Evaluation and measurement of chromium in sea water in order to remove it with mineral absorbent kaolin for desalination

Today, the use of heavy metals and chemical products industry expanded. The presence of significant amounts of, pollutants in industrial waste water can lead to serious risks to the environment and human health have heavy metals like chromium is one example of the future of salmon knock pond environment. Chromium is an essential element in the diet, but high doses of this element is very dangerous. Hence the use of chemical methods as a tool for the removal of metals from waste water pond be used. The aim of this study was to investigate the mineral kaolin adsorbents for the removal of chromium is water. Thus, the effect of different concentrations of absorbent micro amounts of chromium absorption and variable temperature, pH and electrolytes were studied. During the investigation of spectroscopic instrument (Varian) UV-VIS are used. Comparison of the absorption mechanism of chromium adsorption by the adsorbent with nano-absorbent kaolin kaolin was investigated. According to the studies done in the same conditions of temperature, pH and shaking rate of chromium absorption by nano kaolin kaolin is much more attractive. Therefore, its use as an adsorbent abundant, cheap, accessible, efficient and effective is proposed.

Three dimensional models of water flow in the Persian Gulf

Persian Gulf region is globally of great importance due to its economical and political reasons. The importance lies in oil sources and sea exports. Geophysical phenomena dominated in the water circulation affected this region is called Monsoon it stretches from African coasts to the half way of Red Seal affected all coasts of Persian Gulf and goes toward east to the Indian ocean. Other essential factors in the water circulation in this region are net evaporation (several meters in per year), high density and high salinity. In this article the effects of wind stress and evaporation in the water circulation in the region will be considered and model equations for wind forces, density, pressure, gradient, and bottom friction for Persian Gulf will be discussed.

Preparation of environmental monitoring plan pattern for surface water quality in Iran (Case study: Gharehsou River)

Using water quality management programs is a necessary and inevitable way for preservation and sustainable use of water resources. One of the important issues in determining the quality of water in rivers is designing effective quality control networks, so that the measured quality variables in these stations are, as far as possible, indicative of overall changes in water quality. One of the methods to achieve this goal is increasing the number of quality monitoring stations and sampling instances. Since this will dramatically increase the annual cost of monitoring, deciding on which stations and parameters are the most important ones, along with increasing the instances of sampling, in a way that shows maximum change in the system under study can affect the future decision-making processes for optimizing the efficacy of extant monitoring network, removing or adding new stations or parameters and decreasing or increasing sampling instances. This end, the efficiency of multivariate statistical procedures was studied in this thesis. Multivariate statistical procedure, with regard to its features, can be used as a practical and useful method in recognizing and analyzing rivers’ pollution and consequently in understanding, reasoning, controlling, and correct decision-making in water quality management. This research was carried out using multivariate statistical techniques for analyzing the quality of water and monitoring the variables affecting its quality in Gharasou river, in Ardabil province in northwest of Iran. During a year, 28 physical and chemical parameters were sampled in 11 stations. The results of these measurements were analyzed by multivariate procedures such as: Cluster Analysis (CA), Principal Component Analysis (PCA), Factor Analysis (FA), and Discriminant Analysis (DA). Based on the findings from cluster analysis, principal component analysis, and factor analysis the stations were divided into three groups of highly polluted (HP), moderately polluted (MP), and less polluted (LP) stations Thus, this study illustrates the usefulness of multivariate statistical techniques for analysis and interpretation of complex data sets, and in water quality assessment, identification of pollution sources/factors and understanding spatial variations in water quality for effective river water quality management. This study also shows the effectiveness of these techniques for getting better information about the water quality and design of monitoring network for effective management of water resources. Therefore, based on the results, Gharasou river water quality monitoring program was developed and presented.