Deriving a water quality guideline for protection of aquatic communities exposed to triclosan in the Canadian environment.

Triclosan is an antibacterial and antifungal chemical used in a variety of consumer products, including soaps, detergents, moisturizers, and cosmetics. Aquatic ecosystems may be exposed to triclosan following the release of remaining residues in wastewater effluents and biosolids. In December 2017, Environment and Climate Change Canada (ECCC) released a federal environmental quality guideline (FEQG) report that contained a federal water quality guideline (FWQG) for triclosan. This guideline will be used as an adjunct to the risk assessment and risk management of priority chemicals identified under the Government of Canada's Chemicals Management Plan (CMP). The FWQG value for triclosan (0.47 µg/L) was derived by ECCC using a hazardous concentration for 5% of species (HC5) from a species sensitivity distribution (SSD). We recalculated the FWQG after performing an independent analysis and evaluation of the available aquatic toxicity data for triclosan and compared our results with the ECCC FWQG value. Our independent analysis of the available aquatic toxicity data entailed conducting a literature search of all available and relevant studies, evaluating the quality and reliability of all studies considered using thorough and consistent study evaluation criteria, and thereby generating a data set of high-quality toxicity values. The selected data set includes 22 species spanning 5 taxonomic groups. An SSD was developed using this data set following the ECCC approaches. The HC5 from the SSD derived based on our validated data set is 0.76 µg/L. This HC5 value is slightly greater (i.e., less sensitive) than the value presented in ECCC's final FWQG. Integr Environ Assess Manag 2018;14:437-441. © 2018 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals, Inc. on behalf of Society of Environmental Toxicology & Chemistry (SETAC).

A refined ecological risk assessment for California red-legged frog, Delta smelt, and California tiger salamander exposed to malathion.

The California red-legged frog (CRLF), Delta smelt (DS), and California tiger salamander (CTS) are 3 species listed under the United States Federal Endangered Species Act (ESA), all of which inhabit aquatic ecosystems in California. The US Environmental Protection Agency (USEPA) has conducted deterministic screening-level risk assessments for these species potentially exposed to malathion, an organophosphorus insecticide and acaricide. Results from our screening-level analyses identified potential risk of direct effects to DS as well as indirect effects to all 3 species via reduction in prey. Accordingly, for those species and scenarios in which risk was identified at the screening level, we conducted a refined probabilistic risk assessment for CRLF, DS, and CTS. The refined ecological risk assessment (ERA) was conducted using best available data and approaches, as recommended by the 2013 National Research Council (NRC) report "Assessing Risks to Endangered and Threatened Species from Pesticides." Refined aquatic exposure models including the Pesticide Root Zone Model (PRZM), the Vegetative Filter Strip Modeling System (VFSMOD), the Variable Volume Water Model (VVWM), the Exposure Analysis Modeling System (EXAMS), and the Soil and Water Assessment Tool (SWAT) were used to generate estimated exposure concentrations (EECs) for malathion based on worst-case scenarios in California. Refined effects analyses involved developing concentration-response curves for fish and species sensitivity distributions (SSDs) for fish and aquatic invertebrates. Quantitative risk curves, field and mesocosm studies, surface-water monitoring data, and incident reports were considered in a weight-of-evidence approach. Currently, labeled uses of malathion are not expected to result in direct effects to CRLF, DS or CTS, or indirect effects due to effects on fish and invertebrate prey. Integr Environ Assess Manag 2018;14:224-239. © 2017 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals, Inc. on behalf of Society of Environmental Toxicology & Chemistry (SETAC).

Ecological risk assessment for Pacific salmon exposed to dimethoate in California.

A probabilistic risk assessment of the potential direct and indirect effects of acute dimethoate exposure to salmon populations of concern was conducted for 3 evolutionarily significant units (ESUs) of Pacific salmon in California. These ESUs were the Sacramento River winter-run chinook, the California Central Valley spring-run chinook, and the California Central Valley steelhead. Refined acute exposures were estimated using the Soil and Water Assessment Tool, a river basin-scale model developed to quantify the impact of land-management practices in large, complex watersheds. Both direct effects (i.e., inhibition of brain acetylcholinesterase activity) and indirect effects (i.e., altered availability of aquatic invertebrate prey) were assessed. Risk to salmon and their aquatic invertebrate prey items was determined to be de minimis. Therefore, dimethoate is not expected to have direct or indirect adverse effects on Pacific salmon in these 3 ESUs. Environ Toxicol Chem 2017;36:532-543. © 2016 SETAC.

Ecological risk assessment for mink and short-tailed shrew exposed to PCBs, dioxins, and furans in the Housatonic River area.

A probabilistic risk assessment was conducted to characterize risks to a representative piscivorous mammal (mink, Mustela vison) and a representative carnivorous mammal (short-tailed shrew, Blarina brevicauda) exposed to PCBs, dioxins, and furans in the Housatonic River area downstream of the General Electric (GE) facility in Pittsfield, Massachusetts. Contaminant exposure was estimated using a probabilistic total daily intake model and parameterized using life history information of each species and concentrations of PCBs, dioxins, and furans in prey collected in the Housatonic River study area. The effects assessment preferentially relied on dose-response curves but defaulted to benchmarks or other estimates of effect when there were insufficient toxicity data. The risk characterization used a weight of evidence approach. Up to 3 lines of evidence were used to estimate risks to the selected mammal species: 1) probabilistic exposure and effects modeling, 2) field surveys, and 3) species-specific feeding or field studies. The weight of evidence assessment indicated a high risk for mink and an intermediate risk for short-tailed shrew.

Risk assessment considerations with regard to the potential impacts of pesticides on endangered species.

Simple, deterministic screening-level assessments that are highly conservative by design facilitate a rapid initial screening to determine whether a pesticide active ingredient has the potential to adversely affect threatened or endangered species. If a worst-case estimate of pesticide exposure is below a very conservative effects metric (e.g., the no observed effects concentration of the most sensitive tested surrogate species) then the potential risks are considered de minimis and unlikely to jeopardize the existence of a threatened or endangered species. Thus by design, such compounded layers of conservatism are intended to minimize potential Type II errors (failure to reject a false null hypothesis of de minimus risk), but correspondingly increase Type I errors (falsely reject a null hypothesis of de minimus risk). Because of the conservatism inherent in screening-level risk assessments, higher-tier scientific information and analyses that provide additional environmental realism can be applied in cases where a potential risk has been identified. This information includes community-level effects data, environmental fate and exposure data, monitoring data, geospatial location and proximity data, species biology data, and probabilistic exposure and population models. Given that the definition of "risk" includes likelihood and magnitude of effect, higher-tier risk assessments should use probabilistic techniques that more accurately and realistically characterize risk. Moreover, where possible and appropriate, risk assessments should focus on effects at the population and community levels of organization rather than the more traditional focus on the organism level. This document provides a review of some types of higher-tier data and assessment refinements available to more accurately and realistically evaluate potential risks of pesticide use to threatened and endangered species.

A new quality assurance system for the evaluation of ecotoxicity studies submitted under the New Substances Notification Regulations in Canada.

New substances destined for import into, or manufacture in, Canada must be reported to Environment Canada and Health Canada under the New Substances Notification Regulations (Chemicals and Polymers) (NSNR). With the use of information provided by the notifier, and other complementary information available to the 2 departments, the New Substances Program conducts ecological and human health risk assessments. Over the past 10 y, more than 750 ecotoxicity studies have been submitted to the New Substances Program of Environment Canada under the NSNR. Most of these experimental studies are not publicly available but are useful in the ecological risk assessment of new substances and for the development of Quantitative Structure-Activity Relationships (QSARs). In this paper, we describe the development and validation of a computer-based scoring system and our approach in the development of scoring methods used to assess the quality and usability of ecotoxicity studies with fish, Daphnia spp., and green algae. Results of ranking exercises conducted with these methods are described and discussed, together with the potential use of these results in a regulatory context. In addition, the methods are discussed in comparison with other similar evaluation schemes described in the literature.

A comparison of model performance for six quantitative structure-activity relationship packages that predict acute toxicity to fish.

Some regulatory programs rely on quantitative structure-activity relationship (QSAR) models to predict toxic effects to biota. Many currently existing QSAR models can predict the effects of a wide range of substances to biota, particularly aquatic biota. The difficulty for regulatory programs is in choosing the appropriate QSAR model or models for application in their new and existing substances programs. We evaluated model performance of six QSAR modeling packages: Ecological Structure Activity Relationship (ECOSAR), TOPKAT, a Probabilistic Neural Network (PNN), a Computational Neural Network (CNN), the QSAR components of the Assessment Tools for the Evaluation of Risk (ASTER) system, and the Optimized Approach Based on Structural Indices Set (OASIS) system. Using a testing data set of 130 substances that had not been included in the training data sets of the QSAR models under consideration, we compared model predictions for 96-h median lethal concentrations (LC50s) to fathead minnows to the corresponding measured toxicity values available in the AQUIRE database. The testing data set was heavily weighted with neutral organics of low molecular weight and functionality. Many of the testing data set substances also had a nonpolar narcosis mode of action and/or were chlorinated. A variety of statistical measures (correlation coefficient, slope and intercept from a linear regression analysis, mean absolute and squared difference between log prediction and log measured toxicity, and the percentage of predictions within factors of 2, 5, 10, 100, and 1,000 of measured toxicity values) indicated that the PNN model had the best model performance for the full testing data set of 130 substances. The rank order of the remainder of the models depended on the statistical measure employed. TOPKAT also had excellent model performance for substances within its optimum prediction space. Only 37% of the substances in the testing data set, however, fell within this optimum prediction space.

An overview of the use of quantitative structure-activity relationships for ranking and prioritizing large chemical inventories for environmental risk assessments.

Ecological risk assessments for chemical stressors are used to establish linkages between likely exposure concentrations and adverse effects to ecological receptors. At times, it is useful to conduct screening risk assessments to assist in prioritizing or ranking chemicals on the basis of potential hazard and exposure assessment parameters. Ranking of large chemical inventories can provide evidence for focusing research and/or cleanup efforts on specific chemicals of concern. Because of financial and time constraints, data gaps exist, and the risk assessor is left with decisions on which models to use to estimate the parameter of concern. In this review, several methods are presented for using quantitative structure-activity relationships (QSARs) in conducting hazard screening or screening-level risk assessments. The ranking methods described include those related to current regulatory issues associated with chemical inventories from Canada, Europe, and the United States and an example of a screening-level risk assessment conducted on chemicals associated with a watershed in the midwest region of the United States.