DOI: 10.1016/j.atmosenv.2016.12.037
Scopus记录号: 2-s2.0-85007105404
论文题名: 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 T ; , Gould T ; , Riley E ; A ; , Austin E ; , Fintzi J ; , Sheppard L ; , Yost M ; , Simpson C
刊名: Atmospheric Environment
ISSN: 0168-2563
EISSN: 1573-515X
出版年: 2017
卷: 152 起始页码: 201
结束页码: 211
语种: 英语
英文关键词: Mobile monitoring
; On-road air pollution
; Principal component analysis
; Traffic related air pollution
; Vehicle exhaust emission factors
Scopus关键词: Air pollution
; Air quality
; Carbon dioxide
; Nitrogen oxides
; Pollution
; Remote sensing
; Roads and streets
; Vehicles
; Ambient air quality
; Light duty vehicles
; Mobile monitoring
; Mobile source emissions
; Principal Components
; Rotated principal components
; Traffic-related air pollution
; Vehicle exhaust emissions
; Principal component analysis
; black carbon
; carbon dioxide
; carbon monoxide
; fuel
; nitrogen oxide
; air quality
; ambient air
; atmospheric pollution
; black carbon
; environmental monitoring
; exhaust emission
; particulate matter
; principal component analysis
; remote sensing
; spatial distribution
; traffic emission
; air quality
; ambient air
; Article
; dynamometer
; prediction
; principal component analysis
; priority journal
; remote sensing
; response time
; Seattle
; United States
; Washington [United States]
Scopus学科分类: Environmental Science: Water Science and Technology
; Earth and Planetary Sciences: Earth-Surface Processes
; Environmental Science: Environmental Chemistry
英文摘要: 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. NOxhad 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 4.3 × 1015particles/kg for heavy duty vehicles, and 3.2, 22.4, 0.016 g/kg, and 0.19 × 1015particles/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. © 2016 Elsevier Ltd Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/82646
Appears in Collections: 气候变化事实与影响
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作者单位: University of Washington, Department of Civil and Environmental Engineering, Box 352700, Seattle, WA, United States; University of Washington, Department of Environmental and Occupational Health Sciences, Box 357234, Seattle, WA, United States; University of Washington, Department of Biostatistics, Box 357232, Seattle, WA, United States
Recommended Citation:
Larson T,, Gould T,, Riley E,et al. 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[J]. Atmospheric Environment,2017-01-01,152