Investigating the OECD database of per- and polyfluoroalkyl substances – chemical variation and applicability of current fate models

适用范围 环境化学 有机化学品 环境风险评价 化学数据库 化合物 化学 生化工程 数据库 环境科学 计算机科学 数量结构-活动关系 风险评估 有机化学 机器学习 工程类 计算机安全 毒性
作者
Ioana Chelcea,Lutz Ahrens,Stefan Örn,Dániel Mucs,Patrik L. Andersson
出处
期刊:Environmental Chemistry [CSIRO Publishing]
卷期号:17 (7): 498-498 被引量:14
标识
DOI:10.1071/en19296
摘要

Environmental contextA diverse range of materials contain organofluorine chemicals, some of which are hazardous and widely distributed in the environment. We investigated an inventory of over 4700 organofluorine compounds, characterised their chemical diversity and selected representatives for future testing to fill knowledge gaps about their environmental fate and effects. Fate and property models were examined and concluded to be valid for only a fraction of studied organofluorines. AbstractMany per- and polyfluoroalkyl substances (PFASs) have been identified in the environment, and some have been shown to be extremely persistent and even toxic, thus raising concerns about their effects on human health and the environment. Despite this, little is known about most PFASs. In this study, the comprehensive database of over 4700 PFAS entries recently compiled by the OECD was curated and the chemical variation was analysed in detail. The analysis revealed 3363 individual PFASs with a huge variation in chemical functionalities and a wide range of mixtures and polymers. A hierarchical clustering methodology was employed on the curated database, which resulted in 12 groups, where only half were populated by well-studied compounds thus indicating the large knowledge gaps. We selected both a theoretical and a procurable training set that covered a substantial part of the chemical domain based on these clusters. Several computational models to predict physicochemical and environmental fate related properties were assessed, which indicated their lack of applicability for PFASs and the urgent need for experimental data for training and validating these models. Our findings indicate reasonable predictions of the octanol-water partition coefficient for a small chemical domain of PFASs but large data gaps and uncertainties for water solubility, bioconcentration factor, and acid dissociation factor predictions. Improved computational tools are necessary for assessing risks of PFASs and for including suggested training set compounds in future testing of both physicochemical and effect-related data. This should provide a solid basis for better chemical understanding and future model development purposes.
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