2. Please cite this article in press as: Keshavarzi, B., et al., A GIS-based approach for detecting pollution sources and
bioavailability of metals in coastal and marine sediments of Chabahar Bay, SE Iran. Chemie Erde - Geochemistry (2014),
http://dx.doi.org/10.1016/j.chemer.2014.11.003
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interpretation of statistical output (Lee et al., 2006; Gong et al.,
2010; Kharroubi et al., 2012). However, GIS-based study for sed-
iment quality assessment has never been conducted in Chabahar
Bay. Environmental geochemistry mapping provides a reliable
mean for monitoring environmental conditions and identify-
ing problem areas. Therefore, GIS was used as an ideal tool for
interpretation, integration and presentation of geochemical data
obtained from Chabahar Bay sediments.
The main objectives of the present study are: (1) to determine
spatial variation of Cu, Pb, Zn, Cd, Ni, Cr, Co, V and Fe in Chabahar
Bay sediments; (2) to identify probable pollution sources of the
sediments; (3) to assess metals bioavailability in the sediments.
2. Materials and methods
2.1. Study area
Chabahar Bay is the largest bay along the Iranian coastline of Oman Sea. This
omega-shaped bay is situated in Sistan and Baluchestan province, SE Iran. Aver-
age depth is 6 m with a surface area of approximately 320 km2
. The climate is hot
and humid with severe summers (42 ◦
C) and moderate winters (20–28 ◦
C). Annual
precipitation is variable and averages about 150 mm. Geologically, Chabahar Bay
comprises the coastal part of the Makran zone (Ghomashi and Mohebbi, 1996). Ophi-
olitic complexes and flysch deposits constitute two major lithological units in this
zone. Sedimentary units include shallow sea environment marls, sandstones and
conglomerates (Fig. 1).
Sistan and Baluchestan province fishing harbors provide approximately 80% of
Iran’s tuna fish supply (Hamzeh et al., 2013). Commercial and fishing vessels spend
9 months of the year in Oman Sea and Indian Ocean but during summer because of
monsoon climate, Oman Sea is very rough to sail and the vessels are unable to leave
Chabahar Bay. The ongoing process of maintenance and repair of the vessels in the
harbors puts enormous stress on semi-enclosed environment of the bay.
2.2. Sampling and analysis
In this investigation, a total of 19 composite sediment samples including a local
background were collected in 2012. The local background sample was collected
outside and east of Chabahar Bay with no known anthropogenic sources. The geo-
graphical coordinates of sampling stations are plotted in Fig. 1. Intertidal sediments
were collected using a stainless steel spatula during ebb tide and bed sediments
were collected using a Van Veen grab sampler from a boat. Sediments were placed
in sealed polyethylene plastic bags, labeled and stored at 4 ◦
C until analysis. Water
pH was determined in situ using portable devices.
In the laboratory, shells and litter were removed and the samples were air-dried
at room temperature. Then each sample was ground in an agate mortar and pestle,
sieved through a 2-mm nylon sieve and split into two fractions. The first fraction
was used for physico-chemical analysis, while the second, was passed through a
63-m sieve to obtain silt and clay fraction for evaluation of total concentration
and bioavailability of metals. Sediment samples were analyzed using inductively
coupled plasma-mass spectrometry (ICP-MS) for metals (Cu, Pb, Zn, Cd, Ni, Cr, Co, V
and Fe) in an accredited Canadian laboratory (Acme labs ISO 9001). To evaluate the
quality of chemical analysis, a standard reference material (STD OREAS45EA) and a
reagent blank were used. The recovery percentages are Cu (96.8%), Pb (96.8%), Zn
(96.7%), Cd (100.0%), Ni (104.1%), Cr (94.2%), Co (101.3%), V (98.3%) and Fe (106.6%)
indicating a good agreement between the measured and the certified values.
For grain size analysis, sediments were wet-sieved through a 63-m sieve in
order to determine weight percentage of sand fractions. The remaining silt and
clay fractions were analyzed using a Laser Particle Size Analyzer (Fritsch Analysette
22), and subsequently silt and clay weight percentages were calculated. The sedi-
ments are categorized based on the classification of Shepard (1954) using SEDPLOT
software.
Sediment OM content was estimated using the loss on ignition (LOI) method
(550 ◦
C for 4 h) (Heiri et al., 2001). Cation exchange capacity (CEC) was determined
using sodium acetate and ammonium acetate solution. The method is described
by Ryan et al. (2007). Sodium content of the extracted liquids was measured by
an Atomic Absorption Spectrometer (Shimadzu AA-680) in an air-acetylene flame.
Cation exchange capacity was calculated using the following formula:
CEC (cmol/kg) = Na (meq/L) ×
A
Wt
×
100
1000
where A is total volume of the extract (ml) and Wt is weight of the air-dried sediment
(g).
2.3. Sediment contamination assessment
The geo-accumulation index (Igeo) is a common criterion for assessing sedi-
ment’s metal pollution in marine as well as freshwater environments (Yu et al., 2008;
Léopold et al., 2008). Geo-accumulation index was introduced by Muller (1969)
Table 1
Modified BCR sequential extraction procedure.
Fraction Extractant Extracted sediment
component
F1 (acid soluble) 0.11 M HOAc, 16 h Exchangeable ions
and carbonates
F2 (reducible) 0.5 M NH2OH·HCl, pH = 2
(HNO3), 16 h
Iron-manganese
oxides
F3 (oxidable) 8.8 M H2O2, 2 h at 85 ◦
C,
extracted with 1.0 M
NH4OAc, 16 h
Sulfides/organics
F4 (residual) Hot aqua regia: 3
HCl + HNO3
Metals bound in
lithogenic minerals
to determine metal contamination in sediments, by comparing current concentra-
tions with preindustrial levels. Geo-accumulation index was calculated using the
following formula:
Igeo = log2
Cn
1.5Bn
where Cn is measured concentration of an examined metal in a sediment and Bn
is the geochemical background concentration of the metal. In the present study,
concentration of the metals in the local background sample was adopted as Bn. The
factor 1.5 is the background matrix correction factor due to lithogenic variations.
To evaluate overall contamination of sediments in various stations, Cd was cal-
culated using Hakanson (1980) equation:
Cd =
9
i=1
Ci
0−1
Ci
n
where Ci
0−1
refers to mean concentration of each metal in sediment and Ci
n refers to
metal’s geochemical background concentration. In this paper, metals concentration
in the local background sample was adopted as Ci
n.
2.4. Statistical analysis
In the present study, statistical analyses were performed on the metal content
and selected physico-chemical properties (clay size fraction, OM and CEC) of the
sediment samples. The statistical analyses are represented by HCA and Spearman’s
correlation coefficient, using SPSS software version 19.
Hierarchical cluster analysis group variables or sampling stations according to
their similarities in order to detect expected or unexpected clusters including the
presence of outlier. In this way, each variable forms a cluster initially and the prelim-
inary matrix is analyzed. The most similar variables are grouped into a cluster and
the process is repeated until all variables belong to one cluster. Hierarchical cluster
analysis examines the distances between samples and data set (Birth, 2003). In this
paper, Z scores transformation was used to standardize the raw data and Ward’s
method was applied to perform HCA.
2.5. BCR sequential extraction scheme
The modified BCR sequential extraction procedure was carried out on five sedi-
ment samples to evaluate metals bioavailability (Arain et al., 2008; Malferrari et al.,
2009; Yan et al., 2010; Moore et al., 2015). Samples selection was based upon the
sediments metal content and geographical position of the sampling stations. The
sequential extraction was performed progressively on an initial weight of 0.5 g of dry
sediment. The metals concentration in each fraction was determined using induc-
tively coupled plasma-optical emission spectrometry (ICP-OES) as the high salinity
of the extracted phases did not allow the use of ICP-MS. A certified reference mate-
rial (GBW 7312) and a reagent blank were analyzed for analytical quality control.
Recovery percentages for the analyzed metals were found to be: Cu (106.7%), Pb
(88.2%), Zn (98.2%), Ni (100.0%), Cr (100.0%), Co (90.9%), V (104.3%) and Fe (97.0%).
The extractants and operationally defined chemical phases used in the current study
are summarized in Table 1. Apart from checking the validation of sequential extrac-
tion results, the sediments were subjected to total metal digestion by the same
method as in the residual fraction and recovery percentages were calculated as:
Recovery =
CFraction 1 + CFraction 2 + CFraction 3 + CResidue
Ctotal digestion
× 100
where CFraction X and CResidue are concentrations of a metal in each fraction of sequen-
tial extraction analysis and Ctotal digestion is concentration of the metal in the single
digestion. The average recovery values ± SD were 87.3 ± 6.5, 82.5 ± 3.2, 110.0 ± 11.9,
87.2 ± 3.6, 112.7 ± 6.3, 86.1 ± 2.3, 96.8 ± 7.4 and 91.6 ± 4.5% for Cu, Pb, Zn, Ni, Cr, Co,
V and Fe, respectively. Recovery percentages demonstrate that sums of the four
fractions are in good agreement with the total digestion results.
3. Please cite this article in press as: Keshavarzi, B., et al., A GIS-based approach for detecting pollution sources and
bioavailability of metals in coastal and marine sediments of Chabahar Bay, SE Iran. Chemie Erde - Geochemistry (2014),
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Fig. 1. Geological map and sampling locations in Chabahar Bay.
Metals contamination factor is commonly used to indicate the metals risk to
the environment in relation to their retention time (Nemati et al., 2009). Individual
contamination factor (ICF) reflects risk of water body contamination by a pollutant
in various sampling stations but global contamination factor (GCF) assays effects of
a combination of metals contamination in each sampling station (Ikem et al., 2003).
The ICF and GCF were calculated using the following formulas:
ICFmetal =
Cnonresistant
Cresistant
GCF =
n
i=1
ICFi
where Cnonresistant is sum of extracted percentages of a metal in the first three frac-
tions (i.e. acid soluble, reducible and oxidable) and Cresistant is extracted percentage
of the metal in the residual fraction (Ikem et al., 2003).
2.6. GIS and spatial analysis
Geographic information system (GIS) is a system for managing, manipulating,
analyzing and presenting geographically-related data (Collins et al., 1995). Environ-
mental geochemistry maps prepared by GIS are commonly used to identify sediment
quality and sediment contamination hot spot areas. The software used in this study
was ArcGIS version 10.1. In the current study, a shape file was created and GCS WGS
1984 was used as coordinate system. The geographical coordinates of sampling sta-
tions, OM content, CEC, the metals concentrations, calculated Igeo, Cd values, HCA
results and computed ICFs and GCFs were then used as the input data for creating
symbol maps to study distribution and bioavailability of the metals in the sediments.
The obtained maps were then overlaid with other thematic maps, such as drainage,
land and sea, using ArcMap software. Geographic information system (GIS) was used
in this study in the following aspects:
• To locate the sampling stations in the study area and geological map compilation
(as Fig. 1).
• To assess spatial variation of OM and CEC in different stations (as Fig. 2).
• To generate geochemical maps showing the metals distribution in the sediments
(as Fig. 3).
• To classify different stations under Igeo classes for each metal (as Fig. 4).
• To visualize overall pollution of the studied metals in different stations
(as Fig. 5).
• To distinguish polluted stations from unpolluted ones (as Fig. 7).
• To evaluate the metals bioavailability by comparison of their ICFs and GCFs in
different stations (as Fig. 9).
3. Results and discussion
3.1. Sediments physico-chemical properties
Distribution of grain size and OM content are two impor-
tant parameters affecting metal distribution in sediments (Liaghati
et al., 2003). Table 2 reveals that granulometry of the sediments
varies mainly between sandy to clayey. The sediments in S3, S9,
S8, S4, S1, T1, S5 and Ch3 stations display the highest OM content
(Table 2 and Fig. 2). The observed high OM in the sediments is most
likely due to discharge of fuel and sewage from fishing vessels along
with discharge of fishing leftovers. The results are similar to those
obtained by Hamzeh et al. (2013) in three harbors along the Ira-
nian Oman Sea coastline close to and environmentally similar to
Chabahar Bay.
Table 2 and Fig. 2 show that the highest CEC values occur in T3,
S9, S8, S3, S5, S4, S1, S6, T1 and Ch3 stations. Both clay minerals and
OM content play a role in sediments’ CEC.
4. Please cite this article in press as: Keshavarzi, B., et al., A GIS-based approach for detecting pollution sources and
bioavailability of metals in coastal and marine sediments of Chabahar Bay, SE Iran. Chemie Erde - Geochemistry (2014),
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Fig. 2. Spatial variation of OM and CEC in the sediments.
3.2. Metals spatial distribution
Table 2 reveals that average concentration of Cu
(16.9 ± 12.9 mg/kg), Zn (49.0 ± 22.5 mg/kg), Cd (0.23 ± 0.24 mg/kg),
Ni (55.8 ± 17.5 mg/kg), Cr (38.5 ± 9.31 mg/kg), Co
(9.97 ± 2.44 mg/kg), V (24.4 ± 5.29 mg/kg) and Fe (2.07 ± 0.54%) in
Chabahar Bay sediments is higher than corresponding concentra-
tions in the local background sample. Metals distribution in the
sediments is demonstrated in Fig. 3 using a series of geochemical
maps produced for each metal. Fig. 3 indicates that Cu, Zn and Cd
concentrations in Ch3, S1, T1, S9, S3 and S4 stations are clearly
higher. The highest Pb concentration (25.5 mg/kg) also occurs in
Ch3 station. Maximum Ni, Cr, Co, V and Fe concentrations were
observed in the sediments of T3 and S9 stations which also display
the highest clay size fraction.
3.3. Sediment contamination assessment
Spatial variation of Igeo in the stations is represented by a series
of maps produced for each metal (Fig. 4). As shown in Fig. 4, Cu
concentration in Ch3 station is strongly polluted and in S1 and
S9 stations is moderately to strongly polluted. The sediments col-
lected from Ch3 station are also unpolluted to moderately polluted
with Pb. Zinc in the sediments of Ch3 and T1 stations is strongly
polluted and moderately to strongly polluted in S1, S3, S4, S5, S7,
S8, S9, M1 and T3 stations. According to Table 2 and Figs. 2–4, not
only metal pollution but also metal concentration, OM content and
clay size fraction of sediments decrease gradually from S9 station
in a NE direction. Hence, it is probable that the sediments in S8
station and to a lesser extent sediments in S7 station are indirectly
affected by the pollution in S9 station. Regarding Cd, S3 station is
Fig. 3. Spatial distribution of analyzed metals in Chabahar Bay sediments.
5. Please cite this article in press as: Keshavarzi, B., et al., A GIS-based approach for detecting pollution sources and
bioavailability of metals in coastal and marine sediments of Chabahar Bay, SE Iran. Chemie Erde - Geochemistry (2014),
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Fig. 4. Spatial variation of Igeo classes in the sediments.
moderately to strongly polluted. The S1, Ch3, S3, S4, S5, T1 and S9
stations are located in Chabahar Bay semi-enclosed harbors which
due to restricted water circulation, trap shipping wastes. The T3,
S9, S8, S3 and S4 stations display the highest Igeo values for Ni. As
it can be seen from Fig. 4, Cr, Co, V and Fe content in sediments
is classified in two Igeo classes as anthropogenic activity has no
impact on their concentrations.
Sediment contamination is illustrated in Fig. 5 by plotting
calculated Cd for Chabahar Bay stations. Fig. 5 reveals that most con-
taminated stations (Ch3, S1 and S3) are located in SE of Chabahar
Fig. 5. Contamination degree variation in Chabahar Bay sediments.
6. Please cite this article in press as: Keshavarzi, B., et al., A GIS-based approach for detecting pollution sources and
bioavailability of metals in coastal and marine sediments of Chabahar Bay, SE Iran. Chemie Erde - Geochemistry (2014),
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Table2
Metalsconcentrationsandselectedphysico-chemicalpropertiesofChabaharBaysediments.
SamplingstationsCu(mg/kg)Pb(mg/kg)Zn(mg/kg)Cd(mg/kg)Ni(mg/kg)Cr(mg/kg)Co(mg/kg)V(mg/kg)Fe(%)CEC(cmol/kg)OM(%)Sand(%)Silt(%)Clay(%)Sedimenttype
S136.118.576.20.4756.042.59.8029.02.3615.13.4555.818.625.6Clayeysand
S212.99.4935.80.1447.834.68.2024.01.757.802.3082.110.67.30Sand
S321.812.863.90.8865.345.610.928.02.4022.25.8672.513.114.4Clayeysand
S421.414.654.30.7664.346.410.630.02.3921.13.5441.820.437.8Sandsiltclay
S512.611.040.30.1257.038.99.6024.02.0321.63.1326.519.753.8Sandyclay
S68.819.2337.40.0854.835.39.6021.01.9315.12.2133.822.843.4Sandsiltclay
S710.610.240.80.0961.439.411.023.02.149.302.3349.315.235.5Clayeysand
S813.611.754.30.1280.249.313.629.02.8423.93.9848.34.8046.9Clayeysand
S929.012.573.70.1385.152.813.831.02.8826.15.036.2018.875.0Clay
S106.198.4628.00.0740.627.38.2019.01.548.942.5213.073.913.1Clayeysilt
S117.528.1229.50.0641.630.38.1019.01.598.811.9421.163.115.8Sandysilt
S1212.411.928.70.1245.429.48.0018.01.578.162.3087.86.106.10Sand
T317.621.260.60.0888.154.415.333.02.9227.31.945.9014.979.2Clay
Ko14.829.8120.60.0827.926.57.6017.01.2710.01.4615.474.110.5Sandysilt
Ch356.225.587.80.3852.138.89.5027.02.2113.62.8050.719.729.6Clayeysand
T117.616.090.90.2857.441.010.426.02.1414.93.2024.218.557.3Sandyclay
M111.321.843.00.1156.940.110.027.02.315.891.2812.870.316.9Clayeysilt
A14.3012.216.50.0822.120.75.2015.01.0713.00.9418.970.710.4Sandysilt
Average16.913.649.00.2355.838.59.9724.42.0715.22.7937.030.932.1–
SD12.95.0522.50.2417.59.312.445.290.546.891.2625.625.823.0–
Background4.1614.76.700.1410.39.408.6017.01.237.891.1390.55.254.25Sand
Fig. 6. Dendrogram of the metals, clay size fraction, OM content and CEC in the
sediments.
Bay with contamination decreasing in a NW direction. The S9
station, located west of the bay, is as contaminated as SE stations.
3.4. Statistical analysis
Hierarchical cluster analysis was conducted to identify major
source(s) of the metals in Chabahar Bay sediments (Fig. 6). Cluster
A contains Ni, Cr, Co, V and Fe, probably contributed by geogenic
sources. Moreover, CEC, clay size fraction and the metals occur in
the same cluster. Considering the low CEC in sediments and the
role of OM in CEC, metals adsorption on clay minerals is proba-
bly insignificant and Ni, Cr, Co, V and Fe are incorporated in the
crystalline structure of the clay size fraction. Lorand and Ceuleneer
(1989), Leblanc and Ceuleneer (1991) and Hamzeh et al. (2013)
believe that Oman Sea and Makran ophiolites contain chromite and
nickel sulfide minerals. Discharge of river and seasonal streams
flowing on the northern weathered ophiolites of Makran moun-
tains, and also oceanic crust weathering apparently release clay
size fraction of metalliferous sediments into Oman Sea water. A
fraction of the sediments is carried to coastal areas by waves, while
some will deposit on Oman Sea bed. Sea bed sediments disturbance
can resuspend the clay size fraction in Oman Sea water. Accord-
ing to annual mean global wind-induced upwelling maps (Xie and
Hsieh, 1995), upwelling velocity in Oman Sea is about 5–10 cm/day.
Hence, suspended clay size fraction moves toward coastal areas and
contributes to the geogenic pollution of the metals in Chabahar Bay
sediments. Hamzeh et al. (2013) also reported that Ni and Cr pol-
lution in sediments of three harbors along the Iranian Oman Sea
coast comes from the ophiolitic units found in the northern Makran
mountains. Moreover, de Mora et al. (2004) described that high con-
centration of Ni in the sediments of southern coasts of Oman Sea
is contributed by ophiolites and metalliferous sediments of marine
origin.
Copper, Pb, Zn and Cd are present in cluster B reflecting simi-
lar source(s) or geochemical properties. Organic matter also occurs
in this cluster indicating that OM is an important metal carrier.
Numerous paint stains on sediments of the harbors indicate that at
least some of the metals pollution come from antifouling and sea
vessel paints. Colored paint fragments also come from boats main-
tenance yard and grounded ships. It is already reported that Cu, Pb,
Zn and Cd are present in paints and pigments (Sparks, 2005) and
their high total concentration is also reported in soils and dusts
contaminated by marine antifouling paints (Turner et al., 2009).
7. Please cite this article in press as: Keshavarzi, B., et al., A GIS-based approach for detecting pollution sources and
bioavailability of metals in coastal and marine sediments of Chabahar Bay, SE Iran. Chemie Erde - Geochemistry (2014),
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Fig. 7. Hierarchical cluster analysis results for 18 sampling stations of Chabahar Bay.
Antifouling paints are most identified major sources of Cu and
Zn pollution in marine environments (Singh and Turner, 2009a,
2009b; Jones and Turner, 2010). Furthermore, copper-containing
wood preservatives applied in marine environments constitute a
potential source of Cu (Singhasemanon et al., 2009).
Hierarchical cluster analysis was also carried out to distin-
guish anthropogenic impacted stations. The 18 sampling sites were
clustered into two different groups depending upon their metal
concentration, OM, clay size fraction and CEC (Fig. 7). Sediments
that appear in the same group, either have similar physico-chemical
properties or anthropogenic/natural pollution source. The S1, S3,
S4, S8, S9, Ch3 and T1 stations in cluster B are probably affected by
anthropogenic activity. Similar Ni, Cr, Co, V and Fe content and CEC
in sediments of T3 station with those in S8 and S9 stations, put T3
in cluster B. Other sampling stations which are grouped in cluster
A probably are not impacted by anthropogenic pollution.
Distribution of the metals concentration and the physico-
chemical parameters in the sediment samples is non-normal,
therefore Spearman’s correlation coefficient was performed to sup-
port HCA results and determine the most important geochemical
carriers of the metals. In general, based on Table 3 the correlations
between anthropogenic metals (Cu, Pb, Zn and Cd) are significant
(r ≥ 0.55). The association of Ni, Cr, Co, V and Fe is strong (r ≥ 0.86),
so these metals in the sediments may share the same geogenic
source. Clay size fraction and CEC show significant positive cor-
relations (r ≥ 0.68 and 0.67, respectively) with Ni, Cr, Co, V and
Fe which is in agreement with the HCA results. Percentage of clay
size fraction in S3 and S4 stations is low, while Ni concentration in
the sediments is high suggesting possible anthropogenic pollution.
However, further investigation is needed to confirm this assump-
tion. In addition, there is a significant correlation between Fe, OM
and anthropogenic metals probably reflecting the importance of
Fe oxy-hydroxides and OM in the metals mobility. Lack of such a
significant correlation for OM–Pb and Fe–Cd indicates that Pb and
Cd mobility is controlled by Fe oxy-hydroxides and OM, respec-
tively (Table 3). Furthermore, average pH of 8.12 at Chabahar Bay
is the reason for negative charge of Fe oxy-hydroxides which play
an essential role in the metals adsorption. These results agree with
those of Okafor and Opuene (2007) and Luoma and Rainbow (2008).
3.5. Metals bioavailability
Total Cu, Pb, Zn, Ni, Cr, Co, V, and Fe concentration and extracted
percentage of the metals in the chemical fractions of Chabahar Bay
sediments are shown in Fig. 8. Since the concentration of Cd in
different chemical fractions is below the detection limit, fraction-
ation of this metal is ignored. The figure reveals that the highest
Cu, Pb and Zn percentages in the majority of the samples occur
in the reducible fraction, reflecting their potential bioavailability
in the sediments. According to Sundaray et al. (2011), colloids of
Fe–Mn oxides are efficient scavengers of Cu, Pb and Zn. On the con-
trary, Ni, Cr, Co, V and Fe are the least bioavailable metals with the
Table 3
Spearman’s correlation among selected physico-chemical properties and the metals in the sediments.
Elements Clay CEC OM Fe V Co Cr Ni Cd Zn Pb Cu
Cu 0.46 0.54*
0.74**
0.80**
0.84**
0.60**
0.75**
0.65**
0.69**
0.90**
0.68**
1.00
Pb 0.33 0.31 0.21 0.62**
0.63**
0.42 0.56*
0.45 0.55*
0.72**
1.00
Zn 0.65**
0.54*
0.65**
0.82**
0.82**
0.72**
0.80**
0.72**
0.65**
1.00
Cd 0.08 0.30 0.59*
0.39 0.44 0.23 0.37 0.26 1.00
Ni 0.78**
0.73**
0.59**
0.92**
0.87**
0.97**
0.96**
1.00
Cr 0.76**
0.72**
0.61**
0.98**
0.96**
0.95**
1.00
Co 0.78**
0.67**
0.55*
0.91**
0.86**
1.00
V 0.68**
0.67**
0.61**
0.97**
1.00
Fe 0.70**
0.69**
0.60**
1.00
OM 0.38 0.58*
1.00
CEC 0.74**
1.00
Clay 1.00
*
Correlation is significant at the 0.05 level (two-tailed).
**
Correlation is significant at the 0.01 level (two-tailed).
8. Please cite this article in press as: Keshavarzi, B., et al., A GIS-based approach for detecting pollution sources and
bioavailability of metals in coastal and marine sediments of Chabahar Bay, SE Iran. Chemie Erde - Geochemistry (2014),
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8 B. Keshavarzi et al. / Chemie der Erde xxx (2014) xxx–xxx
Fig. 8. Total Cu, Pb, Zn, Ni, Cr, Co, V and Fe concentration and the metals extracted percentage in the chemical fractions of the sediments.
9. Please cite this article in press as: Keshavarzi, B., et al., A GIS-based approach for detecting pollution sources and
bioavailability of metals in coastal and marine sediments of Chabahar Bay, SE Iran. Chemie Erde - Geochemistry (2014),
http://dx.doi.org/10.1016/j.chemer.2014.11.003
ARTICLE IN PRESSG Model
CHEMER-25338; No.of Pages11
B. Keshavarzi et al. / Chemie der Erde xxx (2014) xxx–xxx 9
Fig. 9. ICFs and GCFs of Cu, Pb, Zn, Ni, Cr, Co, V and Fe in the sediments.
highest percentage (over 58.7% on average) being in the residual
fraction. The results indicate that Ni, Cr, Co, V and Fe are strongly
associated with the crystalline phases in the sediments. Hamzeh
et al. (2013) suggested clinochlore and chromite as important min-
eralogical sources of Ni and Cr in sediments of the Iranian Oman Sea
coast. Bioavailability of the studied metals considering their total
concentration is as follows:
3.5.1. Copper
It is obvious from Fig. 8 that the highest Cu concentration occurs
in the sediments of Ch3 and S9 stations (56.2 and 29.0 mg/kg,
respectively) which indicate high Cu percentage (50.8 and 79.5%,
respectively) in the reducible fraction. Among the other three sta-
tions, Cu bioavailability in the sediments of T1 station is higher
because of high Cu total concentration and extracted Cu percentage
(66.4%) in the first two fractions.
3.5.2. Lead
Not only the highest Pb concentration is seen in the sediments of
Ch3 station but as already mentioned, it is the only station impacted
by Pb pollution. Hence, the highest Pb bioavailability is expected,
because the highest extracted Pb (63.9%) occurs in the reducible
fraction (Fig. 8).
3.5.3. Zinc
Total Zn concentration in T1 and Ch3 stations (90.9 and
87.8 mg/kg, respectively) is higher than that of S9 station
(73.7 mg/kg) but as in the sediments of S9 station, the majority
of Zn (54.3%) is bound to the acid soluble fraction (the most labile
fraction), Zn bioavailability is higher in this station (Fig. 8). In addi-
tion, Zn bioavailability in T1 station is higher than Ch3 station due
to higher Zn percentage (17.2%) in the first fraction.
3.5.4. Nickel, chromium, cobalt, vanadium and iron
According to Fig. 8, Ni, Cr, Co, V and Fe concentration and frac-
tionation display more or less similar patterns. At least 55.0% of Ni,
Cr, V and Fe and 43.0% of Co are extracted from the residual fraction
indicating that the metals bioavailability is low regardless of their
total concentration.
The ICFs and GCFs of Cu, Pb, Zn, Ni, Cr, Co, V and Fe in Chababar
Bay sediments are depicted in Fig. 9. The highest Cu ICF occurs in S9
and T3 stations (8.26 and 8.12, respectively), being insignificant in
other stations. High ICF in T3 station is seemingly due to occurrence
of the highest Cu percentage (34.0%) in the oxidable fraction (the
least labile fraction). Moreover, Cu concentration in the sediments
of T3 station (17.6 mg/kg) is not as high as Ch3, S9 and T1 stations
(56.2, 29.0 and 17.6 mg/kg, respectively) so high ICF value in this
station is not important. If one takes Cu concentration into consid-
eration, risk of water body contamination by the metal in different
stations is in the order of S9 > Ch3 > T1 > T3 > M1.
The highest measured Pb concentration (25.5 mg/kg) and calcu-
lated Pb ICF (4.26) in Ch3 station pose high Pb risk for water body
(Fig. 9). The highest Zn ICF was computed in S9, T1 and Ch3 stations
being 3.89, 3.17 and 1.82, respectively while the lowest was calcu-
lated in M1 (1.27) and T3 (0.54) stations. The results agree with the
sequential extraction analysis and reveal that Zn risk in stations
follows the order of S9 > T1 > Ch3 > M1 > T3.
According to sequential extraction analysis, since high percent-
ages of Ni, Cr, Co, V and Fe mostly occur in the residual fraction, ICF
of these metals is very low. Furthermore, as these metals share the
same geogenic source, their ICF variations are also low (Fig. 9).
Average ICFs of the metals in Chabahar Bay sediments displays
the following decreasing order: Cu (5.32) > Pb (3.28) > Zn (2.16) > Co
(0.87) > Fe (0.55) > V (0.48) > Cr (0.43) > Ni (0.29). Thus, generally
speaking, Cu, Pb and Zn which come from anthropogenic sources,
pose the highest risk for the bay contamination from the sediments.
10. Please cite this article in press as: Keshavarzi, B., et al., A GIS-based approach for detecting pollution sources and
bioavailability of metals in coastal and marine sediments of Chabahar Bay, SE Iran. Chemie Erde - Geochemistry (2014),
http://dx.doi.org/10.1016/j.chemer.2014.11.003
ARTICLE IN PRESSG Model
CHEMER-25338; No.of Pages11
10 B. Keshavarzi et al. / Chemie der Erde xxx (2014) xxx–xxx
The GCF values computed by summing the metals ICF in the sed-
iments of each station follow the order of S9 > Ch3 > T1 > M1 > T3.
According to Luoma and Rainbow (2008) metals tend to accumu-
late in sediments and contamination tends to be localized in a
hotspot near the input, and then gradually disperses regionally in
lower concentrations. Hence, those stations, especially S9, Ch3 and
T1, located in the area of anthropogenic activity pose the highest
potential risk for Chabahar Bay biota (Fig. 9).
4. Conclusion
High OM content in Chabahar Bay sediments is most likely the
result of fuel and sewage discharge from fishing vessels along with
discharge of fishing leftovers. Geo-accumulation index results indi-
cate that Ch3 is the most polluted station with Cu and Pb, while
Zn in Ch3 and T1 stations is strongly polluted. Also sediments of
S3 station are moderately to strongly polluted with Cd. The sed-
iments collected from T3, S9, S8, S3 and S4 stations display the
highest Ni Igeo. Chabahar Bay sediments are classified as unpolluted
to moderately polluted with respect to Cr, Co, V and Fe. Significant
correlations among OM, Fe, Cu, Pb, Zn and Cd possibly reflect the
important role of Fe oxy-hydroxides and OM in the metals mobil-
ity. The results of this investigation revealed that Cu, Pb, Zn and Cd
mostly come from anthropogenic sources (antifouling and sea ves-
sel paints), while Ni, Cr, Co, V and Fe probably come from geogenic
sources (ophiolites and deep sea sediments). Copper, Pb and Zn are
mostly extracted in the reducible fraction reflecting the fact that
these metals are potentially bioavailable in the sediments. More-
over, substantial percentages of Ni, Cr, Co, V and Fe occur in the
residual fraction reflecting their immobility under natural condi-
tions. Average ICFs reveals that Chabahar Bay sediments pose the
highest environmental threat by Cu, Pb and Zn. Calculated GCF
indicates that S9, Ch3 and T1 stations bear the highest potential
risk for Chabahar Bay biota. Urgent environmental measures are
recommended to avoid future undesirable consequences.
Acknowledgements
This research was supported by “Shiraz University Medical Geol-
ogy Research Center” to whom the authors are indebted. The
authors would also like to express their gratitude to the author-
ity and employees of Iranian National Institute for Oceanography
and Atmospheric Science (INIOAS) for their assistance in the field.
Thanks are extended to two anonymous reviewers and the asso-
ciate editor whose constructive comments has greatly improved
the quality of the paper.
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