Evidence map›Paper›PMID 39808683›Full record

ArticlePloS one2025

Decoupling evolution of water footprint of energy and its driving factors: Evidence from Northeast China.

Liying Cui, Shaoping Li, Hengshuo Zhang

Abstract read
In one paragraph

Article in PloS one, 2025. 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

3 authors.

Liying CuiSchool of Economics and Management, Northeastern Petroleum University, Daqing, China.ORCID 0009-0004-3725-1871
Shaoping LiSchool of Economics and Management, Northeastern Petroleum University, Daqing, China.
Hengshuo ZhangSchool of Economics and Management, Northeastern Petroleum University, Daqing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Energy and water are interlinked and inseparable resources of vital importance to the survival and development of human society. Exploring the relationship between energy and water is of great practical significance for the sustainable development of resources. The uneven regional distribution of energy and water in China has exacerbated energy-related water shortages. Base on the water footprint of energy (WFE), this paper takes Northeast China, the old industrial base, as the research object, and explores the regional distribution characteristics and development trend of WFE, so as to provide quantitative basis for the development of regional energy transformation in coordination with energy and water. This study uses the ISO model and the decoupling model, and analyzes the spatial and temporal changes in the water footprint (WF) of energies and the decoupling effects in Northeast China from the perspective of energy production. The findings show: (1) the WFE grew slowly, and the WF of power gradually exceeded that of fossil energy; (2) the spatial distribution of WFE was unbalanced, with higher WF of fossil energy in Heilongjiang and higher WF of power in Jilin and Liaoning; (3) the decoupling status of WFE from GDP was better than that of WFE from total water consumption. This study also analyzes the driving factors of indicators of water endowment, economic development, energy consumption, environmental governance and life quality, on the WFE based on the Lasso model, and provide policy implications for the coordinated development of energy and water in Northeast China.

Indexed as

WaterWater SupplyChinaHumansModels, TheoreticalSustainable DevelopmentWater

Identifiers

PMID39808683
PMCPMC11731739

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.