Abstract
Dumping of waste at sea can be harmful to the marine environment. Minimization of its impact is a timely and essential issue in modern sea pollution mitigation politics. This can be successfully achieved based on mathematical modeling of the processes. Mathematical modeling involves determining the distribution and redistribution of energy and matter in the ocean. A new methodology is proposed for studying the transport and diffusion of pollutants in Shallow Water basins.
First a simple procedure is developed for processing the synoptic data, obtained from observation; next, the climatic information archives are set up for the region of interest. Then, using the Monte-Carlo method, a probabilistic-statistical method is discussed for simulating changes in wind on the basis of the archives of consistent patterns. The method allows modeling of climatic nonstationary nonhomogeneous fields of wind. These fields are used as the free boundary condition in the modeling of hydrodynamics.
The equations of the Shallow Water Theory in two-dimensional approximation, along with the equation of conservative substance transportation, are adopted for modeling of fields of currents and pollutants. The value of the turbulent diffusion coefficient, estimated by the data of field experiments in the area, is used in the assessment of pollutant concentration.
Finally, results of two series of numerical experiments are discussed. The results show that this new methodology of wind simulation produces different spatial patterns for the distribution of the pollutant concentration compared to the standard methodology of setting up the constant homogeneous wind.
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Makarynskyy, O., Makarynska, D., Pires-Silva, A.A. (2001). Modeling Pollutant Diffusion with a Statistical Characterization of Wind Conditions. In: Linkov, I., Palma-Oliveira, J. (eds) Assessment and Management of Environmental Risks. NATO Science Series, vol 4. Springer, Dordrecht. https://doi.org/10.1007/978-94-010-0987-4_18
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DOI: https://doi.org/10.1007/978-94-010-0987-4_18
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