Articles | Volume 24, issue 11
https://doi.org/10.5194/acp-24-6539-2024
https://doi.org/10.5194/acp-24-6539-2024
Research article
 | 
04 Jun 2024
Research article |  | 04 Jun 2024

Impact of weather patterns and meteorological factors on PM2.5 and O3 responses to the COVID-19 lockdown in China

Fuzhen Shen, Michaela I. Hegglin, and Yue Yuan

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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-2023-2425', Anonymous Referee #1, 15 Dec 2023
  • RC2: 'Comment on egusphere-2023-2425', Anonymous Referee #2, 24 Jan 2024

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload
AR by Fuzhen Shen on behalf of the Authors (15 Apr 2024)  Author's response   Author's tracked changes 
EF by Polina Shvedko (17 Apr 2024)  Manuscript 
ED: Publish subject to technical corrections (18 Apr 2024) by Peer Nowack
AR by Fuzhen Shen on behalf of the Authors (22 Apr 2024)  Manuscript 
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Short summary
We attempt to use a novel structural self-organising map and machine learning models to identify a weather system and quantify the importance of each meteorological factor in driving the unexpected PM2.5 and O3 changes under the specific weather system during the COVID-19 lockdown in China. The result highlights that temperature under the double-centre high-pressure system plays the most crucial role in abnormal events.
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