Evidence map›Paper›PMID 35297408›Full record

ArticleNature communications2022

Tropical methane emissions explain large fraction of recent changes in global atmospheric methane growth rate.

Liang Feng, Paul I Palmer, Sihong Zhu, Robert J Parker, Yi Liu

Abstract read
In one paragraph

Article in Nature communications, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing 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

16 citing papers in PubMed.

  1. Strategic restoration of global inland peatlands can maximize local and global co-benefits.Ecological applications : a publication of the Ecological Society of America · 2026
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  5. Microbial driver of 2006-2023 CHProceedings of the National Academy of Sciences of the United States of America · 2025
    Article
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  12. Inverse modeling of 2010-2022 satellite observations shows that inundation of the wet tropics drove the 2020-2022 methane surge.Proceedings of the National Academy of Sciences of the United States of America · 2024
    Article
  13. Review
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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.

Liang FengNational Centre for Earth Observation, University of Edinburgh, Edinburgh, UK.
Paul I PalmerNational Centre for Earth Observation, University of Edinburgh, Edinburgh, UK. paul.palmer@ed.ac.uk.ORCID 0000-0002-1487-0969
Sihong ZhuSchool of GeoSciences, University of Edinburgh, Edinburgh, UK.
Robert J ParkerNational Centre for Earth Observation, University of Leicester, Leicester, UK.ORCID 0000-0002-0801-0831
Yi LiuInstitute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Large variations in the growth of atmospheric methane, a prominent greenhouse gas, are driven by a diverse range of anthropogenic and natural emissions and by loss from oxidation by the hydroxyl radical. We used a decade-long dataset (2010-2019) of satellite observations of methane to show that tropical terrestrial emissions explain more than 80% of the observed changes in the global atmospheric methane growth rate over this period. Using correlative meteorological analyses, we show strong seasonal correlations (r = 0.6-0.8) between large-scale changes in sea surface temperature over the tropical oceans and regional variations in methane emissions (via changes in rainfall and temperature) over tropical South America and tropical Africa. Existing predictive skill for sea surface temperature variations could therefore be used to help forecast variations in global atmospheric methane.

Indexed as

Greenhouse GasesMethaneAfricaHydroxyl RadicalOceans and SeasGreenhouse GasesHydroxyl RadicalMethane

Identifiers

PMID35297408
PMCPMC8927109

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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.