Estimates of Inhalation Exposures to Oil-Related Components on the Supporting Vessels During the Deepwater Horizon Oil Spill
Year: 2020
Type: article
Abstract: The Deepwater Horizon oil spill response and clean-up (OSRC) involved over 9000 large and small vessels deployed in waters of the Gulf of Mexico across four states (Alabama, Florida, Louisiana, and Mississippi). For the GuLF STUDY, we developed exposure estimates of oil-related components for many work groups to capture a wide range of OSRC operations on these vessels, such as supporting the four rig vessels charged with stopping the spill at the wellhead; skimming oil; in situ burning of oil; absorbing and containing oil by boom; and environmental monitoring. Work groups were developed by: (i) vessel activity; (ii) location (area of the Gulf or state); and (iii) time period. Using Bayesian methods, we computed exposure estimates for these groups for: total hydrocarbons measured as total petroleum hydrocarbons (THC), benzene, toluene, ethylbenzene, xylene, and n-hexane (BTEX-H). Estimates of the arithmetic means for THC ranged from 0.10 ppm [95% credible interval (CI) 0.04, 0.38 ppm] in time periods 2 and 3 (16 July-30 September 2010) to 15.06 ppm (95% CI 10.74, 22.41 ppm) in time period 1a (22 April-15 May 2010). BTEX-H estimates were substantially lower (in the parts per billion range). Exposure levels generally fell over time and differed statistically by activity, location, and time for some groups. These exposure estimates have been used to develop job-exposure matrices for the GuLF STUDY.
Institutions: Drexel University, West Virginia University, Johns Hopkins University, University of California, Los Angeles, National Cancer Institute, Division of Cancer Epidemiology and Genetics, National Institutes of Health, National Institute of Environmental Health Sciences, University of North Carolina at Chapel Hill
Language: English
Subfield: Pollution
Field: Environmental Science
Domain: Physical Sciences
SDG: Life below water
Open Access status: bronze
Awards: G1017297203, Collaborative Research: Hierarchical Sparsity-Inducing Gaussian Process Models for Bayesian Inference on Large Spatiotemporal Datasets, G1917857442, G3060169895, III: Medium: Collaborative Research: Bayesian Modeling and Inference for Quantifying Terrestrial Ecosystem Functions, G4431743973, G4935303797, G5066532509, G5733225247, G5804557140, G5839942973, G7034721383, HEALTH AND SAFETY TRAINING MODULE FOR VIETNAMESE NAIL SALON WORKERS: A FEASIBILITY STUDY, G7807069925, G8641591732, G9000062673, G9000198917, G9000304877, UNC Center for Environmental Health and Susceptibility
OpenAlex ID: W3139974345