We have constructed an atmospheric inversion framework based on TM5-4DVAR to jointly assimi- late 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 con- structed, multi-agency database of CH4 and δ13C measurements. We find that traditional CH4-only atmospheric inversions are unlikely to estimate emissions consistent with atmospheric δ13C data, and assimilating δ13C 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 δ13C data. We find that at global and continental scales, δ13C 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 δ13C measurement coverage. Finally, we find that the largest uncertainty in using δ13C 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.

Estimating emissions of methane consistent with atmospheric measurements of methane and δ13C of methane

Arduini, Jgor;
2022

Abstract

We have constructed an atmospheric inversion framework based on TM5-4DVAR to jointly assimi- late 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 con- structed, multi-agency database of CH4 and δ13C measurements. We find that traditional CH4-only atmospheric inversions are unlikely to estimate emissions consistent with atmospheric δ13C data, and assimilating δ13C 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 δ13C data. We find that at global and continental scales, δ13C 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 δ13C measurement coverage. Finally, we find that the largest uncertainty in using δ13C 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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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11576/2711212
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