Articles | Volume 14, issue 2
Geosci. Model Dev., 14, 675–702, 2021
https://doi.org/10.5194/gmd-14-675-2021

Special issue: Simulation chambers as tools in atmospheric research (AMT/ACP/GMD...

Geosci. Model Dev., 14, 675–702, 2021
https://doi.org/10.5194/gmd-14-675-2021

Model description paper 02 Feb 2021

Model description paper | 02 Feb 2021

PyCHAM (v2.1.1): a Python box model for simulating aerosol chambers

Simon Patrick O'Meara et al.

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Cited articles

Barley, M., Topping, D., and McFiggans, G.: Critical Assessment of Liquid Density Estimation Methods for Multifunctional Organic Compounds and Their Use in Atmospheric Science, J. Phys. Chem. A, 117, 3428–3441, https://doi.org/10.1021/jp304547r, 2013. a
Bertrand, A., Stefenelli, G., Pieber, S. M., Bruns, E. A., Temime-Roussel, B., Slowik, J. G., Wortham, H., Prévôt, A. S. H., El Haddad, I., and Marchand, N.: Influence of the vapor wall loss on the degradation rate constants in chamber experiments of levoglucosan and other biomass burning markers, Atmos. Chem. Phys., 18, 10915–10930, https://doi.org/10.5194/acp-18-10915-2018, 2018. a
Carslaw, N., Mota, T., Jenkin, M. E., Barley, M. H., and McFiggans, G.: A Significant Role for Nitrate and Peroxide Groups on Indoor Secondary Organic Aerosol, Environ. Sci. Technol., 46, 9290–9298, https://doi.org/10.1021/es301350x, 2012. a
Charan, S. M., Huang, Y., and Seinfeld, J. H.: Computational Simulation of Secondary Organic Aerosol Formation in Laboratory Chambers, Chem. Rev., 119, 11912–11944, https://doi.org/10.1021/acs.chemrev.9b00358, 2019. a, b, c, d, e
Chen, B. T., Yeh, H. C., and Cheng, Y. S.: Evaluation of an Environmental Reaction Chamber, Aerosol Sci. Tech., 17, 9–24, https://doi.org/10.1080/02786829208959556, 1992. a
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User-friendly and open-source software for simulating aerosol chambers is a valuable tool for research scientists in designing and analysing their experiments. This paper describes a new version of such software and will therefore provide a useful reference for those applying it. Central to the paper is an assessment of the software's accuracy through comparison against previously published simulations.