Biological Evidence 2018, Vol.8, No.3, 21-31
24
1.10 Geo-accumulation index
Geo-accumulation index (Igeo) is used to determine the level of pollutant associated with anthropogenic activities
(Bhutiani et al., 2017; Izah et al., 2017c). Geo-accumulation index was developed by Muller (1969) and have been
severally applied by authors (Hassaan et al., 2016; Kowalska et al., 2016; Todorova et al., 2016; El-Metwally et al.,
2017; Bhutiani et al., 2017; Izah et al., 2017c; Gasiorek et al., 2017).
Igeo =Log
2
( )
.
( )
(Equation 5)
Where Elements (c) is the measured concentration of heavy metals in the sample, Element (b) is the background
value for the heavy metals; 1.5 is a constant factor used in the calculation because of possible variations of the
background data due to lithological differences.
1.11 Ecological risk index
Ecological risk index (ERI) is used to assess the extent a particular activity posed to the environment. The
Potential ecological risk (ER) is calculated for each individual metals, while the summation of ecological risk
based on location and it’s often expressed as R’ (Singovszka et al., 2014; Izah et al., 2018). Both ER and R’ was
developed by Hakanson (1980) and have been applied by Bhutiani et al. (2017), Izah et al. (2018), Mazurek et al.
(2017), Kowalska et al. (2016), Gasiorek et al. (2017), Todorova et al. (2016).
ER = Tr x CF (Equation 6)
Where Tr is the toxic response factor viz: Pb = 5, Cd = 30, Cr = 2, and Zn = 1 (Hakanson, 1980), Ni = 5 (Xu et al.,
2008; Soliman et al., 2015; Bhutiani et al., 2017), Co = 5 (Swarnalatha et al., 2013) and CF represents the
contamination factor.
R’ =
∑ +
+
+ + +
(Equation 7)
1.12 Statistical analysis
SPSS version 20 was used to carry out the statistical analysis. The sediment heavy metals were presented as mean
± standard error. One way analysis of variance was carried out at P=0.05. Tukey Honestly significant difference
was used to compare mean of the different locations. Spearman rho correlation matrix was used to show the
relationship between the various parameters studied. Geometric mean was calculated using Paleontological
statistics software package by Hammer et al. (2001).
2 Results and Discussion
The level of heavy metals in sediment of Nun River at Gbarantoru and Tombia towns in Bayelsa state is presented
in Table 2. While the correlation matrix of the parameters studied is presented in Table 3. The concentration of
cadmium in the sediment ranged from 0.005-0.012 mg/kg, being not significantly different (P>0.05) apart from
Location C (Table 2). Cadmium showed positive significant relationship with chromium (r=0.983), cobalt
(r=0.845), nickel (r=0.933), lead (r=0.917), zinc (r=0.950) and iron (r=0.867) at P<0.01 (Table 3).
The level of chromium in the sediment ranged from 0.001-0.003 mg/kg, and was significantly different (P<0.05)
between the various locations (Table 2). Chromium showed positive significant correlation with cobalt (r=0.887),
nickel (r=0.950), lead (r=0.900), zinc (r=0.967) and iron (r=0.883) at P<0.01 (Table 3).
The level of cobalt in the sediment ranged from 0.001 – 0.002 mg/kg, and showed significant difference (P<0.05)
among the various locations except for Location A (Table 2). Cobalt showed positive significant correlation with
nickel (r=0.803), zinc (r=0.837) and iron (r=0.912) at P<0.01, and lead (r=0.678, p<0.05) (Table 3).
Nickel level in the sediment ranged from 0.001-0.032 mg/kg, and differs significantly (P<0.05) among the various
locations (Table 2). Nickel showed positive significant correlation with lead (r=0.950), zinc (r=0.967) and iron
(r=0.883) at P<0.01 (Table 3).
