## 4 Discussion
The elaboration of specific maps combining energy consumption, building age and energy poverty facilitates the identification of priority areas for intervention. This territorial diagnosis acquires special relevance in the context of public policies aimed at energy rehabilitation, since it allows more focused strategies to be designed, based on criteria of need and not only on technical or economic feasibility. For example, by identifying census tracts where residential buildings present both high energy consumption levels (e.g., \(\mathrm{EP}_{\mathrm{nr}}>200\) kWh/m\({}^{2}\)) and EEIR values above the 2M threshold, it is possible to prioritize areas with greater energy vulnerability. Thus, mapping derived from EPCs should not be understood only as a technical instrument, but as an urban governance tool that can actively contribute to the implementation of more efficient, equitable and territorially sensitive measures in the framework of the energy transition. It should be noted that the main focus of this study is the performance of the residential building stock at the district and census tract level. Under similar socioeconomic conditions, the physical characteristics of dwellings influence energy consumption and utility bills, and therefore, the risk of households falling into energy poverty. To ensure comparability, a total of 45,908 dwellings have been evaluated using a standardized assessment model that assumes identical occupancy and usage patterns. These assumptions are defined by the operational conditions established in the DB-HE section of the Spanish Building Code (CTE), which specify set point temperatures and usage profiles for residential buildings when calculating energy demand and EPC ratings. Although these standardized conditions may not reflect actual occupant behavior, the uniform framework established by Royal Decree 390/2021 allows for consistent comparison of energy efficiency across buildings and provides an initial diagnosis of their energy performance. In this sense, the use of EPCs as the main database in this study presents both advantages and limitations. The \(\mathrm{EP}_{\mathrm{nr}}\) consumption and \(\mathrm{CO}_{2}\) emissions values are estimated and derived from the construction characteristics of the dwelling (especially its thermal envelope) and HVAC equipment, which differs from the actual consumption patterns influenced by the occupants. The literature suggests that in dwellings with lower efficient classifications (F and G), actual consumption tends to be lower than estimated, whereas in more efficient categories (A and B) it tends to be higher [46]. Future research could investigate these trends more thoroughly through empirical validation. It should also be remarked that the GIS-based analysis carried out in this study provides valuable insights into the spatial distribution of energy efficiency and energy poverty at both district and census tract levels in the city of Seville. Nevertheless, the proposed approach could be further enhanced by integrating Building Information Modeling (BIM) methodology. BIM would allow for the inclusion of detailed geometric and non-geometric building-level information (e.g., such as construction systems, envelope materials, etc. ), which is often absent in geospatial datasets. GIS/BIM integration has already been identified as a powerful tool for improving the management and digitization of the built environment, facilitating more accurate simulation and data interoperability [47]. This combined approach could support future analyses aimed at refining energy efficiency and vulnerability assessments at urban level.