Articles | Volume 26, issue 20
https://doi.org/10.5194/acp-26-15139-2026
https://doi.org/10.5194/acp-26-15139-2026
Research article
 | 
28 Oct 2026
Research article |  | 28 Oct 2026

Quantifying and attributing CO emissions over Central Asia using TROPOMI and explicit observational uncertainty

Ye Feng, Jason Blake Cohen, Xiaolu Li, Lingxiao Lu, Shuo Wang, Zhewen Liu, Lei Wang, Jian Liu, and Kai Qin

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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-2025-5890', Anonymous Referee #1, 03 Jul 2026
    • AC1: 'Reply on RC1', Ye Feng, 01 Oct 2026
  • RC2: 'Comment on egusphere-2025-5890', Anonymous Referee #2, 20 Aug 2026
    • AC2: 'Reply on RC2', Ye Feng, 01 Oct 2026

Peer review completion

AR – Author's response | RR – Referee report | ED – Editor decision | EF – Editorial file upload
AR by Ye Feng on behalf of the Authors (09 Oct 2026)  Author's response   Author's tracked changes   Manuscript 
ED: Publish as is (11 Oct 2026) by Abhishek Chatterjee
AR by Ye Feng on behalf of the Authors (13 Oct 2026)
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Short summary
Carbon monoxide pollution is difficult to track across Central Asia, where monitoring is limited. We used satellite observations and weather data to estimate emissions from 2019 to 2024 and assessed how uncertainty in the observations influenced the results. Average emissions fell by 37.9%, while the strength of major pollution hotspots declined by 40.8%. The study also identified emissions linked to persistent coal fires and changing industries, helping improve pollution records and monitoring.
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