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Modelling the Fate of Microplastics in river bed sediments.

Zenodo (CERN European Organization for Nuclear Research) 2024
Nidhi Chaudhary, Nidhi Chaudhary, Sourabh Dixit, Sourabh Dixit, Abhyanand Singh Maurya

Summary

Researchers modeled microplastic transport, deposition, and burial in river bed sediments under varying hydrological conditions. River bed sediments were found to act as long-term reservoirs for microplastics, with periodic high-flow events temporarily resuspending and redistributing particles.

Polymers
Study Type Environmental

The proliferation of microplastics (MPs) in rivers poses a significant global challenge and a threat to the environment, livelihoods, and human health. However, there is a lack of knowledge regarding the dispersal patterns and transport of MPs in river sediments. This study examines the distribution patterns of microplastic fibers and fragments, focusing on their dependence on column properties such as seepage velocity, sediment grain size, and the size of the microplastic fibers and fragments. Batch experiments were conducted using steel columns measuring 50 cm in length and 5 cm in diameter, with a flow rate of 15 ml/minute. After the experiments, sediment samples from the columns were collected at different depths and density separation was conducted to extract microplastics from the samples. Subsequently, the vertical profile of MP concentration was found using fluorescence microscopy. The most prominent MP type was Polyethylene (PE). Most of the MP particles were retained up to the depth of 30 cm, some MP fibers were also found in the outlet water which suggests that in actual field conditions, they will be deposited at a depth greater than 50 cm of the river bed. The concentration of MPs was dependent on the size of MPs particles, the grain size of sediments, and the inlet flow rate as indicated by the regression model with (R2 ¿0.90). The empirically derived equations from the regression models suggest that MP particles are prone to deposition at depths greater than 50 cm in the riverbed. Our study concludes that developed regression model is capable of predicting the deposition of MP particles in riverbeds in low flow rate conditions in the rivers. Also see: https://micro2024.sciencesconf.org/559676/document

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