Multidimensional index of fuel poverty in deprived neighbourhoods. Case study of Madrid

[Methodology applied] With the objective of overcoming the limitations of previous studies based on cost and income data, a methodology is proposed for the inclusion of a multidimensional fuel poverty index in the Analysis of Deprived Neighbourhoods in Spain (https://recyt.fecyt.es/index.php/CyTET/article/view/89234/64958). Fuel poverty is a cross-cutting and complex problem that needs to be approached holistically at the urban scale. The DATASET presented here identifies a series of existing vulnerable neighbourhoods from the census of 2011, located in the city of Madrid (Rodríguez-Suárez et al., 2021). From this sample, the areas that contain large amounts of energy inefficient buildings are selected. These areas are scored using a multidimensional index that assesses the risk of fuel poverty. The method proposed here crosses data from the “Observatorio de la Vulnerabilidad Urbana de España” (Hernández Aja et al., 2018) with other studies carried out for the quantification of fuel poverty and its spatial distribution. Energy inefficiency in buildings is addressed as an important vector of fuel poverty. Also, a series of indicators based on its causes and consequences are analysed to compose a multidimensional index: (1) presence of elderly population, (2) high energy costs (fuel and electricity bills), (3) low household income, and (4) inappropriate heating installations. The results can be related to basic indicators of urban deprivation contained at the Catalogue of Vulnerable Neighbourhoods. The full detailed methodology can be found in https://doi.org/10.1016/j.enbuild.2020.110205 (Martín-Consuegra et al., 2020).[File formats, file structure and file nomenclature] See document below.[Legal aspects, access and security policies] Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0).The work presented here is part of the results of the thesis “Análisis de datos espaciales para la erradicación de la pobreza energética en la rehabilitación urbana: el caso de Madrid” (Spatial data analysis for the eradication of fuel poverty in urban retrofitting: the case of Madrid) (Martín-Consuegra Ávila, 2019). It proposes the conceptual development of a Spatial Data Analysis Model that can collect large amounts of information about the energy efficiency of the residential building stock. The model contains information from different databases at various scales, in order to assess the refurbishment needs of entire neighbourhoods. It gives the possibility of planning rehabilitation strategies based on energy needs reduction, taking into account the different environmental, social and economic aspects involved in the process. Two complementary tools are proposed for the data processing of the main existing bases in Spain: the cadastre and the census. These tools generate energy indicators that are used to characterize the thermal performance of buildings, neighbourhoods and cities. https://oa.upm.es/62611/Peer reviewe