treasure valley road dust study: final report - ResearchGate

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?? Sieving each sample to obtain a suspendable fraction (< 38 µm geometric diameter), injecting this fraction into an enclosed chamber, and sampling onto Teflon-membrane and quartz-fiber filters through PM 10 and PM 2.5 impactor inlets (Chow et al., 1994a). In the laboratory, the soil samples were air-dried in a low-relative-humidity (approximately 20% to 30%) environment and sieved through a Tyler 400-mesh screen (< 38 ?m geometric diameter) prior to resuspension in the laboratory chamber following the procedures described by Chow et al. (1994a). Filter samples were drawn through PM 10 and PM 2.5 inlets. Most of the mass of geological material is in the coarse particle portion of PM 10 (Houck et al., 1989a), and similar compositions were found for the PM 2.5 and PM 10 geological profiles (Chow and Watson, 1994b). Two additional samples were collected during the winter sampling period on board the TRAKER vehicle. Particles suspended from the road surface behind a moving tire were sampled through a tube into a plenum. A portion of the sample stream was drawn through a filter pack preceded by impactors with aerodynamic size cuts of either 10 ?m or 2.5 ?m. These filters were analyzed directly for mass and chemical speciation. All source profile samples were weighed and chemically characterized at the Desert Research Institutes Environmental Analysis Facility in Reno, Nevada. Samples were analyzed using Ion Chromatography (IC) for major ions, Automated Colorimetry (AC) for ammonium, X- Ray Fluorescence (XRF) for elements, and Thermal Optical Reflectance (TOR) for organic and elemental carbon. Table 7-1 lists all the chemical species analyzed and their corresponding mnemonics. Coarse particle Al, Si, P, Cl, K, and Ca values determined by XRF were originally adjusted for large particle self-absorption using the theoretical formulation developed by Dzubay (1975). This adjustment is a function of particle size distribution and composition. Since the actual particle size distribution and composition is unknown, the uncertainty of these adjustments is up to ± 25%, and is reflected in the reported uncertainty. Particle size effects for Na and Mg are so large and variable that we cannot make accurate corrections for these two elements. Their raw, uncorrected concentrations are included in the data files, but they should not be considered quantitative for fine or coarse samples. A standard quality assurance test for speciated aerosol samples is to compare the reconstructed mass to the measured mass. Reconstructed mass should be less than or equal to the measured gravimetric mass within the limits of analytical uncertainties. Typical ratios of reconstructed mass to measured mass for PM10 range from 75% to 95%. Reconstructed mass is calculated from major species mass concentrations using the following equations to account for the unmeasured components of the aerosol (i.e., oxygen associated with mineral oxides and hydrogen associated with organic carbon compounds): [Soil] = 2.2*[Al] + 2.49*[Si] + 1.63*[Ca] + 2.42*[Fe] + 1.94*[Ti] [Organic Carbonacious Material (OCM)] = 1.4*[OC] 7-2
[Elemental Carbon (EC)] = [EC] [Ammonium Sulfate] = 1.375*[SO 4 2- ] [Ammonium Nitrate] = 1.29*[NO 3 - ] Comparison of the major aerosol components with the total mass indicates that the contribution of geologic material was over-represented in the source profiles. The average and standard deviation of the ratio of reconstructed mass to measured mass are 1.12 +/- 0.08 for PM 10 and 0.91 +/- 0.09 for PM 2.5 . For many of the speciated PM 10 source profiles, the soil component of the aerosol was larger than the measured mass of the PM 10 . These results suggest that the Dzubay correction described above over compensates for the large particle self absorption. When the correction factor is not applied to the elemental concentrations, the ratio or reconstructed mass to measured mass is 0.75 +/- 0.07 for PM 10 and unchanged for PM 2.5 . Because the sum of aerosol component mass is greater than the measured aerosol mass when the Dzubay correction factor is applied, the decision was made to calculate the final source profiles described below without applying the Dzubay correction factor for large particle self absorption. In order to account for the uncertainties of this phenomenon, the precisions of each chemical abundance are the precisions of the Dzubay corrected abundances. The individual source samples are identified in Table 7-2. The locations at which they were collected are described in the earlier Silt Loading section. Table 7-2 also assigns mnemonic codes to identify the profiles as they appear in the CMB source contribution reports. Not all of the species that contribute to PM10 were measured, and the abundances do not sum to 100%. Not all of these profiles were used in the CMB calculations, but all profiles were made available for initial model sensitivity tests and final source apportionment. Profiles used for source apportionment are often composites derived from several individual sample profiles. For this study, the individual geological profiles were composited based on the following characteristics: season collected (i.e. winter or summer), sample type (paved road, unpaved road, sand used for road traction, chips used for chip-sealing, TRAKER samples), and particle size (i.e. PM10, PM2.5, and Coarse). 7.2 Geological Source Profiles Sampling locations for each of the geological source samples are given in Table 7-2. These included paved-road vacuum samples, road sanding material, and unpaved road swept samples. The top 0.5 or 1 cm of surface material was swept from unpaved surfaces, since this represents the reservoir available for suspension by wind or vehicle movement. Paved road dust was collected by vacuuming surface material samples from several different sections of each surface. Chapter 2 discusses sample collection in greater detail. 7-3
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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 ....................
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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
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Table 4-1. (cont) GIS coverages use
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Table 4-1. (cont) GIS coverages use
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Page 72 and 73: Summer - Ada - Rural Summer - Ada -
Page 74 and 75: The average emissions factor is 6.7
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Page 78 and 79: weeks prior to being swept. While t
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Page 82 and 83: Section 1 Section 2 Section 3 Figur
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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
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Page 95 and 96: County Setting Road Class Speed (m/
Page 97 and 98: January, February, and March were u
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Page 101 and 102: Table 5-9 Precipitation and snow co
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Page 122 and 123: Table 6-1 (continued). Table of geo
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Page 127 and 128: 7.3 Source Profile Summary This a p
Page 129 and 130: Table 7-4. Source profiles of Summe
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Page 146 and 147: Figure A-1. Map of Sample Collectio
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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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