Articles | Volume 24, issue 11
https://doi.org/10.5194/acp-24-6787-2024
https://doi.org/10.5194/acp-24-6787-2024
Research article
 | 
12 Jun 2024
Research article |  | 12 Jun 2024

Diagnosing uncertainties in global biomass burning emission inventories and their impact on modeled air pollutants

Wenxuan Hua, Sijia Lou, Xin Huang, Lian Xue, Ke Ding, Zilin Wang, and Aijun Ding

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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-2023-1822', Anonymous Referee #1, 16 Nov 2023
    • AC1: 'Reply on RC1', Sijia Lou, 02 Feb 2024
  • RC2: 'Comment on egusphere-2023-1822', Anonymous Referee #2, 27 Dec 2023
    • AC2: 'Reply on RC2', Sijia Lou, 02 Feb 2024

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload
AR by Sijia Lou on behalf of the Authors (02 Feb 2024)  Author's response   Author's tracked changes   Manuscript 
ED: Referee Nomination & Report Request started (29 Feb 2024) by N'Datchoh Evelyne Touré
RR by Anonymous Referee #2 (02 Mar 2024)
RR by Anonymous Referee #1 (13 Mar 2024)
ED: Publish as is (02 Apr 2024) by N'Datchoh Evelyne Touré
AR by Sijia Lou on behalf of the Authors (10 Apr 2024)  Manuscript 
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Short summary
In this study, we diagnose uncertainties in carbon monoxide and organic carbon emissions from four inventories for seven major wildfire-prone regions. Uncertainties in vegetation classification methods, fire detection products, and cloud obscuration effects lead to bias in these biomass burning (BB) emission inventories. By comparing simulations with measurements, we provide certain inventory recommendations. Our study has implications for reducing uncertainties in emissions in further studies.
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