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One-second emissions potentials (i.e. kT 1/3 /s) for each road section and heading were averaged. The number of 1-second measurements constituting the averages ranged from 14 (Ponderay northbound after sweeping) to 300 (Quarter Horse westbound after sweeping). Figure 4-18 shows the average emissions potential for each road segment and heading before and after sweeping. The results from these tests are counterintuitive. If the street sweeper is removing suspendable material from the roadway, the emissions potential should decrease after sweeping. Instead, the emissions potential is observed to increase by up to 40% after sweeping. The average emissions potential increase measured on all five roads is 16%. 1.8 1.6 Before Sweeping After Sweeping 1.4 Emissions Potential (g/vkt)/(m/s) 1.2 1 0.8 0.6 0.4 0.2 0 Clark East Clark West Ponderay North Ponderay South Ponderosa East Ponderosa West Quarter Horse East Quarter Horse West Wilcomb North Wilcomb South Figure 4-18. Comparison of emissions potential from 5 streets in Ada County before and after street sweeping. The reason for the increase in emissions potential after sweeping is unclear. It is possible that material displaced from the curb unto the street as the sweeper passes over the road. Alternatively, particles trapped in the cracks and pits of the road may be redistributedacross the road surface by the sweeper, making those particle available for suspension by passing vehicles. In this experiment, the application of the sand has been shown to increase PM 10 emissions, though only for a short time after application. Sand applied to the road drifted to the shoulders within a few hours of application. On the short time-scale of these experiments, it was not possible to investigate whether or not sand blown to the side of the road can serve as a longterm reservoir for subsequent PM 10 emissions. At present, it is uncertain how sweeping affects the urban scale emissions inventory. The sweepers tested effectively capture large material (e.g. sand, trash, and leaf debris) but were not effective in lowering PM 10 emissions in the short-term. We note however that the large material on roadways may be precursors to PM 10 road dust emissions since vehicle tires can disaggregate 4-28
the large material into finer particles. Thus, it is possible that the removal of comparatively large grains of geologic material reduces the total amount of PM 10 that would otherwise be available for emission in the long-term. This mechanism, not examined by the experiments presented here, should be studied further since it may have important implications for the effectiveness of street sweeping programs in PM 10 emissions reduction. 4-29
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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
Page 38 and 39: introduced by the carbon vanes insi
Page 40 and 41: 3.2.4.1 Data Acquisition The TRAKER
Page 42 and 43: Figure 3-6 shows the TRAKER coeffic
Page 44 and 45: 250 200 PM2.5 signal (mg/m 3 ) 150
Page 46 and 47: Line losses associated with the Dus
Page 48 and 49: 1.2 1 Left Diluted Right Diluted Pr
Page 50 and 51: Table 3-2. Regression exponents for
Page 52 and 53: 3.4.2 Flux Calculation from Meteoro
Page 54 and 55: 12.2 m 0.16 9.0 m 0.05 5.7 m 0.22 4
Page 56 and 57: 400 Ford Ranger on NS Road by DW1 4
Page 58 and 59: ceiling can be further stretched to
Page 60 and 61: 100 sL = 2.5717(T*) 0.4741 R 2 = 0.
Page 62 and 63: 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 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 114 and 115: 14 m 0 s 15 s 30 s 60 s 120 s 240 s
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
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8.3 Differences Between Emissions M
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determine at this time what fractio
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sweepers to reduce PM 10 emissions
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McMahon T.A., and P.J. Denison (197
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Figure A-1. Map of Sample Collectio
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Table A-2. Summer 2001 Silt Samplin
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Table A-3. Laboratory Silt Analysis
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Figure A-3. 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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