Assessing groundwater pollution using advanced statistical techniques and pollution indices near a coal fly ash dump in parts of Oji-river, Nigeria.

Abstract

Advanced statistical methods (Pearson correlation matrix, principal component analysis, and hierarchical cluster analysis), pollution indices [pollution load index (PLI), contamination factor (CF), Nemerow integrated pollution index (NIPI), potential ecological risk index (PERi)], and regression model were utilized to evaluate groundwater quality around an abandoned coal fly ash disposal site. These methods can uncover hidden patterns and provide a more robust understanding of the pollution sources. Groundwater samples were collected and analyzed for physicochemical, heavy metals, and metallic elements using standard methods. The Pearson correlation matrix showed weak negative and strong positive correlation for groundwater samples. Strong positive correlations between groundwater and coal fly ash suggest similar anthropogenic associations and positive influence from CFA on groundwater resources. Hierarchical cluster analysis showed substantial similarities among elements. Principal component analysis showed a significant contribution with a positive correlation in PC1, PC2, and PC3. PLI values were > 1, which means the groundwater samples were polluted; CF showed moderate to significant pollution for Hg, Cd, Pb, Cu, and Fe, while As and zinc showed low contamination on groundwater samples. NIPI showed that 90% of samples had slight to serious pollution. The PERi result showed that Mg, Zn, Cu, and Hg posed low risk while Cd, Pb, and As posed moderate to very high risk. The relationship between PLI, NIPI, and PERi showed that PERi is significantly correlated with PLI and NIPI at < 0.5 significance level with a high positive correlation coefficient of 0.809 and 0.785, respectively, suggesting that similar sources of anthropogenic activities may have influenced the observed pollution level in the study area.