Human Health Impacts of Energy Transitions across the United States among Sociodemographic Subpopulations for the Year 2050

Abstract

Strategies to reduce greenhouse gas emissions may provide health benefits through improved air quality, yet these benefits might not be equitably distributed. Understanding these cobenefits and who receives them can aid policymakers in prioritizing mitigation strategies. We investigated four future energy scenarios (port electrification, electric vehicles, natural gas, energy efficiency) and a business-as-usual scenario to determine how changes to ambient fine particle (PM_2.5) levels impact health within the contiguous United States (U.S.) by region, race/ethnicity, urbanicity, and income. We also investigated how methodological assumptions affect findings. Our projections of avoided mortalities from energy transition policies range from 67,011 (95% CI: 45,692, 82,397) to 81,003 (55,286, 99,532) in 2050. The monetized health benefits from avoided mortalities and hospitalizations range from $785.8 billion to $949.9 billion/year. These benefits vary by region and subpopulation, with Black, suburban, and less wealthy Americans experiencing higher percent avoided mortality across scenarios. Results were sensitive to assumptions for future concentration-response functions relating pollution levels to health, baseline incidence rates, and population projections. Our findings indicate energy policies transitioning from fossil fuel production in the U.S. provide substantial health and economic benefits that vary across populations and help reduce environmental health inequities in exposure and associated morality.

Keywords: PM2.5; co-benefits; energy policy; environmental justice; exposure disparities.

Figure 1.

Policy-specific projected population-weighted PM_2.5 concentration changes in 2050 from the 2010 reference for by (a) region, (b) income, (c) race/ethnicity, and (d) urbanicity.

Figure 2.

County-level ambient PM_2.5 concentration changes in 2050, compared to 2010 reference concentrations, for the (a) BAU policy scenario, and the county-level ambient PM2.5 concentration changes in 2050, compared to the BAU scenario in 2050, for each sector-specific policy scenario (b) Port, (c) HighNG, (d) HighEV, and (e) HighEE. Note that (a) BAU has a different scale than (b) Port, (c) HighNG, (d) HighEV, and (e) HighEE to allow for these scenarios to better display concentration changes from the 2050 BAU scenario comparison, where blue is additional reductions from BAU and red is lower reduction than BAU.

Figure 3.

Total avoided death projections in the year 2050, compared to 2010 reference ambient PM_2.5 concentrations under different methodological assumptions (assumptions detailed in Table S1). The Main Approach (Main) and Alternative Approach 1 and 2 (Alt_1 and Alt_2) include breakdowns by racial/ethnic groups, where Alternative Approaches 3–6 only include overall avoided deaths.