Three dimensional modeling of contaminants transportation (oil spill) in Caspian Sea

Nowadays, Caspian Sea is in focus of more attentions than past because of its individualistic as the biggest lake in the world and the existing of very large oil and gas resources within it. Very large scale of oil pollution caused by development of oil exploration and excavation activities not only make problem for coastal facilities but also make severe damage on environment. In the first stage of this research, the location and quality of oil resources in offshore and onshore have been determined and then affected depletion factors on oil spill such as evaporation, emulsification, dissolution, sedimentation and so on have been studied. In second stage, sea hydrodynamics model is offered and tested by determination of governing hydrodynamic equations on sea currents and on pollution transportation in sea surface and by finding out main parameters in these equations such as Coriolis, bottom friction, wind and etc. this model has been calculated by using cell vertex finite volume method in an unstructured mesh domain. According to checked model; sea currents of Caspian Sea in different seasons of the year have been determined and in final stage different scenarios of oil spill movement in Caspian sea on various conditions have been investigated by modeling of three dimensional oil spill movement on surface (affected by sea currents) and on depth (affected by buoyancy, drag and gravity forces) by applying main above mentioned depletion factors.

Seasonal variation of acetylcholinesterase, catalase, glutathione s transferase in different size of Pinctada radiata and metal pollution (Pb, Cd, Ni) in Persian Gulf

There are various tools for monitoring the concentration of pollutants on aquatic ecosystems. Today these studies are based on biological monitoring and biomarkers. The aim of this study was to measure the concentration of the acetylcholinesterase (AChE), glutathione S-transferase and catalase as biomarkers of heavy metal contamination in pearl oyster Pinctada radiata and their mechanism in aquatic ecosystems. Heavy metals lead, cadmium and nickel were measured in soft tissue and studied stations in four seasons. Samples were collected seasonally in Lavan stations, Hendurabi and Nakhilo (in the northern Persian Gulf) from spring 2013 to winter of that year by scuba diving. Pearl oysters are divided according to their shells size; shells separated from soft tissues and were transferred to the laboratory for analysis of heavy metals and enzymes. Moopam standard method for were used for measuring the concentration of heavy metals and for analyzing tissue concentrations of glutathione S-transferase in Clam the method recommended by Habig et al in 1974 were used. For measuring acetylcholinesterase Ellman method were used. Catalase contamination in pearl oyster in the supernatant obtained from the study based on the method homogeate soft tissue of mussels (Abei, 1974) was evaluated. The results showed that the concentration of lead has significant difference in sediments station, the concentration of lead in Lavan is significantly higher than the other two stations, This could be due to the movement of tanker, boats and floating refueling and with a considerable amount of wastewater containing oil and Petroleum into the water, and also due to precipitation and industrial discharges the lead in the region is increasing, land-disposed sewage sludge, has large concentrations of lead. Compare the results of this study with standards related and other similar studies at the regional and international level showed that pollutant concentration of heavy metals in all cases significantly less than all the standards and guide values associated. And also compared to other world research results have been far less than others, Being Less of the conclusion given in this research according that nickel is one of the indicators of oil pollution in the study area and emissions have been relatively low of oil. The concentration of acetylcholinesterase at several stations, in large and small sizes and in the seasons had no significant difference. Variations of catalase, and glutathione S-transferase were almost similar to each other and parameters, station and seasons were significantly different in the concentrations of these enzymes. The effects and interaction between various parameters indicate that following parameters has impact on the concentration of catalase and glutathione S-transferase. Stations; Seasonal changes in antioxidant enzymes related to (assuming a constant in salinity and oxygen) to age, reproductive cycle, availability of food and water temperature. With increasing temperature at warm season, antioxidant enzymes were increase, with increasing temperature and abundance of food in the environment the amount of antioxidant enzymes may increase. The presence of the enzyme concentration may indicate that the higher levels of the enzyme to eliminate ROS activities to be any healthier situation. At the time of gonads maturation and spawning season catalase activity increases. This study also indicates that catalase was significantly higher in the warm season. Due to low pollutants of heavy metals in the study area, a lower level of contaminants were observed in shellfish tissue incidents of international standards and strong correlation between the amount of heavy metal contamination in pearl oyster tissue and enzymes was not observed. Therefore, we can say that the pearl oyster remains in a healthy condition and the amount of enzyme is normal.

Oil spill environmental risk assessment of stationary sources in offshore zones (Innovating a mathematical model)

Nowadays, risks arising from the rapid development of oil and gas industries are significantly increasing. As a result, one of the main concerns of either industrial or environmental managers is the identification and assessment of such risks in order to develop and maintain appropriate proactive measures. Oil spill from stationary sources in offshore zones is one of the accidents resulting in several adverse impacts on marine ecosystems. Considering a site's current situation and relevant requirements and standards, risk assessment process is not only capable of recognizing the probable causes of accidents but also of estimating the probability of occurrence and the severity of consequences. In this way, results of risk assessment would help managers and decision makers create and employ proper control methods. Most of the represented models for risk assessment of oil spills are achieved on the basis of accurate data bases and analysis of historical data, but unfortunately such data bases are not accessible in most of the zones, especially in developing countries, or else they are newly established and not applicable yet. This issue reveals the necessity of using Expert Systems and Fuzzy Set Theory. By using such systems it will be possible to formulize the specialty and experience of several experts and specialists who have been working in petroliferous areas for several years. On the other hand, in developing countries often the damages to environment and environmental resources are not considered as risk assessment priorities and they are approximately under-estimated. For this reason, the proposed model in this research is specially addressing the environmental risk of oil spills from stationary sources in offshore zones.

Impacts of oil exploration and exploitation activities on marine environment

Iran possess huge oil reservoir and occupies second place in OPEC. Recent investigation has revealed that reservoir capacity in the country amount to 60 billion barrel of oil. Many measures has been carried out to increase production capacity of oil fields to 4.2 million barrel per day. Thus any distribution in oil exploration may leave adverse effects on social and economic activities. Unfortunately due to absence of a comprehensive CPM on environmental impact assessment, lots of environmental distribution has been occurred in land and off-shore. It is well known that implementation of EIA can reduce environmental hazards. In the present investigation, all major and minor activities associated with oil exploration is identified and subsequently their effects on physical, chemical and biological environment (aquatic) has been brought out. In this context, economical, social and cultural effects of marine oil exploration is also discussed. Subsequently, all methods of EIA were studied and best mitigation plans were drawn up both for exploitation and exploration phases.

Wind wave prediction in the Caspian Sea

In this thesis, wind wave prediction and analysis in the Southern Caspian Sea are surveyed. Because of very much importance and application of this matter in reducing vital and financial damages or marine activities, such as monitoring marine pollution, designing marine structure, shipping, fishing, offshore industry, tourism and etc, gave attention by some marine activities. In this study are used the Caspian Sea topography data that are extracted from the Caspian Sea Hydrography map of Iran Armed Forces Geographical Organization and the I 0 meter wind field data that are extracted from the transmitted GTS synoptic data of regional centers to Forecasting Center of Iran Meteorological Organization for wave prediction and is used the 20012 wave are recorded by the oil company's buoy that was located at distance 28 Kilometers from Neka shore for wave analysis. The results of this research are as follows: - Because of disagreement between the prediction results of SMB method in the Caspian sea and wave data of the Anzali and Neka buoys. The SMB method isn't able to Predict wave characteristics in the Southern Caspian Sea. - Because of good relativity agreement between the WAM model output in the Caspian Sea and wave data of the Anzali buoy. The WAM model is able to predict wave characteristics in the southern Caspian Sea with high relativity accuracy. The extreme wave height distribution function for fitting to the Southern Caspian Sea wave data is obtained by determining free parameters of Poisson-Gumbel function through moment method. These parameters are as below: A=2.41, B=0.33. The maximum relative error between the estimated 4-year return value of the Southern Caspian Sea significant wave height by above function with the wave data of Neka buoy is about %35. The 100-year return value of the Southern Caspian Sea significant height wave is about 4.97 meter. The maximum relative error between the estimated 4-year return value of the Southern Caspian Sea significant wave height by statistical model of peak over threshold with the wave data of Neka buoy is about %2.28. The parametric relation for fitting to the Southern Caspian Sea frequency spectra is obtained by determining free parameters of the Strekalov, Massel and Krylov etal_ multipeak spectra through mathematical method. These parameters are as below: A = 2.9 B=26.26, C=0.0016 m=0.19 and n=3.69. The maximum relative error between calculated free parameters of the Southern Caspian Sea multipeak spectrum with the proposed free parameters of double-peaked spectrum by Massel and Strekalov on the experimental data from the Caspian Sea is about 36.1 % in spectrum energetic part and is about 74M% in spectrum high frequency part. The peak over threshold waverose of the Southern Caspian Sea shows that maximum occurrence probability of wave height is relevant to waves with 2-2.5 meters wave fhe error sources in the statistical analysis are mainly due to: l) the missing wave data in 2 years duration through battery discharge of Neka buoy. 2) the deportation %15 of significant height annual mean in single year than long period average value that is caused by lack of adequate measurement on oceanic waves, and the error sources in the spectral analysis are mainly due to above- mentioned items and low accurate of the proposed free parameters of double-peaked spectrum on the experimental data from the Caspian Sea.

Coastal zone oil spill modeling

This work presents the development and application of a three-dimensional oil spill model for predicting the movement of an oil slick in the coastal waters of Singapore. In the model, the oil slick is divided into a number of small elements for simulating of the oil processes of spreading, advection, turbulent diffusion. This model is capable of predicting the horizontal movement of surface oil slick. Satellite images and field observations of oil slicks on the surface in the Singapore Straits are used to validate the newly developed model. Compared with the observations, the numerical results of the oil spill model show good conformity. In this study, the 3d model was generated using the geometrical data of Singapore Straits waters by GAMBIT which is a pre-processor of FLUENT programmed.