Evidence map›Paper›PMID 41381589›Full record

ArticleNature communications2025

Worldwide inference of national methane emissions by inversion of satellite observations with UNFCCC prior estimates.

James D East, Daniel J Jacob, Dylan Jervis, Nicholas Balasus, Lucas A Estrada, Sarah E Hancock, Melissa P Sulprizio, John Thomas, Xiaolin Wang, Zichong Chen and 2 more

Abstract read
In one paragraph

Article in Nature communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
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

12 authors.

James D EastSchool of Engineering and Applied Science, Harvard University, Cambridge, MA, USA. jeast@g.harvard.edu.ORCID http://orcid.org/0000-0001-7199-6229
Daniel J JacobSchool of Engineering and Applied Science, Harvard University, Cambridge, MA, USA.ORCID http://orcid.org/0000-0002-6373-3100
Dylan JervisGHGSat, Inc, Montreal, Canada.ORCID http://orcid.org/0009-0009-5387-635X
Nicholas BalasusSchool of Engineering and Applied Science, Harvard University, Cambridge, MA, USA.ORCID http://orcid.org/0009-0003-4825-8414
Lucas A EstradaSchool of Engineering and Applied Science, Harvard University, Cambridge, MA, USA.ORCID http://orcid.org/0000-0002-7823-147X
Sarah E HancockSchool of Engineering and Applied Science, Harvard University, Cambridge, MA, USA.ORCID http://orcid.org/0000-0002-1313-8581
Melissa P SulprizioSchool of Engineering and Applied Science, Harvard University, Cambridge, MA, USA.ORCID http://orcid.org/0000-0003-4641-5546
John ThomasSchool of Engineering and Applied Science, Harvard University, Cambridge, MA, USA.
Xiaolin WangSchool of Engineering and Applied Science, Harvard University, Cambridge, MA, USA.ORCID http://orcid.org/0000-0001-6772-0350
Zichong ChenThrust of Carbon Neutrality and Climate Change, Hong Kong University of Science and Technology, Guangzhou, China.ORCID http://orcid.org/0000-0003-2779-1554
Daniel J VaronDepartment of Aeronautics and Astronautics, Massachusetts Institute of Technology, Cambridge, MA, USA.ORCID http://orcid.org/0000-0002-3207-5731
John R WordenJet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA.ORCID http://orcid.org/0000-0003-0257-9549

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Meeting climate policy goals to reduce methane emissions under the Paris Agreement and the Global Methane Pledge requires nations to set targets and quantify reductions. Individual countries report emissions by sector to the United Nations Framework Convention on Climate Change (UNFCCC) but there are large uncertainties. Here we optimize 2023 national emissions at up to 25 km grid resolution for 161 countries with a globally consistent open-source framework for inverse analysis of Tropospheric Monitoring Instrument (TROPOMI) satellite observations, using UNFCCC reports for prior estimates together with point source information from GHGSat and other satellites. We find global anthropogenic emissions to be 15% higher than UNFCCC reporting (32% for oil-gas), with national emissions more than 50% higher than reporting for a quarter of the countries. Oil-gas emission intensities vary by two orders of magnitude between countries. Sub-Saharan Africa has the highest livestock emission intensity of any region. Hydroelectric reservoirs, generally not included in UNFCCC reporting, contribute 6% of anthropogenic emissions globally. The framework allows updates for subsequent years, enabling monitoring of emission trends and support for improved reporting.

Identifiers

PMID41381589
PMCPMC12698852

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.