A GIS-based statistical approach to prioritize the retrofit of housing stocks at the urban scale (original) (raw)

Cities are responsible for about 70% of the overall primary energy consumption in Europe and play a major role in addressing carbon mitigation. In this respect, the housing s ector has been identified as a key sector for its high energy savings potential achievable by implementing retrofit measures. However, a detailed characterization of the housing energy consumption profile and spatial distribution is needed to properly asse ss the energy saving potential at the urban scale and further support sustainable urban planning and energy policies. This study focused on a statistical approach based on Geographical Information Systems (GIS) developed to identify the energy consumption profile of urban housing stocks, the energy savings potential achievable by implementing retrofit measures and their respective spatial distribution across one entire city. The final energy consumption of individual dwellings was predicted by running a mul tiple linear regression model based on measured ener...