Increase in fertility following coal and oil power plant retirements in California

Sulfur dioxide reduction at coal-fired power plants in North Carolina and associations with preterm birth among surrounding residents

Coal-fired power plants (CFPP) are major contributors of air pollution, including the majority of anthropogenic sulfur dioxide (SO2) emissions, which have been associated with preterm birth (PTB). To address a 2002 North Carolina (NC) policy, 14 of the largest NC CFPPs either installed desulfurization equipment (scrubbers) or retired coal units, resulting in substantial reductions of SO2 air emissions. We investigated whether SO2 air emission reduction strategies at CFPPs in NC were associated with changes in prevalence of PTB in nearby communities.

Methods

We used US EPA Air Markets Program Data to track SO2 emissions and determine the implementation dates of intervention at CFPPs and geocoded 2003-2015 NC singleton live births. We conducted a difference-in-difference analysis to estimate change in PTB associated with change in SO2 reduction strategies for populations living 0-<4 and 4-<10 miles from CFPPs pre- and postintervention, with a comparison of those living 10-<15 miles from CFPPs.

Results

With the spatial-temporal exposure restrictions applied, 42,231 and 41,218 births were within 15 miles of CFPP-scrubbers and CFPP-retired groups, respectively. For residents within 4-<10 miles from a CFPP, we estimated that the absolute prevalence of PTB decreased by -1.5% [95% confidence interval (CI): -2.6, -0.4] associated with scrubber installation and -0.5% (95% CI: -1.6, 0.6) associated with the retirement of coal units at CFPPs. Our findings were imprecise and generally null-to-positive among those living within 0-<4 miles regardless of the intervention type.

Conclusions

Results suggest a reduction of PTB among residents 4-<10 miles of the CFPPs that installed scrubbers.

Estimating Causal Effects of Interventions on Early-life Environmental Exposures Using Observational Data

PURPOSE OF REVIEW

We discuss how epidemiologic studies have used observational data to estimate the effects of potential interventions on early-life environmental exposures. We summarize the value of posing questions about interventions, how a group of techniques known as "g-methods" can provide advantages for estimating intervention effects, and how investigators have grappled with the strong assumptions required for causal inference.

RECENT FINDINGS

We identified nine studies that estimated health effects of hypothetical interventions on early-life environmental exposures. Of these, six examined air pollution. Interventions evaluated by these studies included setting exposure levels at a specific value, shifting exposure distributions, and limiting exposure levels to less than a threshold value. Only one study linked exposure contrasts to a specific intervention on an exposure source, however. There is growing interest in estimating intervention effects of early-life environmental exposures, in part because intervention effects are directly related to possible public health actions. Future studies can build on existing work by linking research questions to specific hypothetical interventions that could reduce exposure levels. We discuss how framing questions around interventions can help overcome some of the barriers to causal inference and how advances related to machine learning may strengthen studies by sidestepping the overly restrictive assumptions of parametric regression models. By leveraging advancements in causal inference and exposure science, an intervention framework for environmental epidemiology can guide actionable solutions to improve children's environmental health.

Source-specific contributions of particulate matter to asthma-related pediatric emergency department utilization

Ambient particulate matter smaller than 2.5 μm (PM_2.5) is associated with different chronic diseases. It is crucial to identify the sources of ambient particulate matter to reduce the impact on health. Still, only a few studies have been linked with specific ambient particulate matter sources. In this study, we estimated the contributions of sources of PM_2.5 and examined their association with daily asthma hospital utilization in Cincinnati, Ohio, USA. We used a model-based clustering method to group days with similar source-specific contributions into six distinct clusters. Specifically, elevated PM_2.5 concentrations occurring on days characterized by low coal combustion contributions showed a significantly reduced risk of hospital utilization for asthma (rate ratio: 0.86, 95% CI: [0.77, 0.95]) compared to other clusters. Reducing coal combustion contribution to PM_2.5 levels could be an effective intervention for lowering asthma-related hospital utilization.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13755-021-00141-z.

Chemical Exposures, Health, and Environmental Justice in Communities Living on the Fenceline of Industry

PURPOSE OF REVIEW

Polluting industries are more likely to be located in low-income communities of color who also experience greater social stressors that may make them more vulnerable than others to the health impacts of toxic chemical exposures. We describe recent developments in assessing pollutant exposures and health threats posed by industrial facilities using or releasing synthetic chemicals to nearby communities in the U.S.

RECENT FINDINGS

More people are living near oil and gas development due to the expansion of unconventional extraction techniques as well as near industrial animal operations, both with suggestive evidence of increased exposure to hazardous pollutants and adverse health effects. Legacy contamination continues to adversely impact a new generation of residents in fenceline communities, with recent studies documenting exposures to toxic metals and poly- and perfluoroalkyl substances (PFASs). Researchers are also giving consideration to acute exposures resulting from inadvertent industrial chemical releases, including those resulting from extreme weather events linked to climate change. Natural experiments of industrial closures or cleanups provide compelling evidence that exposures from industry harm the health of nearby residents. New and legacy industries, coupled with climate change, present unique health risks to communities living near industry due to the release of toxic chemicals. Cumulative impacts from multiple stressors faced by environmental justice communities may amplify these adverse effects.

Detecting the Effects of Early-Life Exposures: Why Fecundity Matters

Prenatal exposures have meaningful effects on health across the lifecourse. Innovations in causal inference have shed new light on these effects. Here, we motivate the importance of innovation in the characterization of fecundity, and prenatal selection in particular. We argue that such innovation is crucial for expanding knowledge of the fetal origins of later life health. Pregnancy loss is common, responsive to environmental factors, and closely related to maternal and fetal health outcomes. As a result, selection into live birth is driven by many of the same exposures that shape the health trajectories of survivors. Lifecourse effects that are inferred without accounting for these dynamics may be significantly distorted by survival bias. We use a set of Monte Carlo simulations with realistic parameters to examine the implications of prenatal survival bias. We find that even in conservatively specified scenarios, true fetal origin effects can be underestimated by 50% or more. In contrast, effects of exposures that reduce the probability of prenatal survival but improve the health of survivors will be overestimated. The absolute magnitude of survival bias can even exceed small effect sizes, resulting in inferences that beneficial exposures are harmful or vice-versa. We also find reason for concern that moderately sized true effects, underestimated due to failure to account for selective survival, are missing from scientific knowledge because they do not clear statistical significance filters. This bias has potential real-world costs; policy decisions about interventions to improve maternal and infant health will be affected by underestimated program impact.

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

Despite improvements in air quality over the past 50 years, ambient air pollution remains an important public health issue in the United States. In particular, emissions from coal-fired power plants still have a substantial impact on both nearby and regional populations. Of particular concern is the potential for this impact to fall disproportionately on low-income communities and communities of color. We conducted a quantitative health impact assessment to estimate the health benefits of the proposed decommissioning of two coal-fired electricity generating stations in the Southern Front Range region of Colorado. We estimated changes in exposures to fine particulate matter and ozone using the Community Multiscale Air Quality model and predicted avoided health impacts and related economic values. We also quantitatively assessed the distribution of these benefits by population-level socioeconomic status. Across the study area, decommissioning the power plants would result in 2 (95% CI: 1-3) avoided premature deaths each year due to reduced PM2.5 exposures and greater reductions in hospitalizations and other morbidities. Health benefits resulting from the modeled shutdowns were greatest in areas with lower educational attainment and other economic indicators. Our results suggest that decommissioning these power plants and replacing them with zero-emissions sources could have broad public health benefits for residents of Colorado, with larger benefits for those that are socially disadvantaged. Our results also suggested that researchers and decision makers need to consider the unique demographics of their study areas to ensure that important opportunities to reduce health disparities associated with point-source pollution.

The unintended impact of ecosystem preservation on greenhouse gas emissions: Evidence from environmental constraints on hydropower development in the United States

Many countries have passed environmental laws aiming at preserving natural ecosystems, such as the Endangered Species Act of 1973 in the United States. Although those regulations seem to have improved preservation, they may have had unintended consequences in energy production. Here we show that while environmental constraints on hydropower may have preserved the wilderness and wildlife by restricting the development of hydroelectric projects, they led to more greenhouse gas emissions. Environmental regulations gave rise to a replacement of hydropower, which is a renewable, relatively low-emitting source of energy, with conventional fossil-fuel power, which is highly polluting. Our estimates indicate that, on average, each megawatt of fossil fuel power-generating capacity added to the grid because of environmental constraints on hydropower development led to an increase in annual carbon dioxide emissions of about 1,400 tons. Environmental regulations focusing only on the preservation of ecosystems appear to have encouraged electric utilities to substitute dirtier fuels for hydropower in electricity generation.