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:: Volume 20, Issue 6 (Iranian South Medical Journal 2018) ::
Iran South Med J 2018, 20(6): 584-594 Back to browse issues page
Modelling Spatial Variation of Arsenic Pollutant Using Empirical Bayesian Kriging in the Southern Part of Kerman Province
Maliheh Abbaszadeh 1
1- Department of Mining Engineering, University of Kashan, Kashan, Iran
Abstract:   (2864 Views)
Background: Arsenic is one of the elements that exist naturally in the earth crust. This element has several applications in the areas such as industrial, agricultural, medicinal. However, it could be seriously harmful because of its toxic effects on live organisms, including humans. Arsene could spread into the environment via two sources, including anthropogenic (produced directly by human activities) and natural (weathering and leaching from rocks and mineral layers of the earth and sedimentation) sources. This study investigates the probable sources of arsenic contaminations by producing the arsenic distribution map in the south of Kerman Province, Iran.
Materials and Methods: We studied an area of 5000 km2 in the south of Kerman Province. The results of assaying the 1804 stream sediment samples for arsenic contamination were used for spatially modeling. In other non-sampling areas, Empirical Bayesian Kriging (EBK) modeling was applied to assess the prediction of arsenic contamination.
Results: The level of arsenic concentration is more than the standard value (12 ppm) in the north-western part of the area. This contamination can cause several diseases such as cancer of the skin, bladder, and lung. It also could be a risk factor for diabetes and cardiovascular disorders. Therefore it is necessary to evaluate the prevalence of these diseases in the polluted areas.
Conclusion: Comparison of contaminated area map with the coordination of mineral deposits, mines, chemical industries and agricultural areas shows that the natural sources are more probable to be a source of this contamination compared to anthropogenic sources. The spatial modeling is produced based on the stream sediment samples, hence for the future studies, sampling from the soil, surface and underground water of the contaminated areas seems necessary.
Keywords: Geographical information systems, Bayesian kriging, uncertainty, Arsenic, contamination
Full-Text [PDF 1406 kb]   (939 Downloads)    
Type of Study: Original | Subject: General
Received: 2017/03/2 | Accepted: 2017/06/12 | Published: 2018/01/7
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Abbaszadeh M. Modelling Spatial Variation of Arsenic Pollutant Using Empirical Bayesian Kriging in the Southern Part of Kerman Province. Iran South Med J. 2018; 20 (6) :584-594
URL: http://ismj.bpums.ac.ir/article-1-909-en.html

Volume 20, Issue 6 (Iranian South Medical Journal 2018) Back to browse issues page
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