## 3 Results and Discussion
### Partial Correlation Matrix among PMs of Gangneung (G) and PMs of Beijing (B)
\begin{table}
\begin{tabular}{c c c c c c c c c c} \hline \hline \multirow{2}{*}{**Period**} & \multirow{2}{*}{**Item**} & \(\mathbf{PM_{10}}\) & \(\mathbf{PM_{2.5}}\) & \(\mathbf{PM_{1}}\) & \(\mathbf{Temp}\) & \(\mathbf{Wind}\) & \(\mathbf{RH}\) & \(\mathbf{PM_{10}}\) & \(\mathbf{PM_{2.5}}\) \\  & & **(G)** & **(G)** & **(G)** & **(G)** & **(G)** & **(G)** & **(G)** & **(B)** & **(B)** \\ \hline \multirow{6}{*}{Before} & PM\({}_{10}\) (G) & \multirow{2}{*}{1.000} & 0.913 & 0.854 & \(-\)0.112 & \(-\)0.218 & 0.019 & \(-\)0.035 & \(-\)0.260 \\  & PM\({}_{2.5}\) (G) & & 1.000 & 0.989 & \(-\)0.385 & \(-\)0.150 & 0.320 & 0.210 & \(-\)0.003 \\  & PM\({}_{1}\) (G) & & & 1.000 & \(-\)0.444 & \(-\)0.132 & 0.403 & 0.267 & 0.067 \\  & Temp (G) & & & & 1.000 & 0.100 & \(-\)0.897 & \(-\)0.701 & \(-\)0.694 \\  & Wind (G) & & & & & 1.000 & \(-\)0.009 & 0.084 & 0.131 \\  & RH (G) & & & & & & 1.000 & 0.623 & 0.644 \\  & PM\({}_{10}\) (B) & & & & & & & 1.000 & 0.952 \\  & PM\({}_{2.5}\) (B) & & & & & & & & 1.000 \\ \hline \multirow{6}{*}{During} & PM\({}_{10}\) (G) & \multirow{2}{*}{1.000} & 0.725 & 0.689 & 0.117 & 0.244 & \(-\)0.286 & 0.407 & \(-\)0.119 \\  & PM\({}_{2.5}\) (G) & & 1.000 & 0.996 & 0.030 & \(-\)0.013 & \(-\)0.007 & 0.567 & 0.411 \\  & PM\({}_{1}\) (G) & & & 1.000 & 0.041 & 0.005 & \(-\)0.005 & 0.574 & 0.466 \\  & Temp (G) & & & & 1.000 & 0.395 & \(-\)0.794 & 0.060 & \(-\)0.021 \\  & Wind (G) & & & & & 1.000 & \(-\)0.651 & \(-\)0.103 & \(-\)0.056 \\  & RH (G) & & & & & & 1.000 & 0.112 & 0.226 \\  & PM\({}_{10}\) (B) & & & & & & & 1.000 & 0.459 \\  & PM\({}_{2.5}\) (B) & & & & & & & & 1.000 \\ \hline \multirow{6}{*}{After} & PM\({}_{10}\) (G) & \multirow{2}{*}{1.000} & 0.732 & 0.709 & 0.419 & 0.212 & \(-\)0.470 & 0.279 & 0.584 \\  & PM\({}_{2.5}\) (G) & & 1.000 & 0.997 & 0.346 & \(-\)0.180 & \(-\)0.111 & 0.391 & 0.847 \\  & PM\({}_{1}\) (G) & & & 1.000 & 0.356 & \(-\)0.171 & \(-\)0.127 & 0.372 & 0.846 \\  & Temp (G) & & & & 1.000 & 0.209 & \(-\)0.741 & \(-\)0.167 & 0.344 \\  & Wind (G) & & & & & 1.000 & \(-\)0.475 & \(-\)0.095 & \(-\)0.225 \\  & RH (G) & & & & & & 1.000 & 0.190 & \(-\)0.110 \\  & PM\({}_{10}\) (B) & & & & & & & 1.000 & 0.551 \\  & PM\({}_{2.5}\) (B) & & & & & & & & 1.000 \\ \hline \multirow{6}{*}{All} & PM\({}_{10}\) (G) & \multirow{2}{*}{1.000} & 0.767 & 0.685 & 0.453 & 0.247 & \(-\)0.166 & 0.458 & 0.091 \\  & PM\({}_{2.5}\) (G) & & 1.000 & 0.990 & 0.217 & \(-\)0.121 & 0.273 & 0.583 & 0.425 \\ \cline{1-1}  & PM\({}_{1}\) (G) & & & 1.000 & 0.179 & \(-\)0.158 & 0.325 & 0.580 & 0.479 \\ \cline{1-1}  & Temp (G) & & & & 1.000 & 0.355 & \(-\)0.548 & \(-\)0.036 & \(-\)0.133 \\ \cline{1-1}  & Wind (G) & & & & & 1.000 & \(-\)0.623 & \(-\)0.100 & \(-\)0.281 \\ \cline{1-1}  & RH (G) & & & & & & 1.000 & 0.391 & 0.629 \\ \cline{1-1}  & PM\({}_{10}\) (B) & & & & & & & 1.000 & 0.780 \\ \cline{1-1}  & PM\({}_{2.5}\) (B) & & & & & & & & 1.000 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Partial correlation matrix among PMs associated with meteorological parameters of Gangneung city (G) and PMs of Beijing city (B), before, during and after the dust periods.