Interactions between perfluorinated alkyl substances (PFAS) and microplastics (MPs): Findings from an extensive investigation

• Comprehensive insight into PFAS-microplastic interactions • Workflow optimization shows significant adsorption behavior of PFAS onto glass vials and nylon filter • Among 18 polymers, polyamides exhibit the highest PFAS uptake up to 100 % • PFAS uptake onto Polymers with functional groups such as carbonyl and carbamate functions are highly pH dependent • Experimental data is validated via computational modeling Per- and polyfluoroalkyl substances (PFAS) pose significant environmental and health concerns due to their widespread use and persistence in ecosystems and living beings. The same applies to microplastics (MPs), making PFAS and MPs two of the most widespread contaminants worldwide. The presented study aims to investigate the complex interactions between those two contaminants in order to deepen our understanding of their behavior under environmental conditions. Utilizing advanced analytical techniques, such as liquid chromatography-tandem mass spectrometry (LC-MS/MS), we conducted a series of experiments, including 18 polymer types and eight PFAS, to explore the adsorption kinetics, influence of pH, and impact of polymer type and PFAS properties on their interaction. Within a pre-experimental design, we evaluated the suitability of used HPLC vials and syringe filters for undesired loss of PFAS. Main experiments at a concentration of 100 µg L⁻¹ showed that polyamide (PA) polymers adsorbed up to 100% of PFAS (equivalent to 8 mg per gram polymer in the context of this work). Moreover, the polarity of PFAS compounds significantly influenced their adsorption behavior. pH variation studies showed that functional groups in polymers, particularly amide functionalities, play a crucial role in PFAS uptake, emphasizing the importance of chemical composition and environmental conditions in evaluating PFAS –MP interactions. In order to verify the findings of the experimental study, computational modeling using a global optimization (MACE-OFF23) neural network potential and GFN2-xTB re-optimization was conducted for representative molecules. Yielded interaction energies of -126 kJ mol⁻¹ for polyamide-perfluorobutanoic acid (PFBA) and -117 kJ mol⁻¹ for polyamide-perfluorooctane sulfonic acid (PFOS), compared to weaker interactions of -32 and -39 kJ mol⁻¹ for polyethylene with PFBA and PFOA, respectively, underscoring the experimental results. These findings advance our understanding of the interaction behavior between two of the most prominent environmental contaminants.