Application of a multi-lag regression approach to determine on-road PM10 and PM2.5 emission rates

被引：27

作者：

Abu-Allaban, M ^{[1
]}

Gillies, JA ^{[1
]}

Gertler, AW ^{[1
]}

机构：

[1] Desert Res Inst, Reno, NV 89512 USA

来源：

ATMOSPHERIC ENVIRONMENT | 2003年 / 37卷 / 37期

关键词：

mobile source emissions; particulate matter; heavy-duty diesel trucks; light-duty spark ignition vehicles; time-series data analysis;

D O I：

10.1016/j.atmosenv.2003.02.002

中图分类号：

X [环境科学、安全科学];

学科分类号：

08 ; 0830 ;

摘要：

Intensive measurements were performed at roadside locations in Reno, Nevada, and Durham/Research Triangle Park, North Carolina to derive mass emission factors from on-road vehicles. Measurements included continuous particulate matter (PM) concentrations (PM2.5, and PM10), wind speed, wind direction, and vehicle number, class, and speed. A multi-lag linear regression approach was applied to calculate mass emission rates using the continuous data. The output of the multi-lag regression model, the regression coefficients, along with the vehicle specifications and the wind speed/direction at each site were then used to calculate mass emission factors for light-duty spark ignition (LDSI) and heavy-duty diesel (HDD) vehicles. PM 10 emission factors ranged from 530 to 9 100 mg/km, and from 90 to 850 mg/ km for HDD and LDSI vehicles, respectively. PM2.5 emission factors ranged from 120 to 170 mg/km, and from 10 to 90mg/km for HDD and LDSI vehicles, respectively. (C) 2003 Elsevier Ltd. All rights reserved.

引用

页码：5157 / 5164

页数：8

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