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Low-Carbon Impact of Urban Rail Transit Based on Passenger Demand Forecast in Baoji

Author

Listed:
  • Na Zhang

    (School of Highway, Chang’an University, Xi’an 710064, China)

  • Zijia Wang

    (Beijing Engineering and Technology Research Center of Rail Transit Line Safety and Disaster Prevention, Beijing Jiaotong University, Beijing 100044, China
    School of Civil Engineering, Beijing Jiaotong University, Beijing 100044, China)

  • Feng Chen

    (School of Highway, Chang’an University, Xi’an 710064, China
    Beijing Engineering and Technology Research Center of Rail Transit Line Safety and Disaster Prevention, Beijing Jiaotong University, Beijing 100044, China)

  • Jingni Song

    (School of Highway, Chang’an University, Xi’an 710064, China)

  • Jianpo Wang

    (School of Highway, Chang’an University, Xi’an 710064, China)

  • Yu Li

    (School of Highway, Chang’an University, Xi’an 710064, China)

Abstract

There are increasing traffic pollution issues in the process of urbanization in many countries; urban rail transit is low-carbon and widely regarded as an effective way to solve such problems. The passenger flow proportion of different transportation types is changing along with the adjustment of the urban traffic structure and a growing demand from passengers. The reduction of carbon emissions brought about by rail transit lacks specific quantitative research. Based on a travel survey of urban residents, this paper constructed a method of estimating carbon emissions from two different scenarios where rail transit is and is not available. This study uses the traditional four-stage model to forecast passenger volume demand at the city level and then obtains the basic target parameters for constructing the carbon emission reduction model, including the trip origin-destination (OD), mode, and corresponding distance range of different modes on the urban road network. This model was applied to Baoji, China, where urban rail transit will be available from 2023. It calculates the changes in carbon emission that rail transit can bring about and its impact on carbon emission reductions in Baoji in 2023.

Suggested Citation

  • Na Zhang & Zijia Wang & Feng Chen & Jingni Song & Jianpo Wang & Yu Li, 2020. "Low-Carbon Impact of Urban Rail Transit Based on Passenger Demand Forecast in Baoji," Energies, MDPI, vol. 13(4), pages 1-18, February.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:4:p:782-:d:319115
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    References listed on IDEAS

    as
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    Cited by:

    1. Liudan Jiao & Fenglian Luo & Fengyan Wu & Yu Zhang & Xiaosen Huo & Ya Wu, 2022. "Exploring the Interactive Coercing Relationship between Urban Rail Transit and the Ecological Environment," Land, MDPI, vol. 11(6), pages 1-20, June.
    2. Jianming Zhang & Jun Cai & Mengjia Wang & Wansong Zhang, 2024. "An Estimation Method for Passenger Flow Volumes from and to Bus Stops Based on Land Use Elements: An Experimental Study," Land, MDPI, vol. 13(7), pages 1-18, July.
    3. Zijia Wang & Juanjuan Ding & Lichang Wang & Ziqiang Zhu, 2022. "Ex-ante and ex-post approaches of evaluating carbon emission reduction in urban rail transit," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 27(7), pages 1-21, October.

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