Evidence map›Paper›PMID 41872269›Full record

ArticleScientific reports2026

The mechanisms and spatiotemporal patterns of the digital economy's effect on China's pollution reduction and carbon efficiency.

Boda Xin, Shuliang Ren, Lianhong Lv, Mengyu Xiang, Jingjing Dong

Abstract read
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
–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

5 authors.

Boda Xin *Chinese Research Academy of Environmental Sciences, Beijing, 100012, China.
Shuliang Ren *Institute of Remote Sensing and Geographical Information Systems, School of Earth and Space Sciences, Peking University, Beijing, 100871, China.
Lianhong LvChinese Research Academy of Environmental Sciences, Beijing, 100012, China. lvlianhong@126.com.
Mengyu XiangChinese Research Academy of Environmental Sciences, Beijing, 100012, China.
Jingjing DongChinese Research Academy of Environmental Sciences, Beijing, 100012, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The digital economy has emerged as a pivotal driver of China’s green and low-carbon transformation; however, its specific transmission mechanisms and spatiotemporal heterogeneity regarding environmental effects remain insufficiently explored. Utilizing panel data from 30 Chinese provinces (2011–2020), this study employs mediation analysis and Geographically and Temporally Weighted Regression (GTWR) to estimate the impact of the digital economy on pollution and carbon emissions. The results indicate that: (1) The expansion of the digital economy significantly mitigates environmental pressures, reducing pollutant and carbon emission intensities by 0.247 and 0.258 units per unit of growth, respectively. (2) Transmission mechanism analysis reveals that technological innovation is the primary channel, mediating 40.01% of the total effect, significantly outweighing the contribution of industrial structure optimization (16.85%). (3) The effects are spatially heterogeneous, with stronger pollution reductions in northeastern and eastern provinces and larger carbon-intensity reductions in western provinces. (4) The synergistic effects strengthened from 2016 to 2020. The earlier spatial misalignment between pollution control and carbon mitigation was effectively eliminated.

Indexed as

Carbon emission reductionDigital economyMediation effectPollution reduction

Identifiers

PMID41872269
PMCPMC13153165

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.