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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Views and downloads (calculated since 23 Apr 2019)

Month	HTML	PDF	XML	Total
Apr 2019	88	36	1	125
May 2019	67	13	0	80
Jun 2019	37	20	1	58
Jul 2019	24	11	1	36
Aug 2019	29	5	2	36
Sep 2019	295	65	1	361
Oct 2019	64	56	4	124
Nov 2019	20	96	0	116
Dec 2019	33	82	0	115
Jan 2020	27	66	1	94
Feb 2020	16	8	0	24
Mar 2020	12	9	0	21
Apr 2020	24	9	0	33
May 2020	28	6	0	34
Jun 2020	18	14	0	32
Jul 2020	29	77	5	111
Aug 2020	19	20	2	41
Sep 2020	18	9	0	27
Oct 2020	19	14	8	41
Nov 2020	15	11	3	29
Dec 2020	15	10	2	27
Jan 2021	23	9	6	38
Feb 2021	18	8	5	31
Mar 2021	28	9	9	46
Apr 2021	14	4	5	23
May 2021	22	18	5	45
Jun 2021	13	13	1	27
Jul 2021	12	13	2	27
Aug 2021	13	15	2	30
Sep 2021	27	20	2	49
Oct 2021	17	43	1	61
Nov 2021	11	28	0	39
Dec 2021	28	6	1	35
Jan 2022	19	11	2	32
Feb 2022	19	16	2	37
Mar 2022	13	7	0	20
Apr 2022	13	8	1	22
May 2022	13	12	1	26
Jun 2022	11	6	2	19
Jul 2022	6	6	0	12
Aug 2022	47	11	1	59
Sep 2022	26	4	1	31
Oct 2022	35	5	1	41
Nov 2022	12	14	1	27
Dec 2022	14	11	2	27
Jan 2023	11	18	2	31
Feb 2023	17	10	1	28
Mar 2023	10	10	0	20
Apr 2023	18	3	0	21
May 2023	25	15	1	41
Jun 2023	12	6	1	19
Jul 2023	6	7	0	13
Aug 2023	16	16	3	35
Sep 2023	17	8	3	28
Oct 2023	16	3	2	21
Nov 2023	6	1	0	7
Dec 2023	29	1	4	34
Jan 2024	35	8	2	45
Feb 2024	10	8	0	18
Mar 2024	20	7	3	30
Apr 2024	18	8	2	28
May 2024	16	7	7	30
Jun 2024	44	9	2	55
Jul 2024	247	10	2	259
Aug 2024	43	14	3	60
Sep 2024	21	11	0	32
Oct 2024	74	9	4	87
Nov 2024	29	4	1	34

Cumulative views and downloads (calculated since 23 Apr 2019)

Month	HTML	PDF	XML	Total
Apr 2019	88	36	1	125
May 2019	67	13	0	80
Jun 2019	37	20	1	58
Jul 2019	24	11	1	36
Aug 2019	29	5	2	36
Sep 2019	295	65	1	361
Oct 2019	64	56	4	124
Nov 2019	20	96	0	116
Dec 2019	33	82	0	115
Jan 2020	27	66	1	94
Feb 2020	16	8	0	24
Mar 2020	12	9	0	21
Apr 2020	24	9	0	33
May 2020	28	6	0	34
Jun 2020	18	14	0	32
Jul 2020	29	77	5	111
Aug 2020	19	20	2	41
Sep 2020	18	9	0	27
Oct 2020	19	14	8	41
Nov 2020	15	11	3	29
Dec 2020	15	10	2	27
Jan 2021	23	9	6	38
Feb 2021	18	8	5	31
Mar 2021	28	9	9	46
Apr 2021	14	4	5	23
May 2021	22	18	5	45
Jun 2021	13	13	1	27
Jul 2021	12	13	2	27
Aug 2021	13	15	2	30
Sep 2021	27	20	2	49
Oct 2021	17	43	1	61
Nov 2021	11	28	0	39
Dec 2021	28	6	1	35
Jan 2022	19	11	2	32
Feb 2022	19	16	2	37
Mar 2022	13	7	0	20
Apr 2022	13	8	1	22
May 2022	13	12	1	26
Jun 2022	11	6	2	19
Jul 2022	6	6	0	12
Aug 2022	47	11	1	59
Sep 2022	26	4	1	31
Oct 2022	35	5	1	41
Nov 2022	12	14	1	27
Dec 2022	14	11	2	27
Jan 2023	11	18	2	31
Feb 2023	17	10	1	28
Mar 2023	10	10	0	20
Apr 2023	18	3	0	21
May 2023	25	15	1	41
Jun 2023	12	6	1	19
Jul 2023	6	7	0	13
Aug 2023	16	16	3	35
Sep 2023	17	8	3	28
Oct 2023	16	3	2	21
Nov 2023	6	1	0	7
Dec 2023	29	1	4	34
Jan 2024	35	8	2	45
Feb 2024	10	8	0	18
Mar 2024	20	7	3	30
Apr 2024	18	8	2	28
May 2024	16	7	7	30
Jun 2024	44	9	2	55
Jul 2024	247	10	2	259
Aug 2024	43	14	3	60
Sep 2024	21	11	0	32
Oct 2024	74	9	4	87
Nov 2024	29	4	1	34

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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.

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

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