## 4 Results and Discussions
The performance of PM\({}_{2.5}\) estimation in spring, summer, and autumn does not show a significant discrepancy according to the AOD used. In winter, however, the quality of PM\({}_{2.5}\) estimation is relatively dependent on the AOD used. Although the MISR AOD results in the highest correlation (R = -0.9) and slope (-0.9), the OMI AOD results in the lowest correlation (R = -0.65) and slope (\(<\)-0.5), and highest RMSE, indicating a weak capability of capturing the surface aerosol properties in winter. MODIS AODs also show different performances: MODIS-3 km and MODIS-DT AOD are related to a high correlation and slope, but MODIS-DB is related to a relatively low correlation and slope. This feature indicates that the consistency of various satellite AOD data is not high in winter. It appears that the number of data is not significantly associated with the quality of PM\({}_{2.5}\) estimation (Figure 2a). This inconsistency may be attributed to the accuracy of AOD retrieval in winter. The quality of AOD retrieval can be degraded due to a high solar zenith angle [41; 42] or bright surface albedo caused by snow cover [43; 44], which are representative of winter conditions on the Korean peninsula. Some retrieval algorithms can be largely affected by the winter characteristics of surface albedo. For example, the MODIS DT algorithm selects the minimum surface albedo in 30-day data for each pixel, and the high-reflecting surface case can be selected if there retains a snow-covered surface for a long period during winter. Different particle shapes can be associated with the variation in AOD quality if combined with the other influencing factors noted above (e.g., SZA and surface albedo). Aerosol retrieval of MISR using multi-view angles appears to be more advantageous for the separation of surface and aerosol signals than other sensors, resulting in better reliability in retrieved AOD across seasons. Therefore, according to the specification of satellite sensors and properties of the retrieval algorithm, the AOD difference can be relatively larger in winter. Further research will be required to reduce the gap in the PM\({}_{2.5}\) estimation in winter. Because aerosol pollution in South Korea is most serious during winter [45], the quality improvement in wintertime PM\({}_{2.5}\) estimation is essential. Because we found that the MODIS AOD values resulted in different performance of PM\({}_{2.5}\) estimation according to the retrieval algorithm, we also inspected if the result of PM\({}_{2.5}\) estimation was different when the MODIS AOD of the Terra (or Aqua) satellite is only used. Figure 3 shows the comparison of correlation, slope, and RMSE results between observed and estimated PM\({}_{2.5}\) when the MODIS-DT, MODIS-DB, and MODIS-3 km onboard the Terra (or Aqua) satellite AOD was used with M3-1 and M3-2 models. Itdoes not appear that an obvious change was derived from this comparison but, in general, the MODIS AODs onboard the Terra satellite resulted in a slightly higher accuracy. The difference in the correlation coefficients appears negligible, but the slope difference between the Terra and Aqua AOD cases is sometimes significant (higher that 0.05 difference). The number of data of the MODIS AODs of the Terra satellite are slightly higher but this does not appear to be a critical factor. One significant difference is the temporal difference; the overpassing time of the Terra satellite is around 10:30 AM local time, whereas that of Aqua satellite is around 1:30 PM local time. Considering that PBLH is generally higher in the afternoon compared to the morning due to the enhanced vertical mixing driven by the surface heating [21; 46], it is feasible to expect a smaller portion of surface aerosol concentration in the total columnar aerosol density, which may explain the relatively lower accuracy of the estimated PM\({}_{2.5}\). This comparison provides an insight into identifying the role of AOD measurement time in PM\({}_{2.5}\) estimation.