Fine particulate matter and incident coronary heart disease events up to 10 years of follow-up among Deepwater Horizon oil spill workers.

BACKGROUND: During the 2010 Deepwater Horizon (DWH) disaster, in-situ burning and flaring were conducted to remove oil from the water. Workers near combustion sites were potentially exposed to burning-related fine particulate matter (PM2.5). Exposure to PM2.5 has been linked to increased risk of coronary heart disease (CHD), but no study has examined the relationship among oil spill workers. OBJECTIVES: To investigate the association between estimated PM2.5 from burning/flaring of oil/gas and CHD risk among the DWH oil spill workers. METHODS: We included workers who participated in response and cleanup activities on the water during the DWH disaster (N = 9091). PM2.5 exposures were estimated using a job-exposure matrix that linked modelled PM2.5 concentrations to detailed DWH spill work histories provided by participants. We ascertained CHD events as the first self-reported physician-diagnosed CHD or a fatal CHD event that occurred after each worker's last day of burning exposure. We estimated hazard ratios (HR) and 95% confidence intervals (95%CI) for the associations between categories of average or cumulative daily maximum PM2.5 exposure (versus a referent category of water workers not near controlled burning) and subsequent CHD. We assessed exposure-response trends by examining continuous exposure parameters in models. RESULTS: We observed increased CHD hazard among workers with higher levels of average daily maximum exposure (low vs. referent: HR = 1.26, 95% CI: 0.93, 1.70; high vs. referent: HR = 2.11, 95% CI: 1.08, 4.12; per 10 µg/m3 increase: HR = 1.10, 95% CI: 1.02, 1.19). We also observed suggestively elevated HRs among workers with higher cumulative daily maximum exposure (low vs. referent: HR = 1.19, 95% CI: 0.68, 2.08; medium vs. referent: HR = 1.38, 95% CI: 0.88, 2.16; high vs. referent: HR = 1.44, 95% CI: 0.96, 2.14; per 100 µg/m3-d increase: HR = 1.03, 95% CI: 1.00, 1.05). CONCLUSIONS: Among oil spill workers, exposure to PM2.5 from flaring/burning of oil/gas was associated with increased risk of CHD.

Exposure to volatile hydrocarbons and neurologic function among oil spill workers up to 6 years after the Deepwater Horizon disaster.

BACKGROUND: During the 2010 Deepwater Horizon (DWH) disaster, oil spill response and cleanup (OSRC) workers were exposed to toxic volatile components of crude oil. Few studies have examined exposure to individual volatile hydrocarbon chemicals below occupational exposure limits in relation to neurologic function among OSRC workers. OBJECTIVES: To investigate the association of several spill-related chemicals (benzene, toluene, ethylbenzene, xylene, n-hexane, i.e., BTEX-H) and total petroleum hydrocarbons (THC) with neurologic function among DWH spill workers enrolled in the Gulf Long-term Follow-up Study. METHODS: Cumulative exposure to THC and BTEX-H across the oil spill cleanup period were estimated using a job-exposure matrix that linked air measurement data to detailed self-reported DWH OSRC work histories. We ascertained quantitative neurologic function data via a comprehensive test battery at a clinical examination that occurred 4-6 years after the DWH disaster. We used multivariable linear regression and modified Poisson regression to evaluate relationships of exposures (quartiles (Q)) with 4 neurologic function measures. We examined modification of the associations by age at enrollment (<50 vs. ≥50 years). RESULTS: We did not find evidence of adverse neurologic effects from crude oil exposures among the overall study population. However, among workers ≥50 years of age, several individual chemical exposures were associated with poorer vibrotactile acuity of the great toe, with statistically significant effects observed in Q3 or Q4 of exposures (range of log mean difference in Q4 across exposures: 0.13-0.26 µm). We also observed suggestive adverse associations among those ≥ age 50 years for tests of postural stability and single-leg stance, although most effect estimates did not reach thresholds of statistical significance (p < 0.05). CONCLUSIONS: Higher exposures to volatile components of crude oil were associated with modest deficits in neurologic function among OSRC workers who were age 50 years or older at study enrollment.

Lung function in oil spill responders 4-6 years after the Deepwater Horizon disaster.

Oil spill response and clean-up (OSRC) workers were exposed to hazardous airborne chemicals following the 2010 Deepwater Horizon disaster. The aim of this study was to evaluate lung function in workers 4-6 years following the disaster using a prospective cohort. Participants who completed two spirometry test sessions 1-3 years, and 4-6 years after the spill (N = 1,838) were included and forced expiratory volume in 1 s (FEV1; ml), forced vital capacity (FVC; ml), and ratio (FEV1/FVC; %) determined. Linear mixed models were utilized to estimate relationships between OSRC exposures and lung function 4-6 years after the spill and changes since the prior measurement. Despite suggestive reduced lung function at 1-3 years, at the  4-6-year exam workers with total hydrocarbon (THC) exposure 1-2.99 ppm and ≥3 ppm compared to those with ≤0.29 ppm exhibited higher FEV1 (ß: 108 ml, 95% CI: 17, 198) and (ß: 118 ml, 95% CI: 5, 232), respectively. Compared with support workers, those in higher exposed jobs displayed greater improvement in FEV1 between visits: cleanup on water (ß: 143 ml, 95% CI: 35, 250), operations (ß: 132 ml, 95% CI: 30, 234) and response (ß: 149 ml, 95% CI: 43, 256). Greater FEV1 improvement was also associated with higher versus the lowest level THC exposure: 1-2.99 ppm (ß: 134 ml, 95% CI: 57, 210) and ≥3 ppm (ß: 205 ml, 95% CI: 109, 301). Lung function decrements seen shortly after the spill were no longer apparent 4-6 years later, with the greatest improvement among those with the highest exposures.

Exposure to Total Hydrocarbons During Cleanup of the Deepwater Horizon Oil Spill and Risk of Heart Attack Across 5 Years of Follow-up.

Exposure to total hydrocarbons (THC) and volatile organic compounds from air pollution is associated with risk of coronary heart disease. THC exposure from oil spills might be similarly associated, but no research has examined this. We assessed the relationship between THC exposure during the response and cleanup of the Deepwater Horizon oil spill (Gulf of Mexico) and heart attack risk among 24,375 oil spill workers enrolled in the Gulf Long-Term Follow-up Study. There were 312 first heart attacks (self-reported physician-diagnosed myocardial infarction, or fatal coronary heart disease) ascertained during the study period (2010-2016). THC exposures were estimated using a job-exposure matrix incorporating self-reported activities and personal air measurements. We used Cox proportional hazards regression to estimate hazard ratios, with inverse-probability weights to account for confounding and censoring. Maximum THC levels of ≥0.30 parts per million (ppm) were associated with heart attack risk, with a 1.8-fold risk for exposure of ≥3.00 ppm versus <0.30 ppm (hazard ratio = 1.81, 95% confidence interval: 1.11, 2.95). The risk difference for highest versus lowest THC level was 10 excess cases per 1,000 workers. This is the first study of the persistent health impacts of THC exposure during oil spill work, and results support increased protection against oil exposure during cleanup of future spills.

Deepwater Horizon oil spill exposures and neurobehavioral function in GuLF study participants.

INTRODUCTION: The 2010 Deepwater Horizon (DWH) disaster exposed tens of thousands of oil spill response and cleanup (OSRC) workers to hydrocarbons and other hazardous chemicals. Some hydrocarbons, such as toluene and hexane, have been found to have acute adverse effects on the central nervous system in occupational settings. However, no studies have examined the association between oil spill exposures and neurobehavioral function. METHODS: We used data from the Gulf Long-term Follow-up Study, a cohort of adults who worked on the DWH response and cleanup. Total hydrocarbon (THC) exposure attributed to oil spill cleanup work was estimated from a job-exposure matrix linking air measurement data to detailed cleanup work histories. Participants were also categorized into 6 job categories, or OSRC classes, based on their activity with the highest exposure. Neurobehavioral performance was assessed at a clinical exam 4-6 years after the spill. We used multivariable linear regression to evaluate relationships of ordinal THC levels and OSRC classes with 16 neurobehavioral outcomes. RESULTS: We found limited evidence of associations between THC levels or OSRC classes and decreased neurobehavioral function, including attention, memory, and executive function. Workers exposed to ≥3 ppm THC scored significantly worse (difference1.0-2.9ppm = -0.39, 95% confidence interval (CI) = -0.74, -0.04) than workers exposed to <0.30 ppm THC for the digit span forward count test. There was also a possible threshold effect above 1 ppm THC for symbol digit test total errors (difference1.0-2.9ppm = -0.56 (95% CI = -1.13, -0.003), difference≥3.0ppm = -0.55 (95% CI = -1.20, 0.10)). Associations appeared to be stronger in men than in women. A summary latency measure suggested an association between more highly exposed jobs (especially support of operations workers) and decreased neurobehavioral function. CONCLUSION: OSRC-related exposures were associated with modest decreases in neurobehavioral function, especially attention, memory, and executive function.

Lung Function in Oil Spill Response Workers 1-3 Years After the Deepwater Horizon Disaster.

BACKGROUND: Little is known about the effects of inhalation exposures on lung function among workers involved in the mitigation of oil spills. Our objective was to determine the relationship between oil spill response work and lung function 1-3 years after the Deepwater Horizon (DWH) disaster. METHODS: We evaluated spirometry for 7,775 adults living in the Gulf states who either participated in DWH response efforts (workers) or received safety training but were not hired (nonworkers). At an enrollment interview, we collected detailed work histories including information on potential exposure to dispersants and burning oil/gas. We assessed forced expiratory volume in 1 second (FEV1; mL), forced vital capacity (FVC; mL), and the ratio (FEV1/FVC%) for differences by broad job classes and exposure to dispersants or burning oil/gas using multivariable linear and modified Poisson regression. RESULTS: We found no differences between workers and nonworkers. Among workers, we observed a small decrement in FEV1 (Beta, -71 mL; 95% confidence interval [CI], -127 to -14) in decontamination workers compared with support workers. Workers with high potential exposure to burning oil/gas had reduced lung function compared with unexposed workers: FEV1 (Beta, -183 mL; 95% CI, -316 to -49) and FEV1/FVC (Beta, -1.93%; 95% CI, -3.50 to -0.36), and an elevated risk of having a FEV1/FVC in the lowest tertile (prevalence ratio, 1.38; 95% CI, 0.99 to 1.92). CONCLUSIONS: While no differences in lung function were found between workers and nonworkers, lung function was reduced among decontamination workers and workers with high exposure to burning oil/gas compared with unexposed workers.

Multivariate left-censored Bayesian model for predicting exposure using multiple chemical predictors.

Environmental health exposures to airborne chemicals often originate from chemical mixtures. Environmental health professionals may be interested in assessing exposure to one or more of the chemicals in these mixtures, but often exposure measurement data are not available, either because measurements were not collected/assessed for all exposure scenarios of interest or because some of the measurements were below the analytical methods' limits of detection (i.e. censored). In some cases, based on chemical laws, two or more components may have linear relationships with one another, whether in a single or in multiple mixtures. Although bivariate analyses can be used if the correlation is high, often correlations are low. To serve this need, this paper develops a multivariate framework for assessing exposure using relationships of the chemicals present in these mixtures. This framework accounts for censored measurements in all chemicals, allowing us to develop unbiased exposure estimates. We assessed our model's performance against simpler models at a variety of censoring levels and assessed our model's 95% coverage. We applied our model to assess vapor exposure from measurements of three chemicals in crude oil taken on the Ocean Intervention III during the Deepwater Horizon oil spill response and clean-up.

Estimating diesel fuel exposure for a plumber repairing an underground pipe.

We estimated the diesel fuel exposure of a plumber repairing an underground water line leak at a truck stop. The repair work was performed over three days during which the plumber spent most of his time in a pit filled with a mixture of water and diesel fuel. Thus, the plumber was exposed via both the inhalation and dermal routes. While previously asymptomatic, he was diagnosed with acute renal failure 35 days after working at this site. No measurements were available for estimating either inhalation or dermal exposures or the cumulative dose and, therefore, two different approaches were used that were based on simple models of the exposure scenario. The first approach used the ideal gas law with the vapor pressure of the diesel fuel mixture to estimate a saturation vapor concentration, while the second one used a mass balance of the petroleum hydrocarbon component of diesel fuel in conjunction with the Henry's Law constant for this mixture. These inhalation exposure estimates were then adjusted to account for the limited ventilation in a confined space. The inhalation exposure concentrations predicted when handling the water layer alone is much lower than that expected from the organic layer. This case study illustrates the large differences in inhalation exposure associated with volatile organic layers and aqueous solution containing these chemicals. The estimate of dermal exposure was negligible compared to the inhalation exposure because the skin presents a much smaller surface area of exposure to the contaminant compared to the lungs. The methodology presented here is useful for situations where little information is available for more formal mathematical exposure modeling, but where adjustments to the worst-case exposures, estimated simply, can provide reasonable exposure estimates.

A Comparison of the ß-Substitution Method and a Bayesian Method for Analyzing Left-Censored Data.

Classical statistical methods for analyzing exposure data with values below the detection limits are well described in the occupational hygiene literature, but an evaluation of a Bayesian approach for handling such data is currently lacking. Here, we first describe a Bayesian framework for analyzing censored data. We then present the results of a simulation study conducted to compare the ß-substitution method with a Bayesian method for exposure datasets drawn from lognormal distributions and mixed lognormal distributions with varying sample sizes, geometric standard deviations (GSDs), and censoring for single and multiple limits of detection. For each set of factors, estimates for the arithmetic mean (AM), geometric mean, GSD, and the 95th percentile (X0.95) of the exposure distribution were obtained. We evaluated the performance of each method using relative bias, the root mean squared error (rMSE), and coverage (the proportion of the computed 95% uncertainty intervals containing the true value). The Bayesian method using non-informative priors and the ß-substitution method were generally comparable in bias and rMSE when estimating the AM and GM. For the GSD and the 95th percentile, the Bayesian method with non-informative priors was more biased and had a higher rMSE than the ß-substitution method, but use of more informative priors generally improved the Bayesian method's performance, making both the bias and the rMSE more comparable to the ß-substitution method. An advantage of the Bayesian method is that it provided estimates of uncertainty for these parameters of interest and good coverage, whereas the ß-substitution method only provided estimates of uncertainty for the AM, and coverage was not as consistent. Selection of one or the other method depends on the needs of the practitioner, the availability of prior information, and the distribution characteristics of the measurement data. We suggest the use of Bayesian methods if the practitioner has the computational resources and prior information, as the method would generally provide accurate estimates and also provides the distributions of all of the parameters, which could be useful for making decisions in some applications.

Using checklists and algorithms to improve qualitative exposure judgment accuracy.

Most exposure assessments are conducted without the aid of robust personal exposure data and are based instead on qualitative inputs such as education and experience, training, documentation on the process chemicals, tasks and equipment, and other information. Qualitative assessments determine whether there is any follow-up, and influence the type that occurs, such as quantitative sampling, worker training, and implementing exposure and risk management measures. Accurate qualitative exposure judgments ensure appropriate follow-up that in turn ensures appropriate exposure management. Studies suggest that qualitative judgment accuracy is low. A qualitative exposure assessment Checklist tool was developed to guide the application of a set of heuristics to aid decision making. Practicing hygienists (n = 39) and novice industrial hygienists (n = 8) were recruited for a study evaluating the influence of the Checklist on exposure judgment accuracy. Participants generated 85 pre-training judgments and 195 Checklist-guided judgments. Pre-training judgment accuracy was low (33%) and not statistically significantly different from random chance. A tendency for IHs to underestimate the true exposure was observed. Exposure judgment accuracy improved significantly (p <0.001) to 63% when aided by the Checklist. Qualitative judgments guided by the Checklist tool were categorically accurate or over-estimated the true exposure by one category 70% of the time. The overall magnitude of exposure judgment precision also improved following training. Fleiss' κ, evaluating inter-rater agreement between novice assessors was fair to moderate (κ = 0.39). Cohen's weighted and unweighted κ were good to excellent for novice (0.77 and 0.80) and practicing IHs (0.73 and 0.89), respectively. Checklist judgment accuracy was similar to quantitative exposure judgment accuracy observed in studies of similar design using personal exposure measurements, suggesting that the tool could be useful in developing informed priors and further demonstrating its usefulness in producing accurate qualitative exposure judgments.

Comparison of methods for analyzing left-censored occupational exposure data.

The National Institute for Environmental Health Sciences (NIEHS) is conducting an epidemiologic study (GuLF STUDY) to investigate the health of the workers and volunteers who participated from April to December of 2010 in the response and cleanup of the oil release after the Deepwater Horizon explosion in the Gulf of Mexico. The exposure assessment component of the study involves analyzing thousands of personal monitoring measurements that were collected during this effort. A substantial portion of these data has values reported by the analytic laboratories to be below the limits of detection (LOD). A simulation study was conducted to evaluate three established methods for analyzing data with censored observations to estimate the arithmetic mean (AM), geometric mean (GM), geometric standard deviation (GSD), and the 95th percentile (X0.95) of the exposure distribution: the maximum likelihood (ML) estimation, the ß-substitution, and the Kaplan-Meier (K-M) methods. Each method was challenged with computer-generated exposure datasets drawn from lognormal and mixed lognormal distributions with sample sizes (N) varying from 5 to 100, GSDs ranging from 2 to 5, and censoring levels ranging from 10 to 90%, with single and multiple LODs. Using relative bias and relative root mean squared error (rMSE) as the evaluation metrics, the ß-substitution method generally performed as well or better than the ML and K-M methods in most simulated lognormal and mixed lognormal distribution conditions. The ML method was suitable for large sample sizes (N ≥ 30) up to 80% censoring for lognormal distributions with small variability (GSD = 2-3). The K-M method generally provided accurate estimates of the AM when the censoring was <50% for lognormal and mixed distributions. The accuracy and precision of all methods decreased under high variability (GSD = 4 and 5) and small to moderate sample sizes (N < 20) but the ß-substitution was still the best of the three methods. When using the ML method, practitioners are cautioned to be aware of different ways of estimating the AM as they could lead to biased interpretation. A limitation of the ß-substitution method is the absence of a confidence interval for the estimate. More research is needed to develop methods that could improve the estimation accuracy for small sample sizes and high percent censored data and also provide uncertainty intervals.

Comparing Antoine parameter sources for accurate vapor pressure prediction across a range of temperatures.

Determining the vapor pressure of a substance at the relevant process temperature is a key component in conducting an exposure assessment to ascertain worker exposure. However, vapor pressure data at various temperatures relevant to the work environment is not readily available for many chemicals. The Antoine equation is a mathematical expression that relates temperature and vapor pressure. The objective of this analysis was to compare Antoine parameter data from 3 independent data sources; Hansen, Yaws, and Custom data and identify the source that generates the most accurate vapor pressure values with the least bias, relative to the referent data set from the CRC Handbook of Chemistry and Physics. Temperatures predicted from 3 different Antoine sources across a range of vapor pressures for 59 chemicals are compared to the reference source. The results show that temperatures predicted using Antoine parameters from the 3 sources are not statistically significantly different, indicating that all 3 sources could be useful. However, the Yaws dataset will be used in the SDM 2.0 because the data is readily available and robust.

Association between spill-related exposure to fine particulate matter and peripheral motor and sensory nerve function among oil spill response and cleanup workers following the Deepwater Horizon oil spill.

BACKGROUND: Burning/flaring of oil/gas during the Deepwater Horizon oil spill response and cleanup (OSRC) generated high concentrations of fine particulate matter (PM2.5). Personnel working on the water during these activities may have inhaled combustion products. Neurologic effects of PM2.5 have been reported previously but few studies have examined lasting effects following disaster exposures. The association of brief, high exposures and adverse effects on sensory and motor nerve function in the years following exposure have not been examined for OSRC workers. OBJECTIVES: We assessed the relationship between exposure to burning/flaring-related PM2.5 and measures of sensory and motor nerve function among OSRC workers. METHODS: PM2.5 concentrations were estimated from Gaussian plume dispersion models and linked to self-reported work histories. Quantitative measures of sensory and motor nerve function were obtained 4-6 years after the disaster during a clinical exam restricted to those living close to two clinics in Mobile, AL or New Orleans, LA (n = 3401). We obtained covariate data from a baseline enrollment survey and a home visit, both in 2011-2013. The analytic sample included 1186 participants. RESULTS: We did not find strong evidence of associations between exposure to PM2.5 and sensory or motor nerve function, although there was a suggestion of impairment based on single leg stance among individuals with high exposure to PM2.5. Results were generally consistent whether we examined average or cumulative maximum exposures or removed individuals with the highest crude oil exposures to account for co-pollutant confounding. There was no evidence of exposure-response trends. IMPACT STATEMENT: Remediating environmental disasters is essential for long-term human and environmental health. During the Deepwater Horizon oil spill disaster, burning and flaring of oil and gas were used to remove these pollutants from the environment, but led to potentially high fine particulate matter exposures for spill response workers working on the water. We investigate the potential adverse effects of these exposures on peripheral nerve function; understanding the potential health harm of remediation tactics is necessary to inform future clean up approaches and protect human health.

Volatile Hydrocarbon Exposures and Incident Coronary Heart Disease Events: Up to Ten Years of Follow-up among Deepwater Horizon Oil Spill Workers.

BACKGROUND: During the 2010 Deepwater Horizon (DWH) disaster, response and cleanup workers were potentially exposed to toxic volatile components of crude oil. However, to our knowledge, no study has examined exposure to individual oil spill-related chemicals in relation to cardiovascular outcomes among oil spill workers. OBJECTIVES: Our aim was to investigate the association of several spill-related chemicals [benzene, toluene, ethylbenzene, xylene, n-hexane (BTEX-H)] and total hydrocarbons (THC) with incident coronary heart disease (CHD) events among workers enrolled in a prospective cohort. METHODS: Cumulative exposures to THC and BTEX-H across the cleanup period were estimated via a job-exposure matrix that linked air measurement data with self-reported DWH spill work histories. We ascertained CHD events following each worker's last day of cleanup work as the first self-reported physician-diagnosed myocardial infarction (MI) or a fatal CHD event. We estimated hazard ratios (HR) and 95% confidence intervals for the associations of exposure quintiles (Q) with risk of CHD. We applied inverse probability weights to account for bias due to confounding and loss to follow-up. We used quantile g-computation to assess the joint effect of the BTEX-H mixture. RESULTS: Among 22,655 workers with no previous MI diagnoses, 509 experienced an incident CHD event through December 2019. Workers in higher quintiles of each exposure agent had increased CHD risks in comparison with the referent group (Q1) of that agent, with the strongest associations observed in Q5 (range of HR=1.14-1.44). However, most associations were nonsignificant, and there was no evidence of exposure-response trends. We observed stronger associations among ever smokers, workers with ≤high school education, and workers with body mass index <30 kg/m2. No apparent positive association was observed for the BTEX-H mixture. CONCLUSIONS: Higher exposures to volatile components of crude oil were associated with modest increases in risk of CHD among oil spill workers, although we did not observe exposure-response trends. https://doi.org/10.1289/EHP11859.

Exposure Assessment Techniques Applied to the Highly Censored Deepwater Horizon Gulf Oil Spill Personal Measurements.

The GuLF Long-term Follow-up Study (GuLF STUDY) is investigating potential adverse health effects of workers involved in the Deepwater Horizon (DWH) oil spill response and cleanup (OSRC). Over 93% of the 160 000 personal air measurements taken on OSRC workers were below the limit of detection (LOD), as reported by the analytic labs. At this high level of censoring, our ability to develop exposure estimates was limited. The primary objective here was to reduce the number of measurements below the labs' reported LODs to reflect the analytic methods' true LODs, thereby facilitating the use of a relatively unbiased and precise Bayesian method to develop exposure estimates for study exposure groups (EGs). The estimates informed a job-exposure matrix to characterize exposure of study participants. A second objective was to develop descriptive statistics for relevant EGs that did not meet the Bayesian criteria of sample size ≥5 and censoring ≤80% to achieve the aforementioned level of bias and precision. One of the analytic labs recalculated the measurements using the analytic method's LOD; the second lab provided raw analytical data, allowing us to recalculate the data values that fell between the originally reported LOD and the analytical method's LOD. We developed rules for developing Bayesian estimates for EGs with >80% censoring. The remaining EGs were 100% censored. An order-based statistical method (OBSM) was developed to estimate exposures that considered the number of measurements, geometric standard deviation, and average LOD of the censored samples for N ≥ 20. For N < 20, substitution of ½ of the LOD was assigned. Recalculation of the measurements lowered overall censoring from 93.2 to 60.5% and of the THC measurements, from 83.1 to 11.2%. A total of 71% of the EGs met the ≤15% relative bias and <65% imprecision goal. Another 15% had censoring >80% but enough non-censored measurements to apply Bayesian methods. We used the OBSM for 3% of the estimates and the simple substitution method for 11%. The methods presented here substantially reduced the degree of censoring in the dataset and increased the number of EGs meeting our Bayesian method's desired performance goal. The OBSM allowed for a systematic and consistent approach impacting only the lowest of the exposure estimates. This approach should be considered when dealing with highly censored datasets.

Estimation of Aerosol Concentrations of Oil Dispersants COREXIT™ EC9527A and EC9500A during the Deepwater Horizon Oil Spill Response and Clean-up Operations.

The April 2010 Deepwater Horizon drilling unit explosion at the Macondo oil well resulted in the release of approximately 779 million l of oil into the Gulf of Mexico. As part of the response effort to break up oil slicks on the water's surface, 6.81 million l of chemical dispersants COREXIT™ EC9500A and COREXIT™ EC9527A were applied by plane or vessel or injected near the seabed. The GuLF Long-term Follow-up Study is investigating possible adverse health effects of workers involved in the oil spill response and clean-up (OSRC). In this paper, we describe potential dispersant-related air concentrations generated from aerial spraying of dispersants to provide insight as to what concentrations OSRC workers may have been exposed under worst-case conditions. Personal exposure measurement data were not collected. Modeling, therefore, was conducted to estimate airborne concentrations of total aerosol to COREXIT™ EC9527A and EC9500A. Using the AgDISP model, we estimated air concentrations to dispersant total aerosols, defined as all components of the dispersant including active ingredients, surfactants, and water, resulting from aerial and vessel applications, as average 1-h and 2-min concentrations. For comparison, 1-h air concentrations associated with aerial spraying were estimated using another model, AERMOD. At 152 m horizontal to the flight path, average 1-h total aerosol concentrations associated with aerial applications were estimated to be as high as 49.3 µg m-3 (9527A) and 45.4 µg m-3 (9500A), and both decreased with increased distance from the flight line. The estimates for spraying 9500A from vessels indicated that total aerosol concentrations were potentially as high as 0.33 µg m-3 at 10 m from the nozzles. These results suggest that personal exposures to dispersant aerosols were negligible.

Estimation of Airborne Vapor Concentrations of Oil Dispersants COREXIT™ EC9527A and EC9500A, Volatile Components Associated with the Deepwater Horizon Oil Spill Response and Clean-up Operations.

The Deepwater Horizon (DWH) drilling unit explosion above the Macondo oil well on 20 April 2010 caused the release of approximately 4.9 million barrels (779 million L) of oil into the Gulf of Mexico. As part of a larger spill response and clean-up effort, approximately 1.84 million gallons (6.81 million L) of chemical dispersants COREXIT™ EC9500A and COREXIT™ EC9527A were applied to the resultant oil slicks through spraying on the water surface by plane and by vessel and through injection at the release source near the seabed. The GuLF STUDY is investigating the health effects of workers involved in the oil spill response and clean-up after the DWH explosion, and estimates of possible exposure to chemical dispersants were needed. Exposures were estimated to the volatile components of COREXIT™ EC9500A [petroleum distillates, hydrotreated light, and propylene glycol (PG)] and of COREXIT™ EC9527A [2-butoxyethanol (2-BE) and PG] using two of AIHA IHMOD2.0© mathematical modeling tools along with the dispersants' chemical and physical properties. Monte Carlo simulations were used to reflect uncertainty in input parameters with both the two-box, constant emission model and the near and mid field plume model for indoor and outdoor activities, respectively. Possible exposure scenarios considered various evaporation rates, sizes of the dispersant pool, wind speeds, and ventilation rates. For the two-box model, mean near field exposure estimates to 2-BE ranged from 0.9 to 5.7 ppm, while mean far field estimated exposures ranged from 0.3 to 3.5 ppm. Estimates of mean near field plume model exposures ranged from 0.01 to 3.7 ppm at 2.5 ft from the source, and <0.01 to 0.3 ppm at 10 ft from the source. Estimated exposures to PG were approximately 10% of the calculated 2-BE exposures and exposures to petroleum distillates about 40% higher than the 2-BE estimates. Results indicate that compared with current occupational exposure guidelines, overexposure to petroleum distillates and PG probably did not occur in our study, but under some conditions, for short periods, exposure to 2-BE may have exceeded the limits for peak exposures. These estimates were developed for use in job-exposure matrices to estimate exposures of workers having contact with dispersant vapors for the GuLF STUDY.

Estimates of Inhalation Exposures to Oil-Related Components on the Supporting Vessels During the Deepwater Horizon Oil Spill.

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.

Exposure Group Development in Support of the NIEHS GuLF Study.

In the GuLF Study, a study investigating possible adverse health effects associated with work on the oil spill response and clean-up (OSRC) following the Deepwater Horizon disaster in the Gulf of Mexico, we used a job-exposure matrix (JEM) approach to estimate exposures. The JEM linked interview responses of study participants to measurement data through exposure groups (EGs). Here we describe a systematic process used to develop transparent and precise EGs that allowed characterization of exposure levels among the large number of OSRC activities performed across the Gulf of Mexico over time and space. EGs were identified by exposure determinants available to us in our measurement database, from a substantial body of other spill-related information, and from responses provided by study participants in a detailed interview. These determinants included: job/activity/task, vessel and type of vessel, weathering of the released oil, area of the Gulf of Mexico, Gulf coast state, and time period. Over 3000 EGs were developed for inhalation exposure and applied to each of 6 JEMs of oil-related substances (total hydrocarbons, benzene, toluene, ethylbenzene, total xylene, and n-hexane). Subsets of those EGs were used for characterization of exposures to dispersants, particulate matter, and oil mist. The EGs allowed assignment to study participants of exposure estimates developed from measurement data or from estimation models through linkage in the JEM for the investigation of exposure-response relationships.

Estimates of Occupational Inhalation Exposures to Six Oil-Related Compounds on the Four Rig Vessels Responding to the Deepwater Horizon Oil Spill.

BACKGROUND: The 2010 Deepwater Horizon (DWH) oil spill involved thousands of workers and volunteers to mitigate the oil release and clean-up after the spill. Health concerns for these participants led to the initiation of a prospective epidemiological study (GuLF STUDY) to investigate potential adverse health outcomes associated with the oil spill response and clean-up (OSRC). Characterizing the chemical exposures of the OSRC workers was an essential component of the study. Workers on the four oil rig vessels mitigating the spill and located within a 1852 m (1 nautical mile) radius of the damaged wellhead [the Discoverer Enterprise (Enterprise), the Development Driller II (DDII), the Development Driller III (DDIII), and the HelixQ4000] had some of the greatest potential for chemical exposures. OBJECTIVES: The aim of this paper is to characterize potential personal chemical exposures via the inhalation route for workers on those four rig vessels. Specifically, we presented our methodology and descriptive statistics of exposure estimates for total hydrocarbons (THCs), benzene, toluene, ethylbenzene, xylene, and n-hexane (BTEX-H) for various job groups to develop exposure groups for the GuLF STUDY cohort. METHODS: Using descriptive information associated with the measurements taken on various jobs on these rig vessels and with job titles from study participant responses to the study questionnaire, job groups [unique job/rig/time period (TP) combinations] were developed to describe groups of workers with the same or closely related job titles. A total of 500 job groups were considered for estimation using the available 8139 personal measurements. We used a univariate Bayesian model to analyze the THC measurements and a bivariate Bayesian regression framework to jointly model the measurements of THC and each of the BTEX-H chemicals separately, both models taking into account the many measurements that were below the analytic limit of detection. RESULTS: Highest THC exposures occurred in TP1a and TP1b, which was before the well was mechanically capped. The posterior medians of the arithmetic mean (AM) ranged from 0.11 ppm ('Inside/Other', TP1b, DDII; and 'Driller', TP3, DDII) to 14.67 ppm ('Methanol Operations', TP1b, Enterprise). There were statistical differences between the THC AMs by broad job groups, rigs, and time periods. The AMs for BTEX-H were generally about two to three orders of magnitude lower than the THC AMs, with benzene and ethylbenzene measurements being highly censored. CONCLUSIONS: Our results add new insights to the limited literature on exposures associated with oil spill responses and support the current epidemiologic investigation of potential adverse health effects of the oil spill.