A Framework for Developing Tools to Predict PFAS Physical–Chemical Properties and Mass-Partitioning Parameters

Abstract

A framework for developing predictive models for PFAS physical–chemical properties and mass-partitioning parameters is presented. The framework is based on the objective of developing tools that are of sufficient simplicity to be used rapidly and routinely for initial site investigations and risk assessments. This is accomplished by the use of bespoke PFAS-specific QSPR models. The development of these models entails aggregation and curation of measured data sets for a target property or parameter, supplemented by estimates produced with quantum–chemical ab initio predictions. The application of bespoke QSPR models for PFAS is illustrated with several examples, including partitioning to different interfaces, uptake by several fish species, and partitioning to four different biological materials. Reasonable correlations to molar volume were observed for all systems. One notable observation is that the slopes of all of the regression functions are similar. This suggests that the partitioning processes in all of these systems are to some degree mediated by the same mechanism, namely hydrophobic interaction. Special factors and elements requiring consideration in the development of predictive models are discussed, including differences in bulk-phase versus interface partitioning processes.