1. Mapping of Airborne Particulate Matter under Two Land Uses: Agriculture and Unpaved Road

2. Principal Investigator: Manoj K. Shukla, Ph.D. Assistant Professor of Environmental Soil Physics Department of Plant and Environmental Sciences New Mexico State University, MSC 3Q, P.O. Box 30003 Las Cruces, NM-88003, USA Co- Investigators: Juan Pedro Flores Margez, Ph.D. Assistant Professor Universidad Autónoma de Ciudad Juárez, México and D. R. Miller; University of Connecticut, USA R. Arimoto; Carlsbad Environ. Monitoring & Research Center, NMSU, Carlsbath

3. Particulate matter (PM) of aerodynamic diameter ≤ 10 microns (PM 10 ) and 2.5 microns (PM 2.5 ) 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.)

4. 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 PM 10 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

5.  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

6. 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

7. 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 32 o 11’35.84” N and 106 o 44’08.75”W

8. Field for Ag Dust Experiment Unpaved road for vehicle generated dust experiment Rio Grande River

9. Plot Layout for Agriculture Dust Experiment Plots Dust Track Samplers 0, 0

10. 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

11. Dust Track Sonic Anemometer Disking Chiseling

12. Plot Moisture Content SandSiltClay Bulk Density Penetration cm 3 cm -3 %%g cm -3 Kg cm -2 10.096±0.0129.6±2.345.0±2.025.4±1.21.32±0.1515.05±2.87 20.101±0.01126.0±2.547.4±2.126.6±0.51.20±0.1610.90±1.32 30.105±0.00423.7±2.049.4±2.126.8±0.41.27±0.0910.69±1.64 40.096±0.01124.1±3.048.9±2.627.0±0.51.34±0.1215.33±2.21 50.100±0.01224.8±1.647.8±1.527.4±0.51.32±0.0413.92±1.53 60.094±0.01628.4±1.546.0±1.425.6±1.91.33±0.0611.46±0.88 Antecedent Soil Moisture Content and Soil Physical Properties

13. Moisture contentBulk density Clay contentPenetration resistance

14. Plot Moisture Content SandSiltClay Bulk Density Penetration 1 0.100.080.040.050.120.19 2 0.110.100.040.020.130.12 3 0.040.080.040.010.070.15 4 0.110.120.050.020.090.14 5 0.120.060.030.020.030.11 6 0.170.050.030.070.050.08 Coefficient of Variation (CV) of Soil Physical Properties CV 0.35, high; 0.15 < CV < 0.35, moderate

15. Wind Velocity in x, y, z direction Sonic Anemometer

16. PM concentration by dust track sampler for plots during Disking

17.  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

18. PM concentration by dust track sampler for plots during Chiseling

19.  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

20. Surface map for maximum dust concentration observed during disking Surface map for maximum dust concentration observed during chiseling

21. DiskingChiseling Plot Peak Concentration Min Concentration Peak Concentration Min Concentration 10.180.470.500.77 20.170.490.710.43 30.230.500.490.40 40.310.750.540.53 50.230.630.690.16 61.030.510.700.47 Coefficient of Variation (CV) of Dust Concentrations

22. Relationship between dust concentration during chiseling and soil parameters using stepwise regression PeakC = 0.955 – 7.322 * AMC R 2 = 0.23; P = 0.003 PeakC = 0.746 – 7.333 * AMC + 0.016*PR R 2 = 0.28; P = 0.004 MinC = 0.029 – 0.001 * Clay R 2 = 0.11; P = 0.04 MinC = 0.019 – 0.001 * Clay + 0.023*PR R 2 = 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

23.  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 (R 2 =0.28; P<0.004) Conclusions

24. 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

25. (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

26. 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

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

28. Parameter Sand % Silt % Clay % Moisture content % Number of blows at 5 cm Number of blows at 10 cm Number of blows at 15 cm Compaction at 5 cm (kg cm -2 ) Mean27.847.624.63.026.635.340.3 20.5 SE3.42.80.70.04.16.14.8 1.1 Median28.646.025.44.023.032.038.0 19.3 Mode-46.025.44.018.0-- 17.6 Stdev7.76.31.60.0110.716.012.8 3.8 Variance59.240.32.70.0115.0257.2163.9 14.4 Kurtosis-0.30.2-1.70.08-0.22.41.9 0.3 Skewness0.30.0-0.5-1.181.11.41.3 1.0 Minimum18.639.022.42.018.019.027.0 15.5 Maximum38.656.026.44.045.067.065.0 28.1 Descriptive statistics for physical property data from the unpaved road (n = 12)

29.  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

30. 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

31. Average and standard deviations of volume sampled in m 3 (Y- axis) using rotorod and sticky tapes at different heights above ground surface for two different vehicle speeds

32. Average and standard deviations of concentration of dust particles in g/m 3 /min (Y-axis) by using rotorods and sticky tapes at different heights above ground surface for two different vehicle speeds

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

34. 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

35. 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

36. Total number of particles for size ranges of PM 10 ≤ particles > PM 2.5 Total number of particles for size ranges of particles ≤PM 2.5

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

38. The particles used for elemental investigation

39. The elemental composition of dust particles

40.  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 PM 10 and PM 2.5 did not correlate with vehicle speed but particles ≤PM 2.5 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

41. 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

42. 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

43. UJRC

44. Property Rodela Sand (%)0.04 Silt (%)0.040.20 Clay (%)2.650.70 MC (% )0.200.22 pH0.010.03 EC(dS/m)0.060.63 TN (mg/kg)0.250.09 P (mg/Kg)1.080.71 Coefficient of Variation (CV) of Soil Properties

45. 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

46. 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

47. Elemental composition of particles Rodela road UJRC road

48. 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

49. 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

50. 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).

51.  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