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ARTICLE IN PRESSG ModelHEMER-25338; No. of Pages 11

Chemie der Erde xxx (2014) xxx–xxx

Contents lists available at ScienceDirect

Chemie der Erde

j o ur na l ho mepage: www.elsev ier .de /chemer

GIS-based approach for detecting pollution sources andioavailability of metals in coastal and marine sediments of Chabaharay, SE Iran

ehnam Keshavarzi1, Pooria Ebrahimi ∗, Farid Moore1

epartment of Earth Sciences, College of Sciences, Shiraz University, Shiraz 71454, Iran

r t i c l e i n f o

rticle history:eceived 3 June 2014ccepted 21 November 2014ditorial handling – Dr. K. Heide

eywords:habahar BayedimentISetal

ollutionequential extraction analysis

a b s t r a c t

Chabahar Bay in SE of Iran is a shallow semi-enclosed environment affected by anthropogenic activities.In this paper, 19 sediment samples were collected and concentration of selected metals (Cu, Pb, Zn, Cd, Ni,Cr, Co, V and Fe) was determined using ICP-MS analytical method. Sediment samples from five stationswere also selected for sequential extraction analysis and concentration of metals in each fraction wasdetermined using ICP-OES. In order to investigate the environmental quality of Chabahar Bay, geographicinformation system (GIS) along with geochemical data, environmental indices and statistical analyseswere used. Calculated contamination degree (Cd) revealed that most contaminated stations (Ch3, S1and S3) are located SE of Chabahar Bay and contamination decreases in a NW direction. The S9 station,west of the bay, is also contaminated. High organic matter (OM) content in the sediments is most likelythe result of fuel and sewage discharge from fishing vessels along with discharge of fishing leftovers.Significant correlation coefficient among OM, Fe, Cu, Pb, Zn and Cd seemingly reflects the importance ofthe role that OM and Fe oxy-hydroxides play in the metals mobility. The results of hierarchical cluster
analysis (HCA), computed correlation coefficient and sequential extraction analysis suggest that Cu, Pb,Zn and Cd probably come from antifouling and sea vessel paints, while Ni, Cr, Co, V and Fe are mostlikely contributed by ophiolitic formations located north of the bay and/or deep sea sediments. Averageindividual contamination factors (ICFs) indicated that the highest health hazard from the bay is posed byCu, Pb and Zn.
. Introduction

Coastal and marine sediments are considered sinks for variousetals naturally present in marine water and transported from the

and in both dissolved and suspended solid forms. Marine orga-isms and vegetation in coastal environments may bioaccumulateome metals and increase their potential capability for entry intohe food chain. Recent studies revealed that metals accumulation inoastal environments has significantly increased because of anthro-ogenic activity (Dessai and Nayak, 2009; Botté et al., 2010; Lint al., 2012). Sediments are commonly used in the preliminaryhase of environmental assessment to distinguish areas of possible

Please cite this article in press as: Keshavarzi, B., et al., Abioavailability of metals in coastal and marine sediments of Chttp://dx.doi.org/10.1016/j.chemer.2014.11.003

oncern, and trace temporal changes of contaminants (Rivaro et al.,004; Al-Ghadban and El-Sammak, 2005; Gao and Li, 2012).

∗ Corresponding author. Tel.: +98 9171260447.E-mail address: [email protected] (P. Ebrahimi).

1 Tel.: +98 711 2284572; fax: +98 711 2284572.

ttp://dx.doi.org/10.1016/j.chemer.2014.11.003009-2819/© 2014 Elsevier GmbH. All rights reserved.

© 2014 Elsevier GmbH. All rights reserved.

Most studies dealing with sediment metal contamination, useonly total metal content as a criterion to evaluate potential effectsof polluting metals. However, it is well understood that sediments’total metal content cannot predict bioavailability and toxicity ofmetals (Pagnanelli et al., 2004; Zemberyova et al., 2006; Clozelet al., 2006). Metals are generally present in a variety of chemicalforms in sediments and exhibit different physico-chemical behav-iors in terms of chemical interaction, mobility, bioavailability andpotential toxicity (Du Laing et al., 2008; Zhao et al., 2009; Alvarezet al., 2011). Several sequential extraction procedures have alreadybeen proposed, that mostly differ in nature of reagents used, andthe time required for optimum extraction. The most employedprocedure is the European Community Bureau of Reference (BCR)three-step sequential extraction technique (Ure et al., 1993) whichharmonizes the various sequential extraction procedures (Cuongand Obbard, 2006; Malferrari et al., 2009; Yan et al., 2010; Oyeyiola

GIS-based approach for detecting pollution sources andhabahar Bay, SE Iran. Chemie Erde - Geochemistry (2014),

et al., 2011; Moore et al., 2015).Geographic information system (GIS) is increasingly applied

in more recent environmental pollution studies to recognize non-point sources pollutants, and to refine and confirm geochemical

dx.doi.org/10.1016/j.chemer.2014.11.003


http://www.sciencedirect.com/science/journal/00092819

http://www.elsevier.de/chemer

mailto:[email protected]


IN PRESSG ModelC

2 ie der Erde xxx (2014) xxx–xxx

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Table 1Modified BCR sequential extraction procedure.

Fraction Extractant Extracted sedimentcomponent

F1 (acid soluble) 0.11 M HOAc, 16 h Exchangeable ionsand carbonates

F2 (reducible) 0.5 M NH2OH·HCl, pH = 2(HNO3), 16 h

Iron-manganeseoxides

F3 (oxidable) 8.8 M H2O2, 2 h at 85 ◦C,extracted with 1.0 MNH4OAc, 16 h

Sulfides/organics

ARTICLEHEMER-25338; No. of Pages 11

B. Keshavarzi et al. / Chem

nterpretation of statistical output (Lee et al., 2006; Gong et al.,010; Kharroubi et al., 2012). However, GIS-based study for sed-

ment quality assessment has never been conducted in Chabaharay. Environmental geochemistry mapping provides a reliableean for monitoring environmental conditions and identify-

ng problem areas. Therefore, GIS was used as an ideal tool fornterpretation, integration and presentation of geochemical databtained from Chabahar Bay sediments.

The main objectives of the present study are: (1) to determinepatial variation of Cu, Pb, Zn, Cd, Ni, Cr, Co, V and Fe in Chabaharay sediments; (2) to identify probable pollution sources of theediments; (3) to assess metals bioavailability in the sediments.

. Materials and methods

.1. Study area

Chabahar Bay is the largest bay along the Iranian coastline of Oman Sea. Thismega-shaped bay is situated in Sistan and Baluchestan province, SE Iran. Aver-ge depth is 6 m with a surface area of approximately 320 km2. The climate is hotnd humid with severe summers (42 ◦C) and moderate winters (20–28 ◦C). Annualrecipitation is variable and averages about 150 mm. Geologically, Chabahar Bayomprises the coastal part of the Makran zone (Ghomashi and Mohebbi, 1996). Ophi-litic complexes and flysch deposits constitute two major lithological units in thisone. Sedimentary units include shallow sea environment marls, sandstones andonglomerates (Fig. 1).

Sistan and Baluchestan province fishing harbors provide approximately 80% ofran’s tuna fish supply (Hamzeh et al., 2013). Commercial and fishing vessels spend

months of the year in Oman Sea and Indian Ocean but during summer because ofonsoon climate, Oman Sea is very rough to sail and the vessels are unable to leave

habahar Bay. The ongoing process of maintenance and repair of the vessels in thearbors puts enormous stress on semi-enclosed environment of the bay.

.2. Sampling and analysis

In this investigation, a total of 19 composite sediment samples including a localackground were collected in 2012. The local background sample was collectedutside and east of Chabahar Bay with no known anthropogenic sources. The geo-raphical coordinates of sampling stations are plotted in Fig. 1. Intertidal sedimentsere collected using a stainless steel spatula during ebb tide and bed sedimentsere collected using a Van Veen grab sampler from a boat. Sediments were placed

n sealed polyethylene plastic bags, labeled and stored at 4 ◦C until analysis. WaterH was determined in situ using portable devices.

In the laboratory, shells and litter were removed and the samples were air-driedt room temperature. Then each sample was ground in an agate mortar and pestle,ieved through a 2-mm nylon sieve and split into two fractions. The first fractionas used for physico-chemical analysis, while the second, was passed through a

3-�m sieve to obtain silt and clay fraction for evaluation of total concentrationnd bioavailability of metals. Sediment samples were analyzed using inductivelyoupled plasma-mass spectrometry (ICP-MS) for metals (Cu, Pb, Zn, Cd, Ni, Cr, Co, Vnd Fe) in an accredited Canadian laboratory (Acme labs ISO 9001). To evaluate theuality of chemical analysis, a standard reference material (STD OREAS45EA) and aeagent blank were used. The recovery percentages are Cu (96.8%), Pb (96.8%), Zn96.7%), Cd (100.0%), Ni (104.1%), Cr (94.2%), Co (101.3%), V (98.3%) and Fe (106.6%)ndicating a good agreement between the measured and the certified values.

For grain size analysis, sediments were wet-sieved through a 63-�m sieve inrder to determine weight percentage of sand fractions. The remaining silt andlay fractions were analyzed using a Laser Particle Size Analyzer (Fritsch Analysette2), and subsequently silt and clay weight percentages were calculated. The sedi-ents are categorized based on the classification of Shepard (1954) using SEDPLOT

oftware.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 determinedsing sodium acetate and ammonium acetate solution. The method is describedy Ryan et al. (2007). Sodium content of the extracted liquids was measured byn Atomic Absorption Spectrometer (Shimadzu AA-680) in an air-acetylene flame.ation exchange capacity was calculated using the following formula:

EC (cmol/kg) = Na (meq/L) × A

Wt× 100

1000

here A is total volume of the extract (ml) and Wt is weight of the air-dried sedimentg).


.3. Sediment contamination assessment

The geo-accumulation index (Igeo) is a common criterion for assessing sedi-ent’s metal pollution in marine as well as freshwater environments (Yu et al., 2008;

éopold et al., 2008). Geo-accumulation index was introduced by Muller (1969)

F4 (residual) Hot aqua regia: 3HCl + HNO3

Metals bound inlithogenic minerals

to determine metal contamination in sediments, by comparing current concentra-tions with preindustrial levels. Geo-accumulation index was calculated using thefollowing 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 . Thefactor 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

Ci0−1

Cin

where Ci0−1 refers to mean concentration of each metal in sediment and Ci

n refers tometal’s geochemical background concentration. In this paper, metals concentrationin the local background sample was adopted as Ci

n .

2.4. Statistical analysis

In the present study, statistical analyses were performed on the metal contentand selected physico-chemical properties (clay size fraction, OM and CEC) of thesediment samples. The statistical analyses are represented by HCA and Spearman’scorrelation coefficient, using SPSS software version 19.

Hierarchical cluster analysis group variables or sampling stations according totheir similarities in order to detect expected or unexpected clusters including thepresence 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 andthe process is repeated until all variables belong to one cluster. Hierarchical clusteranalysis examines the distances between samples and data set (Birth, 2003). In thispaper, Z scores transformation was used to standardize the raw data and Ward’smethod 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 thesediments metal content and geographical position of the sampling stations. Thesequential extraction was performed progressively on an initial weight of 0.5 g of drysediment. The metals concentration in each fraction was determined using induc-tively coupled plasma-optical emission spectrometry (ICP-OES) as the high salinityof 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 studyare summarized in Table 1. Apart from checking the validation of sequential extrac-tion results, the sediments were subjected to total metal digestion by the samemethod 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 singledigestion. 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 fourfractions are in good agreement with the total digestion results.


ARTICLE IN PRESSG ModelCHEMER-25338; No. of Pages 11

B. Keshavarzi et al. / Chemie der Erde xxx (2014) xxx–xxx 3

mplin

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I

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wto

2

amqw1trsTli

•

•

Fig. 1. Geological map and sa

Metals contamination factor is commonly used to indicate the metals risk tohe environment in relation to their retention time (Nemati et al., 2009). Individualontamination factor (ICF) reflects risk of water body contamination by a pollutantn various sampling stations but global contamination factor (GCF) assays effects of

combination of metals contamination in each sampling station (Ikem et al., 2003).he ICF and GCF were calculated using the following formulas:

CFmetal = Cnonresistant

Cresistant

CF =n∑

i=1

ICFi

here Cnonresistant is sum of extracted percentages of a metal in the first three frac-ions (i.e. acid soluble, reducible and oxidable) and Cresistant is extracted percentagef the metal in the residual fraction (Ikem et al., 2003).

.6. GIS and spatial analysis

Geographic information system (GIS) is a system for managing, manipulating,nalyzing and presenting geographically-related data (Collins et al., 1995). Environ-ental geochemistry maps prepared by GIS are commonly used to identify sediment

uality and sediment contamination hot spot areas. The software used in this studyas ArcGIS version 10.1. In the current study, a shape file was created and GCS WGS

984 was used as coordinate system. The geographical coordinates of sampling sta-ions, OM content, CEC, the metals concentrations, calculated Igeo, Cd values, HCAesults and computed ICFs and GCFs were then used as the input data for creatingymbol maps to study distribution and bioavailability of the metals in the sediments.he obtained maps were then overlaid with other thematic maps, such as drainage,and and sea, using ArcMap software. Geographic information system (GIS) was used


n 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).

g locations in Chabahar Bay.

• 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 (Liaghatiet al., 2003). Table 2 reveals that granulometry of the sedimentsvaries 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 mostlikely due to discharge of fuel and sewage from fishing vessels alongwith discharge of fishing leftovers. The results are similar to thoseobtained 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 andOM content play a role in sediments’ CEC.



4 B. Keshavarzi et al. / Chemie der Erde xxx (2014) xxx–xxx

f OM a

3

(N(CtsmchCot

Fig. 2. Spatial variation o

.2. Metals spatial distribution

Table 2 reveals that average concentration of Cu16.9 ± 12.9 mg/kg), Zn (49.0 ± 22.5 mg/kg), Cd (0.23 ± 0.24 mg/kg),i (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%) inhabahar Bay sediments is higher than corresponding concentra-ions in the local background sample. Metals distribution in theediments is demonstrated in Fig. 3 using a series of geochemicalaps produced for each metal. Fig. 3 indicates that Cu, Zn and Cd

oncentrations in Ch3, S1, T1, S9, S3 and S4 stations are clearly


igher. The highest Pb concentration (25.5 mg/kg) also occurs inh3 station. Maximum Ni, Cr, Co, V and Fe concentrations werebserved in the sediments of T3 and S9 stations which also displayhe highest clay size fraction.

Fig. 3. Spatial distribution of analyzed m

nd CEC in the sediments.

3.3. Sediment contamination assessment

Spatial variation of Igeo in the stations is represented by a seriesof maps produced for each metal (Fig. 4). As shown in Fig. 4, Cuconcentration in Ch3 station is strongly polluted and in S1 andS9 stations is moderately to strongly polluted. The sediments col-lected from Ch3 station are also unpolluted to moderately pollutedwith Pb. Zinc in the sediments of Ch3 and T1 stations is stronglypolluted 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, notonly metal pollution but also metal concentration, OM content and


clay size fraction of sediments decrease gradually from S9 stationin a NE direction. Hence, it is probable that the sediments in S8station and to a lesser extent sediments in S7 station are indirectlyaffected by the pollution in S9 station. Regarding Cd, S3 station is

etals in Chabahar Bay sediments.




f Igeo

msdSi

Fig. 4. Spatial variation o

oderately to strongly polluted. The S1, Ch3, S3, S4, S5, T1 and S9tations are located in Chabahar Bay semi-enclosed harbors which


ue to restricted water circulation, trap shipping wastes. The T3,9, S8, S3 and S4 stations display the highest Igeo values for Ni. Ast can be seen from Fig. 4, Cr, Co, V and Fe content in sediments

Fig. 5. Contamination degree variatio

classes in the sediments.

is classified in two Igeo classes as anthropogenic activity has noimpact on their concentrations.


Sediment contamination is illustrated in Fig. 5 by plottingcalculated Cd for Chabahar Bay stations. Fig. 5 reveals that most con-taminated stations (Ch3, S1 and S3) are located in SE of Chabahar

n in Chabahar Bay sediments.





Tab

le

2M

etal

s

con

cen

trat

ion

s

and

sele

cted

ph

ysic

o-ch

emic

al

pro

per

ties

of

Ch

abah

ar

Bay

sed

imen

ts.

Sam

pli

ng

stat

ion

s

Cu

(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

(cm

ol/k

g)

OM

(%)

San

d

(%)

Silt

(%)

Cla

y

(%)

Sed

imen

t ty

pe

S1

36.1

18.5

76.2

0.47

56.0

42.5

9.80

29.0

2.36

15.1

3.45

55.8

18.6

25.6

Cla

yey

san

dS2

12.9

9.49

35.8

0.14

47.8

34.6

8.20

24.0

1.75

7.80

2.30

82.1

10.6

7.30

San

dS3

21.8

12.8

63.9

0.88

65.3

45.6

10.9

28.0

2.40

22.2

5.86

72.5

13.1

14.4

Cla

yey

san

dS4

21.4

14.6

54.3

0.76

64.3

46.4

10.6

30.0

2.39

21.1

3.54

41.8

20.4

37.8

San

d

silt

clay

S5

12.6

11.0

40.3

0.12

57.0

38.9

9.60

24.0

2.03

21.6

3.13

26.5

19.7

53.8

San

dy

clay

S6

8.81

9.23

37.4

0.08

54.8

35.3

9.60

21.0

1.93

15.1

2.21

33.8

22.8

43.4

San

d

silt

clay

S7

10.6

10.2

40.8

0.09

61.4

39.4

11.0

23.0

2.14

9.30

2.33

49.3

15.2

35.5

Cla

yey

san

dS8

13.6

11.7

54.3

0.12

80.2

49.3

13.6

29.0

2.84

23.9

3.98

48.3

4.80

46.9

Cla

yey

san

dS9

29.0

12.5

73.7

0.13

85.1

52.8

13.8

31.0

2.88

26.1

5.03

6.20

18.8

75.0

Cla

yS1

0

6.19

8.46

28.0

0.07

40.6

27.3

8.20

19.0

1.54

8.94

2.52

13.0

73.9

13.1

Cla

yey

silt

S11

7.52

8.12

29.5

0.06

41.6

30.3

8.10

19.0

1.59

8.81

1.94

21.1

63.1

15.8

San

dy

silt

S12

12.4

11.9

28.7

0.12

45.4

29.4

8.00

18.0

1.57

8.16

2.30

87.8

6.10

6.10

San

dT3

17.6

21.2

60.6

0.08

88.1

54.4

15.3

33.0

2.92

27.3

1.94

5.90

14.9

79.2

Cla

yK

o1

4.82

9.81

20.6

0.08

27.9

26.5

7.60

17.0

1.27

10.0

1.46

15.4

74.1

10.5

San

dy

silt

Ch

3

56.2

25.5

87.8

0.38

52.1

38.8

9.50

27.0

2.21

13.6

2.80

50.7

19.7

29.6

Cla

yey

san

dT1

17.6

16.0

90.9

0.28

57.4

41.0

10.4

26.0

2.14

14.9

3.20

24.2

18.5

57.3

San

dy

clay

M1

11.3

21.8

43.0

0.11

56.9

40.1

10.0

27.0

2.31

5.89

1.28

12.8

70.3

16.9

Cla

yey

silt

A1

4.30

12.2

16.5

0.08

22.1

20.7

5.20

15.0

1.07

13.0

0.94

18.9

70.7

10.4

San

dy

silt

Ave

rage

16.9

13.6

49.0

0.23

55.8

38.5

9.97

24.4

2.07

15.2

2.79

37.0

30.9

32.1

–SD

12.9

5.05

22.5

0.24

17.5

9.31

2.44

5.29

0.54

6.89

1.26

25.6

25.8

23.0

–B

ackg

rou

nd

4.16

14.7

6.70

0.14

10.3

9.40

8.60

17.0

1.23

7.89

1.13

90.5

5.25

4.25

San

d

Fig. 6. Dendrogram of the metals, clay size fraction, OM content and CEC in thesediments.

Bay with contamination decreasing in a NW direction. The S9station, located west of the bay, is as contaminated as SE stations.

3.4. Statistical analysis

Hierarchical cluster analysis was conducted to identify majorsource(s) of the metals in Chabahar Bay sediments (Fig. 6). ClusterA contains Ni, Cr, Co, V and Fe, probably contributed by geogenicsources. Moreover, CEC, clay size fraction and the metals occur inthe same cluster. Considering the low CEC in sediments and therole of OM in CEC, metals adsorption on clay minerals is proba-bly insignificant and Ni, Cr, Co, V and Fe are incorporated in thecrystalline 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 andnickel sulfide minerals. Discharge of river and seasonal streamsflowing on the northern weathered ophiolites of Makran moun-tains, and also oceanic crust weathering apparently release claysize fraction of metalliferous sediments into Oman Sea water. Afraction of the sediments is carried to coastal areas by waves, whilesome will deposit on Oman Sea bed. Sea bed sediments disturbancecan resuspend the clay size fraction in Oman Sea water. Accord-ing to annual mean global wind-induced upwelling maps (Xie andHsieh, 1995), upwelling velocity in Oman Sea is about 5–10 cm/day.Hence, suspended clay size fraction moves toward coastal areas andcontributes to the geogenic pollution of the metals in Chabahar Baysediments. Hamzeh et al. (2013) also reported that Ni and Cr pol-lution in sediments of three harbors along the Iranian Oman Seacoast comes from the ophiolitic units found in the northern Makranmountains. Moreover, de Mora et al. (2004) described that high con-centration of Ni in the sediments of southern coasts of Oman Seais contributed by ophiolites and metalliferous sediments of marineorigin.

Copper, Pb, Zn and Cd are present in cluster B reflecting simi-lar source(s) or geochemical properties. Organic matter also occursin this cluster indicating that OM is an important metal carrier.Numerous paint stains on sediments of the harbors indicate that atleast some of the metals pollution come from antifouling and seavessel 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) andtheir high total concentration is also reported in soils and dustscontaminated by marine antifouling paints (Turner et al., 2009).




lts for

AZ2wp

gcctpSaiiA

ctpcb(ssr

TS

Fig. 7. Hierarchical cluster analysis resu

ntifouling paints are most identified major sources of Cu andn pollution in marine environments (Singh and Turner, 2009a,009b; Jones and Turner, 2010). Furthermore, copper-containingood preservatives applied in marine environments constitute aotential source of Cu (Singhasemanon et al., 2009).

Hierarchical cluster analysis was also carried out to distin-uish anthropogenic impacted stations. The 18 sampling sites werelustered into two different groups depending upon their metaloncentration, OM, clay size fraction and CEC (Fig. 7). Sedimentshat appear in the same group, either have similar physico-chemicalroperties or anthropogenic/natural pollution source. The S1, S3,4, S8, S9, Ch3 and T1 stations in cluster B are probably affected bynthropogenic activity. Similar Ni, Cr, Co, V and Fe content and CECn sediments of T3 station with those in S8 and S9 stations, put T3n cluster B. Other sampling stations which are grouped in cluster

probably are not impacted by anthropogenic pollution.Distribution of the metals concentration and the physico-

hemical parameters in the sediment samples is non-normal,herefore Spearman’s correlation coefficient was performed to sup-ort HCA results and determine the most important geochemicalarriers of the metals. In general, based on Table 3 the correlationsetween 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),o these metals in the sediments may share the same geogenicource. Clay size fraction and CEC show significant positive cor-elations (r ≥ 0.68 and 0.67, respectively) with Ni, Cr, Co, V and

able 3pearman’s correlation among selected physico-chemical properties and the metals in th

Elements Clay CEC OM Fe V Co

Cu 0.46 0.54* 0.74** 0.80** 0.84** 0.6Pb 0.33 0.31 0.21 0.62** 0.63** 0.4Zn 0.65** 0.54* 0.65** 0.82** 0.82** 0.7Cd 0.08 0.30 0.59* 0.39 0.44 0.2Ni 0.78** 0.73** 0.59** 0.92** 0.87** 0.9Cr 0.76** 0.72** 0.61** 0.98** 0.96** 0.9Co 0.78** 0.67** 0.55* 0.91** 0.86** 1.0V 0.68** 0.67** 0.61** 0.97** 1.00Fe 0.70** 0.69** 0.60** 1.00OM 0.38 0.58* 1.00CEC 0.74** 1.00Clay 1.00

* Correlation is significant at the 0.05 level (two-tailed).** Correlation is significant at the 0.01 level (two-tailed).

18 sampling stations of Chabahar Bay.

Fe which is in agreement with the HCA results. Percentage of claysize fraction in S3 and S4 stations is low, while Ni concentration inthe 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, OMand anthropogenic metals probably reflecting the importance ofFe oxy-hydroxides and OM in the metals mobility. Lack of such asignificant correlation for OM–Pb and Fe–Cd indicates that Pb andCd mobility is controlled by Fe oxy-hydroxides and OM, respec-tively (Table 3). Furthermore, average pH of 8.12 at Chabahar Bayis the reason for negative charge of Fe oxy-hydroxides which playan essential role in the metals adsorption. These results agree withthose 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 extractedpercentage of the metals in the chemical fractions of Chabahar Baysediments are shown in Fig. 8. Since the concentration of Cd indifferent chemical fractions is below the detection limit, fraction-ation of this metal is ignored. The figure reveals that the highestCu, Pb and Zn percentages in the majority of the samples occur


in the reducible fraction, reflecting their potential bioavailabilityin the sediments. According to Sundaray et al. (2011), colloids ofFe–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

e sediments.

Cr Ni Cd Zn Pb Cu

0** 0.75** 0.65** 0.69** 0.90** 0.68** 1.002 0.56* 0.45 0.55* 0.72** 1.002** 0.80** 0.72** 0.65** 1.003 0.37 0.26 1.007** 0.96** 1.005** 1.000


Please cite this article in press as: Keshavarzi, B., et al., A GIS-based approach for detecting pollution sources andbioavailability 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



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.




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Fig. 9. ICFs and GCFs of Cu, Pb, Zn

ighest percentage (over 58.7% on average) being in the residualraction. The results indicate that Ni, Cr, Co, V and Fe are stronglyssociated with the crystalline phases in the sediments. Hamzeht al. (2013) suggested clinochlore and chromite as important min-ralogical sources of Ni and Cr in sediments of the Iranian Oman Seaoast. Bioavailability of the studied metals considering their totaloncentration is as follows:

.5.1. CopperIt is obvious from Fig. 8 that the highest Cu concentration occurs

n the sediments of Ch3 and S9 stations (56.2 and 29.0 mg/kg,espectively) which indicate high Cu percentage (50.8 and 79.5%,espectively) in the reducible fraction. Among the other three sta-ions, Cu bioavailability in the sediments of T1 station is higherecause of high Cu total concentration and extracted Cu percentage66.4%) in the first two fractions.

.5.2. LeadNot only the highest Pb concentration is seen in the sediments of

h3 station but as already mentioned, it is the only station impactedy Pb pollution. Hence, the highest Pb bioavailability is expected,ecause the highest extracted Pb (63.9%) occurs in the reducibleraction (Fig. 8).

.5.3. ZincTotal Zn concentration in T1 and Ch3 stations (90.9 and

7.8 mg/kg, respectively) is higher than that of S9 station73.7 mg/kg) but as in the sediments of S9 station, the majority


f Zn (54.3%) is bound to the acid soluble fraction (the most labileraction), Zn bioavailability is higher in this station (Fig. 8). In addi-ion, Zn bioavailability in T1 station is higher than Ch3 station dueo higher Zn percentage (17.2%) in the first fraction.

r, Co, V and Fe in the sediments.

3.5.4. Nickel, chromium, cobalt, vanadium and ironAccording 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 fractionindicating that the metals bioavailability is low regardless of theirtotal concentration.

The ICFs and GCFs of Cu, Pb, Zn, Ni, Cr, Co, V and Fe in ChababarBay sediments are depicted in Fig. 9. The highest Cu ICF occurs in S9and T3 stations (8.26 and 8.12, respectively), being insignificant inother stations. High ICF in T3 station is seemingly due to occurrenceof the highest Cu percentage (34.0%) in the oxidable fraction (theleast labile fraction). Moreover, Cu concentration in the sedimentsof 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 thisstation is not important. If one takes Cu concentration into consid-eration, risk of water body contamination by the metal in differentstations 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 stationsbeing 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 thesequential extraction analysis and reveal that Zn risk in stationsfollows 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, ICFof these metals is very low. Furthermore, as these metals share thesame 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, generallyspeaking, Cu, Pb and Zn which come from anthropogenic sources,pose the highest risk for the bay contamination from the sediments.


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The GCF values computed by summing the metals ICF in the sed-ments of each station follow the order of S9 > Ch3 > T1 > M1 > T3.ccording to Luoma and Rainbow (2008) metals tend to accumu-

ate in sediments and contamination tends to be localized in aotspot near the input, and then gradually disperses regionally in

ower concentrations. Hence, those stations, especially S9, Ch3 and1, located in the area of anthropogenic activity pose the highestotential risk for Chabahar Bay biota (Fig. 9).

. Conclusion

High OM content in Chabahar Bay sediments is most likely theesult of fuel and sewage discharge from fishing vessels along withischarge of fishing leftovers. Geo-accumulation index results indi-ate that Ch3 is the most polluted station with Cu and Pb, whilen in Ch3 and T1 stations is strongly polluted. Also sediments of3 station are moderately to strongly polluted with Cd. The sed-ments collected from T3, S9, S8, S3 and S4 stations display theighest Ni Igeo. Chabahar Bay sediments are classified as unpollutedo moderately polluted with respect to Cr, Co, V and Fe. Significantorrelations among OM, Fe, Cu, Pb, Zn and Cd possibly reflect themportant role of Fe oxy-hydroxides and OM in the metals mobil-ty. The results of this investigation revealed that Cu, Pb, Zn and Cd

ostly come from anthropogenic sources (antifouling and sea ves-el paints), while Ni, Cr, Co, V and Fe probably come from geogenicources (ophiolites and deep sea sediments). Copper, Pb and Zn areostly extracted in the reducible fraction reflecting the fact that

hese metals are potentially bioavailable in the sediments. More-ver, substantial percentages of Ni, Cr, Co, V and Fe occur in theesidual fraction reflecting their immobility under natural condi-ions. Average ICFs reveals that Chabahar Bay sediments pose theighest environmental threat by Cu, Pb and Zn. Calculated GCF

ndicates that S9, Ch3 and T1 stations bear the highest potentialisk for Chabahar Bay biota. Urgent environmental measures areecommended to avoid future undesirable consequences.

cknowledgements

This research was supported by “Shiraz University Medical Geol-gy Research Center” to whom the authors are indebted. Theuthors would also like to express their gratitude to the author-ty and employees of Iranian National Institute for Oceanographynd Atmospheric Science (INIOAS) for their assistance in the field.hanks are extended to two anonymous reviewers and the asso-iate editor whose constructive comments has greatly improvedhe quality of the paper.

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a gis-based approach for detecting pollution sources and bioavailability of metals in coastal and...

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