Articles | Volume 12, issue 7
https://doi.org/10.5194/gmd-12-2983-2019
https://doi.org/10.5194/gmd-12-2983-2019
Development and technical paper
 | 
15 Jul 2019
Development and technical paper |  | 15 Jul 2019

A simplified parameterization of isoprene-epoxydiol-derived secondary organic aerosol (IEPOX-SOA) for global chemistry and climate models: a case study with GEOS-Chem v11-02-rc

Duseong S. Jo, Alma Hodzic, Louisa K. Emmons, Eloise A. Marais, Zhe Peng, Benjamin A. Nault, Weiwei Hu, Pedro Campuzano-Jost, and Jose L. Jimenez

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Cited articles

Allen, H. M., Draper, D. C., Ayres, B. R., Ault, A., Bondy, A., Takahama, S., Modini, R. L., Baumann, K., Edgerton, E., Knote, C., Laskin, A., Wang, B., and Fry, J. L.: Influence of crustal dust and sea spray supermicron particle concentrations and acidity on inorganic NO3- aerosol during the 2013 Southern Oxidant and Aerosol Study, Atmos. Chem. Phys., 15, 10669–10685, https://doi.org/10.5194/acp-15-10669-2015, 2015. 
Bates, K. H. and Jacob, D. J.: A new model mechanism for atmospheric oxidation of isoprene: global effects on oxidants, nitrogen oxides, organic products, and secondary organic aerosol, Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2019-328, in review, 2019. 
Bates, K. H., Crounse, J. D., St. Clair, J. M., Bennett, N. B., Nguyen, T. B., Seinfeld, J. H., Stoltz, B. M., and Wennberg, P. O.: Gas phase production and loss of isoprene epoxydiols, J. Phys. Chem. A, 118, 1237–1246, https://doi.org/10.1021/jp4107958, 2014. 
Bey, I., Jacob, D. J., Yantosca, R. M., Logan, J. A., Field, B. D., Fiore, A. M., Li, Q.-B., Liu, H.-Y., Mickley, L. J., and Schultz, M. G.: Global Modeling of Tropospheric Chemistry with Assimilated Meteorology: Model Description and Evaluation, J. Geophys. Res., 106, 73–95, https://doi.org/10.1029/2001JD000807, 2001. 
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Short summary
We developed a parameterization method for IEPOX-SOA based on the detailed chemical mechanism. Our parameterizations were tested using a box model and 3-D chemical transport model, which accurately captured the spatiotemporal distribution and response to changes in emissions compared to the explicit full chemistry, while being more computationally efficient. The method developed in this study can be applied to global climate models for long-term studies with a lower computational cost.