## 3 Algorithm Description
### Aerosol Model Assumptions  
To improve computational efficiency, the algorithm takes the LUT approach. AOPs for three aerosol types are integrated from AERONET inversion data and used in the LUT calculation.  
Physically, aerosol types can be generally categorized into highly absorbing coarse (e.g., dust), highly absorbing fine (HAF; e.g., carbonaceous), non-absorbing (NA) coarse (sea-salt) and non-absorbing fine (sulfate) particles [30; 37; 38]. Because of the high sensitivity of near-UV radiance to aerosol absorptivity, three aerosol types (HAF, dust and NA) were used in this study to classify particles based on AERONET inversion products using the aerosol type classification method suggested by [PERSON] et al. [30]. The size of NA particles was not considered here because radiance in the UV range is not sensitive to particle size [7]. The categorized aerosol types of dust, HAF and NA accounted for 33.98%, 15.73% and 16.19% of the entire AERONET inversion product, respectively. The remaining 44.00% of particles can be classified as polluted dust (12.22%) and moderately absorbing fine particles (21.87%), which represent mixtures of particle size and absorptivity, respectively, in accordance with [PERSON] et al. [30]. These mixture conditions are not considered here. The developed algorithm is designed to retrieve AOPs over Asia but the AOPs of the aerosol model were estimated from a global dataset to ensure sufficient data for each aerosol type.  
The optical properties for each aerosol type, which were obtained by averaging the integrated AERONET inversion dataset, are summarized in Table 3. In terms of the volume size distribution, the coarse mode of the bimodal size distribution is clearly dominant for dust, whereas the fine mode is dominant for HAF and NA. The Absorbing Angstrom Exponent (AAE), which represents the wavelength dependence of particle absorption, differs significantly between dust and the other two types in the 440-675 nm wavelength range. At shorter wavelengths, spectral variations of the imaginary part of the refractive index for the HAF and dust types are assumed based on [PERSON] et al. [39] and [PERSON] et al. [40], respectively. [PERSON] et al. [39] showed that the imaginary index  
Figure 3: Flowchart of the UV-visible algorithm used to retrieve AOD, SSA and ALH.  
for brown carbon varies following a power law in the UV range. The exponent (\(\omega\)) in the power formula was obtained as 3.9 and adopted for the HAF properties in this study. [PERSON] et al. (2016) obtained the spectral variation from 0.2 to 1.0 \(\upmu\)m by assuming transported Asian dust consists of internally mixed mineral components and showed that the imaginary index varies more slowly between 350 and 500 nm than indicated by the Optical Properties of Aerosols and Clouds (OPAC)'mineral-transported' dataset ([PERSON] et al., 2016). Using the results of [PERSON] et al. (2016), the \(\omega\) for dust was obtained as 1.835. This \(\omega\) value is generally lower than the values of the Saharan dust sample described by [PERSON] et al. (2012). The \(\omega\) value for NA particles is assumed to be 0, following the optical properties of water-soluble particles in the OPAC dataset.