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

Cartwright, Laura; Zammit-Mangion, Andrew; Bhatia, Sangeeta; Schroder, Ivan; Phillips, Frances; Coates, Trevor; Negandhi, Karita; Naylor, Travis; Kennedy, Martin; Zegelin, Steve; Wokker, Nick; Deutscher, Nicholas M.; Feitz, Andrew

doi:https://doi.org/10.5194/amt-12-4659-2019

Articles | Volume 12, issue 9

https://doi.org/10.5194/amt-12-4659-2019

© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Special issue:

The 10th International Carbon Dioxide Conference (ICDC10)...

https://doi.org/10.5194/amt-12-4659-2019

© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 12, issue 9

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, Andrew Zammit-Mangion, Sangeeta Bhatia, Ivan Schroder, Frances Phillips, Trevor Coates, Karita Negandhi, Travis Naylor, Martin Kennedy, Steve Zegelin, Nick Wokker, Nicholas M. Deutscher, and Andrew Feitz

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Final revised paper (published on 02 Sep 2019)
Preprint (discussion started on 23 Apr 2019)

Interactive discussion

Status: closed

AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment

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RC1: 'Review of Cartwright et al.', Anonymous Referee #1, 06 Jun 2019
- AC1: 'Response to R1 comments', Laura Cartwright, 25 Jul 2019
RC2: 'Referee comments', Anonymous Referee #2, 19 Jun 2019
- AC2: 'Response to R2 comments', Laura Cartwright, 25 Jul 2019

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

AR by Laura Cartwright on behalf of the Authors (31 Jul 2019) Manuscript

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.