Review of existing terrestrial bioaccumulation models and terrestrial bioaccumulation modeling needs for organic chemicals

Protocols for terrestrial bioaccumulation assessments are far less-developed than for aquatic systems. This article reviews modeling approaches that can be used to assess the terrestrial bioaccumulation potential of commercial organic chemicals. Models exist for plant, invertebrate, mammal, and avian species and for entire terrestrial food webs, including some that consider spatial factors. Limitations and gaps in terrestrial bioaccumulation modeling include the lack of QSARs for biotransformation and dietary assimilation efficiencies for terrestrial species; the lack of models and QSARs for important terrestrial species such as insects, amphibians and reptiles; the lack of standardized testing protocols for plants with limited development of plant models; and the limited chemical domain of existing bioaccumulation models and QSARs (e.g., primarily applicable to nonionic organic chemicals). There is an urgent need for high-quality field data sets for validating models and assessing their performance. There is a need to improve coordination among laboratory, field, and modeling efforts on bioaccumulative substances in order to improve the state of the science for challenging substances.

Towards an improved understanding of processes controlling absorption efficiency and biomagnification of organic chemicals by fish

Dietary exposure is considered the dominant pathway for fish exposed to persistent, hydrophobic chemicals in the environment. Here we present a dynamic, fugacity-based three-compartment bioaccumulation model that describes the fish body as one compartment and the gastrointestinal tract (GIT) as two compartments. The model simulates uptake from the GIT by passive diffusion and micelle-mediated diffusion, and chemical degradation in the fish and the GIT compartments. We applied the model to a consistent measured dietary uptake and depuration dataset for rainbow trout (n=215) that is comprised of chlorinated benzenes, biphenyls, dioxins, diphenyl ethers, and polycyclic aromatic hydrocarbons (PAHs). Model performance relative to the measured data is statistically similar regardless of whether micelle-mediated diffusion is included; however, there are considerable uncertainties in modeling this process. When degradation in the GIT is assumed to be negligible, modeled chemical elimination rates are similar to measured rates; however, predicted concentrations of the PAHs are consistently higher than measurements by up to a factor of 20. Introducing a kinetic limit on chemical transport from the fish compartment to the GIT and increasing the rate constant for degradation of PAHs in tissues of the liver and/or GIT are required to achieve good agreement between the modelled and measured concentrations for PAHs. Our results indicate that the apparent low absorption efficiency of PAHs relative to the chemicals with similar hydrophobicity is attributable to biotransformation in the liver and/or the GIT. Our results provide process-level insights about controls on the extent of bioaccumulation of chemicals.

Application of the Activity Framework for Assessing Aquatic Ecotoxicology Data for Organic Chemicals

Toxicological research in the 1930s gave the first indications of the link between narcotic toxicity and the chemical activity of organic chemicals. More recently, chemical activity has been proposed as a novel exposure parameter that describes the fraction of saturation and that quantifies the potential for partitioning and diffusive uptake. In the present study, more than 2000 acute and chronic algal, aquatic invertebrates and fish toxicity data, as well as water solubility and melting point values, were collected from a series of sources. The data were critically reviewed and grouped by mode of action (MoA). We considered 660 toxicity data to be of acceptable quality. The 328 data which applied to the 72 substances identified as MoA 1 were then evaluated within the activity-toxicity framework: EC50 and LC50 values for all three taxa correlated generally well with (subcooled) liquid solubilities. Acute toxicity was typically exerted within the chemical activity range of 0.01-0.1, whereas chronic toxicity was exerted in the range of 0.001-0.01. These results confirm that chemical activity has the potential to contribute to the determination, interpretation and prediction of toxicity to aquatic organisms. It also has the potential to enhance regulation of organic chemicals by linking results from laboratory tests, monitoring and modeling programs. The framework can provide an additional line of evidence for assessing aquatic toxicity, for improving the design of toxicity tests, reducing animal usage and addressing chemical mixtures.

Risk-Based High-Throughput Chemical Screening and Prioritization using Exposure Models and in Vitro Bioactivity Assays

We present a risk-based high-throughput screening (HTS) method to identify chemicals for potential health concerns or for which additional information is needed. The method is applied to 180 organic chemicals as a case study. We first obtain information on how the chemical is used and identify relevant use scenarios (e.g., dermal application, indoor emissions). For each chemical and use scenario, exposure models are then used to calculate a chemical intake fraction, or a product intake fraction, accounting for chemical properties and the exposed population. We then combine these intake fractions with use scenario-specific estimates of chemical quantity to calculate daily intake rates (iR; mg/kg/day). These intake rates are compared to oral equivalent doses (OED; mg/kg/day), calculated from a suite of ToxCast in vitro bioactivity assays using in vitro-to-in vivo extrapolation and reverse dosimetry. Bioactivity quotients (BQs) are calculated as iR/OED to obtain estimates of potential impact associated with each relevant use scenario. Of the 180 chemicals considered, 38 had maximum iRs exceeding minimum OEDs (i.e., BQs > 1). For most of these compounds, exposures are associated with direct intake, food/oral contact, or dermal exposure. The method provides high-throughput estimates of exposure and important input for decision makers to identify chemicals of concern for further evaluation with additional information or more refined models.

Development and evaluation of a database of dietary bioaccumulation test data for organic chemicals in fish

Dietary bioaccumulation tests for fish have been conducted for about 40 years. Standardized test guidance has recently been developed. Test metrics of primary scientific and regulatory interest are the whole body depuration rate constant (kT), whole body growth corrected depuration rate constant (kTg), and corresponding chemical half-lives (t1/2 and t1/2g), dietary chemical absorption efficiency (AE), and biomagnification factor (BMF). A database of 3032 measurement end points for 477 discrete organic chemicals including 964 half-lives, 1199 AEs and 869 BMFs from 19 species (primarily trout and carp) was developed from the literature. Biological properties (e.g., organism weight, lipid content) and exposure conditions (e.g., temperature, feeding rate, dietary lipid content, exposure duration) are documented. Test chemicals range in molar mass from 120 to 1423 g·mol(-1) with log octanol-water partition coefficients (KOW) ranging from 0.8 to 14.3; 50% of the database entries are for polychlorinated biphenyls. The measured end points are derived from various protocols and sources of variability are described. The data are evaluated and categorized using proposed data quality (confidence) criteria derived from the standardized test protocol providing initial guidance for data users. Half-lives range from 0.13 to 2600 days; however, approximately 54% have an identifiable source of uncertainty. The data suggest that chemicals absorbed from the gastrointestinal tract with a log KOW ≥ ∼5 and at least as high as ∼9 have biomagnification potential in fish. A mechanistic bioaccumulation model is compared to the measured data and used to illustrate the influence of growth and biotransformation rates on the BMF.

Quantifying uncertainty in the trophic magnification factor related to spatial movements of organisms in a food web

Trophic magnification factors (TMFs) provide a method of assessing chemical biomagnification in food webs and are increasingly being used by policy makers to screen emerging chemicals. Recent reviews have encouraged the use of bioaccumulation models as screening tools for assessing TMFs for emerging chemicals of concern. The present study used a food web bioaccumulation model to estimate TMFs for polychlorinated biphenyls (PCBs) in a riverine system. The uncertainty associated with model predicted TMFs was evaluated against realistic ranges for model inputs (water and sediment PCB contamination) and variation in environmental, physiological, and ecological parameters included within the model. Finally, the model was used to explore interactions between spatial heterogeneity in water and sediment contaminant concentrations and theoretical movement profiles of different fish species included in the model. The model predictions of magnitude of TMFs conformed to empirical studies. There were differences in the relationship between the TMF and the octanol-water partitioning coefficient (KOW ) depending on the modeling approach used; a parabolic relationship was predicted under deterministic scenarios, whereas a linear TMF-KOW relationship was predicted when the model was run stochastically. Incorporating spatial movements by fish had a major influence on the magnitude and variation of TMFs. Under conditions where organisms are collected exclusively from clean locations in highly heterogeneous systems, the results showed bias toward higher TMF estimates, for example the TMF for PCB 153 increased from 2.7 to 5.6 when fish movement was included. Small underestimations of TMFs were found where organisms were exclusively sampled in contaminated regions, although the model was found to be more robust to this sampling condition than the former for this system.

Model for screening-level assessment of near-field human exposure to neutral organic chemicals released indoors

Screening organic chemicals for hazard and risk to human health requires near-field human exposure models that can be readily parametrized with available data. The integration of a model of human exposure, uptake, and bioaccumulation into an indoor mass balance model provides a quantitative framework linking emissions in indoor environments with human intake rates (iRs), intake fractions (iFs) and steady-state concentrations in humans (C) through consideration of dermal permeation, inhalation, and nondietary ingestion exposure pathways. Parameterized based on representative indoor and adult human characteristics, the model is applied here to 40 chemicals of relevance in the context of human exposure assessment. Intake fractions and human concentrations (C(U)) calculated with the model based on a unit emission rate to air for these 40 chemicals span 2 and 5 orders of magnitude, respectively. Differences in priority ranking based on either iF or C(U) can be attributed to the absorption, biotransformation and elimination processes within the human body. The model is further applied to a large data set of hypothetical chemicals representative of many in-use chemicals to show how the dominant exposure pathways, iF and C(U) change as a function of chemical properties and to illustrate the capacity of the model for high-throughput screening. These simulations provide hypotheses for the combination of chemical properties that may result in high exposure and internal dose. The model is further exploited to highlight the role human contaminant uptake plays in the overall fate of certain chemicals indoors and consequently human exposure.

Relationships between exposure and dose in aquatic toxicity tests for organic chemicals

There is continuing debate about the merits of exposure-based toxicity metrics such as median lethal concentration (LC50) versus organism-based metrics such as critical body residue (CBR) as indicators of chemical toxicity to aquatic organisms. To demonstrate relationships and differences between these 2 metrics, the authors applied a simple one-compartment toxicokinetic mass-balance model for water-exposed fish for a series of hypothetical organic chemicals exhibiting baseline narcotic toxicity. The authors also considered the influence of several toxicity-modifying factors. The results showed that the results of standard toxicity tests, such as the LC50, are strongly influenced by several modifying factors, including chemical and organism characteristics such as hydrophobicity, body size, lipid content, metabolic biotransformation, and exposure durations. Consequently, reported LC50s may not represent consistent dose surrogates and may be inappropriate for comparing the relative toxicity of chemicals. For comparisons of toxicity between chemicals, it is preferable to employ a delivered dose metric, such as the CBR. Reproducible toxicity data for a specific combination of chemical, exposure conditions, and organism can be obtained only if the extent of approach to steady state is known. Suggestions are made for revisions in test protocols, including the use of models in advance of empirical testing, to improve the efficiency and effectiveness of tests and reduce the confounding influences of toxicity-modifying factors, especially exposure duration and metabolic biotransformation. This will assist in linking empirical measurements of LC50s and CBRs, 2 different but related indicators of aquatic toxicity, and thereby improve understanding of the large existing database of aquatic toxicity test results.

Application of mass balance models and the chemical activity concept to facilitate the use of in vitro toxicity data for risk assessment

Practical, financial, and ethical considerations related to conducting extensive animal testing have resulted in various initiatives to promote and expand the use of in vitro testing data for chemical evaluations. Nominal concentrations in the aqueous phase corresponding to an effect (or biological activity) are commonly reported and used to characterize toxicity (or biological response). However, the true concentration in the aqueous phase can be substantially different from the nominal. To support in vitro test design and aid the interpretation of in vitro toxicity data, we developed a mass balance model that can be parametrized and applied to represent typical in vitro test systems. The model calculates the mass distribution, freely dissolved concentrations, and cell/tissue concentrations corresponding to the initial nominal concentration and experimental conditions specified by the user. Chemical activity, a metric which can be used to assess the potential for baseline toxicity to occur, is also calculated. The model is first applied to a set of hypothetical chemicals to illustrate the degree to which test conditions (e.g., presence or absence of serum) influence the distribution of the chemical in the test system. The model is then applied to set of 1194 real substances (predominantly from the ToxCast chemical database) to calculate the potential range of concentrations and chemical activities under assumed test conditions. The model demonstrates how both concentrations and chemical activities can vary by orders of magnitude for the same nominal concentration.

Using model-based screening to help discover unknown environmental contaminants

Of the tens of thousands of chemicals in use, only a small fraction have been analyzed in environmental samples. To effectively identify environmental contaminants, methods to prioritize chemicals for analytical method development are required. We used a high-throughput model of chemical emissions, fate, and bioaccumulation to identify chemicals likely to have high concentrations in specific environmental media, and we prioritized these for target analysis. This model-based screening was applied to 215 organosilicon chemicals culled from industrial chemical production statistics. The model-based screening prioritized several recognized organosilicon contaminants and generated hypotheses leading to the selection of three chemicals that have not previously been identified as potential environmental contaminants for target analysis. Trace analytical methods were developed, and the chemicals were analyzed in air, sewage sludge, and sediment. All three substances were found to be environmental contaminants. Phenyl-tris(trimethylsiloxy)silane was present in all samples analyzed, with concentrations of ∼50 pg m(-3) in Stockholm air and ∼0.5 ng g(-1) dw in sediment from the Stockholm archipelago. Tris(trifluoropropyl)trimethyl-cyclotrisiloxane and tetrakis(trifluoropropyl)tetramethyl-cyclotetrasiloxane were found in sediments from Lake Mjøsa at ∼1 ng g(-1) dw. The discovery of three novel environmental contaminants shows that models can be useful for prioritizing chemicals for exploratory assessment.

QSARs for aquatic toxicity: celebrating, extending and displaying the pioneering contributions of Ferguson, Konemann and Veith

Significant advances were made in the development of quantitative structure-activity relationships (QSARs) relating molecular structure to aquatic toxicity by three studies over 30 years ago by Ferguson in 1939, Konemann in 1981, and Veith and colleagues in 1983. We revisit the original concepts and data from these studies and review these contributions from the bases of current perspectives on the hypothesized mechanism of baseline narcotic toxicity and the underlying thermodynamic and kinetic aspects. The relationships between LC50, octanol-water partition coefficient, aqueous solubility, chemical activity and chemical volume fraction in lipid phases are outlined including kinetic influences on measured toxicities. These relationships provide a compelling and plausible explanation of the success of these and other QSARs for aquatic toxicity. Suggestions are made for further advances in these QSARs to improve assessments of toxicity by baseline narcotic toxicity and selective modes of action, especially using emerging quantum chemical computational capabilities.

Metabolic biotransformation half-lives in fish: QSAR modeling and consensus analysis

Bioaccumulation in fish is a function of competing rates of chemical uptake and elimination. For hydrophobic organic chemicals bioconcentration, bioaccumulation and biomagnification potential are high and the biotransformation rate constant is a key parameter. Few measured biotransformation rate constant data are available compared to the number of chemicals that are being evaluated for bioaccumulation hazard and for exposure and risk assessment. Three new Quantitative Structure-Activity Relationships (QSARs) for predicting whole body biotransformation half-lives (HLN) in fish were developed and validated using theoretical molecular descriptors that seek to capture structural characteristics of the whole molecule and three data set splitting schemes. The new QSARs were developed using a minimal number of theoretical descriptors (n=9) and compared to existing QSARs developed using fragment contribution methods that include up to 59 descriptors. The predictive statistics of the models are similar thus further corroborating the predictive performance of the different QSARs; Q(2)ext ranges from 0.75 to 0.77, CCCext ranges from 0.86 to 0.87, RMSE in prediction ranges from 0.56 to 0.58. The new QSARs provide additional mechanistic insights into the biotransformation capacity of organic chemicals in fish by including whole molecule descriptors and they also include information on the domain of applicability for the chemical of interest. Advantages of consensus modeling for improving overall prediction and minimizing false negative errors in chemical screening assessments, for identifying potential sources of residual error in the empirical HLN database, and for identifying structural features that are not well represented in the HLN dataset to prioritize future testing needs are illustrated.

Estimating screening-level organic chemical half-lives in humans

Relatively few measured data are available for the thousands of chemicals requiring hazard and risk assessment. The whole body, total elimination half-life (HLT) and the whole body, primary biotransformation half-life (HLB) are key parameters determining the extent of bioaccumulation, biological concentration, and risk from chemical exposure. A one-compartment pharmacokinetic (1-CoPK) mass balance model was developed to estimate organic chemical HLB from measured HLT data in mammals. Approximately 1900 HLs for human adults were collected and reviewed and the 1-CoPK model was parametrized for an adult human to calculate HLB from HLT. Measured renal clearance and whole body total clearance data for 306 chemicals were used to calculate empirical HLB,emp. The HLB,emp values and other measured data were used to corroborate the 1-CoPK HLB model calculations. HLs span approximately 7.5 orders of magnitude from 0.05 h for nitroglycerin to 2 × 10(6) h for 2,3,4,5,2',3',5',6'-octachlorobiphenyl with a median of 7.6 h. The automated Iterative Fragment Selection (IFS) method was applied to develop and evaluate various quantitative structure-activity relationships (QSARs) to predict HLT and HLB from chemical structure and two novel QSARs are detailed. The HLT and HLB QSARs show similar statistical performance; that is, r(2) = 0.89, r(2-ext) = 0.72 and 0.73 for training and external validation sets, respectively, and root-mean-square errors for the validation data sets are 0.70 and 0.75, respectively.

Evaluating the environmental fate of short-chain chlorinated paraffins (SCCPs) in the Nordic environment using a dynamic multimedia model

Short chain chlorinated paraffins (SCCPs) raise concerns due to their potential for persistence, bioaccumulation, long-range transport and adverse effects. An understanding of their environmental fate remains limited, partly due to the complexity of the mixture. The purpose of this study was to evaluate whether a mechanistic, integrated, dynamic environmental fate and bioaccumulation multimedia model (CoZMoMAN) can reconcile what is known about environmental emissions and human exposure of SCCPs in the Nordic environment. Realistic SCCP emission scenarios, resolved by formula group, were estimated and used to predict the composition and concentrations of SCCPs in the environment and the human food chain. Emissions at the upper end of the estimated range resulted in predicted total concentrations that were often within a factor of 6 of observations. Similar model performance for a complex group of organic contaminants as for the well-known polychlorinated biphenyls strengthens the confidence in the CoZMoMAN model and implies a relatively good mechanistic understanding of the environmental fate of SCCPs. However, the degree of chlorination predicted for SCCPs in sediments, fish, and humans was higher than observed and poorly established environmental half-lives and biotransformation rate constants contributed to the uncertainties in the predicted composition and ∑SCCP concentrations. Improving prediction of the SCCP composition will also require better constrained estimates of the composition of SCCP emissions. There is, however, also large uncertainty and lack of coherence in the existing observations, and better model-measurement agreement will require improved analytical methods and more strategic sampling. More measurements of SCCP levels and compositions in samples from background regions are particularly important.

Evaluation of critical body residue data for acute narcosis in aquatic organisms

The Environmental Residue Effects Database was evaluated to identify critical body residues of organic chemicals causing acute baseline neutral narcosis in aquatic organisms. Over 15 000 records for >400 chemicals were evaluated. Mean molar critical body residues in the final data set of 161 records for 29 chemicals were within published ranges but varied within and among chemicals and species (~3 orders of magnitude), and lipid normalization did not consistently decrease variability. All 29 chemicals can act as baseline neutral narcotics, but chemicals and/or their metabolites may also act by nonnarcotic modes of action. Specifically, nonnarcotic toxicity of polycyclic aromatic hydrocarbons and/or their biotransformation derivatives may be a significant source of variability. Complete testing of the narcosis-critical body residue hypothesis was confounded by data gaps for key toxicity modifying factors such as metabolite formation/toxicity, lipid content/composition, other modes of toxic action, and lack of steady-state status. Such problems impede determination of the precise, accurate toxicity estimates necessary for sound toxicological comparisons. Thus, neither the data nor the chemicals in the final data set should be considered definitive. Changes to testing designs and methods are necessary to improve data collection and critical body residue interpretation for hazard and risk assessment. Each of the toxicity metrics discussed-wet weight and lipid weight critical body residues, volume fraction in organism lipid, and chemical activity-has advantages, but all are subject to the same toxicity modifying factors.

High-throughput models for exposure-based chemical prioritization in the ExpoCast project

The United States Environmental Protection Agency (U.S. EPA) must characterize potential risks to human health and the environment associated with manufacture and use of thousands of chemicals. High-throughput screening (HTS) for biological activity allows the ToxCast research program to prioritize chemical inventories for potential hazard. Similar capabilities for estimating exposure potential would support rapid risk-based prioritization for chemicals with limited information; here, we propose a framework for high-throughput exposure assessment. To demonstrate application, an analysis was conducted that predicts human exposure potential for chemicals and estimates uncertainty in these predictions by comparison to biomonitoring data. We evaluated 1936 chemicals using far-field mass balance human exposure models (USEtox and RAIDAR) and an indicator for indoor and/or consumer use. These predictions were compared to exposures inferred by Bayesian analysis from urine concentrations for 82 chemicals reported in the National Health and Nutrition Examination Survey (NHANES). Joint regression on all factors provided a calibrated consensus prediction, the variance of which serves as an empirical determination of uncertainty for prioritization on absolute exposure potential. Information on use was found to be most predictive; generally, chemicals above the limit of detection in NHANES had consumer/indoor use. Coupled with hazard HTS, exposure HTS can place risk earlier in decision processes. High-priority chemicals become targets for further data collection.

Comparison of modeling approaches to prioritize chemicals based on estimates of exposure and exposure potential

While only limited data are available to characterize the potential toxicity of over 8 million commercially available chemical substances, there is even less information available on the exposure and use-scenarios that are required to link potential toxicity to human and ecological health outcomes. Recent improvements and advances such as high throughput data gathering, high performance computational capabilities, and predictive chemical inherency methodology make this an opportune time to develop an exposure-based prioritization approach that can systematically utilize and link the asymmetrical bodies of knowledge for hazard and exposure. In response to the US EPA's need to develop novel approaches and tools for rapidly prioritizing chemicals, a "Challenge" was issued to several exposure model developers to aid the understanding of current systems in a broader sense and to assist the US EPA's effort to develop an approach comparable to other international efforts. A common set of chemicals were prioritized under each current approach. The results are presented herein along with a comparative analysis of the rankings of the chemicals based on metrics of exposure potential or actual exposure estimates. The analysis illustrates the similarities and differences across the domains of information incorporated in each modeling approach. The overall findings indicate a need to reconcile exposures from diffuse, indirect sources (far-field) with exposures from directly, applied chemicals in consumer products or resulting from the presence of a chemical in a microenvironment like a home or vehicle. Additionally, the exposure scenario, including the mode of entry into the environment (i.e. through air, water or sediment) appears to be an important determinant of the level of agreement between modeling approaches.

Mathematical relationships between metrics of chemical bioaccumulation in fish

Five widely used metrics of bioaccumulation in fish are defined and discussed, namely the octanol-water partition coefficient (KOW ), bioconcentration factor (BCF), bioaccumulation factor (BAF), biomagnification factor (BMF), and trophic magnification factor (TMF). Algebraic relationships between these metrics are developed and discussed using conventional expressions for chemical uptake from water and food and first-order losses by respiration, egestion, biotransformation, and growth dilution. Two BCFs may be defined, namely as an equilibrium partition coefficient KFW or as a nonequilibrium BCFK in which egestion losses are included. Bioaccumulation factors are shown to be the product of the BCFK and a novel equilibrium multiplier M containing 2 ratios, namely, the diet-to-water concentration ratio and the ratio of uptake rate constants for respiration and dietary uptake. Biomagnification factors are shown to be proportional to the lipid-normalized ratio of the predator/prey values of BCFK and the ratio of the equilibrium multipliers. Relationships with TMFs are also discussed. The effects of chemical hydrophobicity, biotransformation, and growth are evaluated by applying the relationships to a range of illustrative chemicals of varying KOW in a linear 4-trophic-level food web with typical values for uptake and loss rate constants. The roles of respiratory and dietary intakes are demonstrated, and even slow rates of biotransformation and growth can significantly affect bioaccumulation. The BCFK s and the values of M can be regarded as the fundamental determinants of bioaccumulation and biomagnification in aquatic food webs. Analyzing data from food webs can be enhanced by plotting logarithmic lipid-normalized concentrations or fugacities as a linear function of trophic level to deduce TMFs. Implications for determining bioaccumulation by laboratory tests for regulatory purposes are discussed.

Toward improved models for predicting bioconcentration of well-metabolized compounds by rainbow trout using measured rates of in vitro intrinsic clearance

Models were developed to predict the bioconcentration of well-metabolized chemicals by rainbow trout. The models employ intrinsic clearance data from in vitro studies with liver S9 fractions or isolated hepatocytes to estimate a liver clearance rate, which is extrapolated to a whole-body biotransformation rate constant (kMET ). Estimated kMET values are then used as inputs to a mass-balance bioconcentration prediction model. An updated algorithm based on measured binding values in trout is used to predict unbound chemical fractions in blood, while other model parameters are designed to be representative of small fish typically used in whole-animal bioconcentration testing efforts. Overall model behavior was shown to be strongly dependent on the relative hydrophobicity of the test compound and assumed rate of in vitro activity. The results of a restricted sensitivity analysis highlight critical research needs and provide guidance on the use of in vitro biotransformation data in a tiered approach to bioaccumulation assessment.

Development and evaluation of a mechanistic bioconcentration model for ionogenic organic chemicals in fish

A mechanistic mass balance bioconcentration model is developed and parameterized for ionogenic organic chemicals (IOCs) in fish and evaluated against a compilation of empirical bioconcentration factors (BCFs). The model is subsequently applied to a set of perfluoroalkyl acids. Key aspects of model development include revised methods to estimate the chemical absorption efficiency of IOCs at the respiratory surface (E(W) ) and the use of distribution ratios to characterize the overall sorption capacity of the organism. Membrane-water distribution ratios (D(MW) ) are used to characterize sorption to phospholipids instead of only considering the octanol-water distribution ratio (D(OW) ). Modeled BCFs are well correlated with the observations (e.g., r(2)  = 0.68 and 0.75 for organic acids and bases, respectively) and accurate to within a factor of three on average. Model prediction errors appear to be largely the result of uncertainties in the biotransformation rate constant (k(M) ) estimates and the generic approaches for estimating sorption capacity (e.g., D(MW) ). Model performance for the set of perfluoroalkyl acids considered is highly dependent on the input parameters describing hydrophobicity (i.e., log K(OW) of the neutral form). The model applications broadly support the hypothesis that phospholipids contribute substantially to the sorption capacity of fish, particularly for compounds that exhibit a high degree of ionization at biologically relevant pH. Additional empirical data on biotransformation and sorption to phospholipids and subsequent incorporation into property estimation approaches (e.g., k(M) , D(MW) ) are priorities with respect to improving model performance.

Prioritizing chemicals and data requirements for screening-level exposure and risk assessment

BACKGROUND

Scientists and regulatory agencies strive to identify chemicals that may cause harmful effects to humans and the environment; however, prioritization is challenging because of the large number of chemicals requiring evaluation and limited data and resources.

OBJECTIVES

We aimed to prioritize chemicals for exposure and exposure potential and obtain a quantitative perspective on research needs to better address uncertainty in screening assessments.

METHODS

We used a multimedia mass balance model to prioritize > 12,000 organic chemicals using four far-field human exposure metrics. The propagation of variance (uncertainty) in key chemical information used as model input for calculating exposure metrics was quantified.

RESULTS

Modeled human concentrations and intake rates span approximately 17 and 15 orders of magnitude, respectively. Estimates of exposure potential using human concentrations and a unit emission rate span approximately 13 orders of magnitude, and intake fractions span 7 orders of magnitude. The actual chemical emission rate contributes the greatest variance (uncertainty) in exposure estimates. The human biotransformation half-life is the second greatest source of uncertainty in estimated concentrations. In general, biotransformation and biodegradation half-lives are greater sources of uncertainty in modeled exposure and exposure potential than chemical partition coefficients.

CONCLUSIONS

Mechanistic exposure modeling is suitable for screening and prioritizing large numbers of chemicals. By including uncertainty analysis and uncertainty in chemical information in the exposure estimates, these methods can help identify and address the important sources of uncertainty in human exposure and risk assessment in a systematic manner.

Use of the bioaccumulation factor to screen chemicals for bioaccumulation potential

The fish bioconcentration factor (BCF), as calculated from controlled laboratory tests, is commonly used in chemical management programs to screen chemicals for bioaccumulation potential. The bioaccumulation factor (BAF), as calculated from field-caught fish, is more ecologically relevant because it accounts for dietary, respiratory, and dermal exposures. The BCFBAF™ program in the U.S. Environmental Protection Agency's Estimation Programs Interface Suite (EPI Suite™ Ver 4.10) screening-level tool includes the Arnot-Gobas quantitative structure-activity relationship model to estimate BAFs for organic chemicals in fish. Bioaccumulation factors can be greater than BCFs, suggesting that using the BAF rather than the BCF for screening bioaccumulation potential could have regulatory and resource implications for chemical assessment programs. To evaluate these potential implications, BCFBAF was used to calculate BAFs and BCFs for 6,034 U.S. high- and medium-production volume chemicals. The results indicate no change in the bioaccumulation rating for 86% of these chemicals, with 3% receiving lower and 11% receiving higher bioaccumulation ratings when using the BAF rather than the BCF. All chemicals that received higher bioaccumulation ratings had log K(OW ) values greater than 4.02, in which a chemical's BAF was more representative of field-based bioaccumulation than its BCF. Similar results were obtained for 374 new chemicals. Screening based on BAFs provides ecologically relevant results without a substantial increase in resources needed for assessments or the number of chemicals screened as being of concern for bioaccumulation potential.

Iterative fragment selection: a group contribution approach to predicting fish biotransformation half-lives

There are regulatory needs to evaluate thousands of chemicals for potential hazard and risk with limited available information. An automated method is presented for developing and evaluating Quantitative Structure-Activity Relationships (QSARs) for a range of chemical properties that can be applied for screening level chemical assessments. The method is an integrated algorithm for descriptor generation, data set splitting, cross validation, and model selection. Resulting QSARs are two-dimensional (2D) fragment-based group contribution models. The QSAR development and evaluation method does not require previous expert knowledge for selecting 2D fragments associated with the chemical property of interest. The method includes information on the domain of applicability (structural similarity to the training set) and estimates of the uncertainty in the QSAR predictions. As a demonstration, the method is applied to generate novel QSARs for fish primary biotransformation half-lives (HL(N)). Results from the new HL(N) QSARs are compared to another 2D fragment-based HL(N) QSAR developed with expert judgment, and the predictive powers of the models are found to be similar. The relative merits and limitations of each method are investigated and the new QSAR is found to make comparable predictions with significantly fewer fragments. A coefficient of determination (R(2)) of 0.789 and a root mean squared error (RMSE) of 0.526 were obtained for the training data set and an R(2) of 0.748 and an RMSE of 0.584 were obtained for the validation data set, along with a concordance correlation coefficient (CCC) of 0.857 showing good predictive power.

Comparing laboratory- and field-measured biota-sediment accumulation factors

Standardized laboratory protocols for measuring the accumulation of chemicals from sediments are used in assessing new and existing chemicals, evaluating navigational dredging materials, and establishing site-specific biota-sediment accumulation factors (BSAFs) for contaminated sediment sites. The BSAFs resulting from the testing protocols provide insight into the behavior and risks associated with individual chemicals. In addition to laboratory measurement, BSAFs can also be calculated from field data, including samples from studies using in situ exposure chambers and caging studies. The objective of this report is to compare and evaluate paired laboratory and field measurement of BSAFs and to evaluate the extent of their agreement. The peer-reviewed literature was searched for studies that conducted laboratory and field measurements of chemical bioaccumulation using the same or taxonomically related organisms. In addition, numerous Superfund and contaminated sediment site study reports were examined for relevant data. A limited number of studies were identified with paired laboratory and field measurements of BSAFs. BSAF comparisons were made between field-collected oligochaetes and the laboratory test organism Lumbriculus variegatus and field-collected bivalves and the laboratory test organisms Macoma nasuta and Corbicula fluminea. Our analysis suggests that laboratory BSAFs for the oligochaete L. variegatus are typically within a factor of 2 of the BSAFs for field-collected oligochaetes. Bivalve study results also suggest that laboratory BSAFs can provide reasonable estimates of field BSAF values if certain precautions are taken, such as ensuring that steady-state values are compared and that extrapolation among bivalve species is conducted with caution.

Comparing laboratory and field measured bioaccumulation endpoints

An approach for comparing laboratory and field measures of bioaccumulation is presented to facilitate the interpretation of different sources of bioaccumulation data. Differences in numerical scales and units are eliminated by converting the data to dimensionless fugacity (or concentration-normalized) ratios. The approach expresses bioaccumulation metrics in terms of the equilibrium status of the chemical, with respect to a reference phase. When the fugacity ratios of the bioaccumulation metrics are plotted, the degree of variability within and across metrics is easily visualized for a given chemical because their numerical scales are the same for all endpoints. Fugacity ratios greater than 1 indicate an increase in chemical thermodynamic activity in organisms with respect to a reference phase (e.g., biomagnification). Fugacity ratios less than 1 indicate a decrease in chemical thermodynamic activity in organisms with respect to a reference phase (e.g., biodilution). This method provides a holistic, weight-of-evidence approach for assessing the biomagnification potential of individual chemicals because bioconcentration factors, bioaccumulation factors, biota-sediment accumulation factors, biomagnification factors, biota-suspended solids accumulation factors, and trophic magnification factors can be included in the evaluation. The approach is illustrated using a total 2393 measured data points from 171 reports, for 15 nonionic organic chemicals that were selected based on data availability, a range of physicochemical partitioning properties, and biotransformation rates. Laboratory and field fugacity ratios derived from the various bioaccumulation metrics were generally consistent in categorizing substances with respect to either an increased or decreased thermodynamic status in biota, i.e., biomagnification or biodilution, respectively. The proposed comparative bioaccumulation endpoint assessment method could therefore be considered for decision making in a chemicals management context.

Hexabromocyclododecane: current understanding of chemistry, environmental fate and toxicology and implications for global management

Hexabromocyclododecane (HBCD) is a globally produced brominated flame retardant (BFR) used primarily as an additive FR in polystyrene and textile products and has been the subject of intensified research, monitoring and regulatory interest over the past decade. HBCD is currently being evaluated under the Stockholm Convention on Persistent Organic Pollutants. HBCD is hydrophobic (i.e., has low water solubility) and thus partitions to organic phases in the aquatic environment (e.g., lipids, suspended solids). It is ubiquitous in the global environment with monitoring data generally exhibiting the expected relationship between proximity to known sources and levels; however, temporal trends are not consistent. Estimated degradation half-lives, together with data in abiotic compartments and long-range transport potential indicate HBCD may be sufficiently persistent and distributed to be of global concern. The detection of HBCD in biota in the Arctic and in source regions and available bioaccumulation data also support the case for regulatory scrutiny. Toxicity testing has detected reproductive, developmental and behavioral effects in animals where exposures are sufficient. Recent toxicological advances include a better mechanistic understanding of how HBCD can interfere with the hypothalamic-pituitary-thyroid axis, affect normal development, and impact the central nervous system; however, levels in biota in remote locations are below known effects thresholds. For many regulatory criteria, there are substantial uncertainties that reduce confidence in evaluations and thereby confound management decision-making based on currently available information.

Dechlorane plus and related compounds in the environment: a review

Dechlorane Plus (DP) is a high production volume, chlorinated flame retardant. Despite its long production history, it was only recently found in the environment. The first "sightings" of DP were in the North American Great Lakes, but subsequent work has indicated that DP is a global contaminant. For example, DP has recently been detected along a pole-to-pole transect of the Atlantic Ocean. Although it was initially thought that DP was produced only in North America, another DP production plant has recently been identified in China. During the course of characterizing DP in the environment, other "DP-like" compounds were identified. These DP analogs, some created from impurities contained in the starting materials during DP's synthesis, have also been detected globally. Screening-level modeling data are in general agreement with available environmental measurements, suggesting that DP and it analogs may be persistent, bioaccumulative, and subject to long-range transport and that these chemicals may be candidates for Annex D evaluation under the United Nations Stockholm Convention on Persistent Organic Pollutants. However, more research is required to better quantify the emissions, exposures, and toxicological effects of DP and its analogs in the environment. In particular, there is a need to obtain more monitoring, bioaccumulation, degradation rate, and toxicity information.

Chemical activity as an integrating concept in environmental assessment and management of contaminants

It is suggested that chemical activity in environmental media can serve as an integrating concept for holistic evaluations of contaminants, including their fate and effects. In support of this assertion, information underlying the thermodynamic principles and the relationships between monitored and modeled concentrations and activities are presented. The toxicological significance of activity is discussed, with emphasis on substances that exert baseline narcosis. Illustrations are given of the application of activity using models and monitoring data for chemical risk assessment and management. It is argued that the proximity of prevailing multimedia environmental activities to activities causing toxic effects is a particularly insightful metric of environmental contamination for both narcotics and reactive toxic substances.

Bioaccumulation of organic contaminants in humans: a multimedia perspective and the importance of biotransformation

Bioaccumulation is an important component of the exposure hazard assessment and risk assessment of organic chemicals. Screening criteria for chemical hazard used in national and international regulations are based on the paradigm that partitioning properties are the primary chemical determinants of bioaccumulation. We use a holistic multimedia perspective to evaluate the partitioning property paradigm with respect to assessing human bioaccumulation. Multimedia bioaccumulation factors (mmBAFs) for humans were modeled for hypothetical chemicals with a wide range of physical-chemical properties. Varying partitioning properties over 12 orders of magnitude (a plausible range for nonionizing organics) resulted in only modest changes in mmBAFs (a factor of ∼ 10) for all but very volatile or hydrophilic chemicals. In contrast, varying biotransformation rate constants over 6 orders of magnitude resulted in substantial differences in mmBAFs (greater than a factor of 10(9)). Our model results are supported by empirical observations of well characterized pollutants, which demonstrate that chemicals with similar partitioning properties can have very different bioaccumulation behavior. Susceptibility to biotransformation clearly determines bioaccumulation in humans for many chemicals. We conclude that a holistic multimedia perspective for bioaccumulation assessment is necessary to develop regulations, criteria, and policies that are protective of human health and the environment.

Toward a consistent evaluative framework for POP risk characterization

The purpose of Annex E in the Stockholm Convention (SC) on Persistent Organic Pollutants (POPs) is to assess whether a chemical is likely, as a result of its long-range environmental transport, to lead to significant adverse human health or environmental effects, such that global action is warranted. To date, risk profiles for nominated POPs have not consistently selected assessment endpoints or completed mandated risk characterizations. An assessment endpoint hierarchy is proposed to facilitate risk characterization for the implementation of the SC. The framework is illustrated for a nominated POP, hexabromocyclododecane (HBCD), using three risk estimation methods. Based on current monitoring and toxicity data, the screening-level results indicate that humans and ecological receptors in remote regions such as the Arctic are unlikely to experience significant adverse effects (i.e., low risk) due to long-range environmental transport of HBCD. The results for birds are more uncertain than the results for fish and mammals due to the paucity of avian toxicity data. Risk characterization results for HBCD and for some listed POPs are compared to illustrate how the proposed methods can further assist decision-making and chemical management.

Food web bioaccumulation model for polychlorinated biphenyls in San Francisco Bay, California, USA

We document the development and application of a food web bioaccumulation model for polychlorinated biphenyls (PCBs) in San Francisco Bay, California, USA. The model calculates spatial distributions of PCB concentrations in a range of invertebrate, fish, avian, and mammalian organisms, including harbor seals, double-crested cormorants, and Forster's terns. The performance of the model is evaluated against independent empirical PCB concentrations and shows a mean deviation between observed and model-calculated concentrations of 36% for female harbor seals and 5% for benthic invertebrates and jack smelt. The model was applied to produce bay-wide PCB concentration distributions in fish and wildlife species, which were compared with threshold effect concentrations to determine ecological risks and human health risks of fish consumption. Because of their high trophic position in the food web, harbor seals exhibited the highest concentrations of summation operatorPCBs, which exceeded threshold concentrations for potential adverse effects. The model was also applied to derive bay-wide target sediment concentrations for remediation as part of an ongoing total maximum daily loading characterization. The model calculated bay-wide geometric mean concentrations of summation operatorPCB in sediments of 1.6 to 73 microg/kg dry weight to meet several ecological and human health risk objectives. The bay-wide geometric summation operatorPCB concentration in the sediments at the time of the study was 11.6 microg/kg dry weight. The model was developed for assessing the behavior and risks of bioaccumulative substances on an ecosystem level.

Molecular size cutoff criteria for screening bioaccumulation potential: fact or fiction?

It has been asserted that, when screening chemicals for bioaccumulation potential, molecular size cutoff criteria (or indicators) can be applied above which no, or limited, bioaccumulation is expected. The suggested molecular size values have increased over time as more measurements have become available. Most of the proposed criteria have been derived from unevaluated fish bioconcentration factor (BCF) data, and less than 5% of existing organic substances have measured BCFs.We critically review the proposed criteria, first by considering other factors that may also contribute to reduced bioaccumulation for larger molecules, namely, reduced bioavailability in the water column, reduced rate of uptake corresponding to reduced diffusion rates, and the effects of biotransformation and growth dilution. An evaluated BCF and bioaccumulation factor (BAF) database for more than 700 substances and dietary uptake efficiency data are compared against proposed cutoff values. We examine errors associated with interpreting BCF data, particularly for developing molecular size criteria of bioaccumulation potential. Reduced bioaccumulation that is often associated with larger molecular size can be explained by factors other than molecular size, and there is evidence of absorption of molecules exceeding the proposed cutoff criteria. The available data do not support strict cutoff criteria, indicating that the proposed values are incorrect. Rather than assessing bioaccumulation using specific chemical properties in isolation, holistic methods that account for competing rates of uptake and elimination in an organism are recommended. An integrated testing strategy is suggested to improve knowledge of the absorption and bioaccumulation of large substances.

Multimedia modeling of human exposure to chemical substances: the roles of food web biomagnification and biotransformation

The Risk Assessment IDentification And Ranking (RAIDAR) model is refined to calculate relative human exposures as expressed by total intake, intake fraction (iF), and total body burden (TBB) metrics. The RAIDAR model is applied to three persistent organic pollutants (POPs) and six petrochemicals using four mode-of-entry emission scenarios to evaluate the effect of metabolic biotransformation estimates on human exposure calculations. When biotransformation rates are assumed to be negligible, daily intake and iFs for the nine substances ranged over six orders of magnitude and TBBs ranged over 10 orders of magnitude. Including biotransformation estimates for fish, birds, and mammals reduced substance-specific daily intake and iF by up to 4.5 orders of magnitude and TBB by more than eight orders of magnitude. The RAIDAR iF calculations are compared to the European Union System for the Evaluation of Substances (EUSES) model iF calculations and differences are discussed, especially the treatment of food web bioaccumulation. Model selection and application assumptions result in different rankings of human exposure potential. These results suggest a need to critically consider model selection and to include reliable biotransformation rate estimates when assessing relative human exposure and ranking substances for priority setting. Recommendations for further model evaluations and revisions are discussed.

Modeling exposure to persistent chemicals in hazard and risk assessment

Fate and exposure modeling has not, thus far, been explicitly used in the risk profile documents prepared for evaluating the significant adverse effect of candidate chemicals for either the Stockholm Convention or the Convention on Long-Range Transboundary Air Pollution. However, we believe models have considerable potential to improve the risk profiles. Fate and exposure models are already used routinely in other similar regulatory applications to inform decisions, and they have been instrumental in building our current understanding of the fate of persistent organic pollutants (POP) and persistent, bioaccumulative, and toxic (PBT) chemicals in the environment. The goal of this publication is to motivate the use of fate and exposure models in preparing risk profiles in the POP assessment procedure by providing strategies for incorporating and using models. The ways that fate and exposure models can be used to improve and inform the development of risk profiles include 1) benchmarking the ratio of exposure and emissions of candidate chemicals to the same ratio for known POPs, thereby opening the possibility of combining this ratio with the relative emissions and relative toxicity to arrive at a measure of relative risk; 2) directly estimating the exposure of the environment, biota, and humans to provide information to complement measurements or where measurements are not available or are limited; 3) to identify the key processes and chemical or environmental parameters that determine the exposure, thereby allowing the effective prioritization of research or measurements to improve the risk profile; and 4) forecasting future time trends, including how quickly exposure levels in remote areas would respond to reductions in emissions. Currently there is no standardized consensus model for use in the risk profile context. Therefore, to choose the appropriate model the risk profile developer must evaluate how appropriate an existing model is for a specific setting and whether the assumptions and input data are relevant in the context of the application. It is possible to have confidence in the predictions of many of the existing models because of their fundamental physical and chemical, mechanistic underpinnings and the extensive work already done to compare model predictions and empirical observations. The working group recommends that modeling tools be applied for benchmarking PBT and POPs according to exposure-emissions relationships and that modeling tools be used to interpret emissions and monitoring data. The further development of models that combine fate, long-range transport, and bioaccumulation should be fostered, especially models that will allow time trends to be scientifically addressed in the risk profile.

A cautionary note on implications of the well-mixed compartment assumption as applied to mass balance models of chemical fate in flowing systems

A convenient, simple, and widely used approach for modeling the fate of a chemical in a flowing environmental or biological system is to simulate the system as comprising one or more well-mixed boxes, also known as continuous stirred tank reactors (CSTRs). In principle, any desired level of accuracy can be achieved by increasing the number of boxes. However, highly segmented systems require more input data, they are more computationally intensive, and the results may be more difficult to interpret. Thus there is a tendency to minimize the number of boxes, especially in screening level models. Whereas in the hydrology and engineering literature there is an appreciation of the mathematical errors associated with applying the well-mixed box concept, we believe that these errors are often underappreciated when modeling certain environmental systems. Here, we briefly review the implications of these errors in multimedia models, river and lake simulations, atmospheric transport, flow in soils, gastrointestinal absorption, and metabolism in the liver. The key conclusion is that if over 25% of the chemical entering a box is removed, applying this well-mixed assumption can lead to substantial error. We recommend that results obtained when this criterion is violated be treated with caution.

A quantitative structure-activity relationship for predicting metabolic biotransformation rates for organic chemicals in fish

An evaluated database of whole body in vivo biotransformation rate estimates in fish was used to develop a model for predicting the primary biotransformation half-lives of organic chemicals. The estimated biotransformation rates were converted to half-lives and divided into a model development set (n=421) and an external validation set (n=211) to test the model. The model uses molecular substructures similar to those of other biodegradation models. The biotransformation half-life predictions were calculated based on multiple linear regressions of development set data against counts of 57 molecular substructures, the octanol-water partition coefficient, and molar mass. The coefficient of determination (r2) for the development set was 0.82, the cross-validation (leave-one-out coefficient of determination, q2) was 0.75, and the mean absolute error (MAE) was 0.38 log units (factor of 2.4). Results for the external validation of the model using an independent test set were r2 = 0.73 and MAE = 0.45 log units (factor of 2.8). For the development set, 68 and 95% of the predicted values were within a factor of 3 and a factor of 10 of the expected values, respectively. For the test (or validation) set, 63 and 90% of the predicted values were within a factor of 3 and a factor of 10 of the expected values, respectively. Reasons for discrepancies between model predictions and expected values are discussed and recommendations are made for improving the model. This model can predict biotransformation rate constants from chemical structure for screening level bioaccumulation hazard assessments, exposure and risk assessments, comparisons with other in vivo and in vitro estimates, and as a contribution to testing strategies that reduce animal usage.

Modeling bioaccumulation using characteristic times

A new formulation of existing mass balance models for bioaccumulation is derived and applied to organisms that respire either water or air. This model employs characteristic time parameters and equations that are mathematically equivalent to those used in existing concentration-rate constant and fugacity models. The equivalence of these traditional formulations and the novel formulation is demonstrated. In all three formulations, the required information includes various physiological and dietary parameters as well as chemical concentrations in food and in the respired medium of water or air. Chemical properties are described by the octanol-water or octanol-air partition coefficient and a metabolic biotransformation half-life. Bioaccumulation, biomagnification, and all uptake and loss rates are expressed using characteristic times that have readily identifiable chemical or biological significance. The ability of the characteristic time formulation to provide an evaluation of the bioenergetic consistency of organism properties is briefly discussed. The model is applied illustratively to a trout as a water-respiring organism and to a wolf as an air-respiring organism, and the results are discussed. It is concluded that the use of characteristic time parameters and equations provides valuable additional insights regarding the relative importance of the various uptake and loss processes and, thus, is complementary to the conventional approaches for modeling bioaccumulation phenomena in a variety of organisms.

The physicochemical basis of QSARs for baseline toxicity

The physico-chemical properties relevant to the equilibrium partitioning (bioconcentration) of chemicals between organisms and their respired media of water and air are reviewed and illustrated for chemicals that range in hydrophobicity. Relationships are then explored between freely dissolved external concentrations such as LC50s and chemical properties for one important toxicity mechanism, namely baseline toxicity or narcosis. The 'activity hypothesis' proposed by Ferguson in 1939 provides a coherent and compelling explanation for baseline toxicity of chemicals in both water- and air-respiring organisms, as well as a reference point for identifying more specific toxicity pathways. From inhalation studies with fish and rodents, narcosis is shown to occur at a chemical activity exceeding approximately 0.01 and there is no evidence of narcosis at activities less than 0.001. The activity hypothesis provides a framework for directly comparing the toxic potency of chemicals in both air- and water-breathing animals. The activity hypothesis is shown to be consistent with the critical body residue concept, but it has the advantage of avoiding the confounding effect of lipid content of the test organism. It also provides a theoretically sound basis for assessing the baseline toxicity of mixtures. It is suggested that since activity is readily calculated from fugacity, observed or predicted environmental abiotic and biotic fugacities can be used to evaluate the potential for baseline toxicity. Further, models employing fugacity or activity can be used to improve the experimental design of bioassays, thus possibly reducing unnecessary animal testing.

A database of fish biotransformation rates for organic chemicals

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.

Policies for chemical hazard and risk priority setting: can persistence, bioaccumulation, toxicity, and quantity information be combined?

Existing methods used to screen chemical inventories for hazardous substances that may pose risks to humans and the environment are evaluated with a holistic mass balance modeling approach. The model integrates persistence (P), bioaccumulation (B), toxicity (T), and quantity (Q) information for a specific substance to assess chemical exposure, hazard, and risk. P and B are combined in an exposure assessment factor (EAF), P, B, and T in a hazard assessment factor (HAF), and P, B, T, and Q in a risk assessment factor (RAF) providing single values for transparent comparisons of exposure, hazard, and risk for priority setting. This holistic approach is illustrated using 200 Canadian Domestic Substances List(DSL) chemicals and 12 United Nations listed Persistent Organic Pollutants (POPs). Priority setting results are evaluated with those of multiple category-based screening methods employed by Environment Canada and applied elsewhere that use cutoff criteria in multiple categories (P, B, and T) to identify hazardous chemicals for more comprehensive evaluations. Existing methods have categorized the DSL chemicals as either higher priority (requiring further assessment; screened in) or lower priority (requiring no further action at this time; screened out). The priority setting results of the cutoff-based categorization are largely inconsistent with the proposed integrated method, and reasons for these discrepancies are discussed. Many chemicals screened out using existing methods have equivalent or greater risk potential than chemicals screened in. Decisions for screening assessments using binary classification on the basis of cutoff criteria can be flawed, and complementary holistic methods for priority setting evaluations such as the one proposed should be considered.

Guidance for evaluating in vivo fish bioaccumulation data

Currently, the laboratory-derived fish bioconcentration factor (BCF) serves as one of the primary data sources used to assess the potential for a chemical to bioaccumulate. Consequently, fish BCF values serve a central role in decision making and provide the basis for development of quantitative structure-property relationships (QSPRs) used to predict the bioaccumulation potential of untested compounds. However, practical guidance for critically reviewing experimental BCF studies is limited. This lack of transparent guidance hinders improvement in predictive models and can lead to uninformed chemical management decisions. To address this concern, a multiple-stakeholder workshop of experts from government, industry, and academia was convened by the International Life Sciences Institute Health and Environmental Sciences Institute to examine the data availability and quality issues associated with in vivo fish bioconcentration and bioaccumulation data. This paper provides guidance for evaluating key aspects of study design and conduct that must be considered when judging the reliability and adequacy of reported laboratory bioaccumulation data. Key criteria identified for judging study reliability include 1) clear specification of test substance and fish species investigated, 2) analysis of test substance in both fish tissue and exposure medium, 3) no significant adverse effects on exposed test fish, and 4) a reported test BCF that reflects steady-state conditions with unambiguous units. This guidance is then applied to 2 data-rich chemicals (anthracene and 2,3,7,8-tetrachlorodibenzo-p-dioxin) to illustrate the critical need for applying a systematic data quality assessment process. Use of these guidelines will foster development of more accurate QSPR models, improve the performance and reporting of future laboratory studies, and strengthen the technical basis for bioaccumulation assessment in chemicals management.

Estimating metabolic biotransformation rates in fish from laboratory data

A method is proposed for estimating metabolic biotransformation rate constants for nonionic organic chemicals from measured laboratory bioconcentration and dietary bioaccumulation data in fish. Data have been selected based on a quality review to reduce uncertainty in the measured values. A kinetic mass balance model is used to estimate rates of chemical uptake and elimination. Biotransformation rate constants are essentially calculated as the difference between two quantities, a measured bioconcentration factor or elimination rate constant, and a model-derived bioconcentration factor or elimination rate constant estimated assuming no biotransformation. Model parameterization exploits key empirical data when they are available and assumes default values when study specific data are unavailable. Uncertainty analyses provide screening level assessments for confidence in the biotransformation rate constant estimates. The uncertainty analyses include the range for 95% of the predicted values and 95% confidence intervals for the calculated biotransformation values. Case studies are provided to illustrate the calculation and uncertainty methods. Biotransformation rate constants calculated by the proposed method are compared with other published estimates for 31 chemicals that range in octanol-water partition coefficients from approximately 10(1) to 10(8) and represent over four orders of magnitude in biotransformation potential. The comparison of previously published values with those calculated by the proposed method shows general agreement with 82% of the estimated values falling within a factor of three.

Screening level risk assessment model for chemical fate and effects in the environment

A screening level risk assessment model is developed and described to assess and prioritize chemicals by estimating environmental fate and transport, bioaccumulation, and exposure to humans and wildlife for a unit emission rate. The most sensitive risk endpoint is identified and a critical emission rate is then calculated as a result of that endpoint being reached. Finally, this estimated critical emission rate is compared with the estimated actual emission rate as a risk assessment factor. This "back-tracking" process avoids the use of highly uncertain emission rate data as model input. The application of the model is demonstrated in detail for three diverse chemicals and in less detail for a group of 70 chemicals drawn from the Canadian Domestic Substances List. The simple Level II and the more complex Level III fate calculations are used to "bin" substances into categories of similar probable risk. The essential role of the model is to synthesize information on chemical and environmental properties within a consistent mass balance framework to yield an overall estimate of screening level risk with respect to the defined endpoint. The approach may be useful to identify and prioritize those chemicals of commerce that are of greatest potential concern and require more comprehensive modeling and monitoring evaluations in actual regional environments and food webs.

A food web bioaccumulation model for organic chemicals in aquatic ecosystems

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.