Pharmaceuticals, Pesticides, and Poly- and Perfluoroalkyl Substances at Surface Water Occurrence Levels-Impact of Compound Specific Physicochemical Properties on Nanofiltration and Reverse Osmosis Processes

地表水中药物、农药、多氟烷基和全氟烷基物质的含量水平——化合物特定理化性质对纳滤和反渗透工艺的影响

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Abstract

Pharmaceutically active compounds (PhACs), pesticides, and poly- and perfluoroalkyl substances (PFAS) are increasingly detected in surface waters at trace concentrations, raising concerns for both aquatic systems and, consequently, human health. Conventional solutions are insufficient to achieve complete removal at trace compound concentrations, highlighting the need for advanced separation technologies. This study aims to comprehensively analyze rejection and removal mechanisms of selected PhACs, pesticides, and PFAS present in water solutions at reported environmentally relevant concentrations (300 ng L(-1)), using two nanofiltration (NF) and one reverse osmosis (RO) polyamide membrane. PhACs, pesticides, and PFAS were selected to cover a broad range of physicochemical properties, specifically molecular mass (MM), dissociation constant (pKa), and octanol-water partition coefficient (logK(o/w)). Rejection values ranged from 42.1% (acetaminophen) to apparent 100% (for multiple compounds), depending on water pH, solute properties, and membrane characteristics. Size exclusion and electrostatic interactions were identified as the primary removal mechanisms, with hydrophobic interactions having a lower impact, particularly for carbamazepine, bezafibrate, and perfluorooctane sulfonic acid (PFOS). Addition of sodium chloride (3 g L(-1)) decreased rejection of most negatively charged compounds due to suppression of membrane surface charge, although clarithromycin and ofloxacin exhibited improved rejection. Presented results provide fundamental insight into compound-specific membrane rejection and highlight the importance of membrane-solute interactions under environmentally realistic conditions. The results support further optimization of NF and RO for targeted compound rejection and provide a baseline for data-driven membrane process modeling.

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