## 3 Results
### Energy Vulnerability  
This subsection shows the results obtained from the assessment of the energy vulnerability in Seville's residential building stock. The energy vulnerability assessment is carried out based on the \(EEIR\) index, as indicated in the materials and methods section, and is classified according to the 2M indicator in three ranges: Low (\(EEIR\leq 5\%\)), Moderate (5% < \(EEIR\leq 10\%\)) and High (\(EEIR>10\%\)). Vulnerability is analyzed according to dwelling typology, the relationship between energy efficiency labelling and vulnerability, and the geographical distribution of the results obtained is presented. Table 7 shows the mean EEIR index values of each district. Figure 10 shows the distribution of dwellings by typology and energy vulnerability categories. The analysis reveals that DMBs have a lower percentage of vulnerability compared to SFDs. As the risk increases, the number of DMBs decreases, while the SFDs tend to be concentrated in the moderate risk range. According to the results obtained, 20% of the SFDs face energy vulnerability, while 99% of the DMBs have low or medium vulnerability. Figure 11 shows the urban distribution of energy vulnerability according to the established classification. A high variability of risk can be observed wi \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Type of Dwelling** & **Average \(\text{EP}_{nr}\) (kWh/m\({}^{2}\)-year)** & **Before NBE-CT-79 [45]** & **NBE-CT-1979** & **CTE-2006** \\ \hline \multirow{3}{*}{\
\begin{tabular}{c} Dwellings in \\ multi-family \\ residential \\ buildings (DMBs) \\ \end{tabular} } & Global & 121.02 & 103.08 & 83.1 \\ \cline{2-6}  & Heating & 66.33 & 55.53 & 35.27 \\ \cline{2-6}  & Cooling & 25.53 & 21.73 & 20.11 \\ \cline{2-6}  & DHW & 29.16 & 25.63 & 27.71 \\ \hline \multirow{3}{*}{
\begin{tabular}{c} Single-family \\ dwellings (SFDs) \\ \end{tabular} } & Global & 138.57 & 119.82 & 84.82 \\ \cline{2-6}  & Heating & 86.62 & 74.61 & 39.8 \\ \cline{2-6}  & Cooling & 28.85 & 24.84 & 23.13 \\ \cline{2-6}  & DHW & 23.10 & 20.28 & 21.89 \\ \hline \hline \end{tabular}
\end{table} 
Table 6: \(\text{EP}_{nr}\) consumption according to type of dwelling and building regulations. \begin{table}
\begin{tabular}{c c c c c c c c c c c} \hline \hline
**District ID** & **1** & **2** & **3** & **4** & **5** & **6** & **7** & **8** & **9** & **10** & **11** \\ \hline Mean EEIR value & 7.1 & 10.1 & 7.0 & 12.3 & 8.6 & 7.8 & 9.5 & 8.7 & 9.0 & 8.2 & 7.0 \\ \hline \hline \end{tabular}
\end{table} 
Table 7: Mean EEIR values for each district. Figure 9: Annual \(\text{EP}_{nr}\) consumption and \(\text{CO}_{2}\) emissions by district. the different districts. In general terms, the city center exhibits a higher frequency of low vulnerability, while moderate risk is more commonly observed in the outskirts. Figure 11: Urban distribution of EEIR index in the city of Seville. The numbers indicate the district ID. Figure 10: Percentage of dwellings in each \(EEIR\) ranges by dwelling typology. Additionally, a statistical comparison has been conducted between districts. Since the data did not meet the assumptions of normality and homogeneity of variances, the Kruskal-Wallis nonparametric test was applied to compare EEIR between the different districts. The results obtained from the analysis (Table 8) show statistically significant differences between the districts (H = 9093.945, \(p\) < 0.001). In order to identify in which pairs of districts these differences were found, a post-hoc [PERSON]'s analysis with correction for multiple comparisons was performed (see Appendix A). The results showed significant differences in most of the analyzed pairs of districts (_p_ < 0.001), with the exception of the comparisons between districts 1-3, 3-11, 1-11, 6-10, 5-9, 5-8, and 9-8, where no statistically significant differences were found. Districts 2, 4 and 7 show statistically significant differences with the rest of the districts.