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Clark CJ, Xiong B, Soriano MA, Gutchess K, Siegel HG, Ryan EC, Johnson NP, Cassell K, Elliott EG, Li Y, Cox AJ, Bugher N, Glist L, Brenneis RJ, Sorrentino KM, Plano J, Ma X, Warren JL, Plata DL, Saiers JE, Deziel NC. Assessing Unconventional Oil and Gas Exposure in the Appalachian Basin: Comparison of Exposure Surrogates and Residential Drinking Water Measurements. Environ Sci Technol 2022; 56:1091-1103. [PMID: 34982938 PMCID: PMC10259677 DOI: 10.1021/acs.est.1c05081] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/17/2023]
Abstract
Health studies report associations between metrics of residential proximity to unconventional oil and gas (UOG) development and adverse health endpoints. We investigated whether exposure through household groundwater is captured by existing metrics and a newly developed metric incorporating groundwater flow paths. We compared metrics with detection frequencies/concentrations of 64 organic and inorganic UOG-related chemicals/groups in residential groundwater from 255 homes (Pennsylvania n = 94 and Ohio n = 161). Twenty-seven chemicals were detected in ≥20% of water samples at concentrations generally below U.S. Environmental Protection Agency standards. In Pennsylvania, two organic chemicals/groups had reduced odds of detection with increasing distance to the nearest well: 1,2-dichloroethene and benzene (Odds Ratio [OR]: 0.46, 95% confidence interval [CI]: 0.23-0.93) and m- and p-xylene (OR: 0.28, 95% CI: 0.10-0.80); results were consistent across metrics. In Ohio, the odds of detecting toluene increased with increasing distance to the nearest well (OR: 1.48, 95% CI: 1.12-1.95), also consistent across metrics. Correlations between inorganic chemicals and metrics were limited (all |ρ| ≤ 0.28). Limited associations between metrics and chemicals may indicate that UOG-related water contamination occurs rarely/episodically, more complex metrics may be needed to capture drinking water exposure, and/or spatial metrics in health studies may better reflect exposure to other stressors.
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Affiliation(s)
- Cassandra J Clark
- Yale School of Public Health, Department of Environmental Health Sciences, 60 College Street, New Haven, Connecticut 06510, United States
| | - Boya Xiong
- Massachusetts Institute of Technology, Department of Civil and Environmental Engineering, Parsons Laboratory, 15 Vassar Street, Cambridge, Massachusetts 02139, United States
- University of Minnesota, Department of Civil, Environmental and Geo-Engineering, 500 Pillsbury Dr. SE, Minneapolis, Minnesota 55455, United States
| | - Mario A Soriano
- Yale School of the Environment, 195 Prospect Street, New Haven, Connecticut 06511, United States
| | - Kristina Gutchess
- Yale School of the Environment, 195 Prospect Street, New Haven, Connecticut 06511, United States
| | - Helen G Siegel
- Yale School of the Environment, 195 Prospect Street, New Haven, Connecticut 06511, United States
| | - Emma C Ryan
- Tufts University, Department of Public Health and Community Medicine, 136 Harrison Avenue, Boston, Massachusetts 02111, United States
| | - Nicholaus P Johnson
- Yale School of Public Health, Department of Environmental Health Sciences, 60 College Street, New Haven, Connecticut 06510, United States
| | - Kelsie Cassell
- Yale School of Public Health, Department of Epidemiology of Microbial Diseases, 60 College Street, New Haven, Connecticut 06510, United States
| | - Elise G Elliott
- Yale School of Public Health, Department of Environmental Health Sciences, 60 College Street, New Haven, Connecticut 06510, United States
- Harvard T.H. Chan School of Public Health, Department of Environmental Health, Boston, Massachusetts 02115, USA
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts 02115, United States
| | - Yunpo Li
- Massachusetts Institute of Technology, Department of Civil and Environmental Engineering, Parsons Laboratory, 15 Vassar Street, Cambridge, Massachusetts 02139, United States
| | - Austin J Cox
- Massachusetts Institute of Technology, Department of Civil and Environmental Engineering, Parsons Laboratory, 15 Vassar Street, Cambridge, Massachusetts 02139, United States
| | - Nicolette Bugher
- Massachusetts Institute of Technology, Department of Civil and Environmental Engineering, Parsons Laboratory, 15 Vassar Street, Cambridge, Massachusetts 02139, United States
| | - Lukas Glist
- Massachusetts Institute of Technology, Department of Civil and Environmental Engineering, Parsons Laboratory, 15 Vassar Street, Cambridge, Massachusetts 02139, United States
| | - Rebecca J Brenneis
- Massachusetts Institute of Technology, Department of Civil and Environmental Engineering, Parsons Laboratory, 15 Vassar Street, Cambridge, Massachusetts 02139, United States
| | - Keli M Sorrentino
- Center for Perinatal, Pediatric and Environmental Epidemiology, Yale University Schools of Public Health and Medicine, 1 Church Street, New Haven, Connecticut 06510, United States
| | - Julie Plano
- Center for Perinatal, Pediatric and Environmental Epidemiology, Yale University Schools of Public Health and Medicine, 1 Church Street, New Haven, Connecticut 06510, United States
| | - Xiaomei Ma
- Yale School of Public Health, Department of Chronic Disease Epidemiology, 60 College Street, New Haven, Connecticut 06510, United States
| | - Joshua L Warren
- Yale School of Public Health, Department of Biostatistics, 60 College Street, New Haven, Connecticut 06510, United States
| | - Desiree L Plata
- Massachusetts Institute of Technology, Department of Civil and Environmental Engineering, Parsons Laboratory, 15 Vassar Street, Cambridge, Massachusetts 02139, United States
| | - James E Saiers
- Yale School of the Environment, 195 Prospect Street, New Haven, Connecticut 06511, United States
| | - Nicole C Deziel
- Yale School of Public Health, Department of Environmental Health Sciences, 60 College Street, New Haven, Connecticut 06510, United States
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