Health and Environmental Justice Implications of Retiring Two Coal-Fired Power Plants in the Southern Front Range Region of Colorado

Designing Retirement Strategies for Coal-Fired Power Plants To Mitigate Air Pollution and Health Impacts

Retiring coal power plants can reduce air pollution and health damages. However, the spatial distribution of those impacts remains unclear due to complex power system operations and pollution chemistry and transport. Focusing on coal retirements in Pennsylvania (PA), we analyze six counterfactual scenarios for 2019 that differ in retirement targets (e.g., reducing 50% of coal-based installed capacity vs generation) and priorities (e.g., closing plants with higher cost, closer to Environmental Justice Areas, or with higher CO2 emissions). Using a power system model of the PJM Interconnection, we find that coal retirements in PA shift power generation across PA and Rest of PJM, leading to scenario-varying changes in the plant-level release of air pollutants. Considering pollution transport and the size of the exposed population, these emissions changes, in turn, give rise to a reduction of 6-136 PM2.5-attributable deaths in PJM across the six scenarios, with most reductions occurring in PA. Among our designed scenarios, those that reduce more coal power generation yield greater aggregate health benefits due to air quality improvements in PA and adjacent downwind regions. In addition, comparing across the six scenarios evaluated in this study, vulnerable populations─in both PA and Rest of PJM─benefit most in scenarios that prioritize plant closures near Environmental Justice Areas in PA. These results demonstrate the importance of considering cross-regional linkages and sociodemographics in designing equitable retirement strategies.

A US perspective on closing the carbon cycle to defossilize difficult-to-electrify segments of our economy

Electrification to reduce or eliminate greenhouse gas emissions is essential to mitigate climate change. However, a substantial portion of our manufacturing and transportation infrastructure will be difficult to electrify and/or will continue to use carbon as a key component, including areas in aviation, heavy-duty and marine transportation, and the chemical industry. In this Roadmap, we explore how multidisciplinary approaches will enable us to close the carbon cycle and create a circular economy by defossilizing these difficult-to-electrify areas and those that will continue to need carbon. We discuss two approaches for this: developing carbon alternatives and improving our ability to reuse carbon, enabled by separations. Furthermore, we posit that co-design and use-driven fundamental science are essential to reach aggressive greenhouse gas reduction targets.

Cows as canaries: The effects of ambient air pollution exposure on milk production and somatic cell count in dairy cows

Exposure to air pollution, including criteria pollutants such as fine particulate matter (PM_2.5) and ozone (O₃), has been associated with morbidity and mortality in mammals. As a genetically homogenous population that is closely monitored for health, dairy cattle present a unique opportunity to assess the association between changes in air pollution and mammalian health. Milk yield decreases in the summer if temperature and humidity, measured by the Temperature Humidity Index (THI). As O₃ levels increase with warmer temperatures, and summer PM_2.5 may increase with wildfire smoke, dairy cows may serve as a useful sentinel species to evaluate subacute markers of inflammation and metabolic output and ambient pollution. Over two years, we assessed summertime O₃ and PM_2.5 concentrations from local US EPA air quality monitors into an auto-regressive mixed model of the association between THI and daily milk production data and bulk tank somatic cell count (SCC). In unadjusted models, a 10 unit increase THI was associated with 28,700 cells/mL (95% CI: 17,700, 39,690) increase in SCC. After controlling for ambient air pollutants, THI was associated with a 14,500 SCC increase (95% CI: 3,400, 25,680), a 48% decrease in effect compared to the crude model. Further, in fully adjusted models, PM_2.5 was associated with a 105,500 cells/mL (95% CI: 90,030, 121,050) increase in SCC. Similar results were found for milk production. Results were amplified when high PM_2.5 days (95th percentile of observed values) associated with wildfire smoke were removed from the analyses. Our results support the hypothesis that PM_2.5 confounds the relationships between THI and milk yield and somatic cell count. The results of this study can be used to inform strategies for intervention to mitigate these impacts at the dairy level and potentially contribute to a model where production animals can act as air quality sentinels.

Selecting Data Analytic and Modeling Methods to Support Air Pollution and Environmental Justice Investigations: A Critical Review and Guidance Framework

Given the serious adverse health effects associated with many pollutants, and the inequitable distribution of these effects between socioeconomic groups, air pollution is often a focus of environmental justice (EJ) research. However, EJ analyses that aim to illuminate whether and how air pollution hazards are inequitably distributed may present a unique set of requirements for estimating pollutant concentrations compared to other air quality applications. Here, we perform a scoping review of the range of data analytic and modeling methods applied in past studies of air pollution and environmental injustice and develop a guidance framework for selecting between them given the purpose of analysis, users, and resources available. We include proxy, monitor-based, statistical, and process-based methods. Upon critically synthesizing the literature, we identify four main dimensions to inform method selection: accuracy, interpretability, spatiotemporal features of the method, and usability of the method. We illustrate the guidance framework with case studies from the literature. Future research in this area includes an exploration of increasing data availability, advanced statistical methods, and the importance of science-based policy.

Estimating Health Impacts Due to the Reduction of Particulate Air Pollution from the Household Sector Expected under Various Scenarios

Emissions from the household sector are the most significant source of air pollution in Poland, one of the most polluted countries in the EU. Estimated health impacts of the reduction of these emissions under three scenarios are presented. The EMEP4PL model and base year emission inventory were used to estimate average annual PM10 and PM2.5 concentrations with spatial resolution of 4 km × 4 km. The change in emissions under each of the scenarios was based on data from a survey on household boilers and insulation. Scenario 1 included replacement of all poor-quality coal-fired boilers with gas boilers; Scenario 2 included replacement of all poor-quality coal-fired boilers with low-emission boilers but still using solid fuels; and Scenario 3 included the thermal refurbishment of houses with the worst insulation. Impacts on the following health parameters were estimated: premature deaths (PD), Chronic Bronchitis (CB), Bronchitis in Children (BiC) and Work Days Lost (WDL). The concentration–response functions recommended by the WHO HRAPIE project were used. The analysis was conducted for two regions: Lower Silesia and Lodzkie province. The largest reduction of health impact was observed for Scenario 1. For Lower Silesia, the annual PD decreased by 1122 (34.3%), CB by 1516 (26.6%), BiC by 9602 (27.7%) and WDL by 481k (34.7%). For Lodzkie province, the largest impacts were estimated as decreases in PD by 1438 (29.9%), CB by 1502 (25.3%), BiC by 9880 (26.8%) and WDL by 669k (30.4%).