期刊
ATMOSPHERIC ENVIRONMENT
卷 223, 期 -, 页码 -出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.atmosenv.2019.117212
关键词
Vehicle exhaust emission factors; High-emitting vehicles; Principal component analysis; Traffic related air pollution; Sensitivity analysis
资金
- U.S. Environmental Protection Agency [RD 83479601-0]
- Center for Air, Climate, and Energy Solutions (CACES) - U.S. Environmental Protection Agency [R835873]
The absolute principal component scores (APCS) model was applied to on-road, background-adjusted measurements of NOx, CO, CO2, black carbon (BC), and particle number (PN) obtained from a continuously moving platform deployed during 16 afternoon sampling periods in Los Angeles, CA. High-emitter biasing observations were separated from the vehicle fleet population based on a sensitivity analysis of different a priori screening values of the ratio of CO to CO2. A BC/PN-rich feature consistent with heavy-duty vehicle exhaust, and a separate CO/CO2-rich feature consistent with light-duty vehicle exhaust, described 66% of the variance of the observations. We used bootstrapped APCS model predictions to estimate area-wide, average fuel-based emission factors and their respective 95% confidence limits. If no screening was used, we obtained incongruous average emission factors relative to recent field studies for NOx, CO, BC and PN (5.1, 2.0, 0.13 g/kg, and 1.0 x 10<^>15 particles/kg for heavy-duty vehicles, and 2.0, 111, 0.023 g/kg, and 0.09 x 10<^>15 particles/kg for light-duty vehicles, respectively). However, if reasonable a priori screening values were applied, which differentiate measurements reflecting high-emitter outliers, average emission factors for NOx, CO, BC and PN (12.8, 4.0, 0.37 g/kg, and 2.6 x 10<^>15 particles/kg for heavy-duty vehicles, and 1.5, 40.9, 0.004 g/kg, and 0.08 x 10<^>15 particles/kg for light-duty vehicles, respectively) were consistent with previous estimates based on remote sensing, vehicle chase studies, and recent dynamometer tests.
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