Articles | Volume 16, issue 24
Model description paper
21 Dec 2023
Model description paper |  | 21 Dec 2023

INCHEM-Py v1.2: a community box model for indoor air chemistry

David R. Shaw, Toby J. Carter, Helen L. Davies, Ellen Harding-Smith, Elliott C. Crocker, Georgia Beel, Zixu Wang, and Nicola Carslaw


Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2023-1328', Anonymous Referee #1, 31 Jul 2023
  • RC2: 'Comment on egusphere-2023-1328', Anonymous Referee #2, 30 Aug 2023
  • AC1: 'Final author reply to the editor for egusphere-2023-1328', David Shaw, 20 Oct 2023

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload
AR by David Shaw on behalf of the Authors (20 Oct 2023)  Author's response   Author's tracked changes   Manuscript 
ED: Referee Nomination & Report Request started (30 Oct 2023) by Havala Pye
RR by Amirashkan Askari (01 Nov 2023)
RR by Anonymous Referee #1 (03 Nov 2023)
ED: Publish subject to minor revisions (review by editor) (03 Nov 2023) by Havala Pye
AR by David Shaw on behalf of the Authors (04 Nov 2023)  Author's response   Author's tracked changes   Manuscript 
ED: Publish as is (07 Nov 2023) by Havala Pye
AR by David Shaw on behalf of the Authors (09 Nov 2023)
Short summary
Exposure to air pollution is one of the greatest risks to human health, and it is indoors, where we spend upwards of 90 % of our time, that our exposure is greatest. The INdoor CHEMical model in Python (INCHEM-Py) is a new, community-led box model that tracks the evolution and fate of atmospheric chemical pollutants indoors. We have shown the processes simulated by INCHEM-Py, its ability to model experimental data and how it may be used to develop further understanding of indoor air chemistry.