Download - Adaptation of the DREAM tool
WORKING FOR A HEALTHY FUTURE
INSTITUTE OF OCCUPATIONAL MEDICINE . Edinburgh . UK www.iom-world.org
Development of the DREAM model for dermal exposure assessment of oil clean-up workers in the GuLF STUDY
Melanie Gorman Ng1, John W Cherrie1, Mark Stenzel2,
Richard Kwok3, Berna van Wendel de Joode4, Patricia
Stewart51 Institute of Occupational Medicine
2 Exposure Assessment Applications, LLC
3 National Institute of Environmental Health Sciences
4 Universidad Nacional de Costa Rica
5 Stewart Exposure Assessments, LLC
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GuLF STUDY – Dermal Exposure
• Over 150,000 air measurements
• No dermal or surface contamination measurements
• Need to assess dermal exposure to:
Oil Residues, (e.g.. VOCs, PAHs, BTEX)Dispersants (e.g. 2-butosyethanol, propylene glycol)
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DREAM
• Develop estimates from task descriptive information
• Estimates are reproducible between assessors
• Estimates exposure in “Dream Units” - DU
• Validation study showed reasonable correlation with measurement data
van Wendel de Joode et al. Accuracy of a semiquantitative method for Dermal Exposure Assessment (DREAM). Occup Environ Med (2005) vol. 62 (9) pp. 623-32
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Challenges for GuLF STUDY
• Poor precision when range of exposure levels is small (less than half an order of magnitude)
• Does not take into account many factors that may be important (e.g. heat, use of sun screen, insect repellents, etc)
• Model is ten years old and based on limited data
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DREAM
Exposure Assessors estimate exposure from each of the three pathways of dermal exposure:
• Immersion• Surface Contact• Deposition
ctorotectionFaClothingPr
Emission IntrinsicIntensityFrequencysureDermalExpo
xx
Substance characteristics
Skin area exposed
Number of exposure events
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Updating DREAM
• Update/review literature on model parameters relevant to GuLF STUDY:• viscosity and stickiness• evaporation • gloves and protective clothing• seawater and sweat• sun screens & insect repellents
• Amend other variables as necessary based on recent literature
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Major updates -PPE
• Available biomonitoring studies suggest gloves are less effective than DREAM had previously assumed
• E.g. Pesticide applicators: 90% vs. 40% (Brouwer and van Hemmen, 1997)
• E.g. Creosote workers: 60% vs. 50% reduction in 1-hydroxy-pyrene (vam Rooij et al, 1993)
Brouwer and van Hemmen (1997). Brighton Crop Protection Conference: 1059-65.
van Rooij et al (1993) Scand J Work Envir Hlth; 19:200-7
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Major Updates - Evaporation
Original DREAM Based on Boiling point
<50ºC = 150 - 100ºC = 3>150ºC = 10
GuLF DREAM uses equations used in IHSkinPerm and NIOSH Skin Permeation Calculator (Kasting and Miller, 2006)
Kasting and Miller (2006). Kinetics of finite dose absorption through skin 2: Volatile Compounds. J Pharm Sci; 95(2):268-280.
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78.0
76.0
6320
MWTR
MWVPVnRateEvaporatio
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Major Updates - Evaporation
Ratio Highest to Lowest Expected Evaporation Rate
500
1.67 11 1.10
100
200
300
400
500
600
Vapour Pressure Molecular Weight Wind Speed Temperature
Examined change in evaporation rate over expected range holding other parameters constant
Developed DREAM multipliers within expected range
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Major Updates – Exposure Pathway
Skin exposure less likely to be correlated with air concentration when workers also exposed to contaminated surfaces (Burstyn et al, 2002; Pronk et al, 2006; Links et al, 2007)
Also included different effect of viscosity by exposure pathway:
Exposure increases with viscosity but effect is strongest for immersion
GM 7821 µg/cm2
GM 0.6 µg/cm2
GM 0.22 µg/cm2
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Comparison DREAM vs GuLF DREAM
Boom Deployment,
Near Shore
DU: 0.15
GDU: 1.46
Boom Retrieval,
Near Shore
DU 7.00
GDU: 20.26
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Future Challenges
• Matching DREAM categories to GuLF questionnaire categories
• Addressing uncertainty (Monte Carlo approach?)
• Model calibration
• Exposure assessor training
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Acknowledgements
Wendy McDowell – McDowell Safety & Health Services
Hans Kromhout – IRAS, Utrecht
Anne Sleeuwenhoek - IOM