Evidence map›Paper›PMID 42100676›Full record

ArticleEnvironmental science and ecotechnology2026

Global data-water symbiosis reduces AI infrastructure's carbon and water footprint.

Aijie Wang, Congchao Zhang, Tiefu Xu, Dragan Savic, Jingjing Jiang, Peng Xiao, Chuan He, Yu Tao, Glen Daigger, Nanqi Ren

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Environmental science and ecotechnology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Aijie WangSchool of Eco-Environment, Harbin Institute of Technology, Shenzhen, 518055, China.
Congchao ZhangState Key Laboratory of Urban-rural Water Resource & Environment, School of Environment, Harbin Institute of Technology, Harbin, 150090, China.
Tiefu XuSchool of Civil Engineering, Heilongjiang University, Harbin, 150080, China.
Dragan SavicKWR Water Research Institute, Nieuwegein, 3430, BB, Netherlands.
Jingjing JiangSchool of Economics and Management, Harbin Institute of Technology, Shenzhen, 518055, China.
Peng XiaoState Key Laboratory of Urban-rural Water Resource & Environment, School of Environment, Harbin Institute of Technology, Harbin, 150090, China.
Chuan HeSchool of Eco-Environment, Harbin Institute of Technology, Shenzhen, 518055, China.
Yu TaoSchool of Eco-Environment, Harbin Institute of Technology, Shenzhen, 518055, China.
Glen DaiggerDepartment of Civil and Environmental Engineering, University of Michigan, Ann Arbor, MI, 48109, USA.
Nanqi RenSchool of Eco-Environment, Harbin Institute of Technology, Shenzhen, 518055, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Data centres support artificial intelligence (AI) development but place rapidly increasing demands on electricity and freshwater resources, with cooling representing a significant portion of their total energy consumption. Wastewater treatment plants (WWTPs) discharge large volumes of treated effluent with substantial cooling potential; however, their integration with data centre infrastructure has not been evaluated. Here we construct a global geodatabase of over 4775 data centres and 57,547 municipal WWTPs across 98 countries, integrating spatial analysis, engineering systems modelling, optimisation, and life-cycle assessment to quantify the benefits of combining treated water reuse with bidirectional thermal recovery. The analysis reveals a strong global spatial co-occurrence between data centres and WWTPs, enabling optimized national-scale pairings in which treated effluent is used for data centre cooling and the return heat is recovered to support sludge drying and anaerobic digestion. This symbiotic approach reduces greenhouse gas emissions by approximately 84 million tonnes of CO

Indexed as

Carbon mitigationData centreInfrastructure symbiosisWater savingWWTP

Identifiers

PMID42100676
PMCPMC13147368

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.