Numerical Modeling of the Concentration of Microplastics in Lakes and Rivers in Kazakhstan
[EN] This research presents a detailed numerical modeling study focused on estimating the concentration of microplastics (MPs) in freshwater ecosystems. This research covers three lakes (Kopa, Zerendinskoye, and Borovoe) and the Yesil River, applying di¿erential equations to model the spatial distri...
| Autores: | , , , , |
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| Tipo de documento: | artigo |
| Data de publicação: | 2025 |
| País: | España |
| Recursos: | Universitat Politècnica de València (UPV) |
| Repositório: | RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia |
| Idioma: | inglês |
| OAI Identifier: | oai:riunet.upv.es:10251/230375 |
| Acesso em linha: | https://riunet.upv.es/handle/10251/230375 |
| Access Level: | Acceso aberto |
| Palavra-chave: | Microplastics Numerical modeling Freshwater ecosystems Kazakhstan 03.- Garantizar una vida saludable y promover el bienestar para todos y todas en todas las edades |
| Resumo: | [EN] This research presents a detailed numerical modeling study focused on estimating the concentration of microplastics (MPs) in freshwater ecosystems. This research covers three lakes (Kopa, Zerendinskoye, and Borovoe) and the Yesil River, applying di¿erential equations to model the spatial distribution and seasonal variations in MP concentrations. The methodology integrates ¿eld survey data collected during three di¿erent seasons (spring, summer, and autumn) from both sediment and water samples. The MP concentrations were found to follow an exponential decay pattern from the shore toward the center of the lakes, with higher concentrations near the shoreline. The modeling framework is calibrated using regression analysis, which provides the best-¿t parameters for the distance¿concentration curves. This study employs sensitivity analysis to justify the decay coe¿cient, resulting in a selected value of k = 0.09. Model performance is assessed using statistical metrics such as the root mean square error (RMSE) and the coe¿cient of determination (R2 ), ensuring accuracy in predicting MP concentrations across di¿erent environmental compartments. This work represents a novel contribution to the ¿eld by applying numerical modeling techniques to an understudied geographical area. The ¿ndings highlight signi¿cant seasonal and spatial variations in MP concentrations, emphasizing the need for comprehensive monitoring. This study¿s results contribute valuable insights into the environmental behavior of MPs in freshwater systems and support e¿orts to develop e¿ective management strategies to mitigate pollution. |
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