A Review of Mechanistic Models for Predicting Adverse Effects in Sediment Toxicity Testing.

Since recognizing the importance of bioavailability for understanding the toxicity of chemicals in sediments, mechanistic modelling has advanced over the last 40 years by building better tools for estimating exposure and making predictions of probable adverse effects. This review provides an up-to-date survey of the status of mechanistic modelling in contaminated sediment toxicity assessments. Relative to exposure, advancements have been most substantial for nonionic organic contaminants (NOCs) and divalent cationic metals with several equilibrium partitioning-based (Eq-P) models having been developed. This has included the use of Abraham equations to estimate partition coefficients for environmental media. As a result of the complexity of their partitioning behavior, progress has been less substantial for ionic/polar organic contaminants. When the EqP-based estimates of exposure and bioavailability are combined with water-only effects measurements, predictions of sediment toxicity can be successfully made for NOCs and selected metals. Both species sensitivity distributions (SSDs) and toxicokinetic and toxicodynamic (TKTD) models are increasingly being applied to better predict contaminated sediment toxicity. Further, for some classes of contaminants, like polycyclic aromatic hydrocarbons (PAHs), adverse effects can be modelled as mixtures, making the models useful in real-world applications, where contaminants seldomly occur individually. Despite the impressive advances in the development and application of mechanistic models to predict sediment toxicity, several critical research needs remain to be addressed. These needs and others represent the next frontier in the continuing development and application of mechanistic models for informing environmental scientists, managers and decisions makers of risks associated with contaminated sediments.