Bioaccumulation assessment is important in the scientific evaluation of risks that chemicals may pose to humans and the environment and is a current focus of regulatory effort. The status of bioaccumulation evaluations for organic chemicals in aquatic systems is reviewed to reduce uncertainty in bioaccumulation measurement, to provide quality data for assessment, and to assist in model development. A review of 392 scientific literature and database sources includes 5317 bioconcentration factor (BCF) and 1656 bioaccumulation factor (BAF) values measured for 842 organic chemicals in 219 aquatic species. A data quality assessment finds that 45% of BCF values are subject to at least one major source of uncertainty and that measurement errors generally result in an underestimation of actual BCF values. A case study of organic chemicals on the Canadian Domestic Substances List indicates that empirical data are available for less than 4% of the chemicals that require evaluation and of these chemicals, 76% have less than three acceptable quality BCF or BAF values. Field BAFs tend to be greater than laboratory BCFs emphasizing the importance of environmental measurement for reliable assessment; however, only 0.2% of current use organic chemicals have BAF measurements. Key parameters influencing uncertainty and variability in BCF and BAF data are discussed using reviewed data and models. A critical evaluation of representative BCF and BAF models in relation to existing measurements and regulatory criteria in Canada indicate the probability of Type II errors, i.e., false negatives or ``misses'', using BCF models for bioaccumulation assessment may be as high as 70.6% depending on the model. Recommendations for the selection of measured and modelled values used in bioaccumulation assessment are provided, and improvements for the science and regulatory criteria are proposed.Key words: bioconcentration, bioconcentration factor, bioaccumulation, bioaccumulation factor, octanol–water partition coefficient, fish.

The present study examines a new bioaccumulation model for hydrophobic organic chemicals in aquatic food webs. The purpose of the model is to provide site-specific estimates of chemical concentrations and associated bioconcentration factors, bioaccumulation factors, and biota-sediment accumulation factors in organisms of aquatic food webs using a limited number of chemical, organism, and site-specific data inputs. The model is a modification of a previous model and incorporates new insights regarding the mechanism of bioaccumulation derived from laboratory experiments and field studies as well as improvements in model parameterization. The new elements of the model include: A model for the partitioning of chemicals into organisms; kinetic models for predicting chemical concentrations in algae, phytoplankton, and zooplankton; new allometric relationships for predicting gill ventilation rates in a wide range of aquatic species; and a mechanistic model for predicting gastrointestinal magnification of organic chemicals in a range of species. Model performance is evaluated using empirical data from three different freshwater ecosystems involving 1,019 observations for 35 species and 64 chemicals. The effects of each modification on the model's performance are illustrated. The new model is able to provide better estimates of bioaccumulation factors in comparison to the previous food web bioaccumulation model while the model input requirements remain largely unchanged.

Substances that accumulate to hazardous levels in living organisms pose environmental and human-health risks, which governments seek to reduce or eliminate. Regulatory authorities identify bioaccumulative substances as hydrophobic, fat-soluble chemicals having high octanol-water partition coefficients (K(OW))(>/=100,000). Here we show that poorly metabolizable, moderately hydrophobic substances with a K(OW) between 100 and 100,000, which do not biomagnify (that is, increase in chemical concentration in organisms with increasing trophic level) in aquatic food webs, can biomagnify to a high degree in food webs containing air-breathing animals (including humans) because of their high octanol-air partition coefficient (K(OA)) and corresponding low rate of respiratory elimination to air. These low K(OW)-high K(OA) chemicals, representing a third of organic chemicals in commercial use, constitute an unidentified class of potentially bioaccumulative substances that require regulatory assessment to prevent possible ecosystem and human-health consequences.

Recent reviews by researchers from academia, industry, and government have revealed that the criteria used by the Stockholm Convention on persistent organic pollutants under the United Nations Environment Programme are not always able to identify the actual bioaccumulative capacity of some substances, by use of chemical properties such as the octanol-water partitioning coefficient. Trophic magnification factors (TMFs) were suggested as a more reliable tool for bioaccumulation assessment of chemicals that have been in commerce long enough to be quantitatively measured in environmental samples. TMFs are increasingly used to quantify biomagnification and represent the average diet-to-consumer transfer of a chemical through food webs. They differ from biomagnification factors, which apply to individual species and can be highly variable between predator-prey combinations. The TMF is calculated from the slope of a regression between the chemical concentration and trophic level of organisms in the food web. The trophic level can be determined from stable N isotope ratios (δ(15) N). In this article, we give the background for the development of TMFs, identify and discuss impacts of ecosystem and ecological variables on their values, and discuss challenges and uncertainties associated with contaminant measurements and the use of δ(15) N for trophic level estimations. Recommendations are provided for experimental design, data treatment, and statistical analyses, including advice for users on reporting and interpreting TMF data. Interspecies intrinsic ecological and organismal properties such as thermoregulation, reproductive status, migration, and age, particularly among species at higher trophic levels with high contaminant concentrations, can influence the TMF (i.e., regression slope). Following recommendations herein for study design, empirical TMFs are likely to be useful for understanding the food web biomagnification potential of chemicals, where the target is to definitively identify if chemicals biomagnify (i.e., TMF > or < 1). TMFs may be less useful in species- and site-specific risk assessments, where the goal is to predict absolute contaminant concentrations in organisms in relation to threshold levels.