The National Arsenic Intake Study: A Probabilistic Approach. D. B. Menzel, M. D. Dillencourt, D. M. Meacher, L. Bic, R. A. Schoof, D. W. Cragin, and C. H. Farr, University of California, Irvine, CA; Exponent, Bellevue, WA; and Elf Atochem, Philadelphia, PA
We report a new tool for risk assessment using a probabilistic approach and geospecific data with MESSENGERS. We simulated the relative contribution of four sources (air, food, soil and water) using analytic data on the inorganic arsenic content of each source at discrete geospatial locations in the US. A probability density function for daily inorganic arsenic intake was used with geospecific data; exposure models based on physiological terms, and census data to calculate the ingested inorganic arsenic internal dose for the adult US population according to age and sex. Two-dimensional maps of daily inorganic arsenic intake were then calculated by use of very large-scale simulations using MESSENGERS, a system for distributed computation, and a network of SUN microcomputers. From these data, we can rank the total daily inorganic arsenic intake and the relative contributions of each source for various subpopulations in any region of the conterminous US. Water and food represent the most important sources of inorganic arsenic; soil represents a source of less importance and air a minor source. The probabilities of daily inorganic arsenic intake at several levels of concern were calculated (50th, 90th, 95th or 99th percentiles). This large-scale computation was easily achieved with MESSENGERS without resorting to super computing.
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