Abstract
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.
Highlights
According to the US Environmental Protection Agency (EPA), in 2010 mobile sources in the U.S contributed 58% of carbon monoxide (CO), 56% of nitrogen oxide (NOx), and 33% of volatile organic compound (VOC) [1]
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
The top 3 arterial models considered are shown in Equations (2), (3), and (4) below
Summary
According to the US Environmental Protection Agency (EPA), in 2010 mobile sources in the U.S contributed 58% of carbon monoxide (CO), 56% of nitrogen oxide (NOx), and 33% of volatile organic compound (VOC) [1]. At the state and regional levels, transportation and air quality engineers are developing various transportation models to help estimate vehicle exhaust emissions. Emissions estimates are important for ascertaining the effects of sources, as well as developing emissions control strategies [2,3,4]. For example, be used to estimate the emission benefits derived from intelligent transportation systems (ITS) or coordinating traffic signals [5]. Due to growing concerns about climate change, models for estimating carbon dioxide emissions from mobile sources are of increasing importance. A number of vehicle emission models have been developed in the past decade(s), including the following: MOVES: The US EPA’s Motor Vehicle Emission
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