School of Civil and Environmental Engineering, Water Research Centre, University of New South Wales, Sydney, NSW 2052, Australia.
School of Civil Engineering and Environmental Science, University of Oklahoma, Norman, OK 73019, USA.
Sci Total Environ. 2022 Nov 20;848:157663. doi: 10.1016/j.scitotenv.2022.157663. Epub 2022 Jul 27.
Per- and polyfluoroalkyl substances (PFAS) are widely-detected environmental contaminants known to concentrate at surfaces and interfaces. Many of the most commonly-detected PFAS function as ionic surfactants under environmental conditions. The interfacial behaviors of ionic surfactants, including PFAS, are strongly dependent on salt concentration and composition, with interfacial affinity potentially varying by orders of magnitude for the same compound under different conditions. The work described here presents a tool for predicting the salt-dependent adsorption of PFAS compounds based entirely on chemical structure, something of great value for predicting the real-world environmental behavior of many of the large numbers of PFAS compounds for which experimental data are not available. The approach combines two different previously-developed models, one a mass-action model designed to predict the effects of salts on interfacial adsorption of ionic PFAS (the UNSW-OU salt model), and the second a group-contribution model designed to predict interfacial adsorption of PFAS in the absence of salt based on chemical structure. The challenge of combining the two models comes from the fact that both are based on different isotherms. The salt model can produce sigmoidal isotherms under salt-limited conditions (an isotherm shape that is supported by experimental evidence), while the group-contribution model can generate Langmuir parameters from calculations based on chemical structure. Equations were derived to determine salt model isotherm parameters from Langmuir parameters (either from the group-contribution model or experimental sources) by matching surface tension curves in the vicinity of the concentration of highest second derivative. Refined group-contribution model parameters were determined based on data from an additional 40 surface tension curves to allow improved structure-based predictions for important classes of PFAS that were not sufficiently well-represented in the original model. The resulting equations provide a tool allowing quantitative predictions of PFAS behavior under realistic environmental conditions for compounds for which little or no experimental data are available.
全氟和多氟烷基物质（PFAS）是广泛存在的环境污染物，已知它们在表面和界面处浓缩。最常见的 PFAS 中的许多物质在环境条件下作为离子表面活性剂发挥作用。离子表面活性剂的界面行为，包括 PFAS，强烈依赖于盐浓度和组成，在不同条件下，同一化合物的界面亲和力可能相差几个数量级。这里描述的工作提供了一种基于化学结构预测 PFAS 化合物盐依赖性吸附的工具，这对于预测大量缺乏实验数据的 PFAS 化合物的实际环境行为非常有价值。该方法结合了两种不同的先前开发的模型，一种是设计用于预测盐对离子 PFAS 界面吸附影响的质量作用模型（UNSW-OU 盐模型），另一种是设计用于根据化学结构预测无盐条件下 PFAS 界面吸附的基团贡献模型。两种模型相结合的挑战来自于这样一个事实，即两者都是基于不同的等温线。盐模型可以在盐有限条件下产生 S 型等温线（实验证据支持的等温线形状），而基团贡献模型可以根据基于化学结构的计算生成 Langmuir 参数。通过在最接近二阶导数浓度的附近匹配表面张力曲线，推导出了从 Langmuir 参数（来自基团贡献模型或实验来源）确定盐模型等温线参数的方程。基于另外 40 个表面张力曲线的数据确定了改进的基团贡献模型参数，以允许对在原始模型中代表性不足的重要 PFAS 类进行基于结构的改进预测。所得到的方程提供了一种工具，允许对缺乏或几乎没有实验数据的化合物在实际环境条件下进行 PFAS 行为的定量预测。
