文章基本信息

标题：Statistical Model for Estimating Carbon Dioxide Emissions from a Light-Duty Gasoline Vehicle
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作者：Benjamin Afotey ; Melanie Sattler ; Stephen P. Mattingly 等
期刊名称：Journal of Environmental Protection
印刷版ISSN：2152-2197
电子版ISSN：2152-2219
出版年度：2013
卷号：4
期号：8A1
页码：8-15
DOI：10.4236/jep.2013.48A1002
出版社：Scientific Research Publishing
摘要：The objective of this research was development of a statistical model for estimating vehicle tailpipe emissions of carbon dioxide (CO₂). Forty hours of second-by-second emissions data (144,000 data points) were collected using an On-Board emissions measurement System (Horiba OBS-1300) installed in a 2007 Dodge Charger car. Data were collected for two roadway types, arterial and highway, around Arlington, Texas, and two different time periods, off peak and peak (both a.m. and p.m.). Multiple linear regression and SAS software were used to build emission models from the data, using predictor variables of velocity, acceleration and an interaction term. The arterial model explained 61% of the variability in the emissions; the highway model explained 27%. The arterial model in particular represents a reasonably good compromise between accuracy and ease of use. The arterial model could be coupled with velocity and acceleration profiles obtained from a micro-scale traffic simulation model, such as CORSIM, or from field data from an instrumented vehicle, to estimate percent emission reductions associated with local changes in traffic system operation or management.
关键词：Carbon Dioxide; Model; On-Board Emissions Measurement System; Mobile Sources