Ambient air quality measurements from a continuously moving mobile platform: Estimation of area-wide, fuel-based, mobile source emission factors using absolute principal component scores

作者：Larson Timothy; Gould Timothy; Riley Erin A; Austin Elena; Fintzi Jonathan; Sheppard Lianne; Yost Michael; Simpson Christopher

来源：Atmospheric Environment, 2017, 152: 201-211.

DOI：10.1016/j.atmosenv.2016.12.037

• Vehicle exhaust emission factors
• Mobile monitoring
• Principal component analysis
• Traffic related air pollution
• On-road air pollution

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.

• 出版日期2017-3