Application of multivariate statistical approach to identify heavy metal sources in sediment and waters: a case study in Yangzhong, China

2007 ◽  
Vol 54 (2) ◽  
pp. 373-380 ◽  
Author(s):  
Jian Zhou ◽  
Dongsheng Ma ◽  
Jiayong Pan ◽  
Wenming Nie ◽  
Kai Wu
Keyword(s):  
Heavy Metal ◽  
Statistical Approach ◽  
Multivariate Statistical ◽  
Metal Sources ◽  
Multivariate Statistical Approach ◽  
Heavy Metal Sources

Characteristics and evolution of hydrochemical compositions in groundwater under mining-induced disturbance: a case study

2015 ◽  
Vol 10 (3) ◽  
pp. 609-615
Author(s):  
Song Chen ◽  
Herong Gui
Keyword(s):  
Coal Mine ◽  
Statistical Approach ◽  
Chemical Compositions ◽  
Deep Groundwater ◽  
Multivariate Statistical ◽  
Carbonation Process ◽  
Groundwater Samples ◽  
Multivariate Statistical Approach ◽  
Quaternary Aquifers

To understand the hydrochemistry evolution characters of deep groundwater under the coal mine exploitation, 66 historical chemical data of groundwater samples were collected from 1997 to 2011 in Qinan coal mine, Anhui Province, China, the hydrochemical characteristics and its evolution characters were obtained by the methods such as multivariate statistical approach and conventional graphical. The results showed that the concentrations of Na+ + K+ are higher in all groundwater samples, whereas the contents of Ca2+ and Mg2+ are lower. The concentrations of Na+ + K+ were decreasing as follows: limestone aquifer < quaternary aquifers < coal bearing aquifer. The chemical compositions of groundwater collected from three aquifer were varied obviously from 1997 to 2011. Three principle component factors could be extracted through statistical approach, PC1 was affirmed the dissolution of limestone, dolomite and gypsum dissolution. PC2 could be as the carbonation process or desulfurizing process, while PC3 indicated the weathering process of feldspar minerals weathering by the carbonate acid.

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