Ecological Risk Assessment of Selected Elements in Sediments from
Communities of the River Nun, Bayelsa State, Nigeria
Aigberua A.O1* and Tarawou T2 1,2Department of Chemical Sciences, Niger Delta University, Wilberforce Island, Bayelsa State, Nigeria
Received date: April 19, 2018; Accepted date: May 09, 2018; Published date:
May 17, 2018
*Corresponding author: Aigberua A.O, Department of Chemical Sciences, Faculty
of Science, Niger Delta University, Wilberforce Island, Bayelsa State, Nigeria, E-mail:
The ecological risks of some fractionated toxic elements (Pb, Cu, Cr, Cd, Zn and Ni) were assessed in sediments from communities around the
river Nun in the Niger Delta region of Nigeria. Mean value of secondary data (contaminated and control area) was used to calculate the ecological
risk following standard protocol. The resulting values were compared with standards. Results of contamination factors of study metals revealed
moderate contamination, all other heavy metals were uncontaminated except for Cu and Ni which depicted an index of geo-accumulation from not
contaminated to moderately contaminated, potential ecological risk index showed low ecological risk. Apart from Cr and Zn which revealed low
sum of pollution index all other metals ranged from moderate to high sum of pollution index. The Pollution Load Index (PLI) showed deterioration of
site quality with values greater than 1. However, results of the sum of pollution index and pollution load index may not be limited to activities of the
numerous oil and gas activities especially from makeshift refineries and bunkery in the vicinity of the river. Indiscriminate and uncontrolled discharge
of municipal wastes may be another potential source of heavy metals.
Keywords: Heavy metals; Contamination factor; Index of geo-accumulation; Potential ecological risk index; Sum of pollution index; Pollution load
index; River Nun;
As a result of the exploitation and exploration of crude oil and natural
gas, the ambient environment receives loads of human and industrial
effluents which may be detrimental to the health of its inhabitants
(Inengite et al., 2010). Consequent upon this is the resultant discharge
of waste and process water washings. In a country like Nigeria, where
the emission and disposal of all sorts of wastes into the environment
is not monitored, the contribution of heavy metals pollutants to the
environment by anthropogenic sources is overwhelming, hence, repeated
evaluation of the pollution status of the environment especially the soil
is imperative (Nriagu et al., 1988). According to Amnesty International’s
report, Shell has been responsible for 1,427 of the oil spills since 2007.
The report also looks at the Nigerian Agip Oil Company, a subsidiary of
the Italian Company ENI, which, it claims, has been another persistent
culprit. From the start of 2013 to the end of September, Agip recorded
471 spills compared to Shell’s 138, though the volume of Shell’s spills far
exceeded Agip’s at 16,000 barrels compared to Agip’s 4,000 (TAP, 2013).
An estimated 9 million – 13 million (1.5 million tons) of oil has been
spilled into the Niger Delta ecosystem over the past 50 years; 50 times
the estimated volume spilled in the Exxon Valdez oil spill in Alaska
1989 (FME, NCF, WWF, UK, CEESP-IUCN 2006).The Niger Delta has
a complex and extensive system of pipelines running across the region
and large amounts of oil spill incidences have occurred through the
pipelines and storage facility failures which may be caused by material
defect, pipeline corrosion, soil erosion or sabotage. The Department
of Petroleum Resources contends that 88% of the oil spill incidences
are traceable to equipment failure, main causes of oil spills in the Niger
Delta are vandalism, oil blowouts from the flow stations, accidental
and deliberate releases and oil tankers at sea (Nwilo and Badejo, 2004,
2005a,b). Additionally, oil spills occur when the carrier pipelines are not
regularly checked and maintained on a routine basis in such manner as to
ensure that their protective coatings have not undergone wear.
One of the major constituent of the soil majorly impacted by wastes is
heavy metals composition (Izah et al., 2017a-c, 2018). Heavy metals are
metals and metalloids which are stable and have density greater than 5g/
cm3 (Izah and Angaye, 2016; Izah et al., 2016; Izah et al., 2017d; Idris et al.,
2013; John and Duffus, 2002; Tamunobereton-ari et al., 2010).They have
also been defined based on density, some on atomic number or atomic
weight; and some on chemical properties or toxicity (John and Duffus,
2002). Presently, heavy metal is a major source of concern to human health
and the environment (Hassan et al., 2016). This could be due to the toxic
effect they pose in biological organisms and the food chain. Heavy metals
concentration in soil is usually higher within their top most regions (Wei
and Yang, 2010; Mazurek et al., 2017). The presence of metals in sediment
provides one of the largest storage of such within the river system (Peng
et al., 2009). Furthermore, sediments conserve important environmental
information and are increasingly recognized as both carrier and possible
source of contaminants in aquatic systems (Gungun and Ozturk, 2001).
Some past spills have led to the complete relocation or loss of some
communities, ancestral shrines and homes, potable drinking water,
forest and agricultural land, and most significantly is the loss of fishing
grounds and fish population, which is the major source of income for
the Niger Delta people (Kadafa, 2012). Particularly, the inter-tidal nature
of the nun river results in the intermittent washing ashore of pollutants
and the continuous redistribution of run offs from nearby agricultural
farmlands.Several studies have been conducted on water quality of
Nun River in Bayelsa state. But most of these studies mainly focused
on general physicochemical parameters (Ogamba et al., 2015; Agedah
et al., 2015) and microbial quality (Seiyaboh et al., 2017; Agedah et al.,
2015). Furthermore heavy metals (Aigberua et al., 2017) and microbial
characteristics (Kigigha et al., 2018) have been reported in Nun River
system. Aigberuaand Tarawou (2018), Aghoghovwia et al. (2018)
reported heavy metals in sediment of river Nun. But information about
the environmental risk assessment appears scanty in literatures.Therefore
it has become imperative that the ecological risk assessment of heavy
metals in bottom sediments within the river systems of the Niger Delta
region of Nigeria be evaluated using several pollution indices which
include the contamination factor, index of geo-accumulation, potential
ecological risk index and sum of pollution index. The intention of this
study is to evaluate the potential environmental impact or risk of heavy
metals availability within the aquatic ecosystem by applying theoretical
pollution indices modules.
The river Nun is one of the major navigable channels of the Niger Delta
region and one of the bifurcations of the Niger River course. The river
flows for about 160 km south to the Gulf of Guinea and empties into the
Atlantic Ocean at Akassa. The river course flows through sparse settlements
and swamps (Encyclopaedia Britannica, 2013). The main course of the
river lies between the coordinates of latitude 5.298847ºN and longitude
6.414350ºE and plays host to numerous oil and gas installations and illegal
oil refineries.The samples were collected around numerous communities
including Peremabiri, Otuan, Akpobeleiowei, Letughene, Ogboinbiri,
Yenagoa, Otuoke, Oloibiri, Amassoma and Sagbama. While the control
points were located about 2km away from the Sagbama community and
it’s environ.Like other regions within the Niger Delta, two predominant
climatic conditions depict the area including dry season (November to
March) and wet season (April to October). The region is characterized by
relative humidity and temperature of 50 – 95% and 30 ± 7oC respectively
all year round (Izah et al., 2017a-c, 2018; Aigberua et al., 2016).
Secondary data was used for this study. Data obtained for sediment
samples collected from two (2) control points were compared against
those from the contaminated areas across twelve (12) sampling points
within the river system as previously published by Aigberua and Tarawou
(2018). The overall mean of the contaminated and control areas of the
published work of Aigberua and Tarawou (2018) was summarized and
presented in Table 1. The baseline data obtained for the control point
sediments represent the maximum amount of that element in a naturally
undisturbed environment beyond which the environment is considered
polluted with the test elements (Puyate, 2007; Aigberua et al., 2017).
Furthermore, several mean have been used to calculate environmental
risks of heavy metals including median, geometric mean of contaminated
areas (Izah et al., 2017a-c; 2018) and arithmetic mean of the control area.
Therefore,the control data was used for the assessment of the ecological
risk of heavy metals in bottom sediments of the Nun river system. The
predominant heavy metals considered for the study include Pb, Cu, Cr,
Cd, Zn and Ni. The perceptual mapping of heavy metals distribution
across the Nun river system is presented in Figure 1. [Table 1]
Figure 1: Perceptual mapping of heavy metals distribution across the
Nun river system
Heavy metal pollution indices (HMPI)
Based on the data (Table 1), pollution indices model calculations that
have been employed to assess the impact of anthropogenic inputs, and
how they alter the concentration and distribution of toxic heavy metals
across bottom sediments were assessed for the Nun river system. The
following heavy metal pollution indices were applied: (i) Contamination
factor (Cif), (ii) Potential ecological risk index (Eir), (iii) Index of geo-accumulation, and (iv) Sum of pollution index.
Table 1: Mean heavy metal concentrations across various locations and
Lead, Pb (mg/kg)
Copper, Cu (mg/kg)
Chromium, Cr (mg/kg)
Cadmium, Cd (mg/kg)
Zinc, Zn (mg/kg)
Nickel, Ni (mg/kg)
Modified from Aigberua and Tarawou (2018)
Contamination factor (CF)
The contamination factor as suggested by Hakanson (1980) has been
used to describe the contamination of a given toxic substance in a lake
or sub-basin where Cif = Ci0-1/Cin where Ci0-1 is the mean content of
the substance and Cin is the pre-industrial reference level. The degree
for expressing the contamination factor can be described as: Cif< 1,
low contamination factor; 1 ≤ Cif< 3, moderate contamination factors;
3 ≤ Cif< 6, considerable contamination factors; and Cif ≥ 6, very high
Potential ecological risk index (PERI)
An ecological risk factor or index (Eri) to quantitatively express
the potential ecological risk of a given contaminant also suggested by
(Hakanson, 1980; Xu et al., 2008) is Eri = Tri xCif; where Tri is the toxic
response factor for a given substanceviz: Pb = Cu = 5, Cd = 30, Cr = 2,
and Zn = 1 (Hakanson, 1980), Ni = 5 (Izah et al., 2018; Xu et al., 2008;
Soliman et al., 2015; Bhutiani et al., 2017; Izah et al., 2018), and Cif is the
contamination factor. The following terminologies are used to describe the
risk factor: Eri< 40, low potential ecological risk; 40 ≤ Eri< 80, moderate
potential ecological risk; 80 ≤ Eri< 160, considerable potential ecological
risk; 160 ≤ Eri< 320, high potential ecological risk; and Eri ≥ 320, very high
Index of geo-accumulation (I-GEO)
The index of geo-accumulation proposed by (Muller, 1979; Muller,
1981) has been used to determine and define metal contamination in
sediments from Kolo creek in the Niger Delta (Inengite et al., 2010).
Geo-accumulation index serves to assess contamination by comparing
current and pre-industrial concentration of heavy metals (Muller, 1979;
Muller, 1981). Heavy metal concentration of a geographically similar
unaffected plot was used as control and its values expressed as the preindustrial
reference levels, similar to the work of (Pam et al., 2013). It
can be calculated using the equation: IGEO= log2[Ci/(1.5Cb)] where Ci
is the measured concentration of the examined metal i in the sediment,
and Cb is the geochemical background concentration or reference value
of the metal i and the factor 1.5 is used because of possible variations in
background values for a given metal in the environment.
The geo-accumulation index (IGEO) was distinguished into seven
classes by Muller: IGEO ≤ 0, class 0, practically uncontaminated; 0 < IGEO
≤ 1, class 1, uncontaminated to moderately uncontaminated; 1 < IGEO ≤
2, class 2, moderately contaminated; 2 < IGEO ≤ 3, class 3, moderately
to heavily contaminated; 3 < IGEO ≤ 4, class 4, heavily contaminated; 4
< IGEO ≤ 5, class 5, heavily to extremely contaminated; and 5 < IGEO< 6,
class 6, extremely contaminated (Muller, 1981).
Sum of pollution index (SPI)
Sum of pollution index is classified as integrated indices that serve
as indicators for calculating the contamination of more than one metal.
Consequently, this can be referred to as a bulk property. It can be defined
using the formula SPI = ΣPi where Pi is the single pollution index of
heavy metal i, and m is the count of the heavy metal species (6 in this
study). Soil and sediment quality assessment by heavy metals have been
previously studied (Hakanson, 1980; Kwon and Lee, 1998).The degree
of contamination (Cd), defined as the sum of all contamination factors
is used to describe the contamination degree as Cd< m, low degree of
contamination; m ≤ Cd< 2m, moderate degree of contamination; 2m ≤
Cd< 4m, considerable degree of contamination; and Cd> 4m, very high
degree of contamination (Caeiro et al., 2005; Pekey et al., 2004).
Pollution load index (PLI)
Pollution load index (PLI) as developed by Tomlinson et al. (1980),
being earlier adopted by Mohamed et al. (2014), Izah et al. (2017b) and
applied to evaluate the extent of metal pollution across each sampling
point within the river system (table 1). The mathematical expression:
PLI = (PI1 * PI2 * PI3 * ……….PIn)1/n
Where n is the number of metals evaluated (6 in this study) and PI is the
PI = Cn/Cb, where, Cn is the mean content of metals from at least five
sampling sites and Cb is the pre-industrial concentration of individual
metal. The PLI provides simple but comparative means for assessing
a site quality, where a PLI < 1 depicts perfection; PLI =1 depicts that
only baseline levels of pollutants are present and PL > 1 would indicate
deterioration of site quality. [Table 2]
Table 2: Heavy metal pollution indices of heavy metals in the Nun river system
Contamination factor, CF
Index of geo-accumulation, IGEO
Potential ecological risk index, PERI
Sum of pollution index, SPI
Pollution load index, PLI
Pollution indices (HMPI)
iv)CF≥6=very high CF
ii)0<IGEO≤1=uncontaminated to moderate contamination;
iv)2<IGEO≤3=moderate to heavy contamination;
vi)4<IGEO≤5=heavy to extreme contamination;
v)Er≥320=very high PERI
ii)PLI=1: only baseline levels of pollutants present
ii)PLI>1=deterioration of site quality
Results and Discussion
All heavy metals in this study revealed moderate contamination factor
for bottom sediments of the river Nun. This was contrary to an earlier
assessment of two auto mechanic workshops by Pam et al. (2013) where
a considerable to very high contamination factor was observed for Pb
and Cu. Overall, the heavy metal contamination factors for the Nun river
depicted the following trend: Cr < Pb < Cd < Zn < Cu < Ni (Table 2).
Likewise, heavy metals in sediments revealed low potential ecological
risk factor (Table 2) with Cd reflecting the most significant PERI value of
39.60. Generally, potential ecological risk index depicted the trend: Zn <
Cr < Pb< Cu < Ni < Cd (Table 2).
Likewise, heavy metals in sediments revealed low potential ecological risk factor (Table 2) with Cd reflecting the most significant PERI value of 39.60. Generally, potential ecological risk index depicted the trend: Zn < Cr
Bottom sediments of the Nun river system mostly revealed a geoaccumulation
index of the class 0 category for heavy metal accumulation
(that is, uncontaminated), apart from Cu and Ni which revealed
uncontaminated to moderately contaminated. Test metal levels depicted
the trend Cr < Pb< Cd < Zn < Cu < Ni (Table 2).
where higher IGEO values were reported for soils close to phosphate
fertilizer plant in Egypt. Also, this study contradicted earlier reports by
Inengite et al.(2010) where Pb, Ni, Cr and V depicted non-pollution on
the index of geo-accumulation scale. However, the result of this study
showed slight similarity of trend with cassava mill effluent contaminated
soil as reported by Izah et al. (2017c)
Apart from chromium and zinc which depicted low sum of pollution
indices all other heavy metals ranged from moderate to high degree of
contamination. The heavy metals being studied depicted the following
trend: Zn < Cr < Pb< Cu < Ni < Cd (Table 2).
The Pollution Load Index (PLI) revealed a deterioration of site quality
based on the observed degree of contamination which exceeded the value
of 1. PLI values of this study compared to that of Mohamed et al. (2014).
The perceptual mapping of the spatial distribution of heavy metals
across the Nun river was pictorially represented (Figure 1); this was used
to portray a vivid pictorial representation of the spread of the test metals
across the sampling points. Generally, the order of metal distribution
revealed the following trend: Zn > Ni > Cr >Pb> Cu > Cd (Figure 1).
Additionally, test metals were reported below the DPR permissive limit
for standard sediment environment.
This study assessed the ecological risk of selected elements across
spatial distributions in bottom sediments of the Nun river which is located
in the Niger Delta region of Nigeria. The associated ecological risk index
of heavy metals (viz: Pb, Cu, Cr, Cd, Zn and Ni) is an indicator that the
Nun river is been threatened by the load of anthropogenic inputs to which
it is subjected. The deterioration of site quality as revealed by the Pollution
Load Index (PLI) further substantiates this standpoint. However, the
significant pollutant load in the river may not be limited to activities of
the numerous oil and gas companies in the region as the river is also
prone to the indiscriminate and uncontrolled discharge of municipal
wastes and the activities of illegal oil refineries along some of its estuaries.
Even though the level of contaminating activities in the river is not yet
threatening to consume the natural resources of the aquatic ecosystem,
adequate measures must be taken to forestall the occurrence of oil spills as
the network of numerous carrier pipelines underwater threaten to become
future time-bombs if not regularly checked and maintained on a routine
The abstract of this work was selected for E-Poster at the “12th
International Conference on Environmental Toxicology and Ecological
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