Literature DB >> 28505886

Modeling carbon emissions from urban traffic system using mobile monitoring.

Daniel Jian Sun1, Ying Zhang2, Rui Xue3, Yi Zhang4.   

Abstract

Comprehensive analyses of urban traffic carbon emissions are critical in achieving low-carbon transportation. This paper started from the architecture design of a carbon emission mobile monitoring system using multiple sets of equipment and collected the corresponding data about traffic flow, meteorological conditions, vehicular carbon emissions and driving characteristics on typical roads in Shanghai and Wuxi, Jiangsu province. Based on these data, the emission model MOVES was calibrated and used with various sensitivity and correlation evaluation indices to analyze the traffic carbon emissions at microscopic, mesoscopic and macroscopic levels, respectively. The major factors that influence urban traffic carbon emissions were investigated, so that emission factors of CO, CO2 and HC were calculated by taking representative passenger cars as a case study. As a result, the urban traffic carbon emissions were assessed quantitatively, and the total amounts of CO, CO2 and HC emission from passenger cars in Shanghai were estimated as 76.95kt, 8271.91kt, and 2.13kt, respectively. Arterial roads were found as the primary line source, accounting for 50.49% carbon emissions. In additional to the overall major factors identified, the mobile monitoring system and carbon emission quantification method proposed in this study are of rather guiding significance for the further urban low-carbon transportation development.
Copyright © 2017 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Carbon emissions; Emission factor; MOVES; Mobile monitoring; Urban traffic

Year:  2017        PMID: 28505886     DOI: 10.1016/j.scitotenv.2017.04.186

Source DB:  PubMed          Journal:  Sci Total Environ        ISSN: 0048-9697            Impact factor:   7.963


  5 in total

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4.  Goal-oriented possibilistic fuzzy C-Medoid clustering of human mobility patterns-Illustrative application for the Taxicab trips-based enrichment of public transport services.

Authors:  Miklós Mezei; Imre Felde; György Eigner; Gyula Dörgő; Tamás Ruppert; János Abonyi
Journal:  PLoS One       Date:  2022-10-06       Impact factor: 3.752

5.  Short-Term Trend Forecast of Different Traffic Pollutants in Minnesota Based on Spot Velocity Conversion.

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Journal:  Int J Environ Res Public Health       Date:  2018-09-04       Impact factor: 3.390

  5 in total

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