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Progress and future directions bridging microplastics transport from pore to continuum scale: A comprehensive review for experimental and modeling approaches
Summary
This review bridges current understanding of microplastic transport modeling with monitoring data, identifying gaps between field observations and computational predictions of microplastic fate in aquatic systems. The authors propose future directions for integrating real-world data into transport frameworks.
The anomalous (i.e., non-Fickian) transport characteristics (e.g., early arrival/long tailing and other non-Gaussian plume properties) make it challenging to apply classical transport theories to the transport and retention of microplastics in soil due to their heterogeneity. This overview attempts 1) to delineate the previous studies on the transport of colloids and MPs, which used the recently developed analytical devices (e.g., microfluidics and micro-CT) and process-based (e.g., lattice Boltzmann method (LBM) and pore network modeling (PNM)) or data-driven models (e.g., machine learning (ML) techniques) and 2) to provide future directions for bridging the pore- and continuum-scale properties. Although the LBM and PNM offer significant advantages in depicting particle transport at the pore scale, their employment at larger scales is hindered by computational demands. Nonetheless, applying these methods to generate datasets for ML techniques is anticipated to provide a robust tool for an accurate and rapid continuum-scale microplastics transport model.
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