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Volume 4 Issue 4
Dec.  2016
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YU Kai-ning, LI Jian, LI Hui, et al. 2016: Statistical characteristics of heavy metals content in groundwater and their interrelationships in a certain antimony mine area. Journal of Groundwater Science and Engineering, 4(4): 284-292.
Citation: YU Kai-ning, LI Jian, LI Hui, et al. 2016: Statistical characteristics of heavy metals content in groundwater and their interrelationships in a certain antimony mine area. Journal of Groundwater Science and Engineering, 4(4): 284-292.

Statistical characteristics of heavy metals content in groundwater and their interrelationships in a certain antimony mine area

  • In recent years, most of domestic and foreign researches about heavy metal pollutions of metal mine mainly focus on water, soil and plants on the surface. There is lack of researches about heavy metal pollution in groundwater of metal mine. In this research, a certain antimony mine area is selected as a typical study area. Also, the study about statistical characteristics of heavy metals in groundwater has been carried out. Furthermore, the interrelationships have been preliminarily discussed through related analysis, such as relevant analysis, cluster analysis and principle component analysis. The results show that: the excessive elements in groundwater of study area are Sb, As, Pb, Se, and Ni. The average mass concentration of Sb, As, and Pb is higher than that of drinking water standards (GB5749-2006). The concentration of most heavy metals in dry season is lower than or equal to that in wet season for groundwater. Zn is the only metal in groundwater showing a different pattern, the concentration of which in dry season is higher than that in wet season. Under the impacts of stratum leaching and absorption effect, the concentration of heavy metals (except Pb and Ba) in groundwater are lower than or equal to that in surface water. As and Se, the two heavy metals have a significant positive correlation, which shows the two elements might have gone through similar environmental geochemical effect. Also, the connection among Zn, Hg, Pb, and Mn is not obvious; therefore, the sources of those elements are quite different. In addition, the elements of Se and As have obvious positive interrelationship with elements of CO32- and F-. Also, the Pb has significant positive correlation with PO43-, H2SiO3 and oxygen consumption. The results of cluster analysis show that 9 different heavy metals in the study area can be divided into 3 categories: Zn, Cd, Mn, Hg, Cu, and Cr belong to the first category, Se and As belong to the second one, and the last category is Pb. Also, the principle component analysis divides 6 heavy metals (Zn, As, Hg, Pb, Mn, and Se) into 4 different principle components, which can be utilized to assess heavy metals pollution situations in groundwater. The reliability of this method is higher than 91%. Moreover, the research provides theory basis and models for establishing evaluation index system and exploring the evaluation method of heavy mental pollution in groundwater.
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