Urban Energy Consumption in the City of Naples (Italy): A Geographically Weighted Regression Approach

The energy transition has been advocated at a worldwide level as a policy priority in promoting sustainability and delivering the Green Deal. The nexus between raw materials supply and related GHG emissions of the production process makes the energy issue relevant for all decision-makers. If there is now a widespread acceptance that action at the local level is essential and decisive to realize low-carbon cities that can efficiently save energy, a lack of integration between energy-saving solutions and urban planning continues to affect the work of local decision-makers, technicians and practitioners. According to this, the work investigates the relationships between urban characteristics and residential energy consumption data, through the integration of statistics and spatial statistics techniques. The principal component analysis and the geographically weighted regression were applied on an urban scale to support the policy-makers in increasing the energy sustainability due to climate challenges and new emerging geopolitical scenarios regarding energy supply. All spatial analyses were based on a set of variables related to the main urban characteristics: socio-economic, physical, functional and environmental ones. The test area refers to the City of Naples (Italy) where the results show the GWR prediction model estimating the higher residential energy consumption values related to the urban input variables. The outcomes of the analysis can be useful for local decision-makers in defining strategies and interventions oriented to reduce energy consumption.