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  4. 2010–2015 North American methane emissions, sectoral contributions, and trends: a high-resolution inversion of GOSAT observations of atmospheric methane

2010–2015 North American methane emissions, sectoral contributions, and trends: a high-resolution inversion of GOSAT observations of atmospheric methane

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Author(s)
Maasakkers, Joannes D
•
Jacob, Daniel J
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Sulprizio, Melissa P
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Scarpelli, Tia R
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Nesser, Hannah
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Sheng, Jianxiong
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Zhang, Yuzhong
•
Lu, Xiao
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Bloom, A Anthony
•
Bowman, Kevin W
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Date Issued
March 22, 2021
Journal
Atmospheric Chemistry and Physics
Publisher
Copernicus GmbH
Citation
Maasakkers, J. D., Jacob, D. J., Sulprizio, M. P., Scarpelli, T. R., Nesser, H., Sheng, J., Zhang, Y., Lu, X., Bloom, A. A., Bowman, K. W., Worden, J. R., and Parker, R. J.: 2010–2015 North American methane emissions, sectoral contributions, and trends: a high-resolution inversion of GOSAT observations of atmospheric methane, Atmos. Chem. Phys., 21, 4339–4356
Version
Final published version
Abstract
We use 2010–2015 Greenhouse Gases Observing Satellite (GOSAT) observations of atmospheric methane columns over North America in a high-resolution inversion of methane emissions, including contributions from different sectors and their trends over the period. The inversion involves an analytical solution to the Bayesian optimization problem for a Gaussian mixture model (GMM) of the emission field with up to 0.5 ◦ ×0.625◦ resolution in concentrated source regions. The analytical solution provides a closedform characterization of the information content from the inversion and facilitates the construction of a large ensemble of solutions exploring the effect of different uncertainties and assumptions in the inverse analysis. Prior estimates for the inversion include a gridded version of the Environmental Protection Agency (EPA) Inventory of US Greenhouse Gas Emissions and Sinks (GHGI) and the WetCHARTs model ensemble for wetlands. Our best estimate for mean 2010– 2015 US anthropogenic emissions is 30.6 (range: 29.4– 31.3) Tg a−1 , slightly higher than the gridded EPA inventory (28.7 (26.4–36.2) Tg a−1 ). The main discrepancy is for the oil and gas production sectors, where we find higher emissions than the GHGI by 35 % and 22 %, respectively. The most recent version of the EPA GHGI revises downward its estimate of emissions from oil production, and we find that these are lower than our estimate by a factor of 2. Our best estimate of US wetland emissions is 10.2 (5.6–11.1) Tg a−1 , on the low end of the prior WetCHARTs inventory uncertainty range (14.2 (3.3–32.4) Tg a−1 ), which calls for better understanding of these emissions. We find an increasing trend in US anthropogenic emissions over 2010–2015 of 0.4 % a−1 , lower than previous GOSAT-based estimates but opposite to the decrease reported by the EPA GHGI. Most of this increase appears driven by unconventional oil and gas production in the eastern US. We also find that oil and gas production emissions in Mexico are higher than in the nationally reported inventory, though there is evidence for a 2010–2015 decrease in emissions from offshore oil production.
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Creative Commons Attribution
https://creativecommons.org/licenses/by/4.0/
Persistent DSpace Link
https://dspace.mit.edu/handle/1721.1/167388
DOI of Published Version
https://doi.org/10.5194/acp-21-4339-2021
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