Articles | Volume 15, issue 23
https://doi.org/10.5194/amt-15-7155-2022
https://doi.org/10.5194/amt-15-7155-2022
Research article
 | 
13 Dec 2022
Research article |  | 13 Dec 2022

Detecting and quantifying methane emissions from oil and gas production: algorithm development with ground-truth calibration based on Sentinel-2 satellite imagery

Zhan Zhang, Evan D. Sherwin, Daniel J. Varon, and Adam R. Brandt

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Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2022-771', Anonymous Referee #1, 19 Sep 2022
    • AC2: 'Reply on RC1', Zhan Zhang, 28 Sep 2022
  • AC1: 'Comment on egusphere-2022-771', Zhan Zhang, 28 Sep 2022
  • RC2: 'Comment on egusphere-2022-771', Anonymous Referee #2, 30 Sep 2022
    • AC3: 'Reply on RC2', Zhan Zhang, 11 Nov 2022

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload
AR by Zhan Zhang on behalf of the Authors (13 Nov 2022)  Author's response   Author's tracked changes   Manuscript 
ED: Referee Nomination & Report Request started (14 Nov 2022) by Joanna Joiner
RR by Anonymous Referee #2 (16 Nov 2022)
RR by Anonymous Referee #1 (21 Nov 2022)
ED: Publish as is (21 Nov 2022) by Joanna Joiner
AR by Zhan Zhang on behalf of the Authors (21 Nov 2022)  Manuscript 
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Short summary
This work developed a multi-band–multi-pass–multi-comparison-date Sentinel-2 methane retrieval algorithm, and the method was calibrated by data from a controlled release test. To our knowledge, this is the first study that validates the performance of a Sentinel-2 methane detection algorithm by calibration with a ground-truth testing. It illustrates the potential for additional validation with systematic future experiments wherein algorithms can be tuned to meet different detection expectations.