Soil quality assessment using GIS-based chemometric approach and pollution indices: Nakhlak mining district, Central Iran

被引:31
|
作者
Moore, Farid [1 ]
Sheykhi, Vahideh [2 ]
Salari, Mohammad [1 ]
Bagheri, Adel [3 ]
机构
[1] Shiraz Univ, Shiraz, Fars, Iran
[2] Shiraz Univ, Fac Sci, Dept Earth Sci, Shiraz, Fars, Iran
[3] Islamic Azad Univ, Shiraz Branch, Shiraz, Fars, Iran
关键词
Integrated approach; Mining activity; Soil quality; Toxic metal; HEAVY-METALS; SEQUENTIAL EXTRACTION; GEOSTATISTICAL ANALYSES; URBAN SOILS; PART; AREA; LEAD; FRACTIONATION; CONTAMINATION; ENVIRONMENTS;
D O I
10.1007/s10661-016-5152-3
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
This paper is a comprehensive assessment of the quality of soil in the Nakhlak mining district in Central Iran with special reference to potentially toxic metals. In this regard, an integrated approach involving geostatistical, correlation matrix, pollution indices, and chemical fractionation measurement is used to evaluate selected potentially toxic metals in soil samples. The fractionation of metals indicated a relatively high variability. Some metals (Mo, Ag, and Pb) showed important enrichment in the bioavailable fractions (i.e., exchangeable and carbonate), whereas the residual fraction mostly comprised Sb and Cr. The Cd, Zn, Co, Ni, Mo, Cu, and As were retained in Fe-Mn oxide and oxidizable fractions, suggesting that they may be released to the environment by changes in physicochemical conditions. The spatial variability patterns of 11 soil heavy metals (Ag, As, Cd, Co, Cr, Cu, Mo, Ni, Pb, Sb, and Zn) were identified and mapped. The results demonstrated that Ag, As, Cd, Mo, Cu, Pb, Sb, and Zn pollution are associated with mineralized veins and mining operations in this area. Further environmental monitoring and remedial actions are required for management of soil heavy metals in the study area. The present study not only enhanced our knowledge regarding soil pollution in the study area but also introduced a better technique to analyze pollution indices by multivariate geostatistical methods.
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页数:16
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