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Understanding aerosol chemical composition is essential for quantifying aerosol impacts on climate, air quality, and human health, as well as for improving the representation of aerosols in chemical transport and climate models. The chemical composition of aerosols directly determines their optical, microphysical, hygroscopic properties. The aim of this study is to investigate how different assumptions regarding aerosol chemical composition and size distribution and, employed within GRASP Chemical Component approach, affect the accuracy and consistency of retrieved aerosol optical properties.In this approach, aerosols are represented as internal mixtures of predefined chemical species based on Maxwell–Garnett or linear volume mixing rules, instead of retrieving flexible, spectrally varying complex refractive indices. Aerosol size distributions are parameterized using lognormal functions with 5 to 9 bins. The baseline retrieval configuration assumes a Maxwell–Garnett mixture with aerosol components distributed between two modes: a fine mode consisting of Black Carbon, Brown Carbon, and Quartz mixed with water and soluble species, and a coarse mode composed of Iron Oxide and Quartz with water and soluble species, using a five-bin lognormal size distribution. A series of validation experiments was conducted to assess the impact of alternative modeling assumptions, including increasing the number of size bins, incorporating organic matter into the coarse mode, separating Sea Salt and Dust into two distinct coarse modes, and replacing Brown Carbon refractive indices with CAMS values.GRASP Chemical Component approach were applied to ground-based AERONET observations of direct Sun radiance and sky-scanning diffuse radiation at wavelengths primarily between 440 and 1020 nm for different aerosol types (UV and SWIR channels for several sites), and were validated against standard AERONET products (AE, SSA, refractive index, and size distribution). The results demonstrate good agreement between retrieved AE and AERONET reference products for both dust- and smoke-dominated sites. The assumptions regarding brown carbon refractive indices improve the spectral dependence of SSA, particularly during biomass-burning events. Furthermore, separating sea salt and dust into distinct coarse modes yields a more physically realistic representation of aerosol chemical composition across different AERONET sites. Overall, the proposed configuration changes have the potential to improve the interpretation of aerosol type and enhance the consistency between remote sensing data and chemical composition models of aerosols. For a more qualitative assessment, it is planned to use extensive statistical information with a larger volume of AERONET measurements.