Abstract
Drinking water quality for human consumption is a global matter of paramount importance. The study aimed to assess the physicochemical and bacteriological quality of drinking water from five major sources in Sapele, Delta State. Using a convenient sampling method, 40 water samples were collected from river, rain, well, borehole, and sachet water sources and examined for physicochemical and bacteriological characteristics. The pH of the water sources examined ranged from 4.5 to 6.8, the total dissolved solids (TDS) ranged between 5 and 14,000 mg/l, the electrical conductivity (EC) ranged between 10 and 740 μS/cm, and the turbidity ranged between 0.01 and 23.9 NTU. Mean levels of chloride, calcium, iron, lead, copper, and cadmium were below the maximal permissible ceilings based on WHO and NSDWQ standards. The total coliform count ranged between 0 and 9,000 MN/100 ml, with the mean concentration ranging between 0.001 and 1,268.13 MPN/100 ml. Water samples from different sources had physicochemical parameters within the stipulated standards, but the biological parameters revealed water sources with contamination. It is recommended that consumers of water from these different sources employ measures to purify their drinking water to forestall potential health risks.
HIGHLIGHTS
This study describes the assessment of the quality of drinking water in an urban area in South-South, Nigeria.
The study assessed the physicochemical qualities of drinking water quantitatively.
The study also assessed the bacteriological qualities of drinking water using quantitative techniques.
Several sources of drinking water in the study location were assessed.
Local and international standards were employed in the assessment of the drinking water quality.
Graphical Abstract
INTRODUCTION
Water is an important natural resource both for domestic, industrial, and agricultural purposes (FAO 2022). Despite its importance in the sustenance of life and livelihood, the inability to access safe and potable water has been identified as a major cause of morbidity and mortality (Cheng et al. 2012; Umar et al. 2020).
Although significant progress has been made in increasing access to clean drinking water and sanitation, billions of people, especially in rural areas, still lack drinking water. Globally, one in every three people lack access to safe drinking water, two out of every five people lack access to a basic hand-washing facility with soap and water, and more than 673 million people continue to practice open defaecation (UN 2022). About 2 billion people drink water that has been polluted by faeces (WHO 2019). Water scarcity affects more than 40% of the global population and is projected to rise. Over 1.7 billion people are currently living in river basins where water use exceeds recharge (UN 2022). It has been reported that about 42% of individuals resident in Sub-Saharan Africa drink from water sources that are not improved, and 72% are without fundamental sanitation (Eberhard 2019).
Ample supply of potable water is critical in the prevention of gastrointestinal diseases; in this regard, drinking water quality has a significant impact on public health (Durmishi 2012). Pollutants such as bacteria, heavy metals, nitrates, and salts find their way into water bodies as a result of insufficient treatment of human, agricultural, and industrial wastes before discharge into water bodies. The discharge of industrial wastewater (e.g., brine) degrades water quality, and thus water cannot be directly used for potable water (via desalination) or industrial applications (Panagopoulos 2022a, 2022b; Panagopoulos & Giannika 2022).
Furthermore, newer techniques of treating waste produced from industrial activity such as the use of Chlorella vulgaris and nitrifying-enriched activated sludge, ammonia feeding of conventional activated sludge (CAS) have been studied. Research has shown that nitrite-oxidizing bacteria (NOB) enrichment and nitratation intensification strategy through zero C/N ratio offers microbial metabolite reduction by as much as 50% compared with conventional process and enhances nitrification efficiency in activated sludge-involved processes (Sepehria & Sarrafzadeh 2018, 2019; Sepehria et al. 2020).
Natural levels of metals and other chemicals exceeding the acceptable limit can be injurious to human health even in the absence of anthropogenic sources of pollutants in water (Hadzi et al. 2015). Water sources, particularly those with unimproved origins, are polluted by natural factors such as flooding, climate, weathering of parent material, topography, and others, and not just by anthropogenic factors alone.
Physicochemical and biological variables must be considered in assessing the quality of drinking water (Hadzi et al. 2015). Physical parameters of water include colour, smell, temperature, pH, turbidity, EC, etc. There are several chemical substances that may be naturally present in or introduced into water, including chemicals used for water treatment. The World Health Organization (WHO) has developed guidelines for maximum allowable concentrations (limits) of chemicals in drinking water. These chemical substances include iron (Fe), lead (Pb), mercury (Hg), residual chlorine (Cl), chromium (Cr), etc. (Hadzi et al. 2015; Abhishek et al. 2017; Lukubye & Andama 2017).
A biological (microbial) parameter is employed for the assessment of drinking water quality using the index/indicator concept (Abhishek et al. 2017). Generally, the presence of organic pollutants helps detect the presence of pathogens in drinking water. The thermotolerant Escherichia coli (E. coli) is widely used as an index organism to assess water treatment and is widely preferred as the index organism for faecal contamination (Abhishek et al. 2017). Thermotolerant coliform count (faecal coliform) is acceptable where E. coli detection is not possible (WHO 2013; Abhishek et al. 2017). The presence of other microbes may indicate faecal contamination as well. Faecal streptococci, for example, indicate recent faeces contamination of water sources (Abhishek et al. 2017; Lukubye & Andama 2017).
Globalization and the rapid increase in population have placed enormous demands on commerce and industry; the availability and quality of drinking water have also been adversely affected. Sapele, a large local government area (LGA) in Delta State, in the Niger-Delta region of Nigeria, is an example of an urban area with rapid population growth, which has placed pressure on the availability of potable drinking water. The major sources of water for inhabitants of the town include boreholes, wells, rain, sachets (packaged water), and rivers. The water is utilized primarily for the purposes of drinking, cooking, and washing.
Pollution of the water can arise from the siting of boreholes close to soakaways or septic tanks, which culminates in the percolation of the content of the soakaway or septic tank into groundwater and, by extension, cause waterborne illness such as cholera when the water is utilized for domestic purposes such as drinking (Sundar & Nirmala 2015; Asabe & Michael 2016).
Periodic evaluation of drinking water quality is imperative to ensure that trace elements do not exceed acceptable ceilings because of their deleterious effects at elevated levels, which include mutagenicity, mortality, growth retardation, and structural malformations (Usman et al. 2020). Taking into cognizance the close siting of boreholes to soakaways or septic tanks in Sapele LGA and the risks of pollution from the effluents discharged by oil firms domiciled in the LGA, evaluation of the physicochemical and bacteriological quality of borehole water in the LGA formed the justification for this study with a view to ascertaining the potability of the water.
The objective of this study is to assess the physicochemical and bacteriological qualities of drinking water from five major water sources in Sapele LGA of Delta State, to compare the values obtained with the WHO and Nigerian Standard for Drinking Water Quality (NSDWQ) acceptable values, and by extension, to make recommendations to stakeholders on ways of improving drinking water quality.
METHODS
This was a descriptive, cross-sectional, analytical study conducted in Sapele Local Government Area of Delta State, Nigeria, to assess the physiochemical and bacteriological quality of drinking water. Sapele Local Government Area is one of the 25 LGAs in Delta State, with its administrative headquarters situated in Sapele in the central senatorial zone. Sapele lies near the Benin River, off the confluence point of the Benin and Jamieson Rivers, with the Ethiope River flowing through the area. The estimated population of Sapele LGA is 298,310 with Urhobo being the predominant ethnic group and the Urhobo language commonly spoken. Christianity and traditionalism are widely practiced in the area. The LGA also has an estimated total precipitation of 3,050 mm of rainfall per year. Trading and farming are the major economic activities, with oil palm and rubber being the main food and cash crops in the LGA. Other economic enterprises engaged in by the inhabitants of Sapele LGA include fishing, lumbering, and craftsmaking (Manpower 2022).
Eight out of a total of 11 political wards in Sapele LGA were selected by balloting. Five sources of water supply in the study area, namely, wells, boreholes, rivers/streams, sachet water, and rain, were identified and selected as units of analysis for the study. Using a convenient sampling method, one water sample was collected from each of the five sources in the eight selected political wards in the LGA to make a total of 40 water specimens collected from the five different sources. The water samples were tested in the laboratory for pH, total dissolved solids (TDS), EC, turbidity, chloride (Cl), calcium (Ca), iron (Fe), lead (Pb), copper (Cu), cadmium (Cd), and total coliform count.
Ethical approval No. ADM/E22/A/Vol. VII/14831195 was obtained from the health research ethical committee of the University Teaching Hospital Benin City before the commencement of this study.
Sample collection
Water samples were collected using 1-l sample bottles. The bottles and their covers were washed thoroughly and sterilized using a dry-air oven set at 170 °C for 1 h. During the collection of the samples, the sterile bottles were cleaned with the water to be sampled three times before the final collection of the samples. A concentration of 0.2 ml of sodium thiosulphate solution was added to each bottle before sterilization to stop the action of residual chlorine on Escherichia coli (E. coli) in the water sample for bacteriological analysis.
The nozzles of the taps were disinfected using ethanol and flame and allowed to cool by allowing water to run for a few seconds. The sample bottles were then filled with the sampled water via a gentle flow from the taps. The bottles were thereafter covered and labelled for easy identification.
Water samples from streams and other surface waters were collected by simply dipping the neck of the bottle downwards about 30 cm below the water surface and then tilting it upwards until the water filled it. The covers of the bottles were replaced, and the bottles were labelled appropriately (DELG 2017).
Water samples from wells were collected using bottles with a string tied above the metal weights. The crowns of the bottles were aseptically removed and lowered into wells to a depth of approximately 1 m and thereafter pulled out of the wells, and their crowns were thereafter replaced meticulously and the bottles labelled. Because the water sample size was not extremely large, all samples were collected one-by-one from the various sampling sites, which could make the process arduous and, as a result, influence the outcome of the laboratory investigation. However, the advent of technologies such as drones has made it possible to collect extremely large water samples one-time only, removing challenges such as the exhaustiveness of the process and its potential impact on laboratory analysis results (Hanlon et al. 2022).
The water samples were stored in coolers containing ice packs and transported within an hour to a state government-approved environmental analysis laboratory for investigation. Standard methods stipulated by the American Public Health Association (APHA 2012; Ukpong & Peter 2012) were employed to analyse the physicochemical parameters, including the pH, TDS, turbidity, EC, chloride, calcium, iron, lead, cadmium, and copper contents. Electrometry was performed to determine pH, conductivity, and TDS, while nephelometry was performed to measure turbidity. Atomic absorption spectrometry was employed to determine iron, calcium, lead, cadmium, and copper. The Multiple Tube Fermentation (MTF) method, as described by Aneja (2017), was employed to estimate total coliforms. The origin of the source of the sampled water was not disclosed to the laboratory scientists.
Statistical analysis
The data were collated, screened for completeness, coded, and entered into a spreadsheet. Continuous variables that were normally distributed were summarized using means and standard deviation, while categorical data were summarized as frequencies and proportions. The coefficient of variation, expressed as a percentage, was used to compare the variability of measurements made in different units of the various parameters of the collected water samples. A one-way ANOVA was used to compare differences in means of parameters such as pH, TDS, EC, turbidity, chloride, calcium, iron, lead, copper, cadmium, and total coliforms between the various sources of drinking water. A post hoc test was used to determine which group's means for various parameters and sources of water were significantly different from other group means. The level of statistical significance was set at 0.05. The results were compared with WHO and NSDWQ guideline values for drinking water quality.
RESULTS
Results of the laboratory analysis of various parameters for river, rain, and well water sources are shown in Table 1, while those for borehole and sachet water sources are shown in Table 2. The pH ranges of the water samples collected from the river, rain, well, borehole, and sachet samples were lower than the WHO (6.5–8.5) and NSDWQ (6.5–8.5) recommended ranges (Table 3).
Parameter . | River . | WHO*MPL . | NSDWQ*MPL . | |||||||
---|---|---|---|---|---|---|---|---|---|---|
River1 . | River2 . | River3 . | River4 . | River5 . | River6 . | River7 . | River8 . | |||
pH | 6.4 | 6.6 | 6.5 | 6.4 | 6.8 | 5.5 | 6.6 | 6.3 | 6.5–8.5 | 6.5–8.5 |
TDS (mg/l) | 40 | 15 | 20 | 12 | 45 | 24 | 18 | 10 | 500–1,000 | 500 |
Electrical Conductivity (μS/cm) | 60 | 25 | 30 | 20 | 40 | 25 | 15 | 35 | 500 | 1,000 |
Turbidity (NTU) | 8.68 | 10.92 | 15.57 | 17.72 | 15.23 | 19.77 | 23.97 | 6.92 | 5 | 5 |
Chloride (mg/l) | 12.72 | 6.01 | 8.46 | 4.54 | 10.2 | 7.64 | 5.23 | 3.42 | 250 | 250 |
Calcium (mg/l) | 0.001 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | 100 | 75 |
Iron (mg/l) | 2.702 | <0.001 | <0.001 | 0.109 | 0.204 | 0.106 | <0.001 | 0.115 | 0.3 | 0.3 |
Lead (mg/l) | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | 0.001 | 0.001 |
Copper (mg/l) | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | 1 | 1 |
Cadmium (mg/l) | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | 0.126 | <0.001 | 0.003 | 0.003 |
Total Coliform (MPN/100 ml) | 2,800 | 1,700 | 500 | 700 | 1,200 | 900 | 300 | 2,500 | 0 | 0 |
Rain . | . | . | ||||||||
Parameter . | Rain1 . | Rain2 . | Rain3 . | Rain4 . | Rain5 . | Rain6 . | Rain7 . | Rain8 . | WHO*MPL . | NSDWQ*MPL . |
pH | 5.8 | 6.0 | 6.4 | 5.5 | 5.8 | 6.2 | 6.7 | 5.3 | 6.5–8.5 | 6.5–8.5 |
TDS (mg/l) | 10 | 20 | 5 | 15 | 10 | 8 | 20 | 12 | 500–1,000 | 500 |
Electrical Conductivity (μS/cm) | 20 | 30 | 25 | 10 | 20 | 35 | 40 | 15 | 500 | 1,000 |
Turbidity (NTU) | 0.61 | 1.3 | 0.32 | 0.09 | 0.18 | 0.69 | 1.67 | 0.11 | 5 | 5 |
Chloride (mg/l) | 1.76 | 9.53 | 4.28 | 1.53 | 7.06 | 2.66 | 5.77 | 1.39 | 250 | 250 |
Calcium (mg/l) | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | 100 | 75 |
Iron (mg/l) | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | 0.3 | 0.3 |
Lead (mg/l) | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | 0.001 | 0.001 |
Copper (mg/l) | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | 1 | 1 |
Cadmium (mg/l) | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | 0.003 | 0.003 |
Total Coliform (MPN/100 ml) | 9,000 | 1,100 | 0 | 20 | 0 | 0 | 25 | 0 | 0 | 0 |
. | Well . | . | . | |||||||
Parameter . | W1 . | W2 . | W3 . | W4 . | W5 . | W6 . | W7 . | W8 . | WHO*MPL . | NSDWQ*MPL . |
pH | 5.5 | 5.8 | 5.8 | 4.7 | 6.2 | 5.6 | 6.8 | 6.0 | 6.5–8.5 | 6.5–8.5 |
TDS (mg/l) | 240 | 250 | 380 | 270 | 240 | 680 | 311 | 425 | 500–1,000 | 500 |
Electrical Conductivity (μS/cm) | 350 | 370 | 540 | 410 | 320 | 740 | 265 | 440 | 500 | 1,000 |
Turbidity (NTU) | 2.04 | 0.01 | 2.62 | 2.44 | 2.36 | 0.15 | 3.82 | 1.70 | 5 | 5 |
Chloride (mg/l) | 29.08 | 32.45 | 68.16 | 54.53 | 41.82 | 22.08 | 38.33 | 52.16 | 250 | 250 |
Calcium (mg/l) | 22.46 | 21.52 | 16.00 | 8.14 | 10.13 | 14.11 | 28.35 | 6.83 | 100 | 75 |
Iron (mg/l) | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | 0.106 | <0.001 | 0.149 | 0.3 | 0.3 |
Lead (mg/l) | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | 0.001 | 0.001 |
Copper (mg/l) | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | 0.112 | 0.109 | 1 | 1 |
Cadmium (mg/l) | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | 0.003 | 0.003 |
Total Coliform (MPN/100 ml) | 90 | 90 | 110 | 140 | 70 | 120 | 50 | 85 | 0 | 0 |
Parameter . | River . | WHO*MPL . | NSDWQ*MPL . | |||||||
---|---|---|---|---|---|---|---|---|---|---|
River1 . | River2 . | River3 . | River4 . | River5 . | River6 . | River7 . | River8 . | |||
pH | 6.4 | 6.6 | 6.5 | 6.4 | 6.8 | 5.5 | 6.6 | 6.3 | 6.5–8.5 | 6.5–8.5 |
TDS (mg/l) | 40 | 15 | 20 | 12 | 45 | 24 | 18 | 10 | 500–1,000 | 500 |
Electrical Conductivity (μS/cm) | 60 | 25 | 30 | 20 | 40 | 25 | 15 | 35 | 500 | 1,000 |
Turbidity (NTU) | 8.68 | 10.92 | 15.57 | 17.72 | 15.23 | 19.77 | 23.97 | 6.92 | 5 | 5 |
Chloride (mg/l) | 12.72 | 6.01 | 8.46 | 4.54 | 10.2 | 7.64 | 5.23 | 3.42 | 250 | 250 |
Calcium (mg/l) | 0.001 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | 100 | 75 |
Iron (mg/l) | 2.702 | <0.001 | <0.001 | 0.109 | 0.204 | 0.106 | <0.001 | 0.115 | 0.3 | 0.3 |
Lead (mg/l) | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | 0.001 | 0.001 |
Copper (mg/l) | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | 1 | 1 |
Cadmium (mg/l) | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | 0.126 | <0.001 | 0.003 | 0.003 |
Total Coliform (MPN/100 ml) | 2,800 | 1,700 | 500 | 700 | 1,200 | 900 | 300 | 2,500 | 0 | 0 |
Rain . | . | . | ||||||||
Parameter . | Rain1 . | Rain2 . | Rain3 . | Rain4 . | Rain5 . | Rain6 . | Rain7 . | Rain8 . | WHO*MPL . | NSDWQ*MPL . |
pH | 5.8 | 6.0 | 6.4 | 5.5 | 5.8 | 6.2 | 6.7 | 5.3 | 6.5–8.5 | 6.5–8.5 |
TDS (mg/l) | 10 | 20 | 5 | 15 | 10 | 8 | 20 | 12 | 500–1,000 | 500 |
Electrical Conductivity (μS/cm) | 20 | 30 | 25 | 10 | 20 | 35 | 40 | 15 | 500 | 1,000 |
Turbidity (NTU) | 0.61 | 1.3 | 0.32 | 0.09 | 0.18 | 0.69 | 1.67 | 0.11 | 5 | 5 |
Chloride (mg/l) | 1.76 | 9.53 | 4.28 | 1.53 | 7.06 | 2.66 | 5.77 | 1.39 | 250 | 250 |
Calcium (mg/l) | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | 100 | 75 |
Iron (mg/l) | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | 0.3 | 0.3 |
Lead (mg/l) | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | 0.001 | 0.001 |
Copper (mg/l) | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | 1 | 1 |
Cadmium (mg/l) | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | 0.003 | 0.003 |
Total Coliform (MPN/100 ml) | 9,000 | 1,100 | 0 | 20 | 0 | 0 | 25 | 0 | 0 | 0 |
. | Well . | . | . | |||||||
Parameter . | W1 . | W2 . | W3 . | W4 . | W5 . | W6 . | W7 . | W8 . | WHO*MPL . | NSDWQ*MPL . |
pH | 5.5 | 5.8 | 5.8 | 4.7 | 6.2 | 5.6 | 6.8 | 6.0 | 6.5–8.5 | 6.5–8.5 |
TDS (mg/l) | 240 | 250 | 380 | 270 | 240 | 680 | 311 | 425 | 500–1,000 | 500 |
Electrical Conductivity (μS/cm) | 350 | 370 | 540 | 410 | 320 | 740 | 265 | 440 | 500 | 1,000 |
Turbidity (NTU) | 2.04 | 0.01 | 2.62 | 2.44 | 2.36 | 0.15 | 3.82 | 1.70 | 5 | 5 |
Chloride (mg/l) | 29.08 | 32.45 | 68.16 | 54.53 | 41.82 | 22.08 | 38.33 | 52.16 | 250 | 250 |
Calcium (mg/l) | 22.46 | 21.52 | 16.00 | 8.14 | 10.13 | 14.11 | 28.35 | 6.83 | 100 | 75 |
Iron (mg/l) | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | 0.106 | <0.001 | 0.149 | 0.3 | 0.3 |
Lead (mg/l) | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | 0.001 | 0.001 |
Copper (mg/l) | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | 0.112 | 0.109 | 1 | 1 |
Cadmium (mg/l) | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | 0.003 | 0.003 |
Total Coliform (MPN/100 ml) | 90 | 90 | 110 | 140 | 70 | 120 | 50 | 85 | 0 | 0 |
Parameter . | Borehole . | WHO*MPL . | NSDWQ*MPL . | |||||||
---|---|---|---|---|---|---|---|---|---|---|
B1 . | B2 . | B3 . | B4 . | B5 . | B6 . | B7 . | B8 . | |||
pH | 4.8 | 5.6 | 4.9 | 5.0 | 5.5 | 5.8 | 4.5 | 6.4 | 6.5–8.5 | 6.5–8.5 |
TDS (mg/l) | 70 | 340 | 1,400 | 200 | 25 | 120 | 150 | 90 | 500–1,000 | 500 |
Electrical Conductivity (μS/cm) | 110 | 490 | 220 | 310 | 40 | 60 | 180 | 250 | 500 | 1,000 |
Turbidity (NTU) | 0.38 | 0.2 | 0.47 | 0.17 | 1.55 | 1.37 | 0.52 | 0.62 | 5 | 5 |
Chloride (mg/l) | 12.27 | 47.71 | 15.93 | 27.26 | 6.35 | 19.04 | 10.88 | 8.16 | 250 | 250 |
Calcium (mg/l) | <0.001 | 46.672 | <0.001 | 6.104 | <0.001 | 0.642 | 2.283 | <0.001 | 100 | 75 |
Iron (mg/l) | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | 0.3 | 0.3 |
Lead (mg/l) | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | 0.001 | 0.001 |
Copper (mg/l) | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | 1 | 1 |
Cadmium (mg/l) | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | 0.001 | <0.001 | <0.001 | 0.003 | 0.003 |
Total Coliform (MPN/100 ml) | 0 | 20 | 0 | 0 | 20 | 0 | 0 | 30 | 0 | 0 |
. | Sachet . | . | . | |||||||
Parameter . | S1 . | S2 . | S3 . | S4 . | S5 . | S6 . | S7 . | S8 . | WHO*MPL . | NSDWQ*MPL . |
pH | 6.0 | 6.2 | 5.7 | 5.0 | 5.8 | 6.6 | 5.6 | 6.4 | 6.5–8.5 | 6.5–8.5 |
TDS (mg/l) | 20 | 15 | 10 | 40 | 20 | 35 | 18 | 25 | 500–1,000 | 500 |
Electrical Conductivity (μS/cm) | 30.0 | 25.0 | 20.0 | 60.0 | 30.0 | 55.0 | 10.0 | 20.0 | 500 | 1,000 |
Turbidity (NTU) | 0.09 | 0.05 | 0.01 | 0.09 | 0.23 | 0.03 | 0.06 | 0.18 | 5 | 5 |
Chloride (mg/l) | 7.45 | 4.18 | 2.72 | 9.54 | 7.12 | 6.24 | 1.08 | 3.47 | 250 | 250 |
Calcium (mg/l) | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | 100 | 75 |
Iron (mg/l) | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | 0.3 | 0.3 |
Lead (mg/l) | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | 0.001 | 0.001 |
Copper (mg/l) | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | 1 | 1 |
Cadmium (mg/l) | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | 0.003 | 0.003 |
Total Coliform (MPN/100 ml) | 0 | 0 | 170 | 0 | 0 | 0 | 40 | 0 | 0 | 0 |
Parameter . | Borehole . | WHO*MPL . | NSDWQ*MPL . | |||||||
---|---|---|---|---|---|---|---|---|---|---|
B1 . | B2 . | B3 . | B4 . | B5 . | B6 . | B7 . | B8 . | |||
pH | 4.8 | 5.6 | 4.9 | 5.0 | 5.5 | 5.8 | 4.5 | 6.4 | 6.5–8.5 | 6.5–8.5 |
TDS (mg/l) | 70 | 340 | 1,400 | 200 | 25 | 120 | 150 | 90 | 500–1,000 | 500 |
Electrical Conductivity (μS/cm) | 110 | 490 | 220 | 310 | 40 | 60 | 180 | 250 | 500 | 1,000 |
Turbidity (NTU) | 0.38 | 0.2 | 0.47 | 0.17 | 1.55 | 1.37 | 0.52 | 0.62 | 5 | 5 |
Chloride (mg/l) | 12.27 | 47.71 | 15.93 | 27.26 | 6.35 | 19.04 | 10.88 | 8.16 | 250 | 250 |
Calcium (mg/l) | <0.001 | 46.672 | <0.001 | 6.104 | <0.001 | 0.642 | 2.283 | <0.001 | 100 | 75 |
Iron (mg/l) | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | 0.3 | 0.3 |
Lead (mg/l) | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | 0.001 | 0.001 |
Copper (mg/l) | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | 1 | 1 |
Cadmium (mg/l) | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | 0.001 | <0.001 | <0.001 | 0.003 | 0.003 |
Total Coliform (MPN/100 ml) | 0 | 20 | 0 | 0 | 20 | 0 | 0 | 30 | 0 | 0 |
. | Sachet . | . | . | |||||||
Parameter . | S1 . | S2 . | S3 . | S4 . | S5 . | S6 . | S7 . | S8 . | WHO*MPL . | NSDWQ*MPL . |
pH | 6.0 | 6.2 | 5.7 | 5.0 | 5.8 | 6.6 | 5.6 | 6.4 | 6.5–8.5 | 6.5–8.5 |
TDS (mg/l) | 20 | 15 | 10 | 40 | 20 | 35 | 18 | 25 | 500–1,000 | 500 |
Electrical Conductivity (μS/cm) | 30.0 | 25.0 | 20.0 | 60.0 | 30.0 | 55.0 | 10.0 | 20.0 | 500 | 1,000 |
Turbidity (NTU) | 0.09 | 0.05 | 0.01 | 0.09 | 0.23 | 0.03 | 0.06 | 0.18 | 5 | 5 |
Chloride (mg/l) | 7.45 | 4.18 | 2.72 | 9.54 | 7.12 | 6.24 | 1.08 | 3.47 | 250 | 250 |
Calcium (mg/l) | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | 100 | 75 |
Iron (mg/l) | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | 0.3 | 0.3 |
Lead (mg/l) | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | 0.001 | 0.001 |
Copper (mg/l) | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | 1 | 1 |
Cadmium (mg/l) | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | 0.003 | 0.003 |
Total Coliform (MPN/100 ml) | 0 | 0 | 170 | 0 | 0 | 0 | 40 | 0 | 0 | 0 |
Parameter . | Source of water . | ||||
---|---|---|---|---|---|
River . | Rain . | Well . | Borehole . | Sachet . | |
pH | |||||
Range | 5.5–6.8 | 5.3–6.7 | 4.7– 6.8 | 4.5–6.4 | 5.0–6.6 |
Mean ± SD | 6.4 ± 0.39 | 5.9 ± 0.46 | 5.8 ± 0.6 | 5.3 ± 0.6 | 5.9 ± 0.5 |
Coeff. Var (%) | 6.14 | 7.77 | 10.38 | 11.33 | 8.54 |
WHO | 6.5–8.5 | 6.5–8.5 | 6.5–8.5 | 6.5–8.5 | 6.5–8.5 |
NSDWQ(MPL) | 6.5–8.5 | 6.5–8.5 | 6.5–8.5 | 6.5–8.5 | 6.5–8.5 |
Total dissolved solids (mg/l) | |||||
Range | 10–45 | 5–20 | 240– 680 | 25– 1,400 | 10–40 |
Mean ± SD | 23 ± 12.9 | 12.5 ± 5.5 | 349.5 ± 150.0 | 299.4 ± 454.9 | 22.9 ± 10.1 |
Coeff. Var (%) | 56.0 | 43.6 | 42.9 | 151.9 | 44.1 |
WHO | 500–1,000 | 500–1,000 | 500–1,000 | 500–1,000 | 500–1,000 |
NSDWQ(MPL) | 500 | 500 | 500 | 500 | 500 |
Electrical conductivity (μS/cm) | |||||
Range | 15–60 | 10–60 | 265–740 | 40–490 | 10–60 |
Mean ± SD | 31.3 ± 14.1 | 24.4 ± 10.2 | 429.4 ± 150.2 | 207.5 ± 147.5 | 31.3 ± 17.5 |
Coeff. Var (%) | 45.1 | 41.7 | 34.9 | 71.1 | 55.9 |
WHO | 500 | 500 | 500 | 500 | 500 |
NSDWQ(MPL) | 1,000 | 1,000 | 1,000 | 1,000 | 1,000 |
Turbidity (NTU) | |||||
Range | 6.9–23.9 | 0.09–1.67 | 0.01–3.82 | 0.17–1.55 | 0.01– 0.23 |
Mean ± SD | 14.8 ± 5.8 | 0.621 ± 0.585 | 1.88 ± 1.255 | 0.660 ± 0.52 | 0.09 ± 0.08 |
Coeff. Var (%) | 38.8 | 94.2 | 66.8 | 78.6 | 81.7 |
WHO | 5 | 5 | 5 | 5 | 5 |
NSDWQ(MPL) | 5 | 5 | 5 | 5 | 5 |
Parameter . | Source of water . | ||||
---|---|---|---|---|---|
River . | Rain . | Well . | Borehole . | Sachet . | |
pH | |||||
Range | 5.5–6.8 | 5.3–6.7 | 4.7– 6.8 | 4.5–6.4 | 5.0–6.6 |
Mean ± SD | 6.4 ± 0.39 | 5.9 ± 0.46 | 5.8 ± 0.6 | 5.3 ± 0.6 | 5.9 ± 0.5 |
Coeff. Var (%) | 6.14 | 7.77 | 10.38 | 11.33 | 8.54 |
WHO | 6.5–8.5 | 6.5–8.5 | 6.5–8.5 | 6.5–8.5 | 6.5–8.5 |
NSDWQ(MPL) | 6.5–8.5 | 6.5–8.5 | 6.5–8.5 | 6.5–8.5 | 6.5–8.5 |
Total dissolved solids (mg/l) | |||||
Range | 10–45 | 5–20 | 240– 680 | 25– 1,400 | 10–40 |
Mean ± SD | 23 ± 12.9 | 12.5 ± 5.5 | 349.5 ± 150.0 | 299.4 ± 454.9 | 22.9 ± 10.1 |
Coeff. Var (%) | 56.0 | 43.6 | 42.9 | 151.9 | 44.1 |
WHO | 500–1,000 | 500–1,000 | 500–1,000 | 500–1,000 | 500–1,000 |
NSDWQ(MPL) | 500 | 500 | 500 | 500 | 500 |
Electrical conductivity (μS/cm) | |||||
Range | 15–60 | 10–60 | 265–740 | 40–490 | 10–60 |
Mean ± SD | 31.3 ± 14.1 | 24.4 ± 10.2 | 429.4 ± 150.2 | 207.5 ± 147.5 | 31.3 ± 17.5 |
Coeff. Var (%) | 45.1 | 41.7 | 34.9 | 71.1 | 55.9 |
WHO | 500 | 500 | 500 | 500 | 500 |
NSDWQ(MPL) | 1,000 | 1,000 | 1,000 | 1,000 | 1,000 |
Turbidity (NTU) | |||||
Range | 6.9–23.9 | 0.09–1.67 | 0.01–3.82 | 0.17–1.55 | 0.01– 0.23 |
Mean ± SD | 14.8 ± 5.8 | 0.621 ± 0.585 | 1.88 ± 1.255 | 0.660 ± 0.52 | 0.09 ± 0.08 |
Coeff. Var (%) | 38.8 | 94.2 | 66.8 | 78.6 | 81.7 |
WHO | 5 | 5 | 5 | 5 | 5 |
NSDWQ(MPL) | 5 | 5 | 5 | 5 | 5 |
Coeff. Var, coefficient of variation; WHO MPL, World Health Organization Maximum Permissible Limit; NSDWQ MPL, Nigerian Standard for Drinking Water Quality Maximum Permissible Limit.
The TDSTDS ranged from 10 to 45 mg/l; 5 to 20 mg/l; 240 to 680 mg/l; 25 to 1,400 mg/l; and 10 to 40 mg/l for river, rain, well, borehole, and sachet water samples, respectively.
The range for maximum permissible limits of EC for the five water sources was below WHO and NSDWQ recommended levels. Similarly, the range for the maximum permissible limit of turbidity for the five water sources was below the WHO and NSDWQ recommended levels.
Table 4 shows the chemical parameters for the water sources investigated. All the water sources sampled had levels of chloride, calcium, iron, lead, copper, and cadmium lower than the WHO and NSDWQ maximum permissible limits.
Parameter . | Source of water . | ||||
---|---|---|---|---|---|
River . | Rain . | Well . | Borehole . | Sachet . | |
Chloride (mg/l) | |||||
Range | 3.42–12.72 | 1.39–9.53 | 22.1–68.2 | 6.35–47.7 | 1.08–9.54 |
Mean ± SD | 7.277 ± 3.114 | 4.25 ± 2.99 | 42.3 ± 15.2 | 18.5 ± 13.6 | 5.2 ± 2.8 |
Coeff. Var (%) | 42.8 | 70.3 | 35.9 | 73.5 | 54.1 |
WHO | 250 | 250 | 250 | 250 | 250 |
NSDWQ(MPL) | 250 | 250 | 250 | 250 | 250 |
Calcium (mg/l) | |||||
Range | <0.001 | <0.001 | 6.8– 28.4 | <0.001–46.7 | <0.001 |
Mean ± SD | 0.001 ± 0.000 | 0.001 ± 0.000 | 15.9 ± 7.6 | 6.9 ± 16.2 | 0.001 ± 0.000 |
Coeff. Var (%) | 0.00 | 0.00 | 47.9 | 232.4 | 0.00 |
WHO | 100 | 100 | 100 | 100 | 100 |
NSDWQ(MPL) | 75 | 75 | 75 | 75 | 75 |
Iron (mg/l) | |||||
Range | <0.001– 0.21 | <0.001 | <0.001 | <0.001 | <0.001 |
Mean ± SD | 0.404 ± 0.93 | 0.001 ± 0.000 | 0.033 ± 0.597 | 0.001 ± 0.000 | 0.001 ± 0.000 |
Coeff. Var (%) | 230.5 | 0.00 | 1,809.1 | 0.00 | 0.00 |
WHO | 0.3 | 0.3 | 0.3 | 0.3 | 0.3 |
NSDWQ(MPL) | 0.3 | 0.3 | 0.3 | 0.3 | 0.3 |
Lead (mg/l) | |||||
Range | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 |
Mean ± SD | 0.001 ± 0.000 | 0.001 ± 0.000 | 0.001 ± 0.000 | 0.001 ± 0.000 | 0.001 ± 0.000 |
Coeff. Var (%) | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 |
WHO | 0.001 | 0.001 | 0.001 | 0.001 | 0.001 |
NSDWQ(MPL) | 0.001 | 0.001 | 0.001 | 0.001 | 0.001 |
Copper (mg/l) | |||||
Range | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 |
Mean ± SD | 0.001 ± 0.000 | 0.001 ± 0.000 | 0.284 ± 0.05 | 0.001 ± 0.000 | 0.001 ± 0.000 |
Coeff. Var (%) | 0.00 | 0.00 | 17.96 | 0.00 | 0.00 |
WHO | 1 | 1 | 1 | 1 | 1 |
NSDWQ(MPL) | 1 | 1 | 1 | 1 | 1 |
Cadmium (mg/l) | |||||
Range | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 |
Mean ± SD | 0.017 ± 0.044 | 0.001 ± 0.000 | 0.001 ± 0.000 | 0.001 ± 0.000 | 0.001 ± 0.000 |
Coeff. Var (%) | 258.8 | 0.00 | 0.00 | 0.00 | 0.00 |
WHO | 0.003 | 0.003 | 0.003 | 0.003 | 0.003 |
NSDWQ(MPL) | 0.003 | 0.003 | 0.003 | 0.003 | 0.003 |
Parameter . | Source of water . | ||||
---|---|---|---|---|---|
River . | Rain . | Well . | Borehole . | Sachet . | |
Chloride (mg/l) | |||||
Range | 3.42–12.72 | 1.39–9.53 | 22.1–68.2 | 6.35–47.7 | 1.08–9.54 |
Mean ± SD | 7.277 ± 3.114 | 4.25 ± 2.99 | 42.3 ± 15.2 | 18.5 ± 13.6 | 5.2 ± 2.8 |
Coeff. Var (%) | 42.8 | 70.3 | 35.9 | 73.5 | 54.1 |
WHO | 250 | 250 | 250 | 250 | 250 |
NSDWQ(MPL) | 250 | 250 | 250 | 250 | 250 |
Calcium (mg/l) | |||||
Range | <0.001 | <0.001 | 6.8– 28.4 | <0.001–46.7 | <0.001 |
Mean ± SD | 0.001 ± 0.000 | 0.001 ± 0.000 | 15.9 ± 7.6 | 6.9 ± 16.2 | 0.001 ± 0.000 |
Coeff. Var (%) | 0.00 | 0.00 | 47.9 | 232.4 | 0.00 |
WHO | 100 | 100 | 100 | 100 | 100 |
NSDWQ(MPL) | 75 | 75 | 75 | 75 | 75 |
Iron (mg/l) | |||||
Range | <0.001– 0.21 | <0.001 | <0.001 | <0.001 | <0.001 |
Mean ± SD | 0.404 ± 0.93 | 0.001 ± 0.000 | 0.033 ± 0.597 | 0.001 ± 0.000 | 0.001 ± 0.000 |
Coeff. Var (%) | 230.5 | 0.00 | 1,809.1 | 0.00 | 0.00 |
WHO | 0.3 | 0.3 | 0.3 | 0.3 | 0.3 |
NSDWQ(MPL) | 0.3 | 0.3 | 0.3 | 0.3 | 0.3 |
Lead (mg/l) | |||||
Range | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 |
Mean ± SD | 0.001 ± 0.000 | 0.001 ± 0.000 | 0.001 ± 0.000 | 0.001 ± 0.000 | 0.001 ± 0.000 |
Coeff. Var (%) | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 |
WHO | 0.001 | 0.001 | 0.001 | 0.001 | 0.001 |
NSDWQ(MPL) | 0.001 | 0.001 | 0.001 | 0.001 | 0.001 |
Copper (mg/l) | |||||
Range | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 |
Mean ± SD | 0.001 ± 0.000 | 0.001 ± 0.000 | 0.284 ± 0.05 | 0.001 ± 0.000 | 0.001 ± 0.000 |
Coeff. Var (%) | 0.00 | 0.00 | 17.96 | 0.00 | 0.00 |
WHO | 1 | 1 | 1 | 1 | 1 |
NSDWQ(MPL) | 1 | 1 | 1 | 1 | 1 |
Cadmium (mg/l) | |||||
Range | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 |
Mean ± SD | 0.017 ± 0.044 | 0.001 ± 0.000 | 0.001 ± 0.000 | 0.001 ± 0.000 | 0.001 ± 0.000 |
Coeff. Var (%) | 258.8 | 0.00 | 0.00 | 0.00 | 0.00 |
WHO | 0.003 | 0.003 | 0.003 | 0.003 | 0.003 |
NSDWQ(MPL) | 0.003 | 0.003 | 0.003 | 0.003 | 0.003 |
Coeff. Var, coefficient of variation; WHO MPL, World Health Organization Maximum Permissible Limit; NSDWQ MPL, Nigerian Standard for Drinking Water Quality Maximum Permissible Limit.
The biological parameters of the five water sources sampled are shown in Table 5. All the water samples investigated had coliform counts except the borehole and sachet water samples, which had coliform counts that ranged from 0 to 30 (MPN/100 ml) and 0 to 170 (MPN/100 ml), respectively. Rain, borehole, and sachet water samples had coefficients of variation exceeding 100.0% in respect of the total coliform count of the samples investigated.
Total Coliform (MPN/100 ml) . | Source of water sample . | ||||
---|---|---|---|---|---|
River . | Rain . | Well . | Borehole . | Sachet . | |
Range | 300–2,800 | 20–9,000 | 50–140 | 0–30 | 0–170 |
Mean ± SD | 1,325 ± 926.9 | 1,268.1 ± 3,147.5 | 94.4 ± 28.5 | 8.750 ± 12.5 | 26.3 ± 59.7 |
Coeff. Var (%) | 69.96 | 248.2 | 30.2 | 142.5 | 227.6 |
WHO | 0 | 0 | 0 | 0 | 0 |
NSDWQ(MPL) | 0 | 0 | 0 | 0 | 0 |
Total Coliform (MPN/100 ml) . | Source of water sample . | ||||
---|---|---|---|---|---|
River . | Rain . | Well . | Borehole . | Sachet . | |
Range | 300–2,800 | 20–9,000 | 50–140 | 0–30 | 0–170 |
Mean ± SD | 1,325 ± 926.9 | 1,268.1 ± 3,147.5 | 94.4 ± 28.5 | 8.750 ± 12.5 | 26.3 ± 59.7 |
Coeff. Var (%) | 69.96 | 248.2 | 30.2 | 142.5 | 227.6 |
WHO | 0 | 0 | 0 | 0 | 0 |
NSDWQ(MPL) | 0 | 0 | 0 | 0 | 0 |
Coeff. Var, coefficient of variation; WHO MPL, World Health Organization Maximum Permissible Limit; NSDWQ MPL, Nigerian Standard for Drinking Water Quality Maximum Permissible Limit.
Table 6 shows the results of one-way ANOVA with Tukey post hoc tests to determine whether there were statistically significant differences in the means of parameters such as pH, TDS, EC, turbidity, chloride, calcium, iron, lead, copper, cadmium, and total coliform between the various drinking water sources. The test revealed a significant mean difference in pH between river and borehole (p = 0.02), TDS; between the river and well (p = 0.033), rain and well (p = 0.026), and well and sachet (p = 0.033); EC; between the river and well (p = 0.0001), river and borehole (p = 0.004), rain and well (p 0.0001), well and borehole (p 0.0001), sachet and well (p = 0.001). There were no significant mean differences for Fe, Cu, Cd, and total coliform count between the different water sources. There were significant mean differences among other parameters of water between the different water sources.
Parameter . | (I) Source . | (J) Source . | Mean Difference (I–J) . | p-value . |
---|---|---|---|---|
pH | River | Borehole | 1.08 | 0.002 |
TDS | River | Well | − 326.50 | 0.033 |
Rain | Well | − 337.00 | 0.026 | |
Sachet | Well | − 326.63 | 0.033 | |
EC | River | Well | − 398.13 | < 0.0001 |
Rain | Well | − 405.00 | < 0.0001 | |
Borehole | − 183.13 | 0.004 | ||
Well | Borehole | 221.88 | < 0.0001 | |
Sachet | 398.13 | 0.001 | ||
Borehole | River | 176.25 | 0.006 | |
Sachet | 176.25 | 0.006 | ||
Turbidity | River | Rain | 14.22 | < 0.0001 |
Well | 12.96 | < 0.0001 | ||
Borehole | 14.18 | < 0.0001 | ||
Sachet | 14.75 | < 0.0001 | ||
Cl | Sachet | Well | − 37.07 | < 0.0001 |
River | Well | − 35.02 | < 0.0001 | |
Rain | Well | − 38.05 | < 0.0001 | |
Rain | Borehole | − 14.26 | 0.035 | |
Well | Borehole | − 14.20 | 0.035 | |
Ca | Well | Rain | 15.94 | 0.003 |
Sachet | 5.94 | 0.003 |
Parameter . | (I) Source . | (J) Source . | Mean Difference (I–J) . | p-value . |
---|---|---|---|---|
pH | River | Borehole | 1.08 | 0.002 |
TDS | River | Well | − 326.50 | 0.033 |
Rain | Well | − 337.00 | 0.026 | |
Sachet | Well | − 326.63 | 0.033 | |
EC | River | Well | − 398.13 | < 0.0001 |
Rain | Well | − 405.00 | < 0.0001 | |
Borehole | − 183.13 | 0.004 | ||
Well | Borehole | 221.88 | < 0.0001 | |
Sachet | 398.13 | 0.001 | ||
Borehole | River | 176.25 | 0.006 | |
Sachet | 176.25 | 0.006 | ||
Turbidity | River | Rain | 14.22 | < 0.0001 |
Well | 12.96 | < 0.0001 | ||
Borehole | 14.18 | < 0.0001 | ||
Sachet | 14.75 | < 0.0001 | ||
Cl | Sachet | Well | − 37.07 | < 0.0001 |
River | Well | − 35.02 | < 0.0001 | |
Rain | Well | − 38.05 | < 0.0001 | |
Rain | Borehole | − 14.26 | 0.035 | |
Well | Borehole | − 14.20 | 0.035 | |
Ca | Well | Rain | 15.94 | 0.003 |
Sachet | 5.94 | 0.003 |
DISCUSSION
Natural and human activities induce changes in water quality that are mostly observed in its physical, chemical, and microbiological parameters (Martiez-Santos et al. 2017). The transmission of waterborne disease is still a subject of importance, despite global attempts and up-to-the minute technology that is employed for the provision of potable drinking water (ADB 2010).
The probable causes of pollution of water sources in Sapele LGA include urbanization, lack of a proper or appropriate waste management system, unprotected wells, poor handling of fetchers, oil spillage, and indiscriminate dumping of solid waste (refuse) and sewage on drainage channels, as well as the practice of open defecation, especially in the rural areas.
pH is considered one of the most imperative water quality variables. pH defines the acidity or alkalinity of water. A specimen is deemed acidic if the pH is below 7.0 and alkaline if the pH is above 7.0, based on the pH meter scale. The pH values show that the different sources, both surface and groundwater, were acidic. The acidity may be attributed to the upsurge in acidic precipitate induced by incessant gas flaring and waste disposal, as well as the impact of oil spills on the soil and water bodies in the area. This finding is buttressed by previous studies, which have revealed that 98% of all global groundwater is influenced by calcium and bicarbonate ions occasioned by calcium trioxocarbonate (IV) erosion in the watersheds and subterranean water beds (WHO 2011). The pH results of this study, however, differ from those of Luvhimbi et al. (2022), who reported a pH of 7.15–9.92, indicating an alkaline water as opposed to the acidic water observed in this study. In this study, only the pH values of samples R5, R7, and W7 were found to be within the admissible range of WHO and NSDWQ. Water with a low pH has corrosive properties, and acidic water could induce the gradual chemical erosion of water mains and conduits in domestic water systems. If not properly managed, it could induce the pollution of drinking water and have a negative impact on its taste and colour (WHO 2012). Alkaline water exhibits disinfection capacity in water. Sodium sulphate and calcium carbonate can be employed to modify low pH values to conventional or acceptable values. Considering the long-term adverse health consequences of employing chemical substances such as sodium sulphate and sodium bicarbonate to increase acidic pH levels to slightly alkaline to make it potable for drinking, a natural substance composed of environmental elements extracted from silica using the thermal fusion technique has been proposed as an alternative method for managing acidic water (water with low pH) (Yehia & Said 2021). In their study, Yehia and Said proposed that the combination of natural material SiO2 and fusion technology produces a biofield in the region of 80 cm, which would have an effect on the oxonium ions and, as a result, modify the water into an alkaline state due to the active bond formed between silica and sodium atoms (Yehia & Said 2021). Also, the coefficients of variation of pH values for the various water sources in our study were comparatively low. This indicates a low degree of variation in pH among the different sources. Water with a pH above 11 and below 4 is known to induce skin and eye irritation and can exacerbate existing skin diseases (Ezeribe et al. 2012).
TDS are the mineral salts and minute quantities of natural substances that are contained in water as solutions (WHO & FAO 2003). Water has the capacity to solvate a broad range of man-made minerals and some natural minerals or salts, such as sulphates, magnesium, sodium, bicarbonates, chlorides, and so on. These minerals create an undesirable colour and taste in water (Meride & Ayenew 2016). A high TDS value in water indicates that it has been heavily mineralized. The TDS values obtained in this study for all sample sources were below the maximal admissible ceiling for TDS as stipulated by WHO and NSDWQ. The TDS values for well water samples W1, W2, W4, and W5 were close to the values obtained for well water specimens in a study conducted in Gombe State, Nigeria (EPA 2011). Universally, water with TDS values less than 500 mg/l is regarded as water of improved quality. TDS levels exceeding the WHO and NSDWQ maximal admissible ceilings can precipitate corrosion, reduce the solubility of gases, enhance water density, and make water unsuitable for drinking. EC is the capacity of any medium-water in this scenario to conduct electric current. The water is able to conduct current owing to the presence of dissolved solids such as magnesium, chloride, and calcium chloride (Rahmanian et al. 2015).
The EC values obtained for all samples in this study were within the maximal permissible ceilings of the WHO and NSDWQ except for the well (W6) sample, which had a value of 740 μS/cm which was above the WHO threshold of 500 μS/cm but was within the NSDWQ ceiling of 1,000 μS/cm. This finding is at variance with the study of Elahcene et al. (2019), which reported EC levels that exceeded WHO and NSDWQ standard values. The EC of water is occasioned by the ionic constituent of the sample, which in turn is determined by the dissolved salts (Jatoi et al. 2018). Generally, EC increases with temperature but has no explicit health effects. However, high conductivity is an indication of the presence of contaminants in the water.
Turbidity is primarily due to the presence of finely suspended particles and colloids. It is also described as the cloudiness of water induced by different particles and is another significant variable in drinking water assessment. It is also associated with the content of disease-causing organisms in water, which may result from soil runoff (Rahmanian et al. 2015). The values for all river water samples were above the maximal admissible ceiling of 5 NTU for WHO and NSDWQ benchmarks, suggesting an unsatisfactory condition of the water. When water is turbid, it often demonstrates the presence of bacteria, which may have deleterious effects on health when consumed (Pakistan EPA 2010).
The chloride concentration levels were regarded as acceptable and satisfactory considering the fact that they were below the maximum admissible ceiling stipulated by WHO and NSDWQ. The results obtained for chloride in this study are inconsistent with the results obtained by Adamou et al. (2020) in their study, in which they reported chloride levels for some of the water samples exceeding the WHO threshold. The presence of chloride in drinking water can be an indication of contamination, with probable origins being chloride from seawater, effluvium from industries, and sludge. Also, studies have reported probable sources of chloride in drinking water to include cross-contamination of sewage, mechanical effluvium, and surface runoff from cities and salty encroachment, as well as from edible salt (Aremu et al. 2010). A high amount of chloride in water corrodes metallic materials.
Water hardness is caused by the presence of cations in water, particularly calcium and magnesium cations, which cause the furring of kettles or boilers when heated. The values obtained for the cations in all samples analysed were within the maximum admissible ceiling of WHO and NSDWQ except for river sample R1, which had an iron value above the recommended value, and river sample R7, which had cadmium and iron values also exceeding the recommended thresholds of 0.3 and 0.003 mg/l for iron and cadmium, respectively, according to WHO and NSWQ standards. The slightly high cadmium level may be attributed to industrial effluents from the operations of oil firms located at Site R7 of the study area. Cadmium is present naturally in rocks and soils and finds its way into water when it comes in contact with soft groundwater or surface water. Furthermore, it may be introduced by industrial activities such as sewage sludge disposal, and fertilizer, electroplating and fossil fuel combustion, pigments, plastic stabilizers, paints, mining, and smelting operations (Rahmanian et al. 2015). Sources of cadmium contamination in the oil industry include stack emissions from refineries or emissions from the combustion of hydrocarbon fuels (Stigtera et al. 2000).
High levels of cadmium have a toxic effect in the body, leading to complications such as cancer, renal problems, neurological, respiratory, gastrointestinal, and reproductive health problems. Also, the mean concentrations of calcium, iron, lead, copper, and cadmium were negligible, as shown in this study. Iron is noxious owing to the terrible taste it induces in water. High iron concentration levels could precipitate iron-dependent microorganisms that have the capacity to induce deterioration in the quality of water through the evolution of slime and the production of objectionable odour. The concentration of lead, which was within the WHO and NSDWQ maximum admissible ceiling, demonstrates that the samples from the five different sources were not exposed to improper dumping of objects such as lead batteries. Also, copper is known to play a key role in enzymatic activities (Ahmed et al. 2010). Calcium at an acceptable level in the body is important in muscle contraction, oocyte activation, building strong bones and teeth, conduction of nerve impulses, etc.
The fact that almost two-thirds of all the sampled sources of water had high coliform values is worrisome, as this makes the water unhealthy and unsuitable for consumption, except when it is adequately treated with chlorine or other treatment methods such as boiling and filtration, coagulation/flocculation using alum, etc. The presence of coliform is an indication of pollution of these sources by bacteria, possibly E. coli. The massive contamination of the water accessible to inhabitants of Sapele LGA with coliform bacteria indicates that the water is not potable and therefore unfit for consumption. Water unsuitable for drinking purposes must be appropriately treated prior to utilization. This aligns perfectly with the assessment of physicochemical variables in relation to the potability of water as defined by WHO (2017).
The presence of high concentrations of coliform in half of the rainwater samples could be attributed to the method of collection, which was the roof-collected rainwater (RCRW) technique. Several studies have stated that RCRW for drinking or domiciliary utilization has been linked to bacterial-related morbidity threats or epidemics (Kaushika et al. 2012; Heijnsbergen et al. 2014; Lake et al. 2021). The presence of coliform in one-quarter of the sachet water samples suggests inadequate purification of some sachet water samples. Additionally, the presence of coliform in a little more than one-third of the borehole samples and all the well water samples may be attributed to the close siting of the boreholes and wells to septic tanks. This is at variance with WHO recommendations, which state that a well or borehole must be sited at least 30 m away from any source of contamination. Because faecal matter can easily flow into water from closet sewers, the insanitary conditions of the wells investigated may indicate possible faecal contamination of the water sources. This seepage can be prevented by increasing the distance of the water sources from the source of contamination (Akinbile et al. 2016). It has been stated that contagious waterborne diseases are common in developing countries and that unless drinking water reticulation systems are enhanced, the hope of stemming the transmission of infectious disease is low (Alamgir et al. 2019). Coliforms in drinking water may encourage the transmission of waterborne illnesses such as giardiasis, cholera, typhoid fever, gastroenteritis, dysentery, etc.
This study is different from the bacterial study of Adesakin et al. (2020), which conducted bacterial isolation tests in contrast to the coliform count analysis conducted in this study. However, in both studies, the presence of bacteria was observed in the water samples. It is suggested that further studies on the drinking water quality status in Sapele LGA be conducted, especially on the probable pollution of drinking water sources by heavy metals in oil-producing communities in the LGA based on the discovery of slightly higher cadmium content in one of the samples (R7). It is also suggested that a further study be carried out on the isolation of coliforms to identify the precise bacteria present in drinking water sources in the LGA based on the results of the coliform count conducted in this study.
CONCLUSION
This study investigated the quality status of drinking water from varied sources in Sapele LGA. The findings of the study indicate that most of the physicochemical parameter values were within the maximal admissible ceiling stipulated by WHO and NSDWQ. A maximum total coliform count of 9,000 MPN/100 ml and a minimum count of 10 MPN/100 ml were detected in all the samples, suggesting the presence of bacteria in the water sample sources.
Also, in this study, the turbidity values for rain water samples were all above the recommended WHO and NSDWQ guidelines. The iron content of one of the river water samples (R1), which was 2.702 mg/l, was above the maximal admissible ceiling of the WHO and NSDWQ standards. The cadmium content of river water R7 exceeded the WHO and NSDWQ permissible ceilings slightly. The surface, groundwater, and sachet water sources in the study area had an enormous amount of coliforms compared to the WHO and NSDWQ benchmarks. Sachet water was insignificantly polluted; therefore, it can be considered potable for drinking purposes in comparison with other water sources. The comparative analyses of the physicochemical and bacteriological properties of the drinking water in the LGA showed that some of the water variables had values above the stipulated values of the WHO and NSDWQ. On the basis of the outcomes of this study, it can be established that some of the water sources in Sapele LGA are contaminated and therefore a potential source of health risk when consumed. This may suggest that the study area is not on track to achieving SDG 6 target 6.1. It is recommended that consumers of water from these different origins employ measures to purify their drinking water to forestall potential health risks associated with the use of polluted water. Overall, the findings of this study will serve as an invaluable reference for future studies on drinking water quality assessment in Sapele LGA. The findings of this study will also have application in efficacious drinking water quality monitoring through the provision of data that can be employed for the water quality index (WQI) of different drinking water sources in the LGA, which by extension will help policy makers and stakeholders in the water sector furnish the LGA with guidelines and advisories on potable water consumption to prevent water-related disease outbreaks.
DATA AVAILABILITY STATEMENT
All relevant data are included in the paper or its Supplementary Information.
CONFLICT OF INTEREST
The authors declare there is no conflict.