Environmental Safety of the Use of Major Surfactant Classes in North America.

This paper brings together over 250 published and unpublished studies on the environmental properties, fate, and toxicity of the four major, high-volume surfactant classes and relevant feedstocks. The surfactants and feedstocks covered include alcohol sulfate or alcohol sulfate (AS), alcohol ethoxysulfate (AES), linear alkylbenzene sulfonate (LAS), alcohol ethoxylate (AE), and long-chain alcohol (LCOH). These chemicals are used in a wide range of personal care and cleaning products. To date, this is the most comprehensive report on these substance's chemical structures, use, and volume information, physical/chemical properties, environmental fate properties such as biodegradation and sorption, monitoring studies through sewers, wastewater treatment plants and eventual release to the environment, aquatic and sediment toxicity, and bioaccumulation information. These data are used to illustrate the process for conducting both prospective and retrospective risk assessments for large-volume chemicals and categories of chemicals with wide dispersive use. Prospective risk assessments of AS, AES, AE, LAS, and LCOH demonstrate that these substances, although used in very high volume and widely released to the aquatic environment, have no adverse impact on the aquatic or sediment environments at current levels of use. The retrospective risk assessments of these same substances have clearly demonstrated that the conclusions of the prospective risk assessments are valid and confirm that these substances do not pose a risk to the aquatic or sediment environments. This paper also highlights the many years of research that the surfactant and cleaning products industry has supported, as part of their environmental sustainability commitment, to improve environmental tools, approaches, and develop innovative methods appropriate to address environmental properties of personal care and cleaning product chemicals, many of which have become approved international standard methods.

Protein and lipid binding parameters in rainbow trout (Oncorhynchus mykiss) blood and liver fractions to extrapolate from an in vitro metabolic degradation assay to in vivo bioaccumulation potential of hydrophobic organic chemicals.

Binding of hydrophobic chemicals to colloids such as proteins or lipids is difficult to measure using classical microdialysis methods due to low aqueous concentrations, adsorption to dialysis membranes and test vessels, and slow kinetics of equilibration. Here, we employed a three-phase partitioning system where silicone (polydimethylsiloxane, PDMS) serves as a third phase to determine partitioning between water and colloids and acts at the same time as a dosing device for hydrophobic chemicals. The applicability of this method was demonstrated with bovine serum albumin (BSA). Measured binding constants (K(BSAw)) for chlorpyrifos, methoxychlor, nonylphenol, and pyrene were in good agreement with an established quantitative structure-activity relationship (QSAR). A fifth compound, fluoxypyr-methyl-heptyl ester, was excluded from the analysis because of apparent abiotic degradation. The PDMS depletion method was then used to determine partition coefficients for test chemicals in rainbow trout (Oncorhynchus mykiss) liver S9 fractions (K(S9w)) and blood plasma (K(bloodw)). Measured K(S9w) and K(bloodw) values were consistent with predictions obtained using a mass-balance model that employs the octanol-water partition coefficient (K(ow)) as a surrogate for lipid partitioning and K(BSAw) to represent protein binding. For each compound, K(bloodw) was substantially greater than K(S9w), primarily because blood contains more lipid than liver S9 fractions (1.84% of wet weight vs 0.051%). Measured liver S9 and blood plasma binding parameters were subsequently implemented in an in vitro to in vivo extrapolation model to link the in vitro liver S9 metabolic degradation assay to in vivo metabolism in fish. Apparent volumes of distribution (V(d)) calculated from the experimental data were similar to literature estimates. However, the calculated binding ratios (f(u)) used to relate in vitro metabolic clearance to clearance by the intact liver were 10 to 100 times lower than values used in previous modeling efforts. Bioconcentration factors (BCF) predicted using the experimental binding data were substantially higher than the predicted values obtained in earlier studies and correlated poorly with measured BCF values in fish. One possible explanation for this finding is that chemicals bound to proteins can desorb rapidly and thus contribute to metabolic turnover of the chemicals. This hypothesis remains to be investigated in future studies, ideally with chemicals of higher hydrophobicity.

Perspectives on advancing consumer product exposure models.

Predictive models are used to estimate exposures from consumer products to support risk management decision-making. These model predictions may be used alone in the absence of measured data or integrated with available exposure data. When different models are used, the resulting estimates of exposure and conclusions of risk may be disparate and the origin of these differences may not be obvious. This Perspectives Paper provides recommendations that could promote more systematic evaluation and a wider range of applicability of consumer product exposure models and their predictions, improve confidence in model predictions, and result in more accurate communication of consumer exposure model estimates. Key insights for the exposure science community to consider include: consistency in product descriptions, exposure routes, and scenarios; consistent and explicit definitions of exposure metrics; situation-dependent benefits from using one or multiple models; distinguishing between model algorithms and exposure factors; and corroboration of model predictions with measured data.

Exposure to selected preservatives in personal care products: case study comparison of exposure models and observational biomonitoring data.

Exposure models provide critical information for risk assessment of personal care product ingredients, but there have been limited opportunities to compare exposure model predictions to observational exposure data. Urinary excretion data from a biomonitoring study in eight individuals were used to estimate minimum absorbed doses for triclosan and methyl-, ethyl-, and n-propyl- parabens (TCS, MP, EP, PP). Three screening exposure models (European Commission Scientific Commission on Consumer Safety [SCCS] algorithms, ConsExpo in deterministic mode, and RAIDAR-ICE) and two higher-tier probabilistic models (SHEDS-HT, and Creme Care & Cosmetics) were used to model participant exposures. Average urinary excretion rates of TCS, MP, EP, and PP for participants using products with those ingredients were 16.9, 3.32, 1.9, and 0.91 µg/kg-d, respectively. The SCCS default aggregate and RAIDAR-ICE screening models generally resulted in the highest predictions compared to other models. Approximately 60-90% of the model predictions for most of the models were within a factor of 10 of the observed exposures; ~30-40% of the predictions were within a factor of 3. Estimated exposures from urinary data tended to fall in the upper range of predictions from the probabilistic models. This analysis indicates that currently available exposure models provide estimates that are generally realistic. Uncertainties in preservative product concentrations and dermal absorption parameters as well as degree of metabolism following dermal absorption influence interpretation of the modeled vs. measured exposures. Use of multiple models may help characterize potential exposures more fully than reliance on a single model.

Refining aggregate exposure: example using parabens.

The need to understand and estimate quantitatively the aggregate exposure to ingredients used broadly in a variety of product types continues to grow. Currently aggregate exposure is most commonly estimated by using a very simplistic approach of adding or summing the exposures from all the individual product types in which the chemical is used. However, the more broadly the ingredient is used in related consumer products, the more likely this summation will result in an unrealistic estimate of exposure because individuals in the population vary in their patterns of product use including co-use and non-use. Furthermore the ingredient may not be used in all products of a given type. An approach is described for refining this aggregate exposure using data on (1) co-use and non-use patterns of product use, (2) extent of products in which the ingredient is used and (3) dermal penetration and metabolism. This approach and the relative refinement in the aggregate exposure from incorporating these data is illustrated using methyl, n-propyl, n-butyl and ethyl parabens, the most widely used preservative system in personal care and cosmetic products. When these refining factors were used, the aggregate exposure compared to the simple addition approach was reduced by 51%, 58%, 90% and 92% for methyl, n-propyl, n-butyl and ethyl parabens, respectively. Since biomonitoring integrates all sources and routes of exposure, the estimates using this approach were compared to available paraben biomonitoring data. Comparison to the 95th percentile of these data showed that these refined estimates were still conservative by factors of 2-92. All of our refined estimates of aggregate exposure are less than the ADI of 10mg/kg/day for parabens.

The state of in vitro science for use in bioaccumulation assessments for fish.

Through the concerted evaluations of thousands of commercial substances for the qualities of persistence, bioaccumulation, and toxicity as a result of the United Nations Environment Program's Stockholm Convention, it has become apparent that fewer empirical data are available on bioaccumulation than other endpoints and that bioaccumulation models were not designed to accommodate all chemical classes. Due to the number of chemicals that may require further assessment, in vivo testing is cost prohibitive and discouraged due to the large number of animals needed. Although in vitro systems are less developed and characterized for fish, multiple high-throughput in vitro assays have been used to explore the dietary uptake and elimination of pharmaceuticals and other xenobiotics by mammals. While similar processes determine bioaccumulation in mammalian species, a review of methods to measure chemical bioavailability in fish screening systems, such as chemical biotransformation or metabolism in tissue slices, perfused tissues, fish embryos, primary and immortalized cell lines, and subcellular fractions, suggest quantitative and qualitative differences between fish and mammals exist. Using in vitro data in assessments for whole organisms or populations requires certain considerations and assumptions to scale data from a test tube to a fish, and across fish species. Also, different models may incorporate the predominant site of metabolism, such as the liver, and significant presystemic metabolism by the gill or gastrointestinal system to help accurately convert in vitro data into representative whole-animal metabolism and subsequent bioaccumulation potential. The development of animal alternative tests for fish bioaccumulation assessment is framed in the context of in vitro data requirements for regulatory assessments in Europe and Canada.

Axilla surface area for males and females: measured distribution.

With the recent introduction of exposure-based Quantitative Risk Assessment (QRA) as an approach to the evaluation, of materials in finished consumer products that are potential dermal sensitizers, the need for robust exposure data was clearly identified. The objective of this current study is to provide a value for the axilla surface area (SA) that is statistically derived and can be used in dermal sensitization QRA for ingredients of personal care products meant for use on the axilla. The axilla surface area measured for 60 men and 60 women resulted in a median surface area for a single axilla of 64.5 cm(2) for females and 135.5 cm(2) for males. These participants were representative of the United States population in their range of heights and weights. Furthermore, combining these surface area data with measured use data from this and other studies has enabled calculations of consumer exposure to solid APDO products on a dose/unit area/day basis (9.1 mg/cm(2)/d).

In vitro biotransformation of surfactants in fish. Part I: linear alkylbenzene sulfonate (C12-LAS) and alcohol ethoxylate (C13EO8).

Developing regulatory activities (e.g., REACh, [DGEE. 2003. Directorates General Enterprise and Environment. The new EU chemicals legislation REACH. DG Enterprise, Brussels, Belgium. (http://www.europa.eu.int/comm/enterprise/reach/index_en.htm)]) will require bioaccumulation to be assessed for thousands of chemicals. Further, there is increasing pressure to reduce, refine or replace animal tests. Given this scenario, there is an urgent need to evaluate the feasibility of in vitro systems to supply data useful for bioaccumulation estimation. Subcellular and cellular hepatic systems were tested to determine the biotransformation of two surfactants: C12-2-LAS (2-phenyl dodecane p-sulfonate) and an alcohol ethoxylate C13EO8 (Octaethylene glycol monotridecyl ether). The subcellular systems tested were liver homogenates and microsomes from the common carp (Cyprinus carpio) and rainbow trout (Oncorhynchus mykiss). Cellular systems consisted of primary hepatocytes from the common carp (Cyprinus carpio) and PLHC-1 cells, hepatocarcinoma cells from the desert topminnow (Poeciliopsis lucida). All in vitro systems were exposed to radiolabeled test compounds and assayed for biotransformation using liquid scintillation and thin layer chromatographic methods. First-order kinetics were used to estimate rates of biotransformation. Bioconcentration of test materials in fish were predicted using an in vitro to in vivo metabolic rate extrapolation model linked to a mass-balance model commonly used to predict bioaccumulation in fish. Subcellular biotransformation rates for each of the surfactants were greatest with microsomes. Cellular loss rates exceeded subcellular rates, leading to lower predicted BCF values. Predicted BCFs corresponded closely to measured values in several fish species, verifying the utility of in vitro systems in refining Kow-only-based BCFs via the inclusion of biotransformation rates.

Approach for extrapolating in vitro metabolism data to refine bioconcentration factor estimates.

National and international chemical management programs are assessing thousands of chemicals for their persistence, bioaccumulative and environmental toxic properties; however, data for evaluating the bioaccumulation potential for fish are limited. Computer based models that account for the uptake and elimination processes that contribute to bioaccumulation may help to meet the need for reliable estimates. One critical elimination process of chemicals is metabolic transformation. It has been suggested that in vitro metabolic transformation tests using fish liver hepatocytes or S9 fractions can provide rapid and cost-effective measurements of fish metabolic potential, which could be used to refine bioconcentration factor (BCF) computer model estimates. Therefore, recent activity has focused on developing in vitro methods to measure metabolic transformation in cellular and subcellular fish liver fractions. A method to extrapolate in vitro test data to the whole body metabolic transformation rates is presented that could be used to refine BCF computer model estimates. This extrapolation approach is based on concepts used to determine the fate and distribution of drugs within the human body which have successfully supported the development of new pharmaceuticals for years. In addition, this approach has already been applied in physiologically-based toxicokinetic models for fish. The validity of the in vitro to in vivo extrapolation is illustrated using the rate of loss of parent chemical measured in two independent in vitro test systems: (1) subcellular enzymatic test using the trout liver S9 fraction, and (2) primary hepatocytes isolated from the common carp. The test chemicals evaluated have high quality in vivo BCF values and a range of logK(ow) from 3.5 to 6.7. The results show very good agreement between the measured BCF and estimated BCF values when the extrapolated whole body metabolism rates are included, thus suggesting that in vitro biotransformation data could effectively be used to reduce in vivo BCF testing and refine BCF model estimates. However, additional fish physiological data for parameterization and validation for a wider range of chemicals are needed.

Decamethylcyclopentasiloxane (D5) environmental sources, fate, transport, and routes of exposure.

The environmental sources, fate, transport, and routes of exposure of decamethylcyclopentasiloxane (D5; CAS no. 541-02-6) are reviewed in the present study, with the objective of contributing to effective risk evaluation and assessment of this and related substances. The present review, which is part of a series of studies discussing aspects of an effective risk evaluation and assessment, was prompted in part by the findings of a Board of Review undertaken to comment on a decision by Environment Canada made in 2008 to subject D5 to regulation as a toxic substance. The present review focuses on the early stages of the assessment process and how information on D5's physical-chemical properties, uses, and fate in the environment can be integrated to give a quantitative description of fate and exposure that is consistent with available monitoring data. Emphasis is placed on long-range atmospheric transport and fate in water bodies receiving effluents from wastewater treatment plants (along with associated sediments) and soils receiving biosolids. The resulting exposure estimates form the basis for assessments of the resulting risk presented in other studies in this series. Recommendations are made for developing an improved process by which D5 and related substances can be evaluated effectively for risk to humans and the environment.

Putting science into persistence, bioaccumulation, and toxicity evaluations.

In recent decades, advances have been made in the processes used to identify substances as persistent, bioaccumulative, and toxic (PBT). Key processes have been identified, and scientifically sound assessment methods have been developed. Regulatory agencies around the world have sought practical methods for implementing policies to protect both environment and human health. In the present paper, we review the various contributions that Mackay (in collaboration with his students and colleagues) has made to the development of scientifically sound methods for the identification of PBT substances and persistent organic pollutants. These contributions include efforts to clearly define the terminology and to develop scientifically defensible assessment models and evaluation frameworks.

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.

Bioaccumulation data from laboratory and field studies: are they comparable?

Once they are released into the environment, a number of chemicals are known to bioaccumulate in organisms, sometimes to concentrations that may threaten the individual or their predators. However, use of physical or chemical properties or results from laboratory bioaccumulation tests to predict concentrations sometimes found in wild organisms remains a challenge. How well laboratory studies and field measurements agree or disagree, and the cause of any discrepancies, is a subject of great interest and discussion from both a scientific and a regulatory perspective. A workshop sponsored by the ILSI Health and Environmental Sciences Institute, US Environmental Protection Agency, and the Society of Environmental Toxicology and Chemistry assembled scientists from academia, industry, and government to compare and contrast laboratory and field bioaccumulation data. The results of this workshop are summarized in a series of 5 articles published in this issue of Integrated Environmental Assessment and Management. The articles describe: 1) a weight-of-evidence approach that uses fugacity ratios to bring field measurements into the assessment of biomagnification potential for legacy chemicals; 2) a detailed comparison between laboratory and field data for the most commonly measured bioaccumulation endpoint, the biota-sediment accumulation factor; 3) a study that identifies and quantifies the differences between laboratory and field metrics of bioaccumulation for aquatic and terrestrial organisms; and 4) 2 reports on trophic magnification factors: the 1st addresses how trophic magnification factors are determined and interpreted and the 2nd describes how they could be used in regulatory assessments. Collectively, these articles present the workshop participants' current understanding and assessment of bioaccumulation science and make a number of recommendations on how to improve the collection and interpretation of bioaccumulation data.

Assessment of metabolic stability using the rainbow trout (Oncorhynchus mykiss) liver S9 fraction.

Standard protocols are given for assessing metabolic stability in rainbow trout using the liver S9 fraction. These protocols describe the isolation of S9 fractions from trout livers, evaluation of metabolic stability using a substrate depletion approach, and expression of the result as in vivo intrinsic clearance. Additional guidance is provided on the care and handling of test animals, design and interpretation of preliminary studies, and development of analytical methods. Although initially developed to predict metabolism impacts on chemical accumulation by fish, these procedures can be used to support a broad range of scientific and risk assessment activities including evaluation of emerging chemical contaminants and improved interpretation of toxicity testing results. These protocols have been designed for rainbow trout and can be adapted to other species as long as species-specific considerations are modified accordingly (e.g., fish maintenance and incubation mixture temperature). Rainbow trout is a cold-water species. Protocols for other species (e.g., carp, a warm-water species) can be developed based on these procedures as long as the specific considerations are taken into account.

Use of quantitative structural analysis to predict fish bioconcentration factors for pesticides.

The focus of this research was to develop a model based solely on molecular descriptors capable of predicting fish bioconcentration factors (BCF). A fish BCF database was developed from high-quality, regulatory agency reviewed studies for pesticides based on the same laboratory protocol and the same fish species, Lepomis macrochirus. A commercially available software program was used to create a quantitative structure-activity relationship (QSAR) from 93 BCF studies based on unique molecules. An additional 16 molecules were used to test the accuracy of QSAR model predictions for a variety of pesticide classes. Regression of the measured versus predicted log BCF values yielded a regression coefficient of 0.88 for the validation data set. On the basis of the results from this research, the ability to predict BCF by a QSAR regression model is improved using a fully structurally derived model based solely on structural data such as the number of atoms for a given group (e.g., -CH3) or the local topology of each atom as derived from electron counts. Such descriptors provide insightful information on a molecule's potential BCF behavior in aquatic systems.

In vitro biotransformation of surfactants in fish. Part II--Alcohol ethoxylate (C16EO8) and alcohol ethoxylate sulfate (C14EO2S) to estimate bioconcentration potential.

Recent regulatory pressures (e.g., REACh, CEPA) requiring bioaccumulation assessments and the need for reduced animal use have increased the necessity for the development of in vitro-based methods to estimate bioaccumulation. Our study explored the potential use of subcellular and cellular hepatic systems to determine the biotransformation potential of two surfactants: octaethylene glycol monohexadecyl ether (C16EO8) and diethylene glycol monotetradecyl ether sulfate (C14EO2S). The subcellular systems tested were liver homogenates and microsomes from the common carp (Cyprinus carpio) and rainbow trout (Oncorhynchus mykiss). Cellular systems consisted of primary hepatocytes from the common carp (C. carpio) and PLHC-1 cells, hepatocarcinoma cells from the desert topminnow (Poeciliopsis lucida) cell line. Each in vitro system was exposed to radiolabeled test compounds and assayed for biotransformation using liquid scintillation and thin layer chromatographic methods. First-order kinetics were used to estimate rates of biotransformation. Bioconcentration of test materials in fish were predicted using an in vitro to in vivo metabolic rate extrapolation model linked to a mass-balance model commonly used to predict bioaccumulation in fish. Both subcellular and cellular tests using microsomes, liver homogenates and hepatocytes respectively showed biotransformation of the parent surfactants. Biotransformation rates were fastest for hepatocytes, followed by microsomes and homogenates. Rates were too low from homogenate tests to extrapolate to in vivo-based biotransformation rates using the extrapolation model. Trout microsomes metabolized C16EO8 faster than carp microsomes, yet rates were approximately the same for C14EO2S. Predicted BCF values incorporating in vitro biotransformation rates from hepatocytes were similar to measured in vivo or USEPA's bioconcentration model (BCFWIN) predicted values. Predicted BCF values using microsomal-based rates from trout and carp studies were only slightly less than default BCF values which assumes a linear logKow to BCF relationship with no biotransformation. However, hepatocyte-based results showed substantially decreased BCFs compared to the default BCF values. These results indicate that BCF estimates based on in vitro metabolic rates can provide reasonable estimates of in vivo BCF values, therefore, supporting the use of in vitro approaches within a tiered approach to assess bioconcentration.

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.