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来自连续移动移动平台的环境空气质量测量:使用绝对主成分得分估算区域范围内基于燃料的移动源排放因子。

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.

作者信息

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

机构信息

University of Washington, Department of Civil and Environmental Engineering, Box 352700 Seattle, WA 98195-2700, USA.

University of Washington, Department of Environmental and Occupational Health Sciences, Box 357234, Seattle, WA 98195-7234, USA.

出版信息

Atmos Environ (1994). 2017 Mar;152:201-211. doi: 10.1016/j.atmosenv.2016.12.037. Epub 2016 Dec 21.

Abstract

We have applied the absolute principal component scores (APCS) receptor model to on-road, background-adjusted measurements of NOx, CO, CO, 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 CO. NO 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 4.3×10 particles/kg for heavy duty vehicles, and 3.2, 22.4, 0.016 g/kg, and 0.19×10 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.

摘要

我们已将绝对主成分得分(APCS)受体模型应用于在华盛顿州西雅图市九个下午采样期内通过连续移动平台获得的道路上经背景调整的氮氧化物(NOx)、一氧化碳(CO)、二氧化碳(这里原文重复了CO,推测有误,按二氧化碳CO₂翻译)、黑碳(BC)和颗粒物数量(PN)测量值。两个经过方差最大化旋转的主成分特征描述了观测值总方差的75%。一个重型车辆特征与黑碳和颗粒物数量相关,而一个轻型车辆特征与一氧化碳和二氧化碳相关。一氧化氮(NO)与这两个特征都有中等程度的相关性。通过自抽样的APCS模型预测用于估计区域范围内基于燃料的平均排放因子及其各自的95%置信区间。氮氧化物、一氧化碳、黑碳和颗粒物数量的平均排放因子(重型车辆分别为14.8、18.9、0.40克/千克和4.3×10⁶个颗粒/千克,轻型车辆分别为3.2、22.4、0.016克/千克和0.19×10⁶个颗粒/千克)与先前基于遥感、车辆追踪研究和近期测功机测试的估计结果一致。还获得了关于这两类车辆在采样期间相对于背景的浓度空间分布信息。

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本文引用的文献

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3
Effects of Particle Filters and Selective Catalytic Reduction on Heavy-Duty Diesel Drayage Truck Emissions at the Port of Oakland.
Environ Sci Technol. 2015 Jul 21;49(14):8864-71. doi: 10.1021/acs.est.5b01117. Epub 2015 Jun 26.
5
Transferability and generalizability of regression models of ultrafine particles in urban neighborhoods in the Boston area.
Environ Sci Technol. 2015 May 19;49(10):6051-60. doi: 10.1021/es5061676. Epub 2015 Apr 30.
6
On-road heavy-duty vehicle emissions monitoring system.
Environ Sci Technol. 2015 Feb 3;49(3):1639-45. doi: 10.1021/es505534e. Epub 2015 Jan 21.
7
8
Multi-pollutant mobile platform measurements of air pollutants adjacent to a major roadway.
Atmos Environ (1994). 2014 Dec 1;98:492-499. doi: 10.1016/j.atmosenv.2014.09.018.
10
Ultrafine particle size distributions near freeways: Effects of differing wind directions on exposure.
Atmos Environ (1994). 2012 Dec;63:250-260. doi: 10.1016/j.atmosenv.2012.09.045.

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