Multivariate statistics and hydrogeochemical modeling for source identification of major elements and heavy metals in the groundwater of Qareh-Ziaeddin plain,NW Iran

The present study aims to evaluate the possible source of major and some minor elements and heavy metals in the groundwater of Qareh-Ziaeddin plain, NW Iran with respect to chemical elements, saturation index, and multivariate statistics including correlation coefficient, cluster analysis, and factor analysis. Groundwater samples were collected in Jun 2016 and measured with respect to EC, pH, major and some minor elements and heavy metals including Fe, Mn, Zn, Cr, Pb, Cd, Al, and As. Among all the measured parameters, some of the samples exceed the World Health Organization (WHO) guideline value for EC, Na, Mg, HCO₃, SO₄, Cl, NO₃, F, As, Zn, and Pb. The results of correlation analysis show that weathering and dissolution of minerals especially evaporites and silicates, water-rock interaction, and cation exchange are dominant occurred processes in the groundwater of the study area. Also, denitrification process is occurred in the groundwater system. Cluster analysis categorizes the samples into three distinct groups which are different based on their EC and dependent variables, e.g., Na, Ca, Cl, SO₄ and pH, Pb, Cd, and As. It can be found that volcanic, evaporite, and clay formations have the least impact on the chemistry of the cluster 1 samples while clay and evaporite formations have the highest impact on the cluster 3 and also calcareous formations on cluster 2. Factor analysis shows that five factors, with total variance of 83%, are effective in the release of heavy metals and groundwater chemistry which are mostly geogenic.     

The role of land use patterns in earthquake resilience: a case study of the Ahvaz Manba Ab neighborhood

Natural Hazards - Urban resilience to natural disasters has constantly been a challenge to sustainable development in human societies. Since Iran is always exposed to natural disasters such as...     

The efficiency of Penicillium commune for bioremoval of industrial oil

Among all environmental contaminations, industrial oil is one of the major pollutants of soil, water, and air. There are different chemical, physical, and biological methods to remove all types of oil pollutions. One of the common biological methods is to utilize the microorganisms like yeast, fungi or bacteria. Previous studies concerning the biodegradation of an aromatic compound in industrial waste water by Aspergillus niger have been reported. In this study, we tried to identify an oil-derived microorganism and evaluate its efficacy on self-removal of industrial oil. Firstly, the strain of isolated fungus from various bulks of used oil was defined via colonial identification and DNA sequencing. Secondly, bioremoval activity of defined fungus (Penicillium commune) was evaluated using gas chromatography–mass spectrometry. The optimum conditions in biological elimination of oil including the incubation time, pH level of culture, and amount of reagents were determined. In the best condition, a removal rate of 95.4 % was obtained.