Articles | Volume 23, issue 18
https://doi.org/10.5194/acp-23-10313-2023
https://doi.org/10.5194/acp-23-10313-2023
Research article
 | 
15 Sep 2023
Research article |  | 15 Sep 2023

Reduction in vehicular emissions attributable to the Covid-19 lockdown in Shanghai: insights from 5 years of monitoring-based machine learning

Meng Wang, Yusen Duan, Zhuozhi Zhang, Qi Yuan, Xinwei Li, Shuwen Han, Juntao Huo, Jia Chen, Yanfen Lin, Qingyan Fu, Tao Wang, Junji Cao, and Shun-cheng Lee

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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-2023-204', Anonymous Referee #1, 26 Apr 2023
  • RC2: 'Comment on egusphere-2023-204', Anonymous Referee #2, 06 May 2023
  • AC1: 'Comment on egusphere-2023-204', Meng Wang, 09 Jul 2023

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload
AR by Meng Wang on behalf of the Authors (09 Jul 2023)  Author's response   Author's tracked changes   Manuscript 
ED: Referee Nomination & Report Request started (11 Jul 2023) by Thomas Berkemeier
RR by Anonymous Referee #1 (12 Jul 2023)
RR by Anonymous Referee #2 (23 Jul 2023)
ED: Publish subject to minor revisions (review by editor) (23 Jul 2023) by Thomas Berkemeier
AR by Meng Wang on behalf of the Authors (27 Jul 2023)  Author's response   Author's tracked changes   Manuscript 
ED: Publish as is (27 Jul 2023) by Thomas Berkemeier
AR by Meng Wang on behalf of the Authors (03 Aug 2023)  Manuscript 
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Short summary
Hourly elemental carbon (EC) and NOx were continuously measured for 5 years (2016–2020) at a sampling site near a highway in western Shanghai. We use a machine learning model to rebuild the measured EC and NOx, and a business-as-usual (BAU) scenario was assumed in 2020 and compared with the measured EC and NOx.
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