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Modeling microplastic transport through porous media: challenges arising from dynamic transport behavior
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This perspective article reviews microplastic transport through porous media such as soils and aquifers, identifying the limitations of existing hydrogeological models and proposing research directions for more effectively modelling the dynamic, particle-specific transport behaviour of microplastics in porous environments.
Modelling microplastic transport through porous media, such as soils and aquifers, is an emerging research topic, where existing hydrogeological models for (reactive) solute and colloid transport have shown limited effectiveness thus far. This perspective article draws upon recent literature to provide a brief overview of key microplastic transport processes, with emphases on less well-understood processes, to propose potential research directions for efficiently modeling microplastic transport through the porous environment. Microplastics are particulate matter with distinct physicochemical properties. Biogeochemical processes and physical interactions with the surrounding environment cause microplastic properties such as material density, geometry, chemical composition, and DLVO interaction parameters to change dynamically, through complex webs of interactions and feedbacks that dynamically affect transport behavior. Furthermore, microplastic material densities, which cluster around that of water, distinguish microplastics from other colloids, with impactful consequences that are often underappreciated. For example, (near-)neutral material densities cause microplastic transport behavior to be highly sensitive to spatio-temporally varying environmental conditions. The dynamic nature of microplastic properties implies that at environmentally relevant large spatio-temporal scales, the complex transport behavior may be effectively intractable to direct physical modeling. Therefore, efficient modeling may require integrating reduced-complexity physics-constrained models, with stochastic or statistical analyses, supported by extensive environmental data. This is a sub-project (focusing on microplastics in the environment) of the Digital Waters Flagship funded by the Research Council of Finland, where we aim to create a digital ecosystem for machine learning aided hydrological modelling of various hydrosphere processes across all environmental compartments, focusing particularly on the critical zone.
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Modeling microplastic transport through porous media: Challenges arising from dynamic transport behavior
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This perspective article examines the challenges of modeling how microplastics move through soil and groundwater systems, noting that existing transport models designed for other particles fall short. Microplastic properties change dynamically as they interact with their environment, altering their density, surface chemistry, and movement behavior in ways that are difficult to predict. The study argues that new modeling approaches, potentially using data-driven methods, are needed to accurately predict microplastic transport at meaningful environmental scales.
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