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/a...
| Autores: | , , |
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| Tipo de recurso: | conjunto de datos |
| Fecha de publicación: | 2021 |
| País: | España |
| Institución: | Consejo Superior de Investigaciones Científicas (CSIC) |
| Repositorio: | DIGITAL.CSIC. Repositorio Institucional del CSIC |
| OAI Identifier: | oai:digital.csic.es:10261/256282 |
| Acceso en línea: | http://hdl.handle.net/10261/256282 |
| Access Level: | acceso abierto |
| Palabra clave: | Fuel Poverty Building energy efficiency Urban deprivation |
| Sumario: | [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). |
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