SPATIAL DISTRIBUTION OF ARTISANAL GOLD MINING ON SOIL AND WATER QUALITY IN KATERIGI LOCAL GOVERNMENT OF NIGER STATE, NIGERIA
Journal: Environmental Contaminants Reviews (ECR)
Author: Bessie H., Mahmud A., Ishaya I.K., Sufiyan I.
This is an open access article distributed under the Creative Commons Attribution License CC BY 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited
Doi:10.26480/ecr.01.2023.17.23
ABSTRACT
The mineral resources of Niger State are largely underdeveloped and therefore are characterized by artisanal miners’ activities reportedly operate illegally and informally. Niger State is among many other States in Nigeria that has abundance of mineral resources such as; Tantalite, Baryte, Chalcopyrite, Iron ore, Cassiterite, Coal, Columbite, Clay, Limestone, Felspar, Lead, Silica Sand, Sphalerite, Marble, Bauxite, Granite and Gold. These solid minerals are found in each of the twenty five Local Government Areas (LGA’s) of the State. For instance, at Kataergi LGA is blessed with Gold, Coal and Baryte. In Niger state, mining of gold has being left in the hands of artisanal miners who do not have enough resources and adequate equipment, technology and education required for the mining activities. Minna and its environment as a major gold field are in the hands of artisanal miners particularly in Luku, Chanchaga Katerigi just to mention a few. ArcGIS 10.8 was used in mapping the soil and water quality parameters for interpolating the nitrate and other physicochemical concentration. Interpolation methods such as kiriging, spline, IDW and natural neighbor are analytical tools used in determining the heavy and low metal concentration. Inverse Distance Weighting (IDW) determines multivariate interpolation with a known scattered set of points. The result of the communalities shows that all the variables are well and completely fitted with the factor solution and none could possibly be dropped from the analysis. From the table 1-5, it can be deduced that 6.66% of the variance associated with the variable in (mg/g). Similarly, there was variance of 98.7%, 98.4%, 91.7%, 98.3%, 97.9%, 76%, 95.6% and 73.2% for heavy metals such as Ni, Cr, Pb, Cu, Zn, Cd, Mn, and Fe.
KEYWORDS
Mining, Spatial Distribution, Interpolation, Gold, Heavy/low Metals