## 3 Results and Discussion
### Spatial Variations of Air Pollutants
#### 3.4.1 Differences between Pollutant Concentrations at the Roadside and the On-Site AQMS
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline  & & \multicolumn{4}{c}{**Relative Differences in Concentrations 1**} \\  & & \multicolumn{4}{c}{**(Standard Deviation (1 \(\sigma\)) in Parenthesis)**} & **Avg. AQMS Conc. (1 \(\sigma\))** \\ \cline{3-6}  & & **Site-1** & **Site-2** & **Site-3** & **Site-4** & \\ \hline \multirow{4}{*}{Summer} & CO & 19.0 (29.8) & 37.3 (27.7) & / & 11.9 (24.4) & 469.8 (174.2) \\  & NO\({}_{2}\) & 43.7 (61.5) & 33.6 (50.9) & / & \(-\)20.8 (23.2) & 28.1 (15.3) \\  & O\({}_{3}\) & \(-\)77.9 (19.9) & \(-\)77.7 (23.7) & / & \(-\)48.4 (25.7) & 24.9 (19.4) \\  & PM\({}_{2.5}\) & \(-\)3.1 (23.7) & \(-\)2.9 (23.3) & / & \(-\)6.9 (23.3) & 12.7 (6.0) \\ \hline \multirow{4}{*}{\
\begin{tabular}{c} Winter (Cold-wave) \\ \end{tabular} } & CO & 9.2 (13.2) & 24.4 (18.4) & 23.1 (20.1) & \(-\)1.9 (9.4) & 429.2 (68.3) \\  & NO\({}_{2}\) & 42.9 (36.7) & 111.5 (56.9) & 115.1 (68.4) & 32.3 (31.9) & 15.3 (4.5) \\  & O\({}_{3}\) & \(-\)5.4 (12.4) & \(-\)51.2 (11.4) & \(-\)52.4 (16.3) & 0.7 (9.9) & 21.6 (5.4) \\  & PM\({}_{2.5}\) & \(-\)4.6 (12.9) & 1.9 (13.0) & 6.8 (15.9) & \(-\)0.8 (13.3) & 17.0 (6.0) \\ \hline \multirow{4}{*}{
\begin{tabular}{c} Winter (PM\({}_{2.5}\) \\ pollution \\ period) \\ \end{tabular} } & CO & 3.5 (10.7) & 8.2 (11.6) & 0.8 (12.7) & \(-\)10.6 (5.1) & 1170 (337.7) \\  & NO\({}_{2}\) & 6.5 (18.3) & 7.7 (19.3) & 3.8 (18.0) & 5.2 (18.5) & 65.9 (10.5) \\ \cline{1-1}  & O\({}_{3}\) & \(-\)90.7 (23.3) & \(-\)88.6 (23.5) & \(-\)88.5 (23.0) & \(-\)72.0 (39.5) & 5.5 (4.7) \\ \cline{1-1}  & PM\({}_{2.5}\) & \(-\)0.006 (8.0) & 3.6 (7.4) & 5.0 (9.2) & 5.5 (8.0) & 76.5 (11.1) \\ \hline \hline \end{tabular}  
* \({}^{1}\) RD = \(\frac{\text{Site-4-AQMS}}{\text{AQMS}}\times 100\) (using 1-hr averaged conc.).  
\end{table} 
Table 3: Mean relative differences in concentrations at each sub-site with respect to the AQMS data (%) \({}^{1}\) (zone data were used only for the period of 11:00–17:00 because of the near-zero roadside concentrations during the night). The RD values for NO\({}_{2}\) at Site-1 and Site-4 (32-43%) were similar to the value in summer at Site-1 (44%). In addition, the RD of ozone was significantly decreased at all sites. These differences were a consequence of the lower NO\({}_{2}\) and O\({}_{3}\) concentrations at the AQMS, with similar levels at each sub-site compared to those in the summer. The AQMS was located on the roof of the building at Site-4 (with minimal traffic) and was therefore not likely to be directly affected by local traffic emissions. The stronger prevailing and ground-level winds for the cold wave period (Figure 3) might enhance the ventilation and eddy diffusion efficiency, decreasing urban background NOx concentrations. The reduced wintertime solar radiation weakened ozone production, lowering the urban background ozone concentration. However, these effects were relatively minor at roadside locations due to the direct impacts of traffic emissions, resulting in a larger RD in micro-environments with strong traffic emission impacts. However, for the polluted period in winter, ground-level CO and NO\({}_{2}\) concentrations at each sub-site were slightly higher than at the AQMS, with a significantly reduced RD (Table 3). Wintertime pollution events in Korea are linked to stagnant synoptic meteorological conditions [28], and occur at a regional scale, potentially masking local emission effects. The RD of daytime ozone was similar to that in summer at all sub-sites but given that the mean concentration at the AQMS was only 5.5 ppb, these differences were negligible. The RD of PM\({}_{2.5}\) in winter was also insignificant at all sub-sites for both the cold wave and polluted periods. These results suggest that the spatial distributions of PM\({}_{2.5}\) were homogeneous regardless of the season, at least within the monitoring spatial scale (\(\sim\)1 \(\times\) 1 km), even in urban areas with a dense traffic network and various different micro-environments.