Geoscientific Model Development (Dec 2023)

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

  • D. R. Shaw,
  • T. J. Carter,
  • H. L. Davies,
  • E. Harding-Smith,
  • E. Harding-Smith,
  • E. C. Crocker,
  • G. Beel,
  • G. Beel,
  • Z. Wang,
  • N. Carslaw

DOI
https://doi.org/10.5194/gmd-16-7411-2023
Journal volume & issue
Vol. 16
pp. 7411 – 7431

Abstract

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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 (rewrite of source code) 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, and 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 an experimental campaign which investigate the effects of 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. A comparative analysis with a similar zero-dimensional model, AtChem2, verifies the solution of the gas-phase chemistry. 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.