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Transport and retention mechanism of microplastics in saturated porous media: Dominance of layer sequence and modulation by solution chemistry
Summary
Researchers found that the layered sequence of sand structures in saturated porous media dominates microplastic transport and retention patterns, with coarse-to-fine layering trapping more particles than fine-to-coarse sequences, and solution chemistry further modulating these physical effects.
Microplastics (MPs) pose significant environmental risks due to their persistence and potential to contaminate soil and groundwater. This study investigated the transport and retention of MPs in saturated porous media, focusing on how the sequence of layered sand structures (Coarse-Fine: C-F; Coarse-Fine-Coarse: C-F-C; Fine-Coarse: F-C) controlled MP fate, and how this physical framework was modulated by solution chemistry. Controlled column experiments revealed that the physical structure, specifically the layer sequence, was the primary driver of MP retention. This "layer sequence effect" predominantly governed MP mobility, with transport efficiency decreasing in the order: C-F > C-F-C > F-C. When the fine layer was positioned farthest from the inlet, its higher specific surface area and lower permeability more readily facilitated MP deposition. The influence of solution chemistry (ionic strength: 1-30 mM; cation valence: Navs. Mg; pH: 5-9) was systematically examined within the C-F structure. Increased ionic strength and the presence of Mg enhanced MP retention, while higher pH (e.g., 9) promoted MP transport. Nevertheless, the significantly higher retention in the fine sand layer remained the dominant pattern across all chemical conditions. These findings underscore that the geological framework sets the stage for MP transport, while solution chemistry modulates the attachment efficiency within that framework. This work establishes a mechanistic baseline under controlled conditions and demonstrates the necessity of incorporating stratigraphic architecture, especially layer sequence, into predictive models and risk assessments for MP contamination.
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