Stochastic Framework for Addressing Chemical Partitioning and Bioavailability in Contaminated Sediment Assessment and Management.

Passive sampling to quantify net partitioning of hydrophobic organic contaminants between the porewater and solid phase has advanced risk management for contaminated sediments. Direct porewater (Cfree) measures represent the best way to predict adverse effects to biota. However, when the need arises to convert between solid-phase concentration (Ctotal) and Cfree, a wide variation in observed sediment-porewater partition coefficients (KTOC) is observed due to intractable complexities in binding phases. We propose a stochastic framework in which a given Ctotal is mapped to an estimated range of Cfree through variability in passive sampling-derived KTOC relationships. This mapping can be used to pair estimated Cfree with biological effects data or inversely to translate a measured or assumed Cfree to an estimated Ctotal. We apply the framework to both an effects threshold for polycyclic aromatic hydrocarbon (PAH) toxicity and an aggregate adverse impact on an assemblage of species. The stochastic framework is based on a "bioavailability ratio" (BR), which reflects the extent to which potency-weighted, aggregate PAH partitioning to the solid-phase is greater than that predicted by default, KOW-based KTOC values. Along a continuum of Ctotal, we use the BR to derive an estimate for the probability that Cfree will exceed a threshold. By explicitly describing the variability of KTOC and BR, estimates of risk posed by sediment-associated contaminants can be more transparent and nuanced.

Application of the tissue residue approach in ecological risk assessment.

The objective of this work is to present a critical review of the application of the tissue residue approach (TRA) in ecological risk and/or impact assessment (ERA) of chemical stressors and environmental criteria development. A secondary goal is to develop a framework for integrating the TRA into ecological assessments along with traditional, exposure concentration-based assessment approaches. Although widely recognized for its toxicological appeal, the utility of the TRA in specific applications will depend on numerous factors, such as chemical properties, exposure characteristics, assessment type, availability of tissue residue-response data, and ability to quantify chemical exposure. Therefore, the decision to use the TRA should include an evaluation of the relative strengths, limitations, and uncertainties among exposure and residue-based methods for characterizing toxicological effects. Furthermore, rather than supplanting exposure concentration-based toxicity assessments, the TRA can be highly effective for evaluating and reducing uncertainty when used in a complementary manner (e.g., when evaluating multiple lines of evidence in field studies). To address limitations with the available tissue residue-response data, approaches for extrapolating residue-based toxicity data across species, tissues, and exposure durations are discussed. Some of these approaches rely on predicted residue-response relationships or toxicological models that have an implicit residue-response basis (e.g., biotic ligand model). Because risk to an organism is a function of both its exposure potential and inherent sensitivity (i.e., on a residue basis), bioaccumulation models will be required not only for translating tissue residue criteria into corresponding water and sediment criteria, but also for defining the most vulnerable species in an assemblage (i.e., highly exposed and highly sensitive species). Application of the TRA in ecological assessments and criteria development are summarized for bioaccumulative organic chemicals, TBT, and in situ bioassays using bivalve molluscs.

Adverse outcome pathways: a conceptual framework to support ecotoxicology research and risk assessment.

Ecological risk assessors face increasing demands to assess more chemicals, with greater speed and accuracy, and to do so using fewer resources and experimental animals. New approaches in biological and computational sciences may be able to generate mechanistic information that could help in meeting these challenges. However, to use mechanistic data to support chemical assessments, there is a need for effective translation of this information into endpoints meaningful to ecological risk-effects on survival, development, and reproduction in individual organisms and, by extension, impacts on populations. Here we discuss a framework designed for this purpose, the adverse outcome pathway (AOP). An AOP is a conceptual construct that portrays existing knowledge concerning the linkage between a direct molecular initiating event and an adverse outcome at a biological level of organization relevant to risk assessment. The practical utility of AOPs for ecological risk assessment of chemicals is illustrated using five case examples. The examples demonstrate how the AOP concept can focus toxicity testing in terms of species and endpoint selection, enhance across-chemical extrapolation, and support prediction of mixture effects. The examples also show how AOPs facilitate use of molecular or biochemical endpoints (sometimes referred to as biomarkers) for forecasting chemical impacts on individuals and populations. In the concluding sections of the paper, we discuss how AOPs can help to guide research that supports chemical risk assessments and advocate for the incorporation of this approach into a broader systems biology framework.