05 Jul 2022
05 Jul 2022
Status: this preprint is currently under review for the journal ACP.

Estimating Emissions of Methane Consistent with Atmospheric Measurements of Methane and δ13C of Methane

Sourish Basu1,2, Xin Lan3,4, Edward Dlugokencky4, Sylvia Michel5, Stefan Schwietzke6, John Bharat Miller4, Lori Bruhwiler4, Youmi Oh4, Pieter P. Tans4, Francesco Apadula7, Luciana Vanni Gatti8, Armin Jordan9, Jaroslaw Necki10, Motoki Sasakawa11, Shinji Morimoto12, Tatiana Di Iorio13, Haeyoung Lee14, Jgor Arduini15, and Giovanni Manca16 Sourish Basu et al.
  • 1Global Modeling and Assimilation Office, NASA Goddard Space Flight Center, Greenbelt MD
  • 2Earth System Science Interdisciplinary Center, University of Maryland, College Park MD
  • 3Cooperative Institute for Research in Environmental Science, University of Colorado, Boulder CO
  • 4Global Monitoring Laboratory, National Oceanic and Atmospheric Administration, Boulder CO
  • 5Institute for Arctic and Alpine Research, University of Colorado, Boulder CO
  • 6Environmental Defense Fund, Berlin, Germany
  • 7Ricerca sul Sistema Energetico (RSE S.p.A.), Milano, Italy
  • 8Instituto Nacional de Pesquisas Espaciais, São José dos Campos, São Paulo, Brazil
  • 9Max Planck Institute for Biogeochemistry, Jena, Germany
  • 10AGH University of Science and Technology, Krakow, Poland
  • 11National Institute for Environmental Studies, Tsukuba-shi, Ibaraki, Japan
  • 12Center for Atmospheric and Oceanic Studies, Tohoku University, Sendai, Japan
  • 13Italian National Agency for New Technologies, Energy, and Sustainable Economic Devlopment (ENEA), Rome, Italy
  • 14National Institute of Meteorological Sciences, Seogwipo-si, Jeju-do, Korea
  • 15Università degli Studi di Urbino, Urbino, Italy
  • 16European Commission, Joint Research Center, Ispra, Italy

Abstract. We have constructed an atmospheric inversion framework based on TM5 4DVAR to jointly assimilate measurements of methane and δ13C 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 CH4 and δ13CH4 measurements. We find that traditional CH4-only atmospheric inversions are unlikely to estimate emissions consistent with atmospheric δ13CH4 data, and assimilating δ13CH4 data is necessary to deriving 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 δ13CH4 data. We find that at global and continental scales, δ13CH4 data can separate microbial from fossil methane emissions much better than CH4 data alone can, and at smaller scales this ability is limited by the current δ13CH4 measurement coverage. Finally, we find that the largest uncertainty in using δ13CH4 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.

Sourish Basu et al.

Status: open (until 16 Aug 2022)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on acp-2022-317', Anonymous Referee #2, 19 Jul 2022 reply
  • RC2: 'Comment on acp-2022-317', Martin Manning, 21 Jul 2022 reply

Sourish Basu et al.

Model code and software

TM5 4DVAR atmospheric inverse model Sourish Basu, Arjo Segers, and other TM5 model developers

Sourish Basu et al.


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Short summary
Top-down models try to estimate methane emissions from atmospheric methane measurements. The ability of such models to distinguish between emissions from different sources such as fossil fuels and wetlands is limited. However, different sources emit methane with different C13 : C12 ratios. We have used atmospheric measurements of this ratio to derive source-specific emissions. We posit that the majority of the post-2007 increase in atmospheric methane is driven by microbial and not fossil sources.