Multivariate and Statistical Approaches for the Source Apportionment and Evaluation of Trace Elements Pollution at Mining Areas (Case study: Mehdi Abad Pb/Zn mine)

Abstract

Mining activities are among the main sources of trace elements in the environment, which constitute a real concern worldwide, especially in developing countries. This study aimed to investigate the multivariate approaches such as Correlation Matrix and Hierarchical Cluster Analysis (HCA) for the identification of probable sources of trace elements in the deposited dust near the Mehdi Abad Pb/Zn mine located in Mehriz, Yazd province, as well as the evaluation of dust contamination based on the Geo-accumulation Index (I geo), Nemerow Pollution Index (PI Nemerow), Improved Nemerow Index (IN), and Combined Pollution Index (CPI). In addition, an anthropogenic index was used to determine the sources of the elements.  For this purpose, deposited dust was collected in nine sites using a marble dust collector (MDCO). Next, the chemical analysis of dust was determined using Inductively Coupled Plasma-Mass Spectrometry (ICP-MS). Statistics analysis was carried out using SPSS 22.0. The results showed that concentrations of zinc, thallium, silver, aluminium, arsenic, bismuth, calcium, cadmium, cerium, caesium, erbium, europium, gadolinium, hafnium, potassium, lutetium, manganese, sodium, phosphorus, antimony, scandium, and samarium in the deposited dust was higher than the background value. HCA identified two origins for the elements. The anthropogenic index confirmed the geogenic origin of elements in the deposited dust. Furthermore, CPI and PI Nemerow indices values showed that all sampling sites were in the heavily contaminated class. The results of IN Index showed that 56% of sampling sites were in the heavily contaminated class. The analysis of I geo, PI Nemerow, and IN indices showed that arsenic caused extreme contamination of the deposited dust at sampling sites.