Modelling and Simulation of Marine Oil Snow Formation

Marine oil snow (MOS) forms through the aggregation of oil droplets with marine snow (MS) aggregates. The formation of MOS is influenced by the presence of biopolymer-producing phytoplankton, hydrodynamic conditions, and other environmental factors. To predict the occurrence, formation timescales, and dynamics of MOS, a numerical model is developed consisting: (1) Phytoplankton Growth Module and (2) Aggregation Module. The phytoplankton growth module captures multi-nutrient, multi-limitation phytoplankton bloom dynamics, and the aggregation module uses the Smoluchowski coagulation kinetics to simulate the aggregation processes. The model accounts for key environmental factors, including nutrient concentrations, temperature, pH, light availability, buffer capacity, and hydrodynamic factors such as cross-haline mixing and turbulent shear rates, accurately predicting phytoplankton bloom occurrence. The aggregation module effectively modelled the influence of critical parameters such as turbulent shear, stickiness index, and porosity, capturing the transition from primary particles to complex aggregates. Each module was validated against published experimental datasets. The phytoplankton growth module was validated using Engel et al. (2002), while the aggregation module was tested using Grossart et al. (2006) for MS and Fu et al. (2014) for MOS. Further validation was performed using satellite data following the Deepwater Horizon blowout event. The model showed strong agreement with the validation datasets. Model robustness was assessed through a comprehensive sensitivity analysis of key parameters. This modelling framework serves as a critical tool for predicting the likelihood of MOS formation and estimating the associated timescales during oil spill accidents.