Skip to main content

Advertisement

Log in

Impact of high-speed rail on road traffic and greenhouse gas emissions

  • Article
  • Published:

From Nature Climate Change

View current issue Submit your manuscript

An Author Correction to this article was published on 08 December 2021

This article has been updated

Abstract

Carbon emission reduction in the transportation sector is essential in the global mitigation effort, and a large-scale public transport system has the potential to be an effective instrument. High-speed rail (HSR) is one such example, yet it is unclear how much reduction in road traffic results from new rail routes. Using the difference-in-differences method, we show that new HSR routes in China lead to a 20.5 log-point reduction in the number of passenger vehicles and a 15.7 log-point reduction in freight vehicles running on parallel highways. These reductions were not seen on ordinary national roads. These effects translate into an annual reduction of 11.183 million tons of CO2 equivalent of GHG emissions or 1.33% of GHG emissions in China’s transport sector. This mitigation effect mainly comes from the substitution of highway goods transport with the conventional railway instead of the direct replacement of highway passenger transport with HSRs. The environmental benefit of HSR in China has not been fully realized because of the thermal-dominated electricity supply. Our further projections suggest that in greener electricity conditions, the HSR in China can substantially contribute more to the reduction in GHG emissions from the transport sector.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1: Evolution of the HSR network in China from 2008 to 2016.
Fig. 2: Event study.
Fig. 3: Net change in GHG emissions.

Similar content being viewed by others

Data availability

The datasets analysed during the current study are not publicly available due to the confidentiality of the road monitoring data subject to a non-disclosure agreement but are available from the corresponding author on reasonable request.

Code availability

The Stata code used for the analysis of HSR’s effect in this Article is available from https://github.com/MondayX/Code_HSReffect_NCC.git.

Change history

References

  1. CO2 Emissions by Sector, World 1990–2018 (IEA, 2021); https://www.iea.org/data-and-statistics/data-browser/?country=WORLD&fuel=CO2%20emissions&indicator=CO2BySector

  2. Oil Products Final Consumption by Sector, World 19902018 (IEA, 2021); https://www.iea.org/data-and-statistics/data-browser/?country=WORLD&fuel=Energy%20consumption&indicator=OilProductsConsBySector

  3. Hayashi, Y., Morichi, S., Oum, T. H. & Rothengatter, W. Intercity Transport and Climate Change: Strategies for Reducing the Carbon Footprint (Springer, 2014).

  4. The Future of Rail: Opportunities for Energy and the Environment (IEA, 2019).

  5. Borsati, M. & Albalate, D. On the modal shift from motorway to high-speed rail: evidence from Italy. Transp. Res. Part A 137, 145–164 (2020).

    Google Scholar 

  6. Duranton, G. & Turner, M. A. The fundamental law of road congestion: evidence from US cities. Am. Econ. Rev. 101, 2616–2652 (2011).

    Article  Google Scholar 

  7. 2020 China Railway Yearbook (China State Railway Group Co. Ltd., 2021)

  8. Chen, Y. & Whalley, A. Green infrastructure: the effects of urban rail transit on air quality. Am. Econ. J. Econ. Policy 4, 58–97 (2012).

    Article  CAS  Google Scholar 

  9. Lalive, R., Luechinger, S. & Schmutzler, A. Does expanding regional train service reduce air pollution? J. Environ. Econ. Manag. 92, 744–764 (2018).

    Article  Google Scholar 

  10. Bauernschuster, S., Hener, T. & Rainer, H. When labor disputes bring cities to a standstill: the impact of public transit strikes on traffic, accidents, air pollution, and health. Am. Econ. J. Econ. Policy 9, 1–37 (2017).

  11. Guo, X., Sun, W., Yao, S. & Zheng, S. Does high-speed railway reduce air pollution along highways? Evidence from China. Transp. Res. Part D 89, 102607 (2020).

    Article  Google Scholar 

  12. Beaudoin, J. & Lawell, C.-Y. C. L. in Urban Transport Systems (ed. Yaghoubi, H.) Ch. 6 (IntechOpen, 2017).

  13. Rivers, N., Saberian, S. & Schaufele, B. Public transit and air pollution: evidence from Canadian transit strikes. Can. J. Econ.53, 496–525 (2020).

    Article  Google Scholar 

  14. He, H. The revenue of China’s high-speed rail exceeds expectations. Chinanews (7 December 2010); http://www.chinanews.com/cj/2010/12-07/2706603.shtml

  15. CO2 Emissions by Sector, People’s Republic of China 1990–2018 (IEA, 2021); https://www.iea.org/data-and-statistics/data-browser/?country=CHINA&fuel=CO2%20emissions&indicator=CO2BySector

  16. 2020 China Energy Statistical Yearbook (Department of Energy Statistics of the National Bureau of Statistics, 2021).

  17. Notice on the Preparation of the ‘The Fourteenth Five-Year Plan’ for Renewable Energy Development (National Energy Administration, 2020); http://zfxxgk.nea.gov.cn/2020-04/09/c_138978661.htm

  18. Ou, X., Xiaoyu, Y. & Zhang, X. Life-cycle energy consumption and greenhouse gas emissions for electricity generation and supply in China. Appl. Energy 88, 289–297 (2011).

    Article  CAS  Google Scholar 

  19. Zhou, G., Ou, X. & Zhang, X. Development of electric vehicles use in China: a study from the perspective of life-cycle energy consumption and greenhouse gas emissions. Energy Policy 59, 875–884 (2013).

    Article  Google Scholar 

  20. Chang, Y. et al. The energy use and environmental emissions of high-speed rail transportation in China: a bottom-up modeling. Energy 182, 1193–1201 (2019).

    Article  Google Scholar 

  21. Zhu, P., Lin, Y. & Guo, Y. How Much Does High-speed Rail Substitute for Air Travel? Implications for Transport, Environmental and Energy Policies Working Paper (Research Square, 2020); https://doi.org/10.21203/rs.3.rs-106949/v1

  22. Electricity Generation by Source, France 2019 (IEA, 2021); https://www.iea.org/data-and-statistics/data-tables?country=FRANCE&energy=Electricity&year=2019

  23. Electricity Generation by Source, Canada 2019 (IEA, 2021); https://www.iea.org/data-and-statistics/data-tables?country=CANADA&energy=Electricity&year=2019

  24. Electricity Generation by Source, Denmark 2019 (IEA, 2021); https://www.iea.org/data-and-statistics/data-tables?country=DENMARK&energy=Electricity&year=2019

  25. Electricity Generation by Source, Spain 2019 (IEA, 2021); https://www.iea.org/data-and-statistics/data-tables?country=SPAIN&energy=Electricity&year=2019

  26. Electricity Generation by Source, Japan 2019 (IEA, 2021); https://www.iea.org/data-and-statistics/data-tables?country=JAPAN&energy=Electricity&year=2019

  27. Electricity Generation by Source, Germany 2019 (IEA, 2021); https://www.iea.org/data-and-statistics/data-tables?country=GERMANY&energy=Electricity&year=2019

  28. Report of Nutrition and Chronic Diseases of Chinese Residents (The National Health Commission of the People’s Republic of China, 2015); http://www.nhc.gov.cn/jkj/s5879/201506/4505528e65f3460fb88685081ff158a2.shtml

  29. 2017 Yearbook of China Transportation & Communications (China Communications and Transportation Association, 2018).

  30. 2017 China Logistics Yearbook (China Federation of Logistics & Purchasing, 2018).

  31. Cai, H. & Xie, S. Determination of emission factors from motor vehicles under different emission standards in China. Acta Sci. Nat. Univ. Pekin. 46, 319–326 (2010).

    CAS  Google Scholar 

  32. Song, R., Yang, S. & Sun, M. GHG Protocol Tool for Energy Consumption in China v2.1 (World Resources Institute, 2013).

Download references

Acknowledgements

We highly appreciate L. Zhu and L. Shao for their work cleaning raw data. We are also grateful for the funding by the National Natural Science Foundation of China (projects 71874093 and 91546113) received by J.W.

Author information

Authors and Affiliations

Authors

Contributions

All authors equally contributed to the Article. Y.L., Y.Q. and J.W. conceptualized the study and carried out initial planning. M.X. constructed the dataset and carried out the statistical analysis under the guidance of Y.L., Y.Q. and J.W. All four authors contributed to the writing of the manuscript.

Corresponding author

Correspondence to Yu Qin.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Peer review information Nature Climate Change thanks the anonymous reviewers for their contribution to the peer review of this work.

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Supplementary Information

Supplementary Note, Figs. 1–3, Tables 1–22 and Refs. 1–24.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Lin, Y., Qin, Y., Wu, J. et al. Impact of high-speed rail on road traffic and greenhouse gas emissions. Nat. Clim. Chang. 11, 952–957 (2021). https://doi.org/10.1038/s41558-021-01190-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41558-021-01190-8

  • Springer Nature Limited

This article is cited by

Navigation