The present study was aimed at bridging the gaps in the knowledge concerning heavy metals (Pb, Cd, Cr, Ni, Zn, Cu, Mn and Fe) concentrations in the groundwaters of the Ntem watershed in Yaoundé. Representative groundwater samples (25 numbers) were collected from five hand-dug wells, and their metal concentrations were assessed as per standard procedures, and deterministic interpolation techniques were used to perform the spatial distribution of heavy metal concentration maps. The ranges of concentrations of these metals in groundwaters were: Pb (0.11–0.34 mg/L > 0.025 mg/L); Cd (0.00–0.08 mg/L > 0.005 mg/L); Cr (0.12–1.33 mg/L > 0.05 mg/L) and Ni (0.11–0.46 mg/L > 0.05 mg/L). Besides, the average metal concentrations in the groundwaters of the sampling sites were in general higher than the prescribed World Health Organization (WHO) norms. The risk assessment indicated that the population concerned are considered unsafe, and are therefore exposed to non-carcinogenic and carcinogenic effects on health. The occurrence of more than permissible levels of heavy metals in the representative groundwaters and their spatial distribution indicate that there is a potential threat from these contaminants to the public health in the Ntem watershed.

INTRODUCTION

Environmental pollution management is a major challenge in many cities of sub-Saharan Africa in general and in Yaoundé in particular. Since 50 years, the population of Yaoundé has experienced an explosive growth, averagely 4%/year (Nguendo 2010). Between 1957 and 2005, the population increased from 58,099 to 1,817,524 (Zogning Moffo et al. 2011). The spectacular growth of the population has had an impact on the spatial evolution of the city, which itself has been multiplied by nine times between 1956 and 2000 (from 1,740 to 15,900 ha). Spatial dynamics of the city at the expense of existing forest has contributed to increase in the frequency of floods in the city and in some pericentral areas. In the city of Yaoundé, and particularly in the Ntem watershed, the consequences of this urbanization are visible through the increase in impermeable surfaces (buildings and tarred roads), extension of urban agriculture, increase in sewage and solid wastes, and improper waste dumping sites.

Furthermore, Yaoundé is characterized by a progressive increased rate of vehicular pollution due to the congested urban circulation (Matcheubou et al. 2009). Some reports have also revealed that drinking water provisioning in the city of Yaoundé by the public water distribution network can satisfy less than 65% of the city's needs, with the rest of the population using groundwater from wells/springs. There are very limited investigations on the quality of these water sources, as their heavy metal status is not very well quantified.

The present study investigated the heavy metal concentrations (Cd, Pb, Cr, Ni, Zn, Mn, Cu and Fe) in groundwaters of the Ntem urban watershed in Yaoundé.

MATERIALS AND METHODS

Study area

The city town of Yaoundé (Figure 1) is built on a hilly site and valleys, and is exposed to many natural hazards (mass movements, seismic hazards) amongst which floods have been the most common and the most damaging for three decades. Its position in the South Cameroon plateau between forest and savannah exposes it to a sub-equatorial Guinean climate, with 8 months of rainy season and 4 months of dry season (Zogning Moffo et al. 2011). Yaoundé, the capital city of the Republic of Cameroon, is divided into seven communes: Yaoundé 1, Yaoundé 2, Yaoundé 3, Yaoundé 4, Yaoundé 5, Yaoundé 6 and Yaoundé 7.
Figure 1

Location of the Ntem drainage basin within Yaoundé City, Cameroon (adapted from Mabou 2013).

Figure 1

Location of the Ntem drainage basin within Yaoundé City, Cameroon (adapted from Mabou 2013).

The study area is the Ntem drainage basin (Figure 1), situated in the eastern part of Yaoundé City, between latitudes N 03°55′06″ and N 03°52′33″ and longitudes E 011°31′26″ and E 011°33′02″. The hydrographic network is moderate, and the main stream that runs through the watershed from up to downstream is called ‘Ntem’. The surface area of this basin is evaluated as 556 ha, and its average altitude is about 744.14 m (Kalla 2007). The mean annual rainfall in the city of Yaoundé is about 1,600 mm per year. The mean annual temperature is 24.23 °C. The primary vegetation, which was formerly equatorial forest, has been transformed by urbanization into tertiary forests. The geology of Yaoundé reveals the existence of metamorphic rocks, constituted of gneiss. In the Ntem drainage basin, the hydrogeology is characterized by a shallow aquifer overlying a deep aquifer reposing on faulted gneiss (Kalla 2007).

Groundwater sampling procedure

A total of 25 representative groundwater samples were collected from five hand dug wells located at the selected sites P1, P2, P3, P4 and P5 in the watershed (Figure 2). Sampling sites were selected from different topographic levels (P1, P2, P3 and P4 were located at a slope of <3%; P5 was at mid-slope <20%), and according to the site proximity to pollution sources:
  1. Tarred roads and railway (P1, P2, P3, P4 and P5)

  2. Waste dumpsites and wastewater effluents (P1, P2, P3, P4 and P5)

  3. Urban agricultural soils and commercial activities (mechanics, repair shops, painting) (P1, P2, P3, P4 and P5)

  4. Upstream of Ntem river (P1 and P2), its downstream (P4) and Ntem river tributary (P2 and P3).

Figure 2

Presentation of the Ntem watershed, the sampling points and the distribution of the soil units.

Figure 2

Presentation of the Ntem watershed, the sampling points and the distribution of the soil units.

One more important criteria was the proximity of sampling sites to water points that are most solicited by the populations. Plastic bottles of 500 ml capacity (previously rinsed with distilled water and sterilized with alcohol), were used to collect water samples as previously described by Rodier et al. (2006). In each well, water samples were collected at 30 cm below the water table. In each sample, a 0.1 N solution of HCl was added to avoid complexation of ions. The samples were stored in a cooler (at 4 degrees Celsius) and transported to the laboratory and kept in a refrigerator for analysis.

Determination of heavy metal concentrations in groundwater samples in the laboratory

Total Pb, Cd, Cr and Ni were primarily extracted by the digestion method with diacid. Briefly, 50 ml groundwater sample was put in a 250 ml conical flask, and 15 ml of diacid (9 V:4 V ratio of Perchloric acid and Nitric acid) was added. The mixture was heated on a hot plate for 1 hour until digestion was completed (with the appearance of a white and dense smoke). Usually, cations and anions in groundwater are analysed only after 0.45 μm filtering. In the specific case of this study, groundwater samples were not filtered when sampling, but conserved as collected (with possible content of some soil particles and organics) in the field for further processing in the laboratory (digestion and analytical results in an atomic absorption spectrophotometer (AAS)). The aim was to estimate the total content of heavy metals in these groundwater resources, usually collected by the riparians (especially poor families without access to the public water network) and used for their needs without any particular treatment (filtration). The digestion method was used to recover the total amount of metal ions that are free in water samples, as well as those bonded to different solid matrices, to assess the exact concentrations of metals that may affect the health of the users of these groundwaters. Digested samples were therefore cooled down for 30 minutes. Thereafter, the conical flasks were washed out and their contents were transferred by filtration (Wathman paper No. 42) in 50 mL volumetric flasks. Then, the volume was made up to 50 ml with distilled water. The determination of heavy metal concentrations in samples is performed with an AAS after calibration of the device with standard solutions. The results obtained were reported as mg/L. Equally, total micronutrient (Zn, Cu, Mn, and Fe) extraction was performed using the Mehlich 3 procedure (Mehlich 1984) and was determined by AAS after filtration.

Data evaluation and analysis

The calculation of the mean concentration and standard deviation values of heavy metals was performed using MS Excel.

Spatial distribution of heavy metals in groundwaters in the Ntem watershed

The deterministic interpolation techniques, creating surfaces from measured points, based on inverse distance weighted, were used to perform the spatial distribution of heavy metal concentrations in groundwaters using ArcGIS 10.0. These geostatistical analyst tools were used to explore data, test spatial interpolation methods, analyse spatial distribution and autocorrelation of heavy metal concentrations, and finally to predict and map heavy metal concentrations.

Assessment of health risks associated with metals using water pollution index and USEPA health risk assessment model

Water pollution index or water quality index method
The weighted arithmetic water quality index (WQI) method classifies water quality according to the degree of purity by using the most commonly measured water quality variables. The method has been widely used in previous works, and the calculation of WQI was made using the following equation (Mohan et al. 1996): 
formula
The quality rating scale (Qi) for each parameter is calculated by using this expression: 
formula
are the monitored heavy metal, ideal (assumed equal to zero in this study: Ii = 0, except pH = 7.0 and DO = 14.6 mg/L), and standard values of the ith metal, respectively, i measured in the groundwater, and the unit weight (Wi) for each water quality parameter is calculated by using the following formula: 
formula
where k is the proportionality constant and can also be calculated by using the following equation: 
formula
where Si is the recommended standard value (norm) of the ith metal measured in the groundwater, n = 8 is the number of metals studied.
Health risk assessment
Risk assessment is defined as the process of estimating the probability of occurrence of an event and the probable magnitude of adverse health effects on human exposures to environmental hazards over a specified time period (Boateng et al. 2015). Risk assessment contains hazard identification, exposure assessment, dose response and risk characterization (Boateng et al. 2015). There are two toxicity risk indices that have been reported, which are: the slope factor (SF) for carcinogen risk characterization and the reference dose (RfD) for non-carcinogen characterization. The non-carcinogenic hazards quotient (HQ) was determined by using the formula (USEPA IRIS 2011): 
formula
where ADD (mg/kg) is the Average Daily Dose and RfD (mg/kg/day) is the oral toxicity reference dose (RfD) value recommended by the US EPA.

The oral toxicity reference dose (RfD) values recommended by the US EPA database as shown in Table 1.

Table 1

The toxicity responses (dose response) to heavy metals as the oral reference dose (RfD) (USEPA IRIS 2011)

Heavy metalsOral RfD (mg/kg/day)
Pb 3.5 × 10−3 
Cd 5.0 × 10−4 
Cr 0.15 
Ni 0.02 
Cu 4.0 × 10−2 
Zn 0.3 
Fe 0.7 
Mn 0.014 
Heavy metalsOral RfD (mg/kg/day)
Pb 3.5 × 10−3 
Cd 5.0 × 10−4 
Cr 0.15 
Ni 0.02 
Cu 4.0 × 10−2 
Zn 0.3 
Fe 0.7 
Mn 0.014 

The estimations of the magnitude, frequency and duration of human exposure in the environment have been analysed as the average daily dose (ADD) for each water sample. The following equations were used to calculate the ADD through water ingestion (Muhammed et al. 2011): 
formula
The parameters of the estimation of ADD are given in Table 2.
Table 2

Input parameters to characterize the ADD value (Boateng et al. 2015)

Concentration of groundwaterCValues
Ingestion rate IR 2.2 
Exposure frequency EF 365 
Exposure duration ED 70 
Body weight BW 70 
Average time AT 25,550 days 
Concentration of groundwaterCValues
Ingestion rate IR 2.2 
Exposure frequency EF 365 
Exposure duration ED 70 
Body weight BW 70 
Average time AT 25,550 days 

For the risk assessments of a mixture of chemicals, the individual HQs are summed to form a hazard index (HI): Values of HI under unity (HI < 1) are considered as safe, while (HI > 1) is an unacceptable risk of non-carcinogenic effects on health (Boateng et al. 2015).

The chronic daily intake (CDI) in the present study was calculated using the following expression (Muhammed et al. 2011): 
formula
where Ci, DI, and BW represent the concentration of heavy metal in the water samples (mg/L), average daily intake rate (2.2 L/day), and body weight (70 kg), respectively.

RESULTS AND DISCUSSIONS

Heavy metal distribution in groundwater

Table 3 presents the comparison between the groundwater samples investigated for their heavy metal content in the Ntem watershed and the international norms applied to potable water.

Table 3

Heavy metal concentrations in groundwater samples and norms applied for potable water

HeavySampling sites
metals (mg/L)P5P1P2P3P4Norm concentration in potable water (mg/L)Observations
Pb 0.11 ± 0.07 0.28 ± 0.06 0.29 ± 0.18 0.34 ± 0.25 0.32 ± 0.23 0.025a Groundwater polluted by lead at P1, P2, P3 and P4 
Cd 0.00 ± 0.00 0.00 ± 0.00 0.03 ± 0.01 0.08 ± 0.07 0.00 ± 0.00 0.005a Groundwater polluted by Cd at P2 and P3 
Cr 0.12 ± 0.34 0.88 ± 0.31 1.33 ± 0.63 0.64 ± 0.48 0.84 ± 0.42 0.05a Groundwater polluted by Cr at P1, P2, P3 and P4 
Ni 0.11 ± 0.05 0.63 ± 0.06 0.46 ± 0.02 0.25 ± 0.15 0.4 ± 0.18 0.05a Groundwater polluted by Ni at P1, P2, P3 and P4 
Zn 0.21 ± 0.02 0.02 ± 0.02 0.02 ± 0.02 0.02 ± 0.02 0.02 ± 0.02 3b Not polluted 
Cu 0.01 ± 0.00 0.01 ± 0.01 0.01 ± 0.00 0.01 ± 0.00 0.01 ± 0.00 2b Not polluted 
Mn 0.11 ± 0.01 0.13 ± 0.00 0.13 ± 0.00 0.57 ± 0.00 0.13 ± 0.00 0.4b Polluted at P3 
Fe 0.23 ± 0.02 0.26 ± 0.02 0.26 ± 0.01 0.26 ± 0.02 11.96 ± 0.85 0.3b Polluted at P4 
HeavySampling sites
metals (mg/L)P5P1P2P3P4Norm concentration in potable water (mg/L)Observations
Pb 0.11 ± 0.07 0.28 ± 0.06 0.29 ± 0.18 0.34 ± 0.25 0.32 ± 0.23 0.025a Groundwater polluted by lead at P1, P2, P3 and P4 
Cd 0.00 ± 0.00 0.00 ± 0.00 0.03 ± 0.01 0.08 ± 0.07 0.00 ± 0.00 0.005a Groundwater polluted by Cd at P2 and P3 
Cr 0.12 ± 0.34 0.88 ± 0.31 1.33 ± 0.63 0.64 ± 0.48 0.84 ± 0.42 0.05a Groundwater polluted by Cr at P1, P2, P3 and P4 
Ni 0.11 ± 0.05 0.63 ± 0.06 0.46 ± 0.02 0.25 ± 0.15 0.4 ± 0.18 0.05a Groundwater polluted by Ni at P1, P2, P3 and P4 
Zn 0.21 ± 0.02 0.02 ± 0.02 0.02 ± 0.02 0.02 ± 0.02 0.02 ± 0.02 3b Not polluted 
Cu 0.01 ± 0.00 0.01 ± 0.01 0.01 ± 0.00 0.01 ± 0.00 0.01 ± 0.00 2b Not polluted 
Mn 0.11 ± 0.01 0.13 ± 0.00 0.13 ± 0.00 0.57 ± 0.00 0.13 ± 0.00 0.4b Polluted at P3 
Fe 0.23 ± 0.02 0.26 ± 0.02 0.26 ± 0.01 0.26 ± 0.02 11.96 ± 0.85 0.3b Polluted at P4 

bMean ± SD corresponds to the mean and standard deviation for five values.

Table 1 indicates that the average heavy metal concentrations in groundwater were generally higher than those of the World Health Organization (WHO) norms, irrespective of the metal investigated and the sampling station, except for Zn and Cu. The ranges of concentrations of these metals in the groundwater were: Pb (0.11–0.34 mg/L > 0.025 mg/L); Cd (0.00–0.08 mg/L > 0.005 mg/L at some stations); Cr (0.12–1.33 mg/L > 0.05 mg/L) and Ni (0.11–0.46 mg/L > 0.05 mg/L). For micronutrients, the range of concentrations recorded were: Zn (0.02–0.022 mg/L), Cu (0.01 mg/L) regardless of the sampling point, Mn (0.13–0.57 mg/L), Fe (0.23–11.96 mg/L). The results indicate that Pb polluted sites are: P1, P2, P3 and P4. Only site P3 is polluted by Cd (0.08 mg/L). The groundwater pollution by Cr at sites P1, P3 and P4 (0.64–0.84 mg/L) is similar, while at site P2, the level of pollution is much higher (1.33 mg/L). Cd was detected at a small amount above threshold levels in the groundwater at site P2 (0.03 mg/L), while it was not detected at stations P1 and P4. The groundwater resources were polluted by this metal (Cd) only at station P3, while all the groundwater samples investigated were polluted by Ni. Concerning Zn, Cu, Mn and Fe, the ranges of the concentrations of these metals in the groundwater showed that groundwater resources are safe from metals such as Zn and Cu regardless of the sampling site, for while sites P3 and P4 were found to be polluted by Mn and Fe, respectively. The comparison of the heavy metal concentrations in groundwaters of the present study to other findings in some developing countries is shown in Table 4.

Table 4

Overview of groundwater polluted by heavy metals in some developing countries

CountryMetal investigatedGroundwater pollution statusPollution sourcesAuthors
Cameroon (Yaoundé) Pb, Cr, Cd, Ni, Zn, Cu, Mn and Fe Generally polluted by these metals except Zn and Cu Improper waste dumpsites, vehicular emissions, urban agriculture, runoff, etc. The present study 
Nigeria (Aladimma) Pb, Cr Not polluted Waste dumpsite Amadi (2011)  
Nigeria (Obajana) Pb, Cu, Zn, Cd Not polluted Cement factory Musa et al. (2013)  
Nigeria (Ibadan) Pb, Cd, Cr, Ni and Cu Only polluted by Cu Mechanic workshop villages Adelekan & Abegunde (2011)  
India (Tamil Nadu) Cu, Fe, Mn, and Cr Polluted only by Pb Improper dumpsites Abdul Jameel et al. (2012)  
CountryMetal investigatedGroundwater pollution statusPollution sourcesAuthors
Cameroon (Yaoundé) Pb, Cr, Cd, Ni, Zn, Cu, Mn and Fe Generally polluted by these metals except Zn and Cu Improper waste dumpsites, vehicular emissions, urban agriculture, runoff, etc. The present study 
Nigeria (Aladimma) Pb, Cr Not polluted Waste dumpsite Amadi (2011)  
Nigeria (Obajana) Pb, Cu, Zn, Cd Not polluted Cement factory Musa et al. (2013)  
Nigeria (Ibadan) Pb, Cd, Cr, Ni and Cu Only polluted by Cu Mechanic workshop villages Adelekan & Abegunde (2011)  
India (Tamil Nadu) Cu, Fe, Mn, and Cr Polluted only by Pb Improper dumpsites Abdul Jameel et al. (2012)  

Groundwater resources were found to be polluted by Pb, Cr, Cd, and Ni across the whole watershed. That fact was related to the variation of heavy metal concentrations observed from one sampling site to another, and the effects of the pollution sources (atmospheric deposition, improper waste dumpsites, and agricultural activities, etc.) observed in the watershed. In contrast, some authors have found groundwater unpolluted in the vicinity of some point sources of pollution. Then, Amadi (2011) assessed the effects of a dumpsite on groundwater in Nigeria and showed that the concentrations of Pb and Cr in groundwater were 0.01 mg/L, less than the threshold value admissible by WHO (2004) for drinking water (0.025 mg/L and 0.05 mg/L for Pb and Cr, respectively). In Nigeria, Musa et al. (2013) in Obajana (the site of the Dangote cement factory) have drawn the same conclusion from the study of heavy metals such as copper, zinc, cadmium and lead in groundwater. Adelekan & Abegunde (2011) revealed similar information for heavy metals such as Cd, Pb, Cr and Ni in the groundwater at mechanic villages located in Ibadan, Nigeria, with the exception of Cu, where all the values were higher than the limits. Abdul Jameel et al. (2012) have found Cu, Fe, Mn, and Cr below the permissible limits in groundwater in Tamil Nadu, India, except for Pb, which concentrations were above the permissible limit for drinking water. They have associated the source of pollution to the presence of an improper solid waste dumpsite with special reference to heavy metal pollution.

The spatial distribution characteristics of heavy metals

The spatial distributions of Pb, Cd, Cr and Ni in groundwaters are presented in Figure 3.
Figure 3

Geospatial interpolations of Pb, Cd, Cr and Ni in the groundwater of the Ntem watershed.

Figure 3

Geospatial interpolations of Pb, Cd, Cr and Ni in the groundwater of the Ntem watershed.

Figure 3 shows the spatial distribution of Pb, Cd, Cr and Ni in the groundwaters of the Ntem watershed. The most expanded range of concentrations of Pb are: 0.25–0.29 mg/L, which covered more than 60% of the total surface area, followed by 0.25–0.34 mg/L, which covered about 20%; the range of concentrations from 0.20 to 0.25 mg/L covered about 10%. Besides this, each of the lowest concentration levels (0.16–0.20 mg/L and 0.11–0.15 mg/L) covered less than 5% of the total groundwater surface. All the ranges of concentrations of Pb were above the norms (0.005 mg/L). These observations may be associated with the intensive vehicular exhaust pollution in the area (Matcheubou et al. 2009). Similarly, 100% of the surfaces of the groundwaters were covered by concentrations of Cr and Ni ranged above the norms. Among them, more than 70% of groundwater surfaces were covered by the highest concentration levels of these pollutants. The expansion of Cr and Ni may be attributed to urban agriculture, waste dumpsites, painting, etc. (Ngendo 2010; Mabou 2013). In contrast, for Cd, the extended area where the concentration levels were higher than norms (0.005 mg/L) was located around sampling point P3, and this area represents less than 10% of the total groundwater surfaces of the watershed. Then, more than 90% of the surface area of the groundwaters contained Cd in concentrations less than norms.

The spatial distributions of Mn, Zn, Cu and Fe in groundwaters are presented in Figure 4.
Figure 4

Geospatial interpolations of Mn, Zn, Cu and Fe in groundwaters of the Ntem watershed.

Figure 4

Geospatial interpolations of Mn, Zn, Cu and Fe in groundwaters of the Ntem watershed.

Figure 4 shows the spatial distribution of Mn, Zn, Cu and Fe in the groundwaters of the Ntem watershed. Mn and Zn show a relatively similar spatial distribution pattern. The highest ranges (0.30–0.57 mg/L and 0.09–0.21 mg/L, respectively, for Zn and Mn) covered less than 20% of the total surface area. The range of concentration levels (<0.30 mg/L for Zn and <0.096 mg/L for Mn) covered more than 80% of the total surface area of the groundwaters.

The highest values of concentration levels were distributed around P3, P4 and P5. This may be connected to the expansion of urban agriculture, proliferation of waste dumpsites and surface runoff (Zogning Moffo et al. 2011; Adelekan & Abegunde 2011). However, the overall concentration levels for Mn and Zn were less than the norms.

The spatial distribution of the highest values of Cu (0.010–0.11 mg/L) were found around the sampling point P1 located behind the waste dumpsites of the General Hospital of Yaoundé and surrounded by urban agricultural soils in waterlogging areas. This covered less than 10% of the total surface area of groundwaters, while 90% of the total surfaces of the groundwater were covered by Cu concentrations <0.010 mg/L. For Fe, more than 80% of the surface area of the groundwaters were covered by Fe concentrations ranged between 0.23 to 2.58 mg/L, and only 20% were covered by concentrations ranging from 2.50 mg/L to 11.98 mg/L. The overall surface area of the groundwaters contained Fe concentrations above the norms. Similar observations were recorded by Abdul Jameel et al. (2012) in India, where the pollution was due to improper waste dumpsites.

Assessment of health risks associated with metals using water pollution index and US EPA health risk assessment model

Water pollution index or water quality index

The WQI values computed for different sampling stations of the Ntem watershed are presented in Table 5.

Table 5

WQI calculated at different sampling sites

WQI 
Sampling stationWQI valuesRating of water qualityGrading
P1 14.9 Excellent water quality 
P2 19.0 Excellent water quality 
P3 17.3 Excellent water quality 
P4 27.1 Good quality water 
P5 3.5 Excellent water quality 
WQI 
Sampling stationWQI valuesRating of water qualityGrading
P1 14.9 Excellent water quality 
P2 19.0 Excellent water quality 
P3 17.3 Excellent water quality 
P4 27.1 Good quality water 
P5 3.5 Excellent water quality 

Table 5 shows an excellent water quality for sampling stations P1, P2, P3 and P5, indicated by values of WQI ranged between 0 and 25 (0 < WQI < 25), while the water quality is typified as ‘Good quality water’ at sampling point P5, indicated by a WQI ranged between 25 and 50 (25 < WQI < 50). Despite this arithmetic, WQI is useful to communicate the overall water quality in terms of groundwater metal content, but it presents some demerits such as (i) WQI may not carry enough information about the real situation of the water and (ii) many uses of water quality cannot be met with this index and it eclipses and over-emphasizes a single bad parameter value (Mohan et al. 1996).

Health risk assessment

The health risk was assessed in relation to its non-carcinogenic (HI) as well as carcinogenic effects based on the calculation of ADD estimates and defined toxicity according to the following relationships (US EPA IRIS 2011)

The non-carcinogenic HQ and HI are reported in Table 6.

Table 6

Non-carcinogenic HQ and HI of groundwaters in the Ntem watershed

 HQ and HI in different sampling stations
MetalsP5P1P2P3P4
Pb 0.849 0.216 0.224 0.262 0.247 
Cd 0.000 0.000 1.667 4.444 0.000 
Cr 0.022 0.016 0.025 0.012 0.016 
Ni 0.153 0.875 0.639 0.347 0.556 
Zn 0.162 0.015 0.015 0.015 0.015 
Cu 0.008 0.008 0.008 0.008 0.008 
Mn 0.022 0.026 0.026 0.113 0.026 
Fe 0.009 0.010 0.010 0.010 0.475 
HI = ΣHQ 1.224 1.166 2.613 5.212 1.341 
 HQ and HI in different sampling stations
MetalsP5P1P2P3P4
Pb 0.849 0.216 0.224 0.262 0.247 
Cd 0.000 0.000 1.667 4.444 0.000 
Cr 0.022 0.016 0.025 0.012 0.016 
Ni 0.153 0.875 0.639 0.347 0.556 
Zn 0.162 0.015 0.015 0.015 0.015 
Cu 0.008 0.008 0.008 0.008 0.008 
Mn 0.022 0.026 0.026 0.113 0.026 
Fe 0.009 0.010 0.010 0.010 0.475 
HI = ΣHQ 1.224 1.166 2.613 5.212 1.341 

According to Table 6, the HI values obtained in the Ntem watershed irrespective of the sampling stations were found to be higher than 1 (HI > 1), indicating that the exposed population are considered unsafe, or there are unacceptable risk effects on health. Boateng et al. (2015) and Muhammed et al. (2011) found that HI < 1 for hand-dug wells' water in Ghana and Pakistan, indicating that these water are safe from non-carcinogenic risks.

Boateng et al. (2015) pointed out that the health risk associated with drinking water depends on the volume of water consumed and the weight of the individual. Therefore, the health risk assessment associated with the exposure duration (ADD) was determined using the concentration of Pb, Cd, Cr Ni, Mn, Zn, Cu and Fe in the groundwater samples. The results are presented in Table 7.

Table 7

Exposure duration, ADD (mg/kg-day) for the selected hand-dug well stations

 ADD (mg.L−1 day−1)
Metals/stationsP1P2P3P4P5
Pb 0.00800 0.00829 0.00944 0.00914 0.00306 
Cd 0.00000 0.00085 0.00222 0.00000 0.00000 
Cr 0.02514 0.03800 0.01777 0.02400 0.00333 
Ni 0.01800 0.01314 0.00694 0.01143 0.00306 
Zn 0.00057 0.00057 0.00055 0.00057 0.00583 
Cu 0.00029 0.00029 0.00028 0.00028 0.00028 
Mn 0.00371 0.00371 0.01583 0.00371 0.00306 
Fe 0.00743 0.00743 0.00722 0.34171 0.00639 
 ADD (mg.L−1 day−1)
Metals/stationsP1P2P3P4P5
Pb 0.00800 0.00829 0.00944 0.00914 0.00306 
Cd 0.00000 0.00085 0.00222 0.00000 0.00000 
Cr 0.02514 0.03800 0.01777 0.02400 0.00333 
Ni 0.01800 0.01314 0.00694 0.01143 0.00306 
Zn 0.00057 0.00057 0.00055 0.00057 0.00583 
Cu 0.00029 0.00029 0.00028 0.00028 0.00028 
Mn 0.00371 0.00371 0.01583 0.00371 0.00306 
Fe 0.00743 0.00743 0.00722 0.34171 0.00639 

The ADD values ranged from 0.00306 to 0.00944, 0.00000 to 0.00085, 0.00333 to 0.03800; 0.00306 to 0.01800; 0.00055 to 0.00057; 0.00028 to 0.00029; 0.00306 to 0.01583; 0.00639 to 0.34171 mg/kg/day for Pb, Cd, Cr, Ni, Zn, Cu, Mn and Fe, respectively (Table 7). All these values exceeded the cancer risk, for which the acceptable limit is 1.0 × 10−6. These observations indicated that a cancer risk may occur. Thus, the health risk assessment indicates that the situation is alarming within this area. Alternative technologies for appropriate potable water supply of remediation technology must be applied to mitigate the hazard of metals on the public health in the watershed.

From Table 8, The average CDI levels for carcinogenic risk of Pb, Cd, Cr, Ni, Zn, Cu, Mn and Fe were found to be 0.00744; 0.00061; 0.02117; 0.01028, 0.00161; 0.00028, 0.00594 and 0.07206, respectively. The CDI indices were in the order: Fe > Cr > Ni > Pb > Mn > Zn > Cd > Cu. According to US EPA IRIS (2011), a CDI value of 1.0 × 10−6 is the limit for the acceptable health risk. The values of CDI for all the groundwater samples exceed this acceptable limit, indicating an increased cancer risk for individuals because of their lifetime exposure to these carcinogens (Boateng et al. 2015).

Table 8

CDI in groundwater samples from the selected hand-dug well stations

 CDI (mg.L−1 day−1)
Metals/stationsP1P2P3P4P5Average
Pb 0.00778 0.00806 0.00944 0.00889 0.00306 0.00744 
Cd 0.00000 0.00083 0.00222 0.00000 0.00000 0.00061 
Cr 0.02444 0.03694 0.01778 0.02333 0.00333 0.02117 
Ni 0.01750 0.01278 0.00694 0.01111 0.00306 0.01028 
Zn 0.00056 0.00056 0.00056 0.00056 0.00583 0.00161 
Cu 0.00028 0.00028 0.00028 0.00028 0.00028 0.00028 
Mn 0.00361 0.00361 0.01583 0.00361 0.00306 0.00594 
Fe 0.00722 0.00722 0.00722 0.33222 0.00639 0.07206 
 CDI (mg.L−1 day−1)
Metals/stationsP1P2P3P4P5Average
Pb 0.00778 0.00806 0.00944 0.00889 0.00306 0.00744 
Cd 0.00000 0.00083 0.00222 0.00000 0.00000 0.00061 
Cr 0.02444 0.03694 0.01778 0.02333 0.00333 0.02117 
Ni 0.01750 0.01278 0.00694 0.01111 0.00306 0.01028 
Zn 0.00056 0.00056 0.00056 0.00056 0.00583 0.00161 
Cu 0.00028 0.00028 0.00028 0.00028 0.00028 0.00028 
Mn 0.00361 0.00361 0.01583 0.00361 0.00306 0.00594 
Fe 0.00722 0.00722 0.00722 0.33222 0.00639 0.07206 

CONCLUSION

Groundwater resources in the Ntem watershed were found to be polluted by heavy metals. The occurrence of these pollutants in the groundwater was a consequence of anthropogenic activities in the Ntem watershed. The assessment of health risks suggested that the riparians of the watershed who consume these groundwaters are exposed to non-carcinogenic as well as to carcinogenic risks. Therefore, the pollution of these groundwater resources is a potential threat to public health as that groundwater constitutes a major source of water supply for the population in this region.

ACKNOWLEDGEMENTS

The first author received a partial research grant from the University of Dschang. The authors would like to thank Late Pr. Alexandre Nono for his scientific support, the International Institute of Tropical Agriculture (IITA) and IRAD (Institut de Recherche Agricole pour le Développement) of Yaoundé for the analysis of groundwater samples.

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