Global data–water symbiosis reduces AI infrastructure's carbon and water footprint
of freshwater, and provides net annual cost savings of approximately US$95.4 billion. The greatest mitigation and water-saving potential lies in the United States, Japan, China, the Netherlands, and the United Kingdom. These findings establish data-water symbiosis as a readily scalable infrastructure solution that decouples AI from its carbon and water footprints. WWTPs are poised to evolve from disposal facilities into critical energy-coupling hubs, enabling efficient thermal and water exchange across urban systems and accelerating progress towards multiple Sustainable Development Goals.
Authors
- Chuan He (ORCID: https://orcid.org/0000-0003-0612-5448)
- Dragan A. Savic (ORCID: https://orcid.org/0000-0001-9567-9041)
- Yu Tao (ORCID: https://orcid.org/0000-0002-5688-0073)
- Glen T. Daigger
- Peng Xiao (ORCID: https://orcid.org/0000-0002-7422-6534)
- Tiefu Xu
- Nanqi Ren
- Congchao Zhang
- Jingjing Jiang
- Aijie Wang
Institutions
- Harbin Institute of Technology (CN)
- University of Exeter (GB)
- University of Michigan (US)
- KWR Water Research Institute (NL)
- Heilongjiang University (CN)
Publication Details
- Journal
- Environmental Science and Ecotechnology
- Published
- 2026-04-26
- DOI
- https://doi.org/10.1016/j.ese.2026.100702
- Primary Topic
- Water-Energy-Food Nexus Studies
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China
- Science, Technology and Innovation Commission of Shenzhen Municipality
- European Research Council