Grouping strategies for assessing and managing persistent and mobile substances.

Background: Persistent, mobile and toxic (PMT), or very persistent and very mobile (vPvM) substances are a wide class of chemicals that are recalcitrant to degradation, easily transported, and potentially harmful to humans and the environment. Due to their persistence and mobility, these substances are often widespread in the environment once emitted, particularly in water resources, causing increased challenges during water treatment processes. Some PMT/vPvM substances such as GenX and perfluorobutane sulfonic acid have been identified as substances of very high concern (SVHCs) under the European Registration, Evaluation, Authorisation and Restriction of Chemicals (REACH) regulation. With hundreds to thousands of potential PMT/vPvM substances yet to be assessed and managed, effective and efficient approaches that avoid a case-by-case assessment and prevent regrettable substitution are necessary to achieve the European Union's zero-pollution goal for a non-toxic environment by 2050. Main: Substance grouping has helped global regulation of some highly hazardous chemicals, e.g., through the Montreal Protocol and the Stockholm Convention. This article explores the potential of grouping strategies for identifying, assessing and managing PMT/vPvM substances. The aim is to facilitate early identification of lesser-known or new substances that potentially meet PMT/vPvM criteria, prompt additional testing, avoid regrettable use or substitution, and integrate into existing risk management strategies. Thus, this article provides an overview of PMT/vPvM substances and reviews the definition of PMT/vPvM criteria and various lists of PMT/vPvM substances available. It covers the current definition of groups, compares the use of substance grouping for hazard assessment and regulation, and discusses the advantages and disadvantages of grouping substances for regulation. The article then explores strategies for grouping PMT/vPvM substances, including read-across, structural similarity and commonly retained moieties, as well as the potential application of these strategies using cheminformatics to predict P, M and T properties for selected examples. Conclusions: Effective substance grouping can accelerate the assessment and management of PMT/vPvM substances, especially for substances that lack information. Advances to read-across methods and cheminformatics tools are needed to support efficient and effective chemical management, preventing broad entry of hazardous chemicals into the global market and favouring safer and more sustainable alternatives.

Retrieval, Selection, and Evaluation of Chemical Property Data for Assessments of Chemical Emissions, Fate, Hazard, Exposure, and Risks.

Reliable chemical property data are the key to defensible and unbiased assessments of chemical emissions, fate, hazard, exposure, and risks. However, the retrieval, evaluation, and use of reliable chemical property data can often be a formidable challenge for chemical assessors and model users. This comprehensive review provides practical guidance for use of chemical property data in chemical assessments. We assemble available sources for obtaining experimentally derived and in silico predicted property data; we also elaborate strategies for evaluating and curating the obtained property data. We demonstrate that both experimentally derived and in silico predicted property data can be subject to considerable uncertainty and variability. Chemical assessors are encouraged to use property data derived through the harmonization of multiple carefully selected experimental data if a sufficient number of reliable laboratory measurements is available or through the consensus consolidation of predictions from multiple in silico tools if the data pool from laboratory measurements is not adequate.

Identifying organic chemicals not subject to bioaccumulation in air-breathing organisms using predicted partitioning and biotransformation properties.

Because the respiration processes contributing to the elimination of organic chemicals deviate between air- and water-breathing organisms, existing and widely used procedures for identifying chemicals not subject to bioaccumulation in aquatic organisms based on the octanol-water partition ratio KOW need to be complemented with similar procedures for organisms respiring air. Here, we propose such a procedure that relies on the comparison of a compound's predicted KOW , octanol-air partition ratio KOA , and biotransformation half-life HLB with three threshold values, below which elimination is judged to be sufficiently rapid to prevent bioaccumulation. The method allows for the consideration of the effect of dissociation on the efficiency of urinary and respiratory elimination. Explicit application of different types of the prediction error, such as the 95% prediction interval or the standard error, allows for variable tolerance for false-negative decisions, that is, the potential to judge a chemical as not bioaccumulative even though it is. A test with a set of more than 1000 diverse organic chemicals confirms the applicability of the prediction methods for a wide range of compounds and the procedure's ability to categorize approximately four-fifth of compounds as being of no bioaccumulation concern, suggesting its usefulness to screen large numbers of commercial chemicals to identify those worthy of further scrutiny. The test also demonstrates that a screening based solely on KOW and KOA would be far less effective because the fraction of chemicals that can be judged as sufficiently volatile and/or sufficiently water soluble for rapid respiratory and urinary elimination based on the partitioning properties predicted for their neutral form is relatively small. Future improvements of the proposed procedure depend largely on the development of prediction methods for the biotransformation kinetics in air-breathing organisms and for the potential for renal reabsorption. Integr Environ Assess Manag 2022;18:1297-1312. © 2021 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC).

Reliable Prediction of the Octanol-Air Partition Ratio.

The octanol-air equilibrium partition ratio (KOA ) is frequently used to describe the volatility of organic chemicals, whereby n-octanol serves as a substitute for a variety of organic phases ranging from organic matter in atmospheric particles and soils, to biological tissues such as plant foliage, fat, blood, and milk, and to polymeric sorbents. Because measured KOA values exist for just over 500 compounds, most of which are nonpolar halogenated aromatics, there is a need for tools that can reliably predict this parameter for a wide range of organic molecules, ideally at different temperatures. The ability of five techniques, specifically polyparameter linear free energy relationships (ppLFERs) with either experimental or predicted solute descriptors, EPISuite's KOAWIN, COSMOtherm, and OPERA, to predict the KOA of organic substances, either at 25 °C or at any temperature, was assessed by comparison with all KOA values measured to date. In addition, three different ppLFER equations for KOA were evaluated, and a new modified equation is proposed. A technique's performance was quantified with the mean absolute error (MAE), the root mean square error (RMSE), and the estimated uncertainty of future predicted values, that is, the prediction interval. We also considered each model's applicability domain and accessibility. With an RMSE of 0.37 and a MAE of 0.23 for predictions of log KOA at 25 °C and RMSE of 0.32 and MAE of 0.21 for predictions made at any temperature, the ppLFER equation using experimental solute descriptors predicted the KOA the best. Even if solute descriptors must be predicted in the absence of experimental values, ppLFERs are the preferred method, also because they are easy to use and freely available. Environ Toxicol Chem 2021;40:3166-3180. © 2021 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Model-based exploration of the variability in lake trout (Salvelinus namaycush) bioaccumulation factors: The influence of physiology and trophic relationships.

Because dietary consumption of fish is often a major vector of human exposure to persistent organic pollutants (POPs), much effort is directed toward a quantitative understanding of fish bioaccumulation using mechanistic models. However, many such models fail to explicitly consider how uptake and loss rate constants relate to fish physiology. We calculated the bioaccumulation factors (BAFs) of hypothetical POPs, with octanol-water partition coefficients ranging from 104.5 to 108.5 , in lake trout (Salvelinus namaycush) with a food-web bioaccumulation model that uses bioenergetics to ensure that physiological parameters applied to a species are internally consistent. We modeled fish in 6 Canadian lakes (Great Slave Lake, Lake Ontario, Source Lake, Happy Isle Lake, Lake Opeongo, and Lake Memphremagog) to identify the factors that cause the BAFs of differently sized lake trout to vary between and within lakes. When comparing differently sized lake trout within a lake, larger fish tend to have the highest BAF because they allocate less energy toward growth than smaller fish and have higher activity levels. When comparing fish from different lakes, the model finds that diet composition and prey energy density become important in determining the BAF, in addition to activity and the amount of total energy allocated to growth. Environ Toxicol Chem 2019;38:831-840. © 2019 SETAC.