Groundwater quality assessment using pollution index of groundwater (PIG), ecological risk index (ERI) and hierarchical cluster analysis (HCA): A case study

Egbueri, Johnbosco C.

doi:10.1016/j.gsd.2019.100292

Cited by 192 publications

(70 citation statements)

References 17 publications

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“…All over the world, the consumption (ingestion) of heavy metals-contaminated waters has been reported to cause serious health issues (disasters) like skin, lung, and bladder cancers; bronchiectasis; intellectual disabilities; neurological, cardiovascular, kidney, and bone diseases; hyperpigmentation of the palm and sole; hypertension; myocardial damage; liver damage; Bowens disease; diabetes, etc. (Rahman et al 2017;Sridharan and Nathan 2018;Mgbenu and Egbueri 2019;Ukah et al 2019;Egbueri 2019cEgbueri , 2020a.…”

Section: Introductionmentioning

confidence: 99%

Chemometric analysis for pollution source identification and human health risk assessment of water resources in Ojoto Province, southeast Nigeria

Egbueri

Mgbenu

2020

Appl Water Sci

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This paper quantified the level of heavy metals contamination, identified possible sources of pollution, and assessed the human health risks associated with drinking water resources in Ojoto Province, Nigeria. The study's gross findings revealed that the suitability of some water sources for consumption purposes in this province is questionable. Based on water quality index, 57.14% of the total samples are within acceptable limits, while 42.86% are unsuitable for drinking. It was observed that the northwestern and southern parts of the study area have more of deteriorated water quality. The health hazard index revealed that 25% of the samples predispose their consumers (both adult and children populations) to high chronic health risks. Moreover, heavy metal pollution index, contamination index, and probability of cancer risk (CR) revealed that about 25% of the total samples were unsuitable and off the CR standard acceptable range of ≤ 1 × 10 −6-1 × 10 −4. Correlation and component factor analyses linked the origin of major ions to geogenic processes and that of the heavy metals to both natural and anthropogenic processes. Cluster analysis divided the samples into two equal classes (50% each): poor and excellent quality waters. This study indicated that Pb is the priority pollutant impacting the water quality. The various assessments revealed that waters from hand-dug wells and deeper boreholes are the least contaminated and hence best suited for drinking than waters from springs, streams, and shallow wells.

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Section: Introductionmentioning

confidence: 99%

Chemometric analysis for pollution source identification and human health risk assessment of water resources in Ojoto Province, southeast Nigeria

Egbueri

Mgbenu

2020

Appl Water Sci

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“…So, employing the hydrogeochemical data into HCA is an incomparable approach. HCA simplifies data grouping assembled on similarities of the studied physicochemical parameters [59,60]. The FA and HCA were performed on 13 subsets of hydrogeochemical parameters.…”

Section: Hierarchical Clustering Analysismentioning

confidence: 99%

Quality reassessment using water quality indices and hydrochemistry of groundwater from the Basement Complex section of Kaduna Basin, NW Nigeria

2020

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Water quality indices allow for defining the acceptable limits for water usage. This paper evaluates the suitability of water for industrial and domestic uses. Hydrogeochemical data were derived from previous studies and exposed to an internal consistency test. Groundwater was classified using physicochemical parameters and water quality indices. Multivariate analysis (factor and clustering analyses) was applied to identify the sources of ions and classify groundwater. Similarly, regression analysis was used to model the hydrochemistry of the study area. Results indicated groundwater of varying quality based on hardness, TDS, EC, chloride, and nitrate. Groundwater classification based on the Chadha diagram revealed a Na-HCO 3 water type in the Kudenda-Nassarawa area. Kaduna South and Kakuri and its Environs have a Ca-Mg-Cl water type. Calcium, Mg, Na, and TDS constituted the major elements influencing the hydrochemistry of groundwater based on regression analysis. Factor analysis showed that aquifers are strongly influenced by rock weathering. Also, cluster analysis revealed different types of water sources based on their hydrogeochemical characteristics. The results of multivariate analysis concurred with Gibb's model. However, groundwater is unsuitable for industrial use since it is undersaturated with calcium carbonate. Thus, water treatment is required to avoid serious corrosion.

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“…The use of HCA in the hydrochemical analysis was confirmed to be logical by discerning hydrogeochemical data that behaves inversely. Using HCA, the sampling boreholes having similar hydrochemical properties were grouped into a separate cluster [19,20,37]. The graphics collections of the grouping process were offered as a dendrogram (Fig.…”

Section: Hierarchical Cluster Analysismentioning

confidence: 99%

Hydrogeochemical evaluation and mechanisms controlling groundwater in different geologic environments, Western Sokoto Basin, Northwestern Nigeria

2020

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The hydrogeochemistry of aquifers in the western Sokoto basin was assessed. The objective of this study is to identify the impact of geological variability on groundwater hydrochemistry and the mechanisms controlling the hydrochemistry of aquifers. Univariate statistics (several samples ANOVA), Pearson's (r), and multivariate statistics-hierarchical cluster analysis (HCA) and Factor analysis (FA) were used to interpret the hydrochemistry of aquifers. Subsequently, geochemical modeling was applied to assess the saturation index (SI) of rock minerals. Forty groundwater samples were collected from Gwandu (n = 20) and Illo (n = 20) formations. ANOVA results indicated that geological variability exerted a considerable impact on groundwater in Gwandu and Illo aquifers. It is characterized by a substantial amount of Ca 2+ , Mg 2+ , SO 4 2− , HCO 3 − , Na + , and K +. The hydrogeochemical facies indicated mixing conditions. FA and correlations analysis further revealed that groundwater received the noticeable influence of silicate weathering and dissolution of carbonates. There were significant differences in SI values for chrysotile, goethite, gypsum, H 2 (g), H 2 O(g), H 2 S(g), illite, and sepiolite minerals between the two geologic environments. Positive SI values for gibbsite were noticed in eleven sampling locations, indicative of potential recharge zones. Likewise, all the sampling locations have positive values for K-feldspar and are supersaturated with mica, suggesting both discharge and transition zones. The HCA classified aquifers into three clusters based on their hydrogeochemical characteristics. Geochemical modeling, univariate, and multivariate analyses are user-friendly tools for hydrochemical analysis.

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Groundwater quality assessment using pollution index of groundwater (PIG), ecological risk index (ERI) and hierarchical cluster analysis (HCA): A case study

Cited by 192 publications

References 17 publications

Chemometric analysis for pollution source identification and human health risk assessment of water resources in Ojoto Province, southeast Nigeria

Chemometric analysis for pollution source identification and human health risk assessment of water resources in Ojoto Province, southeast Nigeria

Quality reassessment using water quality indices and hydrochemistry of groundwater from the Basement Complex section of Kaduna Basin, NW Nigeria

Hydrogeochemical evaluation and mechanisms controlling groundwater in different geologic environments, Western Sokoto Basin, Northwestern Nigeria

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