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Research on the Emission Reduction Effect of High-Speed Rail and Its Impact Mechanism

In: Liss 2023

Author

Listed:
  • Yumeng Mao

    (Beijing Jiaotong University)

  • Xuemei Li

    (Beijing Jiaotong University)

  • Guanyi Liu

    (Beijing Jiaotong University)

  • Dehan Jiao

    (Beijing Jiaotong University)

  • Qingxian Zhao

    (Beijing Jiaotong University)

Abstract

Energy saving, and emission reduction are one of the most crucial tasks for the current and future high-quality progression of China’s economy and society, and as an efficient and healthy transportation mode, high-speed rail (HSR) is significant for improving China’s ecological environment. In this paper, we take the “quasi-natural experiment” of whether to open HSR as an opportunity to empirically analyze the mitigation effect of emissions, spatial heterogeneity, and mechanism of the effect of HSR’s opening based on the panel data of China from 2006 to 2020 and using double difference model. The results clarify that HSR can effectively suppress urban pollutant emissions, including urban sulfur dioxide emissions and wastewater emissions, with an emission reduction effect, and the subsequent robustness tests confirm this conclusion. Heterogeneity test’s results by region display that the effect of HSR on energy saving and emission reduction shows a decreasing trend from West, Central to East. Additionally, the operation of HSR declines the emission of pollutant sulfur dioxide mainly through the STI effect, and the impact on wastewater emission is not significant. In the current strategic context of a strong transportation country and green transportation, this study contributes to an in-depth understanding of the importance of upgrading transportation infrastructure for regional sustainable development.

Suggested Citation

  • Yumeng Mao & Xuemei Li & Guanyi Liu & Dehan Jiao & Qingxian Zhao, 2024. "Research on the Emission Reduction Effect of High-Speed Rail and Its Impact Mechanism," Lecture Notes in Operations Research, in: Daqing Gong & Yixuan Ma & Xiaowen Fu & Juliang Zhang & Xiaopu Shang (ed.), Liss 2023, pages 763-780, Springer.
    • Handle: RePEc:spr:lnopch:978-981-97-4045-1_60
    DOI: 10.1007/978-981-97-4045-1_60
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