Articles | Volume 12, issue 9
Atmos. Meas. Tech., 12, 4659–4676, 2019
https://doi.org/10.5194/amt-12-4659-2019

Special issue: The 10th International Carbon Dioxide Conference (ICDC10)...

Atmos. Meas. Tech., 12, 4659–4676, 2019
https://doi.org/10.5194/amt-12-4659-2019

Research article 02 Sep 2019

Research article | 02 Sep 2019

Bayesian atmospheric tomography for detection and quantification of methane emissions: application to data from the 2015 Ginninderra release experiment

Laura Cartwright et al.

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Interactive discussion

Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision
AR by Laura Cartwright on behalf of the Authors (29 Jul 2019)  Author's response    Manuscript
ED: Publish subject to technical corrections (30 Jul 2019) by Hubertus Fischer
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Short summary
Despite extensive research, emission detection and quantification of greenhouse gases (GHGs) remain an open problem. This article presents a novel statistical framework for detecting and quantifying methane emissions and showcases its efficacy on data collected from different instruments in the 2015 Ginninderra controlled-release experiment. The developed techniques can be used to aid GHG emission reduction schemes by, for example, detecting and quantifying leaks from carbon storage facilities.