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

Related authors

A novel probabilistic source apportionment approach: Bayesian auto-correlated matrix factorization
Anton Rusanen, Anton Björklund, Manousos I. Manousakas, Jianhui Jiang, Markku T. Kulmala, Kai Puolamäki, and Kaspar R. Daellenbach
Atmos. Meas. Tech., 17, 1251–1277, https://doi.org/10.5194/amt-17-1251-2024,https://doi.org/10.5194/amt-17-1251-2024, 2024
Short summary
Rolling vs. seasonal PMF: real-world multi-site and synthetic dataset comparison
Marta Via, Gang Chen, Francesco Canonaco, Kaspar R. Daellenbach, Benjamin Chazeau, Hasna Chebaicheb, Jianhui Jiang, Hannes Keernik, Chunshui Lin, Nicolas Marchand, Cristina Marin, Colin O'Dowd, Jurgita Ovadnevaite, Jean-Eudes Petit, Michael Pikridas, Véronique Riffault, Jean Sciare, Jay G. Slowik, Leïla Simon, Jeni Vasilescu, Yunjiang Zhang, Olivier Favez, André S. H. Prévôt, Andrés Alastuey, and María Cruz Minguillón
Atmos. Meas. Tech., 15, 5479–5495, https://doi.org/10.5194/amt-15-5479-2022,https://doi.org/10.5194/amt-15-5479-2022, 2022
Short summary
Role of ammonia in European air quality with changing land and ship emissions between 1990 and 2030
Sebnem Aksoyoglu, Jianhui Jiang, Giancarlo Ciarelli, Urs Baltensperger, and André S. H. Prévôt
Atmos. Chem. Phys., 20, 15665–15680, https://doi.org/10.5194/acp-20-15665-2020,https://doi.org/10.5194/acp-20-15665-2020, 2020
Short summary
Sources of organic aerosols in Europe: a modeling study using CAMx with modified volatility basis set scheme
Jianhui Jiang, Sebnem Aksoyoglu, Imad El-Haddad, Giancarlo Ciarelli, Hugo A. C. Denier van der Gon, Francesco Canonaco, Stefania Gilardoni, Marco Paglione, María Cruz Minguillón, Olivier Favez, Yunjiang Zhang, Nicolas Marchand, Liqing Hao, Annele Virtanen, Kalliopi Florou, Colin O'Dowd, Jurgita Ovadnevaite, Urs Baltensperger, and André S. H. Prévôt
Atmos. Chem. Phys., 19, 15247–15270, https://doi.org/10.5194/acp-19-15247-2019,https://doi.org/10.5194/acp-19-15247-2019, 2019
Short summary
Secondary organic aerosol formation from smoldering and flaming combustion of biomass: a box model parametrization based on volatility basis set
Giulia Stefenelli, Jianhui Jiang, Amelie Bertrand, Emily A. Bruns, Simone M. Pieber, Urs Baltensperger, Nicolas Marchand, Sebnem Aksoyoglu, André S. H. Prévôt, Jay G. Slowik, and Imad El Haddad
Atmos. Chem. Phys., 19, 11461–11484, https://doi.org/10.5194/acp-19-11461-2019,https://doi.org/10.5194/acp-19-11461-2019, 2019
Short summary

Related subject area

Atmospheric sciences
Accurate space-based NOx emission estimates with the flux divergence approach require fine-scale model information on local oxidation chemistry and profile shapes
Felipe Cifuentes, Henk Eskes, Enrico Dammers, Charlotte Bryan, and Folkert Boersma
Geosci. Model Dev., 18, 621–649, https://doi.org/10.5194/gmd-18-621-2025,https://doi.org/10.5194/gmd-18-621-2025, 2025
Short summary
Exploring a high-level programming model for the NWP domain using ECMWF microphysics schemes
Stefano Ubbiali, Christian Kühnlein, Christoph Schär, Linda Schlemmer, Thomas C. Schulthess, Michael Staneker, and Heini Wernli
Geosci. Model Dev., 18, 529–546, https://doi.org/10.5194/gmd-18-529-2025,https://doi.org/10.5194/gmd-18-529-2025, 2025
Short summary
Quantifying uncertainties in satellite NO2 superobservations for data assimilation and model evaluation
Pieter Rijsdijk, Henk Eskes, Arlene Dingemans, K. Folkert Boersma, Takashi Sekiya, Kazuyuki Miyazaki, and Sander Houweling
Geosci. Model Dev., 18, 483–509, https://doi.org/10.5194/gmd-18-483-2025,https://doi.org/10.5194/gmd-18-483-2025, 2025
Short summary
ML-AMPSIT: Machine Learning-based Automated Multi-method Parameter Sensitivity and Importance analysis Tool
Dario Di Santo, Cenlin He, Fei Chen, and Lorenzo Giovannini
Geosci. Model Dev., 18, 433–459, https://doi.org/10.5194/gmd-18-433-2025,https://doi.org/10.5194/gmd-18-433-2025, 2025
Short summary
Coupling the urban canopy model TEB (SURFEXv9.0) with the radiation model SPARTACUS-Urbanv0.6.1 for more realistic urban radiative exchange calculation
Robert Schoetter, Robin James Hogan, Cyril Caliot, and Valéry Masson
Geosci. Model Dev., 18, 405–431, https://doi.org/10.5194/gmd-18-405-2025,https://doi.org/10.5194/gmd-18-405-2025, 2025
Short summary

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. 
Download
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 %.
Share