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Article ? AI-assigned paper type based on the abstract. Classification may not be perfect — flag errors using the feedback button. Tier 2 ? Original research — experimental, observational, or case-control study. Direct primary evidence. Marine & Wildlife Sign in to save

Comment on egusphere-2025-529

2025 Score: 38 ? 0–100 AI score estimating relevance to the microplastics field. Papers below 30 are filtered from public browse.
Kaimathuruthy, Betty John, Kaimathuruthy, Betty John, Kaimathuruthy, Betty John, Kaimathuruthy, Betty John, Kaimathuruthy, Betty John, Jalón-Rojas, Isabel, Jalón-Rojas, Isabel, Jalón-Rojas, Isabel, Sous, Damien Sous, Damien Sous, Damien Sous, Damien Sous, Damien

Summary

This commentary examines the challenges and methodological requirements for process-based numerical modelling of microplastic transport and fate in estuaries, emphasizing the need for accurate hydrodynamic representation and robust parameterization of plastic particle properties. The piece argues that models must integrate observational data to capture dispersion trends that field measurements alone cannot resolve.

<strong class="journal-contentHeaderColor">Abstract.</strong> The study of microplastic transport and fate in estuaries poses significant challenges due to the complex, dynamic nature of these ecosystems and the diverse characteristics of microplastics. Process-based numerical models have become indispensable for studying microplastics, complementing observational data by offering insights into transport processes and dispersion trends that are difficult to capture through in-situ measurements alone. Effective model implementations require an accurate representation of the hydrodynamic conditions, relevant transport processes, particle properties, and their dynamic behaviour and interactions with other environmental components. In this paper, we provide a comprehensive review of the different process-based modelling approaches used to study the transport of microplastics in estuaries, including Eulerian Idealized 2DV models, Eulerian Realistic Models, Lagrangian Particle Tracking Models, and Population Balance Equation Models. We detail each approach and analyze previous applications, examining key aspects such as parameterizations, input data, model setups, and validation methods. We assess the strengths and limitations of each approach and provide recommendations, good practices, and future directions to address challenges, improve the accuracy of predictions, and advance modelling strategies, ultimately benefiting the research field.

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