%0 Journal Article %J R Soc Open Sci %D 2019 %T Discovery of common chemical exposures across three continents using silicone wristbands. %A Holly Dixon %A Armstrong, Georgina %A Michael L Barton %A Alan J Bergmann %A Melissa Bondy %A Mary L Halbleib %A Winnifred Hamilton %A Erin N Haynes %A Julie Herbstman %A Peter D Hoffman %A Paul C Jepson %A Molly Kile %A Laurel D Kincl %A Paul J Laurienti %A Paula E North %A Paulik, L Blair %A Petrosino, Joe %A Points, Gary L %A Carolyn M Poutasse %A Diana Rohlman %A Richard P Scott %A Brian W Smith %A Lane G Tidwell %A Cheryl Walker %A Katrina M Waters %A Kim A Anderson %X
To assess differences and trends in personal chemical exposure, volunteers from 14 communities in Africa (Senegal, South Africa), North America (United States (U.S.)) and South America (Peru) wore 262 silicone wristbands. We analysed wristband extracts for 1530 unique chemicals, resulting in 400 860 chemical data points. The number of chemical detections ranged from 4 to 43 per wristband, with 191 different chemicals detected, and 1339 chemicals were not detected in any wristband. No two wristbands had identical chemical detections. We detected 13 potential endocrine disrupting chemicals in over 50% of all wristbands and found 36 chemicals in common between chemicals detected in three geographical wristband groups (Africa, North America and South America). U.S. children (less than or equal to 11 years) had the highest percentage of flame retardant detections compared with all other participants. Wristbands worn in Texas post-Hurricane Harvey had the highest mean number of chemical detections (28) compared with other study locations (10-25). Consumer product-related chemicals and phthalates were a high percentage of chemical detections across all study locations (36-53% and 18-42%, respectively). Chemical exposures varied among individuals; however, many individuals were exposed to similar chemical mixtures. Our exploratory investigation uncovered personal chemical exposure trends that can help prioritize certain mixtures and chemical classes for future studies.
%B R Soc Open Sci %V 6 %P 181836 %8 02/2019 %G eng %N 2 %R 10.1098/rsos.181836 %0 Journal Article %J Mar Pollut Bull %D 2019 %T A passive sampling model to predict PAHs in butter clams (Saxidomus giganteus), a traditional food source for Native American tribes of the Salish Sea Region. %A D James Minick %A Paulik, L Blair %A Richard P Scott %A Molly Kile %A Diana Rohlman %A Kim A Anderson %K Animals %K Bivalvia %K Consumer Product Safety %K Environmental Monitoring %K Food Contamination %K Humans %K Indians, North American %K Polycyclic Aromatic Hydrocarbons %K Shellfish %K Water Pollutants, Chemical %XNative Americans face disproportionate exposures to environmental pollution through traditional subsistence practices including shellfish harvesting. In this study, the collection of butter clams (Saxidomus giganteus) was spatially and temporally paired with deployment of sediment pore water passive samplers at 20 locations in the Puget Sound region of the Salish Sea in the Pacific Northwest, USA, within adjudicated usual and accustomed tribal fishing grounds and stations. Clams and passive samplers were analyzed for 62 individual PAHs. A linear regression model was constructed to predict PAH concentrations in the edible fraction of butter clams from the freely dissolved fraction (C) in porewater. PAH concentrations can be predicted within a factor of 1.9 ± 0.2 on average from the freely dissolved PAH concentration in porewater using the following equation: PAHClam=4.1±0.1×PAHporewater This model offers a simplified, cost effective, and low impact approach to assess contaminant levels in butter clams which are an important traditional food.
%B Mar Pollut Bull %V 145 %P 28-35 %8 2019 Aug %G eng %R 10.1016/j.marpolbul.2019.05.020 %0 Journal Article %J Environ Pollut %D 2018 %T Environmental and individual PAH exposures near rural natural gas extraction. %A Paulik, L Blair %A Kevin A Hobbie %A Diana Rohlman %A Brian W Smith %A Richard P Scott %A Laurel D Kincl %A Erin N Haynes %A Kim A Anderson %K Air Pollutants %K Air Pollution %K Environmental Exposure %K Environmental Monitoring %K Humans %K Linear Models %K Natural Gas %K Oil and Gas Fields %K Petroleum %K Polycyclic Aromatic Hydrocarbons %K Pyrenes %K Silicones %K Tandem Mass Spectrometry %XNatural gas extraction (NGE) has expanded rapidly in the United States in recent years. Despite concerns, there is little information about the effects of NGE on air quality or personal exposures of people living or working nearby. Recent research suggests NGE emits polycyclic aromatic hydrocarbons (PAHs) into air. This study used low-density polyethylene passive samplers to measure concentrations of PAHs in air near active (n = 3) and proposed (n = 2) NGE sites. At each site, two concentric rings of air samplers were placed around the active or proposed well pad location. Silicone wristbands were used to assess personal PAH exposures of participants (n = 19) living or working near the sampling sites. All samples were analyzed for 62 PAHs using GC-MS/MS, and point sources were estimated using the fluoranthene/pyrene isomer ratio. ∑PAH was significantly higher in air at active NGE sites (Wilcoxon rank sum test, p < 0.01). PAHs in air were also more petrogenic (petroleum-derived) at active NGE sites. This suggests that PAH mixtures at active NGE sites may have been affected by direct emissions from petroleum sources at these sites. ∑PAH was also significantly higher in wristbands from participants who had active NGE wells on their properties than from participants who did not (Wilcoxon rank sum test, p < 0.005). There was a significant positive correlation between ∑PAH in participants' wristbands and ∑PAH in air measured closest to participants' homes or workplaces (simple linear regression, p < 0.0001). These findings suggest that living or working near an active NGE well may increase personal PAH exposure. This work also supports the utility of the silicone wristband to assess personal PAH exposure.
%B Environ Pollut %V 241 %P 397-405 %8 2018 Oct %G eng %R 10.1016/j.envpol.2018.05.010