Estimating emissions of methane consistent with atmospheric measurements of methane and <italic>δ</italic><sup>13</sup>C of methane
Abstract δ 13 C of methane in order to estimate source-specific methane emissions. Here we present global emission estimates from this framework for the period 1999–2016. We assimilate a newly constructed, multi-agency database of CH 4 δ 13 C measurements. We find that traditional CH 4 δ 13 C data, and assimilating δ 13 C data is necessary to derive emissions consistent with both measurements. Our framework attributes ca. 85 % of the post-2007 growth in atmospheric methane to microbial sources, with about half of that coming from the tropics between 23.5∘ N and 23.5∘ S. This contradicts the attribution of the recent growth in the methane budget of the Global Carbon Project (GCP). We find that the GCP attribution is only consistent with our top-down estimate in the absence of δ 13 C data. We find that at global and continental scales, δ 13 C data can separate microbial from fossil methane emissions much better than CH 4 δ 13 C measurement coverage. Finally, we find that the largest uncertainty in using δ 13 C data to separate different methane source types comes from our knowledge of atmospheric chemistry, specifically the distribution of tropospheric chlorine and the isotopic discrimination of the methane sink.
- Location
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Deutsche Nationalbibliothek Frankfurt am Main
- Extent
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Online-Ressource
- Language
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Englisch
- Bibliographic citation
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Estimating emissions of methane consistent with atmospheric measurements of methane and
δ 13C of methane ; volume:22 ; number:23 ; year:2022 ; pages:15351-15377 ; extent:27
Atmospheric chemistry and physics ; 22, Heft 23 (2022), 15351-15377 (gesamt 27)
- Creator
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Basu, Sourish
Lan, Xin
Dlugokencky, Edward
Michel, Sylvia
Schwietzke, Stefan
Miller, John B.
Bruhwiler, Lori
Oh, Youmi
Tans, Pieter P.
Apadula, Francesco
Gatti, Luciana V.
Jordan, Armin
Necki, Jaroslaw
Sasakawa, Motoki
Morimoto, Shinji
Di Iorio, Tatiana
Lee, Haeyoung
Arduini, Jgor
Manca, Giovanni
- DOI
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10.5194/acp-22-15351-2022
- URN
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urn:nbn:de:101:1-2022120804260510758033
- Rights
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Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Last update
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15.08.2025, 7:20 AM CEST
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Associated
- Basu, Sourish
- Lan, Xin
- Dlugokencky, Edward
- Michel, Sylvia
- Schwietzke, Stefan
- Miller, John B.
- Bruhwiler, Lori
- Oh, Youmi
- Tans, Pieter P.
- Apadula, Francesco
- Gatti, Luciana V.
- Jordan, Armin
- Necki, Jaroslaw
- Sasakawa, Motoki
- Morimoto, Shinji
- Di Iorio, Tatiana
- Lee, Haeyoung
- Arduini, Jgor
- Manca, Giovanni
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