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Heavy metal toxicity in the water column and benthic sediments of a degraded tropical stream
Ecotoxicology and Environmental Safety 190 (2020) 110153
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Heavy metal toxicity in the water column and benthic sediments of a degraded tropical stream
T
Emmanuel O. Akindelea,∗, Omobukola D. Omisakina, Oluwagbemiga A. Onia, Olanrewaju O. Aliua,b, Gbenga E. Omoniyic, Oluwaseun T. Akinpelud a
Department of Zoology, Obafemi Awolowo University, Ile-Ife, Nigeria Health Safety, Security and Environment, Eterna PLC, Lagos, Nigeria c Department of Biology/Microbiology/Biotechnology, Alex Ekwueme Federal University, Ndufu-Alike Ikwo, Ebonyi State, Nigeria d Department of Animal Biology, Federal University of Technology, Minna, Nigeria b
A R T I C LE I N FO
A B S T R A C T
Keywords: Agriculture Pollution Riparian corridor Stream Tropical freshwaters
Agriculture and other anthropogenic activities on riparian corridors pose a great ecotoxicological risk to freshwater ecosystem and human health. Using the atomic absorption spectroscopy, concentrations of heavy metals (Cd, Cu, Fe, Zn, Pb and As) in the water column and benthic sediments of a degraded tropical stream (Opa Stream, Ile-Ife, Nigeria), were assessed with a view to determining the stream's health status. Three metals (Cu, Pb, and As) showed significant positive correlations between concentrations in the water column and the benthic sediments. All but one heavy metal (i.e. Zn) had reached disturbing concentrations in the stream's water column and exceeded their recommended limits in surface freshwaters. The geo-accumulation index (Igeo) and contamination factor (CF) indicated that the stream was moderately contaminated with Cd (0 < Igeo < 1; CF much closer to 1). This study concludes that the stream was impacted with heavy metals in its water column and slightly impacted with Cd on its bed, thus raising health concerns for plankton, benthic organisms and all users of the surface water. More conservation attention by relevant stakeholders through monitoring and regulation of human activities in river basins, is recommended for the sustenance of tropical freshwater ecosystem and human health.
1. Introduction
waterbody; thus, they are the most important sink of heavy metals in freshwater environments (Morin et al., 2007). Heavy metals are among persistent bioaccumulative toxicants (PBTs) just like organo-metal compounds. They are ubiquitous, persistent and bioaccumulative in aquatic systems (Ray and McCormick-Ray, 2014), consequent on which they have gained so much public attention due to their implications for environmental health (Ahmed et al., 2015; Islam et al., 2015). A heavy metal refers to any metal or metalloid element which density ranges from 3.5 to 7 g/cm3 and which is toxic at low concentrations (Tchounwou et al., 2012). Heavy metals are also regarded as trace elements because of their presence in trace concentrations in various environmental matrices. They occur naturally in the environment (i.e. lithogenic) but their concentrations may also increase astronomically through anthropogenic activities e.g. domestic/ industrial effluents and agricultural activities (Ravindra et al., 2014; Outa et al., 2019). Among heavy metal toxicological studies in tropical freshwaters are the works of Aprile and Bouvy (2010) on a river basin in northeastern Brazil, Ahmad et al. (2010) in Buriganga River
One of the unique features of pristine or near-pristine tropical streams and rivers is the presence of riparian forests which play a very crucial role in limnological characteristics and conservation of such systems. Whenever these forests are removed for agricultural or industrial purpose, the impacts are felt in adjacent water bodies through the release of chemicals, soil erosion and the reduction of riparian cover (Mori et al., 2015). Loss of riparian forests or bankside vegetation removal has also been attributed to high sediment load in surface waters, with attendant consequences on water quality and aquatic ecosystem health (Naiman et al., 2005). These sediments, which are typically transported by fluid flow, eventually settle on the stream bed when the flow velocity is too low to keep them in suspension (Akindele and Olutona, 2014). Hence, heavy metals that are bound to particulate matters (suspended sediments) eventually settle down and become incorporated into bottom (benthic) sediments. Comparatively, benthic sediments have a higher retention capacity than any other section of a
∗
Corresponding author. E-mail address: [email protected] (E.O. Akindele).
https://doi.org/10.1016/j.ecoenv.2019.110153 Received 11 October 2019; Received in revised form 30 December 2019; Accepted 30 December 2019 0147-6513/ © 2019 Elsevier Inc. All rights reserved.
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bimonthly from August 2017 to February 2018 between 09:00 and 12:00 on each sampling day. At each site, percentage vegetation cover was estimated as the proportion of the channel width that was covered by vegetation, and their corresponding values were 90%, 50%, 10% and 95% at Stations 1, 2, 3 and 4, respectively. Float displacement method (Akindele et al., 2018) was used to determine flow velocity; water depth was determined with a calibrated line attached to a weight; and channel width was determined by measuring the distance across the two sides of the stream. Discharge was derived from the product of flow velocity, water depth and channel width (Chapman and Kimstach, 2006), at each station and sampling period. Water samples were collected in new and sterilized 2-L plastic containers, and which were later rinsed with water from each site before sample collection. The water samples were kept in a cold environment and stored in a refrigerator under a frozen condition pending their laboratory analyses. Two composite sediment samples were collected at each station with the aid of a grab and homogenized as one representative sample. The samples were stored in a polythene bag and taken to the laboratory.
(Bangladesh), Reza and Singh (2010) in India, and Chidya et al. (2011) in Likangala River (Malawi). Other studies include the works of Akindele et al. (2017) in Osun River (Nigeria), Asare et al. (2018) in Bontanga Reservoir (Ghana), Ezemonye et al. (2019) in Benin River (Nigeria), Outa et al. (2019) in the Kenyan part of Lake Victoria, and Wasike et al. (2019) in Kuywa River (Kenya). In some of these studies, heavy metal contaminations were recorded in surface waters and benthic sediments. For instance, the concentrations of Pb and Cd in Kenya's Kuywa River ranged from 0.57 ± 0.09–3.36 ± 1.15 mg/L and 0.32 ± 0.02–0.99 ± 0.67 mg/L, respectively; as against their respective recommended limits of 0.005 mg/L and 0.01 mg/L for freshwater life. In the same vein, Ezemonye et al. (2019) have reported above-limit concentrations for Cd (0.01 mg/L) and Pb (0.18 mg/L) in the Benin River of Nigeria. A study on the distribution of some selected heavy metals in the Kenyan part of Lake Victoria by Outa et al. (2019) has also further established the role of anthropogenic impacts on the concentration of heavy metals in inland waters. The study revealed that the part of the lake that was closest to industrial and municipal waste water discharges was severely polluted with Cu and Pb. Opa Stream is a lotic tropical freshwater system which has been degraded through substantial loss of its riparian cover and conversion of the forest to various purposes to meet human needs (e.g. subsistence and commercial farming, car wash, abattoir, gas station and residential buildings). This trend has been reported in Nigeria as the human population grows with attendant encroachments on riparian corridors and waste dumping in surface waters (Akindele and Olutona, 2014). Furthermore, current human population growth in many Afro-tropical nations and future predictions (UN DESA, 2017) imply that more wetlands may be lost or degraded except stringent practices are introduced to initiate early conservation measures. This research is thus hinged on the following hypotheses: (1) Human activities on the riparian corridor could have a significant impact on a stream's health through heavy metal contamination; (2) suspended solids and dissolved solids determine metal concentrations in water columns; and (3), metal concentrations in a water column may determine those on a stream bed.
2.3. Laboratory and data analyses Total suspended solids (TSS) and total dissolved solids (TDS) were both analysed by gravimetric method (APHA, 2005). In the case of sediment, samples were first air-dried in the laboratory after which they were ground to fine particles using a mortar and a pestle. Digestion of samples was as described by Makinde et al. (2016) i.e. with aqua-regia (HNO3−:1, HCl:3). Metals in both water and sediment samples were analysed by atomic absorption spectrophotometry as described by Welz and Sperling (1999). The samples were analysed with PG990 spectrophotometer (Beijing Purkinje General Instrument Co. Ltd, China) by flame atomization, using air-acetylene flame and single element hollow cathode lamp. As a quality control measure, reference standards were compared in each case with both water and sediment samples, and a calibration curve was plotted. The detection limits of the metals (in mg/ L) were 0.0028 Cd, 0.004 Cu, 0.0046 Fe, 0.003 Zn, 0.16 Pb and 0.16 As. Shapiro-Wilk test for normality indicated that most of the investigated parameters were normally distributed (p > 0.05); hence the use of analysis of variance (ANOVA) for temporal and spatial variations, and Pearson's correlation for relationships between metals and hydrological parameters/TSS/TDS. Principal component analysis was used to establish the relationships among metals in the water as well as in the stream bed. Paleontological Statistics (PAST) and ‘r’ statistical software were used for data analysis. Pollution status of heavy metals in the sediment was assessed using the geo-accumulation index (Igeo) and contamination factor (CF). The geo-accumulation index was promulgated by Müller (1969) and has since, been used to ascertain the level of heavy metal contamination in sediments/soils (Raut et al., 2017). It is mathematically expressed as:
2. Materials and methods 2.1. Study area The downstream section of Opa Stream in Ile-Ife was chosen for this study. It is along Ede Road with GPS estimates of 004°30′38″E − 004°3048″E and 07°29′95″N - 07°30′18″N. Two seasons characterize the study area, viz: the dry season (low flow/discharge) which lasts from November to March and the wet season (high flow/discharge) which lasts from April to October. During the rainy season, the stream's water level rises and becomes turbid due to a high volume of water from the upstream reservoir and the surrounding farmland. The primary lowland rainforest of the area has almost been taken over by a secondary forest as a result of intensive agricultural practices. Among the dominant crops in the area are cocoa plantation, plantain vegetation, and many food crops. Other noticeable anthropogenic interferences on the stream's riparian corridor are block-making industries, petroleum and cooking gas station, car wash, abattoir, hostels and residential buildings. Subsistence and commercial farmers in the area use agrochemicals (e.g. Ridomine, Lindane, Glyphosate) to increase the quality of their farm produce without taking cognizance of the environmental effects of such practice on the stream. By and large, wastewater entering the stream can be ascribed mainly to point sources such as the car wash, abattoir, block-making industries and commercial farmlands.
Cn ⎞ Igeo = log 2 ⎛ ⎝ 1.5 Bn ⎠ where. Igeo = Geo-accumulation index Cn = Measured concentration of heavy metal in the sediment Bn = Geochemical background value of heavy metal in the earth crust 1.5 = Background matrix correction factor due to lithogenic variations and very small anthropogenic influences According to Müller (1969) and Raut et al. (2017), there are seven classes of geo-accumulation index ranging from 0 to 6, and these were used to determine the level of contamination of each metal in the sediment. Geo-accumulation index < 0 indicates sediment is practically uncontaminated, Igeo 0–1 indicates very moderate contamination, 1–2 indicates moderate contamination, 2–3 indicates moderate to heavy
2.2. Field determinations and collection of samples Four sampling stations were established along the longitudinal flow of the stream in the study area (Fig. 1), and samples were collected 2
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Fig. 1. Map of the study area showing the sampling stations (Inset: Maps of Africa, Nigeria and Osun State showing the study area).
Three metals (Cu, Zn & As) recorded their lowest concentrations at St. 1 while another three (Cd, Cu & Zn) recorded their highest values at St. 3 (Supplemental Fig. 1). There were however no significant (p > 0.05) spatial variations for the metals. The overall mean concentrations of the metals in the water column were 0.019 ± 0.004 mg/L Cd, 4.780 ± 1.409 mg/L Cu, 1.106 ± 0.313 mg/L Fe, 0.448 ± 0.108 mg/L Zn, 0.010 ± 0.002 mg/L Pb, and, 0.018 ± 0.004 mg/L As. Relationships among metals in the water column indicate significant negative correlations between Cd and Pb (r = −2.83 × 10−14, p < 0.001), Fe and Zn (r = −0.860, P < 0.05), Pb and Zn (r = −0.933, p < 0.01), and Pb and As (r = −0.894, p < 0.05). Significant positive relationships were recorded between Cu and Zn (r = 0.997, p < 0.001) and Cu and As (r = 0.824, p < 0.05), while Cu and Pb were negatively correlated (r = −0.959, p < 0.01). Principal component analysis indicates that two components accounted for 68.9% of the variance and there was a very strong relationship between Zn and As, and among Cu, Pb and Cd (Fig. 3).
contamination, 3–4 indicates heavy contamination, 4–5 indicates heavy/extreme contamination, and 5–6 indicates extreme contamination. Contamination factor of heavy metals was calculated using the formula prescribed by Forstner and Wittmann (1981),
i. e . CF = C / Cn where. C = measured concentration of each metal in the sediments Cn = background value of heavy metal/geochemical background value of heavy metal in the earth crust Using CF as indices of pollution assessment, Nasr et al. (2006) and Mmolawa et al. (2011) have identified four categories of contamination. Contamination factor < 1 indicates low contamination, 1 ≤ CF < 3 indicates moderate contamination; 3 ≤ CF < 6 means considerable contamination and CF > 6 indicates very high contamination. Geochemical background values of heavy metals in this study were taken as their average upper continental crust (UCC) composition due to lack of particular local reference for each metal. The use of UCC in lieu of local/specific geochemical background value due to lack of local reference has been recommended and adopted in many studies (e.g. Olutona et al., 2016; Raut et al., 2017). The geochemical background values of the six heavy metals (Cd, Cu, Fe, Zn, Pb and As) as provided by Rudnick and Gao (2003) and Hu and Gao (2008) are 0.06 mg/kg, 27 mg/kg, 52,000 mg/kg, 75 mg/kg, 11 mg/kg and 5.7 mg/kg dry mass, respectively.
3.2. Hydrological parameters, suspended and dissolved solids and their relationships with metal concentrations The spatial mean values of flow velocity, water depth, water channel width, discharge, TSS and TDS are provided in Table 1. Station 1 recorded the highest flow velocity but lowest water depth while St. 2 recorded the lowest flow velocity but highest water depth. Channel width and discharge were both lowest at St. 1 and highest at St. 3. Highest concentrations of TSS and TDS were both recorded at St. 1, while their lowest values were at Stations 4 and 2, respectively. Significant spatial variations were recorded for channel width (p ≤ 0.001) and TDS (p ≤ 0.01). With the exception of channel width and Zn, all hydrological parameters showed negative correlations with the metals, though not all were significant. Water depth, discharge, and TSS all showed significant negative correlations (p < 0.05) with Cd while Cu, Pb and As also showed significant negative correlations (p < 0.05) with TSS (Supplemental Table 1). Total dissolved solids showed positive correlations with all the metals save As though significant correlation (p < 0.05) was only reported for Fe.
3. Results 3.1. Metal concentrations in the water column Lowest values of trace metals in the water column alternated between the rainy season periods of August and October 2017, while the highest values in all cases were recorded in February 2018 (Fig. 2a and b). Four metals were statistically significant in this temporal trend i.e. Cd (p < 0.01), Cu (p < 0.001), Fe (p < 0.05) and Pb (p < 0.05). 3
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Fig. 2. Temporal variation (mean ± sd) of heavy metals in the water column of Opa Stream, Ile-Ife, Nigeria (August 2017–February 2018) (Note: n = 4 per sampling period).
Table 2 provides the geo-accumulation index (Igeo) values of metals in all the stations. Three stations (Stations 1–3) recorded Igeo values of 0 and above for Cd with the highest recorded at Station 2, while Station 4 recorded Igeo value less than 0. The geo-accumulation index values of other metals were all lower than 0. The overall order of Igeo values for the metals was as follows: Cd > Cu > Zn > As > Pb > Fe. Contamination factors (CFs) of Cd were much closer to 1 in all the stations with the highest value recorded at Station 2 and lowest at Station 4. Contamination factors for other metals were much lower than 1 and the order of CFs among the metals was as follows: Cd > Cu > Zn > As > Pb > Fe (Table 2).
3.3. Metal concentrations, geo-accumulation and contamination in the benthic sediment With the exception of Pb which recorded its lowest concentration in October, all the metals recorded their lowest values in August. Four metals (Cd, Cu, Zn & Pb) recorded their highest values in February while Fe and As recorded their highest in October, though only Cu and Pb showed significant temporal variations (p < 0.001 and p < 0.05, respectively) (Fig. 4). There was no spatial trend in the concentrations of the metals and neither was significant difference recorded in any case (i.e. p > 0.05) (Supplemental Fig. 2). There were four significant negative correlations among the metals: Fe & Cd (r = −0.872, p < 0.05), As & Cd (r = −0.829, p < 0.05), Zn & As (r = −0.962, p < 0.01), Fe & Zn (r = −0.9770, p < 0.001). There was only one significant positive correlation recorded among the metals i.e. Fe & As (r = 0.983, p < 0.001). Fig. 5 further shows the relationship among the metals. Two components accounted for 56.8% of the variance and there was a strong cluster between Fe and As, and among Cu, Zn, Cd and Pb.
3.4. Relationships between metal concentrations in the water column and benthic sediment With the exception of Cd and Zn, all other metals showed positive correlations between concentrations in the water column and benthic sediment (Supplemental Table 2). There was no significant correlation (i.e. p > 0.05) in each case for Cd and Zn, in terms of their relative 4
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Fig. 3. Relationships among trace metals in the water column of Opa Stream, Ile-Ife, Nigeria (August 2017–February 2018).
subsistence and commercial farming were noticeable features of the riparian corridor. Comparatively, Cu recorded the highest concentration among the metals which was indicative of agricultural activities in the basin. A close relationship has empirically been established between agricultural practice (through the use of pesticides) and high Cu concentration in freshwater systems (e.g. Adewunmi et al., 1996; GimenoGarcia et al., 1996), and this was well observed during the field study. This study has also shown that hydrological parameters as well as suspended and dissolved solids play a role in the concentrations of metals in water columns. Hydrological parameters indicate that concentrations of the metals tend to decrease with water volume or quantity in the basin. Metal concentrations also appear to be positively influenced by dissolved solids but negatively influenced by suspended solids. This suggests that the metals only become available in dissolved forms. Based on the WHO recommendations for freshwater systems, concentrations of Cd, Cu, Fe and As in the water were above recommended limits for freshwater life (0.005 mg/L, 2.0 mg/L, 2.0 mg/L, and 0.01 mg/L, respectively); while concentration was just at the recommended limit (0.01 mg/L) in the case of Pb (Raut et al., 2017). These metals were particularly highest in the dry season period when water abstraction from the basin for dry season irrigation, is the norm. This trend could have been further exacerbated by evaporation from the basin, low precipitation and low inflow from the upstream reservoir; all of which are characteristic of the dry season. The suitability of the water for farming and the stream's planktonic community could thus,
concentrations in the water column and the sediment. Significant positive correlations were however recorded for Cu (p < 0.001), Pb (p < 0.05) and As (p < 0.05). 4. Discussion All the heavy metals in the water column of Opa Stream recorded their highest values in the rainy season sampling periods (i.e. August/ October), which were also periods of low water discharge. The significant indirect relationship of Cd with some hydrological parameters (water depth and discharge) indicates that high water volume could considerably reduce the impact of pollutants in a lotic freshwater system. Based on discharge values, Meybeck et al. (2006) classified running waters into brooks, small streams, streams, small rivers, rivers, large rivers, and very large rivers. Following this classification, Opa Stream can be categorized as a small stream which typically has its mean discharge ranging from 0.1 to 1.0 m3/s (Meybeck et al., 2006). The susceptibility of streams with low discharge to pollution, has been underscored by Carr and Neary (2006). They opined that slow-flowing streams with low discharge have a low capacity to attenuate pollutants. Low discharge recorded in this study could have thus, increased the impact of Cd on the stream. Stations 2 and 3 were characterized by highly deforested riparian corridors that had been converted to agricultural fields. This could have contributed significantly to the highest concentrations of Cd, Cu and Zn recorded at Station 3, where Table 1 Hydrological parameters and solids in the water column of Opa Stream. Sampling station
Flow velocity (m/s)
Water depth (m)
Channel width (m)
Discharge (m3/s)
TSS (mg/L)
TDS (mg/L)
St. 1 St. 2 St. 3 St. 4 Overall ANOVA
0.28 ± 0.09 0.12 ± 0.08 0.22 ± 0.02 0.18 ± 0.11 0.29 ± 0.09 F = 2.202 p = 0.196
0.21 ± 0.06 0.85 ± 0.45 0.62 ± 0.43 0.59 ± 0.30 0.57 ± 0.39 F = 4.386 p = 0.069
3.75 ± 0.96 7.75 ± 1.50 8.50 ± 2.38 7.25 ± 1.50 6.81 ± 2.40 F = 9.34 p = 0.001
0.25 ± 0.15 1.14 ± 0.86 1.23 ± 1.05 0.88 ± 0.74 0.87 ± 0.96 F = 1.975 p = 0.232
15.25 ± 5.18 15.15 ± 14.17 14.23 ± 10.04 11.28 ± 7.88 135.40 ± 22.08 F = 0.202 p = 0.892
164.75 ± 6.85 124.85 ± 17.19 125.78 ± 16.01 126.23 ± 17.47 13.98 ± 8.99 F = 11.82 p = 0.006
Note: n = 4 for each station. 5
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Fig. 4. Temporal variation (mean ± sd) of heavy metals in the benthic sediments of Opa Stream, Ile-Ife, Nigeria (August 2017–February 2018) (Note: n = 4 per sampling period). Table 2 Geo-accumulation indices and contamination factors of heavy metals in the benthic sediments. Sampling station
Geo-accumulation index Cd Cu Fe
St. 1 St. 2 St. 3 St. 4 Overall
0.039 0.086 0 −0.09 0.020
Sampling station St. 1 St. 2 St. 3 St. 4 Overall
Zn
Pb
As
−3.168 −2.913 −3.119 −3.197 −3.-092
−5.915 −5.843 −5.745 −5.843 −5.843
−5.141 −5.268 −5.184 −5.183 −5.184
Contamination factor Cd Cu Fe
Zn
Pb
As
0.783 0.817 0.750 0.683 0.767
0.032 0.041 0.033 0.031 0.034
0.002 0.002 0.002 0.002 0.002
0.004 0.004 0.004 0.005 0.004
−2.104 −2.036 −2.080 −1.983 −2.049
0.092 0.098 0.094 0.103 0.097
−7.600 −7.600 −7.607 −7.5680 −7.612
0.0000037 0.0000034 0.0000037 0.0000388 0.0000037
Note: Values supplied in this table were derived based on the mean concentration of each metal. Fig. 5. Relationships among trace metals in the benthic sediments of Opa Stream, Ile-Ife, Nigeria (August 2017–February 2018).
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riparian corridor. During the field study, three of such industries were sighted within the study area and bags of cement were also being washed in the stream. It is, therefore, logical to infer that concentrations of these metals in the water column as well as relatively high concentration of Cd in the stream bed, were mainly being impacted by the blockmaking industries. The implications of these three metals cannot be over-emphasized as their carcinogenic and debilitating impacts on environmental health have been underscored by Ogunbileje et al. (2013).
be a serious concern. Thus, this raises some health concerns for planktivorous fishes as well as consumers of farm produce and the stream's resources. Above-limit concentrations of Cd, Cu, Fe and As have similarly been reported in some tropical streams and rivers (e.g. Singh et al., 2005; Sajidu et al., 2006; Akoto et al., 2008). This suggests that some tropical freshwater systems could be at a great risk of heavy metal toxicity, the consequence of which could be disastrous to both aquatic biota and man. Metal concentrations in the stream's benthic sediment were far below their average values in the earth's crust. With the exception of Cd in Stations 1–3, geo-accumulation indices (Igeo) also revealed that all the metals were within their background concentrations in the earth crust. Following this Igeo system of pollution assessment, the stream bed was practically uncontaminated with Cu, Fe, Zn, Pb and As i.e. Igeo < 0, while there was very moderate contamination with Cd (0 < Igeo < 1). It is also noteworthy to state that the mean value of Cd in the stream bed was much closer to its background concentration in the earth crust (i.e. 76.7%), than other metals were to their background concentrations i.e. from 0.004% for Fe to 9.6% for Cu. This only suggests that the stream bed was most impacted with Cd among all the metals. Contamination factors of the metals further establish the fact that Cd had the highest level of impact on the stream bed, being much closer to 1 than any other metal. Considering CF values, all the metals can be described as having low contamination in the stream bed since they were all lower than 1. This study has also revealed that CFs are less sensitive than Igeo in heavy metal pollution studies of freshwater systems. For instance, while CF was much closer to 1 for Cd, it was much farther in the case of Fe; meanwhile, both were categorized as having low contamination in the stream bed. Spatial values of Igeo and CF for Cd also could also be a reflection of riparian corridor activities in the study area. While Igeo for Cd indicates low contamination at Stations 1–3, it indicates background concentration at Station 4. Riparian corridors of Stations 1–3 were characterized by subsistence and commercial farming while Station 4 was highly forested and devoid of farming or human encroachment. One striking observation in this study was the concentration of Cd in the water and stream bed. Compared to other metals, Cd has been reported to be relatively water-soluble, more mobile and biologically available; hence its alarming concentration in this study. Aside from its high biological availability rate, it has been reported to bioaccumulate more easily in molluscs and microorganisms. It also concentrates on the internal organs of animals (e.g. kidney, liver) than in muscle or fat (Nordic Council of Ministers, 2003). It is readily absorbed and its acute toxicity varies among aquatic animals. It inhibits the uptake of Ca from water by fish, thereby resulting in hypocalcaemia i.e. lack of calcium (AMAP, 1998). It also produces acute and chronic effects (e.g. kidney damage and lung emphysema) among aquatic birds and mammals, as seen in man (IPCS, 1992a; 1992b). The levels of Cd in both water and stream bed of Opa Stream could thus, pose ecotoxicological risks to the plankton, the nekton, the benthos as well as human consumers of resources from the stream. Cadmium concentrations could have been strongly influenced through agricultural practices in the riparian corridors, since it has been regarded as a biotoxic environmental pollutant in agricultural environments (Onweremadu and Duruigbo, 2007). Strong relationships were also established among Pb, Cd and As in both water column and the stream bed, thus pointing to the fact that these metals could have been well influenced through the same anthropogenic source. These three metals have been closely linked to cement production and/or usage. Ogunbileje et al. (2013) in their comparative study of heavy metals in cement dust from Nigeria and United States of America (USA), did not only record Pb and Cd in the cement dust of Nigeria but also found out that their concentrations were much higher than the USA samples. In the same vein, Cd and As have been reported as the main heavy metals associated with cement production (Islam et al., 2006; Cipurkovic et al., 2014). The close association of these three metals as well as their high concentrations in the stream could thus, be as a result of block-making activities on the
5. Conclusion This study revealed that Opa Stream was impacted with heavy metals in its water column and slightly impacted in its benthic sediments. Five heavy metals (Pb, As, Fe, Cu and Cd) had either reached or exceeded their recommended limits for freshwater life, while only one metal (Cd) showed some level of contamination in the benthic sediment. Among other findings, this study also revealed that dissolved solids are stronger determinant of metal concentrations in surface waters than suspended solids. Above all, conversion of riparian corridors to farmlands and some anthropogenic activities could deleteriously affect aquatic ecosystem health. This study has thus, underscored the essence of riparian forest protection and regular monitoring/regulation of human activities in a river or stream's catchments, in order to ensure the health of aquatic ecosystems, and by extension human health. Authors contribution section Emmanuel O. Akindele designed the study, conducted the field sampling, participated in the laboratory analyses and wrote the manuscript; Omobukola D. Omisakin and Oluwagbemiga A. Oni both participated in the field sampling and the laboratory analyses; Olanrewaju O. Aliu co-designed the study and revised the manuscript; Gbenga E. Omoniyi and Oluwaseun T. Akinpelu both participated in the laboratory analyses. Funding This research did not receive any specific grant from funding agencies in the public, commercial or not-for-profit sectors. Declaration of competing interest The authors declare that they have no conflict of interest. Appendix A. Supplementary data Supplementary data to this article can be found online at https:// doi.org/10.1016/j.ecoenv.2019.110153. References Adewunmi, C.O., Becker, W., Kuehmast, O., Oluwole, F., Dorfler, G., 1996. Accumulation of copper, lead and cadmium in freshwater snails in southwestern Nigeria. Sci. Total Environ. 193, 69–73. Ahmad, M.K., Islam, S., Rahman, M.S., Haque, M.R., Islam, M.M., 2010. Heavy metals in water, sediment and some fishes of Buriganga River, Bangladesh. Int. J. Environ. Res. 4, 321–332. Ahmed, M.K., Baki, M.A., Islam, M.S., Kundu, G.K., Sarkar, S.K., Hossain, M.M., 2015. Human health risk assessment of heavy metals in tropical fish and shellfish collected from the River Buriganga, Bangladesh. Environ. Sci. Pollut. Res. 22 (20), 15880–15890. Akindele, E.O., Olutona, G.O., 2014. Water physicochemistry and zooplankton fauna of Aiba Reservoir headwater streams. J. Ecosyst. 105405. Akindele, E.O., Olutona, G.O., Oyeku, O.G., Adeniyi, A.V., 2017. Assessment of two persistent bioaccumulative toxicants in the UNESCO protected river of Osun-Osogbo, Nigeria. Ecol. Process. 6, 30 (2017). Akindele, E.O., Adeniyi, A.V., Oyeku, O.G., Adu, B.W., 2018. Analysis of benthic macroinvertebrates, biological water quality and conservation value of a tropical river and UNESCO-protected environment. Afr. J. Ecol. 56, 488–498. Akoto, O., Bruce, T.N., Darko, G., 2008. Heavy metal pollution profiles in streams serving
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the Owabi Reservoir. Afr. J. Environ. Sci. Technol. 2 (11), 354–359. AMAP, 1998. Assessment Report: Arctic Pollution Issues. Arctic Monitoring and Assessment Programme, Oslo. APHA, 2005. Standard Methods for the Examination of Water and Wastewater, twentyfirst ed. American Public Health Association, Washington, DC. Aprile, F.M., Bouvy, M., 2010. Heavy metal levels in surface water from a tropical river basin, Pernambuco State, northeastern Brazil. Acta Sci. Biol. Sci. 32 (4), 357–364. Asare, M.L., Cobbina, S.J., Akpabey, F.J., Duwiejuah, A.B., Abuntori, Z.N., 2018. Heavy metal concentration in water, sediment and fish species in the Bontanga Reservoir, Ghana. J. Toxicol. Environ. Health Sci. 10, 49–58. Carr, G.M., Neary, J.P., 2006. Water Quality for Ecosystem and Health. United Nations Environment Programme Global Environment Monitoring System (GEMS)/Water Programme, Ontario, Canada. Chapman, D., Kimstach, V., 2006. Selection of water quality variables. In: Chapman, D. (Ed.), Water Quality Assessments: AGuide to the Use of Biota, Sediments and Water Environmental Monitoring. Chapman and Hall, London, pp. 65–122. Chidya, R.C.G., Sajidu, S.M.I., Mwatseteza, J.F., Masamba, W.R.L., 2011. Evaluation and assessment of water quality in Likangala River and its catchment area. Phys. Chem. Earth 36, 865–871. Cipurkovic, A., Trumic, I., Hodžic, Z., Selimbašic, V., Djozic, A., 2014. Distribution of heavy metals in Portland cement production process. Adv. Appl. Sci. Res. 5 (6), 252–259. Ezemonye, L.I., Adebayo, P.O., Enuneku, A.A., Tongo, I., Ogbomida, E., 2019. Potential health risk consequences of heavy metal concentrations in surface water, shrimp (Macrobrachium macrobrachion) and fish (Brycinus longipinnis) from Benin River, Nigeria. Toxicol. Rep. 6 (2019), 1–9. Forstner, U., Wittmann, G.T.W., 1981. Metal Pollution in the Aquatic Environment, second ed. Springer-Verlag, New York. Gimeno-Garcia, E., Andreu, V., Boluda, R., 1996. Heavy metals incidence in the application of inorganic fertilizers andpesticides to rice farming soils. Environ. Pollut. 92 (1), 19–25. Hu, Z., Gao, S., 2008. Upper crustal abundances of trace elements: a revision and update. Chem. Geol. 253, 205–221. IPCS (International Programme on Chemical Safety), 1992a. Cadmium. Geneva, world health organization. International Programme on Chemical Safety (Environmental Health Criteria 134). http://www.inchem.org/documents/ehc/ehc/ehc134.htm. IPCS (International Programme on Chemical Safety), 1992b. Cadmium—Environmental Aspects. World Health Organization, Geneva International Programme on Chemical Safety (Environmental Health Criteria 135). http://www.inchem.org/documents/ ehc/ehc/ehc135.htm. Islam, I., Chng, H.K., Yap, A.U., 2006. X-ray diffraction analysis of mineral trioxide aggregate and Portland cement. Int. Endod. J. 39, 220–225. Islam, M.S., Ahmed, M.K., Raknuzzaman, M., Habibullah-Al-Mamun, M., Islam, M.K., 2015. Heavy metal pollution in surface water and sediment: a preliminary assessment of an urban river in a developing country. Ecol. Indicat. 48, 282–291. Makinde, O.W., Ayodele, O.E., Ayodele, T.I., Oluremi, O.I., Temitope, O.K., Temitope, F.O., 2016. Heavy metal contamination in stream water and sediments of gold mining areas of South Western Nigeria. Afr. J. Environ. Sci. Technol. 10 (5), 150–161. Meybeck, M., Friedrich, D., Thomas, R., Chapman, D., 2006. Rivers. In: Chapman, D. (Ed.), Water Quality Assessments: AGuide to the Use of Biota, Sediments and Water Environmental Monitoring. Chapman and Hall, London, pp. 227–303. Mmolawa, K.B., Likuku, A.S., Gaboutloeloe, G.K., 2011. Assessment of heavy metal pollution in soils along major roadside areas in Botswana. Afr. J. Environ. Sci. Technol. 5 (3), 186–196. Mori, G.B., de Paula, F.R., de Barros Ferraz, S.F., Camargo, A.F.M., Martinelli, L.A., 2015. Influence of landscape properties on stream water quality in agricultural catchments in South eastern Brazil. Ann. Limnol-Int. J. Lim. 51, 11–21.
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Heavy metal toxicity in the water column and benthic sediments of a degraded tropical stream
T
Emmanuel O. Akindelea,∗, Omobukola D. Omisakina, Oluwagbemiga A. Onia, Olanrewaju O. Aliua,b, Gbenga E. Omoniyic, Oluwaseun T. Akinpelud a
Department of Zoology, Obafemi Awolowo University, Ile-Ife, Nigeria Health Safety, Security and Environment, Eterna PLC, Lagos, Nigeria c Department of Biology/Microbiology/Biotechnology, Alex Ekwueme Federal University, Ndufu-Alike Ikwo, Ebonyi State, Nigeria d Department of Animal Biology, Federal University of Technology, Minna, Nigeria b
A R T I C LE I N FO
A B S T R A C T
Keywords: Agriculture Pollution Riparian corridor Stream Tropical freshwaters
Agriculture and other anthropogenic activities on riparian corridors pose a great ecotoxicological risk to freshwater ecosystem and human health. Using the atomic absorption spectroscopy, concentrations of heavy metals (Cd, Cu, Fe, Zn, Pb and As) in the water column and benthic sediments of a degraded tropical stream (Opa Stream, Ile-Ife, Nigeria), were assessed with a view to determining the stream's health status. Three metals (Cu, Pb, and As) showed significant positive correlations between concentrations in the water column and the benthic sediments. All but one heavy metal (i.e. Zn) had reached disturbing concentrations in the stream's water column and exceeded their recommended limits in surface freshwaters. The geo-accumulation index (Igeo) and contamination factor (CF) indicated that the stream was moderately contaminated with Cd (0 < Igeo < 1; CF much closer to 1). This study concludes that the stream was impacted with heavy metals in its water column and slightly impacted with Cd on its bed, thus raising health concerns for plankton, benthic organisms and all users of the surface water. More conservation attention by relevant stakeholders through monitoring and regulation of human activities in river basins, is recommended for the sustenance of tropical freshwater ecosystem and human health.
1. Introduction
waterbody; thus, they are the most important sink of heavy metals in freshwater environments (Morin et al., 2007). Heavy metals are among persistent bioaccumulative toxicants (PBTs) just like organo-metal compounds. They are ubiquitous, persistent and bioaccumulative in aquatic systems (Ray and McCormick-Ray, 2014), consequent on which they have gained so much public attention due to their implications for environmental health (Ahmed et al., 2015; Islam et al., 2015). A heavy metal refers to any metal or metalloid element which density ranges from 3.5 to 7 g/cm3 and which is toxic at low concentrations (Tchounwou et al., 2012). Heavy metals are also regarded as trace elements because of their presence in trace concentrations in various environmental matrices. They occur naturally in the environment (i.e. lithogenic) but their concentrations may also increase astronomically through anthropogenic activities e.g. domestic/ industrial effluents and agricultural activities (Ravindra et al., 2014; Outa et al., 2019). Among heavy metal toxicological studies in tropical freshwaters are the works of Aprile and Bouvy (2010) on a river basin in northeastern Brazil, Ahmad et al. (2010) in Buriganga River
One of the unique features of pristine or near-pristine tropical streams and rivers is the presence of riparian forests which play a very crucial role in limnological characteristics and conservation of such systems. Whenever these forests are removed for agricultural or industrial purpose, the impacts are felt in adjacent water bodies through the release of chemicals, soil erosion and the reduction of riparian cover (Mori et al., 2015). Loss of riparian forests or bankside vegetation removal has also been attributed to high sediment load in surface waters, with attendant consequences on water quality and aquatic ecosystem health (Naiman et al., 2005). These sediments, which are typically transported by fluid flow, eventually settle on the stream bed when the flow velocity is too low to keep them in suspension (Akindele and Olutona, 2014). Hence, heavy metals that are bound to particulate matters (suspended sediments) eventually settle down and become incorporated into bottom (benthic) sediments. Comparatively, benthic sediments have a higher retention capacity than any other section of a
∗
Corresponding author. E-mail address: [email protected] (E.O. Akindele).
https://doi.org/10.1016/j.ecoenv.2019.110153 Received 11 October 2019; Received in revised form 30 December 2019; Accepted 30 December 2019 0147-6513/ © 2019 Elsevier Inc. All rights reserved.
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bimonthly from August 2017 to February 2018 between 09:00 and 12:00 on each sampling day. At each site, percentage vegetation cover was estimated as the proportion of the channel width that was covered by vegetation, and their corresponding values were 90%, 50%, 10% and 95% at Stations 1, 2, 3 and 4, respectively. Float displacement method (Akindele et al., 2018) was used to determine flow velocity; water depth was determined with a calibrated line attached to a weight; and channel width was determined by measuring the distance across the two sides of the stream. Discharge was derived from the product of flow velocity, water depth and channel width (Chapman and Kimstach, 2006), at each station and sampling period. Water samples were collected in new and sterilized 2-L plastic containers, and which were later rinsed with water from each site before sample collection. The water samples were kept in a cold environment and stored in a refrigerator under a frozen condition pending their laboratory analyses. Two composite sediment samples were collected at each station with the aid of a grab and homogenized as one representative sample. The samples were stored in a polythene bag and taken to the laboratory.
(Bangladesh), Reza and Singh (2010) in India, and Chidya et al. (2011) in Likangala River (Malawi). Other studies include the works of Akindele et al. (2017) in Osun River (Nigeria), Asare et al. (2018) in Bontanga Reservoir (Ghana), Ezemonye et al. (2019) in Benin River (Nigeria), Outa et al. (2019) in the Kenyan part of Lake Victoria, and Wasike et al. (2019) in Kuywa River (Kenya). In some of these studies, heavy metal contaminations were recorded in surface waters and benthic sediments. For instance, the concentrations of Pb and Cd in Kenya's Kuywa River ranged from 0.57 ± 0.09–3.36 ± 1.15 mg/L and 0.32 ± 0.02–0.99 ± 0.67 mg/L, respectively; as against their respective recommended limits of 0.005 mg/L and 0.01 mg/L for freshwater life. In the same vein, Ezemonye et al. (2019) have reported above-limit concentrations for Cd (0.01 mg/L) and Pb (0.18 mg/L) in the Benin River of Nigeria. A study on the distribution of some selected heavy metals in the Kenyan part of Lake Victoria by Outa et al. (2019) has also further established the role of anthropogenic impacts on the concentration of heavy metals in inland waters. The study revealed that the part of the lake that was closest to industrial and municipal waste water discharges was severely polluted with Cu and Pb. Opa Stream is a lotic tropical freshwater system which has been degraded through substantial loss of its riparian cover and conversion of the forest to various purposes to meet human needs (e.g. subsistence and commercial farming, car wash, abattoir, gas station and residential buildings). This trend has been reported in Nigeria as the human population grows with attendant encroachments on riparian corridors and waste dumping in surface waters (Akindele and Olutona, 2014). Furthermore, current human population growth in many Afro-tropical nations and future predictions (UN DESA, 2017) imply that more wetlands may be lost or degraded except stringent practices are introduced to initiate early conservation measures. This research is thus hinged on the following hypotheses: (1) Human activities on the riparian corridor could have a significant impact on a stream's health through heavy metal contamination; (2) suspended solids and dissolved solids determine metal concentrations in water columns; and (3), metal concentrations in a water column may determine those on a stream bed.
2.3. Laboratory and data analyses Total suspended solids (TSS) and total dissolved solids (TDS) were both analysed by gravimetric method (APHA, 2005). In the case of sediment, samples were first air-dried in the laboratory after which they were ground to fine particles using a mortar and a pestle. Digestion of samples was as described by Makinde et al. (2016) i.e. with aqua-regia (HNO3−:1, HCl:3). Metals in both water and sediment samples were analysed by atomic absorption spectrophotometry as described by Welz and Sperling (1999). The samples were analysed with PG990 spectrophotometer (Beijing Purkinje General Instrument Co. Ltd, China) by flame atomization, using air-acetylene flame and single element hollow cathode lamp. As a quality control measure, reference standards were compared in each case with both water and sediment samples, and a calibration curve was plotted. The detection limits of the metals (in mg/ L) were 0.0028 Cd, 0.004 Cu, 0.0046 Fe, 0.003 Zn, 0.16 Pb and 0.16 As. Shapiro-Wilk test for normality indicated that most of the investigated parameters were normally distributed (p > 0.05); hence the use of analysis of variance (ANOVA) for temporal and spatial variations, and Pearson's correlation for relationships between metals and hydrological parameters/TSS/TDS. Principal component analysis was used to establish the relationships among metals in the water as well as in the stream bed. Paleontological Statistics (PAST) and ‘r’ statistical software were used for data analysis. Pollution status of heavy metals in the sediment was assessed using the geo-accumulation index (Igeo) and contamination factor (CF). The geo-accumulation index was promulgated by Müller (1969) and has since, been used to ascertain the level of heavy metal contamination in sediments/soils (Raut et al., 2017). It is mathematically expressed as:
2. Materials and methods 2.1. Study area The downstream section of Opa Stream in Ile-Ife was chosen for this study. It is along Ede Road with GPS estimates of 004°30′38″E − 004°3048″E and 07°29′95″N - 07°30′18″N. Two seasons characterize the study area, viz: the dry season (low flow/discharge) which lasts from November to March and the wet season (high flow/discharge) which lasts from April to October. During the rainy season, the stream's water level rises and becomes turbid due to a high volume of water from the upstream reservoir and the surrounding farmland. The primary lowland rainforest of the area has almost been taken over by a secondary forest as a result of intensive agricultural practices. Among the dominant crops in the area are cocoa plantation, plantain vegetation, and many food crops. Other noticeable anthropogenic interferences on the stream's riparian corridor are block-making industries, petroleum and cooking gas station, car wash, abattoir, hostels and residential buildings. Subsistence and commercial farmers in the area use agrochemicals (e.g. Ridomine, Lindane, Glyphosate) to increase the quality of their farm produce without taking cognizance of the environmental effects of such practice on the stream. By and large, wastewater entering the stream can be ascribed mainly to point sources such as the car wash, abattoir, block-making industries and commercial farmlands.
Cn ⎞ Igeo = log 2 ⎛ ⎝ 1.5 Bn ⎠ where. Igeo = Geo-accumulation index Cn = Measured concentration of heavy metal in the sediment Bn = Geochemical background value of heavy metal in the earth crust 1.5 = Background matrix correction factor due to lithogenic variations and very small anthropogenic influences According to Müller (1969) and Raut et al. (2017), there are seven classes of geo-accumulation index ranging from 0 to 6, and these were used to determine the level of contamination of each metal in the sediment. Geo-accumulation index < 0 indicates sediment is practically uncontaminated, Igeo 0–1 indicates very moderate contamination, 1–2 indicates moderate contamination, 2–3 indicates moderate to heavy
2.2. Field determinations and collection of samples Four sampling stations were established along the longitudinal flow of the stream in the study area (Fig. 1), and samples were collected 2
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Fig. 1. Map of the study area showing the sampling stations (Inset: Maps of Africa, Nigeria and Osun State showing the study area).
Three metals (Cu, Zn & As) recorded their lowest concentrations at St. 1 while another three (Cd, Cu & Zn) recorded their highest values at St. 3 (Supplemental Fig. 1). There were however no significant (p > 0.05) spatial variations for the metals. The overall mean concentrations of the metals in the water column were 0.019 ± 0.004 mg/L Cd, 4.780 ± 1.409 mg/L Cu, 1.106 ± 0.313 mg/L Fe, 0.448 ± 0.108 mg/L Zn, 0.010 ± 0.002 mg/L Pb, and, 0.018 ± 0.004 mg/L As. Relationships among metals in the water column indicate significant negative correlations between Cd and Pb (r = −2.83 × 10−14, p < 0.001), Fe and Zn (r = −0.860, P < 0.05), Pb and Zn (r = −0.933, p < 0.01), and Pb and As (r = −0.894, p < 0.05). Significant positive relationships were recorded between Cu and Zn (r = 0.997, p < 0.001) and Cu and As (r = 0.824, p < 0.05), while Cu and Pb were negatively correlated (r = −0.959, p < 0.01). Principal component analysis indicates that two components accounted for 68.9% of the variance and there was a very strong relationship between Zn and As, and among Cu, Pb and Cd (Fig. 3).
contamination, 3–4 indicates heavy contamination, 4–5 indicates heavy/extreme contamination, and 5–6 indicates extreme contamination. Contamination factor of heavy metals was calculated using the formula prescribed by Forstner and Wittmann (1981),
i. e . CF = C / Cn where. C = measured concentration of each metal in the sediments Cn = background value of heavy metal/geochemical background value of heavy metal in the earth crust Using CF as indices of pollution assessment, Nasr et al. (2006) and Mmolawa et al. (2011) have identified four categories of contamination. Contamination factor < 1 indicates low contamination, 1 ≤ CF < 3 indicates moderate contamination; 3 ≤ CF < 6 means considerable contamination and CF > 6 indicates very high contamination. Geochemical background values of heavy metals in this study were taken as their average upper continental crust (UCC) composition due to lack of particular local reference for each metal. The use of UCC in lieu of local/specific geochemical background value due to lack of local reference has been recommended and adopted in many studies (e.g. Olutona et al., 2016; Raut et al., 2017). The geochemical background values of the six heavy metals (Cd, Cu, Fe, Zn, Pb and As) as provided by Rudnick and Gao (2003) and Hu and Gao (2008) are 0.06 mg/kg, 27 mg/kg, 52,000 mg/kg, 75 mg/kg, 11 mg/kg and 5.7 mg/kg dry mass, respectively.
3.2. Hydrological parameters, suspended and dissolved solids and their relationships with metal concentrations The spatial mean values of flow velocity, water depth, water channel width, discharge, TSS and TDS are provided in Table 1. Station 1 recorded the highest flow velocity but lowest water depth while St. 2 recorded the lowest flow velocity but highest water depth. Channel width and discharge were both lowest at St. 1 and highest at St. 3. Highest concentrations of TSS and TDS were both recorded at St. 1, while their lowest values were at Stations 4 and 2, respectively. Significant spatial variations were recorded for channel width (p ≤ 0.001) and TDS (p ≤ 0.01). With the exception of channel width and Zn, all hydrological parameters showed negative correlations with the metals, though not all were significant. Water depth, discharge, and TSS all showed significant negative correlations (p < 0.05) with Cd while Cu, Pb and As also showed significant negative correlations (p < 0.05) with TSS (Supplemental Table 1). Total dissolved solids showed positive correlations with all the metals save As though significant correlation (p < 0.05) was only reported for Fe.
3. Results 3.1. Metal concentrations in the water column Lowest values of trace metals in the water column alternated between the rainy season periods of August and October 2017, while the highest values in all cases were recorded in February 2018 (Fig. 2a and b). Four metals were statistically significant in this temporal trend i.e. Cd (p < 0.01), Cu (p < 0.001), Fe (p < 0.05) and Pb (p < 0.05). 3
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Fig. 2. Temporal variation (mean ± sd) of heavy metals in the water column of Opa Stream, Ile-Ife, Nigeria (August 2017–February 2018) (Note: n = 4 per sampling period).
Table 2 provides the geo-accumulation index (Igeo) values of metals in all the stations. Three stations (Stations 1–3) recorded Igeo values of 0 and above for Cd with the highest recorded at Station 2, while Station 4 recorded Igeo value less than 0. The geo-accumulation index values of other metals were all lower than 0. The overall order of Igeo values for the metals was as follows: Cd > Cu > Zn > As > Pb > Fe. Contamination factors (CFs) of Cd were much closer to 1 in all the stations with the highest value recorded at Station 2 and lowest at Station 4. Contamination factors for other metals were much lower than 1 and the order of CFs among the metals was as follows: Cd > Cu > Zn > As > Pb > Fe (Table 2).
3.3. Metal concentrations, geo-accumulation and contamination in the benthic sediment With the exception of Pb which recorded its lowest concentration in October, all the metals recorded their lowest values in August. Four metals (Cd, Cu, Zn & Pb) recorded their highest values in February while Fe and As recorded their highest in October, though only Cu and Pb showed significant temporal variations (p < 0.001 and p < 0.05, respectively) (Fig. 4). There was no spatial trend in the concentrations of the metals and neither was significant difference recorded in any case (i.e. p > 0.05) (Supplemental Fig. 2). There were four significant negative correlations among the metals: Fe & Cd (r = −0.872, p < 0.05), As & Cd (r = −0.829, p < 0.05), Zn & As (r = −0.962, p < 0.01), Fe & Zn (r = −0.9770, p < 0.001). There was only one significant positive correlation recorded among the metals i.e. Fe & As (r = 0.983, p < 0.001). Fig. 5 further shows the relationship among the metals. Two components accounted for 56.8% of the variance and there was a strong cluster between Fe and As, and among Cu, Zn, Cd and Pb.
3.4. Relationships between metal concentrations in the water column and benthic sediment With the exception of Cd and Zn, all other metals showed positive correlations between concentrations in the water column and benthic sediment (Supplemental Table 2). There was no significant correlation (i.e. p > 0.05) in each case for Cd and Zn, in terms of their relative 4
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Fig. 3. Relationships among trace metals in the water column of Opa Stream, Ile-Ife, Nigeria (August 2017–February 2018).
subsistence and commercial farming were noticeable features of the riparian corridor. Comparatively, Cu recorded the highest concentration among the metals which was indicative of agricultural activities in the basin. A close relationship has empirically been established between agricultural practice (through the use of pesticides) and high Cu concentration in freshwater systems (e.g. Adewunmi et al., 1996; GimenoGarcia et al., 1996), and this was well observed during the field study. This study has also shown that hydrological parameters as well as suspended and dissolved solids play a role in the concentrations of metals in water columns. Hydrological parameters indicate that concentrations of the metals tend to decrease with water volume or quantity in the basin. Metal concentrations also appear to be positively influenced by dissolved solids but negatively influenced by suspended solids. This suggests that the metals only become available in dissolved forms. Based on the WHO recommendations for freshwater systems, concentrations of Cd, Cu, Fe and As in the water were above recommended limits for freshwater life (0.005 mg/L, 2.0 mg/L, 2.0 mg/L, and 0.01 mg/L, respectively); while concentration was just at the recommended limit (0.01 mg/L) in the case of Pb (Raut et al., 2017). These metals were particularly highest in the dry season period when water abstraction from the basin for dry season irrigation, is the norm. This trend could have been further exacerbated by evaporation from the basin, low precipitation and low inflow from the upstream reservoir; all of which are characteristic of the dry season. The suitability of the water for farming and the stream's planktonic community could thus,
concentrations in the water column and the sediment. Significant positive correlations were however recorded for Cu (p < 0.001), Pb (p < 0.05) and As (p < 0.05). 4. Discussion All the heavy metals in the water column of Opa Stream recorded their highest values in the rainy season sampling periods (i.e. August/ October), which were also periods of low water discharge. The significant indirect relationship of Cd with some hydrological parameters (water depth and discharge) indicates that high water volume could considerably reduce the impact of pollutants in a lotic freshwater system. Based on discharge values, Meybeck et al. (2006) classified running waters into brooks, small streams, streams, small rivers, rivers, large rivers, and very large rivers. Following this classification, Opa Stream can be categorized as a small stream which typically has its mean discharge ranging from 0.1 to 1.0 m3/s (Meybeck et al., 2006). The susceptibility of streams with low discharge to pollution, has been underscored by Carr and Neary (2006). They opined that slow-flowing streams with low discharge have a low capacity to attenuate pollutants. Low discharge recorded in this study could have thus, increased the impact of Cd on the stream. Stations 2 and 3 were characterized by highly deforested riparian corridors that had been converted to agricultural fields. This could have contributed significantly to the highest concentrations of Cd, Cu and Zn recorded at Station 3, where Table 1 Hydrological parameters and solids in the water column of Opa Stream. Sampling station
Flow velocity (m/s)
Water depth (m)
Channel width (m)
Discharge (m3/s)
TSS (mg/L)
TDS (mg/L)
St. 1 St. 2 St. 3 St. 4 Overall ANOVA
0.28 ± 0.09 0.12 ± 0.08 0.22 ± 0.02 0.18 ± 0.11 0.29 ± 0.09 F = 2.202 p = 0.196
0.21 ± 0.06 0.85 ± 0.45 0.62 ± 0.43 0.59 ± 0.30 0.57 ± 0.39 F = 4.386 p = 0.069
3.75 ± 0.96 7.75 ± 1.50 8.50 ± 2.38 7.25 ± 1.50 6.81 ± 2.40 F = 9.34 p = 0.001
0.25 ± 0.15 1.14 ± 0.86 1.23 ± 1.05 0.88 ± 0.74 0.87 ± 0.96 F = 1.975 p = 0.232
15.25 ± 5.18 15.15 ± 14.17 14.23 ± 10.04 11.28 ± 7.88 135.40 ± 22.08 F = 0.202 p = 0.892
164.75 ± 6.85 124.85 ± 17.19 125.78 ± 16.01 126.23 ± 17.47 13.98 ± 8.99 F = 11.82 p = 0.006
Note: n = 4 for each station. 5
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Fig. 4. Temporal variation (mean ± sd) of heavy metals in the benthic sediments of Opa Stream, Ile-Ife, Nigeria (August 2017–February 2018) (Note: n = 4 per sampling period). Table 2 Geo-accumulation indices and contamination factors of heavy metals in the benthic sediments. Sampling station
Geo-accumulation index Cd Cu Fe
St. 1 St. 2 St. 3 St. 4 Overall
0.039 0.086 0 −0.09 0.020
Sampling station St. 1 St. 2 St. 3 St. 4 Overall
Zn
Pb
As
−3.168 −2.913 −3.119 −3.197 −3.-092
−5.915 −5.843 −5.745 −5.843 −5.843
−5.141 −5.268 −5.184 −5.183 −5.184
Contamination factor Cd Cu Fe
Zn
Pb
As
0.783 0.817 0.750 0.683 0.767
0.032 0.041 0.033 0.031 0.034
0.002 0.002 0.002 0.002 0.002
0.004 0.004 0.004 0.005 0.004
−2.104 −2.036 −2.080 −1.983 −2.049
0.092 0.098 0.094 0.103 0.097
−7.600 −7.600 −7.607 −7.5680 −7.612
0.0000037 0.0000034 0.0000037 0.0000388 0.0000037
Note: Values supplied in this table were derived based on the mean concentration of each metal. Fig. 5. Relationships among trace metals in the benthic sediments of Opa Stream, Ile-Ife, Nigeria (August 2017–February 2018).
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riparian corridor. During the field study, three of such industries were sighted within the study area and bags of cement were also being washed in the stream. It is, therefore, logical to infer that concentrations of these metals in the water column as well as relatively high concentration of Cd in the stream bed, were mainly being impacted by the blockmaking industries. The implications of these three metals cannot be over-emphasized as their carcinogenic and debilitating impacts on environmental health have been underscored by Ogunbileje et al. (2013).
be a serious concern. Thus, this raises some health concerns for planktivorous fishes as well as consumers of farm produce and the stream's resources. Above-limit concentrations of Cd, Cu, Fe and As have similarly been reported in some tropical streams and rivers (e.g. Singh et al., 2005; Sajidu et al., 2006; Akoto et al., 2008). This suggests that some tropical freshwater systems could be at a great risk of heavy metal toxicity, the consequence of which could be disastrous to both aquatic biota and man. Metal concentrations in the stream's benthic sediment were far below their average values in the earth's crust. With the exception of Cd in Stations 1–3, geo-accumulation indices (Igeo) also revealed that all the metals were within their background concentrations in the earth crust. Following this Igeo system of pollution assessment, the stream bed was practically uncontaminated with Cu, Fe, Zn, Pb and As i.e. Igeo < 0, while there was very moderate contamination with Cd (0 < Igeo < 1). It is also noteworthy to state that the mean value of Cd in the stream bed was much closer to its background concentration in the earth crust (i.e. 76.7%), than other metals were to their background concentrations i.e. from 0.004% for Fe to 9.6% for Cu. This only suggests that the stream bed was most impacted with Cd among all the metals. Contamination factors of the metals further establish the fact that Cd had the highest level of impact on the stream bed, being much closer to 1 than any other metal. Considering CF values, all the metals can be described as having low contamination in the stream bed since they were all lower than 1. This study has also revealed that CFs are less sensitive than Igeo in heavy metal pollution studies of freshwater systems. For instance, while CF was much closer to 1 for Cd, it was much farther in the case of Fe; meanwhile, both were categorized as having low contamination in the stream bed. Spatial values of Igeo and CF for Cd also could also be a reflection of riparian corridor activities in the study area. While Igeo for Cd indicates low contamination at Stations 1–3, it indicates background concentration at Station 4. Riparian corridors of Stations 1–3 were characterized by subsistence and commercial farming while Station 4 was highly forested and devoid of farming or human encroachment. One striking observation in this study was the concentration of Cd in the water and stream bed. Compared to other metals, Cd has been reported to be relatively water-soluble, more mobile and biologically available; hence its alarming concentration in this study. Aside from its high biological availability rate, it has been reported to bioaccumulate more easily in molluscs and microorganisms. It also concentrates on the internal organs of animals (e.g. kidney, liver) than in muscle or fat (Nordic Council of Ministers, 2003). It is readily absorbed and its acute toxicity varies among aquatic animals. It inhibits the uptake of Ca from water by fish, thereby resulting in hypocalcaemia i.e. lack of calcium (AMAP, 1998). It also produces acute and chronic effects (e.g. kidney damage and lung emphysema) among aquatic birds and mammals, as seen in man (IPCS, 1992a; 1992b). The levels of Cd in both water and stream bed of Opa Stream could thus, pose ecotoxicological risks to the plankton, the nekton, the benthos as well as human consumers of resources from the stream. Cadmium concentrations could have been strongly influenced through agricultural practices in the riparian corridors, since it has been regarded as a biotoxic environmental pollutant in agricultural environments (Onweremadu and Duruigbo, 2007). Strong relationships were also established among Pb, Cd and As in both water column and the stream bed, thus pointing to the fact that these metals could have been well influenced through the same anthropogenic source. These three metals have been closely linked to cement production and/or usage. Ogunbileje et al. (2013) in their comparative study of heavy metals in cement dust from Nigeria and United States of America (USA), did not only record Pb and Cd in the cement dust of Nigeria but also found out that their concentrations were much higher than the USA samples. In the same vein, Cd and As have been reported as the main heavy metals associated with cement production (Islam et al., 2006; Cipurkovic et al., 2014). The close association of these three metals as well as their high concentrations in the stream could thus, be as a result of block-making activities on the
5. Conclusion This study revealed that Opa Stream was impacted with heavy metals in its water column and slightly impacted in its benthic sediments. Five heavy metals (Pb, As, Fe, Cu and Cd) had either reached or exceeded their recommended limits for freshwater life, while only one metal (Cd) showed some level of contamination in the benthic sediment. Among other findings, this study also revealed that dissolved solids are stronger determinant of metal concentrations in surface waters than suspended solids. Above all, conversion of riparian corridors to farmlands and some anthropogenic activities could deleteriously affect aquatic ecosystem health. This study has thus, underscored the essence of riparian forest protection and regular monitoring/regulation of human activities in a river or stream's catchments, in order to ensure the health of aquatic ecosystems, and by extension human health. Authors contribution section Emmanuel O. Akindele designed the study, conducted the field sampling, participated in the laboratory analyses and wrote the manuscript; Omobukola D. Omisakin and Oluwagbemiga A. Oni both participated in the field sampling and the laboratory analyses; Olanrewaju O. Aliu co-designed the study and revised the manuscript; Gbenga E. Omoniyi and Oluwaseun T. Akinpelu both participated in the laboratory analyses. Funding This research did not receive any specific grant from funding agencies in the public, commercial or not-for-profit sectors. Declaration of competing interest The authors declare that they have no conflict of interest. Appendix A. Supplementary data Supplementary data to this article can be found online at https:// doi.org/10.1016/j.ecoenv.2019.110153. References Adewunmi, C.O., Becker, W., Kuehmast, O., Oluwole, F., Dorfler, G., 1996. Accumulation of copper, lead and cadmium in freshwater snails in southwestern Nigeria. Sci. Total Environ. 193, 69–73. Ahmad, M.K., Islam, S., Rahman, M.S., Haque, M.R., Islam, M.M., 2010. Heavy metals in water, sediment and some fishes of Buriganga River, Bangladesh. Int. J. Environ. Res. 4, 321–332. Ahmed, M.K., Baki, M.A., Islam, M.S., Kundu, G.K., Sarkar, S.K., Hossain, M.M., 2015. Human health risk assessment of heavy metals in tropical fish and shellfish collected from the River Buriganga, Bangladesh. Environ. Sci. Pollut. Res. 22 (20), 15880–15890. Akindele, E.O., Olutona, G.O., 2014. Water physicochemistry and zooplankton fauna of Aiba Reservoir headwater streams. J. Ecosyst. 105405. Akindele, E.O., Olutona, G.O., Oyeku, O.G., Adeniyi, A.V., 2017. Assessment of two persistent bioaccumulative toxicants in the UNESCO protected river of Osun-Osogbo, Nigeria. Ecol. Process. 6, 30 (2017). Akindele, E.O., Adeniyi, A.V., Oyeku, O.G., Adu, B.W., 2018. Analysis of benthic macroinvertebrates, biological water quality and conservation value of a tropical river and UNESCO-protected environment. Afr. J. Ecol. 56, 488–498. Akoto, O., Bruce, T.N., Darko, G., 2008. Heavy metal pollution profiles in streams serving
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