期刊
ATMOSPHERIC ENVIRONMENT
卷 152, 期 -, 页码 201-211出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.atmosenv.2016.12.037
关键词
Vehicle exhaust emission factors; Mobile monitoring; Principal component analysis; Traffic related air pollution; On-road air pollution
资金
- USEPA grant [RD 83479601-0]
- National Institute of Environmental Health Sciences [P30ES007033, T32 ES015459]
- Kresge Foundation [243365]
We have applied the absolute principal component scores (APCS) receptor model to on-road, background-adjusted measurements of NOx, CO, CO2, black carbon (BC), and particle number (PN) obtained from a continuously moving platform deployed over nine afternoon sampling periods in Seattle, WA. Two Varimax-rotated principal component features described 75% of the overall variance of the observations. A heavy-duty vehicle feature was correlated with black carbon and particle number, whereas a light-duty feature was correlated with CO and CO2. NOx had moderate correlation with both features. The bootstrapped APCS model predictions were used to estimate area-wide, average fuel-based emission factors and their respective 95% confidence limits. The average emission factors for NOx, CO, BC and PN (14.8, 18.9, 0.40 g/kg, and 43 x 10(15) particles/kg for heavy duty vehicles, and 3.2, 22.4, 0.016 g/kg, and 0.19 x 10(15) particles/kg for light-duty vehicles, respectively) are consistent with previous estimates based on remote sensing, vehicle chase studies, and recent dynamometer tests. Information on the spatial distribution of the concentrations contributed by these two vehicle categories relative to background during the sampling period was also obtained. (C) 2016 Elsevier Ltd. All rights reserved.
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