Multivariate and geostatistical analysis of spatial distribution and potential sources of heavy metals in surface waters

Abstract

Although economic growth from industrialization has improved health and quality of life indicators, however, it has intensified the release of chemicals into the environment, with severe effects on health. The present work confers toxic metals contamination levels of surface waters in Zanjan Province, Iran, encompassing several rich mines of lead and zinc. The soluble concentrations of Fe, Cu, Cd, Ni, Pb, Zn and AS in water samples were determined using ICP-MS and the level of contamination was appraised by heavy metal pollution index (HPI). Multivariate statistical methods comprising Pearson’s correlation analysis, hierarchical cluster analysis, and principal component analysis were applied to evaluate the relationships between heavy metals. Geostatistical analyses were carried out to conduct the distribution characteristics and the sources of pollution. The results showed that concentrations of studied heavy metals were higher in the spring compared to the winter, however, the calculated HPI values did not exceed the limit of 15. Anthropogenic activities, for the most part, control the quality of water in this study area with minor natural/geogenic input. All the measured heavy metals were strongly homologous in spring based on correlation coefficients. However, this correlation gets weaker in the winter due to a degree of heterogeneity between Zn, Cd, As and other elements. Distribution pattern of the heavy metals pollution index of surface waters with different land uses decreased in the order of: agricultural>dry farming/water bodies>built up areas>forest areas. Multi hotspots for the above mentioned heavy metals were located in the southeast study areas.

Keywords

• water quality
• heavy metal pollution index
• geostatistics
• spatial distribution