TITLE:
Application of Principal Component Analysis, Cluster Analysis, Pollution Index and Geoaccumulation Index in Pollution Assessment with Heavy Metals from Gold Mining Operations, Tanzania
AUTHORS:
Caren Anatory Kahangwa
KEYWORDS:
Heavy Metals Contamination, Principal Component Analysis, Cluster Analysis, Pollution Index, Geoaccumulation Index
JOURNAL NAME:
Journal of Geoscience and Environment Protection,
Vol.10 No.4,
April
29,
2022
ABSTRACT: Gold mining is now widely acknowledged as one of the significant sources
of soil pollution in developed countries.
In developing countries, the sources and levels of soil contamination
have not been thoroughly addressed. Thus, this study was intended to determine
the source of soil pollution and the level of contamination in the active and
closed gold mining areas. The research paper presents the pollution load of
heavy metals (lead-Pb, chromium-Cr, cadmium-Cd, copper-Cu, arsenic-As,
manganese-Mn, and nickel-Ni) in 90 soil samples collected from the studied
sites. Multivariate statistical analysis, including Principal Component
Analysis (PCA) and Cluster Analysis (CA), coupled with correlation coefficient
analysis, was performed to determine the possible sources of pollution in the
study areas. The results indicated that Pb, Cr, Cu and Mn come from different
sources than Cd, As and Ni. The results obtained from the metal pollution
assessment using the Pollution Index (PI) and the Geoaccumulation Index (Igeo)
confirmed that soils in the mining areas were contaminated in the range from
moderately through strongly to highly contaminated soils. This study verified
that soil contamination in the gold mining
areas results from natural and anthropogenic processes. The current study findings would enhance our
knowledge regarding the soil contamination level in the mining areas and the
source of contamination. It is recommended to use PCA, CA, PI and Igeo to
assess and monitor the heavy metal contaminated soil in gold mining areas.