Dr Anthony Umeh

Bioavailability estimates the actual internal uptake or absorption of contaminants that enter the body (internal dose) and helps in providing a more accurate estimation of the human risks than the usage of total concentration. This is important for exposure assessment for children in relation to their hand-to-mouth activities. For example significant reductions of the bioavailability of long-term contaminated soils have been demonstrated using various animal models. The measurement for bioavailability involves various uncertainties for organic contaminants. It is crucial to determine the parameters that influence the results of bioavailability. This chapter provides a summary of the current state of knowledge for the determination of bioavailability for a range of organic contaminants. The information provided will be useful in facilitating further research efforts for the investigation of bioavailability of contaminants in conducting exposure assessments.

The influence of soil properties on PFOS sorption are not fully understood, particularly for variable charge soils. PFOS batch sorption isotherms were conducted for 114 temperate and tropical soils from Australia and Fiji, that were well-characterized for their soil properties, including total organic carbon (TOC), anion exchange capacity, and surface charge. In most soils, PFOS sorption isotherms were nonlinear. PFOS sorption distribution coefficients (Kd) ranged from 5 to 229 mL/g (median: 28 mL/g), with 63% of the Fijian soils and 35% of the Australian soils showing Kd values that exceeded the observed median Kd. Multiple linear regression showed that TOC, amorphous aluminum and iron oxides contents, anion exchange capacity, pH, and silt content, jointly explained about 53% of the variance in PFOS Kd in soils. Variable charge soils with net positive surface charges, and moderate to elevated TOC content, generally displayed enhanced PFOS sorption than in temperate or tropical soils with TOC as the only sorbent phase, especially at acidic pH ranges. For the first time, two artificial neural networks were developed to predict the measured PFOS Kd (R2 = 0.80) in the soils. Overall, both TOC and surface charge characteristics of soils are important for describing PFOS sorption.