WaterSubject

Nearly 120 million tons of crude oil per annum are shipped through the Gulf of Suez to the SUMED terminal at Ain Sokhna, Egypt, with the vast majority trans-shipped to the West from the Mediterranean terminal at Sidi Kirir. Furthermore, about 85% of Egypt’s production of oil and gas are located in coastal waters. The production facilities in the Gulf of Suez yield 36 million tons of oil and gas annually. Offshore production in the Mediterranean is becoming an increasingly important activity. In total, some 8940 ship movements are recorded in Egypt’s ports. Although the main source of oil pollution in Egyptian waters is oil exploration and production, the high volume of transport traffic renders tanker accidents a serious and continuous threat.

Egyptian waters have been the site of a number of medium-sized spills including Al Duriyah in 1983, the Virgo in 1987, and the ESSO Picardie in 1989. A fuel spill from the Million Hope at the entrance of the Tiran strait in 1996 resulted in contamination of 7.5 km of coastline. Fifty tons of crude oil was also spilt in 1996 from the Kriti Sea into the Suez Canal, contaminating the shores of the Great Bitter Lake. A dispersant was applied in all the above cases, while additional containment and recovery, including shoreline cleanup, were required in the 1996 episodes.

The oil and gas industry is a major player in the Egyptian economy and recognizes that its activities can impact other vital fiscal sectors such as tourism. Unfortunately, information on the environmental impact of the above-mentioned spills was not well documented. Moreover, the response to oil spills in Egypt has been based on experience and personal judgement rather than a rational, scientific approach. In this work, the potential for implementing oil spill models in the Egyptian context to simulate oil trajectory and properties as a function of time was investigated. The expectation is that proper application of such a model will provide environmental, health, and safety units with the necessary technical information to respond more appropriately to an actual spill, and assist planners in prioritizing and coordinating resources as part of a contingency plan.

When oil is spilled at sea, it undergoes a number of physical and chemical changes, some of which will lead to its reduction in the water column, while others cause it to persist. These transformation processes are rate limited and a function of the amount of oil spilled, its initial physical and chemical characteristics, and the prevailing climatic and sea conditions. A mathematical model can incorporate all of this information and processes in order to predict the fate and transport of spilled oil under varying conditions. Using such models will facilitate planners’ ability to forecast the oil slick trajectory, the time until shoreline interaction, and the variation of oil properties with time.

It is estimated that over 50 oil spill models have been developed, but there are only a few that are extensively used in practice today such as ADIOS [National Oceanic and Atmospheric Administration (NOAA)], the S.L. ROSS model [S.L. Ross Environmental Research Ltd., Canada], OSIS [British Maritime Technology], and OILMAP [ASA Consulting Ltd]. The aforementioned models have been either experimentally validated and/or used in actual spill operations. None of these models has been used in specific applications in Egypt such as evaluating the impact of oil spills in environmentally sensitive areas.

The S.L. Ross model was available for use in this research. It predicts oil fate and transport using the basic oil characterization technique (American Society for Testing and Materials (ASTM) procedures) that involves weathering processes. Evaporation, spreading, natural dispersion into the water column, and the formation of water-in-oil emulsions are the most important weathering processes that determine the behaviour of oil spilled on water. These processes are interrelated and, therefore, coupled in the model formulation. The Ross model is as comprehensive and flexible as more expensive models for handling unique case variables such as spill sources and oil type; the major drawback is that it considers only two-dimensional versus three-dimensional dispersion. A model assumption of mixing depth related to the spill, however, provides a coarse estimate of vertical dispersion for the purpose of surface trajectory prediction. The model includes a module to predict the spreading of the area of the slick, A (m²), with time, t (s), assuming gravity-inertia, gravity-viscous, and surface tension-viscous phases.