Articles | Volume 23, issue 16
Research article
19 Sep 2023
Research article |  | 19 Sep 2023

Automated detection and monitoring of methane super-emitters using satellite data

Berend J. Schuit, Joannes D. Maasakkers, Pieter Bijl, Gourav Mahapatra, Anne-Wil van den Berg, Sudhanshu Pandey, Alba Lorente, Tobias Borsdorff, Sander Houweling, Daniel J. Varon, Jason McKeever, Dylan Jervis, Marianne Girard, Itziar Irakulis-Loitxate, Javier Gorroño, Luis Guanter, Daniel H. Cusworth, and Ilse Aben


Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on acp-2022-862', Anonymous Referee #1, 21 Feb 2023
  • RC2: 'Comment on acp-2022-862', Anonymous Referee #2, 06 Mar 2023
  • AC1: 'Comment on acp-2022-862', Berend Schuit, 21 Apr 2023

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload
AR by Berend Schuit on behalf of the Authors (21 Apr 2023)  Author's response   Author's tracked changes   Manuscript 
ED: Referee Nomination & Report Request started (30 Apr 2023) by Qiang Zhang
RR by Anonymous Referee #2 (26 May 2023)
ED: Publish as is (07 Jun 2023) by Qiang Zhang
AR by Berend Schuit on behalf of the Authors (28 Jun 2023)
Short summary
Using two machine learning models, which were trained on TROPOMI methane satellite data, we detect 2974 methane plumes, so-called super-emitters, in 2021. We detect methane emissions globally related to urban areas or landfills, coal mining, and oil and gas production. Using our monitoring system, we identify 94 regions with frequent emissions. For 12 locations, we target high-resolution satellite instruments to enlarge and identify the exact infrastructure responsible for the emissions.
Final-revised paper