Conference Agenda

Households in the United States face compounded risks when high energy burdens intersect with heightened exposure to climate extremes. This study introduces a methodological framework to systematically identify and analyze these dual-vulnerability households. Using the 2020 Residential Energy Consumption Survey (RECS) linked with high-resolution NASA Daymet climate data, I spatially match households to localized measures of extreme climates like heatwaves and cold spells. Geospatial hotspot analysis reveals regions where economic and climatic risks converge, while Local Linear Forest models are employed to identify the primary drivers of household energy expenditures. The results show that climate-related variables, such as extreme temperature events and degree days, together with housing characteristics have a stronger influence on energy costs than income. Policy simulations of interventions, including appliance upgrades, weatherization, smart home technologies, and financial assistance programs, demonstrate heterogeneous effects across household types, with technology-based strategies delivering the largest reductions in energy expenditures. These findings highlight the importance of regionally tailored, climate-responsive policies that integrate technical upgrades with socioeconomic support to enhance resilience among households at the intersection of energy poverty and climate risk.