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Diversifying heat sources in China’s urban district heating systems will reduce risk of carbon lock-in


China’s clean heating policy since 2017 has notably improved air quality. However, the share of non-fossil sources in China’s urban district heating systems remain low, and many new coal-fired combined heat and power plants are being built. Strategic choices for district heating technologies are necessary for China to reach peak carbon emissions by 2030 and achieve carbon neutrality by 2060. Here we find that replacing polluting coal technologies with new and improved coal-fired combined heat and power plants will lead to substantial carbon lock-in and hinder decommissioning of associated coal-fired electricity generation. Expanding the use of industrial waste heat and air/ground-source heat pumps can avoid the need for new combined heat and power construction and reduce carbon emissions by 26% from 2020 to 2030. Our findings indicate the importance of the government’s recent proposals to decarbonize district heating.

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Fig. 1: Carbon emissions and costs for 15 district heating technologies.
Fig. 2: District heating generation, costs and emissions by sources in 2020 and three scenarios projected for 2030.
Fig. 3: Locked-in coal-fired electricity generation and committed CO2 emissions from existing and new CHP plants during the heating season in high-/mid-/low-coal scenarios from 2020 to 2060.
Fig. 4: Required new coal CHP capacity in the low/mid/high-coal scenarios by 2030 and in the pipeline as of June 2023 in northern China.
Fig. 5: Geographic map of city groups and required infrastructure investments in the low-coal scenario.

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Data availability

Datasets of coal-fired coal power plants, steel plants and nuclear plants were obtained from the Global Energy Monitor ( and recent peer-reviewed literature38. Urban district heating data were retrieved from Chinese Urban Infrastructure Statistical yearbooks39. All data generated in this study are available within the Supplementary Information and Supplementary Data files. Source data are provided with this paper.

Code availability

GCAM-China is an open-source model publicly available at and described in a previous paper50. The plant–city matching algorithm is conducted using PuLP 2.7.0, a linear programming model written in Python, available at


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We thank the Princeton School of Public and International Affairs at Princeton University for supporting S.L., the Schmidt Science Fellows in partnership with the Rhodes Trust for supporting Y.G. and the National Natural Science Foundation of China (number 72273102) for supporting H.L.

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Authors and Affiliations



S.L. and D.L.M. conceived the idea for this project and designed the research. S.L. performed the research. Y.G. and F.W. contributed to method design and analysis. Y.G., H.L. and R.Y.C. contributed data. S.L. and D.L.M. wrote the manuscript with feedback from all other authors.

Corresponding author

Correspondence to Denise L. Mauzerall.

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Supplementary information

Supplementary Information

Supplementary Notes 1–3, Tables 1–11 and Figs. 1–10.

Supplementary Table 1

Detailed city-level results.

Source data

Source Data Fig. 1

Statistical source data.

Source Data Fig. 2

Statistical source data.

Source Data Fig. 3

Statistical source data.

Source Data Fig. 4

Statistical source data.

Source Data Fig. 5

Statistical source data.

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Liu, S., Guo, Y., Wagner, F. et al. Diversifying heat sources in China’s urban district heating systems will reduce risk of carbon lock-in. Nat Energy (2024).

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