Multivariate statistical evaluation of trace elements in groundwater in a coastal area in Shenzhen, China.
Multivariate statistical techniques are efficient ways to display complex relationships among many objects. An attempt was made to study the data of trace elements in groundwater using multivariate statistical techniques such as principal component analysis (PCA), Q-mode factor analysis and cluster analysis. The original matrix consisted of 17 trace elements estimated from 55 groundwater samples colleted in 27 wells located in a coastal area in Shenzhen, China. PCA results show that trace elements of V, Cr, As, Mo, W, and U with greatest positive loadings typically occur as soluble oxyanions in oxidizing waters, while Mn and Co with greatest negative loadings are generally more soluble within oxygen depleted groundwater. Cluster analyses demonstrate that most groundwater samples collected from the same well in the study area during summer and winter still fall into the same group. This study also demonstrates the usefulness of multivariate statistical analysis in hydrochemical studies.
Chen
Kouping
K
Department of Earth Sciences, The University of Hong Kong, Hong Kong, China. kpchen@hkusua.hku.hk
Jiao
Jiu J
JJ
Huang
Jianmin
J
Huang
Runqiu
R
D000838:Anions / Q000032:analysis; D002681:China; D016000:Cluster Analysis; D004784:Environmental Monitoring / Q000379:methods; D005163:Factor Analysis, Statistical; D005618:Fresh Water / Q000032:analysis / Q000737:chemistry*; D010084:Oxidation-Reduction; D010100:Oxygen / Q000032:analysis; D025341:Principal Component Analysis / Q000379:methods; D012621:Seasons; D014131:Trace Elements / Q000032:analysis*; D014874:Water Pollutants, Chemical / Q000032:analysis*
D000838:Anions; D014131:Trace Elements; D014874:Water Pollutants, Chemical; D010100:Oxygen