Statistical Model for Estimating Carbon Dioxide Emissions from a Light-Duty Gasoline Vehicle

作     者：Benjamin Afotey Melanie Sattler Stephen P. Mattingly Victoria C. P. Chen 

作者机构：Department of Chemical Engineering Kwame Nkrumah University of Science and Technology Kumasi Ghana Department of Civil Engineering The University of Texas at Arlington Arlington USA Department of Industrial and Manufacturing Systems Engineering The University of Texas at Arlington Arlington USA 

出 版 物：《Journal of Environmental Protection》 (环境保护（英文）)

年 卷 期：2013年第4卷第8期

页      面：8-15页

学科分类：1002[医学-临床医学] 100214[医学-肿瘤学] 10[医学] 

主　　题：Carbon Dioxide Model On-Board Emissions Measurement System Mobile Sources 

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.