Abstract
The primary objective of this paper is to evaluate the impact of traffic congestion on mid-block fine particulate matter (PM2.5) concentrations on an urban arterial. Data of mid-block and background PM2.5 concentrations were collected second by second during peak and non-peak hours on an urban arterial. Then micro traffic conditions were extracted from videos at ten seconds intervals, including traffic volume, traffic flow speed and high-duty vehicle fraction. Results showed that traffic volume had significant influence on mid-block PM2.5 concentrations. Mid-block PM2.5 concentrations were not correlated with traffic level of service. Furthermore, a modified passenger car equivalent was calculated from the aspect of contribution on PM2.5 concentrations using multiple linear regressions model. Then a comprehensive model was established to model the impact of micro traffic conditions on PM2.5 concentrations. Results of the comprehensive model showed that PM2.5 concentrations increased with the increase of total volume or heavy-duty vehicle fraction. Besides, low traffic flow speed resulted in high PM2.5 emission factor, leading to the increase of PM2.5 concentrations. The findings of this study can help better understand traffic congestion and micro traffic conditions on PM2.5 concentrations.
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Project supported by the Fundamental Research Funds for the Central Universities (No. 2018B08014) and by the National Science Foundation of China (No. 51608171).
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Shan, X., Zheng, C., Zhang, X. (2020). Evaluating the Impact of Traffic Congestion on Mid-block Fine Particulate Matter Concentrations on an Urban Arterial. In: Wang, W., Baumann, M., Jiang, X. (eds) Green, Smart and Connected Transportation Systems. Lecture Notes in Electrical Engineering, vol 617. Springer, Singapore. https://doi.org/10.1007/978-981-15-0644-4_106
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DOI: https://doi.org/10.1007/978-981-15-0644-4_106
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