## 3 Algorithm Description
### Aerosol Type Selection  
The aerosol type is selected using the UV and visible AI, which indicate aerosol absorptivity and particle size, respectively [28]. The following equation defines the AI [7]:  
\[\text{AI}=-100[\log\biggl{(}\frac{N_{\lambda_{1}}}{N_{\lambda_{2}}}\biggr{)}_ {meas}-log\biggl{(}\frac{N_{\lambda_{1}}\bigl{(}LER_{\lambda_{1}}\bigr{)}}{N_ {\lambda_{2}}\bigl{(}LER_{\lambda_{2}}\bigr{)}}\biggr{)}_{calc}], \tag{2}\]  
where \(N_{\lambda_{1}}\) and \(N_{\lambda_{2}}\) are the radiance normalized to solar irradiance at two wavelengths (\(\lambda_{2}>\lambda_{1}\)) and the subscripts'meas' and 'calc' denote measured and calculated values, respectively. The LER is the surface reflectance estimated by correcting for Rayleigh scattering in the measured top-of-atmosphere (TOA) signal under the assumption of aerosol-free conditions. Here, two wavelength pairs (354 and 388.0 nm; and 477 and 490 nm) are used to calculate the UV and visible AI, respectively. LER is evaluated at the shorter wavelength in each pair [7]. Recently, the AI in OMAERUV (v1.8.9.1) has been updated to account for the angular dependence of clouds and the wavelength dependence of surface albedo but the updated equation was not adopted in this study. While the spectral variation of visible radiance is sensitive to particle size, the spectral variation in the UV range depends on aerosol absorptivity. Figure 4 shows the difference of normalized radiance as the AOD varies from 0 to 1 with respect to aerosol type and seven conditions of SSA (0.82, 0.85, 0.88, 0.91, 0.94, 0.97 and 1.0). For SSA higher than 0.91, upward radiance increases with AOD, regardless of aerosol type and wavelength. Under low SSA conditions, aerosols absorb upward radiation from the surface and from molecular scattering below the aerosol layer, causing upward radiation to decrease with increasing AOD for wavelengths shorter than about 400 nm. Assuming typical SSA values of 0.88, 0.91 and 0.97 for HAF, dust and NA, respectively, as shown in Table 3, spectral variations can be separated into absorbing (Figure 4a,b) and NA (Figure 4c) types. The increasing value of N, normalized radiance, with UV wavelength leads to positive values for AI and increases AI with increasing particle absorptivity, by definition. [PERSON] et al. [7] showed that UVAI was positive for absorbing aerosols and negative for non-absorbing small particles using RTM simulations. [PERSON] et al. [44] introduced a scattering index based on the negative UVAI but [PERSON] et al. [45] noted that negative UVAI values could generally be attributed to measurement noise. Therefore, the UVAI is useful for identifying absorbing particles with positive UVAI value, rather than categorizing particle absorptivity. At longer wavelengths, the spectral variation depends primarily on particle size. Radiance increases continuously with wavelength only for dust particles (Figure 4b) and thus the visible AI can be used to indicate the presence of dust particles. Accordingly, dust aerosol was detected by positive values of UVAI and visible AI and HAF and NA particles were identified by UVAI. If both of the AIs were negative, the aerosol was identified as NA. Figure 5 shows five RGB images obtained from MODIS (Aqua) measurements on 10 March 2006, 8 April 2006, 10 October 2006, 29 March 2007 and 27 April 2012 and shows UV and visible AI and aerosol type determined from OMI L1B radiance. Each RGB image shows the aerosol plume within the boxed region. Here, the aerosol plume can be identified by particle color, which is indicated by the box color in the figure as follows: red boxes denote white particles (10 October 2006) and yellow boxes denote yellow particles. Most aerosol pixels have positive UVAI but the white aerosol plume that passed through the southern part of the Korean peninsula had a negative UVAI. Because the pixels with negative UVAI also had a negative visible AI, they were classified as fine NA aerosol.