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Geochemical Background and Correlation Study
of Ground Water Quality in Ebocha-Obrikom of
Rivers State, Nigeria
1,2Morufu Olalekan Raimi, 2Abisoye Sunday Oyeyemi, 3Kalada Godson Mcfubara, 2Glory Tetn Richard,
4Iyingiala Austin-Asomeji and 5Adedoyin Oluwatoyin Omidiji
1Department of Environmental Management and Toxicology, Faculty of Sciences, Federal University Otuoke,
Bayelsa, Nigeria
2Department of Community Medicine, Faculty of Clinical Sciences, College of Medical Sciences, Niger Delta University,
Wilberforce Island, Bayelsa, Nigeria
3Department of Public Health Sciences, Faculty of Basic Medical Sciences, River State University, Nkpolu-Oroworukwo,
Port Harcourt, Rivers State, Nigeria
4Department of Community Medicine, Faculty of Clinical Sciences, College of Medical Sciences, Rivers State University,
Nkpolu-Oroworukwo, Port Harcourt, Rivers State, Nigeria
5Department of Geography and Environmental Management, Faculty of Social Sciences, Niger Delta University,
Wilberforce Island, Bayelsa, Nigeria
ABSTRACT
Background and Objective: Pollution in the Niger Delta has resulted in approximately nine million
premature deaths, accounting for 16% of global mortality, surpassing AIDS, TB and malaria combined.
Pollution-related illness claims one in four lives in the most affected nations. The objective is to determine
the relationship between the physicochemical and heavy metals parameters in groundwater in the study
area. Materials and Methods: Between September, 2019 and August, 2020, the sample was collected.
Standardized analytical procedures were used in the study. All sampling, conservation, transportation and
analysis were carried out in accordance with the 2018 APHA recommendations. To stop the deterioration
of the organic components, all obtained samples were transported to the research lab while being
preserved in an icebox. The significance level was set at p<0.05. Results: It shows that most of the
physicochemical indices and heavy metals are correlated significantly with each other during wet and dry
seasons. The sign (+) implies that as one parameter of the groundwater increases, the others increase
significantly and (-) shows the reverse is the case when one parameter of water increase increases, the
other parameters decrease significantly between each of the indices in Ebocha-Obrikom. All the findings
were statistically significant (p<0.001). Conclusion: Groundwater pollution is caused by irresponsible,
short-sighted and unsustainable exploitation of oil and gas resources. Evidence-based strategies are
needed to address pollution at the source and a linear regression analysis technique is an effective tool
for monitoring groundwater. Extensive monitoring is needed to track its development.
KEYWORDS
R eg r es sio n an a ly sis , co r re lat i on , ex tra c ti v e i ndu s tr y , N i ge r De lta environment, groundwater analysis, blocks
of sustainability
Copyright © 2023 Raimi et al. This is an open-access article distributed under the Creative Commons
Attribution License, which permits unrestricted use, distribution and reproduction in any medium, provided
the original work is properly cited.
ISSN: 2151-7908 (Online) Received: 6 Apr. 2023
ISSN: 1819-3579 (Print) Accepted: 4 Aug. 2023
https://doi.org/10.17311/tasr.2023.149.168 Published: 20 Oct. 2023
Page 149
Trends Appl. Sci. Res., 18 (1): 149-168, 2023
INTRODUCTION
Groundwater can become a vector of organic and inorganic contaminants, compromising the quality of
this precious resource and as a result, endangering local people’s living conditions. Groundwater can be
a constraint (dewatering) or an asset for the extractive industry in terms of quantity (meeting the needs
of the people). Using groundwater is undeniably important for meeting Sustainable Development Goals
(SDGs) and its targets in Nigeria’s Niger Delta Region. Access to safe drinking water for the population’s
health and comfort remains a challenge in the core Niger Delta. Development partners and other funders
from around the world work in developing nations to meet water needs through water access
programs1-14. Too often the importance of environmental geochemistry has become more important in
recent years as a means of distinguishing between man-made contamination and geogenic origins.
Previous research has shown that exposure to certain trace elements in drinking water has a negative
human health impact15-20. This is the case of exposure to several reports by different authors21-28. Thus,
human reliance on groundwater resources has increased dramatically in the last 50-60 years as a result
of climate change, rapid urbanization, agricultural development and intensification, food scarcity,
population growth and industrialization29-40, as well as cha nged consu mption pat terns pose a remark able
challenge and are contributing toward the rise in groundwater pollution, which has become a severe
environmental/public health concern in Rivers State’s Ebocha-Obrikom Area in recent years41- 50. Pollution
and a scarcity of surface water are two main causes contributing to the growing demand for groundwater
resources. As a result, the achievement of the goals of sustainable development is jeopardized1,4,5,10,12,38,42-45.
As a result of living in the Anthropocene, it is obligated to limit pollution, shut material loops and secure
the possibility of global economic activity within the planetary boundaries42,47,48,51-54. Citizens, in turn,
require access to infrastructure, information and motivational assistance to contribute positively to this
shift55-60. Groundwater is a significant source, accounting for almost 90% of available freshwater sources.
It is utilized for direct drinking in many places of the world and serves one-third of the world’s
population4,5,11,61-64. It meets roughly 67% of the world’s agricultural irrigation needs (food production),
22% fo r dom es ti c p urpo se s ( dr inki ng wa te r and sa ni tati on ) a nd around 33% of the water supply necessary
for industries14-20,61,62. Currently, around 34% of the world’s total annual water demand is fulfilled by
groundwater4-8,28,34,35,40-45,62-64. However, the contamination of the subsurface water has drawn 200 million
people across 28 nations into danger, making groundwater pollution a global issue21-23,28,31,33,34,41,43-45. The
prolonged carcinogenic exposure as well as non-carcinogenic pollutants even in trace amounts can
produce human health impacts (hypertension, carcinogenic risk, respiratory effects, skin lesions,
cardiovascular, diabetes and neurological issues, etc.) either individually or synergistically4-8,11,12,38,65,66. The
risk of groundwater pollution is highly noticeable in as well as around gas flaring industrial regions posing
a hazard to human health as well as a healthy ecosystem. Thus, groundwater plays an essential role in
society by influencing people’s lifestyles, health and habits and is an essential part of socialization. This
seems to be an essential supply for a variety of activities including domestic requirements, drinking,
agriculture, industrial, as well as ot he r u ses. Fo r t he pa st fe w decades, groundwater has been used to meet
human water needs4-8,11,12,38,45. It is a crucial asset for the country economic prosperity, particularly in
Nigeria’s oil-rich Niger Delta Area. Groundwater quality has become one of humanity’s primary concerns
since, it is directly related to human well-being and the use of this groundwater contaminated with trace
metals may present public and environmental health risks in the oil-rich Niger Delta Region of Nigeria,
depending on the contamination status. While a large part of the population in Ebocha-Obrikom Area of
Rivers State has no access to tap water, drilled wells as well as rivers constitute the only main water
sources for drinking and domestic use for that population4-8,11,12,34,38,43,45. As a result, it was critica l to asse ss
the physical and chemical pollution condition of groundwater in Nigeria’s oil-rich Niger Delta Region.
Strikingly, assessing groundwater quality in terms of its physical and chemical qualities is critical before
ingestion. As a result, the goal of this work was to examine, in light of the key trends, the link between the
physicochemical and heavy metals in the study area in order to determine whether the water is safe for
drinking as well as domestic use. This research is significant since groundwater in Nigeria’s oil-rich Niger
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Trends Appl. Sci. Res., 18 (1): 149-168, 2023
Delta area is mostly utilized for irrigation as well as residential purposes and the consequence of
groundwater pollution on environmental and human health has not been explored deeply and
comprehensively. As a result of the occurrence of high heavy metal concentrations in the study area’s
g ro u nd w ate r , t h e cu r ren t st u dy she d s l i gh t on t h e r e lat i on s hi p between physicochemical and heavy metals
in the study area.
MATERIALS AND METHODS
Study area (Niger Delta-Ebocha-Obrikom geology): In this study, 34 samples of phreatic water were
collected from nine sampling sites at the point-of-use between September, 2019 to August, 2020, the
Niger Delta Basin is one of Nigeria’s seven sedimentary basins. It is regarded as the most re markable du e
to its petroliferous character and as a result, intensive hydrocarbon exploration as well as production
operations that take place both on land and in the sea. The Agbada, Akata and Benin formations are the
three main subgroups of the Niger Delta Basin. The highest level is the Benin formation, including
significant volumes of non-sea sand, mostly sandstone, as well as gravel deposits1,6,67-71. Hydrocarbons are
present in trace levels in the formation6,68-72. The Agbada Formation is located under the Benin Formation
and above the Akata Formation. Reservoir rocks and seals are included in the formation6,69-72. The Akata
Formation, which lies near the bottom, is approximately 7000 m thick and is composed of clay as well as
shale. The formation is rich in organic materials and is thought to be the primary source of hydrocarbons
in the research region1,4-8. The Ebocha-Obrikom Region sits inside Nigeria’s oil and gas hub, one of the
large st settlements in the Niger Delta, situated in Rivers State between latitudes 5°20N-5°27N and
6°40E-6°46E. The Ogba/Egbema/Ndoni area of Rivers State is where the Towns of Obie, Obor, Ebocha,
Obrikom and Agip New Base are all located. The River Nkissa runs through the study research region to
the North, the River Orashi to the West, the River Sombrero to the East and Omoku town to the South.
C ha n ge s in w a te r bod i es , bui l t- u p a r ea s , m ang r ov e ve g et ati o n d e pletion along river and stream shorelines,
vegetation, as well as wetlands are all examples of significant changes in land use/land cover in the area.
According to the Nigerian Meteorological Agency, the annual rainfall ranges from 2100 mm to 4600 mm
and the average temperature is between 30.0 and 33.0°C4,5. Likewise, because of the existence of
businesses that release harmful oxides into the sky, it is situa te d in a tr opi cal we t en vir onm ent wit h l eng thy
and intense rainy seasons, making the rainwater unsafe for drinking. the combined hydrological effects
of Batholomew and Santa Barbara Rivers in the South, the River Sombriero in the East and the Rivers
Orashi and Santa Barbara in the North, as well, as Southwest, considerably influence the overall drainage
pattern.
Field sample collection: The current investigation employed a sample allusion to that used by
Olalekan et al.38, Raimi et al.4 and Raimi et al.5, sampling in a densely populated environment was
concentrated in sensitive locations. These areas are still being polluted not only as a result of their location
but also due to the ongoing exploration and production of crude oil. taken from the sample location’s
groundwater sources, which are primarily used for drinking and residential uses (Table 1). Both
groundwater via dug wells or shallow pumping wells primarily designed for domestic usage was tested.
The wells are 10 to 28 m deep, demonstrating that they are located in a phreatic aquifer. The sampling
sites was recorded using portable GPS devices. For the objectives of this investigation, groundwater
sources in the vicinity of the facility were picked at random but at various distances from each other. Also,
after approximately 20 min of continuous water flow, for ground water (boreholes and wells), samples
were physically taken at nine key points across the study region and placed in previously cleaned, plastic
sampling bottles to ensure adequate aquifer quality that can be appropriately represented.
Groundwater samples remained collected from wells as well as boreholes at each of the nine locations
once a month. All of the samples were collected during the day, from 9:00 am to 4:00 pm. As a result of
instability, floods and the COVID-19 shutdown. Night samples wer e no t ta k en and t he sam p li ng t o ok pla c e
between September, 2019 to August, 2020. The depth varied between 10 and 28 m.
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Table 1: Geographical coordinates of the nine sampling sites (samples)
S/N Locations Altitude (m) Latitude Longitude
Site 1 (Borehole) Opposite Ijeoma Quarters. 10 Lat N05°27'068" Long E006°41'480"
750 m away from Agip Gas Flaring Center Ebocha
Site 2 (Borehole) 200 m Opposite Agip Gas Flaring - Lat N05°27'28.7" Long E006°41'58.1"
Centre Ebocha and 50 m from Agip Waste Pit
Site 3 (Well) The Apple Hotel 500 m from waste pit and 16 Lat N05°27'37.5" Long E006°42'05.3"
150 m away from Mgbede field oil well 7 Ebocha
Site 4 (Well) 1000 m away from the Agip Flare Stack Ebocha 22 Lat N05°26'51.5" Long E006°41'38.8"
Site 5 (Borehole) Abacha Road Obrikom, - Lat N05°23'48.6" Long E006°40'36.8"
800 m away from Agip gas plant
Site 6 (Borehole) Eagle Base Obor, 2,500 m away from Agip gas plant 28 Lat N05°23'00.9" Long E006°41'07.4"
Sites 7 (Well) Obor Road Obie, 2000 m away from Agip gas plant 24 Lat N05°23'22.5" Long E006°40'49.1"
Sites 8 (Borehole) Green River Plant Propagation 17 Lat N05°24'18.9" Long E006°40'55.0"
Centre Naoc 3000 m away from Agip gas plant
Sites 9 35,000 m from Ebocha - Lat N5°4'58.1412" Long E6°39' 30.4806"
Sampling, preservation and analysis: Water sampling, conservation, transportation and analysis followed
the usual protocols indicated in Olalekan et al.38, Raimi et al.4, Raimi et al.5 and American Public Health
Association (APHA)73. Temperature, pH, Electrical Conductivity (EC), Dissolved Oxygen (DO), Total
Dissolved Substance (TDS), turbidity and Total Dissolved Solids (TDS) were all measured in the field using
the HANNA water quality checker73.
Ground water collection: Ground water samples were collected in pre-rinsed 1 L plastic containers for
analysis of physicochemical characteristics. Prior to storage, “pre-rinsed water groundwater samples for
heavy metal analyses were collected with nitric acid in 1 L containers and treated with 2 mL nitric acid
(assaying 100%, Trace Metal Grade, Fisher Scientific)”. This was done to maintain the oxidation conditions
of the metals steady. Two sets of 250 mL glass-stoppered reagent bottles were used to collect
groundwater samples at each sampling location for the Biological Oxygen Demand (BOD) and Dissolved
Oxygen (DO) tests. The bottles were sealed in black polythene bags after the BOD samples were carefully
filled without trapping air. This was done to eliminate the presence of light in the samples, which can
cause autotrophs to produce DO (algae). Before being added to two millilitres of each sample, the BOD
samples were grown for five days. Winkler solutions I and II use a variety of dropping pipettes to slow
down extra biological activity “in each sample, the bottles were ca re fu ll y s ha ke n t o pr ec ip it at e t he f lo c t ha t
was at the bottom of the bottles. Winkler solution I is a manganese sulphate solution, whereas Winkler
so lution II is a com binati on of so dium or potassiu m iodid e, sodium or potassium hydroxide, sodium azide
(sodium nitride), with sodium hydroxide”.
The DO samples were collected in transparent bottles with tight-fitting stoppers. Winkler I and II were
used to preserve dissolved oxygen samples on the spot, which is comparable to that of the samples of
BOD73. All samples had been meticulously identified as well as maintained at 4°C for easy identification.
Electrical Conductivity (EC), Total Dissolved Solids (TDS), Alkalinity (Alka), pH, as well as temperature were
measured on-site to estimate the amounts of unstable as well as sensitive water quality indicators
(Temperature). As a result, Fig. 1. displayed the primary approaches for determining the composition of
groundwater.
Quality Assurance and Quality Control (QA/QC): Importantly, all analytical procedures were
meticulously monitored utilizing high-purity analytical reagents and solvents, as well as quality assurance
and control techniques. Calibration standards were used to calibrate the equipment. The use of process
blanks, triplicate analysis and the inspection of certified reference materials were all part of the analytical
technique validation (CRM). Each organic contaminants limit of detection (LoD), repeatability, precision,
reproducibility and accuracy in groundwater samples were measured.
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Fig. 1: A diagram depicting the quantification methods used in the current investigation
Statistical analysis: Inferential and descriptive data were analyzed using SPSS version 27
(IBM incorporation, USA). Mean was compared using a One-way Analysis of Variance (ANOVA) followed
by the Duncan’s Multiple Range Test (DMRT). The significance level was set at p<0.05.
RESULTS
Nature and strength of the bivariate relationship between any of the physio-chemical parameters during
rainy and dry seasons as shown in Table 2 and 3. The result reveals that temperature has a significant
positive relationship with pH. Also, the result recorded that conductivity has a significant positive
relationship with pH. Similarly, the result shows that DO have a positive relationship with Temperature and
pH. The results of the bivariate relationship also revealed that BOD has a significant positive relationship
with temperature, pH and DO. The COD shows a significant negative relationship with temperature, pH,
DO and BOD. Temperature, pH, DO, BOD. Acidity shows a significant positive relationship with
Temperature, pH, DO, BOD and significant negative relationship with COD. Alkalinity shows a significant
n eg a ti v e re l at i on s hip w it h Tem p er a tur e , p H , D O an d BO D an d Ac i dity but a significant positive relationship
wi th C OD. Tem perature, pH, DO, BOD , Ac idi ty, COD . For H ard nes s, it was positive and significantly related
to pH, conductivity, DO, BOD and Acidity, but significantly negatively related with COD and Alkalinity.
A dd i ti o nal l y, t he r esu l t r e vea l ed t hat T DS h as a si g nif i ca n t po s it i ve r e la t io n shi p wi t h pH , Co n duc t iv i ty, B OD ,
Acidity, Hardness, but significantly negatively related with Turbidity and COD. The TSS also show a
significant negative relationship with Temperature, pH, DO, Acidity, TDS, but significantly positive related
with COD and Alkalinity. Also, salinity has a significantly positive relationship with Turbidity. The result of
the bivariate relationship also reveals that chloride has a significant positive relationship with COD,
Alkalinity, TSS but significant negative relationship with Temperature, DO, Acidity. Fluoride shows a
significant negative relationship with pH, Chloride but significantly positive a relationship with Alkalinity.
Results indicate that Aluminum has a significant negative relationship with conductivity, DO, Hardness,
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Ebocha-Obrikom oil and gas field
Collection of groundwater sample
Analysis of physico-chemical and heavy metal parameters
Laboratory analysis Field analysis Statistical analysis
Correlation
Trends Appl. Sci. Res., 18 (1): 149-168, 2023
TDS but significant positive relationship with Turbidity, Alkalinity, TSS. Salinity and fluoride. Sodium
showed a significant negative relationship with Temperature, DO, Acidity but a significant positive
relationship with COD, Alkalinity, TSS, Chloride, Fluoride, Aluminum. Potassium showed a significant
positive relationship with BOD, Hardness, TDS, TSS, Chloride, Sodium but significant negative relationship
with Temperature. Similarly, the results show that calcium has a significant negative relationship with
temperature, pH, DO, BOD, Acidity, Hardness, TDS, but significant positive relationship with Turbidity,
COD, Alkalinity, TSS, Salinity, Chloride, Aluminum, Sodium. Iron was found to have significant positive
relationship with Salinity, Fluoride, Aluminum and Turbidity. While magnesium showed a significant
positive relationship with Temperature, DO, BOD, COD, Acidity, Hardness, TDS but significant negative
relationship with Alkalinity, TSS, Chloride, Sodium and Calcium. The result indicates that Zinc has a
significant positive relationship with Temperature, pH, DO, BOD, Acidity, Hardness, TDS, Magnesium but
significant negative relationship with COD, Alkalinity, TSS, Chloride, Sodium, Calcium. Additionally, the
results reveal that manganese has a significant positive relationship with Temperature, pH, DO, BOD,
Acidity, Hardness, TDS, Calcium, Magnesium, Zinc but a significant negative relationship with COD,
Alkalinity, TSS, Chloride, Sodium. Also, the result recorded that Cadmium has a significant positive
relationship with Temperature, pH, DO, BOD, Acidity, Hardness, Magnesium, Iron, Zinc, Manganese but
recorded a significant negative relationship with COD, Alkalinity, TSS, Chloride and Calcium. Similarly, the
result shows that lead has a significant negative relationship with Temperature, pH, DO, BOD, Acidity,
Hardness, TDS, Magnesium, Zinc, Manganese, Cadmium, but a significant positive relationship with COD,
Alkalinity, TSS, Chloride, Aluminum, Sodium, Calcium. While copper showed a significant direct positive
relationship with Temperature, pH, DO, BOD, Acidity, Hardness, TDS, Magnesium, Zinc, Manganese,
Cadmium but had a significant negative relationship with COD, Alkalinity, TSS, Chloride, Sodium, Calcium,
Lead. Result indicates that Chromium has a significant positive relationship with Temperature, pH, DO,
BOD, Acidity, Hardness, TDS, Magnesium, Iron, Zinc, Manganese, Cadmium, Copper and significant
negative relationship with COD, Alkalinity, TSS, Chloride, Sodium, Calcium, Lead. There was a significant
positive relationship between sulphate and Temperature, pH, DO, BOD, Acidity, Magnesium, Iron, Zinc,
Manganese, Cadmium, Copper, Chromium. While sulphate was a negatively significant relationship with
COD, Alkalinity, TSS, Chloride, Sodium, Calcium, Lead. Ammonia revealed significant positive relationship
with Temperature, pH, DO, BOD, Acidity, Hardness, TDS, Magnesium, Zinc, Manganese, Cadmium, Copper,
Chromium, Sulphate and significant negative relationship with COD, Alkalinity, TSS, Chloride, Sodium,
Calcium, Lead. Additionally, results indicate that phosphorus has a significantly positive relationship with
Temperature, pH, DO, BOD, Acidity, Hardness, TDS, Magnesium, Zinc, Manganese, Cadmium, Copper,
Chromium, Sulphate, Ammonia. While it shows a significant negative relationship with COD, Alkalinity, TSS,
Chloride, Sodium, Calcium, Lead. Similarly, the result shows that Nitrite has a positive relationship with
Temperature, pH, DO, BOD, Acidity, Hardness, TDS, Magnesium, Zinc, Manganese, Cadmium, Copper,
Chromium, Sulphate, Ammonia, Phosphate, but a significant negative relationship with COD, Alkalinity,
TSS, Chloride, Sodium, Calcium, Lead. The result of the bivariate relationship also reveals that Nitrate has
a significant positive association with Temperature, pH, Turbidity, DO, BOD, Acidity, Hardness, Salinity,
Magnesium, Zinc, Manganese, Cadmium, Copper, Chromium, Sulphate, Ammonia, Phosphate, Nitrite, but
a significant negative relationship with COD, Alkalinity, TSS, Fluoride, Sodium, Calcium, Lead. Nickel
showed a significant positive relationship with Temperature, pH, DO, BOD, Acidity, Magnesium, Zinc,
Manganese, Cadmium, Copper, Chromium, Sulphate, Ammonia, Phosphate, Nitrite, Nitrate but a
significant negative relationship with COD, Alkalinity, TSS, Chloride, Sodium, Calcium, Lead. Lastly, TPH
shows a significant, positive relationship with Temperature, DO, Chloride, Sulphate, Ammonia, Nitrate, but
shows a significant negative relationship with only Alkalinity and Fluoride.
Thus, the principal pollutants’ impacts on human health were diagrammatically depicted in Fig. 2.
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Table 2: Correlation between physicochemical and heavy metals f or wet seaso ns
Correlations (rainy season)
-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
1 2 3 4 5 6 7 8 9 101112 1314151617 1819 20 212223 24 25 2627282930 31323334
1. Temp 1
2. pH 0.350** 1
3. Conduct. -0.143 0.336** 1
4. Turbidity 0.073 0.100 -0.188 1
5. DO 0.553** 0.393** 0.063 0.190 1
6. BOD 0.289* 0.340** 0.106 -0.098 0.399** 1
7. COD -0.449** -0.258* 0.016 0.128 -0.569** -0.462** 1
8. Acidity 0.582** 0.392** -0.012 0.026 0.683** 0.459** -0.806** 1
9. Alkalinity -0.380** -0.406** -0.038 -0.130 -0.660** -0.297* 0.488** -0.740** 1
10. Hardness 0.054 0.382** 0.386** -0.015 0.421** 0.610** -0.347** 0.353** -0.450** 1
11. TDS 0.023 0.267* 0.479** -0.281* 0.212 0.405** -0.310* 0.358** -0.227 0.542** 1
12. TSS -0.361** -0.368** 0.039 0.162 -0.443** -0.220 0.651** -0.725** 0.632** -0.244 -0.314* 1
13. Salinity 0.061 -0.058 -0.101 0.711** 0.106 0.034 -0.032 0.123 -0.065 0.095 -0.101 0.051 1
14. Chloride -0.281* -0.093 0.149 0.092 -0.336** -0.233 0.709** -0.590** 0.258* -0.077 -0.137 0.445** -0.108 1
15. Flouride -0.010 -0.282* -0.145 0.061 -0.218 0.137 -0.177 -0.044 0.302* -0.221 -0.198 0.240 0.223 -0.249* 1
16. Al -0.042 -0.170 -0.367** 0.546** -0.263* -0.003 0.092 -0.139 0.273* -0.256* -0.398** 0.383** 0.484** -0.080 0.679** 1
17. Na -0.427** -0.233 0.089 0.050 -0.541** -0.091 0.442** -0.587** 0.668** -0.116 -0.194 0.507** 0.159 0.356** 0.400** 0.464** 1
18. K -0.250* -0.207 0.194 0.189 -0.028 0.326** 0.105 -0.070 0.027 0.450** 0.393** 0.327** 0.246 0.283* 0.172 0.229 0.310* 1
19. Ca -0.361** -0.326** -0.132 0.378** -0.563** -0.500** 0.766** -0.748** 0.601** -0.359** -0.432** 0.667** 0.279* 0.579** 0.130 0.450** 0.620** 0.208 1
20. Mg 0.350** 0.218 0.162 -0.024 0.582** 0.490** -0.667** 0.821** -0.603** 0.463** 0.476** -0.517** 0.168 -0.571** -0.020 -0.141 -0.444** 0.160 -0.672** 1
21. Fe 0.149 0.113 -0.149 0.535** 0.166 0.084 -0.051 0.121 -0.020 -0.124 -0.095 0.093 0.487** -0.234 0.463** 0.564** 0.124 0.118 0.172 0.153 1
22. Zn 0.497** 0.517** 0.156 0.095 0.688** 0.502** -0.582** 0.822** -0.768** 0.572** 0.440** -0.620** 0.166 -0.250* -0.180 -0.177 -0.398** 0.152 -0.549** 0.696** 0.119 1
23. Mn 0.417** 0.252* 0.013 -0.139 0.529** 0.612** -0.564** 0.687** -0.538** 0.336** 0.438** -0.550** -0.016 -0.361** 0.003 -0.169 -0.434** 0.147 -0.604** 0.631** 0.161 0.669** 1
24. Cd 0.386** 0.391** -0.045 -0.037 0.512** 0.469** -0.518** 0.531** -0.343** 0.310* 0.241 -0.477** 0.201 -0.559** 0.097 -0.035 -0.157 -0.140 -0.441** 0.452** 0.262* 0.542** 0.549** 1
25. Pb -0.417** -0.329** 0.080 0.063 -0.656** -0.448** 0.573** -0.748** 0.676** -0.293* -0.369** 0.662** 0.059 0.415** 0.169 0.266* 0.610** 0.055 0.680** -0.658** -0.151 -0.661** -0.825** -0.499** 1
26. Cu 0.514** 0.368** 0.019 -0.129 0.564** 0.520** -0.763** 0.848** -0.633** 0.264* 0.460** -0.689** 0.034 -0.518** 0.062 -0.170 -0.540** -0.067 -0.733** 0.701** 0.070 0.700** 0.722** 0.568** -0.730** 1
27. Cr 0.360** 0.248* -0.155 0.037 0.431** 0.593** -0.516** 0.590** -0.395** 0.376** 0.425** -0.422** 0.230 -0.473** 0.114 0.054 -0.280* 0.205 -0.418** 0.577** 0.267* 0.619** 0.629** 0.615** -0.577** 0.618** 1
28. Sulphate 0.567** 0.425** -0.090 0.183 0.700** 0.286* -0.456** 0.582** -0.460** 0.144 0.027 -0.362** 0.152 -0.323** 0.029 -0.025 -0.539** -0.117 -0.417** 0.413** 0.361** 0.505** 0.464** 0.480** -0.496** 0.535** 0.358** 1
29. NH30.555** 0.446** 0.111 0.002 0.724** 0.634** -0.608** 0.768** -0.617** 0.476** 0.450** -0.533** 0.048 -0.249* -0.039 -0.164 -0.434** 0.159 -0.605** 0.650** 0.222 0.851** 0.775** 0.569** -0.736** 0.744** 0.639** 0.687** 1
30. PO40.441** 0.510** 0.163 -0.117 0.545** 0.587** -0.618** 0.733** -0.487** 0.421** 0.558** -0.680** 0.038 -0.522** -0.010 -0.179 -0.318* 0.017 -0.644** 0.701** 0.155 0.686** 0.694** 0.701** -0.662** 0.785** 0.705** 0.512** 0.720** 1
31. Nitrite 0.590** 0.436** 0.150 0.132 0.801** 0.521** -0.700** 0.850** -0.701** 0.465** 0.402** -0.537** 0.184 -0.348** -0.036 -0.118 -0.501** 0.159 -0.633** 0.735** 0.180 0.856** 0.687** 0.502** -0.692** 0.753** 0.599** 0.656** 0.876** 0.665** 1
32. Nitrate 0.600** 0.484** -0.011 0.261* 0.748** 0.394** -0.426** 0.679** -0.643** 0.367** 0.173 -0.437** 0.252* -0.104 -0.301* -0.217 -0.547** 0.012 -0.382** 0.496** 0.094 0.775** 0.484** 0.428** -0.551** 0.573** 0.489** 0.695** 0.745** 0.469** 0.796** 1
33. Nickel 0.501** 0.285* -0.004 0.068 0.569** 0.360** -0.587** 0.670** -0.536** 0.218 0.108 -0.473** 0.115 -0.485** -0.004 -0.130 -0.503** -0.156 -0.545** 0.569** 0.073 0.603** 0.475** 0.541** -0.493** 0.666** 0.536** 0.549** 0.585** 0.617** 0.580** 0.593** 1
34. TPH 0.332** 0.193 0.141 0.170 0.306* 0.161 0.208 0.036 -0.273* 0.133 -0.010 0.103 0.080 0.400** -0.271* -0.209 -0.197 0.007 -0.057 0.031 -0.124 0.230 0.034 0.074 -0.053 0.107 -0.045 0.275* 0.298* 0.011 0.235 0.419** 0.162 1
**Correlation is significant at the 0.01 level (2-tailed) and *Correlation is significant at the 0.05 level (2-tailed)
Trends Appl. Sci. Res., 18 (1): 149-168, 2023
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Table 3: Correlation between physicochemical and heavy metals f or dry seasons
Correlations (dry season)
------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
12 3 4 5 6 7 8 9 101112 1314151617 181920 2122 23 24 25 262728293031323334
1. Temp 1
2. pH 0.056 1
3. Conduct. 0.017 0.110 1
4. Turbidity -0.038 0.051 0.158 1
5. DO 0.515** 0.165 0.251 0.315* 1
6. BOD -0.163 0.290 0.141 -0.141 -0.245 1
7. COD -0.254 0.186 0.167 0.083 -0.069 0.140 1
8. Acidity 0.323* 0.067 -0.070 0.168 0.332* 0.102 -0.055 1
9. Alkalinity -0.002 -0.134 0.056 0.141 0.156 0.020 0.129 0.084 1
10. Hardness -0.327* 0.381** 0.411** -0.015 -0.307* 0.802** 0.290 -0.175 0.012 1
11. TDS -0.453** 0.130 0.305* 0.178 -0.148 0.474** 0.257 0.139 0.153 0.636** 1
12. TSS -0.084 0.382** 0.410** 0.071 -0.009 0.796** 0.178 0.091 0.234 0.818** 0.556** 1
13. Salinity -0.024 0.014 0.222 0.282 0.363* -0.194 -0.134 0.162 0.045 -0.042 0.336* 0.066 1
14. Chloride -0.059 0.282 0.410** 0.001 -0.036 0.280 0.339* -0.111 -0.203 0.554** 0.520** 0.232 0.157 1
15. Flouride -0.219 -0.163 -0.103 0.157 -0.379* 0.389** -0.054 0.128 0.040 0.367* 0.426** 0.338* -0.085 -0.104 1
16. Al -0.320* -0.162 0.079 0.492** -0.159 0.182 0.085 0.227 0.267 0.161 0.293 0.245 -0.027 -0.309* 0.612** 1
17. Na -0.377* -0.019 0.048 -0.054 -0.363* 0.650** 0.356* -0.211 0.231 0.654** 0.550** 0.488** 0.038 0.412** 0.321* 0.189 1
18. K -0.500** 0.206 0.371* 0.140 -0.188 0.567** 0.348* -0.005 0.033 0.771** 0.952** 0.618** 0.295* 0.583** 0.391** 0.246 0.642** 1
19. Ca 0.046 -0.092 0.469** 0.274 0.040 0.084 0.276 0.034 0.479** 0.315* 0.424** 0.296* 0.261 0.332* 0.308* 0.286 0.353* 0.361* 1
20. Mg -0.683** 0.079 0.145 0.071 -0.408** 0.145 0.192 -0.096 -0.375* 0.352* 0.604** 0.045 0.226 0.309* 0.283 0.264 0.212 0.642** -0.005 1
21. Fe 0.133 0.062 0.064 0.248 0.342* 0.026 -0.221 0.382** 0.022 -0.130 0.232 0.123 0.160 -0.164 0.317* 0.438** -0.084 0.106 0.114 0.024 1
22. Zn 0.226 0.285 0.440** 0.333* 0.248 0.203 0.224 0.076 -0.201 0.367* 0.285 0.301* 0.180 0.532** 0.102 0.085 0.160 0.344* 0.338* 0.070 0.250 1
23. Mn -0.225 0.278 0.434** 0.163 0.092 0.485** 0.326* 0.246 -0.151 0.550** 0.777** 0.508** 0.295* 0.505** 0.226 0.172 0.387** 0.824** 0.223 0.596** 0.238 0.389** 1
24. Cd 0.139 0.033 0.098 0.255 0.386** 0.215 0.252 0.261 0.629** 0.053 -0.036 0.359* 0.088 -0.391** 0.090 0.423** 0.214 -0.018 0.323* -0.360* 0.154 0.003 0.026 1
25. Pb 0.005 -0.124 0.151 -0.021 -0.075 -0.109 -0.016 0.047 -0.180 -0.058 0.060 0.083 0.478** 0.091 -0.111 -0.121 0.115 0.040 0.054 0.052 -0.005 0.063 0.080 -0.132 1
26. Cu 0.005 0.206 0.058 -0.006 0.043 0.441** 0.153 0.038 0.276 0.321* 0.187 0.263 -0.208 0.140 -0.030 0.106 0.460** 0.269 0.047 0.006 0.080 0.085 0.278 0.393** -0.367* 1
27. Cr -0.132 0.353* 0.340* 0.078 -0.079 0.805** 0.217 0.141 0.304* 0.820** 0.497** 0.882** -0.091 0.165 0.455** 0.372* 0.505** 0.581** 0.348* 0.095 0.079 0.240 0.480** 0.451** -0.210 0.429** 1
28. Sulphate 0.665** 0.077 -0.014 0.165 0.678** -0.319* -0.095 0.295* 0.017 -0.449** -0.267 -0.121 0.096 -0.175 -0.304* -0.193 -0.478** -0.341* 0.016 -0.516** 0.343* 0.157 -0.063 0.244 -0.030 -0.062 -0.254 1
29. NH30.261 0.247 0.256 0.139 0.364* 0.480** -0.034 0.309* -0.018 0.423** 0.486** 0.566** 0.217 0.401** 0.120 -0.065 0.263 0.475** 0.282 -0.117 0.344* 0.484** 0.486** 0.160 0.022 0.254 0.405** 0.442** 1
30. PO4-0.006 0.136 0.040 0.085 0.087 0.494** -0.017 0.403** 0.470** 0.272 0.116 0.593** -0.129 -0.432** 0.387** 0.490** 0.144 0.098 0.125 -0.191 0.324* -0.099 0.112 0.698** -0.166 0.350* 0.682** -0.007 0.196 1
31. Nitrite -0.043 0.243 0.419** 0.362* 0.388** -0.076 0.301* 0.138 -0.301* 0.165 0.427** 0.086 0.526** 0.490** -0.065 0.023 -0.005 0.461** 0.207 0.395** 0.197 0.574** 0.529** -0.036 0.231 -0.055 -0.047 0.239 0.419** -0.318* 1
32. Nitrate 0.450** 0.150 0.582** 0.332* 0.655** -0.169 -0.004 0.182 -0.041 0.025 0.103 0.156 0.514** 0.292 -0.171 -0.143 -0.258 0.098 0.468** -0.140 0.204 0.520** 0.256 0.182 0.166 -0.112 0.028 0.577** 0.545** -0.074 0.658** 1
33. Nickel 0.242 0.130 0.043 0.051 0.213 -0.075 -0.051 0.163 -0.354* -0.089 -0.131 0.063 0.210 0.036 -0.145 -0.107 -0.252 -0.110 -0.144 -0.057 0.133 0.169 -0.014 -0.002 0.356* -0.218 -0.129 0.372* 0.224 -0.021 0.302* 0.341*1
34. TPH 0.230 -0.061 0.140 0.394** 0.588** -0.246 0.249 0.217 0.261 -0.195 0.134 -0.070 0.466** 0.165 -0.124 0.028 0.103 0.086 0.461** -0.228 0.210 0.286 0.111 0.437** 0.183 0.068 -0.150 0.511** 0.411** -0.111 0.606** 0.614** 0.205 1
**Correlation is significant at the 0.01 level (2-tailed) and *Correlation is significant at the 0.05 level (2-tailed)
Trends Appl. Sci. Res., 18 (1): 149-168, 2023
Fig. 2: Main effects of contaminants on human health, indicating the organs or systems affected and the
contaminants causing them
Adapted from Raimi et al.4 and Raimi et al.105
DISCUSSION
The correlation matrix (CM) is known in water chemistry as a popular and helpful statistical technique to
know the positive and negative association of ions. A positive strong connection might imply the same
sources of certain ions, which can be natural or anthropogenic in origin, whereas, a weak correlation shows
that the sources of ions are independent of each other73- 76. Thus, the correlation between and across
different location sources contributes to the groundwater quality of the Ebocha-Obrikom Area of Rivers
State. The groundwater in the studied region is largely used for drinking as well as domestic uses by the
residents. As a result, due consideration should be paid to determining its fitness for human consumption.
Table 2 and 3 showed the concentrations of physicochemical characteristics in groundwater samples from
the research region. The correlation matrix was utilized to assess the interdependence of thirty-four
groundwater characteristic s. The corre lation coefficient table demonstrates that the majority of the
https://doi.org/10.17311/tasr.2023.149.168 | Page 157
Lead, manganese, mercury, tin, PBDEs, PAHs and PCBs
Neurodevelopmental impairment, reduction of intelligence
quotient, behavioural disorder Parkinson-type syndrome and
headache
BTEX, lead, PFAS and PCBs
Altered immune response and reduction response to vaccines
in children
Cadmium, PCBs and PBDEs
Altered metabolism and reproductive hormone level, reduced
thyroid hormones and altered growth
Benzene, lead, mercury, organochlorine
pesticides, PAHs, PFAs, PCBs and microplastics
Hypertension, haemolysis, anaemia, cardiovascular disease,
elevated leukocytosis count and leukaemia
Arsenic, asbestos, cadmium, chromium, copper, mercury
and radon
Pulmonary emphysema, asthma, chemical pneumonia, lung
cancer and mesothelioma
Nitrogen and ionizing radiation
Stomach cancer
Pahthalates and PCBs
Altered insulin metabolism and adipogenesis and diabetes
DDT, chromium, copper, mercury, PAHs, PCBs, PFAS and
phthalates
Increased cholesterol level, liver cancer, elevated hepatic
enzyme level and necrosis
Cadmium, lead, mercury, PAHs and PFAS
Renal tubular dysfunction, kidney weight changes, progressive
nephropathy, chronic inflammation and kidney cancer
Arsenic, copper, lead, mercury, tin, microplastics and POPs
Nausea, vomiting, diarrhea, cancer of gastrointestinal system,
abdominal pain and cramping
Arsenic and lead
Cancer of urinary bladder and urinary changes
Antimony, asbestos, lead, manganese, phthalates, PBDEs,
PCBs and PFAS
Testicular atrophy, early menopause, reduced testosterone,
reproductive alterations, decreased libido, impotence, sexual
dysfunction, endometriosis, hormonal cancers (breast,
prostate, testes), infertility and ovary cancer
Cadmium, lead, PCBs, radium and its decay products
Impaired bones development, slow growth, changes in
metabolism of calcium and bone formation, osteomalacia and
bone cancer
Arsenic, chromium, PAHs and PCBs
Hyperkeratosis, hyperpigmentation, hypopigmentation, skin
irritation and inflammation, chloracne, hirsutism, skin, tooth
and nail abnormalities
Brain
Lymph
nodes
Thyroid
Heart and
cardiovascular
system
Lungs
Stomach
Pancreas
Liver
Kidneys
Intestine
Bladder
Reproductive
system
Bones
and joints
Skin
Trends Appl. Sci. Res., 18 (1): 149-168, 2023
investigated factors strongly correlate with each other at the 1% (p<0.01) and 5% (p<0.05) levels. Positive
correlations at p<0.01 and p<0.05 identified between the majority of the examined heavy metals (HMs)
imply that these metals were deposited in the same atmosphere or came from comparable lithogenic
sources40. There is a positive correlation between conductivity with pH, indicating that a rise in
temperatu re, as well as conduct ivity, cor responds t o an increase in groundwater pH concentrations. Also,
it shows that pH contributes significantly to conductivity and suggests that considerable anthropogenic
activities remain accountable for the addition of these groundwater ions into the area76,77. Likewise, BOD
has a remarkable positive connection with temperature, pH and DO. Thereby showing that DO and BOD
concentration went in parallel with the concentration of Temperature, pH and DO, thus sharing a similar
origi n i n the wate r. Th e COD show s a si gnif ican t neg ativ e rel ationship with temperature, pH, DO and BOD.
Negative correlations between these physicochemical parameters could mean that these parameters have
their origin from different sources78. Acidity shows a significant negative relationship with COD indicating
the medium effect of acidity on the dissolved content of the water. Alkalinity shows a significant negative
relationship with temperature, pH, DO and BOD. For hardness, it was significantly negatively related to
COD and Alkalinity. Furthermore, the result revealed that TDS has a substantial positive association with
pH, Conductivity, BOD, Acidity and Hardness thus, indicating that salt dissolution accelerates the electrical
process of weathering. In the case of the study area, the inputs of Mg, SO4, Na, Cl, TDS, as well as NO3
remain influenced via precipitation as well as human-induced activities but are significantly negatively
relat ed to Tu rbid ity a nd CO D. On the o th er ha nd, t he st udy f ound an interesting pattern between chloride
showing a significant positive relationship with COD, Alkalinity and TSS but a significant negative
relationship with Temperature, DO and Acidity, suggesting that weathering of halite and silicates is an
important process, though may not the sole process, regulating water chemistry in the area. Results
indicate that Aluminum has a significant negative relationship with conductivity, DO, Hardness and TDS
but a significant positive relationship with Turbidity, Alkalinity, TSS, Salinity and fluoride. Sodium showed
a significant negative relationship with Temperature, DO and Acidity but a significant positive relationship
with COD, Alkalinity, TSS, Chloride, Fluoride and Aluminum. All of this may be attributable to Halite (NaCl)
as well as Sylvite (KCl) mineral dissolution, as well as irrigation return flow79. It also revealed the cation
exchang e proce ss in th e groun dwater sys tem, wh ich mig ht be re lated to weathering as well as dissolution
of sedimentary rocks containing F-bearing minerals in the vicinity (e.g., biotite, cryolite and amphiboles).
Thus, indicating that ion-exchange reactions also occurred during the interaction between water and
aquifer. Potassium showed a significant positive relationship with BOD, Hardness, TDS, TSS, Chloride and
Sodium. Although all the aforementioned correlations between parameters are positive, but a significant
negative relationship with Temperature. Similarly, the results show that calcium has a significant negative
relationship with temperature, pH, DO, BOD, Acidity, Hardness and TDS but a significant positive
relationship with Turbidity, COD, Alkalinity, TSS, Salinity, Chloride and Aluminum, Sodium revealing the
fertilizers impact in the groundwater and likely metals co-enrichment through the mentioned ions as well
as evaporitic formations as possible sources as recommended by Srivastava and Ramanathan80. Iron was
found to have a significant positive relationship with Salinity, Fluoride, Aluminum and Turbidity, which
remained ascribed to comparable geochemical procedures as well as circumstances for groundwater
release of these metals80-82. The highly negative value was observed between Magnesium and Alkalinity,
TSS, Chloride, Sodium and Calcium and Magnesium with COD, Alkalinity, TSS, Chloride, Sodium and
Calcium. As well as Manganese with COD, Alkalinity, TSS, Chloride and Sodium. Thus, the weak correlations
obtained between the parameters confirm that oxidation-reduction and l ea chi n g s eem t o b e th e pr oba b le
sources of minerals and metals in groundwater of the generalized aquifers of the Ebocha-Obrikom Area
of Rivers State. The different geological formations of these aquifers clearly show that groundwater
mineralization is intimately linked to the nature of the geology and geomorphology of the area which is
dominant in the study area. Also, cadmium shows a strong negative correlation between COD, Alkalinity,
TSS, Chloride and Calcium. Lead has a significant negative relationship with Temperature, pH, DO, BOD,
Acidity, Hardness, TDS, Magnesium, Zinc, Manganese and Cadmium, while copper had a significant
negative relationship with COD, Alkalinity, TSS, Chloride, Sodium, Calcium and Lead. The result indicates
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Trends Appl. Sci. Res., 18 (1): 149-168, 2023
that Chromium has a strong negative relationship with COD, Alkalinity, TSS, Chloride, Sodium, Calcium and
Lead remain remarkably correlated since they contribute toward water hardness. There is a positive
correlation between Sulphate and Temperature, pH, DO, BOD, Acidity, Magnesium, Iron, Zinc, Manganese,
Cadmium, Copper and Chromium. Ammonia with Temperature, pH, DO, BOD, Acidity, Hardness, TDS,
Magnesium, Zinc, Manganese, Cadmium, Copper, Chromium and Sulphate positive correlations show that
species studied come from comparable sources but also show the existence of chemical reactions in
groundwater, like cations and anions neutralization. All of these indicate the process of neutralization
between all measured parameters that occurred during the studied period. The result of the bivariate
relationship also revealed that Nitrate has a significant positive association with Temperature, pH,
Turbidity, DO, BOD, Acidity, Hardness, Salinity, Magnesium, Zinc, Manganese, Cadmium, Copper,
Chromium, Sulphate, Ammonia, Phosphate, Nitrite elucidate the presence of anthropogenic sources such
as punctured sewer pipelines82,83 and gas flaring but significant negative relationship with COD, Alkalinity,
TSS, Fluoride, Sodium, Calcium and Lead. There is positive correlation between Nickel with Temperature,
pH, DO, BOD, Acidity, Magnesium, Zinc, Manganese, Cadmium, Copper, Chromium, Sulphate, Ammonia,
Phosphate and Nitrite. Also, TPH shows a significant, positive relationship with Temperature, DO, Chloride,
Sulphate, Ammonia and Nitrate, all suggesting that high correlation between metals could be the reason
of same origin and controlling factors. The highly negative value wa s obser ved bet ween Ni trate and COD,
Alkalinity, TSS, Chloride, Sodium, Calcium, as well as Lead. Lastly, TPH shows a significant negative
relationship with only Alkalinity and Fluoride. This finding is consistent with previous studies, as observed
in the present study40,76-83.
Turning to the association for dry seasons (Table 3), there is positive correlation between DO with
Temperature and Turbidity. Acidity with Temperature and DO. Hardness with pH, conductivity and BOD.
TDS with Conductivity, BOD and Hardness, this strong correlation explains ions exchange between TDS
and conductivity. The TSS with pH, Conductivity, BOD, Hardness and TDS. Salinity with DO and TDS.
Chloride with Conductivity, COD, Hardness and TDS, suggesting that weathering is an important process,
though may not be the sole process, regulating water chemistry in the area. Fluoride with BOD, Hardness,
TDS and TSS, indicating the likelihood contribution of carbonate dissolution to water chemistry84. This was
evi de nc ed by th e f ac t tha t t he stud y a re a i s car bo na tes i n n at ure such as calcite and dolomite are common
in the geological formations. Aluminum with Turbidity, Fluoride suggested that these metals were released
into groundwater by forming complexes in solution with evaporites80,85. Sodium with BOD, COD, Hardness,
TDS, TSS, Chloride and Fluoride may be attributed to the dissolution of Halite (NaCl) and Sylvite (KCl)
minerals and irrigation return flow79. It also possibly suggests a common geogenic origin and conditions
that enhanced its mobility. Thus, this showed that the halite dissolution and the silicate weathering
provided solute components, such as feldspar. Potassium with conductivity, BOD, COD, Hardness, TDS,
TSS, Salinity, Chloride, Fluoride and Sodium. Calcium with Conductivity, Alkalinity, Hardness, TDS, TSS,
Chloride, Fluoride, Sodium and Potassium indicating the possible co-enrichment of these metals with the
mentioned ions and evaporitic formations as potential sources as suggested by Barzegar et al.81. It also
suggested that some of these ions may have been derived from calcite dissolution. Magnesium with
Hardness, TDS, Chloride and Potassium indicate that hardness is mostly related to Mg2+. Not only
anthropogenic sources but natural sources are also affecting groundwater quality. Iron with DO, Acidity,
Fluoride and Aluminum. Zinc with Conductivity, Turbidity, Hardne s s, T SS , Ch l or i de , Po tas s iu m an d Ca l ci u m.
The positive correlation between these parameters is in agreement with earlier similar results reported by
Kumar et al.86. Strong positive correlation between Potassium and Calcium was also reported by
Egbueri and Mgbenu87. Manganese has a significant positive relationship with conductivity, BOD, COD,
Hardness, TDS, TSS, Salinity, Chloride, Sodium, Potassium, Magnesium and Zinc. A positive correlation
between these parameters is an indication of their common sensitivity to redox reactions leading to the
reduction of Sodium and Zinc Hydroxides and Manganese Oxides
87,88. This also suggested a similar
geogenic origin86,88 and this study agreed with earlier similar results by Ukah et al.89. The highly positive
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Trends Appl. Sci. Res., 18 (1): 149-168, 2023
cor rela tion was o bser ved s ugge sts t hat h igh c orre lati on be tw een metals could be the reason for the same
origin and controlling factors. Cadmium with DO, Alkalinity, TSS, Aluminum and Calcium, may be due to
the fact that the production and refining processes of Al also contribute to the formation of Ca and Cd89,90.
Lead with Salinity. Copper with BOD, Hardness, Sodium and Cadmium. Chromium with pH, Conductivity,
BOD, Alkalinity, Hardness, TDS, TSS Fluoride, Aluminum, Sodium, Potassium, Calcium, Manganese,
Cadmium and Copper which may be due to oxidation mechanism present in groundwater. All these
parameters may have triggered groundwater mobilization. Sulphate with Temperature, DO, Acidity and
Iron. Ammonia with DO, BOD, Acidity, Hardness, TDS, TSS, Chloride, Potassium, Iron, Zinc, Manganese,
Chromium and Sulphate. Thus, positive correlations probably suggest that the parameters analyzed come
from similar sources, but also indicate the presence of chemical pr oc esse s in t he gr ound wate r, su ch as the
neutralization between anions and cations. For example, the correlation between Ammonia, Chlorides and
Sulphates, indicates the process of neutralization between parameters that occurred during the studied
period. Phosphate with BOD, Acidity, Alkalinity, TSS, Fluoride, Aluminum, Iron, Cadmium, Copper,
Chromium. Nitrite with Conductivity, Turbidity, DO, COD, TDS, Salinity, Chloride, Potassium, Magnesium,
Zinc, Manganese and Ammonia. Nitrate with Temperature, Conductivity, Turbidity, DO, Salinity, Calcium,
Zinc, Sulphate, Ammonia and Nitrite. This is in agreement with the observation of Khan and Jhariya91,
confirming the observation made by the Hierarchical cluster analysis. Nickel with Lead, Sulphate, Nitrite
and Nitrate.
The highly negative value was observed between hardness with temperature and DO. The TDS with
Temperature. Fluoride with DO. Aluminum with Temperature. Sodium with Temperature and DO,
Potassium with Temperature. Magnesium with Temperature, DO and Alkalinity. Cadmium with Chloride
and Magnesium. Copper with Lead. Sulphate with BOD, Hardness, Fluoride, Sodium, Potassium and
Magnesium. Phosphate with Chloride. Nitrite and Nickel with Alkalinity. TPH has a significant positive
relationship with Turbidity, DO, Salinity, Calcium, Cadmium, Sulphate, Ammonia and Nitrite. Thus, human
activity has become one of the most important factors influencing groundwater chemistry and even the
dominant mechanism regulating the hydrochemical composition of groundwater across the global
south3-13,23-47,60,61. For Nitrogen, it is an important indicator of contamination from human community,
which has been widely used to indicate the anthropogenic inputs of pollutant from agricultural practice,
domestic effluents and so on4-8. Generally, groundwater water in th e E bo cha- Ob ri kom A re a o f R ivers State
originates from anthropogenic sources of domestic life, gas flaring, agriculture fertilizer, oil spillage and
livestock manure, etc. Thus, groundwater in these locations was influenced by anthropogenic contaminant
inputs. Hence, the current results align with some but not all findings reported in previous studies
assessing human health risks of trace elements in groundwater in the Niger Delta Region of Nigeria91-94.
Specifically, several studies reported associations between the assessment of groundwater quality for
drinking and irrigation purposes
4-8,95-111. The current study observed an association between some
physicochemical indices and heavy metals. Discrepancies may be due to assessment in differences,
physicochemical and heavy metals measurement and study area. The general finding of higher levels of
risky association between some physicochemical indices and heavy metals overall being associated with
one another is in line with past literature examining the relationships between these variables4,5,40,45,47,105.
Current findings regarding the association between physicochemical indices and heavy metals are in line
with reporting in several studies4,5,40,45,47,95,105,110. All these multi-regional studies offer wide-ranging
interactive information between significant indicators such as the association between groundwater
pollution and environmental background. Thus, the current findings expand the literature by
demonstrating this association within a longitudinal study and specifically in relation to changes in health
risk patterns (Fig. 2). Additionally, this is the first study, to document an association between 34
parameters before and during the COVID-19 pandemic. Future studies are encouraged to provide highly
valuable contributions to the literature. Meanwhile, the overall pollution impact on water bodies and
ecosystems is far more difficult to predict. In conclusion, continuous exposure to trace metals causes
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Trends Appl. Sci. Res., 18 (1): 149-168, 2023
respiratory irritation, renal failure, neurological impairments, immunosuppression, anemia, gastrointestinal
as well as liver cancer, skeletal system abnormalities, liver inflammation and cardiovascular disorders. As
a result, the principal pollutants’ impacts on human health were diagrammatically depicted in Fig. 2. This
finding additionally contributes to a pattern of future groundwater studies based on the impact of health
outcomes. In light of these findings, it is concluded that it is essential that effective policies be
implemented. Furthermore, increased efforts should be made to safeguard groundwater from
anthropogenic contaminations in order to achieve sustainable groundwater development. The findings
of this study not only add to the geochemical characterization of shallow groundwater in Nigeria’s oil-rich
Niger Delta Region but also provide vital information for authorities developing groundwater sustainable
management plans in such areas.
Local-level data are crucial for monitoring pollution levels, identifying as well as assigning suitable
responsibility for each pollution source, appraising intervention successes, directing enforcement,
educating civil society and the public, as well as measuring improvement toward sustainable development
goals. Set up systems to track pollution and its consequences on health. Incorporating modern
technologies into pollution monitoring, like data mining as well as satellite imaging, can boost efficiency,
broaden geographic coverage, as well as reduce costs. The availability of this data is critical and
collaboration with civil society as well as the broader public will assure accountability while also raising
p ub li c ed uc ati on a war en ess . Ev en t iny mo nit ori ng p rog ram s w ith only one or a few sampling sites can help
governments and civil society organizations document pollution and analyze progress toward short and
long-term management goals. To enable the sharing of successes and lessons gained, pollution
management metrics control should be linked into SDG dashboards as well as other monitoring systems.
Furthermore, the study recommendations will be useful for other oil-rich countries experiencing
comparable challenges. Because every decision is based on a projection of its repercussions.
CONCLUSION
High-quality groundwater is critical in minimizing the prevalence of waterborne illnesses in rural regions.
The current study’s findings indicate a positive association between each of the criteria. That is, if the
percentage change in any of the indices’ parameters increases, there will be an increase in other
parameters in Ebocha-Obrikom. In reality, a minor rise in these parameters could result in a significant
increase in long-term oil and gas exploitation as well as gas flaring in the area, both of which have a
dominant and universal effect on solute concentrations and hydrochemical types. It is important to note
that gas flaring may not be the only factor influencing these metrics. In fact, there are numerous other
elements that may be more relevant than gas flaring, such as oil spillage, bunkering, human activities, as
well as distance from gas flaring sites, among others. Consequently, gas flaring data may have been
underestimated, leading to a moderate correlation between each of the metrics. As a result, the
consequences of heavy metal pollution on public health remain poorly understood, as well as its input to
the global sickness burden is almost definitely understated. Surprisingly, the Pearson correlation analysis
method results suggest that the composition of rock dissolution, as well as human activities, have an effect
on the composition of groundwater in the research area. The key governing factors in Rivers State’s
Ebocha-Obrikom Area include evaporating dissolution, human activities and significant cation exchange,
all of which affect the evolution of groundwater quality. Thus, the current study’s findings provide critical
insights into the changing dynamics and can be extrapolated to future exposures to environmental
contaminants throughout developmentally vulnerable windows in early lif e, w hic h co uld cause outbreaks
of infectious respiratory disease as well as infancy death, childhood and chronic, no communicable
diseases that can manifest at any point across the indigenous resident life span, as well as to inform
policymakers of how these toxic chemical parameters are growing into a major threat to human’s health
in oil-rich Niger Delta Regions of Nigeria and also provided a reference to support prioritization and
planning for heavy metals pollution control. While, disease as well as disability induced by heavy metal
pollution have high economic expenses, which might jeopardize national development plans.
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Trends Appl. Sci. Res., 18 (1): 149-168, 2023
SIGNIFICANCE STATEMENT
The wise use and quality of groundwater for industrial, agricultural and drinking reasons have attracted
a lot of attention as a result of environmental contamination and anthropogenic activities. Thus, to shed
light on the causes, correlations of trace metal contamination in drinking water in oil exploration zones
in groundwater pollution in the Niger Delta become necessary. Hence, the findings can serve as a
foundation for making decisions on the scientific management of th e N ige r De lta gr oun dwa ter eco sys te m
and the preservation of public health.
ACKNOWLEDGMENTS
This study was carried out in the framework of the research project entitled “Assessment of groundwater
quality in Ebocha-Obrikom of Rivers State, Nigeria.” The authors would like to express their appreciation
to the Association of African Universities (AAU) for the financial support [grant number 2020-02274]. Also
thanks to the late Professor Mynepalli K. C. Sridhar, Professor Henry Olawale Sawyerr, Professor Innocent
M. Aprioku, Professor Bassey E. Akpan, as well as all anonymous reviewers, for feedback and discussions
that helped to substantially improve this manuscript. Laboratory at Anal Concept Limited and Institute of
Pollution Studies, River State University of Science and Technology (RSUST) for their partial contribution
to the chemical analyses of the samples.
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