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A global methane observation system to track climate feedbacks for verifiable climate impact.

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Title: A global methane observation system to track climate feedbacks for verifiable climate impact.
Authors: Watts, Jennifer D. (AUTHOR), Ordway, Elsa (AUTHOR), Malone, Sparkle L. (AUTHOR), Zhu, Qing (AUTHOR), Palmer, Paul I. (AUTHOR), Patel-Tupper, Dhruv (AUTHOR), Ciais, Philippe (AUTHOR), Li, Fa (AUTHOR), Monteverde, Danielle R. (AUTHOR), Arndt, Kyle A. (AUTHOR), Bruhwiler, Lori (AUTHOR), Buma, Brian (AUTHOR), Cadillo-Quiroz, Hinsby (AUTHOR), Euskirchen, Eugenie (AUTHOR), Hoyt, Alison M. (AUTHOR), Holgerson, Meredith (AUTHOR), Hugelius, Gustaf (AUTHOR), Jackson, Robert B. (AUTHOR), Jacob, Daniel (AUTHOR), Kuhn, McKenzie (AUTHOR)
Source: Science. 3/26/2026, Vol. 391 Issue 6792, p1324-1327. 4p.
Subjects: Atmospheric methane, Climate feedbacks, Greenhouse gas mitigation
Abstract: Methane's outsized but short-lived contributions to atmospheric warming have positioned methane mitigation as a cornerstone of actionable, near-term global climate strategy. Yet, cutting anthropogenic methane emissions alone (i.e., from fossil fuels, livestock, rice cultivation, and waste management) will likely not avoid the worst climate outcomes. Natural methane sources, including those sensitive to climate-driven warming (i.e., from wetland and inland waters), account for over one-third of global methane emissions [see supplementary materials (SM) and table S1], making them a substantial component of the global methane budget, critical for understanding and constraining atmospheric methane growth (1–5). Natural sources, however, have been largely ignored over the past few decades in global methane emission reduction initiatives and efforts to strengthen methane source detection to guide mitigation planning. To inform any extension of the Global Methane Pledge (GMP) and other global initiatives, we propose an integrated Global Ecosystem Methane–Observation System (GEM-OS). [ABSTRACT FROM AUTHOR]
Copyright of Science is the property of American Association for the Advancement of Science and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Psychology and Behavioral Sciences Collection
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  Data: A global methane observation system to track climate feedbacks for verifiable climate impact.
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  Data: <searchLink fieldCode="JN" term="%22Science%22">Science</searchLink>. 3/26/2026, Vol. 391 Issue 6792, p1324-1327. 4p.
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  Data: Methane's outsized but short-lived contributions to atmospheric warming have positioned methane mitigation as a cornerstone of actionable, near-term global climate strategy. Yet, cutting anthropogenic methane emissions alone (i.e., from fossil fuels, livestock, rice cultivation, and waste management) will likely not avoid the worst climate outcomes. Natural methane sources, including those sensitive to climate-driven warming (i.e., from wetland and inland waters), account for over one-third of global methane emissions [see supplementary materials (SM) and table S1], making them a substantial component of the global methane budget, critical for understanding and constraining atmospheric methane growth (1–5). Natural sources, however, have been largely ignored over the past few decades in global methane emission reduction initiatives and efforts to strengthen methane source detection to guide mitigation planning. To inform any extension of the Global Methane Pledge (GMP) and other global initiatives, we propose an integrated Global Ecosystem Methane–Observation System (GEM-OS). [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Science is the property of American Association for the Advancement of Science and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=pbh&AN=192562581
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