Ensuring availability and sustainable management of water and sanitation for all by 2030 is Goal 6 of the Sustainable Development Goals (SDGs). Since developing countries especially in Africa would struggle to meet this target, this study was conceived. Hence, the study was designed to assess the water quality for physiochemical parameters around a mined out site in southern Sierra Leone with the view to determine their levels, determine related associations among indicators and explore environmental forensic options. A finite population correction factor was used to identify fifty (50) groundwater sources from one hundred and fifty two (152) in nine (9) sections of Moriba Town, in Moyamba District, Sierra Leone which constitute the sample size. The study assessed sixteen (16) physical and chemical indicators across the defined boundary of the sample size. Results indicated that almost 80% of all the indicators were in good agreement with water quality standards with the exception of three. Turbidity correlated strongly with , Al and and almost all other indicators did not show meaningful association. High values with significant variance of water quality indicators of physical to chemical ratio were observed for pH, temperature, electrical conductivity (EC) and total dissolved solids (TDS) but no such observation was noted for turbidity. On the whole, the water quality was judged to be good, although more pro active actions were encouraged by the local people and the mining company so as to reduce contamination in some areas.
It is estimated that more than a billion people worldwide do not have access to safe drinking water with more than two million die each year of water related diseases [
A handful of studies on ground water quality in Africa have been reported in the wider literature [
One of the corporate social responsibilities of Sierra Rutile Limited Mining Company is to ensure the provision of safe drinking water facilities for the various mining communities. The company mostly ensures that frequent awareness raising sessions are held to promote good hygiene, water and sanitation practices in order to enhance water quality and also embark on the monitoring of the sources though on a relatively small scale. Despite the gains that the company has made, monitoring was confined to few selected facilities. For this reason, the need for a much bigger monitoring scheme for groundwater sources around a mined out community was conceivable so as to complement the effort of the company in assessing their environmental performances. This project therefore seeks to holistically investigate by extending to a wider area whether or not these measures put in place by the company are sufficient enough to maintain a high water quality standard that is fit for human consumption. Monitoring water quality is essential to determine the water quality status and to improve the environmental conditions and the related public health. Hence, the main objectives of the study were to: (i) evaluate the physico-chemical indicators of groundwater drinking sources at Moriba Town; (ii) deduce the relationship among the water quality indices studied and (iii) explore baseline environmental forensic options between the physical and chemical indicators. Findings of this work would be useful to many organizations including Sierra Rutile Limited, country planners, Environmental Protection Agency Sierra Leone (EPA-SL), international and local nongovernmental organizations.
The study area was mainly Moriba Town (See
typically found in mineral deposits in coastal regions and has been mined in southwest Sierra Leone since the early 1970’s. Moriba Town is partially surrounded by very large artificial lakes left behind after the dredging activity of the company. As a result, there is also a high possibility for the wells to experience intrusion in many locations.
Prior to embarking on the sampling, a listing exercise of all drinking water sources was identified from the various sections within Moriba Town. The study was cross-sectional in which a stratified kind of random sampling method was employed after zoning the entire township into sections or strata from which the required sample size was determined. Sectioning was according to the different settlement patterns. A total of 152 drinking water sources were identified from the listing exercise across the 9 sections, namely; New Site (NST), Zimbabwe (ZIM), Moriba Town Gbangbatoihun (MTG), Gbangbatoihun (GBA), Nyokorvulahun/On the Sand 2 (NYO), Mbelebu/Central (MBE), Tokpoi Town/On the Sand 1 (OTK), Mogbewa 2 (MOG), and Mesima (MES). Two (2) of the sources identified were later verified to be non-drinking sources and were therefore not included in the batch of samples. In determining the overall sample size (S), a sample size determination using a finite population corrector factor formulary was used. (Source: www.qualtrics.co).
where; S = Overall sample size, Ni = Initial estimate (75), Nt = Total Population (152),
where S = Sample size per section, Nf = Final estimated samples, Qs = Quantity per section and Nt = Total Population.
The quantity of samples to be considered for randomization per section was determined from the expression shown.
This however resulted in a net sample size of fifty (50). Hand dug well water samples were thus collected from 50 locations across the nine (9) sections or zones for the determination of physiochemical parameters. The sampling was done in the same month of July-2016 on a daily basis.
A 500 ml high density polyethylene bottle was used to collect samples. Polyethylene bottle was chosen due to its availability, resistance to breakage and light weight. The samples were collected using the local collecting containers available at each sampling point. Indigenous sample collection containers were used to fetch the water from the wells. The 500 ml high density polyethylene sample container was rinsed with the sample before pouring it into each container. Each bottle was appropriately labeled with the following information affixed location, sample code number and date. Samples were then placed in a Coleman stacked with ice packs. The process was repeated at all the sites before being transported to the laboratory where they were refrigerated until analysis using Standard Operating Procedures (SOPs). All samples were taken to the Sierra Rutile Limited laboratory for analysis.
The physical parameters investigated include pH, temperature, turbidity, electrical conductivity (EC) and total dissolved solids (TDS) and that for the chemical were chloride, fluoride, free iron, copper, phosphate, manganese, aluminum, ammonia, nitrate, nitrite and sulphate. The physical parameters were immediately measured in situ using a combined Accumet AC 85 Fischer Scientific pH, temperature and conductivity meter. The meter was calibrated before and during the field campaign using buffer solutions recommended by the manufacturer.
All of the chemical parameters were analyzed using Wagtech Potalab Photometer 9500 (brand name ECOSENSE). The standard operating procedures for all the chemical species were followed during analyses in the laboratory. For instance, the Wagtech chlorine test uses diethyl-p-pheneylenediamine (DPD) which is recognized as the standard test for chlorine and other disinfectant residuals. Free chlorine reacts with DPD in buffer solution to produce a pink coloration. The intensity of the colour is proportional to the free chlorine concentration. Subsequent additions of excess potassium iodide induce a further reaction with any combined chlorine present. In the Wagtech DPD method, the reagents are provided in tablet forms for maximum convenience and simplicity. The colour intensities are measured using a Wagtech photometer. A similar procedure was followed for all the chemical indicators and values reported in the acceptable units.
The study design was purely quantitative which warranted the generation of numeric data. Data generated were subjected to descriptive statistics by summarizing the mean, standard deviation and range of values. The World Health Organization water quality standards were used to compare the threshold of values for this study and same standard values for WHO. A hypothesized threshold at a significance level of 5% was used to test the claim that the observed values were not different from WHO standards. Multivariate statistical technique in the form of Pearson correlation coefficient was used to establish relationship among the physiochemical indicators in other to ascertain whether parameters were from the same origin or having similar pathway of formation or possess the same physical or chemical transformation. A correlation coefficient of 0.5 was taken as a reasonable cut off point to depict association. Individual mean values of the physical and chemical parameters/species were subjected to physio- chemical ratios in order to predict chemical species from simple inexpensive and user friendly probes of physical indicators. Reported results and figures were conducted using JMP 8 software.
Descriptive statistics was used to compare measured variables with WHO water quality standards. Results of the study are presented in the form of mean, standard deviation, minimum and maximum values as reflected in
pH | Temp. (˚C) | Turb (NTU) | EC (µS/cm) | TDS (mg/L) | Cl (mg/L) | F (mg/L) | Fe (mg/L) | NH3 (mg/L) | Cu (mg/L) | Mn (mg/L) | Al (mg/L) | ||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
NST n = 4 | Avg. | 4.62 | 28.85 | 1.40 | 31.75 | 15.88 | 0.04 | 1.61 | 0.02 | 0.01 | 0.22 | 0.21 | 0.01 | 0.14 | 0.07 | 26.75 | 5.00 |
Stdev | 0.17 | 0.42 | 0.54 | 1.58 | 0.82 | 0.03 | 0.04 | 0.01 | 0.00 | 0.15 | 0.08 | 0.00 | 0.03 | 0.06 | 4.27 | 2.45 | |
Max. | 4.84 | 29.30 | 1.88 | 34.10 | 17.10 | 0.07 | 1.65 | 0.02 | 0.01 | 0.42 | 0.28 | 0.01 | 0.18 | 0.12 | 32.00 | 8.00 | |
Min. | 4.44 | 28.30 | 0.90 | 30.80 | 15.40 | 0.01 | 1.55 | 0.01 | N/D | 0.08 | 0.10 | 0.01 | 0.10 | 0.01 | 22.00 | 2.00 | |
ZIM n = 4 | Avg. | 5.17 | 26.98 | 1.04 | 35.25 | 17.49 | 0.02 | 0.46 | 0.02 | 0.03 | 0.05 | 0.29 | 0.02 | 0.14 | 0.09 | 21.97 | 5.75 |
Stdev | 0.49 | 1.09 | 0.44 | 14.83 | 7.30 | 0.01 | 0.76 | 0.01 | 0.05 | 0.05 | 0.16 | 0.03 | 0.03 | 0.04 | 14.43 | 4.92 | |
Max. | 5.71 | 28.60 | 1.61 | 48.50 | 23.80 | 0.03 | 1.60 | 0.04 | 0.10 | 0.12 | 0.52 | 0.07 | 0.18 | 0.15 | 33.00 | 13.00 | |
Min. | 4.54 | 26.30 | 0.64 | 18.19 | 9.07 | N/D | 0.01 | 0.01 | N/D | N/D | 0.18 | 0.01 | 0.11 | 0.05 | 0.90 | 2.00 | |
MTG n = 5 | Avg. | 5.64 | 27.58 | 2.71 | 30.50 | 15.11 | 0.03 | 0.24 | 0.02 | 0.01 | 0.22 | 2.20 | 0.01 | 0.06 | 0.05 | 24.50 | 3.50 |
Stdev | 0.03 | 0.43 | 1.97 | 18.88 | 9.57 | 0.02 | 0.20 | 0.01 | 0.00 | 0.16 | 2.22 | 0.00 | 0.05 | 0.04 | 15.81 | 1.29 | |
Max. | 5.67 | 28.10 | 5.36 | 47.00 | 23.50 | 0.04 | 0.48 | 0.02 | 0.01 | 0.40 | 5.50 | 0.01 | 0.10 | 0.08 | 35.00 | 5.00 | |
Min. | 5.60 | 27.10 | 0.88 | 13.85 | 6.74 | 0.01 | 0.06 | 0.01 | N/D | 0.04 | 0.83 | 0.01 | 0.02 | 0.01 | 0.99 | 2.00 | |
GBA n = 5 | Avg. | 4.70 | 35.32 | 3.38 | 22.25 | 12.02 | 0.18 | 1.35 | 0.07 | 0.01 | 0.24 | 0.32 | 0.01 | 0.11 | 0.06 | 31.20 | 4.40 |
Stdev | 0.16 | 5.53 | 3.36 | 11.08 | 6.45 | 0.29 | 0.75 | 0.10 | 0.00 | 0.16 | 0.07 | 0.00 | 0.05 | 0.04 | 4.21 | 0.55 | |
Max. | 4.90 | 44.40 | 9.22 | 37.30 | 18.80 | 0.70 | 1.80 | 0.25 | 0.02 | 0.39 | 0.40 | 0.01 | 0.16 | 0.10 | 36.00 | 5.00 | |
Min. | 4.52 | 30.30 | 1.05 | 9.42 | 4.71 | 0.01 | 0.01 | 0.01 | N/D | 0.02 | 0.25 | 0.01 | 0.02 | 0.01 | 25.00 | 4.00 | |
NYO n = 8 | Avg. | 4.77 | 26.47 | 1.16 | 30.96 | 15.44 | 0.04 | 0.03 | 0.01 | 0.02 | 0.08 | 0.68 | 0.01 | 0.10 | 0.02 | 28.89 | 3.28 |
Stdev | 0.48 | 1.41 | 0.71 | 14.39 | 7.17 | 0.04 | 0.03 | 0.01 | 0.03 | 0.07 | 0.52 | 0.00 | 0.07 | 0.01 | 4.86 | 3.28 | |
Max. | 5.59 | 28.60 | 2.72 | 56.50 | 28.20 | 0.13 | 0.11 | 0.05 | 0.10 | 0.20 | 1.55 | 0.02 | 0.26 | 0.03 | 36.00 | 10.00 | |
Min. | 4.32 | 25.00 | 0.39 | 12.62 | 6.28 | N/D | N/D | N/D | N/D | N/D | 0.20 | 0.01 | 0.03 | 0.01 | 22.00 | 0.50 | |
MBE n = 8 | Avg. | 5.59 | 28.06 | 45.34 | 102.90 | 51.28 | 0.73 | 0.02 | 0.76 | 0.02 | 0.31 | 1.23 | 0.01 | 0.22 | 0.11 | 22.65 | 7.50 |
Stdev | 0.66 | 1.48 | 121.90 | 114.15 | 56.76 | 1.93 | 0.02 | 2.12 | 0.02 | 0.34 | 2.16 | 0.00 | 0.24 | 0.23 | 14.09 | 8.86 | |
Max. | 7.04 | 30.50 | 347.00 | 366.00 | 182.00 | 5.50 | 0.06 | 6.00 | 0.05 | 1.05 | 6.50 | 0.02 | 0.80 | 0.68 | 35.00 | 27.00 | |
Min. | 4.76 | 26.00 | 0.53 | 22.10 | 11.00 | 0.01 | N/D | N/D | N/D | 0.04 | 0.20 | 0.01 | 0.06 | 0.01 | 0.06 | N/D | |
OTK n = 8 | Avg. | 5.40 | 27.91 | 2.11 | 20.59 | 13.04 | 0.15 | 0.20 | 0.01 | 0.01 | 0.10 | 1.17 | 0.01 | 0.04 | 0.07 | 14.47 | 2.57 |
Stdev | 0.39 | 2.50 | 1.05 | 9.77 | 7.21 | 0.31 | 0.43 | 0.01 | 0.00 | 0.10 | 1.92 | 0.00 | 0.03 | 0.05 | 13.25 | 1.99 | |
Max. | 5.99 | 30.40 | 3.72 | 39.50 | 25.70 | 0.84 | 1.18 | 0.02 | 0.01 | 0.28 | 5.50 | 0.01 | 0.10 | 0.12 | 28.00 | 5.00 | |
Min. | 4.77 | 22.60 | 0.72 | 8.48 | 4.25 | 0.01 | N/D | 0.01 | N/D | N/D | 0.24 | 0.01 | 0.01 | 0.01 | 0.02 | N/D | |
MOG n = 4 | Avg. | 4.56 | 27.68 | 0.88 | 42.28 | 21.15 | 0.03 | 1.17 | 0.02 | 0.01 | 0.17 | 0.40 | 0.01 | 0.13 | 0.07 | 27.25 | 3.00 |
Stdev | 0.08 | 1.61 | 0.54 | 14.16 | 7.05 | 0.02 | 0.75 | 0.01 | 0.00 | 0.11 | 0.08 | 0.00 | 0.07 | 0.04 | 4.35 | 0.82 | |
Max. | 4.62 | 29.30 | 1.54 | 61.00 | 30.40 | 0.05 | 1.70 | 0.03 | 0.01 | 0.34 | 0.50 | 0.01 | 0.21 | 0.11 | 33.00 | 4.00 | |
Min. | 4.45 | 26.10 | 0.22 | 29.20 | 14.60 | 0.01 | 0.08 | 0.01 | N/D | 0.10 | 0.30 | 0.01 | 0.06 | 0.03 | 23.00 | 2.00 | |
MES n = 5 | Avg. | 5.51 | 29.54 | 1.09 | 106.90 | 53.16 | 0.01 | 0.68 | 0.01 | 0.01 | 0.10 | 0.27 | 0.01 | 0.20 | 0.06 | 26.00 | 5.40 |
Stdev | 0.58 | 1.35 | 0.78 | 72.68 | 35.55 | 0.00 | 0.92 | 0.01 | 0.00 | 0.07 | 0.10 | 0.00 | 0.16 | 0.05 | 2.92 | 2.79 | |
Max. | 6.52 | 30.80 | 2.36 | 191.00 | 92.60 | 0.02 | 1.80 | 0.02 | 0.01 | 0.18 | 0.43 | 0.01 | 0.37 | 0.14 | 30.00 | 10.00 | |
Min. | 5.11 | 27.60 | 0.55 | 31.40 | 15.80 | N/D | N/D | N/D | N/D | 0.04 | 0.15 | 0.01 | 0.01 | 0.01 | 22.00 | 3.00 |
Avg. = average; Stdev = standard deviation; Max. = maximum; Min. = minimum; pH = potential of hydrogen; Temp. = temperature; Turb = turbidity; EC = electrical conductivity; TDS = total dissolved solids; NST = New site; ZIM = Zimbabwe; MTG = Moriba Town Gbangbatoihun; GBA = Gbangbatoihun; NYO = Nyokorvulahun; MBE = Mbellebu; OTK = On the Sand/Tokpoi Town; MOG = Mogbewa 2; MES = Messima; N/D = Not detectable.
Avg. | SD | Max. | Min. | P value | WHO Standard | |
---|---|---|---|---|---|---|
pH | 5.13 | 0.58 | 7.04 | 4.32 | <0.001 | 6.5 - 8.5 |
Temp. (˚C) | 28.53 | 3.21 | 44.4 | 22.6 | - | - |
Turb (NTU) | 8.69 | 48.84 | 347 | 0.22 | 0.297 | <5.0 |
EC (µS/cm) | 49.02 | 59.43 | 366 | 8.48 | <0.001 | 450 |
TDS (mg/L) | 24.9 | 29.36 | 182 | 4.25 | <0.001 | 500 |
Cl (mg/L) | 0.17 | 0.78 | 5.5 | N/D | <0.001 | 0.3 - 5.0 |
F (mg/L) | 0.52 | 0.72 | 1.8 | N/D | <0.001 | <1.5 |
Fe (mg/L) | 0.14 | 0.85 | 6.0 | N/D | 0.151 | 0.3 |
NH3 (mg/L) | 0.02 | 0.02 | 0.1 | N/D | <0.001 | 1.5 - 35 |
Cu (mg/L) | 0.16 | 0.18 | 1.05 | N/D | <0.001 | 1.0 - 2.0 |
0.79 | 1.34 | 6.5 | 0.1 | - | - | |
Mn (mg/L) | 0.01 | 0.01 | 0.07 | 0.01 | <0.001 | <0.1 |
Al (mg/L) | 0.13 | 0.12 | 0.8 | 0.01 | <0.001 | 0.2 |
0.06 | 0.1 | 0.68 | 0.01 | <0.001 | 3 | |
24.61 | 10.54 | 36 | 0.02 | <0.001 | 10 | |
4.51 | 4.35 | 27 | 0.01 | <0.001 | <250.0 |
Avg. = average; SD = standard deviation; Max. = maximum; Min. = minimum; pH = potential of hydrogen; Temp. = temperature; Turb = turbidity; EC = electrical conductivity; TDS = total dissolved solids. (˚C) = degree Celsius; NTU = nephelometric turbidity unit; µS/cm = micro Siemens per centimeter; mg/L = milligrams per liter. There were no guideline values for indicators with blank spaces.
character with the strongest acid content of 4.32. The evidence of strong mineral acids (
Nearly 97% of samples exhibit good chloride content. Even though the limits of chloride have been mostly reduced to the physical approach (taste), there have been no adverse health effects on humans who are exposed to high dose of
Almost all the samples (>95) for Al, Cu and Mn trace metals were in good agreement with guideline standards with few exceptions for Al. Being a mining environment for bauxite, it is unsurprising to observe levels of Al which are in excess of WHO standard. Generally, the existence of heavy metals in ground water is in the form of colloidal, particulate or dissolved phases with either natural of anthropogenic origin [
pH | Temp. | Turbidity | EC | TDS | Cl | F | Fe | NH3 | Cu | Mn | Al | |||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
pH | 1.0000 | |||||||||||||||
Temp. | −0.1440 | 1.0000 | ||||||||||||||
Turbidity | 0.4796 | −0.1024 | 1.0000 | |||||||||||||
EC | 0.2382 | −0.0516 | 0.2201 | 1.0000 | ||||||||||||
TDS | 0.2525 | −0.0413 | 0.2201 | 0.9955 | 1.0000 | |||||||||||
Cl | 0.1913 | −0.0265 | −0.0270 | 0.0222 | 0.0193 | 1.0000 | ||||||||||
F | −0.3141 | 0.5576 | −0.1175 | −0.2168 | −0.2227 | −0.1148 | 1.0000 | |||||||||
Fe | −0.0991 | 0.0997 | −0.0293 | −0.0263 | −0.0295 | −0.0343 | −0.1172 | 1.0000 | ||||||||
NH3 | −0.1051 | −0.0115 | −0.0747 | −0.0570 | −0.0557 | −0.0715 | 0.0995 | −0.0715 | 1.0000 | |||||||
Cu | −0.0634 | −0.0221 | −0.1453 | 0.0594 | 0.0482 | 0.0958 | 0.0178 | 0.1031 | −0.2213 | 1.0000 | ||||||
0.3730 | −0.3006 | 0.6165 | 0.0844 | 0.0793 | −0.0851 | −0.2641 | −0.0591 | −0.0938 | −0.0321 | 1.0000 | ||||||
Mn | −0.1705 | −0.0382 | −0.0182 | −0.0005 | −0.0020 | 0.1402 | 0.1954 | −0.0242 | −0.0657 | 0.1645 | −0.1027 | 1.0000 | ||||
Al | 0.2021 | −0.0217 | 0.7771 | 0.4781 | −0.4715 | −0.0598 | −0.1246 | 0.1018 | −0.1332 | −0.0740 | 0.4216 | −0.0007 | 1.0000 | |||
0.4522 | −0.0544 | 0.9025 | 0.2460 | 0.2514 | −0.0834 | 0.0489 | −0.0833 | 0.0193 | −0.1960 | 0.4817 | −0.0331 | 0.6826 | 1.0000 | |||
−0.3181 | 0.1275 | −0.3388 | 0.0325 | 0.0359 | 0.1584 | −0.0635 | 0.0838 | 0.0442 | 0.2311 | −0.2068 | 0.1616 | −0.2148 | −0.4015 | 1.0000 | ||
0.1490 | 0.0679 | 0.1112 | 0.1015 | 0.1025 | 0.0067 | −0.0658 | −0.0626 | −0.1378 | 0.1549 | −0.0143 | −0.0267 | 0.2074 | 0.0744 | 0.1400 | 1.0000 |
indicator to assess the presence of micro organisms in different watershed [
The distribution profile ratios of physical-chemical indicators are presented in Figures 2(A)-(E). All of the figures in
cannot compete with international scientists in generating reliable water quality data. Nonetheless, this approach needs further study which is more detailed.
The ground water sources at Moriba town are noted to contain high levels of nitrate. Evidence of higher
In Moriba town around Sierra Rutile Mining Company, there is no public water supply system and the communities largely depend on ground water sources for their domestic purposes. In the current study, groundwater sources were drawn from 50 wells and analyzed for physical and chemical parameters, respectively and results were referenced with WHO water quality standards for drinking purposes. Almost 80% of all the water quality indicators were in good agreement for potable water with three exceptions namely; pH, turbidity and nitrate. Greater attention should be given to these indicators which could be a public health risk. The study also revealed no consistent pattern of association among water quality indicators. Even though there were huge variances, the study provided a useful approach to predict chemical species from physical indicators. The study provided insightful information into the development of ground water sources around communities of Sierra Rutile mining concession areas considering their corporate social responsibilities and to some extent, a broader perspective of the conditions of rural water supply.
This study was part of student’s requirement to complete his Bachelor of Science with Honors (B. Sc. Hons) degree in Environmental Management and Quality Control, School of Environmental Sciences, Njala University. Many special thanks extended to the Sierra Rutile Limited for allowing the student (who is also a worker) to use their laboratory resources and facilities.
Massally, R.-E.M., Sheriff, A.B., Kaitibi, D., Abu, A., Barrie, M. and Taylor, E.T. (2017) Comprehensive Assessment of Groundwater Quality around a Major Mining Company in Southern Sierra Leone. Journal of Water Resource and Pro- tection, 9, 601-613. https://doi.org/10.4236/jwarp.2017.96040