XUE, J., V. ZARTARIAN, H. A. OZKAYNAK, W. DANG, G. GLEN, L. SMITH, AND C. STALLINGS. A PROBABILISTIC ARSENIC EXPOSURE ASSESSMENT FOR CHILDREN WHO CONTACT CHROMATED COPPER ARSENATE ( CAA )-TREATED PLAYSETS AND DECKS: PART 2 SENSITIVITY AND UNCERTAINTY ANALYSIS. RISK ANALYSIS. Blackwell Publishing, Malden, MA, 26(2):533-541, (2005).
A probabilistic model (SHEDS-Wood) was developed to examine children's exposure and dose to chromated copper arsenate (CCA)-treated wood, as described in Part 1 of this two part paper. This Part 2 paper discusses sensitivity and uncertainty analyses conducted to assess the key model inputs and areas of needed research for children's exposure to CCA-treated playsets and decks. The following types of analyses were conducted: (1) sensitivity analyses using a percentile scaling approach and multiple stepwise regression; and (2) uncertainty analyses using the bootstrap and 2-stage Monte Carlo techniques. The five most important variables, based on both sensitivity and uncertainty analyses, were: wood surface residue-to-skin transfer efficiency; wood surface residue levels; fraction of hand surface area mouthed per mouthing event; average fraction of non-residential outdoor time a child plays on/around CCA-treated public playsets; and frequency of hand washing. In general, there was a factor of 8 for the 5th and 95th percentiles and a factor of 4 for the 50th percentile in the uncertainty of predicted population dose estimates due to parameter uncertainty. Data were available for most of the key model inputs identified with sensitivity and uncertainty analyses; however, there were few or no data for some key inputs. To evaluate and improve the accuracy of model results, future measurement studies should obtain longitudinal time-activity diary information on children, spatial and temporal measurements of residue and soil concentrations on or near CCA treated playsets and decks, and key exposure factors. Future studies should also address other sources of uncertainty in addition to parameter uncertainty, such as scenario and model uncertainty.
The primary objective of this research is to produce a documented version of the aggregate SHEDS-Pesticides model for conducting reliable probabilistic population assessments of human exposure and dose to environmental pollutants. SHEDS is being developed to help answer the following questions:
(1) What is the population distribution of exposure for a given cohort for existing scenarios or for proposed exposure reduction scenarios?
(2) What is the intensity, duration, frequency, and timing of exposures from different routes?
(3) What are the most critical media, routes, pathways, and factors contributing to exposures?
(4) What is the uncertainty associated with predictions of exposure for a population?
(5) How do modeled estimates compare to real-world data?
(6) What additional human exposure measurements are needed to reduce uncertainty in population estimates?