A Multi-Model Assessment of the Air Quality and Health Impacts of U.S. Energy Decarbonization
Abstract Net-zero transitions are expected to reduce ambient fine particulate matter (PM2.5) concentrations and the associated mortality burden. The magnitude and distribution of these health effects are substantially affected by energy technology choices and the resulting precursor emissions that contribute to ambient PM2.5. On the basis of a multi-model analysis using three leading energy system models for the United States (US-REGEN, GCAM-USA, and REPEAT), we demonstrate that a net-zero transition yields robust nationwide reductions in ambient PM2.5 concentrations and associated mortality. Under the net-zero scenarios, national PM2.5-attributable mortality rates in 2050 declined by 28–73% compared to 2017 across the three models. This result confirms substantial health benefits from reducing energy-sector pollution, despite concurrent population growth and aging trends that place upward pressure on mortality. Differences across the models result from how CO2 mitigation efforts are allocated across sectors and associated energy technology choices. For instance, the scale of carbon dioxide removal deployment in 2050 varies by a factor of three across the net-zero scenarios developed by the three models, influencing the amount of fossil fuel use that remains in a deeply decarbonized future and, consequently, the precursor emissions contributing to ambient PM2.5. By exploring sensitivity analyses that vary the projected emissions from non-energy activities such as wildfires, we also find that potential future increases in non-energy emissions can offset energy-sector health benefits.
Authors
- Alicia Zhao (ORCID: https://orcid.org/0000-0002-6054-8671)
- Jesse Jenkins (ORCID: https://orcid.org/0000-0002-9670-7793)
- Jinyu Shiwang (ORCID: https://orcid.org/0000-0001-7475-9640)
- John Bistline (ORCID: https://orcid.org/0000-0003-4816-5739)
- Wei Peng (ORCID: https://orcid.org/0000-0002-1980-0759)
- Erin Mayfield (ORCID: https://orcid.org/0000-0001-9843-8905)
- Nicholas A. Mailloux (ORCID: https://orcid.org/0000-0002-4041-3665)
- Xinyuan Huang (ORCID: https://orcid.org/0000-0002-3604-8124)
- Jamil Farbes
- Aranya Venkatesh (ORCID: https://orcid.org/0000-0003-3877-8232)
- Gokul Iyer (ORCID: https://orcid.org/0000-0002-5162-795X)
- Eladio Knipping
- Qianru Zhu
Institutions
- Dartmouth College (US)
- University of Maryland, Baltimore (US)
- Pennsylvania State University (US)
- Electric Power Research Institute (US)
- University of Wisconsin–Madison (US)
- Princeton University (US)
- Watershed (GB)
- Evolved Analytics (United States) (US)
- Dartmouth Hospital (GB)
- Massachusetts Institute of Technology (US)
- University of Maryland, College Park (US)
Publication Details
- Journal
- Environmental Science & Technology
- Published
- 2026-09-17
- DOI
- https://doi.org/10.1021/acs.est.6c02914
- Primary Topic
- COVID-19 impact on air quality
- Type
- article
- Field-Weighted Citation Impact
- 0.00