Estimation of exposure to particulate matter in pregnant individuals living in an area of unconventional oil and gas operations: Findings from the EXPERIVA study.

Autor: Caron-Beaudoin, Élyse, Subramanian, Amrita, Daley, Coreen, Lakshmanan, Siddharthan, Whitworth, Kristina W.
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Zdroj: Journal of Toxicology & Environmental Health: Part A; 2023, Vol. 86 Issue 12, p383-396, 14p
Abstrakt: Northeastern British Columbia (Canada) is an area of oil and gas exploitation, which may result in release of fine (PM2.5) and inhalable (PM10) particulate matter. The aims of this study were to: 1) apply extrapolation methods to estimate exposure to PM2.5 and PM10 concentrations among EXPERIVA (Exposures in the Peace River Valley study) participants using air quality data archives; and 2) conduct exploratory analyses to investigate correlation between PM exposure and metrics of oil and gas wells density, proximity, and activity. Gestational exposure to PM2.5 and PM10 of the EXPERIVA participants (n = 85) was estimated by averaging the concentrations measured at the closest or three closest air monitoring stations during the pregnancy period. Drilling metrics were calculated based upon the density and proximity of conventional and unconventional oil and gas wells to each participant's residence. Phase-specific metrics were determined for unconventional wells. The correlations (ρ) between exposure to PM2.5 and PM10 and metrics of well density/proximity were determined using Spearman's rank correlation test. Estimated PM ambient air concentrations ranged between 4.73 to 12.13 µg/m3 for PM2.5 and 7.14 to 26.61 µg/m3 for PM10. Conventional wells metrics were more strongly correlated with PM10 estimations (ρ between 0.28 and 0.79). Unconventional wells metrics for all phases were positively correlated with PM2.5 estimations (ρ between 0.23 and 0.55). These results provide evidence of a correlation between density and proximity of oil and gas wells and estimated PM exposure in the EXPERIVA participants. [ABSTRACT FROM AUTHOR]
Databáze: Complementary Index