New World A-Coming
In: The journal of negro education: JNE ;a Howard University quarterly review of issues incident to the education of black people, Band 13, Heft 2, S. 199
ISSN: 2167-6437
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In: The journal of negro education: JNE ;a Howard University quarterly review of issues incident to the education of black people, Band 13, Heft 2, S. 199
ISSN: 2167-6437
In: The journal of psychology: interdisciplinary and applied, Band 68, Heft 1, S. 151-157
ISSN: 1940-1019
In: Annals of work exposures and health: addressing the cause and control of work-related illness and injury, Band 62, Heft 7, S. 818-827
ISSN: 2398-7316
In: Globalization: Effects on Fisheries Resources, S. 21-46
In: Annals of work exposures and health: addressing the cause and control of work-related illness and injury, Band 66, Heft Supplement_1, S. i202-i217
ISSN: 2398-7316
Abstract
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.
In: Annals of work exposures and health: addressing the cause and control of work-related illness and injury, Band 66, Heft Supplement_1, S. i188-i202
ISSN: 2398-7316
Abstract
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.
In: Annals of work exposures and health: addressing the cause and control of work-related illness and injury, Band 66, Heft Supplement_1, S. i56-i70
ISSN: 2398-7316
Abstract
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.
In: Annals of work exposures and health: addressing the cause and control of work-related illness and injury, Band 61, Heft 1, S. 76-86
ISSN: 2398-7316
In: Annals of work exposures and health: addressing the cause and control of work-related illness and injury, Band 66, Heft Supplement_1, S. i156-i171
ISSN: 2398-7316
Abstract
Even though the Deepwater Horizon oil spill response and clean-up (OSRC) had one of the largest exposure monitoring efforts of any oil spill, a number of exposure groups did not have sufficient personal data available or there were gaps in days measured to adequately characterize exposures for the GuLF STUDY, an epidemiologic study investigating the health of the OSRC workers. Area measurements were available from real-time air monitoring instruments and used to supplement the personal exposure measurements.
Objectives
The objective was to present a method that used real-time volatile organic compounds (VOCs) area measurements transformed to daily total hydrocarbons (THC) time-weighted averages (TWAs) to supplement THC personal full-shift measurements collected using passive charcoal badges. A second objective was to develop exposure statistics using these data for workers on vessels piloting remotely operated vehicle (ROV) vessels and other marine vessels (MVs) not at the job title level, but at the vessel level.
Methods
From hourly vessel averages derived from ~26 million real-time VOC measurements, we estimated full-shift VOC TWAs. Then, we determined the relationship between these TWAs and corresponding full-shift THC personal measurements taken on the same vessel-day. We used this relationship to convert the full-shift VOC measurements to full-shift 'THC' TWA estimates when no personal THC measurements existed on a vessel-day. We then calculated arithmetic means (AMs) and other statistics of THC exposures for each vessel.
Results
The VOC-derived estimates substantially supplemented the THC personal measurements, with the number of vessel-days for which we have exposure estimates increasing by ~60%. The estimates of the AMs are some of the highest observed in the GuLF STUDY. As expected, the AMs decreased over time, consistent with our findings on other vessels.
Conclusions
Despite the inherent limitations of using real-time area measurements, we were able to develop additional daily observations of personal THC exposures for workers on the ROV vessels and other MVs over time. The estimates likely resulted in more representative estimates of the AMs in the GuLF STUDY. The method used here can be applied in other occupational settings and industries for personal exposure estimation where large amounts of area measurements and more limited numbers of personal measurements are available.
In: Annals of work exposures and health: addressing the cause and control of work-related illness and injury, Band 66, Heft Supplement_1, S. i140-i155
ISSN: 2398-7316
Abstract
The NIEHS GuLF STUDY is an epidemiologic study of the health of workers who participated in the 2010 Deepwater Horizon oil spill response and clean-up effort. Even with a large database of approximately 28 000 personal samples that were analyzed for total hydrocarbons (THCs) and other oil-related chemicals, resulting in nearly 160 000 full-shift personal measurements, there were still exposure scenarios where the number of measurements was too limited to rigorously assess exposures. Also available were over 26 million volatile organic compounds (VOCs) area air measurements of approximately 1-min duration, collected from direct-reading instruments on 38 large vessels generally located near the leaking well. This paper presents a strategy for converting the VOC database into hourly average air concentrations by vessel as the first step of a larger process designed to use these data to supplement full-shift THC personal exposure measurements. We applied a Bayesian method to account for measurements with values below the analytic instrument's limit of detection while processing the large database into average instrument-hour concentrations and then hourly concentrations across instruments on each day of measurement on each of the vessels. To illustrate this process, we present results on the drilling rig ship, the Discoverer Enterprise. The methods reduced the 26 million measurements to 21 900 hourly averages, which later contributed to the development of additional full-shift THC observations. The approach used here can be applied by occupational health professionals with large datasets of direct-reading instruments to better understand workplace exposures.
In: The annals of occupational hygiene: an international journal published for the British Occupational Hygiene Society, S. mev049
ISSN: 1475-3162
In: Annals of work exposures and health: addressing the cause and control of work-related illness and injury, Band 66, Heft Supplement_1, S. i234-i246
ISSN: 2398-7316
Abstract
The GuLF STUDY is investigating health outcomes associated with oil spill-related chemical exposures among workers involved in the spill response and clean-up following the Deepwater Horizon disaster. Due to the lack of dermal exposure measurements, we estimated dermal exposures using a deterministic model, which we customized from a previously published model. Workers provided information on the frequency of contact with oil, tar, chemical dispersants applied to the oil spill and sea water, as well as the use of protective equipment, by job/activity/task. Professional judgment by industrial hygienists served as a source of information for other model variables. The model estimated dermal exposures to total hydrocarbons (THC), benzene, ethylbenzene, toluene, xylene, n-hexane (BTEX-H), polycyclic aromatic hydrocarbons (PAHs), and dispersants in GuLF DREAM units (GDUs). Arithmetic means (AMs) of THC exposure estimates across study participants ranged from <0.02 to 5.50 GDUs for oil and <0.02 to 142.14 GDUs for tar. Statistical differences in the estimates were observed among the AMs of the estimates for some broad groups of worker activities over time and for some time periods across the broad groups of activities. N-Hexane had ranges similar to THC for oil exposures (e.g. AMs up to 2.22 GDUs) but not for tar (up to 5.56 GDUs). Benzene, ethylbenzene, toluene, and xylene, in contrast, were characterized by higher exposure levels than THC for oil (AMs up to 12.77, 12.17, 17.45, and 36.77 GDUs, respectively) but lower levels than THC to tar (AMs up to 3.69, 11.65, 42.37, and 88.18 GDUs, respectively). For PAHs, the AMs were as high as 219.31 and 587.98 for oil and tar, respectively. Correlations of these seven substances to each other were high (>0.9) for most of the substances in oil but were lower for some of the substances in tar. These data were linked to the study participants to allow investigation of adverse health effects that may be related to dermal exposures.
In: Annals of work exposures and health: addressing the cause and control of work-related illness and injury, Band 66, Heft Supplement_1, S. i124-i139
ISSN: 2398-7316
Abstract
Following the Deepwater Horizon oil spill disaster, thousands of workers and volunteers cleaned the shoreline across four coastal states of the Gulf of Mexico. For the GuLF STUDY, we developed quantitative estimates of oil-related chemical exposures [total petroleum hydrocarbons (THC), benzene, toluene, ethylbenzene, xylene, and n-hexane (BTEX-H)] from personal measurements on workers performing various spill clean-up operations on land. These operations included decontamination of vessels, equipment, booms, and personnel; handling of oily booms; hazardous waste management; beach, marsh, and jetty clean-up; aerial missions; wildlife rescue and rehabilitation; and administrative support activities. Exposure estimates were developed for unique groups of workers by (i) activity, (ii) state, and (iii) time period. Estimates of the arithmetic means (AMs) for THC ranged from 0.04 to 3.67 ppm. BTEX-H estimates were substantially lower than THC (in the parts per billion range). Both THC and BTEX-H estimates were substantially lower than their respective occupational exposure limits. The work group, 'Fueled engines' consistently was one of the higher exposed groups to THC and BTEX-H. Notable differences in the AM exposures were observed by activity, time and, to a lesser degree, by state. These exposure estimates were used to develop job-exposure matrices for the GuLF STUDY.
In: Annals of work exposures and health: addressing the cause and control of work-related illness and injury, Band 66, Heft Supplement_1, S. i172-i187
ISSN: 2398-7316
Abstract
The GuLF STUDY, initiated by the National Institute of Environmental Health Sciences, is investigating the health effects among workers involved in the oil spill response and clean-up (OSRC) after the Deepwater Horizon (DWH) explosion in April 2010 in the Gulf of Mexico. Clean-up included in situ burning of oil on the water surface and flaring of gas and oil captured near the seabed and brought to the surface. We estimated emissions of PM2.5 and related pollutants resulting from these activities, as well as from engines of vessels working on the OSRC. PM2.5 emissions ranged from 30 to 1.33e6 kg per day and were generally uniform over time for the flares but highly episodic for the in situ burns. Hourly emissions from each source on every burn/flare day were used as inputs to the AERMOD model to develop average and maximum concentrations for 1-, 12-, and 24-h time periods. The highest predicted 24-h average concentrations sometimes exceeded 5000 µg m−3 in the first 500 m downwind of flaring and reached 71 µg m−3 within a kilometer of some in situ burns. Beyond 40 km from the DWH site, plumes appeared to be well mixed, and the predicted 24-h average concentrations from the flares and in situ burns were similar, usually below 10 µg m−3. Structured averaging of model output gave potential PM2.5 exposure estimates for OSRC workers located in various areas across the Gulf. Workers located nearest the wellhead (hot zone/source workers) were estimated to have a potential maximum 12-h exposure of 97 µg m−3 over the 2-month flaring period. The potential maximum 12-h exposure for workers who participated in in situ burns was estimated at 10 µg m−3 over the ~3-month burn period. The results suggest that burning of oil and gas during the DWH clean-up may have resulted in PM2.5 concentrations substantially above the U.S. National Ambient Air Quality Standard for PM2.5 (24-h average = 35 µg m−3). These results are being used to investigate possible adverse health effects in the GuLF STUDY epidemiologic analysis of PM2.5 exposures.