Sensitivity analysis of area-wide, mobile source emission factors to high-emitter vehicles in Los Angeles. (15th February 2020)

• Record Type: Journal Article
• Authors: Kelp, Makoto; Gould, Timothy; Austin, Elena; Marshall, Julian D.; Yost, Michael; Simpson, Christopher; Larson, Timothy
• Is Part Of: Atmospheric environment. Volume 223(2020)
• Publication Date: 2020-02-15
• Subjects: Vehicle exhaust emission factors -- High-emitting vehicles -- Principal component analysis -- Traffic related air pollution -- Sensitivity analysis; Air -- Pollution -- Periodicals; Air -- Pollution -- Meteorological aspects -- Periodicals; 551.51
• DOI: 10.1016/j.atmosenv.2019.117212
• Languages: English
• ISSNs: 1352-2310

Abstract

Abstract: 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 × 10^15 particles/kg for heavy-duty vehicles, and 2.0, 111, 0.023 g/kg, and 0.09 × 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 × 10^15 particles/kg for heavy-duty vehicles, and 1.5, 40.9, 0.004 g/kg, and 0.08 × 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. Highlights: Mobile monitoring sampled multi-pollutant data over urban area in-flow with traffic. Principal component analysis applied after a priori separation of high-emitters. Fuel-based emission factors were derived for regular heavy- and light-duty vehicles. We report the sensitivity of emission factors to high-emitter biasing observations.