Evidence map›Paper›PMID 40473639›Full record

ArticleScientific data2025

Monthly methane emissions in Chinese mainland provinces from 2013-2022.

Duo Cui, Siyao Yang, Xuanren Song, Xiaoting Huang, Cuncun Duan, Mingrui Ji, Zhongyan Li, Siqi Yu, Zhu Deng, Piyu Ke and 3 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Scientific data, 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

13 authors.

Duo CuiInternational Research Center of Big Data for Sustainable Development Goals, Beijing, 100094, China. duocui@hku.hk.ORCID http://orcid.org/0000-0002-1736-5052
Siyao YangDepartment of Earth System Science, Tsinghua University, Beijing, 100084, China.
Xuanren SongFaculty of Information Technology, Monash University, Melbourne, 3168, Australia.
Xiaoting HuangDepartment of Earth System Science, Tsinghua University, Beijing, 100084, China.ORCID http://orcid.org/0000-0002-5668-4320
Cuncun DuanCollege of Water Sciences, Beijing Normal University, Beijing, 100875, China.
Mingrui JiCollege of Environmental & Resource Sciences, Zhejiang University, Hangzhou, Zhejiang, 310058, China.
Zhongyan LiDepartment of Civil and Environmental Engineering, Stanford University, Stanford, CA, 94305, USA.
Siqi YuDepartment of Earth System Science, Tsinghua University, Beijing, 100084, China.
Zhu DengDepartment of Geography, The University of Hong Kong, Hong Kong SAR, China.ORCID http://orcid.org/0000-0002-6409-9578
Piyu KeDepartment of Earth System Science, Tsinghua University, Beijing, 100084, China.
Xinyu DouDepartment of Earth System Science, Stanford University, Stanford, CA, 94305, USA.
Taochun SunDepartment of Earth System Science, Tsinghua University, Beijing, 100084, China.ORCID http://orcid.org/0000-0003-3640-6005
Zhu LiuInternational Research Center of Big Data for Sustainable Development Goals, Beijing, 100094, China. zhuliu@tsinghua.edu.cn.ORCID http://orcid.org/0000-0002-8968-7050

Funding

National Natural Science Foundation of China (National Science Foundation of China) 72394402
6 · The paper itself

Abstract

As the world's largest source of methane emissions, accurately measuring and tracking China's emissions across various sectors is essential for global climate change efforts. Methane, a potent greenhouse gas, is emitted from diverse anthropogenic and natural sources, many of which exhibit pronounced temporal variability. In particular, emissions from rice cultivation, energy use, and livestock management show strong seasonal patterns, yet high-frequency and spatially detailed methane emission inventories have been lacking. This study introduces the Monthly Methane Emission Inventory for China's Provinces (MMCP), a comprehensive dataset covering the period from January 2013 to December 2022. The dataset includes emissions data from eight key sectors: coal mining, oil and gas systems, energy combustion, rice cultivation, livestock, solid waste, wastewater, and wetlands. By offering sector-specific and temporally resolved emission estimates, MMCP serves as a valuable resource for scientific research, policy evaluation, and emission mitigation planning. This inventory facilitates improved understanding of emission trends and supports more accurate modeling of atmospheric methane concentrations and climate feedbacks.

Identifiers

PMID40473639
PMCPMC12141455

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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.