Evidence map›Paper›PMID 38192782›Full record

ArticleHeliyon2024

Spatial difference analysis and dynamic evolution prediction of urban industrial integrated water use efficiency in China.

Zhao Jingfeng, Sun Fan, Li Yan

Open access · goldAbstract read
In one paragraph

Article in Heliyon, 2024. 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
1.4field-weighted citation impact, top 19% of its field
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, 9 citations in OpenAlex.

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 at 2 institutions in 1 country.

Zhao JingfengSchool of Management and Economics, North China University of Water Resources and Electric Power, Zhengzhou, 450046, Henan Province, China.
Sun FanSchool of Management and Economics, North China University of Water Resources and Electric Power, Zhengzhou, 450046, Henan Province, China.
Li YanSchool of Business Administration, Henan University of Economics and Law, Zhengzhou, 450046, Henan Province, China.
North China University of Water Resources and Electric Power · CNHenan University of Economic and Law · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Comprehensive quantitative assessment of China's urban industrial water use efficiency is effectively promote the green industrial development important steps in order to realize the overall development of high quality. Between 2009 and 2021, 290 in China based on ground level above the panel data of the city, this paper conducts research based on two principles of efficiency improvement and four models of efficiency analysis. The results show that: First, from the perspective of spatial differences, the integrated water use efficiency of urban industry in China presents a slow and uneven upward trend of "low in the east and high in the west, high in the middle and low in the north and south". Second, from the perspective of driving factors, population density and government public investment on the whole inhibit the development of this efficiency, while GDP development and technological innovation promote it. Third, from the perspective of dynamic evolution prediction, the phenomenon of "beggar-thy-neighbor" and "neighborly kindness" coexist. Therefore, the government should implement industrial water-saving measures according to local conditions, the society should improve the supervision of the behavior of wasting industrial water, and the enterprises should speed up the integration process of industrial primary and repeat water efficiency, so as to promote the comprehensive green transformation of the economy and society.

Indexed as

Driving factorsDynamic evolution predictionGreen developmentIndustrial comprehensive water use efficiencySpatial difference

Identifiers

PMID38192782
PMCPMC10772170
OpenAlexW4389856692

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.