Articles | Volume 22, issue 20
https://doi.org/10.5194/acp-22-13881-2022
https://doi.org/10.5194/acp-22-13881-2022
Research article
 | 
28 Oct 2022
Research article |  | 28 Oct 2022

Retrieving CH4-emission rates from coal mine ventilation shafts using UAV-based AirCore observations and the genetic algorithm–interior point penalty function (GA-IPPF) model

Tianqi Shi, Zeyu Han, Ge Han, Xin Ma, Huilin Chen, Truls Andersen, Huiqin Mao, Cuihong Chen, Haowei Zhang, and Wei Gong

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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 acp-2022-180', Anonymous Referee #1, 27 Jun 2022
    • AC1: 'Reply on RC1', Tianqi Shi, 09 Sep 2022
  • RC2: 'Comment on acp-2022-180', Anonymous Referee #2, 27 Jun 2022
    • AC2: 'Reply on RC2', Tianqi Shi, 09 Sep 2022
    • AC3: 'Reply on RC2', Tianqi Shi, 09 Sep 2022

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload
AR by Tianqi Shi on behalf of the Authors (09 Sep 2022)  Author's response   Author's tracked changes   Manuscript 
ED: Referee Nomination & Report Request started (19 Sep 2022) by Martin Dameris
RR by Anonymous Referee #2 (28 Sep 2022)
ED: Publish subject to technical corrections (13 Oct 2022) by Martin Dameris
AR by Tianqi Shi on behalf of the Authors (13 Oct 2022)  Author's response   Manuscript 
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Short summary
CH4 works as the second-most important greenhouse gas, its reported emission inventories being far less than CO2. In this study, we developed a self-adjusted model to estimate the CH4 emission rate from strong point sources by the UAV-based AirCore system. This model would reduce the uncertainty in CH4 emission rate quantification accrued by errors in measurements of wind and concentration. Actual measurements on Pniówek coal demonstrate the high accuracy and stability of our developed model.
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