TY - JOUR
T1 - Estimating emissions of methane consistent with atmospheric measurements of methane and δ13C of methane
AU - Basu, Sourish
AU - Lan, Xin
AU - Dlugokencky, Edward
AU - Michel, Sylvia
AU - Schwietzke, Stefan
AU - Miller, John B.
AU - Bruhwiler, Lori
AU - Oh, Youmi
AU - Tans, Pieter P.
AU - Apadula, Francesco
AU - Gatti, Luciana V.
AU - Jordan, Armin
AU - Necki, Jaroslaw
AU - Sasakawa, Motoki
AU - Morimoto, Shinji
AU - Di Iorio, Tatiana
AU - Lee, Haeyoung
AU - Arduini, Jgor
AU - Manca, Giovanni
N1 - Funding Information:
This research has been supported by the National Aeronautics and Space Administration (grant no. NNX17AK20G) and the National Oceanic and Atmospheric Administration (grant no. NA17OAR4320101).
Funding Information:
This work was supported by funding from the National Aeronautics and Space Administration (NASA) (grant no. NNX17AK20G). All computing work was performed on either NASA's Discover supercomputer at the NASA Center for Climate Simulation (NCCS) or NOAA's Orion supercomputer maintained by Mississippi State University. Sourish Basu was additionally supported by NASA's Modeling, Analysis, and Prediction Program as well as the Carbon Monitoring System Program. Sourish Basu was supported in part by cooperative agreement NA17OAR4320101 between NOAA and the University of Colorado at Boulder. Sourish Basu and Youmi Oh were supported in part by the NOAA National Environmental Satellite, Data, and Information Service (NESDIS). In addition to the co-authors who provided atmospheric and measurements, the authors acknowledge the work of the following people: (i) Ove Hermansen, Cathrine Lund Myhre, and Stephen Platt of the Norwegian Institute for Air Research (NILU) in collecting air samples at the Zeppelin Observatory through the Norwegian Environment Agency (grant no. 21087006), ICOS Norway – Research Council of Norway (grant no. 296012), and ReGAME – Research Council of Norway (grant no. 325610); (ii) Heiko Moosen and Willi A. Brand of the Max Planck Institute for Biogeochemistry – funded by the Max Planck Society; (iii) Doug Worthy of Environment Climate Change Canada; (iv) Casper Labuschagne of the South African Weather Service; (v) László Haszpra of the Hungarian Meteorological Service; (vi) Yosuke Niwa and Taku Umezawa of the National Institute for Environmental Studies, Japan; (vii) Kirk Thoning (NOAA) for collating all measurements into a common format for model use; (viii) Shinya Takatsuji of the Japan Meteorological Agency for measurements at Ryori, Yonagunijima, and Minamitorishima, as well as from JMA's “Aircraft Observation of Atmospheric trace gases” program; (ix) Arlyn Andrews, Bianca Baier, Molly Crotwell, Philip Handley, Jack Higgs, Jon Kofler, Pat Lang, Thomas Legard, Kathryn McKain, Eric Moglia, Don Neff, Tim Newberger, Colm Sweeney, and Sonja Wolter for support of the NOAA GGGRN tower and aircraft programs; (x) Nina Paramonova of the Voeikov Main Geophysical Observatory, Russia; (xi) Dagmar Kubistin of the Deutscher Wetterdienst (DWD); (xii) Karin Uhse and Ludwig Ries of the Umwelt Bundesamt, Germany; (xiii) Juha Hatakka of the Finnish Meterological Institute; (xiv) Emilio Cuevas of the Meteorological State Agency of Spain (AEMET); (xv) Alex Vermeulen of Lund University; and (xvi) John Moncrieff of the University of Edinburgh. The authors also acknowledge atmospheric data provided by the National Institute of Water and Atmospheric Research (NIWA) of New Zealand, the Commonwealth Scientific and Industrial Research Organisation (CSIRO) of Australia, Laboratoire des Sciences du Climat et de l'Environnement (LSCE) of France, and the Swiss Federal Laboratories for Materials Science and Technology (EMPA). We also thank Martin Steinbacher (EMPA) for comments on the paper. NIWA measurements at Arrival Heights and Baring Head were supported by internal funding under Climate and Atmosphere Research Programme CAAC2204 (2021/22 SCI). EMPA measurements at Jungfraujoch were supported by the Swiss National Air Pollution Monitoring Network, the Federal Office for the Environment, and ICOS Switzerland (Swiss National Science Foundation, grant no. 20FI21_148992). RSE's contribution to this work has been financed by the Research Fund for the Italian Electrical System under the contract agreement between RSE S.p.A. and the Ministry of Economic Development – General Directorate for the Electricity Market, Renewable Energy and Energy Efficiency, Nuclear Energy, in compliance with the decree of 16 April 2018.
Publisher Copyright:
© Copyright:
PY - 2022/12/5
Y1 - 2022/12/5
N2 - We have constructed an atmospheric inversion framework based on TM5-4DVAR to jointly assimilate measurements of methane and 13C 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 13C measurements. We find that traditional CH4-only atmospheric inversions are unlikely to estimate emissions consistent with atmospheric 13C data, and assimilating 13C data is necessary to derive emissions consistent with both measurements. Our framework attributes ca. 85g% of the post-2007 growth in atmospheric methane to microbial sources, with about half of that coming from the tropics between 23.5ggN and 23.5ggS. 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 13C data. We find that at global and continental scales, 13C data can separate microbial from fossil methane emissions much better than CH4 data alone, and at smaller scales this ability is limited by the current 13C measurement coverage. Finally, we find that the largest uncertainty in using 13C 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.
AB - We have constructed an atmospheric inversion framework based on TM5-4DVAR to jointly assimilate measurements of methane and 13C 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 13C measurements. We find that traditional CH4-only atmospheric inversions are unlikely to estimate emissions consistent with atmospheric 13C data, and assimilating 13C data is necessary to derive emissions consistent with both measurements. Our framework attributes ca. 85g% of the post-2007 growth in atmospheric methane to microbial sources, with about half of that coming from the tropics between 23.5ggN and 23.5ggS. 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 13C data. We find that at global and continental scales, 13C data can separate microbial from fossil methane emissions much better than CH4 data alone, and at smaller scales this ability is limited by the current 13C measurement coverage. Finally, we find that the largest uncertainty in using 13C 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.
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U2 - 10.5194/acp-22-15351-2022
DO - 10.5194/acp-22-15351-2022
M3 - Article
AN - SCOPUS:85144357465
SN - 1680-7316
VL - 22
SP - 15351
EP - 15377
JO - Atmospheric Chemistry and Physics
JF - Atmospheric Chemistry and Physics
IS - 23
ER -