Document Type : Original Research Paper

Authors

1 Mining Engineering Department, Federal University of Technology Akure, Nigeria

2 Rock Mechanics Lab, Mining Engineering Department, Federal University of Technology Akure, Nigeria

3 Geology Department, Department, Federal University of Technology Akure, Nigeria

4 Chemistry Department, Federal Polytechnic Ede, Nigeria

5 Department of Geosciences, Geotechnology and Materials Engineering for Resources, Graduate School of International Resource Sciences, Akita University, Japan

6 6. Department of Mining Engineering, Aksum University, Aksum, Tigray, Ethiopia

Abstract

Overburden material is typically removed in surface mining operations to expose the primary ore deposit. Because of the presence of trace minerals, environmental pollution and acid drainage are caused when the overburdened materials are removed from the mine site and transported to another location. In order to promote the economic and environmental sustainability of dolomite mining, the waste materials must therefore be evaluated for their environmental impact and potential industrial application. Akoko Edo Nigeria is known for its large production of dolomite and carbonate rock with large tonnage waste. The hydrogeochemical and geotechnical analysis of selected mine in this area is performed by randomly collecting and analyzing soil and water samples from four exploration drill holes using an atomic absorption spectrophotometer. The geotechnical analysis results show that dolomite waste soil is suitable for constriction material addictive such as road subgrade, dam design, highway, and other construction work. According to the study's findings, the mine water is slightly polluted, as measured by both the Overall Index of Pollution (OIP) and the Pollution Load Index (PLI). The chemical analysis of the mine pit water also reveal that the mean value of electrical conductivity, TDS, iron, manganese, copper, and lead all exceed the WHO and SON standards for a safe drinking water. A new pollution assessment model with suitable prediction correlation accuracy (R2= 0.76, mean average error = 0.27) is also developed in this work.

Keywords

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