## 4 Discussion  
Energy Performance Certificate (EPC) databases provide valuable information on energy efficiency and construction characteristics of buildings. The analysis of this information with an aggregated and geo-referenced approach allows the identification of spatial and typological patterns essential to understand the residential building stock and to guide more effective and targeted energy renovation strategies. The results obtained from the analysis of the EPC data of the city of Seville reveal key trends about the residential building stock. First, most of the dwellings--both SFDs and MDBs--were built before the Spanish building code (CTE) came into force, which translates into higher energy consumption and worse ratings in the EPCs. More than 85% of the dwellings analyzed are concentrated in the E, F and G labels, which confirms a generalized low energy efficiency. SFDs show higher consumption and emissions than MDBs, which could be explained by their larger exposed surface area and lower compactness. In addition, a progressive improvement in energy consumption is observed as regulations progress: average EP\({}_{\text{nr}}\) values decrease significantly in dwellings built under NBE-CT and especially with the CTE. This fact supports the effectiveness of regulatory requirements in improving energy performance. At the spatial level, the analysis by districts reveals significant differences in the energy performance of dwellings. Districts 2 (Macarena) and 4 (Cerro-Amate) show the highest average consumptions (with 169 and 174 kWh/m\({}^{2}\)-year respectively), which could be related to an older residential building stock, and therefore to more inefficient construction systems. At the opposite extreme, District 11 (Los Remedios) shows the lowest average consumption (143 kWh/m\({}^{2}\)/year), followed by District 10 (Bellavista-La Palmera) (148 kWh/m\({}^{2}\)/year). Moreover, the interquartile ranges are high in almost all districts, indicating a strong heterogeneity within each area, probably linked to typological and constructive variety. These internal differences are particularly relevant when planning public policies, as they could  
Figure 17: EEIR index in the Cerro-Amate District at the census tract level. mask situations of energy vulnerability in districts that, in aggregate terms, do not seem to be a priority. In this sense, these disparities can be mapped with high accuracy using GIS tools, supporting a more informed and territorially focused decision-making process on the energy performance at the district scale. This reinforces the potential of open EPC databases as a diagnostic and planning tool. With regard to statistical analysis, the Kruskal-Wallis test showed the existence of statistically significant differences between districts. The district with the highest mean EEIR index value was district 4 (Cerro-Amate). Despite the typological differences between SFDs and DMBs, the data reflect a generalized low energy performance in this district, with high average consumptions (185 and 171 kWh/m\({}^{2}\)/year, respectively). The distribution of EPC labels reinforces this observation: more than 70% of the dwellings are concentrated in labels E, F and G, with practically no highly efficient dwellings (A or B). In the case of DMBs, 80.8% are rated E, while this category accounts for 67.7% in SFDs. In terms of energy poverty, there is a remarkable contrast between the two dwelling typologies. One third of the SFDs in the district could be in a situation of overspending (above 10% of income), while the DMBs show a lower profile, with a majority in the intermediate range (between 5% and 10%). In summary, the results obtained show that the EPC data, when integrated and spatially represented by GIS, allow not only to describe the energy status of the building stock, but also to visualize territorial inequalities in terms of energy efficiency and energy poverty.