UNIVERSITY PARK, Pa. — Prioritizing closing coal-fired power plants near vulnerable communities could significantly improve air quality and public health outcomes, according to a new multi-institutional study. Using advanced computational modeling, the researchers found that existing strategies for retiring coal plants could be updated to deliver greater benefits to communities that have historically been the most impacted by pollution.

The study was published in Environmental Science & Technology.

“The study suggests that prioritizing coal plant closures based on health and equity benefits could shift state and regional strategies towards those that yield health and air quality benefits, especially for vulnerable communities, rather than focusing solely on economic factors,” said Carla Campos, a civil and environmental engineering doctoral student at Penn State and a co-lead author of the study.

Since 1961, electric power plants have been the dominant consumer of coal in the U.S., according to the U.S. Energy Information Administration. However, that amount has been declining. In 2023, coal accounted for 16% of electricity generation, down from 50% in 2000. This trend follows growth in economically competitive generation from natural gas and renewables; stricter federal environmental rules aimed at reducing pollution from fossil fuel-fired power plants; federal calls for 100% carbon-free electricity by 2035; and other local, state and regional efforts to incentivize renewables and reduce emissions, such as the Regional Greenhouse Gas Initiative, a multi-state program aimed at capping carbon dioxide emissions. In 2023, renewables provided more than 20% of the electricity in the U.S.

According to the Institute for Energy Economics and Financial Analysis, the U.S. will close about half of its coal-fired plants by 2026 — a trend that is mirrored in Pennsylvania, researchers said.

“Optimizing coal-fired power plant closures based on climate, cost or health objectives can lead to substantial variation in both the magnitude and distribution of health benefits,” Campos said. “This motivated us to understand the equity implications of coal plant retirements — in particular, how to better design coal retirements so as to more effectively mitigate disproportionate environmental burdens historically borne by disadvantaged communities.”

Using 2019 operations as a baseline, the researchers developed and modeled six retirement scenarios spanning two targets and three priorities for Pennsylvania’s coal-fired power plant operations. To assess availability and operational trade-offs, three scenarios were based on a target of retiring 50% of Pennsylvania’s coal-fired capacity, or the maximum amount of electricity a power plant can produce based on its design. Three more scenarios were based on a target of retiring 50% of Pennsylvania’s coal-fired generation, or the annual electricity output of a power plant.

For each target, priorities were defined as cost, climate and environmental justice (EJ). EJ focuses on improving health and environmental outcomes in low-income and low-wealth communities and communities of color that have historically and currently “bear a disproportionate share of detrimental environmental impacts with accompanying adverse health impacts,” according to Pennsylvania’s Department of Environmental Protection. EJ areas in Pennsylvania are now determined by more than 30 indicators, but in 2019, they were defined as census tracts where at least 20% of residents lived below the poverty line and at least 30% of the population identified as a non-white minority.

In the scenarios prioritizing EJ, the researchers first modeled closing plants with the most EJ areas within a 10-mile radius. With the climate priority scenarios, researchers modeled retiring plants with the highest carbon dioxide (CO2) emission rates first. Under the cost priority, they first modeled retiring the plants with the highest marginal costs of generation.

The researchers found that, among scenarios targeting capacity, prioritizing climate resulted in the largest decrease in coal usage and emissions in Pennsylvania. This modeled scenario resulted in a 18% reduction in CO2 and 75% decrease in fine particulate matter pollution (PM2.5).

Using the national Environmental Protection Agency’s Environmental Benefits Mapping and Analysis Program (BenMAP), the researchers also estimated the impacts on deaths attributable to PM2.5 for each scenario. Among scenarios targeting generation, prioritizing closures near EJ communities resulted in the largest estimated returns to health. This retirement scenario resulted in an estimated 13% reduction in PM2.5-attributable deaths in Pennsylvania and a 4.1% reduction in the rest of region serviced by PJM Interconnection, a regional transmission organization. Despite retirements only targeting EJ areas in Pennsylvania, 77% of predicted reductions in PM2.5-attributable deaths in the rest of PJM were also near EJ areas, illustrating the broader distributional impacts of closures in Pennsylvania.

Overall, the health modeling suggests that, depending on the scenario, emissions decreases could prevent up to 136 PM2.5-attributable deaths annually across the PJM service area, according to Emily Pakhtigian, an assistant professor of public policy at Penn State and a co-lead author on the study. She noted, however, that many PM2.5-attributable deaths are the result of long-term exposure, and plant retirement benefits could take time to manifest.  

“By prioritizing coal plant retirements based on health and equity impacts, Pennsylvania could take significant strides toward cleaner air and more just energy policies,” Pakhtigian said. “This study offers a model for balancing environmental, economic and social goals, shaping a healthier future for vulnerable communities.”

Modeling trade-offs between economic, climate and equity objectives can inform policy making, according to Pakhtigian.

“Pre-retirement analysis provides insight into the potential economic and distributional effects of plant closures in the region, allowing for better planning throughout possible energy transitions,” Pakhtigian said. “Policymakers could use such trade-off analysis to make informed policy decisions that improve outcomes and minimize harms.”

Closing large coal plants in Pennsylvania could lead to complex shifts in power generation across regional power systems like PJM Interconnection, according to co-author Joel Landry, a research scientist at CNA, an independent, nonprofit research and analysis organization dedicated to the safety and security of the nation.

“The beauty of our interdisciplinary approach is that it uses complex, coupled modeling methods to account for the entire chain of adjustments that are required to properly assess both the aggregate and distributional impacts of coal plant retirements in Pennsylvania,” Landry said. “It captures not only the public health impacts within Pennsylvania, but also on other communities within the same regional power systems, such as those located near generation assets that may have to operate more to fill the demand gap caused by retiring Pennsyalvania’s coal plants.”

Hannah Wiseman, a professor of law at Penn State and a co-author on the paper, said the findings underscore the need for policymakers to consider the location of coal plants when planning energy transitions.

“Policies could provide enhanced incentives for new clean energy capacity that would displace electricity from coal-fired facilities with the largest health impacts,” Wiseman said. “Policies could similiarly prioritize clean energy built in areas with active coal plants that have large health-based externalities. Regional transmission organizations, in particular, which govern the interconnection of new clean energy generation, should take these factors into account.”

In addition to Pakhtigian, Campos, Landry and Wiseman, other authors on the paper include Wei Peng, Princeton University, and An Pham, University of Michigan.

An Institute of Energy and the Environment seed grant initially funded this project. Penn State’s College of Engineering and Princeton’s Andlinger Center for Energy and the Environment provided additional funding.