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Assessment of Heavy Metal Concentrations (Cu, Cd, Pb, and Zn) in Wastewater from Gusii Treatment Plant in Kisii County, Kenya

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The concentrations of heavy metals were determined from wastewater samples collected from the Gusii wastewater treatment plant, from May to July, 2021. Heavy metal analysis was done using a flame atomic absorption spectrophotometer, model AA 7000 Shimadzu, Japan. The results showed that the concentrations of Zinc and Cadmium were below the detection limit for all the sampling sites. The concentrations of Lead and Copper (Mean ± SE) ranged between 0.34 ± 0.06 mg/L and 0.86 ± 0.08 mg/L and 0.25 ± 0.05 and 0.34 ± 0.01 mg/L respectively. The month of July exhibited a higher mean Cu concentration of 0.35 ± 0.004 mg/L compared to the mean Cu concentration (0.2 ± 0.02 mg/L) of May. Likewise, the mean lead concentration of May (0.60 ± 0.04 mg/L) was higher than the mean (0.53 ± 0.05 mg/L.) of July. The independent sample t-test showed that mean Cu concentration difference was significant between the sampling months (t (34) = 21.58; p < 0.05) while for Pb it was not significant between the sampling months (t (30) = 1.241; p = 0.274). The percentage removals of Copper and Lead were generally low at 12.61 % and 6.27 %, respectively. The continued discharge of effluent into River Riana may lead to accumulation of heavy metals in the environment, which in turn poses health risks to the general public. Therefore, the study recommends that Gusii Water and Sanitation Company continue monitoring and assessing the levels of heavy metals in the treatment plant for its sustainability.
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PASJ 2022. DOI: 10.47787/pasj.v1i02.12 www.panafricajournal.com
Pan Africa Journal of Sciences
ISSN 2709-1473 | Open Access
Assessment of Heavy Metal Concentrations (Cu, Cd, Pb, and
Zn) in Wastewater from Gusii Treatment Plant in Kisii
County, Kenya
Rayori Douglas1*, Getabu Albert1, Omondi Reuben1, Orina Paul2, Nchore Hellen3, Gisacho Boniface4, Nyabaro
Obed4, Omondi Argwings5, Omweno Job1
1 Department of Environment, Natural Resources and Aquatic Sciences, Kisii University, P.O. Box 408-40200, Kisii, Kenya.
2 Kegati Aquaculture Centre, Kenya Marine and Fisheries Research Institute (KMFRI), P.O. Box 3259-40200, Kisii, Kenya.
3 School of Chemistry and Material Sciences, Technical University of Kenya, P. O. Box 52428-00200, Nairobi, Kenya.
4 Department of Chemistry, School of Pure and Applied Sciences, Kisii University, P.O. Box 408-40200, Kisii, Kenya.
5 Department of Medical and Applied Sciences, Sigalagala National Polytechnic, P.O. Box 2966, Kakamega, Kenya.
* Corresponding author: drayori@kisiiuniversity.ac.ke
Received: 7th January 2022; Accepted: 8th February 2022; Published: 10th February 2022
DOI: 10.47787/pasj.v1i02.12
Volume 01 Issue 02
RESEARCH ARTICLE: Environmental Ecology, Technology & Engineering
Abstract
The concentrations of heavy metals were determined from wastewater samples collected from the Gusii wastewater
treatment plant, from May to July, 2021. Heavy metal analysis was done using a flame atomic absorption
spectrophotometer, model AA 7000 Shimadzu, Japan. The results showed that the concentrations of Zinc and
Cadmium were below the detection limit for all the sampling sites. The concentrations of Lead and Copper (Mean
± SE) ranged between 0.34 ± 0.06 mg/L and 0.86 ± 0.08 mg/L and 0.25 ± 0.05 and 0.34 ± 0.01 mg/L respectively.
The month of July exhibited a higher mean Cu concentration of 0.35 ± 0.004 mg/L compared to the mean Cu
concentration (0.2 ± 0.02 mg/L) of May. Likewise, the mean lead concentration of May (0.60 ± 0.04 mg/L) was
higher than the mean (0.53 ± 0.05 mg/L.) of July. The independent sample t-test showed that mean Cu concentration
difference was significant between the sampling months (t (34) = 21.58; p < 0.05) while for Pb it was not significant
between the sampling months (t (30) = 1.241; p = 0.274). The percentage removals of Copper and Lead were generally
low at 12.61 % and 6.27 %, respectively. The continued discharge of effluent into River Riana may lead to
accumulation of heavy metals in the environment, which in turn poses health risks to the general public. Therefore,
the study recommends that Gusii Water and Sanitation Company continue monitoring and assessing the levels of
heavy metals in the treatment plant for its sustainability.
Keywords: Wastewater; Heavy metal concentration; Cadmium; Copper; Zinc; Lead; Permissible limits
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1. INTRODUCTION
The increased level of heavy metal discharge into the environment and their associated risks has
necessitated in-depth research into their occurrence in waste waters. Heavy metals are non-biodegradable
and often bio-accumulate in animals through food chains, building up their concentrations to toxic levels.
Human beings can also get exposed to heavy metals through consumption of foods [1, 2, 3, 4, 5]. The
growing concern of heavy metal pollution in aquatic ecosystems has attracted high scientific and policy
interest. Their sources can be traced to the discharge of waste water from domestic, municipal and
industrial sources, which have become widespread globally [1, 4, 6, 7, 8]. Monitoring of heavy metals
concentration in the aquatic environment has been done through determination of their concentrations in
lotic and lentic water systems or wastewater discharge, especially sewage treatment sites, effluent, sludge,
sediments, and the plankton community (phytoplankton and zooplankton) [3, 5, 9, 10, 11, 12].
Gusii wastewater treatment plant is a conventional plant for wastewater treatment and is the only sewer
system in Kisii County, South-Western Kenya. The lagoon design capacity is 15,000 m3/day an upgrade
from a previous design capacity of 8,000 m3/day. This was purposely to cater for the increased amount of
domestic and industrial wastewater resulting from increased population coupled with heavy rains [13].
Gusii wastewater treatment plant is surrounded by several households who practice mixed subsistence
farming of crops and animals and could either benefiting or affected by the treatment plant. The notable
crops grown include maize, bananas, sugarcane, kales, and Napier grass among others. The processed
sludge from sewage ponds is at times used as fertilizer for these plants [14]. However, limited information
is available on its conformity to standards recommended for application as fertilizer. On the other hand,
the common source of clean water for domestic and agricultural uses for the surrounding households
included either from water springs, boreholes or roof catchments and River Riana as well (Figure 1) [13].
Few studies have been conducted on the treatment plant thus limited information is available on its
effectiveness in wastewater treatment. The selected physical-chemical parameters measurements data
available from GWASCO (2015) indicates that the previous design of the treatment plant effluent
discharged did not meet the stipulated standards by the National Environment Management Authority
(NEMA).
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Figure 1: Some of the activities that occur around the Gusii wastewater treatment plant. Clockwise:
Napier grass planted at the effluent discharge point to river Riana; Banana and sugarcane farming along
River Riana; Water point source for domestic use; Animals (goats) grazing along River Riana water bank
(Source: Author)
The most recent study focused on phytoplankton diversity [15]. Previously, a study conducted by [16]
was on the effectiveness of constructed wetland in polishing wastewater effluent from the treatment plant.
Both of these studies were carried out on the previous treatment plant design. To this end, limited
information is available concerning heavy metals both for the previous and the current treatment plant.
Therefore, the present study was undertaken to determine the concentrations of selected heavy metals (Cu,
Cd, Pb, and Zn) in wastewater from Gusii wastewater treatment plant, to inform policies concerning
human and environmental health.
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2. MATERIALS AND METHODS
2.1 Study area
Gusii wastewater treatment plant is a conventional plant for wastewater treatment and is the only sewer
system in Kisii County, South-Western Kenya. The geographical location of the wastewater treatment
plant is latitudes 00 39’ 30’’ S and Longitude 340 42’ 30’’ E. The treatment plant consists of receiving
units in the screens, grit chambers, and channels to the lagoon. Wastewater moves through the grit
chambers and channels to the lagoon for the removal of debris and is channelled into two anaerobic ponds,
then facultative pond, and two maturation ponds (that’s first and second maturation pond) for treatment
before the effluent is discharged into River Riana (Figure 2).
Figure 2: A sketch showing the wastewater treatment stages and sampling points (marked with star) in
Gusii wastewater treatment plant (Author).
2.2 Wastewater sampling
Wastewater samples were collected in the months of May and July, 2021. There were nine sampling points,
including the inlet, two anaerobic (two composite samples) ponds, one facultative, and two maturation
ponds, the effluent before discharge into the river besides to three points in the river, that is, at the
confluent and 100 meters up and downstream at the effluent discharge point into River Riana (Figure 2).
Wastewater samples were collected in duplicate using 500 ml different transparent plastic bottles totalling
18 samples per sampling session. The sampling bottles were washed thoroughly using a detergent and
rinsed twice with distilled water followed by 10% Nitric (HNO3) acid before embarking on fieldwork.
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The collected wastewater samples were preserved by adding 5 ml of concentrated Nitric acid (HNO3) to
prevent the precipitation of the metals, algae growth and microbial activity. All the collected samples were
clearly labelled, packed and then transported to the laboratory in a cooler box containing ice for heavy
metals analysis.
In the laboratory, 100 ml of each wastewater sample was measured using a measuring cylinder and then
transferred into 250 ml separate beakers. Each sample was digested on a hot plate using 10 ml of Aquaregia
(a mixture of HNO3 and HCl in the ratio 3:1) inside a fume hood. The digested solution of each sample
was then filtered using Whatman No. 42 filter paper and transferred into a separate 100 ml volumetric
flask. The solution was then diluted to the mark with distilled water. The samples were transferred into
clearly labelled separate plastic bottles. In the place of a sample, for the blank, distilled water was used
and the same procedure for digestion was followed. Heavy metal analysis was done using the flame atomic
absorption spectrophotometer, AA 7000 Shimadzu, Japan model.
2.3 Instrument’s operating conditions
The Atomic Absorption Spectroscopy (AAS) operating conditions for heavy metals analysis are
summarized in Table 1. Moreover, the operating conditions were as per the manufacturer's recommended
conditions.
Table 1: The AAS operating conditions
Metal
Lead (Pb)
Zinc (Zn)
Copper (Cu)
Cadmium (Cd)
Wavelength (nm)
283.22
213.73
324.8
228.87
Slit width (nm)
0.7
0.7
0.7
0.7
Lamp current (mA)
10.0
8.0
8.0
8.0
Oxidant flow rate (L/min)
15.0
15.0
15.0
15.0
Fuel flow rate (L/min)
2.0
1.80
1.80
1.80
Burner height (mm)
7.0
7.0
7.0
7.0
Instrument detection limit
0.0038
0.0798
0.0508
0.0092
Flame used
Air/Acetylene
Air/Acetylene
Air/Acetylene
Air/Acetylene
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2.4 Stock solutions, working standards, and calibration curves
All the standards used during this study were freshly prepared whenever the analysis was carried out.
Stock solutions of 1000 mg/L for each metal were prepared using analytical grade salts which were dried
and cooled before weighing. From the prepared stock standard solutions, intermediate standard solutions
were prepared for each element using serial dilution in 50 ml volumetric flasks. The prepared standards
for each element, one after the other, were aspirated into the AAS and their absorbance recorded.
Calibration curves were plotted for each element using the absorbance against concentrations. To obtain
the Y-intercept for each element curve, extrapolation was done while the gradient for each curve was
provided by Microsoft Excel. The respective heavy metal calibration curve prepared was then used to
determine the concentration of heavy metals in the digested wastewater samples.
To validate the method used for heavy metal analysis and ascertain the accuracy of the AAS analytical
procedure, samples with unknown heavy metal concentrations were spiked with standards of known
concentrations and their percentage recovery determined for the respective heavy metals using the
equation 1:
  
 Equation 1
If the calculated values were within 80 120% then they indicated good accuracy for the analysis
procedure (Agoro et al., 2020).
2.5 Heavy metals removal efficiency
Any wastewater treatment plant is deemed effective in wastewater polishing when pollutants are removed
so that the effluent discharged meets the required national standards (Water quality Regulations, 2006;
Legal notice No. 121). To determine the effectiveness of the Gusii wastewater treatment plant design in
wastewater polishing, the heavy metal removal efficiency was calculated according to [6] (equation 2).
  
  Equation 2
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2.6 Compliance index
In Kenya, the Kenya Bureau of Standards (KEBS) and the National Environmental Management
Authority (NEMA) provide guidelines on quality requirements for effluent discharge to the environment
with the intent of controlling pollution. The compliance index value was calculated to show the
effectiveness of the treatment plant design in wastewater polishing. The index value of less than 1 indicates
compliance to the set standards for effluent discharge into the environment or surface waters while the
index of greater than 1 indicates non-compliance. In this study, the compliance index for the heavy metals
was calculated using the equation 3 [6]:
   
 Equation 3
2.7 Statistical analysis
Data recorded from heavy metals analysis was analyzed using SPSS 22.0 for windows. One-way ANOVA
(Analysis of Variance) was performed for determination of variation in the mean value of the heavy metal
concentration between the sampling stations while independent sample t-test was performed for
determination of variation in the mean value of the heavy metal concentration between the sampling
months. The significance differences were determined at p < 0.05.
3. RESULTS
3.1 Calibration curves
Figure 3: shows the individual heavy metal calibration curves used for the determination of the respective
heavy metals concentrations in wastewater samples.
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Figure 3: Calibration curves for the determination of the respective heavy metals concentrations in
wastewater samples
3.2 Spatial variation of the heavy metals concentrations
The results of the concentrations of four heavy metals (Cu, Cd, Pb and Zn) determined from wastewater
samples from Gusii treatment plant are shown in table 2.The concentrations of Zn and Cadmium (Cd)
were below the detection limit in all the sampling sites. However, the concentration of lead (Pb) was only
below the detection limit at the confluent sampling point.
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Figure 4: Mean SE) spatial variation of heavy metal concentrations (in mg/L) in wastewater from Gusii
treatment plant.
The Pb mean concentration of the sampling points ranged from 0.34 ± 0.06 mg/L to 0.86 ± 0.08 mg/L.
The facultative pond had the highest Pb mean concentration with 0.86 ± 0.08 mg/L. One-way ANOVA
test showed that mean Pb concentration was not significantly different among the sampling stations (F (7,
24) = 1.827; p = 0.128). The mean concentration of Cu of the sampling stations also ranged from 0.25 ±
0.05 mg/L to 0.34 ± 0.01 mg/L. The confluent sampling station had the highest concentration while the
maturation pond 2 sampling station had the least Cu concentration with 0.34 ± 0.01 mg/L and 0.25 ± 0.05
mg/L, respectively (Figure 4). One-way ANOVA test showed that the mean Cu concentration was not
significant among the sampling stations (F (8, 27) = 0.354; p = 0.935).
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
Concentration (mg/L)
Cu
Pb
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3.3 Temporal variation of the heavy metals concentrations
Table 2 represents the mean (±SE) heavy metal concentrations for the two sampling months. The mean
Pb concentration recorded for the month of May (0.60 ± 0.04 mg/L) was higher than the mean
concentration (0.53 ± 0.05 mg/L) recorded in July. The independent sample t-test showed that mean Pb
concentration was not significant between the sampling months (t (30) = 1.241; p = 0.274). The month of
July measured a mean Cu concentration of 0.35 ± 0.004 mg/L which was higher compared to the month
of May which had a mean Cu concentration of 0.2 ± 0.02 mg/L. The independent sample t-test showed
that mean Cu concentration was significant between the sampling months (t (34) = 21.58; p < 0.05) (Table
2). The mean concentrations for Zn and Cd were below the detection limit in both sampling months during
the study period.
Table 2: Mean (±SE) temporal variation of heavy metal concentrations (in mg/L) in wastewater from
Gusii treatment plant.
Sampling months
Heavy metal concentrations (mg/L)
Pb
Cu
May
0.60 ± 0.04
0.20 ± 0.02
July
0.53 ± 0.05
0.35 ± 0.004
t- value
t (30) = 1.241; p = 0.274
t (34) = 21.58; p < 0.05
3.4 Heavy metals removal efficiency
The performance of the Gusii wastewater treatment plant was assessed in terms of removal efficiency and
the calculated percentage reduction of the respective heavy metals. The percentage removals of Copper
and Lead were generally low at 12.61 % and 6.27 %, respectively. The low percentages of removal of
heavy metals are generally an indication that the treatment plant does not have a good capacity to remove
these elements from the influent wastewater. Nevertheless, the percentage reductions of Cadmium and
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Zinc were not calculated for the treatment plant because their concentrations were generally below
detection limits.
3.5 Compliance index
The compliance indexes for Cadmium and Zinc were not calculated and referenced for the treatment plant
because their concentrations were generally below detection limits. The index value for Copper, 0.25 was
below 1 indicating compliance. However, the compliance index value for Lead was 53, the value which
is greater than 1, indicating non-compliance to the specified NEMA standards for effluent discharge to
the environment (Table 3).
Table 3: NEMA Standards for effluent discharge into the environment
Parameter
NEMA Maximum Allowable
effluent discharge (Limits)
Effluent
discharge
Compliance
index value
Remark
Lead (Mg/L)
0.01
0.53 ± 0.14
53
Non-compliant
Cadmium (Mg/L)
0.01
BDL
Zinc (Mg/L)
0.5
BDL
Copper (Mg/L)
1.0
0.26 ± 0.15
0.26
Compliant
4. DISCUSSION
Unlike in most developing countries, wastewater is treated before discharge to the environment in the
developed countries. Wastewater is of poor quality as it is rich in pathogenic micro-organisms, heavy
metals, organic and inorganic chemicals, and toxic substances hence not suitable not only for domestic
use but also unfit for and agricultural uses and introduction to the aquatic environment [17]. The effects
associated with the release of untreated or partially treated wastewater include degradation of aquatic
ecosystems, outbreak of food and water-borne diseases, and environmental pollution [4, 6, 17, 18]. Despite
the success in using treated wastewater in aquaculture and other agricultural purposes in India with ready
market for the products, the use of the wastewater in the African continent more so Kenya, is uncertain
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mainly on product safety for human consumption [19, 20]. Therefore, knowledge of the nature and
composition of wastewater is critical in wastewater treatment, disposal and re-use. In Kenya, National
Environment Management Authority (NEMA) and Kenya Bureau of Standards (KEBS) provide
guidelines on quality requirements for effluent discharge to the environment.
In the current study, heavy metals were analyzed in wastewater from the Gusii wastewater treatment plant
and three points along river Riana at the effluent discharge point. Cd and Zn concentrations in the
wastewater samples were below the detection limit of the instrument that was used for heavy metal
analysis and this can be attributed to the fact that they have a lower solubility characteristics compared to
Pb. This corroborates with a study by [21] in a study that investigated heavy metals on fish, water, and
sediments sampled from Southern Caspian Sea, Iran. Therefore, the high levels of Pb in wastewater should
be of public health concern in terms of wastewater reuse and discharge into water bodies. The high levels
of Pb in wastewater can be attributed to greater solubility characteristics and effluents from institutions
(that’s higher learning and research institutions), hospitals and industries within the town. Some studies
have also shown that lead dominates most of the commonly used metal products, paints, pesticides,
pipelines and cables and this can be the reason for the higher levels in the wastewater sample [22]. The
confluent sampling station had the highest concentration of Cu and this can be attributed to anthropogenic
activities and institutional effluents that’s learning and research institutions), hospitals and industries
within the town. On the other hand, the downstream sampling station had the least Cu concentration and
this can be attributed to bioaccumulation by aquatic organisms [23].
Simultaneously, the low concentrations of heavy metals (Zn and Cd) in the wastewater treatment plant
can be attributed to several factors. These include dilution by heavy rainfall in the region during the
sampling period and uptake by phytoplankton and zooplankton which might have bio-accumulated the
heavy metals [11]. In most instances, the sediments might have also act as sinks removing heavy metals
from the water column. Consequently, [6] reported heavy metal variations in wastewater and sewage
sludge from municipal treatment plants in Eastern Cape Province, South Africa. Furthermore, [11] also
studied heavy metal concentration in the bottom sediments Lake Koka in Ethiopia, which they found to
be higher, compared to the wastewater. The retention period of wastewater in treatment plant respective
ponds might be short, therefore, some of the metals might have been transported out of the plant resulting
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in their low concentrations in the treatment plant [24, 25]. Low connectivity of the sewer lines in the
region has led to improper heavy metals contaminated wastewater being disposed to open channels by the
residents. A previous study by [7] showed that wastewater and soil samples were drawn from open waste
channels in industrial areas in Nairobi contained heavy metals.
5. Conclusions
Gusii wastewater treatment plant plays an important role in the treatment of urban and municipal
wastewater from Kisii town and its environs. The observed results showed that Cadmium and Zinc were
below the detection level in all sampling stations. The concentration of Copper was within the permissible
limits by National Environment Management Authority for effluent discharge into the environment while
those of Pb were above the set limits. Therefore, the continued discharge of the effluent to River Riana
may lead to the accumulation of heavy metals in the environment in turn causing a variety of health and
environmental impacts. As a result, Gusii Water and Sewerage Company should consistently monitor and
assess the levels of heavy metals in the treatment plant for its sustainability. Use of permanent heavy
metals sensors linked to a central computer processing point will not only provide data but also inform
need for management improvement over time. There is great need for further research as the County’s fast
growing population exerts pressure on the wastewater treatment plant service into the future.
Acknowledgements: The authors are grateful to Kisii University and the African Development Bank
(AfDB) for the financial and logistical support of this research. We also thank National Commission for
Science Technology and Innovation (NACOSTI) for permission to carry out this research. We are grateful
to Gusii Water and Sanitation Company, Kisii County for the free access to the wastewater treatment plant
during sampling. Also, we are grateful to the Technical University of Kenya (TUK) for laboratory
assistance.
Author Contributions: Conceptualization, R.D., O.A; methodology, R.D., and O.A; validation, G.A.,
O.R., O.P., O.R., and O.A; formal analysis, R.D., O.J., and O.A; data curation, R.D.; writingoriginal
draft preparation, R.D., O.J, O.A., O.R., N.H., G.B., and N.O
Conflict of Interest: The authors declare no conflict of interest. The funding sponsors had no role in the
design of the study and in the decision to publish the results.
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... Dense mats of macrophyte assemblages affect phytoplankton growth through shading which limits light availability for algae [28] , and they also smother algae through their allelopathic effects and competition for nutrients [8,9] . Sometimes, the wastes discharged into the lake contains high concentration of heavy metals such as copper, lead and mercury which bioaccumulate in the muscles of the fish and end up in higher organisms in the aquatic food chains fed directly to human population [29,30,44] . Through collaborative efforts by the Kenya marine and fisheries research institute (KMFRI) and the department of fisheries, periodic restocking of the lake has been conducted with the hope of reviving the lake's declining fisheries [17,18] . ...
... Through collaborative efforts by the Kenya marine and fisheries research institute (KMFRI) and the department of fisheries, periodic restocking of the lake has been conducted with the hope of reviving the lake's declining fisheries [17,18] . However, continuous restocking and introductions of exotic species have caused complex interactions among the existing populations and changing environment and the lake is currently regarded as a natural "pond" because all the species in the lake are introduced [30] . The fish stocks have been unstable and changing over time. ...
... Turbidity affects primary productivity which provides a food base for planktivorous and herbivorous species such as O. leucostictus and T. zillii [29] . It also affects breeding in Black bass, Micropterus salmoides which make their nest at the muddy bottom [24,30] . Species introductions have been made into L. Naivasha since 1925 with most introductions recording little ecological success in the new ecosystem [30] . ...
Article
Full-text available
Lake Naivasha is the second largest freshwater lake in Kenya, located in the floor of the Eastern arm of the Kenyan Great Rift Valley and supports a large biodiversity of macrophytes, aquatic birds and exotic fish species. Consequently, the lake is recognized for tourism, fishing, water provision, and has been designated as a Ramsar site. This paper followed the use of unpublished and published data as the key methodological design. The aim of this paper was to undertake a comprehensive review of the changes of Lake Naivasha fisheries by focusing on the causes, exploitation trends, and conservation measures. The limnological and fishery status of Lake Naivasha have received a significant attention due to the need for better management practices to sustain its ecological and economic values. The fishery of L. Naivasha has been dominated by different species with the current catch contribution consisting mainly of common carp, Cyprinus carpio, Nile tilapia, Oreochromis niloticus, blue-spotted tilapia, O. leucostictus and African catfish, Clarias gariepinus. The previous dwindling trends observed in Lake Naivasha fisheries has been attributed to factors such as catchment degradation, pollution, excessive water abstraction for flower farming and domestic use, introduction of invasive plant and animal species, changing water quality attributed to increasing anthropogenic and climate change. There has been immense amount of efforts put by private and public institutions to arrest this problems affecting the lake towards management and conservation. In order for sustainable utilization, and exploitation of the lake resources, there is urgent need to consider a holistic ecosystem management approach within the lake's catchment area.
... Dense mats of macrophyte assemblages affect phytoplankton growth through shading which limits light availability for algae [28] , and they also smother algae through their allelopathic effects and competition for nutrients [8,9] . Sometimes, the wastes discharged into the lake contains high concentration of heavy metals such as copper, lead and mercury which bioaccumulate in the muscles of the fish and end up in higher organisms in the aquatic food chains fed directly to human population [29,30,44] . Through collaborative efforts by the Kenya marine and fisheries research institute (KMFRI) and the department of fisheries, periodic restocking of the lake has been conducted with the hope of reviving the lake's declining fisheries [17,18] . ...
... Through collaborative efforts by the Kenya marine and fisheries research institute (KMFRI) and the department of fisheries, periodic restocking of the lake has been conducted with the hope of reviving the lake's declining fisheries [17,18] . However, continuous restocking and introductions of exotic species have caused complex interactions among the existing populations and changing environment and the lake is currently regarded as a natural "pond" because all the species in the lake are introduced [30] . The fish stocks have been unstable and changing over time. ...
... Turbidity affects primary productivity which provides a food base for planktivorous and herbivorous species such as O. leucostictus and T. zillii [29] . It also affects breeding in Black bass, Micropterus salmoides which make their nest at the muddy bottom [24,30] . Species introductions have been made into L. Naivasha since 1925 with most introductions recording little ecological success in the new ecosystem [30] . ...
Article
Full-text available
Lake Naivasha is the second largest freshwater lake in Kenya, located in the floor of the Eastern arm of the Kenyan Great Rift Valley and supports a large biodiversity of macrophytes, aquatic birds and exotic fish species. Consequently, the lake is recognized for tourism, fishing, water provision, and has been designated as a Ramsar site. This paper followed the use of unpublished and published data as the key methodological design. The aim of this paper was to undertake a comprehensive review of the changes of Lake Naivasha fisheries by focusing on the causes, exploitation trends, and conservation measures. The limnological and fishery status of Lake Naivasha have received a significant attention due to the need for better management practices to sustain its ecological and economic values. The fishery of L. Naivasha has been dominated by different species with the current catch contribution consisting mainly of common carp, Cyprinus carpio, Nile tilapia, Oreochromis niloticus, blue-spotted tilapia, O. leucostictus and African catfish, Clarias gariepinus. The previous dwindling trends observed in Lake Naivasha fisheries has been attributed to factors such as catchment degradation, pollution, excessive water abstraction for flower farming and domestic use, introduction of invasive plant and animal species, changing water quality attributed to increasing anthropogenic and climate change. There has been immense amount of efforts put by private and public institutions to arrest this problems affecting the lake towards management and conservation. In order for sustainable utilization, and exploitation of the lake resources, there is urgent need to consider a holistic ecosystem management approach within the lake's catchment area.
... Wastewater is of poor quality as it is rich in pathogenic microorganisms [1,2], heavy metals [3][4][5], organic and inorganic chemicals, and toxic substances [6][7][8]. Therefore, wastewater is unsuitable for domestic, agricultural, and industrial uses and pollutes the environment [9][10][11]. ...
Chapter
Full-text available
Knowledge of the nature and composition of wastewater is critical in wastewater treatment, reuse, and disposal. Suneka wastewater treatment plant (Suneka WWTP) treats wastewater from Kisii municipality. The treated effluent is discharged into river Riana. The Suneka WWTP does not have adequate capacity to treat all the wastewater from the municipality fully. The discharge of partially or untreated wastewater into the Riana River, particularly during system breakdown, is of great concern due to the potential health risks it poses to the environment, humans, and animals. This chapter discusses phytoplankton community structure in the Suneka WWTP and their roles in wastewater treatment, especially in heavy metal accumulation. Phytoplankton species identified belonged to Bacillariophyceae, Chlorophyceae, Cyanophyceae, Euglenaphyceae, Zygnematophyceae, and Dinophyceae. The total phytoplankton biovolume recorded was 680.99 mm 3 L −1. The phytoplankton also contributed to wastewater polishing by converting nutrients into their biomass and removing heavy metals from the wastewater column through bioaccumulation.
... The sample was then allowed to cool before adding 5 ml of H 2 O 2 until a clear solution was observed. The content of the flask was transferred into a 50 ml volumetric flask and diluted to the mark of 0.01 N HNO 3 according to a previous study (26) . All the procedures were performed in the fume hood (27). ...
Article
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Introduction This study aimed to measure the concentration of toxic heavy metals in wastewater samples and Nile tilapia ( Oreochromis niloticus ) species inhabiting wastewater (waste stabilization ponds) and evaluate their safety as a food source in southwestern Ethiopia. For this purpose, toxic metals like lead (Pb), cadmium (Cd), arsenic (As), and mercury (Hg) in wastewater samples and fish tissues (muscle, gill, and liver) were independently examined. Methods A laboratory-based cross-sectional study was performed to ascertain the levels of Pb, Cd, As, and Hg in the fish tissues of O. niloticus and wastewater samples. Heavy metal levels were analyzed by microplasma atomic emission spectrometry (Agilent 4210 MP-AES) and hydrogen-generated atomic absorption spectrometry (HGAAS, novAA 400P, Germany). Results Heavy metal concentrations were measured in the following decreasing order (µg L ⁻¹ ): Cd > Pb > As > Hg in facultative and maturation ponds, with Cd (27.66 µg L ⁻¹ ) having the highest concentration and Hg (0.349 µg L ⁻¹ ) having the lowest concentration. Among the heavy metals detected in the wastewater samples, Hg showed a statistically significant difference between the sampling points ( p = 0.023). The maximum metal concentration was measured for Pb (0.35 mg kg ⁻¹ ) and Cd (0.24 mg kg ⁻¹ ) in the muscle tissue of O. niloticus . The value of arsenic (0.02 mg kg ⁻¹ ) detected in fish edible muscles exceeded the FAO/WHO maximum permissible limit (MPL = 0.01) for human consumption. The carcinogenic and non-carcinogenic health risks of consuming fish due to trace metals were relatively low and posed fewer potential threats to human health. According to this finding, children were more susceptible to heavy metal exposure than adults. Conclusion Due to the high quantities of these harmful heavy metals, wastewater from oxidation ponds should not be used for fishing to avoid bioaccumulation. The target carcinogenic risk (TR) and target hazard quotient (THQ) indicated that all heavy metals were below the safe threshold. This research will provide a baseline for monitoring trace metals in various edible aquatic creatures and for future research in artificial habitats and regulatory considerations.
... Finding an effective process for removing poisonous metals is essential to measure these metals with a precise, accurate, and reliable analytical method. Some of the analytical techniques that are employed for measuring the metal concentrations are inductively coupled plasma-optical emission spectrometry (ICP-OES) (Baraud et al. 2020;da Cruz et al. 2022), atomic absorption spectroscopy (AAS) (Douglas et al. 2022;Kassim et al. 2022), X-ray fluorescence (XRF) (Adler et al. 2020;Li et al. 2021b;Wang et al. 2022), and UV-Vis spectrophotometer, which requires the formation of a colored compound with a suitable ligand (Guo et al. 2020). Among the downsides of these methods being expensive and time-consuming are distinguished. ...
Article
Full-text available
This work investigates the use of Aspergillus brasiliensis, this particular species of Aspergillus, as a biosorbent for the first time. It is employed to biosorption Zn(II), Cd(II), and Pb(II) and combines the biosorption experiments with electrochemical measurements for in situ analysis. For the experiments, a batch system was employed with the dead biomass. In order to determine the biosorption capacity, the impact of several operational parameters was examined, including pH, temperature, agitation speed, contact time, and initial metal concentration, and the optimum values were 5, 30 °C, 150 rpm, 2 h, and 150 ppm, respectively. Using 0.2 g biomass in 100 mL solution, the maximal uptake of Zn(II), Cd(II), and Pb(II) at ideal conditions was determined to be 33.67, 24.51, and 36.76, respectively. The Langmuir and Freundlich isotherm model was studied for the biosorption process. An electrochemical sensor using nanomaterials is designed and constructed to monitor the concentration of these metals. The silver nanoparticles functionalized with thiosemicarbazide and 6-mercaptohexanoic acid (mercaptohexanoylhydrazinecarbothioamide-coated silver nanoparticles, MHHC-AgNPs) linked to the carboxylated multi-walled carbon nanotubes (MWCNTs) were utilized for glassy carbon electrode modification (MHHC-AgNPs/MWCNTs/GCE). The concentration range of Zn(II) is 0.7–173 µg/L, Cd(II) is 1.18–293 µg/L, and Pb(II) is 2.17–540 µg/L. The detection limits for Zn(II), Cd(II), and Pb(II) are 0.036 µg/L, 0.15 µg/L, and 0.16 µg/L, respectively. Under optimized conditions, these results were obtained using the differential pulse anodic stripping voltammetry method (DPASV). The successful detection of Zn(II), Cd(II), and Pb(II) was achieved by effectively preventing interference from other common ions. It was effectively employed for measuring ions in industrial wastewater, and the results obtained aligned with those acquired from an atomic absorption spectrometer (AAS). Thus, Aspergillus brasiliensis species, along with this electrochemical sensor, can be used to remediate and monitor environmental pollution, Zn(II), Cd(II), and Pb(II), successfully.
... In urban and peri-urban settlements, irrigation water for crops frequently comes from wastewater in developing and under-developed countries. Due to wastewater irrigation, harmful microbes are introduced, and buildup of HMs including nickel (Ni), chromium (Cr), cadmium (Cd), lead (Pb), and zinc (Zn) endangers the environment's quality and human life associated with the reuse of this water (Othman et al. 2021;Douglas et al. 2022). World Health Organization (WHO) recommendations for the quality of wastewater to be used during irrigation do not fall within standard limits, as paracetamol, triclosan, and various HMs and herbicides (such ciprofloxacin and atrazine) may be found in wastewater sources (Othman et al. 2021). ...
Article
Full-text available
Heavy metal stress poses a significant threat to the productivity of agricultural systems and human health. Silicon (Si) is widely reported to be very effective against the different heavy metal stresses in crops. According to reports, it can help plants that are under cadmium (Cd) and nickel (Ni) stress. The presented work investigated how silicon interacted in Cd- and Ni-stressed wheat and mitigated metal toxicity. A pot experiment was carried out in which wheat crop was irrigated with Cd- and Ni-contaminated water. Application of Cd and Ni-contaminated water to wheat significantly reduced the root and shoot growth parameters and physiological and biochemical factors while increasing the antioxidant enzymatic activity and bioaccumulation of Cd and Ni metal in shoot and root as compared to the control. Application of Si led to an improvement in physiological parameters, i.e., greenness of leaves, i.e., SPAD values (17% and 26%), membrane stability (26% and 25%), and growth parameters i.e., root surface area (42% and 23%), root length (81% and 79%), root dry weight (456% and 190%), root volume (64% and 32%), shoot length (41% and 35%), shoot dry weight of shoot (111% and 117%), and overall grain weight (62% and 72%) under Cd and Ni stress, respectively. It increased the activity of antioxidant activity (max. up to 20%) whereas decreased the metal bioaccumulation of Cd and Ni in the roots and shoot (max. up to 62%) of wheat. It was concluded that the application of Si potentially increases antioxidant activity and metal chelation resulting in decreased oxidative damage and reducing the effect of Cd and Ni stress on wheat which improves growth and physiological parameters as well as inhibits Cd and Ni inclusion in food chain under Cd and Ni toxicity reducing health risks associated with these metals.
... To further polish the effluent, a study was conducted by Omondi [28] on the potential of constructed wetlands. Other studies conducted in the Suneka WWTP have focused on heavy metals concentrations in wastewater samples [4], phytoplankton [11] and zooplankton diversity [12]. The discharge of partially or untreated wastewater into the Riana River particularly ...
Article
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Wastewater is rich with inorganic, organic, and microbial pollutants and has been linked to environmental pollution, and health hazards including water and food borne illnesses. Wastewater polishing is aimed at removing these pollutants, rendering the treated wastewater re-usable for domestic, agricultural, and industrial purposes. The study aimed to assess the efficiency of the Suneka Wastewater Treatment Plant (Suneka WWTP) in wastewater polishing based on the analysis of total and fecal coliform bacteria (TC and FC) removal during the period of August-December, 2019 at seven (7) sampling points. A culture method was used to determine the microbial composition of the wastewater. The coliform levels of the discharged effluent were then compared with the NEMA standards. The means of TC and FC were 76.3 ± 10.98 and 55.66 ± 9.89 counts/100 ml respectively. The mean polishing efficacy of the Suneka WWTP was of major concern as it was observed that coliforms (TC and FC) counts did not meet the required NEMA standards. The Gusii Water and Sanitation Company could use this information to improve wastewater treatment and meet the established guidelines for effluent coliform level discharge into the environment.
... Stormwater can be the largest source of lead followed by laundry and bathrooms (Gray & Becker, 2002). Other studies reported sources of lead including pesticides, pipelines, metal products, cables, and paints in wastewater samples (Douglas et al., 2022;Tyagi, 2014). The high accumulation of Pb can cause hematological changes, anemia, hypertension cardiovascular, reproductive, kidney and joint disorders in adults, whereas in children it can affect growth and learning ability leading to brain disorders (Galadima & Garba, 2012;Mahugija et al., 2018). ...
Article
Full-text available
Rapid increase in population and industrialization has not only improved the lifestyle but adversely affected the quality and availability of water leading to ample amount of wastewater generation. The major contribution towards wastewater production is from sewage. Regular monitoring and treatment of sewage water is necessary to conserve and enhance the quality of water. The present study focuses on monitoring of sewage water within the sewage system of a residential university. A total of 16 samples from different manholes were collected for physicochemical and heavy metals analysis and compared with final effluent collected from integrated constructed wetlands (ICWs) to assess its removal efficiency. The mean concentrations of influent and effluent were compared with national environmental quality standards (NEQS) for municipal discharge (pH 6–9, COD 150 mg/L, TSS 200 mg/L and TDS 3500 mg/L) and international agricultural reuse standards (IARS) (pH 6–8, COD <150 mg/L, TSS < 100 mg/L) respectively. Among all physicochemical parameters, influent values for chemical oxygen demand (COD) (169.56–258.36) mg/L exceeded the limit of NEQS for discharge into inland waters, whereas for total suspended solids (TSS) the concentration exceeded for discharge into STP (406 mg/L) and inland waters (202.33 mg/L). However, effluent concentrations for all the parameters were found within the permissible limit set by IARS. The removal efficiency for different parameters such as phosphate- phosphorus (PO4³-P), COD, TSS, total dissolved solids (TDS) and total kjeldahl nitrogen (TKN) were 52, 53, 54, 35, and 36%, respectively. Heavy metal concentrations were compared with WHO guidelines among which lead (Pb) in effluent and chromium (Cr) in influent exceeded the limit (Pb 0.01 and Cr 0.05 mg/L). Interpolation results showed that zone 2 was highly contaminated in comparison to zone 1 & 3. Statistical analysis showed that correlation of physicochemical parameters and heavy metals was found significant (p < 0.05). Graphical Abstract
... Finding an effective process for removing poisonous metals is essential to measure these metals with a precise, accurate, and reliable analytical method. Some of the analytical techniques that are employed for measuring the metal concentrations are inductively coupled plasma-optical emission spectrometry (ICP-OES) (Baraud et al. 2020;da Cruz et al. 2022), atomic absorption spectroscopy (AAS) (Douglas et al. 2022;Kassim et al. 2022), X-ray fluorescence (XRF) (Adler et al. 2020;Li et al. 2021b;Wang et al. 2022), and UV-Vis spectrophotometer, which requires the formation of a colored compound with a suitable ligand (Guo et al. 2020). Among the downsides of these methods being expensive and time-consuming are distinguished. ...
... Environmental changes in water quality impact zooplankton community groups differently [4]. Wastewater is rich with pollutants and thus of poor quality and more specifically is characterized by high biological oxygen demand (BOD) [5,6]. Wastewater quality affects the plankton that's phytoplankton and zooplankton species structure and distribution [3,7,8,9,10]. ...
Article
Full-text available
Zooplankton have been used as bioindicators of water quality. In this study, we assessed the spatial-temporal variations of zooplankton in the Kisii town wastewater treatment plant and how they were influenced by limnological parameters between May and August 2021. Triplicate zooplankton samples were collected monthly for laboratory analysis. Physical parameters were measured in situ using a YSI multi-parameter probe while triplicate wastewater samples were collected for chemical parameters analyses ex situ. Eleven (11) zooplankton species were identified belonging to three groups. Cladocera was represented by 5 species (45.5 %), Rotifera by 4 species (36.4 %), and Copepoda by 2 species (18.2 %). The total zooplankton density recorded was 515IndL-1 with the family Cladocera dominating (57.7 %) followed by Copepoda (22.8 %) then Rotifera (19.5 %) with the least number in the population density. The limnological parameters measurements indicate considerable wastewater pollutant removal during polishing but negatively influenced zooplankton diversity. Therefore, zooplankton can be used to monitor wastewater treatment progress.
Article
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The levels of heavy metals, namely Mn, Cu, Zn, Ni, Pb in water, flora and sediments along the Thika River, Kenya were studied in September 2015, to investigate their distribution and to determine the extent of pollution. The levels of selected heavy metals were determined using total X-ray fluorescence for water samples and energy dispersive x-ray fluorescence for sediment and algae samples. In general, the concentration levels of heavy metals in water samples ( g/l) were; Mn (53.5 - 605), Cu (< 10 - 303), Zn (22 - 325), Ni (<15 - 77), Pb (<10 - 84) while those in sediment samples (mg/kg) were; Mn (2230 - 8659), Cu (51 - 115), Zn (153 - 432), Ni (67 - 172), Pb (32 - 177). Similarly, the levels of heavy metals in Cladophora (mg/kg) were Mn (3719 - 21200), Cu (65 - 129), Zn (153 - 434), Ni (35 - 235), Pb (17-72). Statistical analyses also revealed that there was a significant difference in heavy metal concentrations between the three media for all elements studied. Based on enrichment factors, geoaccumulation indices, pollution load index and contamination factors, all sampled sediments were generally contaminated with Pb, Cu, Zn, Mn and Ni to a moderate degree, thus requires intervention to curb on the rising levels of pollutants. Statistically significant interrelationship was observed between sediments and Cladophora, which supports the idea that, Cladophora is an appropriate bio-indicator for heavy metal pollution. Keywords: heavy metal, pollution, Cladohphora, geoaccumulation index, enrichment factors
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Karimi RD, Ngeranwa JJN, Njagi ENM, Kariuki S. 2022. The bacterial flora of Oreochromis niloticus and Clarias gariepinus from earthen ponds in Sagana and Masinga, Kenya. Intl J Bonorowo Wetlands 12: 63-73. Food-borne diseases traced to fish consumption have been reported globally, including in Kenya. The aspect of food quality as far as fish consumption is concerned is underestimated in Kenya though aquaculture has been promoted. The bacterial flora of Tilapia (Oreochromis niloticus Linnaeus, 1758) and Catfish (Clarias gariepinus Burchell, 1822) from Masinga Dam and earthen ponds at Sagana fish farm was determined in this study to determine the anti-microbial response of the pathogenic bacteria. Tilapia fish and Catfish samples were collected from Masinga Dam and Sagana farm in the dry and rainy seasons. The fish were skinned, and gut content was taken for laboratory tests. The water and water sediment samples from these two study sites were also collected. Those samples were processed and cultured in MacConkey agar, and the selective media were subcultured in the colonies and then subjected to morphological examination from cultures. Then, the biochemical tests were carried out using commercially available API kits. The study showed the presence of bacterial species belonging to Enterobacter spp. (n=34), Pseudomonas spp. (n=6), Aeromonas spp. (n=5), Vibrio spp. (n=3) and Acinetobacter spp. (n=2) isolates during the dry season, while bacterial species belonging to Enterobacter spp. (n=31), Pseudomonas spp. (n=6), Aeromonas spp. (n=4) isolates during the dry season. The anti-microbial susceptibility analysis showed that the highest resistance rates were found against Ampicillin (Amp) (61.5% of isolates), Amoxicillin (AmL) (65.9% of isolates), Tetracycline (Te) (31.8% of isolates), and Chloramphenicol (C) (27.5% of isolates) while the lowest was Nalidixic acid (Na), Cefuroxime (Cxm) and Streptomycin (S) at (4.4% of isolates) each. All isolates were sensitive to Gentamycin (Gen), Ciprofloxacin (Cip), and Cefotaxime (CTX). The presence of the above organisms, some potentially pathogenic to humans, indicates that improperly handled, undercooked, or consumed raw fish may cause disease in susceptible individuals. At the same time, some isolates’ anti-microbial resistance indicates that the use of antibiotics in aquaculture to promote growth should be studied further with a view to policy formulation.
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Phytoplanktons are free-floating microscopic plants in water and they are the primary producers providing food to aquatic organisms. However, water quality affects the species production and assemblage in terms of diversity, composition, and abundance. This study assessed the spatial and temporal diversity and abundance of phytoplanktons in the Gusii wastewater treatment plant. A total of 124 phytoplankton species were identified and belonged to six families: Euglenophyceae, Bacillariophyceae, Dinophyceae, Cyanophyceae, Chlorophyceae, and Zygnemophyceae. The phytoplankton biovolume was 385.24mm 3 /L, with the family Euglenophyceae contributing the largest percentage. The species diversity index (H') was generally low (H' = 1.759 and 0.7596) in the effluent and influent respectively, indicating a considerable increase in diversity as the wastewater undergoes treatment. The low diversity was attributed to changes in physical, chemical, and biological environmental conditions. The effluent was richer in species, with a value of 5.829, while the influent was the least with 3.409. The low phytoplankton diversity in the wastewater treatment plant was influenced by the physicochemical parameters. It is therefore recommended that the quality of the wastewater during treatment needs to be monitored continuously for quality as baseline information to guide stakeholders and to ensure sustainability for the Gusii wastewater lagoon ecosystem health.
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Lake Koka has several important socioeconomic uses: hydroelectric power generation, domestic water supply, irrigation, recreation and fishery. It is currently under serious threat because of point and non-point pollution inputs. The objective of the present study was to examine the concentration of heavy metals (Mn, Cr, Pb, Zn, Cu, Ni and Cd) and their bioaccumulation, and biomagnification factors along the lake's food chain in order to assess the potential human and ecological health risks. Water, sediment and plankton samples were collected from seven sampling sites, and fishes were purchased on site from fishermen. The analyses were performed using a graphite furnace atomic absorption spectrophotometer. Heavy metal levels in the sediment samples were ranked in the order of Mn > Cr > Pb > Zn > Cu > Ni > Cd. Similarly, the metal concentration in the fish muscles was Cr > Cu > Pb > Cd. The sediment bioaccumulation factor (<1) and water bioaccumulation factor (>1) for Cd, Pb and Cr indicated the lake water exhibited higher concentrations than the sediment. In parallel, the Cr biomagnification factor for zooplankton, catfish, Nile tilapia and common carp was 1.63, 1.18, 1.36 and 2.28, respectively. The Cr concentrations at the Modjo (or Mojo) Upstream, Modjo Downstream and Kentare sites, and the Pb concentrations at riverine sites were above the permissible limits established by the World Health Organization. Cr ranked as fish species > zooplankton> phytoplankton, being above the permissible limits in catfish, Nile tilapia and common carp. Generally, the weekly intake estimates were considerably lower than the tolerable human intake values provided by WHO and others. However, Cr biomagnified along the trophic levels ultimately reaching the top consumers, with Cr (VI) being carcinogenic. The lake is a major fishery source, indicating care must be taken in regard to the weekly intake of the fishes, particularly common carp.
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