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Synergistic pathways to mitigate climate and water scarcity risks


Abstract

Energy security, climate change and water scarcity are inextricably linked challenges that require integrated solutions for sustainable development. A promising approach combining carbon capture and storage (CCS) with enhanced water recovery (EWR), termed CCS–EWR, provides a technically and economically viable solution to the energy–carbon–water dilemma. By developing a high-resolution source–sink matching model for coal-fired power plants in China, we found that retrofitting plants with a total capacity of 567.4 GW with CCS could store 1.6 GtCO2 in 2030. Associated water extraction from EWR is expected to increase from 1.7 Gt (1.5–1.9 Gt) in 2030 to 3.3 Gt (2.9–3.7 Gt) in 2060, equivalent to 79.2% (68.1–90.4%) and 154.1% (136.3–172.0%) of the current industrial water shortage in China. Cumulative water extraction reaches 94.6 Gt (83.0–106.3 Gt) during 2025–2060, with a net increase in blue water extraction of 54.6 Gt (33.3–76.0 Gt) after accounting for additional water requirements with CCS. In 2030, there will be 0.48 Gt of blue water extracted in water-scarce regions through CO2 sequestration from water-abundant regions. With maximum cumulative profits of CCS–EWR expected to be US$370.8 million per year, this approach highlights the transferable framework for assessing energy–carbon–water synergy in regions where energy security, carbon mitigation and water scarcity concerns intersect with geological storage potential.

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Fig. 1: Conceptual framework of energy–carbon–water synergy for the power system.
The alternative text for this image may have been generated using AI.
Fig. 2: Variations in water extraction and consumption of CCS–EWR during 2025–2060.
The alternative text for this image may have been generated using AI.
Fig. 3: Redistribution of water resources with the CCS–EWR approach, based on a high-resolution CCS source–sink matching model.
The alternative text for this image may have been generated using AI.
Fig. 4: Economic feasibility of EWR.
The alternative text for this image may have been generated using AI.
Fig. 5: Costs of deep saline water desalination technologies and typical water diversion projects around the world.
The alternative text for this image may have been generated using AI.

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Data availability

The data that support the findings of this study have been made publicly available. The details of the databases and data sources used in this study are provided in Supplementary Information. Source data are provided with this paper.

Code availability

The code used in this study is available with this paper. The details of the model code and source information are provided in Supplementary Information.

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Acknowledgements

We acknowledge the contributions of X. Zhao, M. Xu, X. Shen and Y. Qin to the data collection and analysis discussion.

Funding

X.Z. discloses support for this research from the National Program for Support of Top-Notch Young Professionals. H.L. discloses support for this research from the Young Elite Scientists Sponsorship Program by the Beijing Association for Science and Technology (BYESS2023234) and from the Fundamental Research Funds for Beijing Municipal Universities (2025JKZX26). J.L. discloses support for this research from the National Natural Science Foundation of China (no. 72503114). K.L., J.F., J.M. and K.H. declare no relevant funding.

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X.Z. and H.L. designed the research. J.L. led the analysis and visualized the results. J.L. drafted the paper. X.Z., H.L., K.L. and J.F. provided the data and performed the source–sink matching model. J.M. and K.H. contributed to the discussions. All authors contributed to the paper revision.

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Correspondence to
Xian Zhang.

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Nature Sustainability thanks Jeffrey Bielicki, Jay Fuhrman and Alena Lohrmann for their contribution to the peer review of this work.

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Supplementary Figs. 1–13, Tables 1–7 and Notes 1–9.

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Supplementary Data 1 (download XLSX )

The total number of CFPPs eligible for CCS retrofits and their corresponding total installed capacity across provinces.

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Statistical source data.

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Statistical source data.

Source Data Fig. 4 (download XLSX )

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Source Data Fig. 5 (download XLSX )

Statistical source data.

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Lv, H., Li, J., Li, K. et al. Synergistic pathways to mitigate climate and water scarcity risks.
Nat Sustain (2026). https://doi.org/10.1038/s41893-026-01880-1

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