Hindcast of oil-spill pollution during the Lebanon crisis in the Eastern Mediterranean, July-August 2006

Development and testing of a 2D offshore oil spill modeling tool (OSMT) supported by an effective calibration method

An Oil Spill Modeling Tool (OSMT) has been developed in this study to predict the transport and fate of oil spills resulting from surface releases. Particularly, the Kullback-Leibler (KL) divergence method is adopted as a performance metric for the first time to formulate a calibration framework for spill trajectory prediction (STP) from the Lagrangian transport model (LTM). By finding the candidate with minimal KL divergences from modeling scenarios using designed parameter combinations, the prediction discrepancy between simulated trajectories of the LTM and oil slicks detected from satellite images is reduced. The developed approach has been evaluated through a comparison analysis between OSMT and Operational Oil Modeling Environment (GNOME) model. Subsequently, a real case study is conducted to examine the applicability and effectiveness of the OSMT. The study results indicate that OSMT can provide reliable spill trajectory simulations, and the KL divergence-based calibration method is effective in calibrating the oil spill LTM.

Dispersants as an oil spill clean-up technique in the marine environment: A review

Oil is a major source of energy in the industrial world. Exploitation of oil and rigging activities, transportation via sea, and many other mechanical failures lead to oil spills into the marine environment. In view of these, the suitability and effectiveness of oil spill response methods have always been a topical discussion worldwide. It has become necessary, now than ever, for existing spill response methods used to remove oil from the environment to be improved upon and more importantly, develop new response materials that are sustainable and environmentally friendly. There exist surfactants in nature that are non-toxic and biodegradable, which can be explored to produce potential dispersants to help remove oil safely from the surface of marine water. This review comprises of the works and resourceful materials produced by various researchers and agencies in the field of oil spill response, placing emphasis on the use of dispersants in the marine environment.

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Smart dispersants have the potential to minimize dispersant wastage.

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Biodegradable dispersants may bring a closure to discussions on toxicity.

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Bio-based formulations have the potential to replace chemical based dispersants.

Oil Spills or Look-Alikes? Classification Rank of Surface Ocean Slick Signatures in Satellite Data

Linear discriminant analysis (LDA) is a mathematically robust multivariate data analysis approach that is sometimes used for surface oil slick signature classification. Our goal is to rank the effectiveness of LDAs to differentiate oil spills from look-alike slicks. We explored multiple combinations of (i) variables (size information, Meteorological-Oceanographic (metoc), geo-location parameters) and (ii) data transformations (non-transformed, cube root, log10). Active and passive satellite-based measurements of RADARSAT, QuikSCAT, AVHRR, SeaWiFS, and MODIS were used. Results from two experiments are reported and discussed: (i) an investigation of 60 combinations of several attributes subjected to the same data transformation and (ii) a survey of 54 other data combinations of three selected variables subjected to different data transformations. In Experiment 1, the best discrimination was reached using ten cube-transformed attributes: ~85% overall accuracy using six pieces of size information, three metoc variables, and one geo-location parameter. In Experiment 2, two combinations of three variables tied as the most effective: ~81% of overall accuracy using area (log transformed), length-to-width ratio (log- or cube-transformed), and number of feature parts (non-transformed). After verifying the classification accuracy of 114 algorithms by comparing with expert interpretations, we concluded that applying different data transformations and accounting for metoc and geo-location attributes optimizes the accuracies of binary classifiers (oil spill vs. look-alike slicks) using the simple LDA technique.

Monitoring oil spill in Norilsk, Russia using satellite data

This paper studies the oil spill, which occurred in the Norilsk and Taimyr region of Russia due to the collapse of the fuel tank at the power station on May 29, 2020. We monitored the snow, ice, water, vegetation and wetland of the region using data from the Multi-Spectral Instruments (MSI) of Sentinel-2 satellite. We analyzed the spectral band absorptions of Sentinel-2 data acquired before, during and after the incident, developed true and false-color composites (FCC), decorrelated spectral bands and used the indices, i.e. Snow Water Index (SWI), Normalized Difference Water Index (NDWI) and Normalized Difference Vegetation Index (NDVI). The results of decorrelated spectral bands 3, 8, and 11 of Sentinel-2 well confirmed the results of SWI, NDWI, NDVI, and FCC images showing the intensive snow and ice melt between May 21 and 31, 2020. We used Sentinel-2 results, field photographs, analysis of the 1980-2020 daily air temperature and precipitation data, permafrost observations and modeling to explore the hypothesis that either the long-term dynamics of the frozen ground, changing climate and environmental factors, or abnormal weather conditions may have caused or contributed to the collapse of the oil tank.

Oil Spill Modeling: A Critical Review on Current Trends, Perspectives, and Challenges

Several oil spill simulation models exist in the literature, which are used worldwide to simulate the evolution of an oil slick created from marine traffic, petroleum production, or other sources. These models may range from simple parametric calculations to advanced, new-generation, operational, three-dimensional numerical models, coupled to meteorological, hydrodynamic, and wave models, forecasting in high-resolution and with high precision the transport and fate of oil. This study presents a review of the transport and oil weathering processes and their parameterization and critically examines eighteen state-of-the-art oil spill models in terms of their capacity (a) to simulate these processes, (b) to consider oil released from surface or submerged sources, (c) to assimilate real-time field data for model initiation and forcing, and (d) to assess uncertainty in the produced predictions. Based on our review, the most common oil weathering processes involved are spreading, advection, diffusion, evaporation, emulsification, and dispersion. The majority of existing oil spill models do not consider significant physical processes, such as oil dissolution, photo-oxidation, biodegradation, and vertical mixing. Moreover, timely response to oil spills is lacking in the new generation of oil spill models. Further improvements in oil spill modeling should emphasize more comprehensive parametrization of oil dissolution, biodegradation, entrainment, and prediction of oil particles size distribution following wave action and well blow outs.

An Operational Supporting System for Oil Spill Emergencies Addressed to the the Italian Coast Guard

Oil spill models are used to simulate the evolution of an oil slick that occurs after an accidental ship collision, malfunctioning of oil extraction platforms, or illegal discharges intentionally released by ships into the marine environment. We present an integrated operational oil spill prediction system that improves capacities in preventing and mitigating maritime risks from oil spills. The objective is to provide forecast information about the transport and the fate of a hypothetical oil spill under Nearly-Real Time hydrodynamic conditions in the western and central Mediterranean Sea. This complex forecast system is developed in the framework of the project SOS-Piattaforme & Impatti Off-Shore to the needs of Italian Coast Guard and other institutions, such as the Ministry of the Environment. This service has been operational since July 2020. The innovative aspect of this work is a graphical user interface (the GUI), which allows to select properties, time, and location of a potential oil spill and show the evolution of oil slick concentration and oil fate parameters. This platform represents the first component of a future Decision Support System aimed to identify the risk assessment of oil spills in order to better manage emergencies and minimize economic damages.

Progress in Operational Modeling in Support of Oil Spill Response

Following the 2010 Deepwater Horizon accident of a massive blow-out in the Gulf of Mexico, scientists from government, industry, and academia collaborated to advance oil spill modeling and share best practices in model algorithms, parameterizations, and application protocols. This synergy was greatly enhanced by research funded under the Gulf of Mexico Research Initiative (GoMRI), a 10-year enterprise that allowed unprecedented collection of observations and data products, novel experiments, and international collaborations that focused on the Gulf of Mexico, but resulted in the generation of scientific findings and tools of broader value. Operational oil spill modeling greatly benefited from research during the GoMRI decade. This paper provides a comprehensive synthesis of the related scientific advances, remaining challenges, and future outlook. Two main modeling components are discussed: Ocean circulation and oil spill models, to provide details on all attributes that contribute to the success and limitations of the integrated oil spill forecasts. These forecasts are discussed in tandem with uncertainty factors and methods to mitigate them. The paper focuses on operational aspects of oil spill modeling and forecasting, including examples of international operational center practices, observational needs, communication protocols, and promising new methodologies.

Model-based reconstruction of the Ulysse-Virginia oil spill, October-November 2018

In response to the oil spill caused by the collision between the Ro-Ro ship Ulysse and CSL Virginia on 7^th October 2018, the Lagrangian oil spill model MEDSLIK-II was utilized to predict spill transport and fate. Oil drift was forced by the high-resolution sea circulation provided by CMEMS and the ECMWF wind. Successive model runs were restarted 5 times with the distinct overflight- and satellite-derived observations provided by REMPEC and the Copernicus Sentinel-1 mission. The results were verified based on the ability to predict the first oil-beaching event that happened near Saint-Tropez (France) in the early afternoon of 16^th October. Despite the general consistency among the runs, only the last initialization was able to forecast the oil beaching. Stochastic MEDSLIK-II simulations forced by the historical meteo-oceanographic datasets 2014-2018 revealed that the coastlines between Cap Lardier and the Gulf of Saint-Tropez were among the most impacted areas.

An Operational Marine Oil Spill Forecasting Tool for the Management of Emergencies in the Italian Seas

Oil extraction platforms are potential sources of oil spills. For this reason, an oil spill forecasting system was set up to support the management of emergencies from the oil fields in the Italian seas. The system provides ready-to-use products to the relevant response agencies and optimizes the anti-pollution resources by assessing hazards and risks related to this issue. The forecasting system covers seven working oil platforms in the Sicily Channel and middle/low Adriatic Sea. It is composed of a numerical chain involving nested ocean models from regional to coastal spatial scales and an oil spill model. The system provides two online services, one automatic and a second dedicated to possible real emergencies or exercises on risk preparedness and responding. The automatic service produces daily short-term simulations of hypothetical oil spill dispersion, transport, and weathering processes from each extraction platform. Products, i.e., risk maps, animations, and a properly called bulletin, are available on a dedicated web-portal. The hazard estimations are computed by performing geo-statistical analysis on the daily forecasts database. The second service is activated in near-real-time producing oil spill simulations for the following 48 h.

Using a genetic algorithm to improve oil spill prediction

The performance of oil spill models is strongly influenced by multiple parameters. In this study, we explored the ability of a genetic algorithm (GA) to determine optimal parameters without the need for time-consuming manual attempts. An evaluation function integrating the percentage of coincidence between the predicted polluted area and the observed spill area was proposed for measuring the performance of a Lagrangian oil particle model. To maximise the objective function, the oil spill was run numerous times with continuously optimised parameters. After many generations, the GA effectively reduced discrepancies between model results and observations of a real oil spill. Subsequent validation indicated that the oil spill model predicted oil slick patterns with reasonable accuracy when equipped with optimal parameters. Furthermore, multiple objective optimisation for observations at different times contributed to better model performance.

Risk assessment of oil spills in the Chinese Bohai Sea for prevention and readiness

Oil spill accidents occur with increasing frequency in the Chinese Bohai Sea because of the presence of extensive number of oil platforms and oil pipelines the Chinese Bohai region. An appropriate risk assessment for oil spill prevention and readiness is necessary. Risk assessment for the entire Chinese Bohai Sea based on a quantitative method is proposed. We created a hypothetical simulation of oil spill trajectories based on an oil spill model for 28 oil platforms in the Chinese Bohai region in 2010. Then, we mapped a risk index in the study areas based on a combination of oil spill trajectories and shoreline susceptibility data. Five high-risk areas were identified in the entire Chinese Bohai Sea. Detailed suggestions for prevention and readiness are described here. These results can help in developing a risk assessment of oil spills in the Chinese Bohai Sea and serve as a useful analytic tool for slick-related emergencies.

Performance evaluation of oil spill software systems in early fate and trajectory of oil spill: comparison analysis of OILMAP and PISCES 2 in Mersin bay spill

The aim of this study is to evaluate the performance level of two advanced oil spill software systems in early transport and fate of oil spill through algorithms accepted in oil spill literature. To do this, the performance level of software systems mostly used in real cases have been compared. OILMAP (the oil spill prediction modeling system) and PISCES 2 (potential incident simulation, control and evaluation system) have been used for spill trajectory in the light of four spill scenarios. The findings reveal that the OILMAP has predicted a relatively larger area of spill. In addition, OILMAP has achieved closer results to the calculations of approaches adopted in the literature for evaporation calculations. Besides, OILMAP software has provided highly reliable results in the evaporation rates of oil compared to the calculations of PISCES 2. On the other hand, as for the determination of the risky area, both software systems have yielded results with high reliability values, which could be used in taking precautions against oil spill in such areas.

Modelling oil plumes from subsurface spills

An oil plume model to simulate the behavior of oil from spills located at any given depth below the sea surface is presented, following major modifications to a plume model developed earlier by Malačič (2001) and drawing on ideas in a paper by Yapa and Zheng (1997). The paper presents improvements in those models and numerical testing of the various parameters in the plume model. The plume model described in this paper is one of the numerous modules of the well-established MEDSLIK oil spill model. The deep blowout scenario of the MEDEXPOL 2013 oil spill modelling exercise, organized by REMPEC, has been applied using the improved oil plume module of the MEDSLIK model and inter-comparison with results having the oil spill source at the sea surface are discussed.

Synergistic use of an oil drift model and remote sensing observations for oil spill monitoring

In case of oil spills due to disasters, one of the environmental concerns is the oil trajectories and spatial distribution. To meet these new challenges, spill response plans need to be upgraded. An important component of such a plan would be models able to simulate the behaviour of oil in terms of trajectories and spatial distribution, if accidentally released, in deep water. All these models need to be calibrated with independent observations. The aim of the present paper is to demonstrate that significant support to oil slick monitoring can be obtained by the synergistic use of oil drift models and remote sensing observations. Based on transport properties and weathering processes, oil drift models can indeed predict the fate of spilled oil under the action of water current velocity and wind in terms of oil position, concentration and thickness distribution. The oil spill event that occurred on 31 May 2003 in the Baltic Sea offshore the Swedish and Danish coasts is considered a case study with the aim of producing three-dimensional models of sea circulation and oil contaminant transport. The High-Resolution Limited Area Model (HIRLAM) is used for atmospheric forcing. The results of the numerical modelling of current speed and water surface elevation data are validated by measurements carried out in Kalmarsund, Simrishamn and Kungsholmsfort stations over a period of 18 days and 17 h. The oil spill model uses the current field obtained from a circulation model. Near-infrared (NIR) satellite images were compared with numerical simulations. The simulation was able to predict both the oil spill trajectories of the observed slick and thickness distribution. Therefore, this work shows how oil drift modelling and remotely sensed data can provide the right synergy to reproduce the timing and transport of the oil and to get reliable estimates of thicknesses of spilled oil to prepare an emergency plan and to assess the magnitude of risk involved in case of oil spills due to disaster.

A high-resolution operational forecast system for oil spill response in Belfast Lough

This paper presents a high-resolution operational forecast system for providing support to oil spill response in Belfast Lough. The system comprises an operational oceanographic module coupled to an oil spill forecast module that is integrated in a user-friendly web application. The oceanographic module is based on Delft3D model which uses daily boundary conditions and meteorological forcing obtained from COPERNICUS and from the UK Meteorological Office. Downscaled currents and meteorological forecasts are used to provide short-term oil spill fate and trajectory predictions at local scales. Both components of the system are calibrated and validated with observational data, including ADCP data, sea level, temperature and salinity measurements and drifting buoys released in the study area. The transport model is calibrated using a novel methodology to obtain the model coefficients that optimize the numerical simulations. The results obtained show the good performance of the system and its capability for oil spill forecast.

Multidisciplinary oil spill modeling to protect coastal communities and the environment of the Eastern Mediterranean Sea

We present new mathematical and geological models to assist civil protection authorities in the mitigation of potential oil spill accidents in the Eastern Mediterranean Sea. Oil spill simulations for 19 existing offshore wells were carried out based on novel and high resolution bathymetric, meteorological, oceanographic, and geomorphological data. The simulations show a trend for east and northeast movement of oil spills into the Levantine Basin, affecting the coastal areas of Israel, Lebanon and Syria. Oil slicks will reach the coast in 1 to 20 days, driven by the action of the winds, currents and waves. By applying a qualitative analysis, seabed morphology is for the first time related to the direction of the oil slick expansion, as it is able to alter the movement of sea currents. Specifically, the direction of the major axis of the oil spills, in most of the cases examined, is oriented according to the prevailing azimuth of bathymetric features. This work suggests that oil spills in the Eastern Mediterranean Sea should be mitigated in the very few hours after their onset, and before wind and currents disperse them. We explain that protocols should be prioritized between neighboring countries to mitigate any oil spills.

Modelling of oil spills in confined maritime basins: The case for early response in the Eastern Mediterranean Sea

Oil spill models are combined with bathymetric, meteorological, oceanographic, and geomorphological data to model a series of oil spill accidents in the Eastern Mediterranean Sea. A total of 104 oil spill simulations, computed for 11 different locations in the Levantine Basin, show that oil slicks will reach the coast of Cyprus in four (4) to seven (7) days in summer conditions. Oil slick trajectories are controlled by prevailing winds and current eddies. Based on these results, we support the use of chemical dispersants in the very few hours after large accidental oil spills. As a corollary, we show shoreline susceptibility to vary depending on: a) differences in coastline morphology and exposure to wave action, b) the existence of uplifted wave-cut platforms, coastal lagoons and pools, and c) the presence of tourist and protected environmental areas. Mitigation work should take into account the relatively high susceptibility of parts of the Eastern Mediterranean.

Towards a common oil spill risk assessment framework – Adapting ISO 31000 and addressing uncertainties

Oil spills are a transnational problem, and establishing a common standard methodology for Oil Spill Risk Assessments (OSRAs) is thus paramount in order to protect marine environments and coastal communities. In this study we firstly identified the strengths and weaknesses of the OSRAs carried out in various parts of the globe. We then searched for a generic and recognized standard, i.e. ISO 31000, in order to design a method to perform OSRAs in a scientific and standard way. The new framework was tested for the Lebanon oil spill that occurred in 2006 employing ensemble oil spill modeling to quantify the risks and uncertainties due to unknown spill characteristics. The application of the framework generated valuable visual instruments for the transparent communication of the risks, replacing the use of risk tolerance levels, and thus highlighting the priority areas to protect in case of an oil spill.

Oil spill contamination probability in the southeastern Levantine basin

Recent gas discoveries in the eastern Mediterranean Sea led to multiple operations with substantial economic interest, and with them there is a risk of oil spills and their potential environmental impacts. To examine the potential spatial distribution of this threat, we created seasonal maps of the probability of oil spill pollution reaching an area in the Israeli coastal and exclusive economic zones, given knowledge of its initial sources. We performed simulations of virtual oil spills using realistic atmospheric and oceanic conditions. The resulting maps show dominance of the alongshore northerly current, which causes the high probability areas to be stretched parallel to the coast, increasing contamination probability downstream of source points. The seasonal westerly wind forcing determines how wide the high probability areas are, and may also restrict these to a small coastal region near source points. Seasonal variability in probability distribution, oil state, and pollution time is also discussed.

Oil spill hazard from dispersal of oil along shipping lanes in the Southern Adriatic and Northern Ionian Seas

An assessment of hazard stemming from operational oil ship discharges in the Southern Adriatic and Northern Ionian (SANI) Seas is presented. The methodology integrates ship traffic data, the fate and transport oil spill model MEDSLIK-II, coupled with the Mediterranean Forecasting System (MFS) ocean currents, sea surface temperature analyses and ECMWF surface winds. Monthly and climatological hazard maps were calculated for February 2009 through April 2013. Monthly hazard distributions of oil show that the zones of highest sea surface hazard are located in the southwestern Adriatic Sea and eastern Ionian Sea. Distinctive "hot spots" appear in front of the Taranto Port and the sea area between Corfu Island and the Greek coastlines. Beached oil hazard maps indicate the highest values in the Taranto Port area, on the eastern Greek coastline, as well as in the Bari Port area and near Brindisi Port area.

Towards improving the representation of beaching in oil spill models: a case study

Oil-shoreline interaction (or "beaching" as commonly referred to in literature) is an issue of major concern in oil spill modeling, due to the significant environmental, social and economic importance of coastal areas. The present work studies the improvement of the representation of beaching brought by the introduction of the Oil Holding Capacity approach to estimate oil concentration on coast, along with new approaches for coast type assignment to shoreline segments and the calculation of permanent oil attachment to the coast. The above were tested for the Lebanon oil spill of 2006, using a modified version of the open-source oil spill model MEDSLIK-II. The modified model results were found to be in good agreement with field observations for the specific case study, and their comparison with the original model results denote the significant improvement in the fate of beached oil brought by the proposed changes.

A three-step model to assess shoreline and offshore susceptibility to oil spills: the South Aegean (Crete) as an analogue for confined marine basins

This study combines bathymetric, geomorphological, geological data and oil spill predictions to model the impact of oil spills in two accident scenarios from offshore Crete, Eastern Mediterranean. The aim is to present a new three-step method of use by emergency teams and local authorities in the assessment of shoreline and offshore susceptibility to oil spills. The three-step method comprises: (1) real-time analyses of bathymetric, geomorphological, geological and oceanographic data; (2) oil dispersion simulations under known wind and sea current conditions; and (3) the compilation of final hazard maps based on information from (1) and (2) and on shoreline susceptibility data. The results in this paper show that zones of high to very-high susceptibility around the island of Crete are related to: (a) offshore bathymetric features, including the presence of offshore scarps and seamounts; (b) shoreline geology, and (c) the presence near the shore of sedimentary basins filled with unconsolidated deposits of high permeability. Oil spills, under particular weather and oceanographic conditions, may quickly spread and reach the shoreline 5-96 h after the initial accident. As a corollary of this work, we present the South Aegean region around Crete as a valid case-study for confined marine basins, narrow seaways, or interior seas around island groups.

Large-scale oil spill simulation using the lattice Boltzmann method, validation on the Lebanon oil spill case

This paper tests the adequacy of using the lattice Boltzmann method in large-scale oil spill modelling, such as the Lebanon oil spill. Several numerical experiments were performed in order to select the most appropriate lattice and to decide between the single- and two-relaxation time models. Large-scale oil spills require simulations with short computational times. In order to speed up the computation and preserve adequate accuracy of the model, five different flux limiting interpolation techniques were compared and evaluated. The model was validated on the Lebanon oil spill with regard to the oil-slick position and concentrations in the sea, and the beaching area on the coast. Good agreement with satellite images of the slick and field data on beaching was achieved. The main advantages of the applied method are the capability of simulating very low oil concentrations and computational times that are by an order of magnitude shorter compared to similar models.

Toxicogenetic profile and cancer risk in Lebanese

An increasing number of genetic polymorphisms in drug-metabolizing enzymes (DME) were identified among different ethnic groups. Some of these polymorphisms are associated with an increased cancer risk, while others remain equivocal. However, there is sufficient evidence that these associations become significant in populations overexposed to environmental carcinogens. Hence, genetic differences in expression activity of both Phase I and Phase II enzymes may affect cancer risk in exposed populations. In Lebanon, there has been a marked rise in reported cancer incidence since the 1990s. There are also indicators of exposure to unusually high levels of environmental pollutants and carcinogens in the country. This review considers this high cancer incidence by exploring a potential gene-environment model based on available DME polymorphism prevalence, and their impact on bladder, colorectal, prostate, breast, and lung cancer in the Lebanese population. The examined DME include glutathione S-transferases (GST), N-acetyltransferases (NAT), and cytochromes P-450 (CYP). Data suggest that these DME influence bladder cancer risk in the Lebanese population. Evidence indicates that identification of a gene-environment interaction model may help in defining future research priorities and preventive cancer control strategies in this country, particularly for breast and lung cancer.

High-resolution pollutant dispersion modelling in contaminated coastal sites

The recent developments in pollutant measurement methods and techniques necessitate improvements in modelling approaches. The models used so far have been based on seasonally averaged data, which is insufficient for making short-term predictions. We have improved the existing modelling tools for pollutant transport and dispersion on three levels. We significantly refined the numerical grid; we used temporally and spatially non-uniform meteorological parameters for predicting pollutant dispersion and transformation processes; we used grid nesting in order to improve the open boundary condition. We worked on a typical contaminated site (The Gulf of Trieste), where mercury poses a significant environmental threat and where an oil-spill is a realistic possibility. By calculating evasion we improved the mass balance of mercury in the Gulf. We demonstrated that the spreading of river plumes under typical wind conditions is different than has so far been indicated by model simulations. We also simulated an oil-spill in real time. The improved modelling approaches and the upgraded models are now suitable for use with the state-of-the-art measurements technology and can represent an important contribution to the decision-making process.

A modeling approach toward oil spill management along the Eastern Mediterranean

This paper examines the temporal and spatial distributions of the largest oil spill along the Eastern Mediterranean and explores management options (boom deployment and fuel upgrade) to reduce potential adverse impacts on the marine environment from similar accidents. For this purpose, the trajectory and weathering of the ~18,000 tons of heavy fuel oil spilled from the Jiyeh thermal power plant were simulated along the coast of Lebanon using the 3D MEDSLIK model, supported with sea water sampling and analysis and field measurements. The base simulation of the spill under existing conditions at the time of occurrence defined the temporal distribution over 90 days of oil spilled in terms of percentage of oil on the surface or evaporated (13.1%), dispersed in the water column or landed on the coast (86.9% landed of which 30.1% were potentially releasable). The spatial distribution defined shoreline stretches with high risk of exposure (located 35 km north of the source and stretching for more than 150 km with medium to low risk exposure). Parametric analysis revealed a relatively higher sensitivity to the drift factor, the current depth, and the time of spill parameters. Deployment of booms reduced shorelines exposure by ~95% in comparison to baseline conditions, and medium or light brands increased evaporation by ~22-42% and reduced oil reaching the coast by ~37-57% in comparison to heavy fuel oil.

A high-resolution real-time forecasting system for predicting the fate of oil spills in the Strait of Bonifacio (western Mediterranean Sea)

The Strait of Bonifacio is a long and narrow area between Corsica and Sardinia. To manage environmental emergencies related to the spill of oil from vessels, an innovative forecasting system was developed. This tool is capable of operationally predicting the dispersion of hydrocarbon spills in the coastal area of the Bonifacio Strait, either from an instantaneous or continuous spill and either in forward or backward mode. Experimental datasets, including ADCP water current measurements and the trajectories of drifter buoys released in the area, were used to evaluate the accuracy of this system. A comparison between the simulation results and experimental data revealed that both the water circulation and the surface transport processes are accurately reproduced by the model. The overall accuracy of the system in reproducing the transport of an oil spill at sea was estimated for both forward and backward prediction mode and in relation to different forecasting time lags.

On the assessment of Argo float trajectory assimilation in the Mediterranean Forecasting System

The Mediterranean Forecasting System (MFS) has been operational for a decade, and is continuously providing forecasts and analyses for the region. These forecasts comprise local- and basin-scale information of the environmental state of the sea and can be useful for tracking oil spills and supporting search-and-rescue missions. Data assimilation is a widely used method to improve the forecast skill of operational models and, in this study, the three-dimensional variational (OceanVar) scheme has been extended to include Argo float trajectories, with the objective of constraining and ameliorating the numerical output primarily in terms of the intermediate velocity fields at 350 m depth. When adding new datasets, it is furthermore crucial to ensure that the extended OceanVar scheme does not decrease the performance of the assimilation of other observations, e.g., sea-level anomalies, temperature, and salinity. Numerical experiments were undertaken for a 3-year period (2005-2007), and it was concluded that the Argo float trajectory assimilation improves the quality of the forecasted trajectories with ~15%, thus, increasing the realism of the model. Furthermore, the MFS proved to maintain the forecast quality of the sea-surface height and mass fields after the extended assimilation scheme had been introduced. A comparison between the modeled velocity fields and independent surface drifter observations suggested that assimilating trajectories at intermediate depth could yield improved forecasts of the upper ocean currents.