Study on the interactive mechanism of urban traffic congestion and air pollution: A big data analysis based on DiDi Chuxing
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X51; C912.6

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    Abstract:

    Urban traffic congestion and air pollution bring severe challenges to the sustainable development of Chinese cities. Based on the merge of DiDi’s customer ordering data,air quality and climate data in Chengdu,we use regression discontinuity and mediation variable analysis to investigate the interactive mechanism of unban traffic congestion and air pollution. Our results show that the increase of urban traffic flow leads to more air pollution,and mobility efficiency plays a mediation role in such a relation,i. e. ,the reduction of mobility efficiency or traffic congestion will increase emission and air pollution. On the other hand,air pollution has a positive impact on mobility efficiency which reduces traffic congestion through the mediation effect of traffic flow and demand reduction under air pollution. Based on the new perspective of public mobility behavior,this study sheds light on the relationship between traffic congestion and air pollution,and provides theoretical and empirical evidence to deal with the problems jointly.

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  • Online: October 25,2021
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