Evidence map›Paper›PMID 42566330›Full record

ArticleEnvironmental science & technology2026

City-Scale, Source-Resolved Methane Inventories Reveal Drivers and Mitigation Pathways Across China's Cities.

Li Zhang, Yifan Chen, Ke Wang, Jing Guo, Sen Liang, Pengcheng Wu, Haoyu Zhang, Jingyi Wu, Ying Cui, Chen Lyu and 5 more

Abstract read
In one paragraph

Article in Environmental science & technology, 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

15 authors.

Li ZhangSchool of the Environment and Safety Engineering, Jiangsu University, Zhenjiang212013, China.ORCID 0000-0003-1145-3569
Yifan ChenDepartment of Data Science, City University of Hong Kong, Hong Kong SAR999077, China.ORCID 0000-0001-8507-4743
Ke WangSchool of Land Science and Technology, China University of Geosciences, Beijing100083, China.
Jing GuoCenter for Carbon Neutrality, Chinese Academy of Environmental Planning, Beijing100043, China.
Sen LiangChinese Academy of Natural Resources Economics , Sanhe City101149, China.
Pengcheng WuSchool of Public Health, Sun Yat-sen University, Guangzhou, Guangdong510080, China.
Haoyu ZhangState Grid Shaanxi Electric Power Company Limited Research Institute, Xi'an710065, China.
Jingyi WuSchool of Environmental Science and Engineering, Shanghai Jiao Tong University, Shanghai Engineering Research Center of Solid Waste Treatment and Resource, Shanghai200240, China.
Ying CuiSchool of Environmental and Chemical Engineering, Shanghai University of Electric Power, Shanghai200090, China.
Chen LyuCenter for Carbon Neutrality, Chinese Academy of Environmental Planning, Beijing100043, China.
Hui XuJiangxi Provincial Key Laboratory of Greenhouse Gas Accounting and Carbon Reduction, Institute of Energy Research, Jiangxi Academy of Sciences, Nanchang330096, China.
Qunwei WangCollege of Economics and Management, Nanjing University of Aeronautics and Astronautics, Nanjing211106, China.
Bofeng CaiCenter for Carbon Neutrality, Chinese Academy of Environmental Planning, Beijing100043, China.
Jinnan WangCenter for Carbon Neutrality, Chinese Academy of Environmental Planning, Beijing100043, China.
Linyan LiDepartment of Data Science, City University of Hong Kong, Hong Kong SAR999077, China.ORCID 0000-0001-5736-2115

Funding

Jiangsu University JDKQ20251106National Natural Science Foundation of China (NSFC) 52270183National Natural Science Foundation of China (NSFC) 72140004National Natural Science Foundation of China (NSFC) 72504111National Social Science Fund of China 24VRC099Research Grants Council, University Grants Committee C6003-22Y
6 · The paper itself

Abstract

City-scale, source-resolved methane (CH4) inventories are needed in China because prefecture-level cities differ in energy systems, agricultural activities, and waste management. These differences lead to divergent dominant sources and mitigation needs. Yet city-level CH4 inventories across the energy, agriculture, and waste sectors remain scarce. This scarcity limits policy design, targeting, and evaluation. Here we develop a harmonized, annually consistent, multisector, source-resolved CH4 inventory for 339 prefecture-level cities in China during 2018-2024. We further use Logarithmic Mean Divisia Index (LMDI) driver attribution and scenario analysis to examine recent emission drivers and explore possible mitigation pathways. Over this period, national anthropogenic CH4 emissions increased by 2.61%, with regional heterogeneity shaped by differences in energy dependence, livestock management, and waste treatment. LMDI decomposition identifies economic activity as the dominant positive driver. Emission-intensity effects alternated between mitigating and reinforcing impacts, while structural effects were minor and population effects varied across space and time. Scenario simulations suggest that integrated multisector strategies could reduce national CH4 from 61.69 Mt in 2024-51.26 Mt in 2030 and 22.26 Mt in 2060, corresponding to a 63.9% reduction. These reductions are primarily driven by energy-sector measures, complemented by improvements in agriculture and waste management. This data set and attribution inform city-specific mitigation planning and source targeting, support monitoring, reporting, and verification, and provide a baseline for benchmarking progress toward national methane targets.

Indexed as

MethaneAir PollutantsChinaCitiesEnvironmental MonitoringAir PollutantsMethanecity-level inventoryLMDI decompositionmethane emissionsmultisector mitigation pathwayssource-resolved emissions

Identifiers

PMID42566330
PMCPMC13492280

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LicenceCC BY
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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.