Assessment of heavy metal pollution in groundwater and prediction of distance of tolerable health risks to a contiguous huge waste dump in a Nigerian City

Abstract

In this study, the heavy metal pollution of the groundwater contiguous to the largest waste dump site in Aba, Abia State Nigeria was investigated to determine the variation of health risks of exposure to the heavy metals with distance away from the waste dumpsite so as to generate regression models that could predict distance to the dumpsite of tolerable health risks. The concentration of the heavy metals in the groundwater was measured using atomic absorption spectrometry (AAS). Heavy metals of common pollution sources and their likely sources were determined using principal component analysis (PCA). The extent of heavy metal pollution of the groundwater was evaluated using heavy metal pollution index (HPI) and heavy metal evaluation index (HEI). The risk index (RI) and hazard index (HI) were employed in ascertaining carcinogenic and non-carcinogenic health risks respectively. The models for prediction of distances of tolerable health risks were generated using linear and polynomial regression models. Results indicate that the concentration of the heavy metals decreased with distance away from the waste dump site. Lead and cadmium had concentrations exceeding that of WHO standard at all the Boreholes at concentrations ranging from 0.03 to 1.94 mg/L for lead and 0.03 to 0.19 mg/L for cadmium. The PCA results indicate that copper and zinc had same source whereas nickel, chromium, lead and cadmium had same source with nickel and cadmium also showing an auxiliary same source. The HEI values (21 to 1401) indicate that some of the boreholes have groundwater of low heavy metal pollution whereas others are either of medium or high heavy metals pollution. The HPI values (275–4307) indicate that the groundwater for all boreholes is heavy metal polluted. The HI and RI values were significant across all boreholes and also significantly decrease with distance away from the dumpsite. The polynomial regression models were more robust in predicting the distance of tolerable health risks. Consequently, polynomial regression models as opposed to linear regression models may find utility in water quality management that is geared towards minimization of health risks.