The objective of this research is to develop and experimentally validate algorithms which predict the absorbed dose following dermal exposure to chemically contaminated soils using known, or easily determined parameters such as exposure time, octanol-water partitioning, molecular weight, soil particle size distribution, and soil organic and water content. The basic assumption is that systemic human health risk from chemical exposure is dependent upon the mass of chemical which is absorbed. Since the skin is a major barrier to many chemicals, the absorbed dose may be significantly less than the exposed dose. Additionally, the large number of potential soil contaminants coupled with a wide variety of potential exposure scenarios, makes the experimental testing of every possible case impossible. In contrast, the use of a validated predictive algorithm would be useful to estimate dermal absorption following exposure to contaminated soils. Thus, this research proposes to systematically evaluate dermal absorption from soils by combining mathematical models with in vitro and in vivo experiments to produce predictive algorithms for the absorbed dose.
