treasure valley road dust study: final report - ResearchGate

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14 m 0 s 15 s 30 s 60 s 120 s 240 s 500 s 12 m 10 m 8 m 6 m 4 m 2 m 0 m 14 m a. 0 s 15 s 30 s 60 s 120 s 240 s 500 s 12 m 10 m 8 m 6 m 4 m 2 m 0 m b. Figure 6-3. Time series of concentration with height for a. neutral conditions and b. stable conditions. Fraction PM10 remaining in suspension 1.2 1 0.8 0.6 0.4 0.2 Neutral conditions 0 0 100 200 300 400 500 600 Time (seconds) Stable conditions Figure 6-4. Fraction of PM 10 remaining in suspension vs. time after emission. The size distribution at the point of emission is given in section 4.1. 6-6
6.3 Discussion The depletion of PM 10 in the proximity of the emissions source has important implications for the use of road dust emissions in air quality models. PM 10 dust emissions used to estimate emissions factors are measured within 5 to 50 m of a road. Emissions calculated based on those factors do not account for the depletion of PM 10 as the plume travels further downwind. Many of the frequently used urban and regional scale air quality models assume that ground level emissions are initially uniformly mixed over a certain height, typically the distance from the ground to the first node in the numerical grid (20 – 40 m). This assumption does not adequately allow for the removal by deposition of the larger particles in the PM 10 size range. Consequently, air quality models that use road dust emissions as input without accommodation for near-source removal of particles will likely overestimate the ambient concentrations of road dust PM 10 . Table 6-4 shows how changes in the parameters used in the model can affect the fraction of PM 10 that remains suspended after 60 seconds. The model is sensitiveto some of the parameter values and fairly insensitive to others. For example, varying the roughness length under neutral conditions over several orders of magnitude has only a modest effect on the fraction of particles remaining in suspension. On the other hand, the value used for deposition rate due to impaction can have substantial consequences. If impaction is not accounted for at all (V i = 0) and particles were only allowed to deposit by gravitational settling, then the fraction that remains in suspension is 95%, considerably higher than the 65% achieved with the model assumptions here. Another important parameter is the assumption for the initial distribution of particles in the vertical direction. A factor of two increase or decrease in the initial pulse height can vary the fraction remaining between 45% and 80%. Table 6-4. The effects of perturbation of model inputs on fraction of particles remaining in suspension at t = 60 seconds. Parameter Stability Baseline value Baseline fraction remaining Perturbed value Fraction remaining z 0, u * Neutral 0.01 m, 0.058 m/s 65% 1 m, 0.17 m/s 60% z 0, u * Neutral 0.01 m, 0.058 m/s 65% 0.1 m, 0.087 m/s 62% z 0, u * Neutral 0.01 m, 0.058 m/s 65% 0.001 m, 0.043 m/s 67% V i Neutral 0.08 m/s 65% 0.16 m/s 63% V i Neutral 0.08 m/s 65% 0.04 m/s 68% V i Neutral 0.08 m/s 65% 0 m/s 95% L Stable 10 m 64% 1 m 70% L Stable 10 m 64% 1000 m 64% Initial distribution Neutral 0-2 m 65% 0-4 m 80% Initial distribution Neutral 0-2 m 65% 0-1 m 46% Z i Neutral 200 m 65% 400 m 65% Z i Neutral 200 m 65% 100 m 65% The model presented here is useful for demonstration of the behavior of road dust emissions near the point of origin. However, several simplifying assumptions have been made in the formulation of this model and many of the parameters only represent approximations. In future work, and in keeping with the suggestions of both Watson and Chow (2000) and Countess (2001), it is important to better estimate the conditions under which emissions from roads are transported. Most notably, better field measurements of the impaction term V i and the initial plume distribution should be obtained under neutral and stable atmospheric conditions. 6-7
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TREASURE VALLEY ROAD DUST STUDY: FI
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EXECUTIVE SUMMARY The Idaho Departm
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TABLE OF CONTENTS 1. INTRODUCTION..
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6.3 DISCUSSION ....................
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are strongly correlated and that on
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Figure 4-17. Map of street sweeper
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xvi
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Table 5-3. Speeds and VKT by county
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Table A-28. Laboratory Silt Analysi
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?? To assess the impact of winterti
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2. SILT MEASUREMENTS For this study
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vehicle tires. The lengths of the s
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Figure 2-1. Map of Sample Collectio
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Table 2-5 Silt Content and Silt Loa
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collectors. In contrast, summer sil
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3.2 TRAKER Measurements For the TVR
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introduced by the carbon vanes insi
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3.2.4.1 Data Acquisition The TRAKER
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Figure 3-6 shows the TRAKER coeffic
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250 200 PM2.5 signal (mg/m 3 ) 150
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Line losses associated with the Dus
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1.2 1 Left Diluted Right Diluted Pr
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Table 3-2. Regression exponents for
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3.4.2 Flux Calculation from Meteoro
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12.2 m 0.16 9.0 m 0.05 5.7 m 0.22 4
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400 Ford Ranger on NS Road by DW1 4
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ceiling can be further stretched to
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100 sL = 2.5717(T*) 0.4741 R 2 = 0.
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4.1.1 Converting TRAKER Data Into E
Page 64 and 65: Table 4-1. (cont) GIS coverages use
Page 66 and 67: Table 4-1. (cont) GIS coverages use
Page 68 and 69: a. b. Figure 4-1. Map of TRAKER Str
Page 70 and 71: egressions, R 2 and P-values are al
Page 72 and 73: Summer - Ada - Rural Summer - Ada -
Page 74 and 75: The average emissions factor is 6.7
Page 76 and 77: Figure 4-5. TRAKER Loop 4.3.1 Tempo
Page 78 and 79: weeks prior to being swept. While t
Page 80 and 81: 4.3.2 Meteorological Effects on Unp
Page 82 and 83: Section 1 Section 2 Section 3 Figur
Page 84 and 85: Figure 4-13. Johnston HSD mechanica
Page 86 and 87: Approximately 8 hours after the ini
Page 88 and 89: One-second emissions potentials (i.
Page 91 and 92: 5. EMISSIONS INVENTORIES FOR THE TR
Page 93 and 94: where E i.10 is the emissions in gr
Page 95 and 96: County Setting Road Class Speed (m/
Page 97 and 98: January, February, and March were u
Page 99 and 100: 5.1.3.2a January 1 - 9, 2000, 2010,
Page 101 and 102: Table 5-9 Precipitation and snow co
Page 103 and 104: complete link-level emissions inven
Page 105 and 106: Table 5-14. Distributions of averag
Page 107: Taken on an average annual basis, T
Page 110 and 111: Z n , K zn , ? c/ ? z n Z 3 , K z3
Page 112 and 113: Table 6-1. Aerodynamic particle siz
Page 116 and 117: Furthermore, the vertical profile o
Page 118 and 119: ?? Sieving each sample to obtain a
Page 120 and 121: 7-4 Table 7-1. Source Profile Key M
Page 122 and 123: Table 6-1 (continued). Table of geo
Page 124 and 125: Treasure Valley Road Dust Winter Pa
Page 127 and 128: 7.3 Source Profile Summary This a p
Page 129 and 130: Table 7-4. Source profiles of Summe
Page 131: Table 7-6. Source profiles of Winte
Page 134 and 135: Bliss experiments were significant
Page 136 and 137: section was swept with a vacuum swe
Page 138 and 139: 8.3 Differences Between Emissions M
Page 140 and 141: determine at this time what fractio
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Page 144 and 145: McMahon T.A., and P.J. Denison (197
Page 146 and 147: Figure A-1. Map of Sample Collectio
Page 148 and 149: Table A-2. Summer 2001 Silt Samplin
Page 150 and 151: Table A-3. Laboratory Silt Analysis
Page 152 and 153: Figure A-3. Map of Silt Loading Loc
Page 158 and 159: Figure A-5. Map of Silt Loading Loc
Page 160 and 161: Table A-10. Laboratory Silt Analysi
Page 162 and 163: Table A-11. Laboratory Silt Analysi
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Figure A-7. Map of Silt Loading Loc
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Figure A-9. Map of Silt Loading Loc
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Figure A-11. Sampling locations of
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APPENDIX B. BOISE PRECIPITATION AND
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Pecentile among days with precipita
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A.1 Wind speed The cumulative frequ
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APPENDIX C : EMISSIONS INVENTORIES:
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C.1.1.2a Field List for worksheets
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values specified by AP-42 and do no
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