IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v341y2025ics0360544225051205.html

Decarbonizing high-speed rail infrastructure in China: An integrated assessment combining machine learning and scenario modeling to 2060

Author

Listed:
  • Guo, Guisong
  • Zhu, Chen
  • Mao, Ruichang
  • Li, Xiaodong
  • Wu, Yankun
  • Chen, Jian

Abstract

China's rapid expansion of high-speed rail (HSR) has triggered extensive construction, maintenance and renovation activities that sharply increase embodied carbon emissions. However, the long-term evolution, emission trajectory, and mitigation potential of HSR remain poorly understood. This study develops a multi-scenario assessment framework that integrates machine learning to predict the evolution of HSR system scale and composition, scenario-based modeling to estimate carbon intensity across different technological pathways, and Shapley value decomposition to attribute emission reductions to interacting mitigation drivers. Applying baseline, medium control, and strict control scenarios, this study assesses embodied emissions and abatement potential for China's HSR systems from 2021 to 2060. Results show that the system scale could reach 72,000 km by 2060, consuming roughly 2711–3455 Mt of materials and 284–287 GWh of electricity, with cumulative embodied emissions of 1000 MtCO2 under the baseline. Maintenance dominates at 49 % of the total. A strict control pathway cuts cumulative emissions by 16.2 % by 2060. The key mitigation strategies are intelligent maintenance (9.6 %), lower emission factors of material and energy (3.9 %), high-performance structures (2.0 %) in construction and lifetime extension (1.0 %) in renovation, providing actionable guidance for HSR decarbonization. These results offer critical policy insights for guiding HSR toward low-carbon development and supply a transferable methodological reference for other infrastructures.

Suggested Citation

  • Guo, Guisong & Zhu, Chen & Mao, Ruichang & Li, Xiaodong & Wu, Yankun & Chen, Jian, 2025. "Decarbonizing high-speed rail infrastructure in China: An integrated assessment combining machine learning and scenario modeling to 2060," Energy, Elsevier, vol. 341(C).
    • Handle: RePEc:eee:energy:v:341:y:2025:i:c:s0360544225051205
    DOI: 10.1016/j.energy.2025.139478
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544225051205
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2025.139478?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    References listed on IDEAS

    as
    1. Shang, Wen-Long & Chen, Yishui & Yu, Qing & Song, Xuewang & Chen, Yanyan & Ma, Xiaolei & Chen, Xiqun & Tan, Zhijia & Huang, Jianling & Ochieng, Washington, 2023. "Spatio-temporal analysis of carbon footprints for urban public transport systems based on smart card data," Applied Energy, Elsevier, vol. 352(C).
    2. Ang, B.W., 1993. "Sector disaggregation, structural effect and industrial energy use: An approach to analyze the interrelationships," Energy, Elsevier, vol. 18(10), pages 1033-1044.
    3. Yang, Jie & Zhang, Zhengxu & Ma, Kai & Yang, Kun & Guo, Shiliang & Li, Haibin, 2024. "A multi-ship power sharing strategy: Using two-stage robust optimization and Shapley value approach," Renewable Energy, Elsevier, vol. 232(C).
    4. Zhang, Zhonglian & Yang, Xiaohui & Yang, Li & Wang, Zhaojun & Huang, Zezhong & Wang, Xiaopeng & Mei, Linghao, 2023. "Optimal configuration of double carbon energy system considering climate change," Energy, Elsevier, vol. 283(C).
    5. Jianyi Lin & Shihui Cheng & Huimei Li & Dewei Yang & Tao Lin, 2019. "Environmental Footprints of High-Speed Railway Construction in China: A Case Study of the Beijing–Tianjin Line," IJERPH, MDPI, vol. 17(1), pages 1-14, December.
    6. Wei, Ting & Chen, Shaoqing, 2020. "Dynamic energy and carbon footprints of urban transportation infrastructures: Differentiating between existing and newly-built assets," Applied Energy, Elsevier, vol. 277(C).
    7. Zhu, Chen & Li, Xiaodong & Zhu, Weina & Gong, Wei, 2022. "Embodied carbon emissions and mitigation potential in China's building sector: An outlook to 2060," Energy Policy, Elsevier, vol. 170(C).
    8. Wang, Xiaolu & Tan, Yumin & Zhou, Guanhua & Jing, Guifei & John Francis, Emolu, 2024. "A framework for analyzing energy consumption in urban built-up areas based on single photonic radar and spatial big data," Energy, Elsevier, vol. 290(C).
    9. Zhang, Lihui & Li, Songrui & Nie, Qingyun & Hu, Yitang, 2022. "A two-stage benefit optimization and multi-participant benefit-sharing strategy for hybrid renewable energy systems in rural areas under carbon trading," Renewable Energy, Elsevier, vol. 189(C), pages 744-761.
    10. Cui, Jingbo & Wang, Chunhua & Zhang, Junjie & Zheng, Yang, 2021. "The effectiveness of China’s regional carbon market pilots in reducing firm emissions," LSE Research Online Documents on Economics 113492, London School of Economics and Political Science, LSE Library.
    11. Liu, Qingchen & Li, Hongchang & Shang, Wen-long & Wang, Kun, 2022. "Spatio-temporal distribution of Chinese cities’ air quality and the impact of high-speed rail," Renewable and Sustainable Energy Reviews, Elsevier, vol. 170(C).
    12. Zhou, Nan & Price, Lynn & Yande, Dai & Creyts, Jon & Khanna, Nina & Fridley, David & Lu, Hongyou & Feng, Wei & Liu, Xu & Hasanbeigi, Ali & Tian, Zhiyu & Yang, Hongwei & Bai, Quan & Zhu, Yuezhong & Xio, 2019. "A roadmap for China to peak carbon dioxide emissions and achieve a 20% share of non-fossil fuels in primary energy by 2030," Applied Energy, Elsevier, vol. 239(C), pages 793-819.
    13. Tao Wang & Jun Zhou & Ye Yue & Jie Yang & Seiji Hashimoto, 2016. "Weight under Steel Wheels: Material Stock and Flow Analysis of High-Speed Rail in China," Journal of Industrial Ecology, Yale University, vol. 20(6), pages 1349-1359, December.
    14. Jianyi Lin & Huimei Li & Wei Huang & Wangtu(Ato) Xu & Shihui Cheng, 2019. "A Carbon Footprint of High‐Speed Railways in China: A Case Study of the Beijing‐Shanghai Line," Journal of Industrial Ecology, Yale University, vol. 23(4), pages 869-878, August.
    15. Zhang, Lidong & Li, Jiao & Xu, Xiandong & Liu, Fengrui & Guo, Yuanjun & Yang, Zhile & Hu, Tianyu, 2023. "High spatial granularity residential heating load forecast based on Dendrite net model," Energy, Elsevier, vol. 269(C).
    16. Xu, Lei & Wen, Shaomu & Huang, Hongfa & Tang, Yongfan & Wang, Yunfu & Pan, Chunfeng, 2025. "Corrosion failure prediction in natural gas pipelines using an interpretable XGBoost model: Insights and applications," Energy, Elsevier, vol. 325(C).
    17. Konhäuser, Koray & Werner, Tim, 2024. "Uncovering the financial impact of energy-efficient building characteristics with eXplainable artificial intelligence," Applied Energy, Elsevier, vol. 374(C).
    18. Yang, Jingjing & Deng, Zhang & Guo, Siyue & Chen, Yixing, 2023. "Development of bottom-up model to estimate dynamic carbon emission for city-scale buildings," Applied Energy, Elsevier, vol. 331(C).
    19. Wu, Chaoxian & Ochieng, Washington & Pien, Kuang-Chang & Shang, Wen-Long, 2025. "Carbon-efficient timetable optimization for urban railway systems considering wind power consumption," Applied Energy, Elsevier, vol. 388(C).
    20. Tan, Xianchun & Lai, Haiping & Gu, Baihe & Zeng, Yuan & Li, Hui, 2018. "Carbon emission and abatement potential outlook in China's building sector through 2050," Energy Policy, Elsevier, vol. 118(C), pages 429-439.
    21. Shang, Wen-Long & Ling, Yantao & Ochieng, Washington & Yang, Linchuan & Gao, Xing & Ren, Qingzhong & Chen, Yilin & Cao, Mengqiu, 2024. "Driving forces of CO2 emissions from the transport, storage and postal sectors: A pathway to achieving carbon neutrality," Applied Energy, Elsevier, vol. 365(C).
    22. Ang, B.W. & Liu, F.L. & Chung, Hyun-Sik, 2004. "A generalized Fisher index approach to energy decomposition analysis," Energy Economics, Elsevier, vol. 26(5), pages 757-763, September.
    23. Janneke van Oorschot & Benjamin Sprecher & Bart Rijken & Pieter Witteveen & Merlijn Blok & Nico Schouten & Ester van der Voet, 2023. "Toward a low‐carbon and circular building sector: Building strategies and urbanization pathways for the Netherlands," Journal of Industrial Ecology, Yale University, vol. 27(2), pages 535-547, April.
    24. Huo, Tengfei & Xu, Linbo & Feng, Wei & Cai, Weiguang & Liu, Bingsheng, 2021. "Dynamic scenario simulations of carbon emission peak in China's city-scale urban residential building sector through 2050," Energy Policy, Elsevier, vol. 159(C).
    25. Cheng, Shulei & Fan, Wei & Chen, Jiandong & Meng, Fanxin & Liu, Gengyuan & Song, Malin & Yang, Zhifeng, 2020. "The impact of fiscal decentralization on CO2 emissions in China," Energy, Elsevier, vol. 192(C).
    26. Ren, Jinhui & Zhang, Qianzhi & Chen, Wenying, 2024. "China's provincial power decarbonization transition in a carbon neutral vision," Energy, Elsevier, vol. 310(C).
    27. Guo, Guisong & Li, Xiaodong & Zhu, Chen & Wu, Yankun & Chen, Jian & Chen, Peng & Cheng, Xi, 2025. "Establishing benchmarks to determine the embodied carbon performance of high-speed rail systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 207(C).
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Liu, Qiqi & Liu, Yuan & Cai, Weiguang & Du, Yongjie, 2025. "Multi-dimensional building carbon emissions echelon peak target setting in China based on building types, sources, and indicators," Applied Energy, Elsevier, vol. 386(C).
    2. Huo, Tengfei & Xu, Linbo & Liu, Bingsheng & Cai, Weiguang & Feng, Wei, 2022. "China’s commercial building carbon emissions toward 2060: An integrated dynamic emission assessment model," Applied Energy, Elsevier, vol. 325(C).
    3. Miao, Ankang & Yuan, Yue & Wu, Han & Ma, Xin & Shao, Chenyu & Xiang, Sheng, 2024. "Pathway for China's provincial carbon emission peak: A case study of the Jiangsu Province," Energy, Elsevier, vol. 298(C).
    4. Xue, Dabin & Du, Sen & Wang, Bing & Shang, Wen-Long & Avogadro, Nicolò & Ochieng, Washington Yotto, 2025. "Low-carbon benefits of aircraft adopting continuous descent operations," Applied Energy, Elsevier, vol. 383(C).
    5. Zhai, Xiongxiong & Luo, Xi & Liu, Xiaojun & Zhou, Tingting & Gao, Xiaoxiao & Gao, Yaru & He, Lin, 2025. "A bottom-up framework incorporating non-commercial energy: Multi-Scenario dynamic simulation for low-carbon transition of rural residential buildings in northwest China," Energy, Elsevier, vol. 340(C).
    6. Yanyan Ke & Lu Zhou & Minglei Zhu & Yan Yang & Rui Fan & Xianrui Ma, 2023. "Scenario Prediction of Carbon Emission Peak of Urban Residential Buildings in China’s Coastal Region: A Case of Fujian Province," Sustainability, MDPI, vol. 15(3), pages 1-17, January.
    7. Huo, Tengfei & Ma, Yuling & Xu, Linbo & Feng, Wei & Cai, Weiguang, 2022. "Carbon emissions in China's urban residential building sector through 2060: A dynamic scenario simulation," Energy, Elsevier, vol. 254(PA).
    8. Jiang, Jingjing & Ye, Bin & Liu, Junguo, 2019. "Peak of CO2 emissions in various sectors and provinces of China: Recent progress and avenues for further research," Renewable and Sustainable Energy Reviews, Elsevier, vol. 112(C), pages 813-833.
    9. Yang, Jingjing & Deng, Zhang & Guo, Siyue & Chen, Yixing, 2023. "Development of bottom-up model to estimate dynamic carbon emission for city-scale buildings," Applied Energy, Elsevier, vol. 331(C).
    10. Li, Rui & Liu, Qiqi & Cai, Weiguang & Liu, Yuan & Yu, Yanhui & Zhang, Yihao, 2023. "Echelon peaking path of China's provincial building carbon emissions: Considering peak and time constraints," Energy, Elsevier, vol. 271(C).
    11. Wu, Chaoxian & Ochieng, Washington & Pien, Kuang-Chang & Shang, Wen-Long, 2025. "Carbon-efficient timetable optimization for urban railway systems considering wind power consumption," Applied Energy, Elsevier, vol. 388(C).
    12. Zou, Runyuan & Wang, Bing & Wang, Kun & Shang, Wen-Long & Xue, Dabin & Ochieng, Washington Yotto, 2025. "A pathway to sustainable aviation: Modeling aircraft takeoff mass for precise fuel consumption and aircraft emission calculations," Energy, Elsevier, vol. 319(C).
    13. Yang, Xiaohui & Wu, Chilv & Huang, Zezhong & Wang, Xiaopeng & Wang, Zhicong & Deng, Fuwei & Hu, Zecheng, 2025. "A two-stage dynamic planning for rural hybrid renewable energy systems under coupled carbon-green certificate trading," Energy, Elsevier, vol. 316(C).
    14. Liu, Qiqi & Li, Rui & Cai, Weiguang & Huo, Tengfei, 2025. "Will China follow the same process of building carbon peak as the US? Evidence from the building carbon peak pattern," Energy, Elsevier, vol. 333(C).
    15. Fu, Xiao & Wu, Peimin, 2025. "Measurement methods and influencing factors of carbon emissions from residents' travel," Applied Energy, Elsevier, vol. 377(PD).
    16. Shang, Wen-Long & Song, Xuewang & Xiang, Qiannian & Chen, Haibo & Elhajj, Mireille & Bi, Huibo & Wang, Kun & Ochieng, Washington, 2025. "The impact of deep reinforcement learning-based traffic signal control on Emission reduction in urban Road networks empowered by cooperative vehicle-infrastructure systems," Applied Energy, Elsevier, vol. 390(C).
    17. Zhu, Chen & Li, Xiaodong & Zhu, Weina & Gong, Wei, 2022. "Embodied carbon emissions and mitigation potential in China's building sector: An outlook to 2060," Energy Policy, Elsevier, vol. 170(C).
    18. Zhang, Junjie & Yan, Zengfeng & Bi, Wenbei & Ni, Pingan & Lei, Fuming & Yao, Shanshan & Lang, Jiachen, 2023. "Prediction and scenario simulation of the carbon emissions of public buildings in the operation stage based on an energy audit in Xi'an, China," Energy Policy, Elsevier, vol. 173(C).
    19. Ma, Meiyan & Tang, Xu & Shi, Changning & Wang, Min & Li, Xinying & Luo, Pengfei & Zhang, Baosheng, 2023. "Roadmap towards clean and low-carbon heating to 2060: The case of northern urban region in China," Energy, Elsevier, vol. 284(C).
    20. Tian, Shirun & Yan, Fei & Shang, Wen-Long & Majumdar, Arnab & Chen, Haibo & Chen, Mingyang & Zeinab, Mohammed & Tian, Yuchen, 2025. "Energy consumption analysis of trains based on multi-mode virtual coupling operation control strategies," Applied Energy, Elsevier, vol. 377(PD).

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:energy:v:341:y:2025:i:c:s0360544225051205. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/energy .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.