Abstract
Clean energy transitions are known to reduce carbon emissions, but their co-benefits for atmospheric heavy metal pollution remain unclear. Here we assess this co-benefit using data from 331 Chinese cities. We find that from 2015 to 2020, the transition reduced atmospheric heavy metal emissions by 258 tonnes, accounting for 6.4% of total reductions during this period. Under a business-as-usual scenario extending to 2060, future reductions could reach 520 tonnes (10.2%). Additional efforts, such as a faster clean energy transition and a radical combination of economic and social pathways, reductions could increase to 1,650 tonnes (30.4%). The co-benefit effects vary across city types, with non-resource-based and comprehensive type I cities showing larger reductions (17.65% and 15.68%) than those in service-based and comprehensive type II cities (7.05% and 8.33%). These findings help monitor clean energy transitions and identify pathways for reducing atmospheric heavy metal pollution in Chinese cities.
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Data availability
The source data for all main figures (Figs. 1–6) in this paper are available via the Figshare repository: https://doi.org/10.6084/m9.figshare.31399224. This dataset contains the numerical values used directly to generate each figure, organized by separate sheets corresponding to Figs. 1–6. The final energy consumption inventory for Chinese cities, which underlies the clean energy transition analysis, is available via https://doi.org/10.6084/m9.figshare.25295545.v2. The atmospheric heavy metal emissions (AHMP) dataset for Chinese cities, which underlies the heavy metal pollution analysis, is available via https://doi.org/10.6084/m9.figshare.24762513.v4.
Code availability
The custom code used to assess the historical contribution of city-level clean energy transition to atmospheric heavy metal pollution reduction and to simulate prospective scenarios is available via Figshare: https://doi.org/10.6084/m9.figshare.31406487. The code is written in Python (version 3.9). The diagrams in Figs. 1–6 were generated using standard software (Microsoft Excel and ArcMap) and do not require custom code.
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Acknowledgements
This work was supported by the National Natural Science Foundation of China (72403107, 42401346, 72243006, 72034003, 72074111), the National Social Science Fund of China (23XGL014), the Special Soft Science Project of Gansu Science and Technology Plan (24JRZA044), The Fundamental Research Funds for the Central Universities (2024lzujbkybh003), Lanzhou University Philosophy and Social Sciences Innovation Team Project, and the Royal Society International Exchanges (IEC\NSFC\252060).
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G.Y. and D. C. initiated, designed and led this study. G.Y. wrote the first draft of the paper. G.Y. and X.W. carried out the data collection, analysis and visualization. G.Y., F.H., S.Y., and Y.Y. offered suggestions on the data analysis and visualization. G.Y., D.C., G.Z., Y.Z., X.Z., D.Z., and Y.S. revised the paper. D.C., D.Z., and Y.S. administered the study.
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Communications Earth and Environment thanks Zhixuan Ji and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Primary Handling Editors: Marie Claire Brisbois and Nandita Basu. A peer review file is available.
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Yang, G., Zhang, G., Cao, D. et al. Mitigating atmospheric heavy metal pollution requires added efforts amid rapid clean-energy transitions in Chinese cities. Commun Earth Environ (2026). https://doi.org/10.1038/s43247-026-03436-9
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DOI: https://doi.org/10.1038/s43247-026-03436-9
