06 – 0.13 0.00022-0.00047

Venkatram and Fitz, 1998 4 Freeway-local 0.1-0.3 0.00036-0.0011

Cahill et al., 1995 19 Intersection <0.3 <0.001

Claiborn et al., 1995 8 Freeway-local 0.5 to 34 0.0018-0.12

Harding Lawson, 1996 6 Freeway-local 0.03 to 180 0.00011-0.65AP-42 Defaulta Arterial-local 0.08-0.53 0.00030-0.0019

ARB Default Arterial-local 0.10-0.61 0.00036-0.0022

a: From silt loadings measured in southern California, assuming 2 ton vehicles



Time Series Emission Rates for Time Series Emission Rates for Las Vegas Test Route (all road types)Las Vegas Test Route (all road types)

PM-10 Emission Rate Las Vegas Test Route February 14, 2005 (mean 0.065 g/km)

-1

0

1

2

3

4

5

6

7

9:00 10:00 11:00 12:00 13:00 14:00 15:00 16:00 17:00 18:00

Time

PM10

Em

issi

on R

ate,

g/k

m



PM10 Emission Rate Plotted PM10 Emission Rate Plotted on Las Vegas Test Routeon Las Vegas Test Route



PM10 Emission Rate Plotted PM10 Emission Rate Plotted at Higher Resolutionat Higher Resolution



ConclusionsConclusions• On-Board Real Time Measurement is a Viable

Method to Characterize PM Emissions form Vehicles on Paved Roads

• Measurements in Southern California were Lower than Those Predicted by the AP-42 Empirical Equation

• Advantages of the Method are:– Low cost– No upwind-downwind calibration required– DustTrak (light scattering sensor) calibrated to PM10 mass

measurement during sampling– Ability to easily collect large amounts of data– Ability to easily determine PM “Hot Spots”



ConclusionsConclusions• Results Showed That Small Fractions of

Roadways are Responsible for Most of the PM10 Emissions.

– These areas would be difficult to locate with scattered silt sampling.

– Allows compliance efforts to focus on problem areas

• The Method has a Precision of Approximately 20% Based on Repeated Test Runs of Routes.

• Comparison with the DRI “TRAKER” Approach Based on over 700 Miles of Co-Sampling is Pending.



AcknowledgementsAcknowledgementsWe thank the Clark County Department of Air We thank the Clark County Department of Air Quality and Environmental Management for Quality and Environmental Management for

providing financial support and Russ Merle and providing financial support and Russ Merle and Rodney Langston for their help in conducting the Rodney Langston for their help in conducting the

Las Vegas field study.Las Vegas field study.

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