Evidence map›Paper›PMID 42225643›Full record

ArticleScientific data2026

China's City-level CO

Boyang Chen, Ming Gao, Yu Liu, Jiafu An, Zhengxian Zhang

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Scientific data, 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.

Boyang Chen *Institute for Climate and Carbon Neutrality, The University of Hong Kong, Hong Kong, Hong Kong SAR, 999077, China.
Ming Gao *School of Public Administration, Southwestern University of Finance and Economics, Chengdu, 611130, China.
Yu LiuCollege of Urban and Environmental Sciences, Peking University, Beijing, 100871, China. Yu.liu@pku.edu.cn.
Jiafu AnInstitute for Climate and Carbon Neutrality, The University of Hong Kong, Hong Kong, Hong Kong SAR, 999077, China. Jiafuan@hku.hk.
Zhengxian ZhangCollege of Urban and Environmental Sciences, Peking University, Beijing, 100871, China.

Funding

National Natural Science Foundation of China 71974186National Science Fund for Distinguished Young Scholars 72125010
6 · The paper itself

Abstract

The power sector is a major contributor to global energy use and greenhouse gas emissions. In 2020, China's power sector accounted for over 40% of national carbon emissions, underscoring the importance of its decarbonization for achieving global climate targets. Effective emission-reduction policies require detailed and reliable carbon data. Given China's "top-down" target-setting system, accurate regional data are essential for designing differentiated local policies and evaluating their effectiveness. In this study, we systematically estimate CO

Identifiers

PMID42225643
PMCPMC13226690

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.