Displays

The current lack of a standardized approach to compute the coastal oil spill hazard due to maritime traffic accidental releases has hindered an accurate estimate of its global impact, which is paramount to manage and intercompare the associated risks. We propose here a hazard estimation approach that is based on ensemble simulations and the extraction of the relevant frequency distributions. We demonstrate that both open ocean and beached oil concentration distributions fit a Weibull curve, a two-parameter fat-tail probability distribution function. The simulation experiments are carried out in all the coastal areas of the Atlantic ocean basin. An indicator that quantify the coastal oil spill hazard is proposed and applied to the study areas.

How to cite: Pinardi, N., Sepp-Neves, A., Trotta, F., and Navarra, A.: A general methodology for beached oil spill hazard mapping and its application to the Atlantic basin coasts, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-6032, https://doi.org/10.5194/egusphere-egu2020-6032, 2020.

The Copernicus Marine Environmental Monitoring Service (CMEMS) is a unique capability to provide daily state-of-the-art ocean analyses and forecasts. In the event of accidental marine pollution incidents, those products can help predict where slicks of pollutant and other substances spilled at sea will drift. For a given area, several products are generally available and it is sometimes difficult to know which is the most suitable for this type of use. The use of several CMEMS products during a major accident in the Bay of Biscay is presented here.

On March 12, 2019, the merchant ship Grande America sank at a depth of 4600 m, 350 km off the French coast, in the Bay of Biscay. It caused a spill of bunker oil and loss of containers. The MOTHY drift model was used daily during the aerial surveillance and recovery at sea period. It provided drift forecasts for oil slicks and containers up to 3 days in deterministic mode and up to 10 days in probabilistic mode. Long-term modelling of residual diffused pollution was also carried out, in particular to manage continuous leakage from the wreck. A technical committee of experts met daily to evaluate drift observations and forecasts. It focused on the best choices of available ocean models.

The operational ocean analysis and forecasting systems IBI (Iberian Biscay Irish) at 1/36 degree and Global Mercator at 1/12 degree were used. They led to significant differences in drift predictions, and only one of the two systems was retained after a few days of use. These differences are analysed in the light of available observations.

Drift forecasts did not indicate any oil arrival to the coast. This allowed the authorities to organize the response at sea without mobilizing resources ashore. No pollution was indeed observed on the coasts.

How to cite: Daniel, P., Drevillon, M., Levier, B., and Gouriou, V.: Relevant CMEMS products to predict oil slick drift in the Grande America accident, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-13905, https://doi.org/10.5194/egusphere-egu2020-13905, 2020.

Oil pollution can enter the marine environment from many sources including land, shipping, and oil installations. It can have significant impacts on the marine environment that, depending on the type of oil, can last for prolonged periods of time. Monitoring oil pollution in the Mediterranean Sea region has been conducted using both aerial and satellite surveillance. This presentation will provide an overview of the sources and volumes of oil entering the Mediterranean, identify impacts on the marine ecosystem in general terms, and will review surveillance activities in the region, including cooperative activities undertaken by regional and EU agencies, for example.

How to cite: Carpenter, A.: Oil Pollution in the Mediterranean Sea: An Overview, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-2982, https://doi.org/10.5194/egusphere-egu2020-2982, 2020.

The fate of micro plastic litter (<5mm) in the marine environment is still largely unknown. H2020 project CLAIM (Cleaning Litter by developing and Applying Innovative Methods) uses model based assessments to improve our knowledge on the micro plastic sources, sinks and pathways. A systematic approach for assessing the sources and pathways of land emitted microplastics was developed and applied for two types of micro plastic from car tyres and cosmetic products. After entering the sea, micro plastic pollutants are affected by transport, biofouling, sinking and sedimentation. A 3D modelling tool has been developed by including these processes. Multi-years-studies (2013-2018) were performed to evaluate seasonal drift pattern and accumulation zones. DMI’s high resolution ocean circulation model HBM, in 900m resolution for the entire Baltic Sea serves as the modelling platform for the assessments. It was found that the fate of micro plastics at sea depends largely on transport and the sinking processes, including biofouling. Tyre wear is heavier than sea water and is accumulating in the deeper parts of the Baltic Sea, whereas micro plastics from cosmetic products are lighter than sea water and are floating near the surface, until biofouling has increased their density sufficiently enough. Key processes that determine the fate micro plastics at sea are introduced and the results of the multi-year study: drift pattern and accumulation zones are presented.

How to cite: Murawski, J. and She, J.: Fate and dynamic of marine micro plastics in the Baltic Sea, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-21297, https://doi.org/10.5194/egusphere-egu2020-21297, 2020.

Marine litter has been systematically registered at selected beaching sites within a framework of the OSPAR commission. We select a number of sites in the North Sea, Norwegian Sea and the Barents Sea to investigate where marine litter at these site could come from. Using results from hydrodynamic ocean models, wave models and atmospheric forecasts we backtrace litter from the beaching sites to possible origins within a limited time frame at the order of years. While the identified sources are hypothetical at first, we compare the types of registered plastic litter with reasonable sources in the regions identified as possible origins from the model. Thereby we distinguish between fishery related litter, industrial litter and litter from personal consumption, as the composition between these types differ between the OSPAR sites. Our modeling experiments are designed in co-production with  stakeholders for planning strategies to address and reduce marine litter.

How to cite: Röhrs, J., Dagestad, K.-F., Mauritzen, C., Opstad Strand, K., Grøsvik, B. E., and Antunes Nogueira, L.: Backtracing of marine litter and microplastic from OSPAR beaches in the North Atlantic, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-5977, https://doi.org/10.5194/egusphere-egu2020-5977, 2020.

Marine debris and pollution of the sea is well recognized problem. Knowledge of the potential destination and time of arrival for buoyant or nearly buoyant contaminants as, for example, microplastics, is necessary for effective policy planning.

This work analyzes characteristics of buoyant objects in the Baltic Sea using simulations of Lagrangian particle movement. Simulations are based on current and wind model data. Initially particles are regularly distributed (spaced 5 km) over the Baltic Sea and a new simulation and particle release is started every day over a period of 10 years – years 2008-2017. It is assumed that upon reaching the coast particle gets washed out on the coast.

The aim of this work was to acquire following 3 drift characteristics for possible buoyant object movement in the Baltic Sea:

1. How many days does it take from different regions of the Sea to reach the coast, what regions (clusters) can be identified that share similar behavior for different seasons;
2. Which coastal regions are most at risk – which regions get particles washed out the most;
3. What are main pathways for the particles – which sea regions affect which coastal regions the most.

As the distributions of floating time and location are non-normal then the methods of Symbolic Data Analysis (SDA) were used. To be more exact, statistics from each sea point or coastal segment was described by empirical distribution function (histogram) and differences/similarities were calculated using squared Wasserstein distance. The simulations cover multiple seasons – therefore the difference between seasons is also examined for each of 3 drift characteristics.

Part of the research is supported from the Latvian Academy of Sciences, project lzp-2018/1-0162 DRIMO - DRIft MOdelling for pollution reduction and safety in the Baltic Sea, 2018 - 2021.

How to cite: Bethere, L., Valainis, A., Sennikovs, J., and Bethers, U.: Drift of buoyant objects in the Baltic sea – model data analysis, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-8659, https://doi.org/10.5194/egusphere-egu2020-8659, 2020.

The Taranto Sea is a Mediterranean lagoon where alarming pressure is expected to further increase, due to industrialization, heavy ship traffic, and densely populated coasts. The area hosts the Trading Port, Industrial Port, and Container Terminal. There is an important refinery, owned by ENI's Refining&Marketing, with a potential of 6 million tons per year (Autorità di Sistema Portuale del Mar Ionio – Porto di Taranto, 2017). A buoyed area in the Mar Grande is used by tankers of up to 300,000 GRT carrying petroleum for the refinery. Being at risk of oil pollution, the Taranto Sea became a pilot site for the development of a universal relocatable platform aimed at the real time management of marine pollution events in the harbors and ports in the framework of the IMPRESSIVE Project.

According to a Project paradigm, marine pollution forecasting system in harbors includes (1) EO observation technologies (satellite, ASV, UAV); (2) high-resolution hydrodynamic models based on downscaling of CMEMS products, and (3) pollution transport models.

To implement the system components for the Taranto Sea the Lagrangian oil spill model MEDSIK-II has been coupled to Southern Adriatic Northern Ionian coastal Forecasting System (SANIFS http://sanifs.cmcc.itFederico et al., 2017) and ECMWF atmospheric forecast. To this end, the SANIFS output discretized on the unstructured horizontal grid at a variable resolution of 3–4 km for the open sea and of 50–500 m for the coastal area is interpolated to a regular grid with a resolution of 150 m. For the first time, MEDSLIK-II can use currents and sea surface temperature of such the resolution, which is almost 15 times less than previously exploited horizontal resolution for the Pilot sites in the framework of coupling to the Adriatic Forecasting System (AFS) (Guarnieri et al., 2010).

The new coupling is planned to run the MEDSLIK-II simulations in stochastic mode in order to evaluate the environmental consequences of possible accidents and malfunctions in the ENI petroleum transport system.

This work is performed in the framework of the IMPRESSIVE project (#821922) co-funded by the European Commission under the H2020 Programme.

References:

Autorità di Sistema Portuale del Mar Ionio – Porto di Taranto, 2017. Three-year operational plan 2017–2019 and Port vision 2030 of the Port of Taranto. http://www.port.taranto.it/index.php/en/

Federico, I., Pinardi, N., Coppini, G., Oddo, P., Lecci, R., Mossa, M. 2017. Coastal ocean forecasting with an unstructured grid model in the southern Adriatic and northern Ionian seas. Nat. Hazards Earth Syst. Sci., 17, 45–59, doi: 10.5194/nhess-17-45-2017.

Guarnieri, A., Oddo, P., Pastore, M., Pinardi, N., 2010. The Adriatic Basin Forecasting System new model and system development. Coastal to Global Operational Oceanography: Achievements and Challenges, pp. 184–190.

How to cite: Liubartseva, S., Federico, I., Coppini, G., and Lecci, R.: Oil spill modeling for the Port of Taranto (SE Italy), EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-2946, https://doi.org/10.5194/egusphere-egu2020-2946, 2020.

The Bulgarian Black Sea coast is an area with intense human activity, but also there is a complex ecosystem. Several anthropogenic sources generate loud sound levels in this area. The two most wide spread are maritime transport and hydrocarbon exploration and exploitation in the Bulgarian offshore sector. Underwater sound may have negative impact on animals in the Bulgarian waters that are sensitive to sound, such as marine mammals and certain fish species. 

The knowledge of ambient noise levels is very important for the characterization of the environmental status with regard to the European Marine Strategy Framework Directive (MSFD). The directive is aiming at a more effective protection of the marine environment including the protection of marine life exposed to noise, and the improvement of the health of the marine environment as a whole.

To estimate this impact the ocean technologies department of Bulgarian Institute of Oceanology developed a system to monitor the sound generated by marine activities following the TSG Noise guidance. The aim was to provide an integrated solution to monitor and asses the noise impact of ship traffic or other marine activities. The development was funded by program BG02 "Integrated management of marine and inland waters" financed by the financial mechanism of the European economic Area (EEA FM) 2009-2014.

The system consists of monitoring and simulation components. The combination of numerical modelling and noise measurements at selected locations offers a credible solution to the problem of underwater noise monitoring. The monitoring component comprises an array of passive sound recorders, equipped with hydrophones, self-contained power supplies, data acquisition and storage electronics. The simulation tool is in development. Suitable modelling approaches, modelling scenarios, and acoustic model input values are being selected and applied for the most important sources of sound and for underwater sound propagation in the Bulgarian waters. The tool computes sound maps produced by multiple noise point sources, as input for assessment of the environmental status. For optimum results, the simulation tool will be validated using acoustic measurements provided by the monitoring tool.

Future work includes development of a post-processing tool of the sound maps to obtain indicators relevant to both the noise anthropogenic pressure and biological effect of underwater noise impact on marine life.

How to cite: Marinova, V. and Stefanov, A.: Development of a system for monitoring and assessment of underwater sound, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-9407, https://doi.org/10.5194/egusphere-egu2020-9407, 2020.

Marine environmental security are facing increasingly prominent problems in recent years. Under the current context of big data, most of the emergency event participants are in a dual dilemma of "knowledge ocean" and "knowledge deficiency" in their responses to emergencies, leading to a result that they fail to quickly acquire and use relevant knowledge. For the need of risk prevention and control over marine environmental security events, it is necessary to make research on the knowledge base of marine environmental security risks’ prevention and control and organize the knowledge base system based on the knowledge related to storm surges, enteromorpha, marine oil spills, tsunamis, sea ice and other marine environmental security events, including such contents as basic knowledge, laws and regulations, plans, cases, prevention and preparation, monitoring and early warning, disposal and rescue, and so on. Through such methods as knowledge maps, multi-type knowledge coupling, digitization of risk prevention and control knowledge and the like, the ontology and detailed element sets are constructed for the knowledge base on prevention and control over comprehensive risks against marine environmental safety, thus forming the entity of the risk prevention and control knowledge base.

How to cite: Wu, L., Xu, F., and Sun, L.: Research on the construction of knowledge base system of Marine disasters and emergencies risk prevention and control, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-12815, https://doi.org/10.5194/egusphere-egu2020-12815, 2020.

The Aegean Sea is one of the world’s busiest waterways, combined with complex and intense weather and sea current patterns with strong seasonality, complicated coastline and bathymetry. Therefore, the uncertainty assessment of the oil spill forecasting systems in this region is of great interest. The purpose of this study is to evaluate the impact of the uncertainty of the atmospheric forcing on the performance of the oil spill modelling and the dispersion of the pollutants in the marine environment. Ensemble simulations were carried out using the ECMWF Ensemble Prediction System and the oil spill model MEDSLIK II. The Aegean Sea was chosen as the study area performing ensembles of 50 members with seven days forecast lead time, during different seasons. Three types of oil were chosen representing lighter, medium and heavier oil spills, covering also a wide range of oil densities. The oil spill duration and the spill rate were chosen taking into account significant accidents of the past like for instance the Prestige case. Preliminary results suggest that the model errors in the oil spill trajectories are sensitive to the atmospheric forcing uncertainties.

Keywords: Aegean Sea, MEDSLIK II, Oil spill, ensemble simulation, uncertainty

How to cite: Kampouris, K., Vervatis, V., Karagiorgos, J., and Sofianos, S.: Oil spill forecasting systems uncertainty assessment in the Aegean Sea, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-20228, https://doi.org/10.5194/egusphere-egu2020-20228, 2020.

Coastal areas are experiencing an increasing anthropic pressure worldwide, especially due to port activities. In addition, valuable ecosystems such as Marine Protected Areas (MPA) might be located close to ports and be potentially subject to pollutant driven by the local current pattern. It is then fundamental to develop tools to analyze and quantify the tendency of a MPA to be affected by generic pollutant released from a port. Present work is based on a series of Lagrangian experiments carried out on a domain containing the port of Livorno and the Meloria Sholas MPA, located in the Tuscany Archipelago (Italy). The flow field employed to force the experiments is obtained from a downscaling modelling chain implemented with the 3D ROMS software. The top level is a 1.2 km low-resolution model covering the North-West portion of the Mediterranean basin which feeds with a one-way nesting algorithm a 400 m mid-resolution model for the Tuscany Archipelago, extending West of Corsica Island and up to the Gulf of Genova. The inner level of the modelling chain is a 50 m high-resolution coastal model (offline nesting) which covers the area of Meloria Shoals, the port, and their surroundings. Hydrodynamic simulations are carried out for one year. Initial conditions are provided by the CMEMS (1/24° res) model Analysis, as well as boundary conditions for the low-resolution model. Atmospheric forcing comes from the downscaling of the ERA-5 reanalysis dataset, consisting on the BOLAM model implemented on a 7 km grid of the Med-CORDEX domain, in which the MOLOCH model is nested on a 2.5 km spaced grid. Lagrangian numerical experiments are carried out considering the consecutive release of passive particles in the port area, at finite intervals for one year, following the trajectories for ten days. To estimate the degree of hydrodynamic connectivity between the port and the MPA and give a measure of the probability of contamination, the “oceanographic distance” is computed in several ways from the calculated trajectories. Preliminary results show the main transport pattern is mostly distributed alongshore, making the MPA less connected to the port compared to areas placed at the same distance.

How to cite: Bendoni, M., Brandini, C., Fattorini, M., Lapucci, C., and Pretti, C.: Estimate hydrodynamic connectivity and probability of contamination through Lagrangian experiments in a high resolution shelf sea model, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-20673, https://doi.org/10.5194/egusphere-egu2020-20673, 2020.

Quantifying fluxes of particulate trace metals to the deep sea is a necessary step to understand their role in many oceanographic processes. The Gulf of Vera, in the SW Mediterranean Sea, is an ideal place to quantify these fluxes given the presence of a metal-rich mine tailings deposit in Portmán Bay, in its northern shore. Portmán Bay is one of the most extreme cases in Europe of mine waste impacts on coastal ecosystems, both inshore and offshore. About 57 million tons of tailings enriched in Fe, Pb, Mn, Zn, As, Ti and other metals were dumped there from 1957 to 1990 [1].

In the frame of the NUREIEV project, five mooring lines equipped with sediment traps and current meters were deployed in the wider Gulf of Vera. Three of the moorings were located in the middle course of three submarine canyons, one in the open continental slope and one in the deep basin. The monitoring period lasted for an annual cycle (March 2015 - March 2016). Our research focused on (1) measuring the temporal variability of particle fluxes in the study area, and (2) determining the concentration of particulate trace metals and metalloids (Zn, Pb, As, Ni, Cd, Cu, Co) as well as other metals (Fe, Mn, Ti) in settling particles.

Preliminary results within the following project NUREIEVA indicate that marine storms are the main processes triggering the transfer of particulate matter to the deep margin, mainly through hundred meters thick nepheloid layers moving not only along the submarine canyons but also across the open slope. High metal fluxes after storms reached up to 120.4 mg Pb m^-2d^-1, 282.3 mg Zn m^-2d^-1 and 40.4 mg As m^-2d^-1 in the canyon stations, four orders of magnitude higher than calculated in open Ligurian Sea [2]. This suggests that submarine canyons are efficient pathways for the transfer of pollutants from the shelf to the deep margin and basin [3].

Peak metal concentrations found so far in the wider Gulf of Vera exceed those found in other canyons in the Mediterranean Sea [2, 4]. The hypothesis that this could be related to the release of metals from the mine tailings deposit in Portmán is plausible but would require further work to be confirmed, including determination of enrichment factors in each station, and discerning between Portmán’s and other potential metal sources.

[1] Oyarzun, R. et al., 2013. Sci. Total Environ. 454-455, 245-249.

[2] Heimbürger, L.E. et al., 2012. Chem. Geol. 291, 141-151.

[3] Canals, M. et al., 2013. Prog. Oceanogr. 118, 1-27.

[4] Palanques, A. et al., 2008. Mar. Geol. 248, 213-227.

How to cite: Tarrés, M., Cerdà-Domènech, M., Sanchez-Vidal, A., Pedrosa-Pàmies, R., Rumín-Caparrós, A., Calafat, A., and Canals, M.: Particle fluxes and trace metal dispersal in the Gulf of Vera, SW Mediterranean Sea, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-8914, https://doi.org/10.5194/egusphere-egu2020-8914, 2020.

In case of maritime pollution, man-overboard, or objects adrift at sea, national maritime authorities of the 9 countries bordering the European North West Continental Shelf (NWS) rely on drift model simulations in order to better understand the situation at stake and plan the best response strategy. So far, the drift forecast services are mainly managed at national levels with almost no integration at the transnational level. Designed as a support service to the national drift forecasting services, NOOS-Drift has the ambition to change this paradigm.   

NOOS-Drift is a distributed transnational multi-model ensemble system to assess and improve drift forecast accuracy in the European North West Continental Shelf. Developed as a one-stop-shop web service, the service allows registered users (national drift model operators or trained maritime authorities) to submit on-demand drift simulation requests to be run by all the national drift forecasting services connected to NOOS-Drift. Within 15 minutes after activation, the NOOS-Drift users shall get access to the drift simulation results of the individual ensemble members, as well as the results of a multi-models joint analysis assessing the ensemble spread and delineating risk areas to locate possible maritime pollution. This operation of such a distributed multi-models service is to our knowledge a world premiere. 

In this communication, we will present the technical and scientific developments that had to be done to make this service possible, including: 

1. a robust, secure and latency-free communication system that coordinates the execution of the different national models
2. a strategy to build the multi-model ensemble
3. a definition of drift forecast accuracy
4. the joint multi-model analysis tools
5. the standard file formats and visualisation means 

Finally we will illustrate on an example how the NOOS-Drift service could change the decision making process.

How to cite: Legrand, S., Dagestad, K.-F., Daniel, P., Kapel, M., and Orsi, S.: NOOS-Drift, an innovative operational transnational multi-model ensemble system to assess ocean drift forecast accuracy., EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-12653, https://doi.org/10.5194/egusphere-egu2020-12653, 2020.

The H2020 funded project ODYSSEA (http://odysseaplatform.eu/) aims to make Mediterranean marine data easily accessible and operational to a broad range of users of the marine space. ODYSSEA develops an interoperable and cost-effective platform, fully integrating networks of observing and forecasting systems across the Mediterranean basin, addressing both the open sea and the coastal zone. The platform integrates marine data from existing Earth Observing Systems, such as Copernicus and EMODnet, receives and processes novel, newly produced datasets (through high-resolution models and on-line sensors such as a novel microplastics sensor) from nine prototype Observatories established across the Mediterranean basin, and applies advanced algorithms to organise, homogenise and fuse the large quantities of data in order to provide to various end-user groups and stakeholders both primary data and on-demand derived data services.

The nine ODYSSEA Observatories are established across the whole Mediterranean basin, covering also areas of marine data gaps along the North African and Middle East coastline. The Observatories comprise observing and forecasting systems and cover coastal and shelf zone environments, Marine Protected Areas and areas with increased human pressure. The operational forecasting system of the Observatories consists of a ‘chain’ of dynamically coupled, high-resolution numerical models comprised of a) the hydrodynamic model Delft3D-FLOW, b) the wave model Delft3D-WAVE (SWAN), c) the water quality model DELWAQ, d) the oil spill fate and transport model MEDSLIK-II, e) the ecosystem model ECOPATH, and f) the in-house mussel farm model developed by the Democritus University of Thrace. This operational system provides forecasts, early warnings and alerts for currents, waves, water quality parameters, oil spill pollution and ecosystem status. In this work, the ODYSSEA forecasting system (developed with the Delft-FEWS software) is implemented for simulating oil spill pollution for the Thracian Sea Observatory.  The area is biodiversity rich and an important spawning and nursery ground for small pelagic species, while in Kavala Gulf, oil exploitation takes place. The Lagrangian oil spill model MEDSLIK-II has been coupled to high-resolution oceanographic fields (currents, temperature, Stokes drift velocity), produced by Delft3D-FLOW and SWAN, and NOAA GFS atmospheric forcing. The hydrodynamic and wave models have been configured for the Thracian Sea based on dynamic downscaling of CMEMS products to a grid resolution of 1/120°. Seasonal hazard maps (surface oil slick, beached oil) are produced employing multiple oil spill scenarios using multi-year hydrodynamics. The results highlight the hazard faced by Thracian Sea Observatory coasts. 

Acknowledgements: This research has received funding from the European Union’s Horizon 2020 research and innovation programme ODYSSEA: OPERATING A NETWORK OF INTEGRATED OBSERVATORY SYSTEMS IN THE MEDITERRANEAN SEA, GA No 72727.

How to cite: Spanoudaki, K., Kokkos, N., Zachopoulos, K., Sylaios, G., Kampanis, N., de Koning, D., Meszaros, L., Wanke, S., and El Serafy, G.: Monitoring and forecasting of marine pollution in the Mediterranean Sea: the ODYSSEA project approach, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-15191, https://doi.org/10.5194/egusphere-egu2020-15191, 2020.

Marine litter is one of the main threats for the marine environment, causing significant damage at ecological, economic and social levels. Approximately, 80% of the marine litter comes from land-based sources, mainly from rivers. A significant percentage of this litter reaches the open oceans and the rest are retained inside the estuaries. The mechanisms that favor the marine litter accumulation inside the estuaries are determined by the interactions between the tide, the river flow, the waves, and the wind, as well as by the physical features of the estuary. In addition, tides and waves can contribute to the introduction of litter from marine sources. Therefore, estuaries frequently act as sinks for marine litter. In this study, a methodology to identify the most probable areas of marine litter accumulation inside estuaries is developed. The methodology is based on numerical modeling and statistical analysis and consists of 4 fundamental steps. First, a series of metocean scenarios (tidal conditions, river flow, waves, and wind), statistically representative of the studied estuary, are identified using the clustering algorithm K-means. Second, these conditions are used as forcing and boundary conditions of a hydrodynamic model to obtain the high spatial resolution currents and waves that determine the transport of litter. Third, with these high-resolution drivers, a Lagrangian transport model is fed to generate a database of potential marine litter trajectories from different litter-sources, where each litter-source is carefully selected according to the activity developed in the area. Finally, the statistical analysis of these trajectories allows identifying the most probable areas of marine litter accumulation. The efficacy of this methodology is demonstrated by its application to the Pas estuary (northern coast of Spain) by comparing the numerical results with field data. Results show that the greatest accumulations of marine litter take place in the curves that imply important changes in the direction of the flow, where the probabilities range between 20 and 30%, and that the distance to the litter-sources also plays a fundamental role.

How to cite: Núñez, P., García, A., Abascal, A. J., Mazarrasa, I., Bárcena, J. F., Chiri, H., Rodriguez-Castillo, T., Juanes, J. A., and Medina, R.: Identification of marine litter accumulation areas in estuaries, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-5199, https://doi.org/10.5194/egusphere-egu2020-5199, 2020.

One of the largest last decade discoveries of hydrocarbons in the Eastern Mediterranean Sea is the Leviathan field, which constitutes a large-scale energy program of the State of Israel. Gas and condensate from the Leviathan well are transferred via pipeline to an offshore platform located ~10 km from the Israeli shoreline, and from there via a pipeline to the coastal Leviathan energy installation. The local communities are concerned from the pollution implications that might occur in case of spillage and/or any malfunction in regular operation.

The present work includes review of previous environmental studies regarding the Leviathan energy project 2007-2011, new extended simulations 2015-2018 for condensate, diesel and grey water leaks and resultant evaporation simulations caused by possible condensate spillage from the offshore platform and the pipe rupture.

In the framework of the current study concerning the Leviathan offshore platform, a robust statistics  is obtained by 5844 spill simulation runs for condensate and diesel against12 runs as mentioned in the previous studies, while for the pipe rupture a robust statistics was made with 104 runs for condensate and diesel compared to12 runs as performed previously.

The previous spillage scenarios from the offshore platform had underestimated by almost order of magnitude the content per design itself (1000bbls vs. ~6000bbls) and documentation of permits. Similarly, the pipe rupture spillage scenarios underestimated by almost half order of magnitude (1200bbls vs. ~3000bbls). Therefore, the current simulations predicted larger spillage quantities, compared to the aforementioned previous simulations.

The main conclusions driven from the 10km counter simulations for the offshore platform spillage show the following: First oil arrival at the Israeli coast from the offshore platform is predicted to be within 8 hours after start of spillage event in winter, and within 11 hours in summer.The first impacted area is predicted to be the coastline between Zichron-Ya'akov/Dor and Atlit. In winter on average, it is predicted that 17% of the spillage is beached, while in summer, twice as higher, i.e. up to 35%. Deposition of spilled condensate in the Hadera desalination plant is estimated to be the highest among the 5 desalination plants examined.

Similarly, the main conclusions driven from the 1km pipe rupture spillage counter show that the first impact on the Israel is predicted to be within 5-6 hours after start of spillage in winter, and within 3-4 hours in summer, with the worst case scenario occurring within half an hour after start of the spillage. The coastline of Zichron-Ya'akov is found to be an epicenter of the highest condensate deposition up to 15 tons/km, regardless the season. Due to the proximity of the pipe rupture to the shore, it is predicted that 38-40% of the condensate washed up the shore nearby, without any significant seasonal or monthly variability. The condensate spillage from the pipe rupture located 1 km from the shoreline will affect mostly the Atlit, Ma'agan-Michael and Caesarea National parks’ and the Hadera desalination plant coastlines.

How to cite: Zodiatis, G., Liubartseva, S., Loizides, L., Pellegatta, M., Coppini, G., Lardner, R., Kallos, G., Kalogeri, C., Bonarelli, R., Sepp Neves, A. A., Nikolaides, P., and Brillant, A.: Evaluation of the Leviathan offshore platform environmental studies in the Eastern Mediterranean Sea, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-5386, https://doi.org/10.5194/egusphere-egu2020-5386, 2020.