## 3 Results
### Effect of Traffic Noise on Sound Environment Evaluations  
According to the results from the MANOVA analysis, both the traffic noise source and the traffic noise level exerted significant influences on sound environment evaluations. Figure 8 shows the relationship between traffic noise sources and acoustic comfort evaluations. A pairwise comparison was conducted to identify significant differences among noise groups. \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline  & \multicolumn{3}{c}{**Acoustic Comfort**} & \multicolumn{3}{c}{**Noise Disturbance**} \\ \cline{2-7}  & **F** & **Sig.** & \(\mathbf{n_{p}^{2}}\) & **F** & **Sig.** & \(\mathbf{n_{p}^{2}}\) \\ \hline IN & 40.87 & 0.00 ** & 0.06 & 37.59 & 0.00 ** & 0.05 \\ TN & 5.35 & 0.00 ** & 0.02 & 8.73 & 0.00 ** & 0.03 \\ SPL & 163.79 & 0.00 ** & 0.10 & 142.83 & 0.00 ** & 0.09 \\ IN \({}^{*}\) TN & 0.37 & 0.96 & 0.00 & 1.36 & 0.19 & 0.01 \\ IN \({}^{*}\) SPL & 8.65 & 0.00 ** & 0.01 & 4.94 & 0.01 * & 0.01 \\ TN \({}^{*}\) SPL & 1.78 & 0.11 & 0.01 & 0.40 & 0.85 & 0.00 \\ IN \({}^{*}\) TN \({}^{*}\) SPL & 0.68 & 0.75 & 0.01 & 0.49 & 0.90 & 0.00 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: MANOVA analysis for the effects of interior noise (IN), traffic noise type (TN), and traffic noise level (SPL) on subjective evaluations of the sound environment. The symbols \({}^{**}\) and \({}^{**}\) represent significance at 0.05 and 0.01 levels, respectively. Figure 8: Effect of traffic noise source and traffic noise level on sound environment evaluations. The symbol \({}^{**}\) represents a significant difference at the 0.05 significance level in the pairwise comparison analysis (LSD method). First, there were significant differences between road traffic noise (R) and three rail traffic noises. Acoustic comfort evaluations with respect to R were significantly higher than those relative to Me, C, and H. However, the differences between R and the other two rail traffic noises (Ma and T) were found to be insignificant. Meanwhile, there were significant differences among rail traffic noises. The evaluations of maglev and tram noises were significantly higher than those relative to conventional train and high-speed train noise. These differences caused by traffic noise sources can be explained by variations in the temporal fluctuation characteristics of the noises. The order of traffic noise sources in Figure 8 is a reflection of the order of the noise temporal fluctuations (L\({}_{10}\)-L\({}_{90}\)) shown in Table 1 (R \(<\) Ma \(<\) T \(<\) Me \(<\) C \(<\) H). Therefore, the results in Figure 8 show that, as the temporal fluctuation (L\({}_{10}\)-L\({}_{90}\)) increased, the impact of traffic noise on people's perception of the sound environment also increased. This resulted in lower acoustic comfort and higher noise disturbance. It was found that acoustic comfort was highly correlated with L\({}_{10}\)-L\({}_{90}\) (R\({}^{2}\) = 0.7), as shown in Figure 8.  
Figure 9 shows the effect of traffic noise levels on subjective evaluations. With the traffic noise level increasing from 40 dB to 50 dB, the acoustic comfort improved, and noise disturbance decreased significantly across all traffic noise groups. This is consistent with the results from the MANOVA analysis that show that SPL was the most influential factor for subjective evaluations. It was also found that the differences in acoustic comfort caused by SPL changes vary among different traffic noise groups. For road traffic noise, the mean acoustic comfort rating was improved from 2.79 (neither comfortable nor uncomfortable) to 3.71 (comfortable) by decreasing the traffic noise level by 10 dB. On the other hand, the effects of a 10 dB SPL decrease on acoustic comfort evaluations in the rail traffic groups were relatively small (Ma: 0.43; T: 0.57; Me: 0.57; C: 0.7; H: 0.67).