Linking Environmental Properties of Surfactants to Molecular Interactions

The aim of this thesis is to identify novel parameters for nonionic and anionic surfactants and use these as a tool to predict their environmental fate and behavior. The surfactant groups discussed in this thesis include one nonionic surfactant group (alcohol ethoxylates) and six anionic surfactant groups whereof four are aliphatic surfactant groups (alkyl benzene sulfonates, alkyl sulfonates, alkyl sulfates and alkyl carboxylates), and two are perfluorinated surfactant groups (perfluoroalkyl carboxylates and perfluoroalkyl sulfonates). Two approaches were applied to investigate the properties of the surfactant molecule 1) Solid Phase Micro-extraction (SPME), in order to obtain polyacrylate-water partition coefficients for surfactants, and 2) High Performance Liquid Chromatography (HPLC), where novel interaction parameters are derived by measuring the retention on several HPLC columns having different properties. Finally, the new interaction parameters have been used to develop new predictive QSAR models for anionic and nonionic surfactants. Most studies on surfactant behavior in the environment focus on a specific surfactant group and often study a single (partition) parameter. Focusing on the different individual physico-chemical properties of surfactants not only results in a better understanding of the mechanisms that drive surfactant behavior, but quantifying these properties allows for a more accurate prediction of their partitioning or distribution from water to other phases in the environment. In this thesis, it is shown that the kC18, kHILIC and kAX interaction parameters allow for the distinction between different surfactant head groups or between hydrocarbon or perfluorocarbon moieties. The presented predictive models further demonstrate the usefulness of these interaction parameters in predicting the environmental properties of nonionic and anionic surfactants using a QSAR approach.