Articles | Volume 14, issue 3
https://doi.org/10.5194/gmd-14-1681-2021
https://doi.org/10.5194/gmd-14-1681-2021
Development and technical paper
 | 
24 Mar 2021
Development and technical paper |  | 24 Mar 2021

Influence of biomass burning vapor wall loss correction on modeling organic aerosols in Europe by CAMx v6.50

Jianhui Jiang, Imad El Haddad, Sebnem Aksoyoglu, Giulia Stefenelli, Amelie Bertrand, Nicolas Marchand, Francesco Canonaco, Jean-Eudes Petit, Olivier Favez, Stefania Gilardoni, Urs Baltensperger, and André S. H. Prévôt

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Cited articles

Akherati, A., Cappa, C. D., Kleeman, M. J., Docherty, K. S., Jimenez, J. L., Griffith, S. M., Dusanter, S., Stevens, P. S., and Jathar, S. H.: Simulating secondary organic aerosol in a regional air quality model using the statistical oxidation model – Part 3: Assessing the influence of semi-volatile and intermediate-volatility organic compounds and NOx, Atmos. Chem. Phys., 19, 4561–4594, https://doi.org/10.5194/acp-19-4561-2019, 2019. 
Akherati, A., He, Y., Coggon, M. M., Koss, A. R., Hodshire, A. L., Sekimoto, K., Warneke, C., de Gouw, J., Yee, L., Seinfeld, J. H., Onasch, T. B., Herndon, S. C., Knighton, W. B., Cappa, C. D., Kleeman, M. J., Lim, C. Y., Kroll, J. H., Pierce, J. R., and Jathar, S. H.: Oxygenated aromatic compounds are important precursors of secondary organic aerosol in biomass-burning emissions, Environ. Sci. Technol., 54, 8568–8579, https://doi.org/10.1021/acs.est.0c01345, 2020. 
Andreani-Aksoyoglu, S. and Keller, J.: Estimates of monoterpene and isoprene emissions from the forests in Switzerland, J. Atmos. Chem., 20, 71–87, https://doi.org/10.1007/bf01099919, 1995. 
Bertrand, A., Stefenelli, G., Bruns, E. A., Pieber, S. M., Temime-Roussel, B., Slowik, J. G., Prevot, A. S. H., Wortham, H., El Haddad, I., and Marchand, N.: Primary emissions and secondary aerosol production potential from woodstoves for residential heating: Influence of the stove technology and combustion efficiency, Atmos. Environ., 169, 65–79, https://doi.org/10.1016/j.atmosenv.2017.09.005, 2017. 
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Short summary
We developed a box model with a volatility basis set to simulate organic aerosol (OA) from biomass burning and optimized the vapor-wall-loss-corrected OA yields with a genetic algorithm. The optimized parameterizations were then implemented in the air quality model CAMx v6.5. Comparisons with ambient measurements indicate that the vapor-wall-loss-corrected parameterization effectively improves the model performance in predicting OA, which reduced the mean fractional bias from −72.9 % to −1.6 %.
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