The public health benefits of insulation retrofits in existing housing in the United States

BACKGROUND: Methodological limitations make it difficult to quantify the public health benefits of energy efficiency programs. To address this issue, we developed a risk-based model to estimate the health benefits associated with marginal energy usage reductions and applied the model to a hypothetical case study of insulation retrofits in single-family homes in the United States. METHODS: We modeled energy savings with a regression model that extrapolated findings from an energy simulation program. Reductions of fine particulate matter (PM(2.5)) emissions and particle precursors (SO(2 )and NOx) were quantified using fuel-specific emission factors and marginal electricity analyses. Estimates of population exposure per unit emissions, varying by location and source type, were extrapolated from past dispersion model runs. Concentration-response functions for morbidity and mortality from PM(2.5 )were derived from the epidemiological literature, and economic values were assigned to health outcomes based on willingness to pay studies. RESULTS: In total, the insulation retrofits would save 800 TBTU (8 × 10(14 )British Thermal Units) per year across 46 million homes, resulting in 3,100 fewer tons of PM(2.5), 100,000 fewer tons of NOx, and 190,000 fewer tons of SO(2 )per year. These emission reductions are associated with outcomes including 240 fewer deaths, 6,500 fewer asthma attacks, and 110,000 fewer restricted activity days per year. At a state level, the health benefits per unit energy savings vary by an order of magnitude, illustrating that multiple factors (including population patterns and energy sources) influence health benefit estimates. The health benefits correspond to $1.3 billion per year in externalities averted, compared with$5.9 billion per year in economic savings. CONCLUSION: In spite of significant uncertainties related to the interpretation of PM(2.5 )health effects and other dimensions of the model, our analysis demonstrates that a risk-based methodology is viable for national-level energy efficiency programs