A probabilistic model for predicting distributions of PAH ratios between oysters and marine sediments

Modeling the uptake of organic chemicals by aquatic organisms is an important step in assessing human exposure to harmful environmental contaminants via seafood consumption. In many cases, investigators have applied the Equilibrium Partitioning (EqP) Model to determine the bioavailability of organic contaminants. This model assumes that a thermodynamic equilibrium exists between local environmental phases. It relies on point-estimated biota-to-sediment ratios (BSRs) to predict the concentration of organic residuals in the lipid tissues of organisms from the measured amounts of contaminants in the organic carbon component of the sediment. The paper presents a modeling analysis of polycyclic aromatic hydrocarbon (PAH) oyster and sediment contamination data collected at Murrells Inlet, SC, a high salinity estuary located in a heavily urbanized area just south of Myrtle Beach, SC. Three representative PAH analytes are considered: phenanthrene (PHE), pyrene (PYR) and chrysene (CRY). Statistical tests and scatter plots of lipid and organic carbon-normalized data clearly indicate that point-estimated BSRs of the EqP model are not appropriate for this system. As an alternative, the paper proposes a probabilistic model that describes the distributions of BSR values for each analyte. BSR upper limit confidence intervals given by these models are equal in magnitude to those derived from equilibrium partitioning. However, contrary to the predictions of the EqP model, BSR values appear to decrease with an increase in the molecular weight of the analyte. This suggests that heavier PAHs are 'falling out' of the water column into the sediment and become less available for uptake by oysters.