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KMID : 1024520070160121451
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Journal of the Environmental Sciences
2007 Volume.16 No. 12 p.1451 ~ p.1462
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Statistical Assessment on the Heavy Metal Variation in the Soils around Abandoned Mine(Case Study for the Samgwang Mine)
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Cho Il-Hyoung
Chun Suk-Young
Chang Soon-Woong
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Abstract
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Heavy metal concentrations in the soil were investigated for the abandoned Samkwang metal mine, Cheongyang-Gun, Chungnam Province, Korea. The concentrations of heavy metal(As, Cd, Cu, Ni, Pb, Zn) were determined in mine soils collected at the abandoned mine sites to obtain a general classification and specification of the pollution in this highly polluted region. The results estimated with the normal test and basis statistic on the central tendency and variation showed that the distribution of heavy metal concentration had significantly different at the range of all locations. The range of spatial distribution on the relationship of heavy metal concentration and pH was and heavy metal concentration on the type of land use was highest in forest land, and also Ni and Zn in farm and rice field showed the high concentration. The distribution of heavy metal concentration on the depth of a soil showed that the metal concentrations in subsoil were higher than of those in surface soil, while the concentration of Cu and Ni had no significant difference on the depth of soil. Results from the correlation analysis using the data except the extreme and unusual data revel that Zn-Cd(r=0.867), Zn-As(r=0.797), Zn-Pb(r=0.764), Cu-Cd(r=0.673), Cu-As(r=0.614) and Zn-Ni(r=0.605) were the most important parameters in assessing variations of heavy metal in soil. To discriminate pattern differences and similarities among samples, principal factor analysis(PFA) and cluster analysis(CF) were performed using a correlation matrix. This study suggests that PFA and CF techniques are useful tools for identification of important heavy metal and parameters. This study presents the necessity and usefulness of multivariate statistical assessment of complex databases in order to get better information about the quality of soil and gives the basis information to clean up the abandoned mine sites.
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KEYWORD
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Heavy metal, Soil, Mine, Distribution, Correlation, Principal factor analysis(PFA), Cluster analysis(CF)
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