# The Effect of Green Areas on Urban Microclimate: A University Campus Model Case
## 3 Results and Discussion
### Regression Model and Applicability
\begin{table}
\begin{tabular}{l c c c c c c c} \hline
**Source** & **DF** & **Contribution** & **Adj SS** & **Adj MS** & **F-Value** & **\(p\)-Value** & **VIF** \\ \hline Model & 14 & 92.49\% & 7285.66 & 520.404 & 81.76 & 0.000 & \\ Linear & 4 & 84.67\% & 983.13 & 245.782 & 38.61 & 0.000 & \\ A (m\({}^{2}\)) & 1 & 0.20\% & 13.00 & 12.997 & 2.04 & 0.156 & 1.17 \\ M (\%) & 1 & 7.87\% & 222.51 & 222.509 & 34.96 & 0.000 & 3.47 \\ WS (m/s ) & 1 & 5.15\% & 1.31 & 1.314 & 0.21 & 0.651 & 4.63 \\ AT (\({}^{\circ}\)C) & 1 & 71.45\% & 762.82 & 762.820 & 119.84 & 0.000 & 4.02 \\ Square & 4 & 3.82\% & 183.96 & 45.989 & 7.22 & 0.000 & \\ A\(\times\)A & 1 & 0.40\% & 31.13 & 31.130 & 4.89 & 0.029 & 1.00 \\ M\(\times\)M & 1 & 3.05\% & 0.98 & 0.977 & 0.15 & 0.696 & 7.65 \\ WS\(\times\)WS & 1 & 0.38\% & 43.03 & 43.034 & 6.76 & 0.011 & 5.41 \\ AT\(\times\)AT & 1 & 0.00\% & 6.01 & 6.010 & 0.94 & 0.334 & 1.79 \\
Figure 9, Residual diagnostics and Pareto chart for Vines. The Pareto chart reveals that AT, M, and the interaction term M\(\times\)AT have the strongest standardized effects on T. The normal probability plot shows residuals closely following the expected trend, validating normal distribution. Additionally, the Versus Fits and Versus Order plots confirm the randomness and independence of residuals, supporting the assumption of homoscedasticity and enhancing the model's statistical credibility. Figure 10, Contour plots for Vines, displaying the combined effects of environmental variables on T. The M\(\times\)AT and AT\(\times\)M plots show strong gradient shifts in color, indicating effective cooling performance through synergistic humidity-temperature interactions. Plots such as WS\(\times\)AT also demonstrate localized thermal variations, especially in transitional zones. Red and yellow regions mark optimal microclimatic outcomes. These visual insights emphasize the importance of incorporating interactive variable effects into urban greening design strategies, particularly when using vine-based vertical vegetation. In order to evaluate the generalizability of these findings, it is important to compare them with similar studies conducted in different climatic and urban contexts. The outcomes of this study are consistent with previous research in cities such as Chicago, Tel Aviv, and Bangkok, where green infrastructure significantly reduced urban temperatures. For instance, ref. [52] demonstrated a strong inverse relationship between vegetation cover and surface temperature in Chicago. Similarly, ref. [53] found that increasing green space coverage from 10% to 30% could eliminate the UHI effect in Tel Aviv. In tropical cities like Bangkok, ref. [54] showed that green roofs and passive cooling strategies were effective in lowering residential temperatures. Furthermore, studies in Addis Ababa and Beijing [65; 83] revealed that the spatial connectivity and composition of green spaces are critical for achieving urban thermal comfort. These cross-regional findings support the idea that green infrastructure design must be adapted to specific climatic contexts and demonstrate that the strategies explored in this study have the potential for broader application.