Environmental Influences on Sleep in the California Teachers Study Cohort.

Only two-thirds of Americans meet the recommended 7 hours of sleep nightly. Insufficient sleep and circadian disruption have been associated with adverse health outcomes, including diabetes and cardiovascular disease. Several environmental disruptors of sleep have been reported, such as artificial light at night (ALAN) and noise. These studies tended to evaluate exposures individually. We evaluated several spatially derived environmental exposures (ALAN, noise, green space, and air pollution) and self-reported sleep outcomes obtained in 2012-2015 in a large cohort of 51,562 women in the California Teachers Study. Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated for sleep duration and latency. After adjusting for age, race/ethnicity, chronotype, use of sleep medication, and self-reported trouble sleeping, ALAN (per 5 millicandela (mcd)/m2 luminance, OR = 1.13, 95% CI: 1.07, 1.20) and air pollution (per 5 µg/m3 PM2.5, OR = 1.06, 95% CI: 1.04, 1.09) were associated with shorter sleep duration (<7 hours), and noise was associated with longer latency (>15 minutes) (per 10 decibels, OR = 1.05, 95% CI: 1.01, 1.10). Green space was associated with increased duration (per 0.1 units, OR = 0.41, 95% CI: 0.28, 0.60) and decreased latency (per 0.1 units, OR = 0.55, 95% CI: 0.39, 0.78). Further research is necessary to understand how these and other exposures (e.g., diet) perturb an individuals' inherited sleep patterns and contribute to downstream health outcomes.

Predicting ambient PM2.5 concentrations in Ulaanbaatar, Mongolia with machine learning approaches.

BACKGROUND: Accurately assessing individual ambient air pollution exposure is a crucial part of epidemiological studies looking at the adverse health effect of poor air quality. This is particularly challenging in developing countries with high levels of air pollution, mostly due to sparse monitoring networks with a lack of consistent data. METHODS: We evaluated the performance of six different machine learning algorithms in predicting fine particulate matter (PM2.5) concentrations in Ulaanbaatar, Mongolia using data between 2010 and 2018. We found that the algorithms produce robust results based on performance metrics. RESULTS: Random forest (RF) and gradient boosting models performed the best with leave-one-location-out cross-validated R2 of 0.82 for when using data from the entire study period. After applying tuned models on the hold-out test set, R2 increased to 0.96 for the RF and 0.90 for the gradient boosting model. We also predicted PM2.5 concentrations for each administrative area (khoroo) of the city using RF and maps of predictions show spatiotemporal variations that are in line with the location of the high-emission area (ger district), city center, and population density. CONCLUSION: Our results provide evidence of the advantage and feasibility of machine learning approaches in predicting ambient PM2.5 levels in a setting with limited resources and extreme air pollution levels.

Flaring from Unconventional Oil and Gas Development and Birth Outcomes in the Eagle Ford Shale in South Texas.

BACKGROUND: Prior studies suggest exposure to oil and gas development (OGD) adversely affects birth outcomes, but no studies have examined flaring-the open combustion of natural gas-from OGD. OBJECTIVES: We investigated whether residential proximity to flaring from OGD was associated with shorter gestation and reduced fetal growth in the Eagle Ford Shale of south Texas. METHODS: We conducted a retrospective cohort study using administrative birth records from 2012 to 2015 (N=23,487) and satellite observations of flaring activity during pregnancy within 5km of maternal residence. Multivariate logistic and linear regression models were used to estimate associations between four outcomes (preterm birth, small-for-gestational age, continuous gestational age, and term birthweight) and exposure to a low (1-9) or high (≥10) number of nightly flare events, as compared with no exposure, while controlling for known maternal risk factors. We also examined associations with the number of oil and gas wells within 5km using data from DrillingInfo (now Enverus). RESULTS: Exposure to a high number of nightly flare events was associated with a 50% higher odds of preterm birth [odds ratio (OR)=1.50 (95% CI: 1.23, 1.83)] and shorter gestation [mean difference=-1.9 (95% CI: -2.8, -0.9) d] compared with no exposure. Effect estimates were slightly reduced after adjustment for the number of wells within 5km. In stratified models these associations were present only among Hispanic women. Flaring and fetal growth outcomes were not significantly associated. Women exposed to a high number of wells (fourth quartile, ≥27) vs. no wells within 5km had a higher odds of preterm birth [OR=1.31 (95% CI: 1.14, 1.49)], shorter gestation [-1.3 (95% CI: -1.9, -0.8) d], and lower average birthweight [-19.4 (95% CI: -36.7, -2.0) g]. DISCUSSION: Our study suggests exposure to flaring from OGD is associated with an increased risk of preterm birth. Our findings need to be confirmed in other populations. https://doi.org/10.1289/EHP6394.

Environmental Justice Dimensions of Oil and Gas Flaring in South Texas: Disproportionate Exposure among Hispanic communities.

Unconventional extraction techniques including hydraulic fracturing or "fracking" have led to a boom in oil and gas production in the Eagle Ford shale play, Texas, one of the most productive regions in the United States. Nearly 400000 people live within 5 km of an unconventional oil or gas well in this largely rural area. Flaring is associated primarily with unconventional oil wells and is an increasingly common practice in the Eagle Ford to dispose of excess gas through combustion. Flares can operate continuously for months and release hazardous air pollutants such as particulate matter and volatile organic compounds in addition to causing light and noise pollution and noxious odors. We estimated ethnic disparities in exposure to flaring using satellite observations from the Visible Infrared Imaging Spectroradiometer between March 2012-December 2016. Census blocks with majority Hispanic (>60%) populations were exposed to twice as many nightly flare events within 5 km as those with <20% Hispanics. We found that Hispanics were exposed to more flares despite being less likely than non-Hispanic White residents to live near unconventional oil and gas wells. Our findings suggest Hispanics are disproportionately exposed to flares in the Eagle Ford shale, a pattern known as environmental injustice, which could contribute to disparities in air pollution and other nuisance exposures.

Characterizing Flaring from Unconventional Oil and Gas Operations in South Texas Using Satellite Observations.

Over the past decade, increases in high-volume hydraulic fracturing for oil and gas extraction in the United States have raised concerns with residents living near wells. Flaring, or the combustion of petroleum products into the open atmosphere, is a common practice associated with oil and gas exploration and production, and has been under-examined as a potential source of exposure. We leveraged data from the Visible Infrared Imaging Spectroradiometer (VIIRS) Nightfire satellite product to characterize the extent of flaring in the Eagle Ford Shale region of south Texas, one of the most productive in the nation. Spatiotemporal hierarchical clustering identified flaring sources, and a regression-based approach combining VIIRS information with reported estimates of vented and flared gas from the Railroad Commission of Texas enabled estimation of flared gas volume at each flare. We identified 43887 distinct oil and gas flares in the study region from 2012 to 2016, with a peak in activity in 2014 and an estimated 4.5 billion cubic meters of total gas volume flared over the study period. A comparison with well permit data indicated the majority of flares were associated with oil-producing (82%) and horizontally drilled (92%) wells. Of the 49 counties in the region, 5 accounted for 71% of the total flaring. Our results suggest flaring may be a significant environmental exposure in parts of this region.