Articles | Volume 22, issue 21
Atmos. Chem. Phys., 22, 14253–14282, 2022
https://doi.org/10.5194/acp-22-14253-2022
Atmos. Chem. Phys., 22, 14253–14282, 2022
https://doi.org/10.5194/acp-22-14253-2022
Research article
08 Nov 2022
Research article | 08 Nov 2022

Transport patterns of global aviation NOx and their short-term O3 radiative forcing – a machine learning approach

Jin Maruhashi et al.

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Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • EC1: 'Editor comment on acp-2022-348', Peer Johannes Nowack, 18 Jul 2022
    • AC1: 'Reply on EC1', Irene Dedoussi, 20 Jul 2022
  • RC1: 'Comment on acp-2022-348', Anonymous Referee #1, 29 Jul 2022
  • RC2: 'Comment on acp-2022-348', Anonymous Referee #2, 27 Aug 2022

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision
AR by Irene Dedoussi on behalf of the Authors (28 Sep 2022)  Author's response    Author's tracked changes    Manuscript
ED: Publish as is (09 Oct 2022) by Peer Johannes Nowack
AR by Irene Dedoussi on behalf of the Authors (15 Oct 2022)  Author's response    Manuscript
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Short summary
Aviation NOx emissions lead to the formation of ozone in the atmosphere in the short term, which has a climate warming effect. This study uses global-scale simulations to characterize the transport patterns between NOx emissions at an altitude of ~ 10.4 km and the resulting ozone. Results show a strong spatial and temporal dependence of NOx in disturbing atmospheric O3 concentrations, with the location that is most impacted in terms of warming not necessarily coinciding with the emission region.
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