Estimation of emissions at signalized intersections using an improved MOVES model with GPS data

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dc.creatorLin, Ciyun
dc.creatorZhou, Xiangyu
dc.creatorWu, Dayong (TTU)
dc.creatorGong, Bowen
dc.date.accessioned2023-03-31T14:46:52Z
dc.date.available2023-03-31T14:46:52Z
dc.date.issued2019
dc.description© 2019 by the authors. Licensee MDPI, Basel, Switzerland. cc-by
dc.description.abstractEmissions from the transport sector are responsible for a large proportion of urban air pollution. Scientific and efficient measurements on traffic pollution emissions have already been a vital concern of decision makers in environmental protection. In China or other counties, many high-technology companies, such as Baidu, DiDi, have a large number of real-time GPS traffic data, but such data have not been fully exploited, especially in purpose of estimation of vehicle fuel consumption and emissions. In this paper, the traditional MOVES (Motor Vehicle Emission Simulator) model has been improved by adding the real-time GPS data and tested in representative signalized intersection in Changchun, China. The results showed that adding the GPS data sets in the MOVES model can effectively improve the estimation accuracy of traffic emissions and provide a strong scientific basis for environmental decision-making, planning and management.
dc.identifier.citationLin, C., Zhou, X., Wu, D., & Gong, B.. 2019. Estimation of emissions at signalized intersections using an improved MOVES model with GPS data. International Journal of Environmental Research and Public Health, 16(19). https://doi.org/10.3390/ijerph16193647
dc.identifier.urihttps://doi.org/10.3390/ijerph16193647
dc.identifier.urihttps://hdl.handle.net/2346/92222
dc.language.isoeng
dc.subjectEmissions
dc.subjectGPS data
dc.subjectMOVES
dc.subjectTraffic pollution
dc.titleEstimation of emissions at signalized intersections using an improved MOVES model with GPS data
dc.typeArticle

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