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A five‐compartment steady‐state food‐web model is constructed that includes a benthic invertebrate compartment Four exposure routes are considered in the description of accumulation by benthic animals ingestion of particulate contaminants associated with (a) sediment organic carbon and (b) overlying phytoplankton and ventilation of free dissolved contaminant in (c) interstitial and (d) overlying water Normalization of organism lipid‐based chemical concentration to sediment organic carbon (the biota sediment factor, BSF) or to overlying water concentration (the bioaccumulation factor, BAF) indicates the significance of the sediment/overlying water partition coefficient for systems that have a benthic component The impact of the benthic component on a forage fish is related directly to this partitioning Application of the model to an amphipod‐scul pin web for Lake Ontario indicates (a) amphipod water exposure is a combination of interstitial and overlying water concentrations, (b) amphipod feeding appears to be a combination of overlying phy toplankton and sediment organic carbon, (c) amphipod and sculpin chemical assimilation efficiency appears to be a complicated function of octanol‐water partition coefficient, (d) observed BAF for amphipod and sculpin is about one order of magnitude higher than log Kow in the range 5 5 to 7 0 and is calculated to be due almost entirely to food‐web transfer from the sediment, as opposed to uptake from the water route

Biotransformation is a key process that can mitigate the bioaccumulation potential of organic substances and is an important parameter for exposure assessments. A recently published method for estimating whole-body in vivo metabolic biotransformation rate constants (kM) is applied to a database of measured laboratory bioconcentration factors and total elimination rate constants for fish. The method uses a kinetic mass balance model to estimate rates of chemical uptake and elimination when measured values are not reported. More than 5400 measurements for more than 1000 organic chemicals were critically reviewed to compile a database of 1535 kM estimates for 702 organic chemicals. Biotransformation rates range over six orders of magnitude across a diverse domain of chemical classes and structures. Screening-level uncertainty analyses provide guidance for the selection and interpretation of kM values. In general, variation in kM estimates from different routes of exposure (water vs diet) and between fish species is approximately equal to the calculation uncertainty in kM values. Examples are presented of structure-biotransformation relationships. Biotransformation rate estimates in the database are compared with estimates of biodegradation rates from existing quantitative structure-activity relationship models. Modest correlations are found, suggesting some consistency in biotransformation capabilities between fish and microorganisms. Additional analyses to further explore possible quantitative structure-biotransformation relationships for estimating kM from chemical structure are encouraged, and recommendations for improving the database are provided.

Passive sampling methods (PSMs) allow the quantification of the freely dissolved concentration (Cfree) of an organic contaminant even in complex matrices such as sediments. Cfree is directly related to a contaminant's chemical activity, which drives spontaneous processes including diffusive uptake into benthic organisms and exchange with the overlying water column. Consequently, Cfree provides a more relevant dose metric than total sediment concentration. Recent developments in PSMs have significantly improved our ability to reliably measure even very low levels of Cfree. Application of PSMs in sediments is preferably conducted in the equilibrium regime, where freely dissolved concentrations in the sediment are well-linked to the measured concentration in the sampler via analyte-specific partition ratios. The equilibrium condition can then be assured by measuring a time series or a single time point using passive samplers with different surface to volume ratios. Sampling in the kinetic regime is also possible and generally involves the application of performance reference compounds for the calibration. Based on previous research on hydrophobic organic contaminants, it is concluded that Cfree allows a direct assessment of 1) contaminant exchange and equilibrium status between sediment and overlying water, 2) benthic bioaccumulation, and 3) potential toxicity to benthic organisms. Thus, the use of PSMs to measure Cfree provides an improved basis for the mechanistic understanding of fate and transport processes in sediments and has the potential to significantly improve risk assessment and management of contaminated sediments. Integr Environ Assess Manag 2014;10:197–209. © 2014 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals, Inc. on behalf of SETAC.

A spreadsheet model (PETROTOX) is described that predicts the aquatic toxicity of complex petroleum substances from petroleum substance composition. Substance composition is characterized by specifying mass fractions in constituent hydrocarbon blocks (HBs) based on available analytical information. The HBs are defined by their mass fractions within a defined carbon number range or boiling point interval. Physicochemical properties of the HBs are approximated by assigning representative hydrocarbons from a database of individual hydrocarbons with associated physicochemical properties. A three-phase fate model is used to simulate the distribution of each structure among the water-, air-, and oil-phase liquid in the laboratory test system. Toxicity is then computed based on the predicted aqueous concentrations and aquatic toxicity of each structure and the target lipid model. The toxicity of the complex substance is computed assuming additivity of the contribution of the individual assigned hydrocarbons. Model performance was evaluated by using direct comparisons with measured toxicity data for petroleum substances with sufficient analytical characterization to run the model. Indirect evaluations were made by comparing predicted toxicity distributions using analytical data on petroleum substances from different product categories with independent, empirical distributions of toxicity data available for the same categories. Predictions compared favorably with measured aquatic toxicity data across different petroleum substance categories. These findings demonstrate the utility of PETROTOX for assessing environmental hazards of petroleum substances given knowledge of substance composition.