We can't find the internet
Attempting to reconnect
Something went wrong!
Hang in there while we get back on track
Mathematical modeling of hydrodynamic processes in shallow waters in the presence of pollutants of various origin, as well as areas covered with plastic waste
AI summary Read the abstract
This paper presents mathematical modeling approaches for simulating hydrodynamic processes in shallow waters contaminated by pollutants including nano- and microplastics. The models incorporate data assimilation, sensitivity analysis, and multi-scale integration to improve accuracy of pollutant transport simulations.
The paper covers the modeling of hydrodynamic processes in shallow waters in the presence of pollutants of various types, as well as areas covered with plastic waste, including nano- and microplastics. The simulation performed using new and effective mathematical instruments, including assimilation methods of measurement data, restoration of the state function, diagnostics of quality of the developed models, the research the sensitivity of models to variations in input data, the integration of models with various scales. Interrelated non-stationary, spatially inhomogeneous mathematical models of hydrodynamics and biological kinetics of shallow waters were developed and numerically implemented. They describe non-linear processes of hydrophysics, biogeochemical cycles, transport and transformation of suspensions and sediments with microplastic particles and other pollutants, absorption of it by zooplankton and fish, movement of plastic particles through food, the forecast of their impact on the main hydrobionts of shallow waters of the Azov-Black Sea basin, including the Azov Sea, Taganrog Bay, Gelendzhik Bay. The models take into account the heat and salt transport; the complex, dynamically changing water geometry; friction on the bottom and wind stresses; turbulent and advective heat and mass exchange in three coordinate directions; the Coriolis force; river flows; evaporation, temperature and oxygen regimes. They make it possible to improve the accuracy of hydrophysical processes modeling in shallow waters, to detect vortex structures of currents that can be a natural pollution traps, including microplastic. Based on a supercomputer, a complex of application has been designed and adapted for solving predictive problems of water ecology and water resources management.
More Papers Like This
Simulation of the development of biological zooplankton communities in shallow water at it pollution by nano- and microplastic particles
AI summary Read the abstract
This paper presents a mathematical model simulating the development of zooplankton communities in shallow water affected by nano- and microplastic particle pollution. The work describes numerical implementation of the model applied to a specific coastal water body.
Beyond advection: A Lagrangian framework for microplastic transport in depth-averaged shallow water flows
AI summary Read the abstract
Researchers built a computer model to predict how microplastics move in shallow water, accounting for factors like sinking, biological buildup on particles, and breakdown over time. Tests on computers and comparison with an experiment showed sinking and biological buildup strongly affected particle movement, while breakdown had little effect, and the model ran efficiently with only a small added computing cost.
Numerieke modellering van dispersie van plastic in aquatische milieus
AI summary Read the abstract
This study developed numerical models to simulate the dispersal and spatiotemporal dynamics of microplastics in aquatic environments — including freshwater, estuarine, coastal, and marine systems — to complement field observations that alone cannot capture the full complexity of plastic transport.
Using hydrodynamic models to understand the impacts and risks of plastic pollution
AI summary Read the abstract
This paper used hydrodynamic computer models to simulate the transport and accumulation of plastic pollution in estuarine and coastal environments. The approach helps predict where marine litter concentrates based on currents and geography, which is useful for targeting cleanup efforts and informing coastal management policies.
Modeling the spatiotemporal distribution, bioaccumulation, and ecological risk assessment of microplastics in aquatic ecosystems: A review
AI summary Read the abstract
Researchers modeled the spatiotemporal distribution and ecological risk of microplastics across a coastal marine environment, incorporating hydrodynamic data and bioaccumulation factors for multiple species. The model predicted highest microplastic concentrations near urban outflows with risk extending through the food web.
Research digests by email
When a large batch of papers lands in the Atlas, we read through it and send a short write-up of what stood out.