The use of complex emissions models such as Environmental Protection Agency (EPA) MOVES to estimate air pollution impacts transportation models is constrained by significant run times when multiple scenarios and large networks are considered. The ultimate goal of this work is to approximate the emissions estimations generated by the most advanced emissions estimations tool, MOtor Vehicle Emission Simulator (MOVES), with a significantly lower run time and without compromising accuracy. Accuracy is important because a very small error in the emissions estimation can cause large overall errors when large network sizes and vehicular volumes are analyzed. Approximated emissions functions are developed for pollutant emissions for different vehicle types by running several scenarios of a sample network in MOVES, and integrated into a geographic information system (GIS)-based tool, known as Assist-Me, that post-processes transportation model output. This allows for quick estimation of pollutant emissions from multiple scenarios or networks without encountering the computation time challenges of MOVES. Additionally, vehicle idling and its effect on air pollution are included in the estimation and analysis, which are found to be a significant component of total vehicular emissions. In this paper, the development of the pollutant estimation approximation functions is described, along with an example applied to two test networks. The results are generated both directly from MOVES runs and the distribution fit analysis tool developed in this study. Results are compared based on the estimated fit functions and are also compared with the previously used MOBILE estimation model. Finally, a discussion is presented on run time and applicability to more complex networks.
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