Urban groundwater quality assessment using pollution indicators and multivariate statistical tools: a case study in southeast Nigeria

ABSTRACT

In recent times, globally, it has been found that several natural and anthropogenic factors are responsible for the degradation and depreciation in quality and quantity of groundwater resources. This problem seems to be more pronounced in urban areas. In this paper, the groundwater quality of Nnewi and Awka urban areas in southeastern Nigeria was assessed using integrated pollution indices and multivariate statistics. pH scores showed that Awka has more of acidic waters than Nnewi. The level of heavy metals in the waters was assessed using heavy metal evaluation index, modified heavy metal index and modified heavy metal pollution index. These indices showed that most of the samples in Awka are polluted with heavy metals (such as Cu, Cd and Pb) whereas they indicated that most samples from Nnewi have low pollution. Similarly, ecological risk assessment was performed to clearly depict the possible impacts of the potentially toxic elements on the water environment. The result revealed that 55% of the total water samples across the two localities recorded low-moderate ecological risk while 45% recorded high-very high ecological risk. The priority pollutants identified by the numerical indicators are Cu, Pb and Cd. Correlation and factor analyses suggested that the associations between the analytes are attributable to both natural and anthropogenic factors. However, human activities seem to have played a higher role. Furthermore, pollution index of groundwater, synthetic pollution index and overall index of pollution were utilised to assess the suitability of the groundwater resources for drinking purpose. Their results appeared to be consistent with other models, indicating that the urban groundwater supply in Awka is posed with higher pollution threat than in Nnewi.

KEYWORDS:

• Urban drinking water
• groundwater quality assessment
• modified heavy metal index
• multivariate statistical analysis
• pollution indicators

Disclosure statement

No potential conflict of interest was reported by the author(s).