Hydrogeochemical approach in the assessment of coastal aquifer for domestic, industrial, and agricultural utilities in Port Harcourt urban, Southern Nigeria

Eyankware, Moses Oghenenyoreme; Akakuru, Obinna Chigoziem; Ulakpa, Ruth Oghenerukevwe Eyankware; Eyankware, Emmanuel Oghenegare

doi:10.1007/s42108-022-00184-2

Cited by 26 publications

(5 citation statements)

References 39 publications

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“…This result agrees with the Nemerow pollution results but it is contrary to the result of the CF, PLI and MPI. Anthropogenic inputs could be responsible for the high levels of pollution seen in this study (Akakuru et al 2021a, b;Agidi 2022, Eyankware et al 2022a. The spatial distribution of Igeo within the region is presented in Fig.…”

Section: Geoaccumulation Index (Igeo)mentioning

confidence: 82%

“…Groundwater is a significant asset extremely pivotal for the supportability of human existence and the climate. It is trusted that around 65-75% of the earth's assets are water, access to quality water for drinking, homegrown and modern objects is restricted particularly in non-industrial nations (Eyankware et al 2022a;Akakuru et al 2022Groundwater has become a fundamental requirement of life as more than 1.5 billion people around the world rely on groundwater as their primary source of drinking water (He et al, 2019;Agidi et al,). 2022).…”

Section: Introductionmentioning

confidence: 99%

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Application of artificial neural network and multi-linear regression techniques in groundwater quality and health risk assessment around Egbema, Southeastern Nigeria

et al. 2023

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This paper examined the efficiency of artificial neural network (ANN) and multivariate linear regression (MLR) models in the prediction of groundwater quality parameters such as ecological risk index (ERI), pollution load index (PLI), metal pollution index (MPI), Nemerow pollution index (NPI), and geoaccumulation index (Igeo). 40 groundwater samples were collected systematically and analyzed for mainly heavy metals. Results revealed that adopting measured parameters is effective in modeling the parameters with high level of accuracy. Contamination factor results reveal that Ni, Zn, Pb, Cd, and Cu have relatively low values <1 within the region while the Iron values ranged from low contamination to very high contamination (>6). PLI, MPI, and ERI results indicated low pollution. NPI results indicated that the majority of the samples were heavily polluted. Quantification of Contamination results revealed that most of the sample's quality was geogenically influenced. Igeo results revealed that most of the samples had extreme pollution. The health risk assessment results revealed that children are substantially prone to more health risk more than adults. The ANN and MLR models showed a high effective tendency in the prediction of ERI, PLI, MPI, NPI and Igeo. Principal Component Analysis results showed appreciable variable loadings while the Correlation matrix results reveal that there exists weak and positive correlation amongst elements. Based on the outcome of this study, this research recommends the use of ANN and MLR models in the prediction of groundwater quality parameters as they yielded positive, reliable, acceptable, and appropriate accuracy performances.

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Section: Geoaccumulation Index (Igeo)mentioning

confidence: 82%

Section: Introductionmentioning

confidence: 99%

Application of artificial neural network and multi-linear regression techniques in groundwater quality and health risk assessment around Egbema, Southeastern Nigeria

et al. 2023

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“…4), Fe (798.32%) had the highest Coefficient of variation (CV), followed by Cd (747.33%), and finally Cd (95.65%). For the apportionment of heavy metal sources, famous researchers from around the world have successfully employed statistical analysis CV (Akaninyene et al, 2021;Wang et al, 2021;Eyankware et al, 2022). With the exception of Mn, Pb, Zn, Cr, and As, which ranged from 26.83%, 27.06%, 2.642%, 26.72%, and 26.77%, respectively, the conducted study showed that the CV of Cu, Fe, Cd, and Fe pollutants were above 60%.…”

Section: Statistical Analysis Results From Heavy Metalsmentioning

confidence: 99%

“…Furthermore, Nwankwor et al, (2016) noted that the rainy season lasts from mid-April to early-November and that July and October are the months with the heaviest rainfall. In the research area's temperature ranges from 26 to 28 °C and its characteristic vegetation is mangrove swamp forest; however, it has been significantly affected by human activities like exploration, logging, and farming (Eyankware et al, 2020, Eyankware et al, 2022. The coastal region of the Niger Delta has an average monthly wind speed pattern that varies between 0 and 3 m/s, with periods of lower and higher trends noted during the night and evening periods (Edokpa and Nwagara, 2017).…”

Section: Study Areamentioning

confidence: 99%

Evaluation of the Effects of Heavy Metals on Water From Illegal Crude Oil Refineries: A Case Study of Three Selected Communities in the Niger Delta Region, Nigeria

Eyankware,

Bariweni,

Eze

et al. 2023

Env.cont.Reviews

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In order to assess the levels of heavy metals and health concerns associated with the operations of illicit refineries in water, 15 surface water samples were taken from Okerenkoko, Peterou-Gbene, and Bille in the Niger Delta region of Nigeria. A number of heavy metal indices, including the Contamination Factor (Cf), Pollution Load Index (PLI), Modified Degree of Contamination (mCd), Ecological Risk Factor (Erf), and Geo Accumulation Index (Igeo), were successfully applied in the evaluation of heavy metal contamination in surface water using World Health Organization WHO (2011) and Nigerian Standard for Water Quality NSDWQ (2007) standards. Additional research from WHO and NSDWQ comparisons revealed that the majority of the investigated heavy metals were higher than permissble limits in comparison to the control site. Although the concentration of heavy metals in the aquatic habitats varies amongst the various communities in the area, according to the CV. Additionally, CV contends that there is a connection between the illicit refiners’ actions at the study site and the water chemistry changes that result in surface water contamination. According to data from the WHO and the NSDWQ, the majority of heavy metal concentration readings in the study sites exceeded the acceptable limits when compared to those in the control site. According to the results of heavy metals indices such as Cf and PLI, the surface water in the analyzed site ranges from very slightly contaminated to extremely contaminated. However, Erf and Igeo findings showed that human activities through illegal refiners increase heavy metal concentration, which results in a very high potential ecological risk associated with surface water. Additional mCd results demonstrated that in the studied sites, the surface water has a high degree of contamination. The findings suggest that surface water assessment is required to warn against a decline in water quality in the area.

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“…According to Eyankware et al (2022b), component loading in the PCA involved reducing a large dataset with numerous variables into a smaller number of linear combinations in the component that accounted for a significant portion of the total data variance and made it simple to connect the variables to their sources or processes via Equation (1).…”

Section: Discussionmentioning

confidence: 99%

Hydrochemical characteristics and a health risk assessment groundwater area of Warri and its adjoining environs, in Delta State Nigeria

Eyankware

Akakuru

Umayah

et al. 2022

Preprint

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In Warri, Delta State, Nigeria, 17 groundwater samples were collected and examined using the American Public Health Association (APHA) method. to evaluate the hydrochemical characteristics and health risks connected with using them as drinking water. For the assessment of the impact of heavy metal contamination in groundwater resources within the region, statistical index analysis using Principal Component Analysis (PCA) and Pearson correlation, heavy metal index such as Contamination Index (CI), Contamination Factor (Cf), Pollution Load Index (PLI), Metal Pollution Index (MPI), Quantification of Contamination (QoC), Potential Ecological Risk Index (ERI), and Pollution Index of Groundwater (PIG) were successfully applied. Additional findings from Pearson correlation and Principal Component Analysis (PCA) suggested that there is an interaction within the groundwater aquifer system and that there are weak to moderate relationships between parameters. PCA also suggests that loadings within the groundwater system may have resulted from anthropogenic activities in the area that are affecting the water chemistry. Results from hydrogeochemical facies showed that in the cation area, Na+K > Mg > Ca > Cl > SO4 > HCO3 with a tendency of 35.3 percent SO4 > 5.9 percent HCO3 > 41.2 percent Cl > 17.6 percent no dominant ionic specie. Findings from heavy metals indexes like Cf and PLI suggested that there is no connection between them and the groundwater that is readily available. Additional MPI results showed that the research area's groundwater is regarded as clean, whereas QoC and ERI findings showed that geological processes promote the transport of heavy metals, the possible ecological danger associated with groundwater. The HI for all indicators was higher in children than in adults, according to health risk data. This increasing HI in the studied area may be primarily due to anthropogenic sources. According to the findings, ongoing groundwater assessment is necessary to warn against a decline in groundwater quality in the research region.

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Hydrogeochemical approach in the assessment of coastal aquifer for domestic, industrial, and agricultural utilities in Port Harcourt urban, Southern Nigeria

Cited by 26 publications

References 39 publications

Application of artificial neural network and multi-linear regression techniques in groundwater quality and health risk assessment around Egbema, Southeastern Nigeria

Application of artificial neural network and multi-linear regression techniques in groundwater quality and health risk assessment around Egbema, Southeastern Nigeria

Evaluation of the Effects of Heavy Metals on Water From Illegal Crude Oil Refineries: A Case Study of Three Selected Communities in the Niger Delta Region, Nigeria

Hydrochemical characteristics and a health risk assessment groundwater area of Warri and its adjoining environs, in Delta State Nigeria

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