Evidence map›Paper›PMID 41882310›Full record

ArticleScientific reports2026

The spatiotemporal effects of electrification on China's synergistic pollution and carbon reduction efficiency.

Wenhui Chen, Ziwen Ruan, Zhenquan Shao, Chuangwang Liu, Tongrong Fu, Qing Mu

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Scientific reports, 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
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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

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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

6 authors.

Wenhui ChenSchool of Economics and Management, Beijing University of Chemical Technology, Beijing, 100029, P. R. China. chenwenhui@buct.edu.cn.
Ziwen RuanCenter for Carbon Neutrality, Chinese Academy of Environmental Planning, Beijing, 100041, China.
Zhenquan ShaoSchool of Economics and Management, China University of Geosciences, Beijing, 100083, China.
Chuangwang LiuSchool of Economics and Management, China University of Geosciences, Beijing, 100083, China. liuchuanwang111@cugb.edu.cn.
Tongrong FuSchool of Economics and Management, Beijing University of Chemical Technology, Beijing, 100029, P. R. China.
Qing MuTsinghua University Carbon Neutrality Research Institute, Tsinghua University, Beijing, 100084, China.

Funding

Ministry of Education Post-Funding Project for Philosophy and Social Sciences Research 24JHQ071the National Natural Science Foundation of China 72104116
6 · The paper itself

Abstract

China’s dual objectives of “Beautiful China” and “Carbon Neutrality” necessitate a synergistic approach to reducing air pollution and carbon emissions. Analyzing the spatiotemporal dynamics of the Efficiency of Synergistic Air Pollution and Carbon Emissions Reduction (ESACR) and its influencing factors, particularly electrification, is critical for enhancing this synergy. This study utilizes provincial-level data from 2000 to 2021, employing the super-efficiency Slack-Based model to measure China’s ESACR. It then integrates Exploratory Spatial Data Analysis, Spatial Econometric Models, and Geographically and Temporally Weighted Regression (GTWR) models to uncover the spatiotemporal evolution of ESACR and dissect the influence of electrification. The results show that the overall ESACR remains relatively low, indicating substantial room for improvement, with a pronounced decreasing trend from East to West. Meanwhile, the positive effect of electrification on ESACR demonstrates significant spatial heterogeneity, being most effective in coastal and certain western provinces. Therefore, effectively unlocking China’s synergistic pollution and carbon reduction potential requires a multi-tiered policy framework that implements differentiated regional electrification strategies, fosters cross-regional system coordination, and integrates electrification with complementary policies on energy efficiency and industrial structure.

Indexed as

Driving factorsElectrification rateGTWR modelSpatio-temporal heterogeneitySynergistic pollution control and carbon reduction

Identifiers

PMID41882310
PMCPMC13172416

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