Mapping Energy Poverty: How Much Impact Do Socioeconomic, Urban and Climatic Variables Have at a Territorial Scale?

Felipe Encinas (), Ricardo Truffello, Carlos Aguirre-Nuñez, Isidro Puig, Francisco Vergara-Perucich, Carmen Freed and Blanca Rodríguez
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Felipe Encinas: School of Architecture, Faculty of Architecture, Design and Urban Studies, Pontificia Universidad Católica de Chile, Santiago 7520245, Chile
Ricardo Truffello: Centro Nacional de Excelencia para la Industria de la Madera (CENAMAD), Pontificia Universidad Católica de Chile, Santiago 7820436, Chile
Carlos Aguirre-Nuñez: Facultad de Ingeniería, Arquitectura y Diseño, Universidad San Sebastián, Santiago 7510157, Chile
Isidro Puig: Observatory of Cities (OCUC), Faculty of Architecture, Design and Urban Studies, Pontificia Universidad Católica de Chile, Santiago 7520246, Chile
Francisco Vergara-Perucich: Center for the Production of Space (CPE), Faculty of Architecture, Design and Construction, Universidad de las Américas, Santiago 7500975, Chile
Carmen Freed: School of Architecture, Faculty of Architecture, Design and Urban Studies, Pontificia Universidad Católica de Chile, Santiago 7520245, Chile
Blanca Rodríguez: Master in Sustainable Architecture and Energy (MASE), School of Architecture, Pontificia Universidad Católica de Chile, Santiago 7520245, Chile

Land, 2022, vol. 11, issue 9, 1-21

Abstract: Energy poverty, considered a form of deprivation distinct from income poverty, is associated with three factors: low-income levels, high energy costs, and poor residential energy efficiency. It is necessary to study the socio-spatial distribution of energy poverty, particularly in metropolitan areas, due to persistent socioeconomic segregation and their public agenda implications, including the U.N. SDGs. A model of these characteristics can propose a spatial analysis of urban and climate implications, contributing evidence for public policy. This article aims to address energy poverty from a spatial approach extended to the urban area in Santiago de Chile through an exploratory model that estimates the impact of socioeconomic, urban, and climatic variables at a territorial scale on the performance of homes. Using a geographical weighted regression with the inside home temperature in winter as the dependent variable, the independent variables were the percentage of professionals, NDVI, annual thermal amplitude, and housing material quality. A housing quality pattern that acts as a proxy for vulnerability to energy poverty was found, repeating the distribution pattern of the different socioeconomic sectors. The findings incorporate a new interpretive matrix into the complex reproduction of segregation and inequality in a capital city from a developing country.

Keywords: energy poverty; spatial analysis; segregation; GWR (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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