Mapping of Airborne Particulate Matter under Two Land Uses: Agriculture and

Unpaved Road

Principal Investigator: Manoj K. Shukla, Ph.D.Assistant Professor of Environmental Soil Physics Department of Plant and Environmental SciencesNew Mexico State University, MSC 3Q, P.O. Box 30003Las Cruces, NM-88003, USACo- Investigators:Juan Pedro Flores Margez, Ph.D.Assistant Professor Universidad Autónoma de Ciudad Juárez, México

andD. R. Miller; University of Connecticut, USAR. Arimoto; Carlsbad Environ. Monitoring & Research Center, NMSU, Carlsbath

Particulate matter (PM) of aerodynamic diameter ≤ 10 microns (PM10) and 2.5 microns (PM2.5) are emitted from a large number of sources:

Point (power plant, cement plant, factories), Mobile (trucks, automobiles), Nonpoint sources (agricultural operations,

unpaved roads, cattle ranches)

The aerosol with small diameter, large surface area, low density, can travel significant distances from the source

The large specific surface area enhances its capacity to absorb other chemicals and transport to downwind locations (i.e., agricultural fields, recreational areas, urban areas, water bodies, etc.)

Most unpaved roads consist of graded and compacted roadbed usually created from the parent material

The rolling wheels of vehicles impart a force, pulverizes the roadbed material and ejects particles from the shearing force as well as by the turbulent wake

More information is needed on the quantity, composition, fluxes and transport distances of fugitive dust from agriculture fields and unpaved roads and their contribution to PM10 exceedances

Agricultural dust sources are difficult to quantify: Complexity Nonpoint nature of agricultural operations, Temporal (i.e., daily, seasonal, annual) and Spatial variability due to inhomogeneous wide area sources

Variability of soil physical properties Variable agricultural practices and implements, Hydrological and meteorological conditions

Knowledge of the variability of these individual factors and their affect on PM emissions is critical to developing accurate air quality standards and models

Overall Objectives

Quantify PM emission from agricultural fields due to tillage operations

Quantify PM emission from unpaved roads due to vehicular traffic

Develop and test a low cost sensor for PM accounting

Particulate Matter Emitted by Tillage Operations in an Agriculture Field in the Messiah Valley of New

Mexico

The agriculture field for the PM emission experiment was located at the Plant Sciences Research Center (PSRC) of New Mexico State University about 12 km south of Las Cruces in the Messiah Valley, Dona Ana County of NM along the Rio Grande River

3232oo11’35.84” N and 10611’35.84” N and 106oo44’08.75”W44’08.75”W

Field for Ag Dust Experiment

Unpaved road for vehicle generated dust experiment

Rio Grande River

Plot Layout for Agriculture Dust Experiment

Plots

Dust Track Samplers 0,

0

A field planted to cotton during 2007 was subdivided into six plots of sizes 5-m by 20-m, separated by a 5-m x 5-m strip

The plots were:

(1) Disked using a Massey Fergusson John Deer 7810 disk plow

(2) Chiseled using Johnson chisel plow with 93 cm height and 245 cm width

(3) Tillage operations were conducted at two speeds with average tractor speeds of 4.8 and 6.5 km/h, respectively

(4) Three dust track samplers were kept at 100 cm height above the soil surface on the windward side of the plot separated by a distance of 270 cm

(5) A sonic anemometer was placed at the north-west corner of field

Dust Track

Sonic Anemometer

Disking Chiseling

Plot Moisture Content Sand Silt Clay Bulk

DensityPenetrat

ioncm3 cm-3 % % % g cm-3 Kg cm-2

1 0.096±0.01 29.6±2.3 45.0±2.0 25.4±1.

21.32±0.

1515.05±2

.87

2 0.101±0.011 26.0±2.5 47.4±2.1 26.6±0.

51.20±0.

1610.90±1

.32

3 0.105±0.004 23.7±2.0 49.4±2.1 26.8±0.

41.27±0.

0910.69±1

.64

4 0.096±0.011 24.1±3.0 48.9±2.6 27.0±0.

51.34±0.

1215.33±2

.21

5 0.100±0.012 24.8±1.6 47.8±1.5 27.4±0.

51.32±0.

0413.92±1

.53

6 0.094±0.016 28.4±1.5 46.0±1.4 25.6±1.

91.33±0.

0611.46±0

.88

Antecedent Soil Moisture Content and Soil Physical Properties

Moisture content

Bulk density

Clay content Penetration resistance

PlotMoistu

re Conten

tSand Silt Clay

Bulk Densit

yPenetrat

ion

1 0.10 0.08 0.04 0.05 0.12 0.192 0.11 0.10 0.04 0.02 0.13 0.123 0.04 0.08 0.04 0.01 0.07 0.154 0.11 0.12 0.05 0.02 0.09 0.145 0.12 0.06 0.03 0.02 0.03 0.116 0.17 0.05 0.03 0.07 0.05 0.08

Coefficient of Variation (CV) of Soil Physical Properties

CV < 0.15, low; CV > 0.35, high; 0.15 < CV < 0.35, moderate

-3

-2

-1

0

1

2

3

4

5

1 51 101 151 201 251 301 351 401 451 501 551

time (1/10) seconds

Win

d Ve

l (m

/s)

Ux Vy Wz

Wind Velocity in x, y, z direction Sonic Anemometer

0

0.3

0.6

0.9

1.2

1.5

10:2

9:00

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9:29

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9:58

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1:25

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2:23

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10:3

4:48

Time

Con

cent

ratio

n

Aerosol Conc (mg/m3)

Plot 1: Disking

0

0.3

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10:3

5:00

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10:4

0:48

Time

Con

cent

ratio

n

Aerosol Conc (mg/m3)

Plot 2: Disking

0

0.3

0.6

0.9

1.2

1.5

10:4

1:00

10:4

1:28

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1:56

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3:48

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4:16

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5:40

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10:4

6:36

Time

Con

cent

ratio

n

Aerosol Conc (mg/m3)

Plot 3: Disking

0

0.3

0.6

0.9

1.2

1.5

10:4

7:00

10:4

7:28

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7:56

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0:16

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1:12

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10:5

2:36

Time

Con

cent

ratio

n

Aerosol Conc (mg/m3)Plot 4: Disking

0

0.3

0.6

0.9

1.2

1.5

10:5

4:00

10:5

4:28

10:5

4:56

10:5

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6:20

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6:48

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7:44

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8:40

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10:5

9:36

Time

Con

cent

ratio

n

Aerosol Conc (mg/m3)

Plot 5: Disking

0

0.3

0.6

0.9

1.2

1.5

11:0

0:00

11:0

0:28

11:0

0:56

11:0

1:24

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1:52

11:0

2:20

11:0

2:48

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3:16

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3:44

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4:12

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4:40

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5:08

11:0

5:36

Time

Con

cent

ratio

n

Aerosol Conc (mg/m3)

Plot 6: Disking

PM concentration by dust track sampler for plots during Disking

The disking produced a distinct pulse of dust particles that are captured by the dust track sampler

The volume and peak concentrations were different among plots

The highest peak concentration of 1.55 mg m-3 was obtained from Plot 6

The lowest concentration of 0.88 mg m-3 was recorded from Plot 5

0

0.3

0.6

0.9

1.2

1.5

12:5

4:00

12:5

4:29

12:5

4:58

12:5

5:27

12:5

5:56

12:5

6:25

12:5

6:54

12:5

7:23

12:5

7:52

12:5

8:21

12:5

8:50

12:5

9:19

12:5

9:48

Time

Con

cent

ratio

n

Aerosol Conc (mg/m3)

Plot 1: Chiseling

0

0.3

0.6

0.9

1.2

1.5

13:0

1:00

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1:56

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6:36

Time

Con

cent

ratio

n

Aerosol Conc (mg/m3)

Plot 2: Chiseling

0

0.3

0.6

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1.2

1.5

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7:00

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2:36

Time

Con

cent

ratio

n

Aerosol Conc (mg/m3)

Plot 3: Chiseling

0

0.3

0.6

0.9

1.2

1.5

13:1

5:00

13:1

5:28

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5:56

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9:12

13:1

9:40

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0:08

13:2

0:36

Time

Con

cent

ratio

n Aerosol Conc (mg/m3)

Plot 4: Chiseling

0

0.3

0.6

0.9

1.2

1.5

13:2

1:00

13:2

1:28

13:2

1:56

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5:40

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13:2

6:36

Time

Con

cent

ratio

n

Aerosol Conc (mg/m3)

Plot 5: Chiseling

0

0.3

0.6

0.9

1.2

1.5

13:2

7:00

13:2

7:28

13:2

7:56

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9:48

13:3

0:16

13:3

0:44

13:3

1:12

13:3

1:40

13:3

2:08

13:3

2:36

Time

Con

cent

ratio

n

Aerosol Conc (mg/m3)

Plot 6: Chiseling

PM concentration by dust track sampler for plots during Chiseling

Chiseling produced a distinct pulse of dust particles that are captured by the dust track sampler

The volume and peak concentrations were different among plots

The highest peak concentration during chiseling operation was obtained from Plot 5 with a concentration of 0.83 mg m-3

The lowest concentration of 0.004 mg m-3 was recorded from Plot 2

Surface map for maximum dust concentration observed during disking

Surface map for maximum dust concentration observed during chiseling

Disking Chiseling

PlotPeak

Concentration

Min Concentrati

on

Peak Concentra

tion

Min Concentra

tion1 0.18 0.47 0.50 0.772 0.17 0.49 0.71 0.433 0.23 0.50 0.49 0.404 0.31 0.75 0.54 0.535 0.23 0.63 0.69 0.166 1.03 0.51 0.70 0.47

Coefficient of Variation (CV) of Dust Concentrations

Relationship between dust concentration during chiseling and soil parameters using stepwise regression

PeakC = 0.955 – 7.322 * AMC R2 = 0.23; P = 0.003

PeakC = 0.746 – 7.333 * AMC + 0.016*PR R2 = 0.28; P = 0.004 MinC = 0.029 – 0.001 * Clay R2 = 0.11; P = 0.04

MinC = 0.019 – 0.001 * Clay + 0.023*PR R2 = 0.20; P = 0.03 where PeakC and MinC are the maximum and minimum concentrations recorded by dust track sampler during chiseling;, respectively; AMC is antecedent soil moisture content; and PR is the penetration resistance

All six plots displayed low variability in sand, silt and clay contents, antecedent soil moisture content as well as penetration resistance with CV ranging from 1-19%

Peak concentration and the base of the concentration plume were different for different plots

Different plots also responded differently to disking and chiseling operations and CV for peak concentration ranged from 17% to 103% for disking operation and 49% to 71% for chiseling operation

Stepwise regression produced significant relationships between peak concentration and AMC and PR (R2=0.28; P<0.004)

Conclusions

Particulate Matter Emitted by a Vehicle Running on Unpaved Road

located in Messiah Valley New Mexico:

Measurement of Emissions and Development and Testing of a Low

Cost Sensor

Williams et al., 2008 Atmospheric Environment

(1)To carry out the mass accounting of airborne PM at different heights emitted by a vehicle traveling at two different speeds

(2)To analyze the collected airborne PM samples on sticky tapes using electron microscopes and image processing softwares to determine the particle size distribution and elemental composition of dust

(3)To demonstrate the usefulness of a simple method (rotorod and sticky tapes)

Objectives

Location of sticky tapes for the two experiments, Exp 1/Exp 2 48 km h-1/64 km h-1; 1/31 indicates slide 1 for Exp 1 and slide 31 for Exp 2

Rotorods and sticky tape installed at east (E), west (W) and top (T) of the tower at 1.5, 4.5 and 6 –m height

0

20

40

60

80

0 3 6 9 12 15 18 21 24

Time( h)

0

100

200

300

400Air Temp HumidityWind speed Wind direction

Average meteorological conditions including air temperature (oC), humidity (%), wind speed (km/h) and wind direction (deg) on 06/14/2006

Parameter Sand%

Silt%

Clay%

Moisture content

%

Number of blows at

5 cm

Number of blowsat 10 cm

Number of blows at15 cm

Compactionat 5 cm (kg

cm-2)

Mean 27.8 47.6 24.6 3.0 26.6 35.3 40.3 20.5

SE 3.4 2.8 0.7 0.0 4.1 6.1 4.8 1.1

Median 28.6 46.0 25.4 4.0 23.0 32.0 38.0 19.3

Mode - 46.0 25.4 4.0 18.0 - - 17.6

Stdev 7.7 6.3 1.6 0.01 10.7 16.0 12.8 3.8

Variance 59.2 40.3 2.7 0.0 115.0 257.2 163.9 14.4

Kurtosis -0.3 0.2 -1.7 0.08 -0.2 2.4 1.9 0.3

Skewness 0.3 0.0 -0.5 -1.18 1.1 1.4 1.31.0

Minimum 18.6 39.0 22.4 2.0 18.0 19.0 27.0 15.5

Maximum 38.6 56.0 26.4 4.0 45.0 67.0 65.028.1

Descriptive statistics for physical property data from the unpaved road (n = 12)

Number of blows displayed large variability with coefficient of variation (CV) ranging from 32% to 45% despite the low variability of moisture content of soil on the road

Using another penetrometer, the penetration resistance was found to vary between 15.5 and 28.1 kg cm-2 (CV=18%) for a depth of 5- cm

The large variability of penetration resistance showed that apart from moisture content, compaction was likely an important factor for dust emission from unpaved roads

0.0000

0.0004

0.0008

0.0012

0.0016

0.0020

E1.5 E4.5 TE6 TM6 TW6 W4.5 W1.5

Dust

Wei

ght (

g)

(g)

48 km/h

64 km/h

Average and standard deviations of amount of dust particles in grams (Y-axis) on sticky tapes at different heights above ground surface at different vehicle speeds

0.0

0.4

0.8

1.2

1.6

E1.5 E4.5 TE6 TM6 TW6 W4.5 W1.5

Volu

me

sam

pled

(m

3 )

) 48 km/h

64 km/h

Average and standard deviations of volume sampled in m3 (Y-axis) using rotorod and sticky tapes at different heights above ground surface for two different vehicle speeds

0.0000

0.0004

0.0008

0.0012

0.0016

0.0020

E1.5 E4.5 TE6 TM6 TW6 W4.5 W1.5

Conc

entra

tion

n-

48 km/h

64 km/h

Average and standard deviations of concentration of dust particles in g/m3/min (Y-axis) by using rotorods and sticky tapes at different heights above ground surface for two different vehicle speeds

Raw image generated by electron microscope showing the dust particles, smudges and bubbles on the sticky tape at different heights

An image of aeolian particles on sticky tape created by electron microscope

Binary image separating the particles and background using Microsoft paint and ImageJ software

0

1000

2000

3000

4000

5000

6000

E 1.5 E 4.5 TE 6 TM 6 TW 6 W 4.5 W 1.5

Tota

l No.

of P

artic

les

48 km/h64 km/h

0.00

50.00

100.00

150.00

200.00

250.00

300.00

E 1.5 E 4.5 TE 6 TM 6 TW 6 W 4.5 W 1.5

Num

ber o

f Par

ticle

s / A

rea

of S

lide

48 km/h

64 km/h

Analysis of the image by Electron Microscopic from sticky tapes using Jimage software for determining the total number of particles

Number of particles per unit area of the sticky tape at different heights above ground surface and different vehicle speeds

0

500

1000

1500

2000

2500

3000

3500

4000

E1.5 E4.5 TE6 TM6 TW6 W4.5 W1.5

Num

ber o

f par

ticle

s

(g)

48 km/h

64 km/h

0

500

1000

1500

2000

2500

3000

3500

4000

E1.5 E4.5 TE6 TM6 TW6 W4.5 W1.5

Num

ber o

f par

ticles

(g)

48 km/h

64 km/h

Total number of particles for size ranges of PM10 ≤ particles > PM2.5

Total number of particles for size ranges of particles ≤PM2.5

0

1000

2000

3000

4000

5000

6000

7000

8000

Texture and Distribution of Particles

No.

of P

artic

les

48 km/h

64 km/h

48 km/h 4988 0 7425 253 30 0 0 0

64 km/h 6613 1 3168 28 5 0 0 0

ClayVery Fine

Silt SiltVery Fine

Sand Fine SandMedium

SandCoarse Sand

Very Coarse Sand

Particle size distribution of the collected particles at both the vehicular speeds

The particles used for elemental investigation

The elemental composition of dust particles

Silt and clay sized particles were retained on the sticky tapes at all three heights

As vehicle speed increased the concentration of clay sized particles on sticky tapes also increased

The amount of particles between PM10 and PM2.5 did not correlate with vehicle speed but particles ≤PM2.5 size did

The height and width of the dust plume increased with the vehicle speed on the unpaved road

The elemental analysis showed carbon, aluminum and silica as major minerals present at all three heights

Overall this study demonstrated the usefulness of sticky tapes for mapping and characterizing airborne PM

Conclusions

Particulate Matter Emitted by Vehicles on Unpaved Agricultural Roads in Valle de Juarez Chihuahua, Mexico: Testing of

a Low Cost Sensor

Margez et al., 2008 submitted

Rotorod hanging from the tower (upper left), portable weather station (upper right), PM sampler (bottom left), experimental sites Google earth photo (bottom right), and truck running underneath the tower and generating dust plume on the unpaved road located in the Juarez Valley, Mexico

Experimental Site

UACJ RODELA0

10

20

30

40

50

60Sand silt clay

a aa

b

b

a

Size Distribution of Soil Particles in Valle de Juarez, Mexico(Means followed by the same letter were not significantly different,small bars indicate standard error, 0.05)

UJRC

PropertyProperty UJRC RodelaSand (%) 0.04 0.04Silt (%) 0.04 0.20Clay (%) 2.65 0.70MC (% ) 0.20 0.22pH 0.01 0.03EC(dS/m) 0.06 0.63TN (mg/kg) 0.25 0.09P (mg/Kg) 1.08 0.71

Coefficient of Variation (CV) of Soil Properties

The average and standard deviations of concentrations of dust particles in mg m-3 (Y-axis) retained on sticky tapes at different heights above ground surface

The average and standard deviations of concentrations of dust particles in mg m-3 (Y-axis) retained on sticky tapes at different heights above ground surface

The concentration of particles (mg m-3; Y-axis) collected by MET-1 samplers located east (E1.5) and west (W1.5) of the roads at 1.5-m above ground surface

The concentration of particles (mg m-3; Y-axis) collected by MET-1 samplers located east (E1.5) and west (W1.5) of the roads at 1.5-m above ground surface

Elemental composition of particles

Rodela road

UJRC road

Total silt and clay content of the unpaved roads was about 51% at both locations with mostly silt

Increasing vehicle speed increased concentration of the particles retained on sticky tapes especially at Rodela road (11% clay)

The concentration of particles retained on sticky tapes increased from 4.02 mg m-3 at 32 km h-1 to 16.07 mg m-3 at 64 km h-1 vehicle speed at Rodela

Dispersion or height and width of the dust plume increased with the vehicle speed on both unpaved roads

Conclusions

The PM10 sampler located 2-m away from unpaved road in the direction of wind showed spike in concentration immediately after vehicle passed

The concentrations measured by PM10 sampler at E1.5 increased from 0.08 mg m-3 at 32 km h-1 to 0.14 mg m-3 at 64 km h-1 vehicle speed at Rodela

The corresponding concentrations measured by sticky tapes were 0.98 mg m-3 and 0.47 mg m-3

This study demonstrated the usefulness of sticky tapes for characterizing airborne PM

PUBLICATIONS/PRESENTATIONS 2007-2008 Wiiliams D. S., M. K. Shukla and J. Ross. 2008. Particulate

matter emitted by a vehicle running on unpaved road. Atmospheric Environment. 42:3899-3905.

Margez J.P.F., M. K. Shukla, J. Wang, 2008. Particulate matter emitted by vehicle running on unpaved roads in Juarez valley of Mexico. Submitted to TERRA LATINOAMERICANA.

Williams S. D., M.K. Shukla, J. Ross and J. P. Margez. 2007. Mapping of airborne particulate matter from unpaved road under two vehicular speeds. Soil Science Society of America Annual Meeting in New Orleans, La, November 4-8, 2007.

Shukla, M.K., J. Pedro-Margez, B. Hernandez A and J. Wang. 2008. Characterization of particulate matter emitted by vehicles on unpaved agricultural roads in Valle de Juarez Chihuahua Mexico; Binational Border Environmental Education Conference in Ciudad Juarez, June 25-27, 2008.

Shukla, M.K., J. Pedro-Margez, B. Hernandez A. and J. Wang. 2008. Vehicle generated dust transport from unpaved roads in arid climate of Juarez Mexico. Accepted for presentation in the Soil Science Society America Meeting at Houston, Texas, October 5-9, 2008.

B. Hernandez A. 2009. Characterization of particulate matter emitted by vehicles on unpaved roads in Valle De juarez, Chihuahua, Mexico. Under Graduate Thesis Universidad Autonoma De Ciudad, Juarez, Mexico (in progress).

New Mexico State University Agriculture Experiment Station

Southwest Center for Environment Research and Policy (SCERP) for funding the project

Staff of Leyendecker Plant Science Center Staff of University of Juarez Agricultural

Experiment Station Students of New Mexico State University Students of University of Juarez Jim Wang of NMSU Jim Ross, EPPWS and NMSU Electron Microscopy Lab

ACKNOWLEDGEMENT