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Parameterization of microplastic-sediment aggregation for improved fate modelling
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Researchers developed parameterization for microplastic-sediment aggregation (MSA) processes to improve numerical fate models predicting microplastic transport and accumulation in rivers and estuaries. The work addressed how suspended sediment flocculates with microplastics to form composite aggregates, altering settling velocities and identifying key deposition zones.
The presence of microplastics in rivers and estuaries poses several environmental challenges. To effectively address these challenges, it is important to identify and localize microplastic sinks within the aquatic environment. This can be achieved through modeling the fate of microplastics with numerical transport models. Microplastic-sediment aggregation (MSA) is a crucial process that influences the fate of microplastics. When suspended sediment aggregates with microplastics, they form flocks which are larger and denser compared to individual microplastics. This leads to an increased settlement of microplastics in flock form. While microplastic transport models can provide a preliminary understanding of the fate of these anthropogenic particles, none of these models fully incorporates the MSA process. Therefore, this project aims to parameterize MSA and to improve transport models, to ultimately enhance our understanding of MSA's impact on the fate of microplastics. Firstly, lab experiments will be conducted to analyze the effect of different microplastic properties on the aggregation with fine-grained sediment and subsequent settlement of the microplastic-sediment flocs. The results obtained from the experiments will be used to parameterize MSA for different types of microplastics. Afterwards, in-situ measurements in the ports of Rotterdam and Hamburg will be used to calibrate and validate the parameterization further. The expected outcome is a microplastic transport model for the Port of Rotterdam, including the parameterization for MSA. This model will enable port authorities to locate microplastic hotspots under different environmental conditions. Additionally, the parameterization derived for MSA can be implemented in other models, enhancing their ability to identify microplastic accumulation areas. Also see: https://micro2024.sciencesconf.org/558780/document
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