Accumulation of heavy metals in sediment and oyster (Saccostrea cucullata) in the intertidal zone of Chabahar coast

In order to understand the extent of heavy metals contamination in sediments and rock oyster Saccostrea cucullata, of Chabahar intertidal zone, samples of sediment and oyster were collected from 5 different stations namely Guatr, Beris, Ramin, Shahid Beheshti and Tiss during low tide. Sediment and tissue samples were acid digested and heavy metals content of the samples were analyzed. Results showed that Cu, Pb and Ni concentration in the sediment samples was 15.87-16.96, 10.98-15.79 and 12.39-17.10 µg/g, respectively. Heavy metals concentration in soft tissues of oyster was 84.96-289.93, 3.83-5.26 and 6.05-7.19 µg/g for Cu, Pb and Ni, respectively. Similarly, Cu, Pb and Ni concentration in shell ranged between 13.83-6.67, 11.32-14.93 and 5.97-7.97 µg/g, respectively. No significant difference was found between Cu and Ni concentrations in sediment samples. It is suggested that metals accumulation in different oyster tissues was related to their essentiality for oyster. Heavy metals concentration in oyster and sediment was found to fall within the range of some available standards, indicating that metals contamination does not seems to be problematic in the area

Heavy metals (Hg, Cd, Pb and Cu) bioaccumulation in the oyster Crassostrea gigas of Imam Khomeini Port

Heavy metals are major group of dangerous contaminants in marine environment. Due to their persistence, they may enter aquatic food chains and transfer from one trophic level to another. They also may be harmful for human being which is placed at the top of the food chain. Imam Khomeini’s Port is located in the north west end of Persian Gulf and ships traffic and several industries especially petrochemical industries around of the port, discharge various organic and non-organic contaminants such as heavy metals into this ecosystem. In this study in order to investigate the levels of heavy metals (Hg, Cd, Pb and Cu) in soft tissue of oyster Crassostrea gigas from Imam Khomeini port, oysters of the same size were sampled on March 2010 from 5 different locations including harbors of Petroshimi, Doc Sorsoreh, 15, 28 and 33 in the Imam Khomeini port. The samples were freeze dried and acid digested in order to determine their heavy metal content with atomic absorption spectrophotometry. Results indicated that the content of Hg, Cd, Pb and Cu in the oysters’ soft tissue were 3.12±2.97, 7.56±3.62, 7.1±3.30 and 440.57±66.17 µg/g of dry weight, respectively. The highest level of Hg, Pb and Cu were recorded in harbor of Petroshimi while the highest level of Cd was measured in harbor no 15.The concentration of Hg, Cd, Cu and Pb in bivalve soft tissue was more than standard limits. This can be dangerous for public health therefore regular monitoring of heavy metals in the area is recommended

The evaluation of sea surface temperature and the relationship between SST and depth in the Persian Gulf by MODIS

Sea surface temperature (SST) is one of the most widely used parameters in studies pertaining to oceanography and the atmosphere. Water surface temperature changes from time to time and plays a significant role in waters and activities of atmospheric system, survival of marine creatures, sea currents, level of salinity and other conditions of sea and lake waters. In order to provide SST images over the Persian Gulf, the MODIS on board the Aqua Satellite was used. Applying lighting assessment out of images from Modis 21-Level 1B Calibrated Radiances -1km in Persian Gulf and the Bushehr sea station (Bouyeh) from global algorithm specified for above sensor was used to estimate the sea surface temperature. With function of Matlab software to extract data of satellite images, and GIS software to convert the matris obtained, the maps of sea surface temperature were used. 48 images taken in 2008, 2009, 2012, and 2013 were selected. Their correlation coefficient was 0.75, 0.86, and 0.75 respectively. Also, the coefficient of determination obtained was 0.86, 0.90, 0.94 and 0.86 respectively. Finally, taking the 31 band temperature into consideration for the years 2008, 2009, 2012, the temperature differences of bands 31 and 32, the sensor angle as independent factors and the Bouyeh temperature as the affiliated factor, the global algorithm coefficient for the Persian Gulf was calibrated through SPSS. In order to check the correctness of the suggested algorithm, the sea surface temperature was reexamined with satellite images from 2013 and the obtained correlation coefficients were 0.96 and 0.94. According to this study, apart from depth, other factors such as sea currents and latitude also have an effect on sea surface temperature. The amount of temperature change especially in the northern and central latitudes, have an inverse relation with depth

Validation of aerosol optical depth using AERONET ground stations in marine areas (Case Study: Persian Gulf)

Dust prediction such as prediction of wind and rain needs to synoptic information to the earth's surface, upper layers of the atmosphere, the prediction maps of land surface and upper levels as well as using radar and satellites. In the meantime, radar and satellite observations included remote sensing can be useful in prediction accuracy. The purpose of this study, use of remote sensing technology and MODIS images to estimate dust optical depth on the Persian Gulf surface and estimating the linear correlation relationship between the dust measurements in ground and atmospheric. The dust optical depth calculated using the code developed in MATLAB software. Evaluation of extracted data conducted using Pearson correlation coefficient, RMSE and RMSD index. In this study, optical depth obtained from image processing compared with the optical depths obtained from AERONET network. The evaluation results showed a high and significant correlation between the obtained optical depth and optical depths obtained from AERONET network (R 2 =0.99). The best and most suitable mode demonstrated for 1.243 and 1.632 bonds. At all stations, AOD value obtained from satellite image is bigger than AOD amount corresponding to the AERONET station and the algorithm used has overestimated. The cause of this more estimate can be use of limited particle's effective radius, because the scope of this effective radius is limited at the distribution of particle size in log-normal. Error resources at the retrieving particulate matter was defined such as sensor calibration error, pollution on the radiation angle, or poor predictor of water reflection