Retirements of Coal and Oil Power Plants in California: Association With Reduced Preterm Birth Among Populations Nearby

Abstract

Coal and oil power plant retirements reduce air pollution nearby, but few studies have leveraged these natural experiments for public health research. We used California Department of Public Health birth records and Energy Information Administration data from 2001-2011 to evaluate the relationship between 8 coal and oil power plant retirements and nearby preterm births ( < 37 weeks gestational age). We conducted a difference-in-differences analysis using adjusted linear mixed models that included 57,005 births-6.5% of which were preterm-to compare the probability of preterm birth before and after power plant retirement among mothers residing within 0-5 km and 5-10 km of the 8 power plants. We found that power plant retirements were associated with a decrease in the proportion of preterm birth within 5 km (-0.019, 95% CI: -0.031, -0.008) and 5-10 km (-0.015, 95% CI: -0.024, -0.007) controlling for secular trends with mothers living 10-20 km away. For the 0-5 km area, this corresponds to a reduction in preterm birth from 7.0% to 5.1%. Subgroup analyses indicated a potentially larger association among non-Hispanic Black and Asian mothers compared to non-Hispanic White and Hispanic mothers and no differences in educational attainment. Future coal and oil power plant retirements may reduce preterm birth among nearby populations.

Comparisons of simple and complex methods for quantifying exposure to individual point source air pollution emissions

“…These are calculated using three unique modeling frameworks (Figure 1 A potential limitation of the two reduced complexity models -HyADS and IDWE -is that they do not, by default, estimate source impacts in terms of air pollution species or physically interpretable concentration units (e.g., µg m -3 or parts per million), and instead provide metrics only interpretable in terms of their relative source impacts. While such relative characterization has proven relevant in some health-outcomes and environmental justice studies 8,11,16 , here we employ a quantitative post-processing procedure to improve the interpretability of the reduced complexity model exposure outputs. This procedure uses results from a second full-scale source impacts modeling platform-the CMAQ-DDM Hybrid-to build statistical models that convert raw HyADS and IDWE exposure metrics to PM2.5 source impacts.…”

“…Despite gains in computational power and algorithm efficiency, the complexity and increasing fidelity of CTMs impedes their application to research questions that would require many model runs. Recent air pollution exposure research has relied on reduced complexity approaches to quantify exposure variability in space and time [7][8][9][10][11][12][13] . These and other epidemiological and environmental justice applications quantify impacts from (many) individual sources over specific time periods and/or consider more refined spatial scales than commonly available in CTMs.…”

Racial disparities in preterm birth in USA: a biosensor of physical and social environmental exposures

“…Additionally, clean-up efforts can improve birth outcomes. Recently, a study of over 57 000 births within 20 miles (36 kilometers) of coal power plants that were retired between 2001 and 2011 demonstrated significant reductions in PTB after the closures with the largest impact among black women 63. Ultimately, exposure reduction of multiple implicated exposures will be required to narrow the racial gap in PTB that has persisted for decades.…”

Technological Approaches to Sustainability

“…They therefore contribute to global warming. On the other hand, like other fossil fuel types, oil and gas-fired power plants can provide seasonal dispatchable generation to balance the use of renewable energy (Casey et al 2018).…”