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

David Shaw, Toby Carter, Helen Davies, Ellen Harding-Smith, Georgia Beel, Elliot Crocker, Zixu Wang, Nicola Carslaw

Research output: Contribution to journalArticle


The Indoor CHEMical model in Python, INCHEM-Py, is an open-source and accessible box model for the simulation of the indoor atmosphere, and is a refactor and significant development of the INdoor Detailed Chemical Model (INDCM). INCHEM-Py creates and solves a system of coupled ordinary differential equations that include gas-phase chemistry, surface deposition, indoor/outdoor air change, indoor photolysis processes and gas-to-particle partitioning for three common terpenes. It is optimised for ease of installation and simple modification for inexperienced users, while also providing unfettered access to customise the physical and chemical processes for more advanced users. A detailed user manual is included with the model and updated with each version release. In this paper, INCHEM-Py v1.2 is introduced, the modelled processes are described in detail, with benchmarking between simulated data and published experimental results presented, alongside discussion of the parameters and assumptions used. It is shown that INCHEM-Py achieves excellent agreement with measurements from two experimental campaigns which investigate the effects of people and different surfaces on the concentrations of different indoor air pollutants. In addition, INCHEM-Py shows closer agreement to experimental data than INDCM. This is due to the increased functionality of INCHEM-Py to model additional processes, such as deposition-induced surface emissions. Published community use-cases of INCHEM-Py are also presented to show the variety of applications for which this model is valuable to further our understanding of indoor air chemistry.
Original languageEnglish
Article number778
Number of pages21
JournalGeoscientific Model Development
Publication statusPublished - 21 Dec 2023

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© Author(s) 2023.
Preprint. Discussion started: 3 July 2023

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