Spatial variability and risk assessment of potentially toxic elements in the effluent of Kumasi Abattoir [sbnd] Ghana

Abstract

Hypothesis-driven experiments have been conducted to explore the spatial variability and potential ecological risk indices (RIs) of potentially toxic elements (PTEs) in untreated in situ effluent continuously discharged downstream by the Kumasi Abattoir Ghana (KAG). The study focused on seven PTEs nickel (Ni), lead (Pb), cadmium (Cd), manganese (Mn), zinc (Zn), copper (Cu), and iron (Fe), based on these hypotheses: (i) Variations in PTE levels may be significant in the effluent; (ii) Comparative RI assessments based on the three background values natural background values (NBVs) for freshwater, maximum admissible concentrations (MACs), and reference values (RVs) provide objective evaluations; and (iii) PTEs’ cluster distances are linked to RIs. Effluent samples were randomly collected in quintuplicates from the drainage receptacle and analyzed using standard methods. The spatial variability of PTEs was investigated using divisive hierarchical cluster analysis (DHCA). The RIs and their uncertainties were computed using Hakanson's equations and standard deviation (SD). PTE dispersion was analyzed using the coefficient of variation (CV). Analysis of variance (ANOVA) was employed to test for the significance of hypotheses 1 and 2, complemented by Scheffé's post-hoc test where significance was detected. Hypothesis 3 was investigated by analyzing PTE cluster distances and RIs based on Pearson's correlation metric. The DHCA produced two clusters Cd–Cu–Mn–Ni and Zn-(Fe)-Pb. The CVs (< 50 %) indicated medium variability, relatively uniform spatial distributions, and minimal fluctuations. High to very high RIs ± SDs obtained were 300 ± 57.5 (MACs), 2900 ± 500 (RVs), and 7666 ± 2980 (NBVs). The ANOVA yielded significant results for both hypotheses, while moderate to high correlations were obtained for the third hypothesis. While RIs provided compelling evidence of inimical effluent, the study highlights the influence of background values on RIs. It further suggests that the PTE cluster distances may be used as surrogates for the RIs.