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We performed stochastic simulations of hypothetical oil spills from a single-point buoy mooring and subsea pipeline for the Port of Taranto given that this port is an essential strategic hub in the European logistic chain. Our methodology integrates (1) the MEDSLIK-II oil spill model coupled to a high-resolution hydrodynamic model run on an unstructured grid in operational forecasting mode; (2) a hypothetical oil spill scenario based on a historical pipeline rupture at the Port of Genoa, 2016; and (3) randomly sampling the environmental conditions over 2018-2020. The main oil drift was found to be directed southwesterly towards the outlet to the open sea. When oil is transported by highly variable currents, waves and turbulent mixing, it is exposed to multiple strandings and washing-offs from concrete constructions in the port. Consequently, oil tends to be dispersed almost isotropically over the Mar Grande, indicating low to moderate pollution indices.

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The cost of tracking Lagrangian particles in a domain discretized on an unstructured grid can become prohibitively expensive as the number of particles or elements grows. A major part of the cost in these calculations is spent on locating the element that hosts a particle and detecting binary collisions, with the latter traditionally requiring 𝒪(N2) operations, N being the number of particles. This paper introduces an optimal search box strategy to significantly reduce the cost of these two operations, ensuring a nearly 𝒪(N) scaling of the cost of collision detection for large-scale simulations. The particle localization strategy is constructed by obtaining an a priori estimate for the optimal number of search boxes as a function of the number of elements, particles, and time steps. The introduced method is generic, as it must be tuned only once for a given implementation and element type. The optimal number of search boxes for collision detection, although complex in form, can be reasonably approximated as the number of particles. The optimality of our method is shown using three drastically varying geometries.

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Intensive economic and shipping activities in Singapore Strait have caused Singapore coastal waters to be under high risk of water pollution. A nested three-dimensional unstructured-grid SUNTANS model is applied to Singapore coastal waters to simulate flow and pollutant transport. The small domain (~50m resolution) Singapore coastal model is nested within a large domain (~200m resolution) regional model. The nested model is able to predict water surface elevations and velocities with high R(2) values of 0.96 and 0.91, respectively. Model results delineate the characteristics of circulation pattern in Singapore coastal waters during the Northeast and Southwest monsoons. The pollutants are modeled as passive tracers, and are released at six key sailing locations Points 1-6 in Singapore coastal waters and are named as Passive Tracers 1-6, respectively. Our results show that the rate of dispersion is twice as large for the Northeast monsoon compared to the Southwest monsoon due to differences in large-scale monsoons and small-scale local winds. The volume averaged concentration (VAC) diminishes faster and the local flushing time is shorter during the Northeast monsoon than the Southwest monsoon. Dispersion coefficients K and the VAC decreasing rate are maximum for Tracers 2 and 3 with shortest local flushing time due to the strong surrounding currents and abrupt bathymetry changes near Senang and St. John Islands. Dispersion coefficients K and the VAC decreasing rate are minimum for Tracer 1 due to weak currents induced by the semi-enclosed coastline near Tuas. It is found that both the lateral dispersion coefficient Ky and the compound dispersion coefficient K obey a "4/3-law", which defines a linear correlation between dispersion coefficients and 4/3-power of selected length scale.

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