Abstract
Wastewater treatment is a key component in ensuring future water resource security. However, this process itself faces major challenges in water and energy consumption. Reducing these inputs at low cost without compromising wastewater treatment effectiveness is crucial for sustainable development. Here, we assess the water and energy footprint of wastewater treatment in China, using estimated data from 10,124 urban wastewater treatment plants and 90 cases. We show that the water and energy footprints of wastewater treatment in China have nearly tripled from 2009 to 2022. By aligning treatment process selection through multi-objective trade-offs, reductions can be effectively achieved. By 2035, China’s wastewater treatment water footprint and energy footprint could be reduced by 16.1% and 25.6%, respectively, with investments below 8% of total treatment costs, while the removal remains stable. Our findings offer a broadly applicable framework to guide sustainable wastewater management and support progress toward the Sustainable Development Goals.
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Data availability
The processed data generated in this study, including provincial- and national-scale water and energy footprints, process-level footprint intensities, and scenario simulation outputs, are provided in Supplementary Data 1 and 2. The wastewater treatment plant (WWTP) process composition, treatment capacity, and technology distribution data used in this study are available under restricted access, as they are part of a paid, print-based statistical publication (Urban Drainage Statistical Yearbook, 2009–2017) published by the Ministry of Housing and Urban-Rural Development of China. Access to this data can be obtained through institutional purchase of the yearbooks or by contacting the publisher. The provincial wastewater discharge data used in this study are available in the China Environmental Statistical Yearbook, published by the Ministry of Ecology and Environment of China, and are publicly accessible on the Ministry's official website (https://www.mee.gov.cn/). Socioeconomic data used in this study, including population size, gross domestic product (GDP), and per capita GDP, are available from the China Statistical Yearbook, published by the National Bureau of Statistics of China, and are publicly accessible via the National Bureau of Statistics data portal (https://www.stats.gov.cn/sj/ndsj/). Engineering case data used to estimate process-level water and energy footprints were compiled from published wastewater treatment plant case studies reported in peer-reviewed literature. The full list of literature sources and extracted parameters is provided in Supplementary Information Section S1. Cost data and total nitrogen (TN) and total phosphorus (TP) removal efficiency data for major wastewater treatment technologies used in the scenario analysis were derived from published literature sources and are provided in Supplementary Information Table S11, with all literature sources listed therein. National technical standards and design codes used in this study to define wastewater treatment plant lifetime, structural parameters, and life cycle assumptions (including GB 50335-2016, GB 50003-2011, GB 50007-2011, and GB/T 50006-2010) are officially issued Chinese national standards and can be queried via the National Public Service Platform for Standards Information (https://std.samr.gov.cn/) and the official website of the Ministry of Housing and Urban-Rural Development of the People’s Republic of China (https://www.mohurd.gov.cn/). Population projection data used in this study are available from the dataset “Provincial and gridded population projection for China under shared socioeconomic pathways (2010-2100)” published by Chen et al. (2020) in Scientific Data.
Code availability
No custom code was developed for this study. All analyses were performed using standard functions in R (version 4.3.3), Python (version 3.11.7), and Origin, without the use of bespoke algorithms. Therefore, no code is required to reproduce the results.
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Acknowledgements
The authors are grateful for financial supports from the State Key Laboratory of Efficient Utilization of Agricultural Water Resources, Pinduoduo-China Agricultural University Research Fund (PC2023A02002, Y. L.), National Natural Science Foundation of China (52339004, Y. L., 52079139, B. Z.), the 2115 Talent Development Program of China Agricultural University (00109023, Y. L.), and European Research Council (ERC) under the European Union’s Horizon Europe research and innovation program (grant agreement 101039426, B-WEX).
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Yunkai Li and B. Z. designed the research. S. H. and B. Z. wrote the manuscript. S.H., B.Z., and Y.W. analyzed the data. Yunkai Li, E.J., T.Y., W.C., X.C., X.K., J.Z., E.X., Y.X., Q.Z., and L.L. provided comments on the manuscript. All authors reviewed the manuscript.
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Han, S., Jones, E.R., Yin, T. et al. Cost-effective strategies can reduce water and energy requirements in China’s wastewater treatment by 2035. Nat Commun (2026). https://doi.org/10.1038/s41467-026-70159-y
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DOI: https://doi.org/10.1038/s41467-026-70159-y
