## 5 Summary and Conclusions  
Based on the MLR method, this study evaluated the accuracy of PM\({}_{2.5}\) estimation in accordance with the type of applied AOD value. We confirmed that all satellite AODs generally resulted in satisfactory PM\({}_{2.5}\) estimation if other influential factors (e.g., PBLH, local meteorology, and the quantity of precursor gases) were simultaneously considered. In spite of this positive result, we also obtained some inconsistent results in winter, when the AOD retrieval can have larger uncertainty. Because the aerosol pollution in the Korean peninsula is usually the most serious in winter, an effort to identify the proper AOD appears to be required to achieve high accuracy of PM\({}_{2.5}\) estimation. The overpassing time of satellite measurements may have an impact on PM\({}_{2.5}\) estimation, but may not be significant. The direct relationship between AOD and PM\({}_{2.5}\) shows a relatively large wavelength dependence, which is negligible, however, if the MLR method is applied. In conclusion, the type of AOD does not significantly affect the accuracy of PM estimation but, nonetheless, careful usage appears to be required if a specific condition is the research target (e.g., diurnal or seasonal variation). Numerous studies have been previously conducted about the estimation of PM using AOD values based on many different statistical methods. Through these works, we determined which factors are significant and should be considered to ensure the quality of PM\({}_{2.5}\) estimation, and recognized the substantial effect of the AOD contribution. Because a number of different AOD values are produced by various satellite and ground-based measurements, it is necessary to determine how the performance of PM\({}_{2.5}\) estimation \begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline \multicolumn{2}{c}{**AERONET AOD**} & \multicolumn{8}{c}{**M3-1**} \\ \cline{3-10}  & **340 nm** & **380 nm** & **440 nm** & **500 nm** & **675 nm** & **870 nm** & **1020 nm** \\ \hline Spring & R & 0.74 & 0.74 & 0.74 & 0.73 & 0.73 & 0.73 & 0.73 \\  & N & 951 & 953 & 953 & 953 & 953 & 953 & 953 \\  & RMSE & 9.83 & 9.86 & 9.89 & 9.91 & 9.95 & 9.97 & 9.98 \\  & Slope & 0.54 & 0.54 & 0.53 & 0.53 & 0.53 & 0.53 & 0.53 \\ Summer & R & 0.79 & 0.78 & 0.78 & 0.78 & 0.78 & 0.78 & 0.78 \\  & N & 337 & 343 & 343 & 343 & 343 & 343 & 343 \\  & RMSE & 6.99 & 6.82 & 6.83 & 6.84 & 6.86 & 6.86 & 6.87 \\  & Slope & 0.62 & 0.66 & 0.66 & 0.66 & 0.66 & 0.66 & 0.66 \\ Autumn & R & 0.81 & 0.82 & 0.82 & 0.82 & 0.82 & 0.82 & 0.82 \\  & N & 511 & 513 & 513 & 513 & 513 & 513 & 513 \\  & RMSE & 5.58 & 5.50 & 5.51 & 5.51 & 5.54 & 5.56 & 5.57 \\  & Slope & 0.68 & 0.67 & 0.67 & 0.67 & 0.66 & 0.66 & 0.66 \\ Winter & R & 0.78 & 0.76 & 0.76 & 0.76 & 0.76 & 0.76 & 0.76 \\  & N & 770 & 774 & 774 & 774 & 774 & 774 & 774 \\  & RMSE & 6.98 & 7.03 & 7.04 & 7.04 & 7.04 & 7.04 & 7.04 \\  & Slope & 0.61 & 0.61 & 0.61 & 0.61 & 0.61 & 0.61 & 0.61 \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Seasonal variation of R, RMSE, slope, and number of data used (N) in correlations between measured and estimated PM\({}_{2.5}\) (unit: \(\mathrm{\mu g/m^{3}}\)) values for various wavelengths. Estimated PM\({}_{2.5}\) values here are from the M3-1 model using AERONET AOD. The unit of RMSE is \(\mathrm{\mu g/m^{3}}\). can change in terms of applied AOD values. Our research provides useful information about this phenomenon and improvements in the search for an approach for better PM\({}_{2.5}\) estimation from AOD values. Conceptualization, S.-M.K. and J.-H.K. ; methodology, S.-M.K., J.-H.K., M.C., S.S. and J.K.; software, S.-M.K. and S.S.; validation, S.-M.K., J.-H.K., M.C. and J.H. ; formal analysis, S.-M.K. and J.-H.K. ; investigation, S.-M.K., J.-H.K. and J.H. ; resources, H.L., J.M., M.C., S.G., S.L., Y.C., J.L. and J.-W.H. ; data curation, H.L., J.M., M.C., S.G., S.L., Y.C., J.L. and J.-W.H. ; writing--original draft preparation, S.-M.K. and J.-H.K. ; writing--review and editing, J.-H.K. and H.L. ; visualization, S.-M.K., H.L. and J.H.