Impacts of shared mobility on energy consumption and emissions in China

Biying Yu, Xiaoyi Li, Meimei Xue

    Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

    3 Citations (Scopus)

    Abstract

    Emerging shared travel modes such as “Zhuanche, " “Kuaiche, " and “Shunfengche” have flourished in China. Such shared mobility in this chapter, indicated as an app-based private taxi, has sparked great debates charging that these sharing services may increase road congestion and air pollution. In this chapter, we aim to find out how to achieve the sustainable development of sharing vehicles by taking China as the empirical context. We conduct a joint research with company called Didi Chuxing in China by employing the raw big trip data. The characteristics of the shared trips in terms of travel time and trip distance are first explored. On the basis of this, we further adopt the life cycle analysis of transport fuels and input-output analysis to measure the direct and indirect impacts of sharing mobility on the energy consumption and emissions, attributing to the travel mode shift and the attitude change toward vehicle purchase. The results show that compared with the case of not using shared mobility, the direct energy consumption and CO2 emission will increase. However, the indirect environmental benefits resulted from the potential influence of shared services on passengers’ vehicle purchase behavior, and then the car manufacture industry is appreciable. Government, enterprise, and consumers need to closely collaborate and clearly define roles, responsibilities, and relationships, so as to achieve the green development of sharing mobility.

    Original languageEnglish
    Title of host publicationTransport and Energy Research
    Subtitle of host publicationA Behavioral Perspective
    PublisherElsevier
    Pages223-242
    Number of pages20
    ISBN (Electronic)9780128159651
    DOIs
    Publication statusPublished - 1 Jan 2019

    Keywords

    • Big trip data
    • EV
    • Energy consumption
    • Ride-sourcing travel
    • Ridesharing
    • Shared mobility

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