In recent years, the carbon emissions in the transport sector have been maintained at annual growth rate over 5%, making it one of the major sources of Greenhouse Gas (GHG) emissions in China. In the background of low-carbon transformation, the "carbon peaking and carbon neutrality" target has put forward higher requirements for energy saving and carbon reduction in the transport sector. Heavy-duty trucks are a major energy consumer in the transport sector and are a key area for carbon neutrality. With the theory of human-machine-environment system engineering, this research figures out the factors affecting the energy consumption of vehicles. Based on the dynamic data of Heavy-duty trucks Global Positioning System (GPS), the research uses big data processing and statistical analysis to estimate the CO2 emissions of heavy-duty trucks over 12 tons in China and puts forward relevant policy suggestions for the development of energy-saving and carbon-reduction in the road freight industry. This paper provides theoretical support and reference for the green transformation of China's transportation industry.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    The research on the carbon footprint of road freight market based on dynamic data of heavy-duty trucks


    Contributors:
    Wang, Xinzi (author) / Xiao, Rongna (author) / Zhao, Nanxi (author)

    Conference:

    Sixth International Conference on Traffic Engineering and Transportation System (ICTETS 2022) ; 2022 ; Guangzhou,China


    Published in:

    Proc. SPIE ; 12591


    Publication date :

    2023-02-16





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    The research on the carbon footprint of road freight market based on dynamic data of heavy-duty trucks

    Wang, Xinzi / Xiao, Rongna / Zhao, Nanxi | British Library Conference Proceedings | 2023


    The Road Freight Industry Green Research Based on Big Data of Heavy-Duty Trucks Operation

    Wang, Xinzi / Zhao, Nanxi / Tang, Junzhong et al. | Springer Verlag | 2024

    Free access



    Conductive Electric Road System for Heavy-Duty Trucks

    Tajima, Takamitsu / Sato, Kouichi / Noguchi, Wataru et al. | British Library Conference Proceedings | 2022