Assessment of pesticide sorption to common microplastics in aqueous media via non-depletive solid phase microextraction.

Authors

Héctor Martínez-Pérez-Cejuela, May Myat Moe, Emanuela Gionfriddo

Published in

Analytica chimica acta. Volume 1422. Pages 346095. Nov 08, 2026. Epub Aug 11, 2026.

Abstract

Microplastics (MPs) pose a significant global pollution concern due to their widespread distribution, persistence, and ability to absorb organic pollutants (OPs) and transport contaminants in aquatic environments. The interactions between OPs and MPs are influenced by factors such as organic matter, pH, and ionic strength. Traditional methods used to study these interactions often perturb partitioning equilibria, potentially affecting the accuracy of the findings.
This study proposes an innovative, automated, solvent-free approach using negligible depletion solid-phase microextraction (nd-SPME) coupled with gas chromatography-mass spectrometry (GC-MS) to investigate sorption equilibria of pesticides onto polyethylene (PE) and polyvinyl chloride (PVC) MPs by overcoming common limitations of traditional methodologies. Method development and optimization were performed to avoid steps such as filtration, centrifugation, or dilution of the sample, commonly reported in the literature, thereby positioning this approach as a non-depletive method for studying contaminant-microplastic interactions. Pesticide sorption onto MPs was explored in real-time through automated sampling. The influence of key parameters, including organic matter content, sample pH, and ionic strength, was examined. Sorption kinetics of pesticides onto MPs followed a pseudo-second-order kinetic model, while the adsorption isotherms were best described by both the Henry and the Freundlich models.
This work introduces a fundamentally non-perturbative strategy for investigating contaminant-microplastic interactions, addressing a critical gap in current methodologies that rely on sample manipulation and may affect native partitioning equilibria.

PMID:
42763155
Bibliographic data and abstract were imported from PubMed on 20 Sep 2026.

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