treasure valley road dust study: final report - ResearchGate

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4.1.1 Converting TRAKER Data Into Emissions Potentials All invalid TRAKER data points (according to the criteria outlined in Section 3) were removed from the dataset. The parameter used in considering valid TRAKER data is the emissions potential of the road. Recall from Section 3 that: T ? T T ? T B (4-1) T ? T * s 3 (4-2) EF ? bs (4-3) 1/ 3 EF ? kT (4-4) where T T is the PM 10 concentration at the vehicle tire, T B is the background aerosol concentration measured at the front bumper, T is the differential TRAKER signal, EF is the emissions factor, s is the vehicle speed, and T * , b, and k are all constants for a given road segment. It follows that 3 ?( k? T / s s? 1/ EF ? )? (4-5) 1/ 3 b ? ( k? T / s) (4-6) where the constant, b, is the road dust emissions potential and is related only to the “dirtiness” of the road. That is, for a given road, b is constant regardless of the speed that the TRAKER traverses the road and has units of [g/vkt/mps] where vkt is the vehicle kilometers traveled and mps is the speed of travel in meters per second. Actual emissions factors for the road (units of g/vkt) are obtained by multiplying b by the speed of the vehicle that is traversing the road. The emissions potential was calculated for each valid TRAKER data point. Note that in some cases, the differential signal T can be negative. This occurs if the background PM concentration measured on the bumper of the vehicle is higher than the influence concentration behind the tire due to instrument noise or a time delay between when a “dirty” air pocket passes by the bumper and then the tires. It is important to retain these negative values in the database so as not to introduce a bias when calculating averages. 4.1.2 Associating TRAKER Data With Roads and Settings All data were imported into a GIS-format database. Using the GIS coverages shown in Table 4-1 and a software utility for joining spatial data, each TRAKER measurement was associated with a road segment or type, county, and setting (urban/rural). For non-residential roads, the TRAKER measurement was associated with a link in the Traffic Demand Model (TDM) that was provided by COMPASS. Each link in the TDM is attributed with a road class (e.g. principal arterial, collector, etc). Residential roads are not reflected in the TDM as physical entities; instead, they are grouped and represented as “Centroid Connectors”. For residential roads, the TRAKER measurement was flagged as “residential” based on spatial joins with separate Ada County and Canyon County street coverages, shown in Table 4-1 as “adastr” and “canstr”, respectively. When attributing a road dust emissions potential to an individual road segment, 1-second TRAKER data for that road segment (link) were averaged. If there were fewer than 10 valid data points for that road segment, then the road segment was not considered to have a valid measurement. 4-2
Table 4-1. GIS coverages used in TRAKER data analysis Coverage/Fields used Coverage: TRAKER Measurements Filename: ALL_BRD_TRAKER_02.mdb Source: DRI Coverage/Field Description Coverage Description: Point coverages of all measurements conducted with TRAKER. This coverage is used to assign attributes to all TRAKER measurements. Attributes include, which road segment the measurement was conducted on, which County, whether or not the TRAKER measurement corresponds to an urban or a rural area. Data Fields Used Datetime Lat, Lon, Elev Field Description The date and time of each measurement in MM/DD/YY HH:MM:SS format. The dates are important for resolving temporal trends in road dust emissions and are also used as a key between all measurements (GPS, DustTraks, PSAs, Database) The latitude, longitude and elevation of each measurement as calculated from differentially-corrected GPS signals. 4-3
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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 ....................
Page 12 and 13: are strongly correlated and that on
Page 14 and 15: Figure 4-17. Map of street sweeper
Page 16 and 17: xvi
Page 18 and 19: Table 5-3. Speeds and VKT by county
Page 20 and 21: Table A-28. Laboratory Silt Analysi
Page 22 and 23: ?? To assess the impact of winterti
Page 25 and 26: 2. SILT MEASUREMENTS For this study
Page 27 and 28: vehicle tires. The lengths of the s
Page 29 and 30: Figure 2-1. Map of Sample Collectio
Page 31 and 32: Table 2-5 Silt Content and Silt Loa
Page 33: collectors. In contrast, summer sil
Page 36 and 37: 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
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Page 60 and 61: 100 sL = 2.5717(T*) 0.4741 R 2 = 0.
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
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Page 107: Taken on an average annual basis, T
Page 110 and 111: Z n , K zn , ? c/ ? z n Z 3 , K z3
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Table 6-1. Aerodynamic particle siz
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14 m 0 s 15 s 30 s 60 s 120 s 240 s
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Furthermore, the vertical profile o
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?? Sieving each sample to obtain a
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7-4 Table 7-1. Source Profile Key M
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Table 6-1 (continued). Table of geo
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Treasure Valley Road Dust Winter Pa
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7.3 Source Profile Summary This a p
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Table 7-4. Source profiles of Summe
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Table 7-6. Source profiles of Winte
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Bliss experiments were significant
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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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Table A-10. Laboratory Silt Analysi
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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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