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Embodied greenhouse gas emissions from building China’s large-scale power transmission infrastructure

Nature Sustainability volume 4, pages 739–747 (2021)Cite this article

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Abstract

China has built the world’s largest power transmission infrastructure by consuming massive volumes of greenhouse gas- (GHG-) intensive products such as steel. A quantitative analysis of the carbon implications of expanding the transmission infrastructure would shed light on the trade-offs among three connected dimensions of sustainable development, namely, climate change mitigation, energy access and infrastructure development. By collecting a high-resolution inventory, we developed an assessment framework of, and analysed, the GHG emissions caused by China’s power transmission infrastructure construction during 1990–2017. We show that cumulative embodied GHG emissions have dramatically increased by more than 7.3 times those in 1990, reaching 0.89 GtCO2-equivalent in 2017. Over the same period, the gaps between the well-developed eastern and less-developed western regions in China have gradually narrowed. Voltage class, transmission-line length and terrain were important factors that influenced embodied GHG emissions. We discuss measures for the mitigation of GHG emissions from power transmission development that can inform global low-carbon infrastructure transitions.

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Fig. 1: Embodied GHG emissions induced by China’s power transmission infrastructure.
Fig. 2: Evolution of cumulative GHG emissions embodied in the power transmission infrastructure of different provincial regions.
Fig. 3: Embodied GHG emissions of typical transmission-line projects in 2017.
Fig. 4: Embodied GHG emissions of typical substation projects in 2017.

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Data availability

All the GHG emission inventories of power transmission projects and China’s 31 provincial regions’ power transmission systems from 1990 to 2017 are listed in Supplementary Tables 5–18. All our data are available to readers and can be freely downloaded from the CEADs website (https://www.ceads.net/data/process/). Source data are provided with this paper.

Code availability

The code for uncertainty analysis can be accessed via our recent work published in Scientific Data (https://doi.org/10.1038/s41597-020-00662-4) or at https://www.ceads.net/data/process/.

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Acknowledgements

W.W. was supported by the National Key R&D Program of China (2019YFC1908501), the National Natural Science Foundation of China (72088101, 71904125 and 71690241) and the Shanghai Sailing Program (18YF1417500). J.L. was supported by the National Natural Science Foundation of China (72074137 and 71961137010) and the Taishan Scholars Program. D.G. was supported by the National Natural Science Foundation of China (41921005 and 91846301). H.Q. was supported by the National Natural Science Foundation of China (71703027). K.F. was supported by the Taishan Scholars Program and the Shandong University Interdisciplinary Research and Innovation Team of Young Scholars. N.Z. was supported by the National Natural Science Foundation of China (72033005).

Author information

Author notes

  1. These authors contributed equally: Wendong Wei, Jiashuo Li.

Authors and Affiliations

  1. School of International and Public Affairs, Shanghai Jiao Tong University, Shanghai, P. R. China

    Wendong Wei

  2. SJTU-UNIDO Joint Institute of Inclusive and Sustainable Industrial Development, Shanghai Jiao Tong University, Shanghai, P. R. China

    Wendong Wei

  3. China Institute for Urban Governance, Shanghai Jiao Tong University, Shanghai, P. R. China

    Wendong Wei

  4. Institute of Blue and Green Development, Shandong University, Weihai, P.R. China

    Jiashuo Li, Pengfei Zhang, Kuishuang Feng & Ning Zhang

  5. Fudan Tyndall Center, Department of Environmental Science & Engineering, Fudan University, Shanghai, P. R. China

    Bin Chen

  6. Business School, University of Shanghai for Science and Technology, Shanghai, P. R. China

    Meng Wang

  7. College of Economics and Management, Nanjing University of Aeronautics and Astronautics, Nanjing, P. R. China

    Meng Wang

  8. Department of Earth System Science, Tsinghua University, Beijing, P. R. China

    Dabo Guan

  9. The Bartlett School of Construction and Project Management, University College London, London, UK

    Dabo Guan & Jing Meng

  10. Institute for Global Public Policy, Fudan University, Shanghai, P. R. China

    Haoqi Qian

  11. State Key Laboratory of Control and Simulation of Power Systems and Generation Equipment, Department of Electrical Engineering, Tsinghua University, Beijing, P. R. China

    Yaohua Cheng & Chongqing Kang

  12. Department of New Energy Science and Technology, School of Energy and Power Engineering, Huazhong University of Science and Technology, Wuhan, P. R. China

    Qing Yang

  13. Centre for Business and Climate Change, Business School, University of Edinburgh, Edinburgh, UK

    Xi Liang

  14. Future Energy Center of Malardalen University, Västerås, Sweden

    Jinjun Xue

  15. Economic Research Center, Nagoya University, Nagoya, Japan

    Jinjun Xue

  16. School of Management and Economics, Kunming University of Science and Technology, Kunming, P. R. China

    Jinjun Xue

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  1. Wendong Wei
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Contributions

W.W., J.L., D.G. and N.Z. conceived the study. H.Q. and K.F. provided the data. W.W., J.L., B.C., M.W. and P.Z. performed the analysis. All authors interpreted the data. W.W. and J.L. prepared the manuscript. All authors revised the manuscript.

Corresponding authors

Correspondence to Jiashuo Li, Dabo Guan or Ning Zhang.

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Peer review information Nature Sustainability thanks Maxime Agez, Daniel Müller and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Supplementary information

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Supplementary Fig. 1, Studies 1 and 2, and Methods.

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Supplementary Tables 1–23.

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Wei, W., Li, J., Chen, B. et al. Embodied greenhouse gas emissions from building China’s large-scale power transmission infrastructure. Nat Sustain 4, 739–747 (2021). https://doi.org/10.1038/s41893-021-00704-8

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