Low-Income Energy Affordability Data (LEAD) Tool Methodology

Abstract

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Localized energy burden, concentrated disadvantage, and the feminization of energy poverty

“…Detailed methods are provided in the online version of this paper and include the following: (Ma et al, 2019), as well as the energy expenditure data from the EIA (U.S. Energy Information Administration, 2020). Stakeholders have used the LEAD tool to fill knowledge gaps, conduct strategies to improve energy program planning, and promote public awareness of LIH issues (Ma et al, 2019).…”

“…Detailed methods are provided in the online version of this paper and include the following: (Ma et al, 2019), as well as the energy expenditure data from the EIA (U.S. Energy Information Administration, 2020). Stakeholders have used the LEAD tool to fill knowledge gaps, conduct strategies to improve energy program planning, and promote public awareness of LIH issues (Ma et al, 2019). Technically, the 2020 county-level energy burden data were estimated from the 2014-2018 county-level information of LIHs' annual income (Income 2014À2018 ij ) and 2020 state-level energy expenditure data by using the following equation ( P k 1 Exp 2020 ijk ).…”

How limitations in energy access, poverty, and socioeconomic disparities compromise health interventions for outbreaks in urban settings

“…We established the 2020 county-level energy consumption poverty (ECB) database for LIHs. Due to the lack of official energy consumption data at zip code or county-level in 2020, the historical energy expenditure (electricity, fuel, and natural gas) and poverty estimation among LIHs were collected from the Low-Income Energy Affordability Data (LEAD) Tool by the National Renewable Energy Laboratory (NREL) and the U.S. Department of Energy (DOE) (Ma et al, 2021) and U.S. Energy Information Administration (EIA) (U.S. Energy Information Administration, 2020a). Technically, the 2020 county-level LIHs' ECB data was estimated from county-level information on LIHs' annual income in 2014-2018 and 2020 state-level energy consumption data by using the following equation:…”

Hot or cold temperature disproportionately impacts U.S. energy burdens

“…Previous studies have engaged in developing comprehensive and innovative metrics and capturing spatial disparities to discuss energy inequities [11,12]. Findings to date have demonstrated that energy burden tends to be strongly associated with vulnerable groups, with Black, Hispanic, low-income, elderly, and households living in energy-inefficient buildings undertaking disproportionately high energy burdens [13][14][15][16], making the energy burden metric a social equity issue, rather than purely an economic concept of affordability.…”