Microplastic transport in meandering open-channel flows: Coupled effects of sinuosity and particle density

초록

This study investigates the interplay between channel sinuosity and particle density in microplastic (MP) transport in meandering channels using a three-dimensional flow and Lagrangian particle tracking simulation framework. A series of meandering channels with systematically varying sinuosity are simulated to isolate its impact on flow and transport characterisitics. Increasing sinuosity strengthens secondary flow and velocity gradients, enhancing transverse mixing and longitudinal dispersion. Particle density exerts a pivotal control on transport behavior through vertical distribution. Buoyant PE and near-neutrally buoyant PS particles travel along the water surface or throughout the water column and respond sensitively to sinuosity-induced flow variability. In contrast, settling-dominated PET particles are transported near the channel bed, where lower and less variable velocities reduce the influence of sinuosity and produce heavy-tailed breakthrough curves (BTCs). The combined effects of sinuosity and particle density reinforce non-Fickian transport characterized by pronounced power-law tailing in BTCs. Higher sinuosity expands near-bed immobile zones that delay PET transport and exacerbate power-law tailing. Such transport dynamics are captured by Lagrangian velocity correlations. With increasing sinuosity and particle density, correlation strength increases while temporal decay slows, indicating that velocity memory underlies anomalous transport behavior. The findings of this study highlight that MP transport mechanisms are governed by the joint roles of particle density and curvature-driven flow structures. Particle density regulates the vertical pathways through which particles sample the flow field, whereas sinuosity controls mixing and dispersion along those pathways. This provides a mechanistic basis for predicting MP transport and retention in riverine environments. © 2026 Elsevier B.V. All rights are reserved, including those for text and data mining, AI training, and similar technologies.

키워드