Target Lipid Model and Empirical Organic Carbon Partition Coefficients Predict Sediment Toxicity of Polychlorinated Biphenyls to Benthic Invertebrates

Evaluating the sensitivity of a chronic plant bioassay relative to an independently derived predicted no-effect thresholds to support risk assessment of very hydrophobic organic chemicals

Environmental risk assessments of very hydrophobic organic compounds (VHOCs) in soils are often difficult because multiple processes (e.g., sorption, volatilization, biodegradation) can complicate the interpretation of results. A standardized soil dosing and aging procedure is presented for assessing bioavailability of VHOCs in a synthetic soil, which was used to evaluate the phytotoxicity of VHOCs. The soil preparation protocol resulted in relatively stable freely dissolved concentrations of test substance compared to bulk soil concentrations with some losses likely due to volatility and biodegradation. This dosing method was used in a chronic terrestrial plant toxicity bioassay to evaluate the potential toxicity of VHOCs on complex reproductive endpoints like inflorescence and seed bud formation. Testing included representative hydrocarbons and three very hydrophobic lubricant substances (logKow > 10). The toxicity data were used to evaluate existing predicted no-effect concentrations (PNECs) that had originally been derived with the target lipid model, which did not have these higher order chronic plant endpoints. The initial exposure concentrations were set at the PNECs to provide an independent validation of the PNEC. This evaluation was performed to expand the domain of applicability of the PNEC to VHOCs and for the chronic terrestrial plant endpoints. No effects were observed on plant biomass or inflorescence production at these low exposure concentrations, demonstrating that the established PNEC is protective of long-term plant health. The results of the present study confirm that the new dosing method is fit for purpose, and that the existing PNEC framework can be extended to chronic plant endpoints for VHOCs.

Integrating ex situ biomimetic extraction analyses into contaminated sediment assessment and management decisions

This study evaluated a novel ex situ passive sampling biomimetic extraction (BE) method to estimate toxic potency in sediments. Gas chromatography with flame ionization detection (GC-FID) analysis of polydimethylsiloxane fibers equilibrated with field sediments was used to quantify bioavailable polyaromatic hydrocarbons (PAHs) and other unresolved, site-specific contaminant mixtures. This method is biomimetic because contaminants partition to the fiber based on hydrophobicity and abundance, and GC-FID quantification accounts for all constituents absorbed to the fiber that may contribute to toxicity. This measurement was compared with conventional approaches that rely on bulk sediment or porewater measurements of a targeted suite of PAHs. The specific objectives of the study were to (1) describe the BE method and explain measurement translation into toxic units (TUs); (2) report sediment BE data collected across 17 diverse field sites; (3) compare TUs predicted from (i) equilibrium partitioning (EqP) calculations based on sediment total organic carbon and bulk PAH chemistry, (ii) PAH porewater concentrations derived using ex situ passive sampling, and (iii) BE concentrations; and (4) discuss implications of this analysis for benthic toxicity assessment. Results showed that TUs obtained from EqP calculations were typically 10× higher than TUs derived from measured porewater PAH concentrations, indicating reduced PAH bioavailability in field sediments. Toxic units derived using the new BE method were more conservative than EqP in one-third of the sediments investigated, which was attributed to unquantified sediment contaminants, possible fiber fouling in the more contaminated sediments, and potential background interferences in less contaminated sediments. Preliminary data are also presented, showing that fluorometric analysis provides a simpler, promising alternative for estimating sediment BE concentrations. Based on this analysis, a decision-support framework is proposed using EqP and BE based TU metrics. Future research priorities are described for supporting framework implementation and extending use of BE analyses to remedial design and monitoring.

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 modeling has advanced over the last 40 years by building better tools for estimating exposure and making predictions of probable adverse effects. Our review provides an up-to-date survey of the status of mechanistic modeling in contaminated sediment toxicity assessments. Relative to exposure, advances have been most substantial for non-ionic 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 and toxicokinetic and toxicodynamic models are increasingly being applied to better predict contaminated sediment toxicity. Furthermore, for some classes of contaminants, such as polycyclic aromatic hydrocarbons, adverse effects can be modeled 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 the risks associated with contaminated sediments. Environ Toxicol Chem 2024;43:1778-1794. © 2023 SETAC. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.