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KORUS-AQ was an international cooperative air quality field study in South Korea that measured local and remote sources of air pollution affecting the Korean peninsula during May-June 2016. Some of the largest aerosol mass concentrations were measured during a Chinese haze transport event (May 24th). Air quality forecasts using the WRF-Chem model with aerosol optical depth (AOD) data assimilation captured AOD during this pollution episode but over-predicted surface particulate matter concentrations, especially PM2.5 often by a factor of 2 or larger. Analysis revealed multiple sources of model deficiency related to the calculation of optical properties from aerosol mass that explain these discrepancies. Using in-situ observations of aerosol size and composition as inputs to the optical properties calculations showed that using a low resolution size bin representation under-estimates the efficiency at which aerosols scatter and absorb light (mass extinction efficiency). Besides using finer-resolution size bins, it was also necessary to increase the refractive indices and hygroscopicity of select aerosol species within the range of values reported in the literature to achieve consistency with measured values of mass/volume extinction efficiencies and light scattering enhancement factor (f(RH)) due to aerosol hygroscopic growth. Furthermore, evaluation of optical properties obtained using modeled aerosol properties revealed the inability of sectional and modal aerosol representations in WRF-Chem to properly reproduce the observed size distribution, with the models displaying a much wider accumulation mode. Other model deficiencies included an under-estimate of organic aerosol density and an over-prediction of the fractional contribution of inorganic aerosols other than sulfate, ammonium, nitrate, chloride and sodium (mostly dust). These results illustrate the complexity of achieving an accurate model representation of optical properties and provide potential solutions that are relevant to multiple disciplines and applications such as air quality forecasts, health-effect assessments, climate projections, solar-power forecasts, and aerosol data assimilation. [ABSTRACT FROM AUTHOR]