A numerical oil spill model based on a hybrid method

The purpose of this paper is the development of a hybrid particle tracking/Eulerian-Lagrangian approach for the simulation of spilled oil in coastal areas. Oil discharge from the source is modeled by the release of particles. When the oil slick thickness or the oil concentration reaches a critical value, particles are mapped on slick thickness or node concentrations, and the calculations proceed in the Eulerian-Lagrangian mode. To acquire accurate environment information, the model is coupled with the 3-D free-surface hydrodynamics model (POM) and the third-generation wave model (SWAN). By simulating the oil processes of spreading, advection, turbulent diffusion, evaporation, emulsification, dissolution and shoreline deposition, it has the ability to predict the horizontal movement of surface oil slick, the vertical distribution of oil particles, the concentration in the water column and the mass balance of spilled oil. An accidental oil release near Dalian coastal waters is simulated to validate the developed model. Compared with the satellite images of oil slicks on the surface, the numerical results indicate that the model has a reasonable accuracy.     

SAR observation and model tracking of an oil spill event in coastal waters

Oil spills are a major contributor to marine pollution. The objective of this work is to simulate the oil spill trajectory of oil released from a pipeline leaking in the Gulf of Mexico with the GNOME (General NOAA Operational Modeling Environment) model. The model was developed by NOAA (National Oceanic and Atmospheric Administration) to investigate the effects of different pollutants and environmental conditions on trajectory results. Also, a Texture-Classifying Neural Network Algorithm (TCNNA) was used to delineate ocean oil slicks from synthetic aperture radar (SAR) observations. During the simulation, ocean currents from NCOM (Navy Coastal Ocean Model) outputs and surface wind data measured by an NDBC (National Data Buoy Center) buoy are used to drive the GNOME model. The results show good agreement between the simulated trajectory of the oil spill and synchronous observations from the European ENVISAT ASAR (Advanced Synthetic Aperture Radar) and the Japanese ALOS (Advanced Land Observing Satellite) PALSAR (Phased Array L-band Synthetic Aperture Radar) images. Based on experience with past marine oil spills, about 63.0% of the oil will float and 18.5% of the oil will evaporate and disperse. In addition, the effects from uncertainty of ocean currents and the diffusion coefficient on the trajectory results are also studied.     

Hebei Spirit oil spill monitored on site by fluorometric detection of residual oil in coastal waters off Taean, Korea

The spatiotemporal distributions of dissolved and/or dispersed oil in seawater and pore water were monitored on site by fluorometric detection method after the Hebei Spirit oil spill. The oil concentrations in intertidal seawater, 15 days after the spill, were as high as 16,600 μg/L and appeared to decrease below the Korean marine water quality standard of 10 μg/L at most sites 10 months after the spill. Fluorometric detection of oil in pore water was introduced to eliminate the effects of grain size for the quantification of oil in sediments and to better explain spatial and temporal distribution of oil pollution at sandy beaches. The fluorescence detection method was compared with the conventional laboratory technique of total petroleum hydrocarbon analysis using gas chromatography. The method of fluorescence detection of oil was capable of generating results much faster and more cost-effectively than the traditional GC technique.     

Development of FBMINC model for particle diffusion in fluids

An accurate particle tracking method using FBMINC （new fractional Brownian motion） is outlined. It generates non-Fickian diffusion rather than Fickian diffusion as traditional particle tracking model does. The FBMINC model is based on fractional Brownian motion （fl3m） which is generalization of regular Brownian motion. The two models of fBms （FBM model and FBMINC model） were explored and the differences of the two models are compared from the three aspects： the standard deviation of each step, the small memory and the effect of the number of particles in the cloud. The results show the FBMINC model is a better model as it produces more accurate statistics. The effect of simple shear dispersion for both Brownian and fBm was investigated. The power law scaling of fBm shear dispersion was correctly identified. In addition, a scaling coettieient was found numerically. The FBMINC model is then used for producing both superdiffusive and subdiffusive particle paths, therefore, the non-Fickian diffusion of soil particle clouds can be modelled. The particle clouds represent soil contaminant are released in an idealised coastal bay and the fBm particle tracking method is used for simulation the particle cloud spreading in the bay. There is a noticeable increase in the spreading rate of the cloud. In addition, owning to the spreading rate of the cloud, a noticeable part of it has escaped the bay area and transported downstream. The variation of the Hurst exponent can lead to an area of the flow being affected by a contaminant cloud which is not picked up by the regular Brownian motion models. The purpose of this paper is to bring soil transport engineers a new angle on soil particle transport research in fluids. Using FBM1NC particle tracking model allows more flexibility in simulation of diffusion in soil contaminant spread in coastal bay or ocean surface.     

Intelligent ship traffic monitoring for oil spill prevention: risk based decision support building on AIS

The paper describes a model, which estimates the risk levels of individual crude oil tankers. The intended use of the model, which is ready for trial implementation at The Norwegian Coastal Administrations new Vard? VTS (Vessel Traffic Service) centre, is to facilitate the comparison of ships and to support a risk based decision on which ships to focus attention on. For a VTS operator, tasked with monitoring hundreds of ships, this is a valuable decision support tool. The model answers the question, "Which ships are likely to produce an oil spill accident, and how much is it likely to spill?".     

Quantification of longitudinal dispersion by upscaling Brownian motion of tracer displacement in a 3D pore-scale network model

We present a 3D network model with particle tracking to upscale 3D Brownian motion of non-reactive tracer particles subjected to a velocity field in the network bonds, representing both local diffusion and convection. At the intersections of the bonds (nodes) various jump conditions are implemented. Within the bonds, two different velocity profiles are used. At the network scale the longitudinal dispersion of the particles is quantified through the coefficient D_L, for which we evaluate a number of methods already known in the literature. Additionally, we introduce a new method for derivation of D_L based on the first-arrival times distribution (FTD). To validate our particle tracking method, we simulate Taylor’s classical experiments in a single tube. Subsequently, we carry out network simulations for a wide range of the characteristic Péclet number Pe_? to assess the various methods for obtaining D_L. Using the new method, additional simulations have been carried out to evaluate the choice of nodal jump conditions and velocity profile, in combination with varying network heterogeneity. In general, we conclude that the presented network model with particle tracking is a robust tool to obtain the macroscopic longitudinal dispersion coefficient. The new method to determine D_L from the FTD statistics works for the full range of Pe_?, provided that for large Pe_? a sufficiently large number of particles is used. Nodal jump conditions should include molecular diffusion and allow jumps in the upstream direction, and a parabolic velocity profile in the tubes must be implemented. Then, good agreement with experimental evidence is found for the full range of Pe_?, including increased D_L for increased porous medium heterogeneity.     

Temporal variation of chlorophyll a concentration in the coastal waters affected by the Hebei Spirit oil spill in the West Sea of Korea

Time series changes in chlorophyll a concentration before and after the Hebei Spirit oil spill that occurred in December 2007 were analyzed using NCEP wind and SeaWiFS/MODIS ocean color data. Prevailing southwesterly winds and northeast/southwestward tidal currents pushed the oil towards Korea’s West Sea coast of Taean. After the oil spill, daily chlorophyll a concentration decreased about 45-50% compared to the normal condition before the oil spill, and this decrease continued for about two weeks. Monthly mean chlorophyll a concentration in December 2007 was lower compared to the average value for the same month between 1998 and 2007, but, in October and November 2007 before the spill and in January-February 2008 after the spill, the concentration value was higher than average for the same period between 1998 and 2007.     

Effects of oil spill on seawater infiltration and macrobenthic community in tidal flats

Tidal flat ecosystem simulators are used to clarify the effects of stranded fuel oil on tidal flat ecosystems. Results show that oil spills increase the periphyton on sediment by decreasing the predation stress caused by deposit feeders. About a month after an oil spill, the total population density of the macrobenthos recovered. The oxidation-reduction potential in the surface sediment drops to a negative value after the oil spill, and the anaerobic condition throughout the sediment seems to be responsible for the decrease in the population density of the macrobenthos. The infiltration volume of seawater into the oil-stranded sediment decreases to a third of that without the oil spill. The recovery of infiltration volume after about a month coincides with the recovery of the population density of the macrobenthos. This result suggests that the macrobenthic population is highly dependent on the infiltration of seawater.     

Temporal and geographical trends in the genotoxic effects of marine sediments after accidental oil spill on the blood cells of striped beakperch (Oplegnathus fasciatus)

To determine the impact of genetic toxicity caused by the Hebei Spirit oil spill on December 7, 2007, we measured DNA damage in the blood cells of striped beakperch in vitro after exposure to extracts from sediments in the Taean area. The objective of this study was to investigate temporal changes of toxic effects caused by residual PAHs in the sediments up to 18 months after an oil spill. In conclusion, DNA damage had reduced over this 18-month period; that is, the sediments recovered quickly from the oil pollution. In addition, statistically significant correlations between PAHs and DNA damage were observed. Because the comet assay is sensitive to DNA damage induced by genotoxic substances from the polluted sediments, the comet assay can be considered a useful tool as a biomarker in investigating genetic toxicity in environmental monitoring and elucidating the recovery of oil pollution after oil spill as well.     

PAH concentrations in Coquina (Donax spp.) on a sandy beach shoreline impacted by a marine oil spill

The BP MC252 well failure in the Gulf of Mexico, April 2010 caused concern for crude oil and polycyclic aromatic hydrocarbon (PAHs) exposure along the sandy beaches of the Florida Panhandle. We began collections of Coquina clams (Donax spp.) from the surf zone of Florida Panhandle beaches to monitor PAH contamination to compliment analysis of surf zone sand samples. These clams had higher levels of PAHs relative to ambient sand, and this allowed us to continue to monitor PAH levels after sand concentrations fell below limits of detection. PAH levels in the Coquina tissues were highly variable, perhaps indicative of the heterogeneous distribution of oil and tar on the beaches and exposure to tar particles. Overall, PAH levels decreased continuously in both sand and Coquina tissues, reaching limits of detection within one and two years respectively after oil landed on Florida Panhandle beaches. Our work suggests these surf zone molluscs may be used to monitor pollutant exposure along high energy sandy beach shorelines.