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Exploring Uptake of Toxic Environmental Pollutants onto Commercial Microplastics: An Insight of Thermodynamic Predictive Scenarios, Kinetics and Influencing Factors

Microplastics 2026

Summary

Researchers tested how naphthalene, pentachlorophenol, sulfamethoxazole, and ibuprofen adsorb onto commercial microplastics and validated the Hansen solubility parameter method — previously applied only to antibiotics — as a thermodynamic predictor of pollutant affinity across multiple chemical classes including PAHs, pesticides, and pharmaceuticals.

This study investigates the sorption process of selected pollutants, namely naphthalene (NAP), pentachlorophenol (PCP), sulfamethoxazole (SMX), and ibuprofen (IBU), onto different real microplastics (MPs) under controlled laboratory conditions. Sorption tests reveal variable affinities depending on the chemical and physical interactions between polymers and pollutants. NAP showed the greatest uptake on the majority of tested MPs, followed by PCP and SMX, while IBU exhibited negligible sorption. Kinetic tests indicate a general rapid initial uptake, followed by lower sorption rates leading to equilibrium within days. Theoretical thermodynamic affinity estimations, based on the Hansen solubility parameter (HSP) method, previously tested only on antibiotics, are applied for the first time to commercial MPs and several pollutant categories such as PAHs, pesticides and other pharmaceuticals. Predictions have been validated with experimental results and generally show very good agreement with the affinity ranking derived by experimental data. However, some limitations occur due to the heterogeneity of the real MPs and different environmental conditions. Factors affecting, to different extents, MPs’ uptake include hydrophobicity and electrostatic forces, as well as pH and particle size. This work advances understanding of MPs’ role as vectors of pollutants in aquatic environments and validates the use of an innovative combined experimental–theoretical approach useful as a tool to predict associated risk.

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