Targeting energy justice: Exploring spatial, racial/ethnic and socioeconomic disparities in urban residential heating energy efficiency. (October 2016)

• Record Type: Journal Article
• Authors: Reames, Tony Gerard
• Is Part Of: Energy policy. Volume 97(2016)
• Page Start: 549
• Page End: 558
• Publication Date: 2016-10
• Subjects: Energy efficiency -- Fuel poverty -- Residential heating -- Spatial analysis -- Energy justice; Energy policy -- Periodicals; Politique énergétique -- Périodiques; Electronic journals; 333.79
• DOI: 10.1016/j.enpol.2016.07.048
• Languages: English
• ISSNs: 0301-4215

Abstract

Abstract: Fuel poverty, the inability of households to afford adequate energy services, such as heating, is a major energy justice concern. Increasing residential energy efficiency is a strategic fuel poverty intervention. However, the absence of easily accessible household energy data impedes effective targeting of energy efficiency programs. This paper uses publicly available data, bottom-up modeling and small-area estimation techniques to predict the mean census block group residential heating energy use intensity (EUI), an energy efficiency proxy, in Kansas City, Missouri. Results mapped using geographic information systems (GIS) and statistical analysis, show disparities in the relationship between heating EUI and spatial, racial/ethnic, and socioeconomic block group characteristics. Block groups with lower median incomes, a greater percentage of households below poverty, a greater percentage of racial/ethnic minority headed-households, and a larger percentage of adults with less than a high school education were, on average, less energy efficient (higher EUIs). Results also imply that racial segregation, which continues to influence urban housing choices, exposes Black and Hispanic households to increased fuel poverty vulnerability. Lastly, the spatial concentration and demographics of vulnerable block groups suggest proactive, area- and community-based targeting of energy efficiency assistance programs may be more effective than existing self-referral approaches. Highlights: Develops statistical model to predict block group (BG) residential heating energy use intensity (EUI), an energy efficiency proxy. Bivariate and multivariate analyses explore racial/ethnic and socioeconomic relationships with heating EUI. BGs with more racial/ethnic minority households had higher heating EUI. BGs with lower socioeconomics had higher heating EUI. Mapping heating EUI can facilitate effective energy efficiency intervention targeting.