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Bioconcentration factors (BCFs) in rainbow trout were measured for 10 anionic surfactants with a range of alkyl chain lengths and different polar head groups. The BCFs ranged from 0.04 L kg–1ww (for C10SO3) to 1370 L kg–1ww (C16SO3). There was a strong correlation between the log BCF and log membrane lipid–water distribution ratio (DMLW, r2= 0.96), and biotransformation was identified as the dominant elimination mechanism. The strong positive influence of DMLWon BCF was attributed to two phenomena: (i) increased partitioning from water into the epithelial membrane of the gill, leading to more rapid diffusion across this barrier and more rapid uptake, and (ii) increased sequestration of the surfactant body burden into membranes and other body tissues, resulting in lower freely dissolved concentrations available for biotransformation. Estimated whole-body in vivobiotransformation rate constants kB-BCFare within a factor three of rate constants estimated from S9 in vitroassays for six of the eight test chemicals for which kB-BCFcould be determined. A model-based assessment indicated that the hepatic clearance rate of freely dissolved chemicals was similar for the studied surfactants. The dataset will be useful for evaluation of in silicoand in vitromethods to assess bioaccumulation.

Cationic surfactants have a strong affinity to sorb to phospholipid membranes and thus possess an inherent potential to bioaccumulate, but there are few measurements of bioconcentration in fish. We measured the bioconcentration of 10 alkylamines plus two quaternary ammonium compounds in juvenile rainbow trout at pH 7.6, and repeated the measurements at pH 6.2 for 6 of these surfactants. The BCF of the amines with chain lengths ≤ C14was positively correlated with chain length, increasing ∼0.5 log units per carbon. Their BCF was also pH dependent and approximately proportional to the neutral fraction of the amine in the water. The BCFs of the quaternary ammonium compounds showed no pH dependence and were >2 orders of magnitude less than for amines of the same chain length at pH 7.6. This indicates that systemic uptake of permanently charged cationic surfactants is limited. The behavior of the quaternary ammonium compounds and the two C16amines studied was consistent with previous observations that these surfactants accumulate primarily to the gills and external surfaces of the fish. At pH 7.6 the BCF exceeded 2000 L kg–1for 4 amines with chains ≥ C13, showing that bioconcentration can be considerable for some longer chained cationic surfactants.

Bioaccumulation assessment is important for cationic surfactants in light of their use in a wide variety of consumer products and industrial processes. Because they sorb strongly to natural surfaces and to cell membranes, their bioaccumulation behavior is expected to differ from other classes of chemicals. Divided over two mixtures, we exposed rainbow trout to water containing 10 alkyl amines and 2 quaternary alkylammonium surfactants for 7 days, analyzed different fish tissues for surfactant residues, and calculated the tissues’ contribution to fish body burden. Mucus, skin, gills, liver, and muscle each contributed at least 10% of body burden for the majority of the test chemicals. This indicates that both sorption to external surfaces and systemic uptake contribute to bioaccumulation. In contrast to the analogue alkylamine bases, the permanently charged quaternary ammonium compounds accumulated mostly in the gills and were nearly absent in internal tissues, indicating that systemic uptake of the charged form of cationic surfactants is very slow. Muscle–blood distribution coefficients were close to 1 for all alkyl amines, whereas liver–blood distribution coefficients ranged from 13 to 90, suggesting that the dominant considerations for sorption in liver are different from those in blood and muscle. The significant fraction of body burden on external surfaces can have consequences for bioaccumulation assessment.

This study describes the development and evaluation of a new bioenergetically balanced bioaccumulation (3B) model for organic chemicals in fish. The 3B model is developed from a large database of routine metabolic (oxygen consumption) rates composed of a range of species, body mass, and temperatures. The chemical uptake and elimination rates of the 3B model are compared against those from three existing bioaccumulation models. A time-variant version of the 3B model is evaluated against measured concentrations of five polychlorinated biphenyls in different-size fish depurated over the course of a year, during which water temperature changed by 22 °C. The “generic” species 3B model predicts fish concentrations to within a factor of 3 of the measured data for the majority of observations (n= 438) and outperforms a previously published “species-specific” bioenergetics model. Bioenergetics aspects of the 3B model are further evaluated by comparing predicted feeding rates and growth rates to measured rates obtained from diverse laboratory conditions (n572). While bioenergetics performance is acceptable, the 3B model seems to generally perform better when ingestion rates are calculated from growth rates rather than vice versa. For field applications, parametrization of the activity multiplier remains a key uncertainty underlying the bioenergetics calculations.

Exposure- and risk-based assessments for chemicals used indoors or applied to humans (i.e., in near-field environments) necessitate an aggregate exposure pathway framework that aligns chemical exposure information from use sources to internal dose and eventually to their potential for health effects. Such a source-to-effect continuum is advocated to balance the complexity of human exposure and the insufficiency of relevant data for thousands of existing and emerging chemicals. Here, we introduce the Risk Assessment, IDentification And Ranking-Indoor and Consumer Exposure (RAIDAR-ICE) model, which establishes an integrated framework to evaluate human exposure due to indoor use and direct application of chemicals to humans. As a model evaluation, RAIDAR-ICE faithfully reproduces exposure estimates inferred from biomonitoring data for 37 chemicals with direct and indirect near-field sources. RAIDAR-ICE generates different rankings for 131 chemicals based on different exposure- and risk-based assessment metrics, demonstrating its versatility for diverse chemical screening goals. When coupled with a far-field RAIDAR model, the near-field RAIDAR-ICE model enables assessment of aggregate human exposure. Overall, RAIDAR-ICE is a powerful tool for high-throughput screening and prioritization of human exposure to neutral organic chemicals used indoors.

The main objective of this study is to develop and evaluate novel Quantitative Structure‐Property Relationships (QSPRs) for predicting entropy of fusion (ΔSM) and melting point (TM) of organic chemicals from chemical structure. The QSPRs are developed using the Iterative Fragment Selection (IFS) method that requires only 2D structural information from the user (SMILES codes) for property prediction. The QSPRs also provide information on the applicability domain for each calculation and uncertainty estimates for the predictions. The root mean square error (RMSE) for the external validation sets are 11.8 J mol−1K−1and 46.9 K for the ΔSMand TMQSPRs, respectively. The performance of the new QSPRs is comparable to other predictive methods but has advantages with respect to availability and ease of use as well as the guidance on applicability domain for each prediction. Limitations of the new QSPRs are discussed. The QSPRs are coded as a user‐friendly, freely available tool.