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Modeling the pathways of microplastics in the Gulf of Finland, Baltic Sea – sensitivity of parametrizations
Summary
Researchers developed an open-source Lagrangian particle tracking model to simulate microplastic transport in the Gulf of Finland, incorporating processes like diffusion, beaching, resuspension, and biofouling. Sensitivity analysis showed that beaching and biofouling were the major factors removing particles from the water column, while stronger diffusion enhanced microplastic export from the gulf. The study provides a foundation for improving microplastic transport simulations in coastal environments.
This study introduces an open software Lagrangian particle tracking model designed for simulating the transport of microplastics (MPs), which incorporates crucial processes such as horizontal diffusion, beaching, resuspension, and biofouling. A sensitivity analysis for the parametrization of these processes was conducted on a regional scale – in the Gulf of Finland (GoF), the eastern Baltic Sea – employing very high-resolution hydrodynamic model output to drive the particle model. The sensitivity analysis underscores the impact of each process on the number of particles in the water column, sediments, beach areas, and at the domain boundary. The results indicate a significant impact of including or excluding a process and relatively high sensitivity of the parametrization on the simulated MP pathways. Stronger diffusion dispersed particles widely throughout the gulf and enhanced the export of the MPs out from the gulf. Beaching and biofouling were the major contributing factors to particle removal from the water column, while resuspension promoted settling in offshore areas. The number of beached particles rapidly increased during the wind-induced downwelling process. Scenario simulations, including parametrizations favoring or hindering MP transport, showed that a coincidence of several factors could lead to very diverse MP pathways. The analysis offers valuable insights, providing a foundation for tuning the model parameters to improve simulations with realistic loads in the future.
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