Enhancing Methane Source Attribution through Co-Assimilation of Ethane Observations in Atmospheric Inversion Methods

Estimating methane emissions using atmospheric inversion methods that assimilate only methane observations presents challenges in accurately attributing methane sources and sinks to specific emission sectors. We explore the potential of co-assimilating observations of co-emitted species alongside methane observations to address this challenge and provide improved sectoral distribution of methane emissions. Ethane is a promising candidate for this purpose. It is primarily co-emitted with methane in the fossil fuel emission sector, particularly through fugitive emissions from natural gas extraction, and is also co-emitted in the biomass and biofuel burning emission sectors, with negligible emissions in other sectors. To assess the potential of co-assimilating ethane observations with methane observations, we use a global chemistry-transport model, LMDZ-SACS, with the Community Inversion Framework (CIF) to perform response functions analysis on methane and ethane emissions over a multi-year period. We utilize the response functions results to meaningfully construct full source-receptor relationship matrices at available observation site, as well as, error covariance matrices for a control vector that includes both species emissions and initial conditions, and perform a large set of analytical inversions that assimilate in-situ and flask observations of both methane and ethane, as well as methane-only observations. This methodology can not only provide improved estimates of the sectoral distribution of methane sources and sinks, but also extends the scope of the analysis to include ethane emissions.