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Oct 19, 2012 - Abstract This investigation presents the temporal and spatial distribution of heavy metals (As, Cd, Cr, Cu, Ni, Pb,. Hg, and Zn), in water and in ...
Environ Earth Sci (2013) 69:2013–2025 DOI 10.1007/s12665-012-2038-8

ORIGINAL ARTICLE

Heavy metal contamination in water and sediment of the Port Klang coastal area, Selangor, Malaysia Seyedeh Belin Tavakoly Sany • Aishah Salleh Abdul Halim Sulaiman • A. Sasekumar • Majid Rezayi • Ghazaleh Monazami Tehrani



Received: 17 January 2012 / Accepted: 1 October 2012 / Published online: 19 October 2012 Ó Springer-Verlag Berlin Heidelberg 2012

Abstract This investigation presents the temporal and spatial distribution of heavy metals (As, Cd, Cr, Cu, Ni, Pb, Hg, and Zn), in water and in sediments of Port Klang, Malaysia. Water and sediment samples were collected from 21 stations at 3-month intervals, and contamination factor ðCf Þ and contamination degree ðCd Þ were calculated to estimate the contamination status at the sampling stations. Cluster analysis was used to classify the stations based on the contamination sources. Results show that concentrations of As, Cd, Hg, and Pb in sediment and As, Cd, Hg, Pb, Cr, and Zn in water were significantly higher than the background values at which these metals are considered hazardous. The main sources of heavy metal contamination in Port Klang were industrial wastewater and port activities. Keywords Heavy metals  Water and sediment pollution  Port Klang  Malaysia

S. B. T. Sany (&)  A. Salleh  A. H. Sulaiman  A. Sasekumar  G. M. Tehrani Institute of Biological Sciences, University of Malaya, 50603 Kuala Lumpur, Malaysia e-mail: [email protected] S. B. T. Sany  M. Rezayi Food Science and Technology Research Institute, ACECR Mashhad Branch, Mashhad, Iran M. Rezayi School of Chemical Sciences and Food Technology, Faculty of Science and Technology, Universiti Kebangsaan Malaysia, 43600 Bangi, Selangor, Malaysia

Introduction The main goal of most contamination-oriented studies of water and sediments is to describe or assess existing conditions and to estimate whether the aquatic systems have been anthropogenically or naturally affected. Low concentrations of many elements occur naturally in the earth’s crust and are mined widely for use. Great amounts of several elements like toxic heavy metals (cadmium, lead, chromium and mercury) are discharged into marine environments as contaminants by anthropogenic activities (Gao et al. 2009; Nduka and Orisakwe 2011; Kassim et al. 2011). Historically, water and sediment quality have been monitored based on the collection and laboratory analysis of samples. Several researches showed that concentrations of heavy metals in sediment are far higher than the concentration of dissolved metals in the water bodies (Sultan and Shazili 2009). Marine sediment acts as both sink and source for heavy metals (Nobi et al. 2010; Gao et al. 2009; Gleyzes et al. 2002). The main pathways of heavy metals partitioning include adsorption, complexation, precipitation and biological uptake. Adsorption is usually the predominant process, because metals have strong affinities for iron and manganese hydroxides, particulate organic matter, and a lesser extent to clay minerals. Consequently, metals tend to accumulate in bottom sediments (Nobi et al. 2010; He et al. 2009; Rezayi et al. 2011). In aquatic systems, monitoring of the dissolved phase is not sufficient to evaluate distribution, concentration, bioaccumulation, and availability of these elements. It is necessary to estimate heavy metal concentrations in the dissolved and solid phases to monitor accurately the metal contamination in temporal and spatial scales. Heavy metal cycling in the marine environment is a serious problem as these metals are stable and a majority of them have toxic

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effects on living organisms (Nobi et al. 2010; He et al. 2009; Pekey 2006; Ismail and Beddri 2009). Bioavailability, mobility, and toxicity of metals depend on their specific chemical form or binding, which are changed by several physical and chemical factors, such as pH, temperature, redox potential, and organic ligand concentrations. These factors can convert metals from a solid phase to a liquid phase and sometimes cause pollution of surrounding water bodies (Sahuquillo et al. 2003; Nobi et al. 2010). The Port Klang is located in the west coast of Peninsular Malaysia, in the narrow Klang Strait; this area is important for fisheries, tourism, navigation, and transportation. After 1981, Klang Strait experienced rapid commercial and industrial development, which caused an increase in population, leading to contamination and deterioration of the marine environment quality. This rapid deterioration of the Port Klang marine environment drew international attention. Thus, several regulations, guidelines and international agreements were ratified by research organizations (Association of Southeast Asian Nations and Department of Environment) to reduce and remedy contamination caused by several anthropogenic activities, such as harbors, industrials sites, and tourism, that released high amounts of contaminants into the marine environment. Nevertheless, the current information on concentration of contaminants in Port Klang’s environment is inadequate. The major objectives of this study are to estimate the concentration levels of metals including As, Cu, Cr, Cd, Ni, Pb, Hg and Zn, in the surface waters and sediments, and to provide baseline data of these metals to assess the responses of the Port Klang marine environment to anthropogenic pollution in future.

Materials and methods Study area and sample collection The Klang Strait covers an area of about 573 km2 and is located in the western tropical coastal region (03°00 N to 101°240 E) of Malaysia (Fig. 1). This port is divided into three subsidiary commercial ports (North, South, and West Port) that are sheltered by surrounding mangrove forests. Several notable activities in this area include farming, industrial factories (palm oil, cement, food, and electrical), and shipping. Klang Strait is located within the tropics experiencing two seasons within the year, the northeast (November to March) and the southeast monsoons (April to October) (Yap 2005). Heavy rainfall, annual flooding and high river flows are commonly experienced during the northeast monsoon or wet season, while dry periods occur later during the season. The mean annual water temperature is 30.04 °C, whereas

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the mean salinity has been reported to be 30.25 %. The annual mean surface and bottom pH values vary between 7.58 and 8.25, and the mean surface dissolved oxygen (DO) was recorded as 5.38 mg/l (Yap 2005). This area is marked by a semi-diurnal tide, which ranges from 2 m during neaps to 5.5 m during spring (Chong et al. 1990). Assessment of the heavy metal status in Klang Strait coastal water is a difficult task due to the great variability in environment conditions. This area is affected extensively by nonpoint sources, different depth, tidal condition and strong marine current, due to the northeast monsoon. These limitations have effect on metals concentration, although the sediment situation in this area is independent of tidal influence (Yap 2005). Several concepts have been used to reduce the impacts of these limitations, such as increasing number of stations, temporal assessment, and multiple sediment samplings during the north and south monsoon. Sediment samples were collected from November 2009 to October 2010 in 21 locations at the three subsidiary ports and this included six stations in North Port, six stations in South Port, and nine stations in West Port. These stations were arranged into three parallel transects from the coastline at three different distances (Fig. 1). A multi-parameter probe (YSI 556 MPS) was used to measure physical parameters namely, temperature, salinity, dissolved oxygen and pH from the surface water layer at a depth of 50 cm (Table 1). The samples were collected every 3 months in triplicate from 2 cm depth of the sediment during low tides. Polyethylene bags were used to store the sediment samples, which were kept in an icebox at 4 °C to reduce biochemical reactions. In the laboratory, the sediment samples were kept in a freezer at -20 °C until further analysis. The water samples were collected from surface water and stored in 500 ml polyethylene bottles that were pre-cleaned with deionized water and rinsed with ambient water before collection of the samples. Water samples were filtered through 0.45 lm millipore filters and acidified to pH \ 2 using concentrated nitric acid, and then stored in the dark at 4 °C. The metal concentrations were measured by ICP-MS. Analytical procedures Sediment samples were oven dried (60 °C) over the night, and passed through a 2 mm mesh sieve to remove coarser particles. The sediment granulometry was analyzed using a multi-wavelength particle size analyzer (model LS 13 320) from Beckman Coulter company. The percentages of three fractions of grain sizes were estimated: Clay (\2 lm), silt (2 lm \ size \ 64 lm) and sand ([64 lm). A carbon analyzer (Horiba Model 8210) was used to estimate the total organic carbon (TOC) following the specific procedure of Fang and Hong (1999). About 0.5 g of the dried sediment

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Fig. 1 Location of sampling stations in west coastal water of Malaysia

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Table 1 The mean concentration of physicochemical parameters during sampling periods Site

Description of stations

Code of Station

Fine fraction (%)

Sand (%)

TOC %

Depth(m)

Salinity (%)

pH

DO (mg l-1)

T (°C)

North Port

Liquid berth line

NL100

58.20

41.79

12.49

14.30

30.15

8.05

6.23

30.27

Remote

NL700

49.63

50.36

10.13

20.5

30.81

8.00

6.26

30.25

Mangrove

NL1500

73.77

26.22

17.04

10.3

31.24

8.09

6.10

30.29

Container berths

NC100

59.78

40.21

11.41

13.5

30.81

8.08

6.22

30.09

Remote

NC700

50.89

49.10

10.08

21.6

31.02

8.02

6.29

30.19

Mangrove

NC1500

65.19

34.80

14.71

11.2

31.36

8.11

6.04

30.25

Cement berth and industrial outlets Remote

WC100 WC500

53.57 45.96

46.42 54.03

10.24 7.74

12.5 19.5

30.86 30.98

8.09 8.01

6.09 6.33

30.08 30.17

West Port

South Port

Mangrove

WC1000

63.42

36.57

11.98

7.8

30.86

8.07

5.86

30.16

Liquid berth and industrial outlets

WL100

56.33

43.66

9.14

13.3

30.44

8.04

6.20

30.06

Remote

WL500

41.10

58.89

7.55

20.3

30.58

8.00

6.27

30.14

Mangrove

WL1000

70.81

29.18

12.76

8.8

30.75

8.04

6.07

30.06

Container berths

WT100

52.31

47.68

10.63

15.5

30.51

7.97

6.28

29.94

Remote

WT500

50.69

49.30

10.15

21.11

30.63

7.96

6.38

30.16

Mangrove

WT1000

70.36

29.63

15.49

6.8

30.77

8.01

6.26

30.15

Mouth of Klang River

SK100

95.39

4.60

22.65

7.5

26.10

7.98

5.51

29.79

Mouth of Klang River

SK1000

93.16

6.83

21.55

10.5

26.12

7.99

5.50

29.99

Semi-urban

SK2000

64.69

35.30

15.59

12.4

30.11

8.05

6.05

30.02

Liquid berth

SL100

69.50

30.49

13.79

10.3

29.45

8.09

5.82

30.10

Industrial

SL1000

69.72

30.27

14.91

11.3

29.54

8.09

5.83

30.10

Mangrove

SL2000

57.73

42.26

11.89

10.4

30.50

8.03

6.19

30.26

was digested in 9 ml nitric acid (HNO3), 3 ml hydrofluoric acid (HF) and 3 ml hydrochloric acid (HCl) in a teflon vessel, and heated in a microwave. After cooling, 18 ml of 5 % boric acid was added to the vessel content to remove the fluoride residue. The vessel content was centrifuged, followed by filtration into 50 ml volumetric flasks, and volume was brought to 50 ml by the double deionized water for measuring the heavy metals (Yap 2005). Heavy metals (As, Cd, Cr, Cu, Ni, Pb, and Zn) were measured by plasma mass spectrometry (ICP-MS) at the department of chemistry and geology of the University of Malaya. Most of the metals measured had levels above detectable limits. ICP-MS was calibrated by external standard solutions to measure metals and the calibration was improved using Re and In as internal standards. Stock reference solutions of 1000 mg/l were diluted to prepare working standards and the matrix matched with similar acidity, both procedures being important to make various concentration ranges. The entire chemical compound used had the actual quality and soap was applied to wash and rinse the crystal material and teflon bottles prior to analysis. Laboratory blanks, field duplicates, and standard reference materials (SRM) 2702 were applied to improve quality assurance during laboratory analysis. SRM 2702 is a natural standard reference of inorganic material collected from marine sediment with the certified

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concentration. In this study, the percentage of recovery varied between 91 and 104. The standard methods indicated warning limits for matrix spike recoveries from 87 to 113 %; thus, the range of recovery was reasonable in this study (EPA 1996; Ilander and Va¨isa¨nen 2007). Potential contamination was detected by reagent blanks, during the analytical and digestion procedure. Contamination factor and contamination degree To describe the contamination of a toxic compound, a contamination factor ðCfi Þ was defined according to Eqs. 1 and 2 (IDEM 2002; Parris et al. 1998; Schantz et al. 2005). n X C0i  1 ð1Þ Cfi ¼ Cfi i¼1 Cd ¼

n X

Cfi :

ð2Þ

i¼1 i Where, Cfi = the contamination factor, C01 = the average content of the compound in question (i) from surface sediment (0–1 cm) at the accumulation area. The value should be estimated in lg g-1 ds (ppm), Cni = the background value of the compound, n = the number of heavy metals, Cd = the contamination degree

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There are several approaches to estimate an accurate natural background level in all projects. This discussion can be treated in different methods: one is to use a general geological reference value such as an element’s concentration in the earth crust, which was introduced by Turekian and Wedepohl in 1961. The other way is to use data older than 10 years as equivalent to pre-industrial or precivilization values. In the first method, all local variations are ignored, and in the second method, all local differences are emphasized. Hakanson (1980) proposed a method to estimate a natural background value based on the second approach. In this study, the background value for sediment was measured based on the Eq. 3 because there were previous data of sediment quality in west coast area of Peninsular Malaysia from 1992 until 2006. Water quality was assessed based on marine water background value presented by Hakanson (1980). Cni ¼ x þ sx :

ð3Þ

Where, Cni is the natural background value, x is the mean of pre-industrial data or old previous studies, and sx is one (1) standard deviation. This contamination factor ranged as low ðCfi \1Þ, moderate ð1  Cfi \3Þ, considerable ð3  Cfi \6Þ, and very high ðCfi  6Þ. The contamination degree ðCd Þwas estimated based on the sum of all contamination factors. The specific terminology is used to describe the contamination degree of sediment—low contamination degree ðCd \8Þ, moderate contamination degree ð8  Cd \16Þ, considerable contamination degree ð16  Cd \32Þ, and a very high contamination degree ðCfi  32Þ. Microsoft Excel and SPSS 17 software were used to perform statistical analyses. The two-way ANOVA test (level of significance is 0.05) was employed to understand the variation of the heavy metal concentration with respect to different seasons and stations. Kendall’s tau-b correlation analysis was constructed to understand the relationship between heavy metals in sediment and other parameters. Standard deviation was estimated to evaluate variation or dispersion from the average of physicochemical parameters based on repeating the analyses 16 times over the four separate months. Results and discussion Some physicochemical parameters of water and surface sediment have been determined to evaluate a possible relationship between these parameters (Table 1). The pH is a main indicator to assess water quality and pollution in marine and coastal systems. According to the guidelines, the acceptable range for pH is 6.5–8.5. In this study, pH ranged 7.96–8.11, which indicates the alkaline nature of the Port Klang coastal waters where mainly influenced by

Klang River discharge and land based runoff. Temperature and dissolved oxygen ranged 29.79–30.29 °C and 5.50–33 mg l-1, respectively. There were no significant differences in temperature and dissolved oxygen at all stations. Salinity ranged between 26.10 and 31.36 %, the lowest salinity value was recorded at stations SK100 and SK1000, because of their location close to the fresh water flow of the Klang River. In the present study, according to reports of the Malaysian Metrological Service (MMS) between 2009 and 2011, the monthly average rainfall ranged from a minimum of 190 mm in August to a maximum of 410 mm in April and May; the average was 266.91 mm. November, April and May were the months with the greatest number of raining days (400–410 mm). Other researchers have reported that the river discharge at Klang Strait is highly correlated with rainfall patterns, and as expected, the maximum river discharges were measured in November 2009 and April and May 2010. Analysis of sediment grain size demonstrated that finegrained sediment (\64 lm) predominated at almost all stations (41.1–95.39 %). The maximum of fine fractions were measured at stations close to the mangrove line and mouth of Klang River, while the highest portion of the sand fraction was recorded at stations WC500 (54.03) and WL500 (58.89). According to the two-way ANOVA, there are significant differences (p \ 0.05, df = 21, f = 8.82, sig = 0.00) between distribution of fine-grained sediment at different stations; however, there is no significant difference (p \ 0.05, df = 3, f = 0.82, sig = 0.66) between its concentration at different seasons. Several factors affect grain size variation in a marine system, such as sediment transportation and sedimentary process (Bowen 1966; Hakanson 1980). In this study, areas with high percentage of fine sediment were found near the mangrove forest. This may be due to the land-based runoff and sedimentary process of mangrove forests. Several studies showed that mangrove forests can increase the suspended solid deposition by decreasing the water dynamic energy and provide enough time for deposition of fine grain sediment (Qin et al. 1989). Moreover, the high percentage of fine-grained sediment was at stations close to the Klang River, which is good evidence to confirm the effect of the river transport mode on the distribution of sediment particles. The TOC content of sediment ranged between 5.35 and 24.88 % and its concentrations were significantly different either at stations (p \ 0.05, df = 21, f = 10.10, sig = 0.00) or in seasons (p \ 0.05, df = 3, f = 3.62, sig = 0.018). The distribution of TOC follows the same pattern as fine-grained sediment in most parts of Port Klang with high concentrations of TOC recorded at stations SK100 and SK1000 near the mouth of Klang River and the

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Table 2 The mean and standard deviation (±) concentrations of the heavy metals in the surface water during sampling periods (lg l-1) STATION

As

Cu

Cr 3.5 ± 2.42

Cd

Ni

Pb

Hg

Zn

NL100

15.8 ± 11.4

2.88 ± 1.61

0.44 ± 0.1

1.86 ± 0.9

3.54 ± 0.8

0.01 ± 0.001

49.5 ± 30.3

NL700

13.3 ± 9.5

1.71 ± 0.66

2.83 ± 1.5

0.44 ± 0.1

1.61 ± 0.7

3.79 ± 0.9

0.01 ± 0.001

45.0 ± 25.5

NL1500

15.3 ± 7.89

1.63 ± 0.71

2.41 ± 1.6

0.42 ± 0.2

1.54 ± 0.7

3.96 ± 0.5

0.01 ± 0.001

44.1 ± 24.8

NC100

20.0 ± 14.9

2.53 ± 1.37

4.28 ± 2.5

0.85 ± 0.6

2.47 ± 0.9

2.32 ± 0.7

0.01 ± 0.001

59.6 ± 40.1

NC500

18.6 ± 14.3

1.19 ± 0.63

3.74 ± 2.3

0.36 ± 0.2

1.83 ± 0.8

1.64 ± 0.8

0.01 ± 0.001

57.7 ± 37.9

NC1000

21.6 ± 13.2

1.54 ± 1.03

3.41 ± 2.1

0.33 ± 0.2

1.79 ± 0.9

2.01 ± 0.7

0.01 ± 0.001

57.5 ± 38.9

WC100

28.0 ± 10.0

2.63 ± 2.26

3.89 ± 2.9

0.41 ± 0.1

2.29 ± 1.4

5.14 ± 0.6

0.03 ± 0.01

47.5 ± 28.2

WC500

32.4 ± 24.2

1.67 ± 1.37

3.91 ± 2.3

0.33 ± 0.2

3.13 ± 2.3

3.56 ± 0.7

0.02 ± 0.01

26.0 ± 5.63

WC1000

23.4 ± 17.3

2.33 ± 1.07

3.44 ± 2.2

0.35 ± 0.2

1.58 ± 0.7

4.70 ± 2.7

0.02 ± 0.01

41.5 ± 19.6

WL100

32.6 ± 6.45

1.67 ± 1.37

5.82 ± 1.6

0.39 ± 0.3

2.29 ± 1.4

6.15 ± 1.3

0.04 ± 0.01

55.9 ± 9.76

WL500 WL1000

16.6 ± 2.20 27.0 ± 9.26

1.17 ± 0.94 2.96 ± 0.84

4.29 ± 1.9 3.91 ± 1.9

0.38 ± 0.2 0.470.3

1.17 ± 0.3 2.10 ± 0.9

3.58 ± 0.8 4.87 ± 1.1

0.03 ± 0.01 0.02 ± 0.01

56.9 ± 17.1 48.7 ± 19.3

WT100

23.2 ± 16.1

3.46 ± 1.48

6.37 ± 1.4

0.40 ± 0.1

2.38 ± 1.5

5.63 ± 1.6

0.04 ± 0.01

52.8 ± 34.9

WT500

35.6 ± 12.4

1.83 ± 1.53

5.33 ± 1.0

0.34 ± 0.2

2.29 ± 1.4

3.74 ± 1.8

0.04 ± 0.01

54.1 ± 29.4

WT1000

34.9 ± 12.7

2.83 ± 2.52

5.16 ± 0.9

0.79 ± 0.6

3.13 ± 2.2

2.92 ± 0.6

0.04 ± 0.01

SK100

46.7 ± 19.3

5.12 ± 1.99

7.24 ± 1.6

1.06 ± 0.3

4.62 ± 2.8

6.94 ± 1.3

0.06 ± 0.001

88.3 ± 31.4

55 ± 28.3

SK1000

47.7 ± 17.2

5.29 ± 1.50

7.33 ± 1.3

1.07 ± 0.4

5.42 ± 3.0

7.17 ± 1.1

0.06 ± 0.01

87.3 ± 31.1

SK2000

18.3 ± 12.4

2.46 ± 1.21

3.97 ± 1.2

0.39 ± 0.1

1.96 ± 1.0

3.27 ± 0.5

0.01 ± 0.001

50.3 ± 28.3

SL100

23.2 ± 6.82

3.29 ± 1.5

0.4 ± 0.1

2.87 ± 1.6

5.06 ± 0.9

0.03 ± 0.001

53 ± 25.1

SL1000

23.1 ± 6.92

2.79 ± 1.57

SL2000

15 ± 9.62

1.68 ± 0.86

5.1 ± 0.85 4.75 ± 0.9 3.9 ± 1.11

0.36 ± 1 0.35 ± 0.2

2.630.9 2.13 ± 1.2

4.61 ± 1.1

0.03 ± 0.01

2.87 ± 0.6

0.01 ± 0.001

54 ± 24.0 42.2 ± 18.4

Minimum

13.3 ± 9.5

1.67 ± 1.37

2.41 ± 1.6

0.33 ± 0.2

1.17 ± 0.3

1.64 ± 0.8

0.01 ± 0.001

26.0 ± 5.63

Maximum

47.7 ± 17.2

5.29 ± 1.50

7.33 ± 1.3

1.07 ± 0.4

5.42 ± 3.0

7.17 ± 1.1

0.06 ± 0.001

88.3 ± 31.4

lower percentage at stations WC500 and WL500. There was high correlation (0.716) between the TOC and finegrained sediment in study area. In November 2009, the TOC percentage increases with decreasing mean grain size because the fine particle size, particularly the clay colloid, has a high tendency to adsorb TOC. Spatial and temporal variation of heavy metals In water, the spatial variation of dissolved metals concentration during the sampling periods and the ranges of values recorded are given in Table 2. There was distinct temporal variation of heavy metals concentration during a year (Fig. 2). Figure 2 shows that all metals have high fluctuations during four samplings times in surface water, and the highest mean metal concentration was recorded in May 2010 and November 2009. The large value of standard deviation (Fig. 2 and Table 2) reflected a wide variation of dissolved metals concentration in temporal and spatial scales in a two-way ANOVA test (Woodroffe 1992; Wolanski et al. 1992; Furukawa et al. 1997; Kathiresan 2003; Cunha-Lignon et al. 2009). This test indicates significant temporal and spatial difference (p \ 0.05, sig = 0.00) in dissolved metal concentration in water.

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The mean concentrations of heavy metals in surface sediment are summarized in Table 3 with their ranges. Fig. 3 shows temporal variations of heavy metal concentrations during a year. The results showed that concentrations of metal in surface sediments were significantly (p \ 0.05, sig = 0.00) changed in temporal and spatial scale in a two-way ANOVA test. The metal concentration in both water and sediment showed a wide variation in temporal and spatial scale. This is attributed to differential derivation of these contaminations from lithogenic and anthropogenic sources such as untreated effluents discharges from industries, port activities and domestic sewage. The highest metal levels in sediment and water samples were measured in South Port, at the SK100 and SK1000 stations, which are close to the mouth of the Klang River. According to several studies, several contaminants such as untreated waste, municipal effluents, and industrial wastes are being discharged directly into the river (Yap 2005), thus the Klang River discharges can be considered a major route of contamination in the Port Klang. The water and sediment in South Port easily exchange with the polluted Klang River fresh water because the water currents in the vicinity of South Port are weak; therefore, there is enough time for the absorption of heavy metals by suspended

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Fig. 2 Temporal variation of the heavy metal in surface water lg l-1 (the grey bar shows the average concentration and the black line of each bar is standard deviation value)

solids for deposition on surface sediments. Heavy metals are not easily deposited in bottom sediments with strong water currents (Tam and Wong 2000). The high percentage of fine-grained sediment is the other main parameter, which causes increased metal concentrations in this study site. Fine-grained sediment is the main parameter which controls the concentration of heavy metals in the marine environment. Fine sediments adsorb heavy metals from water and have a significant capacity to retain heavy metals (Nduka and Orisakwe 2011). Some metals in this study have a significant positive correlation (0.4 \ r, p \ 0.01)

with fine particles, e.g., Cu (r = 0.447), Cd (0.406), Ni (0.432), Zn (0.493). The significant temporal variation of heavy metal concentration is probably due to seasonal fluctuations. This significant difference in metal concentration is unusual during this short period of sampling. However, several studies indicated that chemical properties of metal, water, and sediment, which are associated with other environmental factors such as atmospheric deposition, high dynamics of marine water, tidal and seasonal currents, and change of pollution load of anthropogenic source, can

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Table 3 The mean and standard deviation (±) concentrations of the heavy metals in the surface sediment during sampling periods (lg g-1) STATIONS

As

Cu

Cr

Cd

Ni

Pb

Hg

Zn

NL100

75.6 ± 27.51

17.43 ± 4.4

44.41 ± 5..04

0.79 ± 0.25

11.14 ± 4.50

58.59 ± 19.68

0.24 ± 0.07

52.3 ± 20.4

NL700

60.35 ± 23.11

13.60 ± 2.47

37.2 ± 8.2

0.67 ± 0.29

7.14 ± 2.22

47.5 ± 16.32

0.17 ± 0.05

35.2 ± 7.43

NL1500

76.2 ± 30.4

20.9 ± 5.7

44.5 ± 4.5

0.89 ± 0.29

10.5 ± 2.6

68.5 ± 20.6

0.20 ± 0.08

56.5 ± 19.7

NC100

38.05 ± 8.4

16.5 ± 2.8

39.9 ± 10.0

0.93 ± 0.3

12.4 ± 3.37

0.19 ± 0.06

46.2 ± 20.3

NC500

34.1 ± 7.5

12.4 ± 1.3

30.2 ± 9.1

0.80 ± 0.32

6.2 ± 2.04

47.3 ± 10.01

0.17 ± 0.04

42.2 ± 15.6

NC1000

48.5 ± 16.9

17.6 ± 4.9

37.6 ± 4.6

0.89 ± 0.28

11.8 ± 1.88

48.9 ± 11.4

0.19 ± 0.06

50.1 ± 18.68

WC100

35.8 ± 7.9

16.1 ± 4.7

58.6 ± 6.9

0.68 ± 0.33

11.6 ± 3.01

54.9 ± 7.8

0.25 ± 0.08

49.5 ± 13.3

WC500

51.6 ± 25.4

WC1000

68.13 ± 33.3

11.35 ± 2

47.06 ± 12.5

0.81 ± 0.33

8.8 ± 1.7

14.72 ± 2.5

48.91 ± 10.2

0.89 ± 0.34

10.49 ± 2.5

53.24 ± 6.9

52.5 ± 13.8 51.31 ± 5.9

0.20 ± 0.05

36.4 ± 15.0

0.20 ± 0.05

37.2 ± 12.5

WL100

67.5 ± 32.28

13.96 ± 1.59

37.20 ± 7.16

0.28 ± 0.07

13.03 ± 3.4

57.71 ± 7.9

0.25 ± 0.09

37.32 ± 12.31

WL500 WL1000

47.7 ± 11.24 50.31 ± 5.53

13. ± 2.35 15.69 ± 3.79

36.08 ± 10.88 47.05 ± 8.60

0.28 ± 0.10 0.62 ± 0.43

12.44 ± 3.42 16.02 ± 3.97

54.07 ± 7.95 58.23 ± 6.72

0.30 ± 0.08 0.31 ± 0.07

32.8 ± 10 35.1 ± 11.16

WT100

94.24 ± 37.13

16.81 ± 2.64

60.56 ± 4.21

0.95 ± 0.49

13.84 ± 3.07

0.30 ± 0.09

49.8 ± 20.3

WT500

59.07 ± 14.02

12.1 ± 1.67

42.7 ± 5.51

0.73 ± 0.62

9.6 ± 2.3

WT1000

72.1 ± 19.89 53.46 ± 9.6

0.21 ± 0.02

33 ± 12.51

78.3 ± 33.6

17.6 ± 6.77

45.9 ± 5.26

1.26 ± 0.57

13.38 ± 1.40

71.55 ± 9.8

0.28 ± 0.05

40.02 ± 19.6

SK100

112.8 ± 19.16

40.6 ± 11.3

74.8 ± 8.32

1.55 ± 0.27

17.83 ± 5.68

85.92 ± 6.50

0.35 ± 0.05

126.7 ± 43.5

SK1000

106.01 ± 21.23

38.5 ± 10.4

1.4 ± 0.41

16.08 ± 4.46

126.9 ± 43.6

SK2000

42.38 ± 7.22

16.3 ± 1.7

SL100

67.8 ± 21.8

14.9 ± 2.37

SL1000

50.27 ± 7.87

19.03 ± 3.94

SL2000

40.2 ± 8.2

16.27 ± 2.26

Minimum

34.1 ± 7.5

Maximum

112.8 ± 19.16

40.6 ± 11.3 11.35 ± 2

68.3 ± 5.98

79.4 ± 13.4

0.32 ± 0.05

0.91 ± 0.10

9.80 ± 2

74.7 ± 13.1

0.22 ± 0.01

52.8 ± 13.5

0.84 ± 0.38

12.2 ± 3.93

50.8 ± 10.72

0.20 ± 0.05

52.15 ± 17.66

47.68 ± 7.05

0.89 ± 0.33

12.18 ± 2.29

68.21 ± 16.27

0.21 ± 0.06

53.9 ± 16.7

41.34 ± 3.8

0.57 ± 0.09

7.58 ± 2.36

52.4 ± 12.09

0.19 ± 0.001

47.57 ± 11.4

45.07 ± 4. 50 ± 10.03

74.8 ± 8.32

0.28 ± 0.07

30.2 ± 9.1

1.55 ± 0.27

cause this temporal variation in mobility, bioavailability and enrichment of heavy metals during a short time. For example, several studies recorded that in the rainy season (during monsoon), concentration of heavy metals in sediment is lower than in the dry season; this could be related to high disturbance of the sediment created by huge waves during monsoon. Rainwater causes increased mobility and dilution, which decrease heavy metal concentrations in sediment (Lim et al. 2006; Li et al. 2009). Moreover, during the rainy season most of pollutants load of anthropogenic activities including shipping and fishing decrease or stop in some locations. Subsequently, after this reduction of anthropogenic activities, the level of metals input by the vessels might be decreased leading to occurrence of low metals concentration in sediment. In dry season, by the increase of anthropogenic activities, metals input starts to increase. The sediment is more stable, leading metals level to rise up again (Zhang et al. 2010; Olubunmi and Olorunsola 2010; Aydin onen S et al. 2011). In this research, some metals (Cd, Ni, Zn, Hg, As and Cr) showed significant reduction in their concentration in sediment with increasing rainfall in November 2009 and May 2010 (Fig. 3). This implies that these metals are bound to the exchangeable phase of the minerals in the sediment and probably more easily influenced by dilution

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6.2 ± 2.04 17.83 ± 5.6

47.5 ± 16.32 85.92 ± 6.50

0.17 ± 0.05

32.8 ± 10

0.35 ± 0.05

126.9 ± 43.6

due to heavy rainfall and strong marine currents, which occur during the north-east monsoon and inter-monsoon periods. Likewise, this could be related to reduction of anthropogenic activities during this period. The concentration of Zn and Cu showed the significant increase in their concentration with increasing rainfall, it is suggested that these metals mainly originate from land-based runoff and river discharges in Klang Strait coastal water. In seawater, the highest concentration of all metals (except Hg) was synchronous with heavy rainfall in November 2009 and May 2010 (Fig. 2) because heavy rainfall causes increased land-based runoff and river discharges, which are polluted by several contaminants. Atmospheric deposition is another route for metals to enter the seawater as it can transport a large amount of chemicals for hundred of mile far from their place of origin (Zhang et al. 2010; Aydin onen S et al. 2011). Comparison with natural background values and standard guidelines of metals Table 4 summarizes the general mean metal concentration in Port Klang water in comparison with the standard guidelines and background values. The mean concentrations of all metals were lower than threshold levels stated

Environ Earth Sci (2013) 69:2013–2025

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Fig. 3 Temporal variation of the heavy metals in surface sediment lg l-1 (the grey bar shows the average concentration and the black line of each bar is standard deviation value)

in standard guidelines to regulate marine environmental quality and which protect marine water quality. Concentrations of Cd, As, Pb, Cr and Zn were far higher than the marine background values while other metal concentrations were lower than the background value. In sediment, concentrations of Cu, Cr, Ni, and Zn were lower than thresholds of standard guideline and

background values (Table 5). Concentrations of Cd, Pb and Hg were higher than in background value and TEL (effect range low) in sediment and showed enrichment of metals in surface sediment, which was far higher than those thresholds in sediment. In general, the levels of As, Cd, Cr, Pb, and Zn exceeded their marine background values in sea water and

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Environ Earth Sci (2013) 69:2013–2025

Table 4 Nature concentration and guidelines levels of metals in seawater described in the literature Concentration of heavy metal (lg l-1)

As

Cu

Cr

Cd

Ni

Pb

Hg

Zn

The mean concentration of heavy metals in this study

24.7

2.51

8.77

0.48

2.39

8

0.02

52.9

CMC

69

4.8

1,100

40

74

210

1.8

90

CCC (Nduka and Orisakwe 2011; Rezayi et al. 2012)

36

3.1

50

8.8

8.2

8.1

0.94

81

3

0.05

0.11

5.4

0.3

0.03

10

Nature concentration of marine water (EPA 2002)

3

CMC criteria maximum concentration CCC criteria continuous concentration Table 5 Comparison of heavy metals concentration in the Port Klang with back ground value and sediment quality guidelines (SQG) Concentration of heavy metal (lg g-1)

As

Cu

Cr

Cd

Pb

Ni

Hg

Zn

The mean concentration of heavy metal in this study

60.36

17.43

46.4

0.826

59.45

11.44

0.23

51.05

Heavy metals Back ground value in the Port Klang (Yap 2005)

18.79

23.21

53.71

0.186

39.8

32.77

0.08

141.22

7.24

18.7

52

0.68

30.2

15.9

0.13

124

108

160

4.2

112

42.8

0.7

271

SQG-based (MacDonal 1994) TEL (effect range Low) PEL(effect range medium)

41.6

Table 6 Mean value of the contamination factor Cf and contamination degree Cd in the surface sediment

Table 7 Mean value of the contamination factor Cf and contamination degree Cd in the surface water

Stations

As

Cu

Cr

Cd

Ni

Pb

Hg

Zn

Cdvalue

POINT

As

Cu

NL100

4.03

0.22

0.84

4.23

0.34

1.47

3.04

0.37

14.54

NL100

6

0.96

NL700

3.21

0.21

0.7

3.61

0.22

1.2

2.18

0.25

11.58

NL700

4.45

0.57

NL1500

4.06

0.21

0.84

4.81

0.32

1.72

2.56

0.4

14.92

NL1500

5.12

NC100

2.02

0.19

0.75

5.02

0.38

1.34

2.4

0.33

12.43

NC100

NC500

1.82

0.16

0.57

4.28

0.19

1.19

2.16

0.3

10.67

NC1000

2.58

0.22

0.71

4.78

0.36

1.23

2.43

0.36

12.67

WC100

1.91

0.25

1.1

3.68

0.36

1.38

3.19

0.35

WC500

2.75

0.2

0.89

4.34

0.27

1.32

2.52

WC1000

3.63

0.2

0.92

4.81

0.32

1.29

WL100

3.59

0.21

0.7

1.49

0.4

1.45

WL500

2.54

0.24

0.68

1.53

0.38

WL1000

2.68

0.19

0.88

3.32

WT100

5.02

0.15

1.14

5.11

WT500

3.14

0.17

0.8

WT1000

4.17

0.16

SK100

6.21

0.21

SK1000

5.64

SK2000

Cd

Ni

Pb

Hg

Zn

Cdvalue

7.00

4.00

0.34

11.80

0.33

4.96

34.68

5.67

4.00

0.30

12.63

0.33

4.51

32.47

0.54

4.83

3.82

0.29

13.20

0.33

4.41

32.54

6.67

0.84

8.57

7.73

0.46

7.75

0.33

6.03

38.31

NC500

6.22

0.40

7.48

3.27

0.34

6.3

0.33

5.78

30

NC1000

7.22

0.51

6.83

3.00

0.33

6.72

0.33

5.75

30.70

12.22

WC100

9.34

0.88

7.78

3.73

0.42

17.15

1.00

4.75

45.05

0.26

12.55

WC500

10.81

0.56

7.83

3.00

0.58

11.88

0.67

2.61

37.94

2.51

0.26

13.94

WC1000

7.81

0.78

6.88

3.18

0.29

15.68

0.67

4.15

39.44

3.13

0.26

11.23

WL100

10.89

0.56

11.65

3.55

0.42

20.52

1.33

5.60

54.51

1.36

3.8

0.23

10.76

WL500

6

0.39

8.58

3.45

0.22

11.95

1.00

5.70

36.84

0.49

1.46

3.93

0.25

13.2

WL1000

9

0.99

7.83

4.27

0.39

16.25

0.67

4.88

44.27

0.42

1.81

3.72

0.35

17.72

WT100

7.74

1.15

12.75

3.64

1

18.78

1.33

5.28

51.12

3.94

0.29

1.34

2.66

0.23

12.57

WT500

11.87

0.61

10.67

3.09

0.42

12.47

0.92

5.42

45

0.86

6.78

0.41

1.8

3.5

0.28

17.96

WT1000

11.65

1

10.33

7.18

1

9.73

1.33

6.02

47.26

1.41

8.31

0.54

2.16

4.33

0.93

23.86

SK100

15.59

1.71

14.48

9.64

1

23.13

2.00

8.73

76.14

0.2

1.28

7.78

0.49

1.99

3.98

0.91

22.26

SK1000

15.39

1.76

14.67

9.73

1

23.90

2.00

8.73

77.39

2.26

0.14

0.85

4.87

0.3

1.88

2.71

0.37

13.38

SK2000

6.12

0.82

7.95

3.55

0.36

10.92

0.33

5.03

35.08

SL100

3.61

0.17

0.94

4.52

0.37

1.28

2.52

0.37

13.78

SL100

7.74

1.10

10.20

3.64

0.53

16.88

1.00

5.30

46.39

SL1000

2.68

0.21

0.9

4.79

0.37

1.71

2.67

0.38

13.71

SL1000

7.70

0.93

9.50

3.27

0.49

15.38

1.00

5.41

43.68

SL2000

2.14

0.18

0.78

3.08

0.23

1.32

2.38

0.34

10.45

SL2000

6

0.56

7.80

3.18

0.39

9.58

0.33

4.23

31.08

Minimum

1.82

0.2

0.57

1.49

0.19

1.19

2.18

0.25

10.45

Minimum

4.45

0.57

4.83

3

0.22

6.3

0.33

2.61

30

Maximum

6.21

0.24

1.41

8.31

0.54

2.16

4.33

0.93

23.86

Maximum

15.39

1.76

14.67

9.73

1

23.90

2.00

8.73

77.39

concentrations of As, Cd, Hg, and Pb measured were far higher than the sediment background values and TEL values. Metals released into Port Klang by some anthropogenic sources can be adsorbed on sediment particles. Moreover, As, Cd, and Hg are easily absorbed by plants and then enrich the sediment through the plant decomposition and

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Cr

nutrient cycling (NBO 2009; Lee et al. 2007; Ke Pan and Wang 2011). As, Cd, Pb and Hg originate mostly from industrial activities such as burning of fossil fuels, mining, cement manufacturing, paper and glass production and waste recycling (Zhang et al. 2010). Several industries such as palm oil, cement manufacturing, and oil/electrical-based power

Environ Earth Sci (2013) 69:2013–2025

generation release waste into Port Klang. Moreover, these metals might be released by atmospheric deposition, terrestrial runoffs, and tsunami sediment deposition, which are the main routes of metal into marine environment. Boat docking and corrosion of ships, organic insecticides (lead-arsenate), pesticides, and fertilizers applied in agriculture activities are other sources of pollution in the Port Klang coastal waters. Metal contamination level in water and sediment Contamination factor Cf and contamination degree Cd are applied to assess the state of conservation of an environment and to monitor its condition (Fishbein 1981; Jennings and Rainbow 1979; Cossa et al. 2010; Ke Pan and Wang 2011; Davis et al. 2009). Tables 6 and 7 show variations of contamination factor and contamination degree in water and sediment. In general, the highest values of contamination degree and contamination factor were estimated at stations SK100 and SK1000 in water and sediment. The Cf values for all metals follow this sequences in the sediment: Cu \ Ni \ Zn \ Cr \ Pb \ Hg \ As \ Cd while the sequence of Cf -value in water was Ni \ Hg \ Cu \ Cd \ Zn \ As \ Cr \ Pb. The differences between contamination factor sequences of water and sediment can be related to physicochemical parameters, which control the rate of adsorption and desorption of heavy metals. All heavy metals exist in surface waters in particulate colloidal, and dissolved phases, but the dissolved concentration are generally low. The particulate and colloidal metal can be found in hydroxides, silicates oxides, or adsorbed to silica, clay, or organic material. Adsorption removes the heavy metal from the water and stores the metal in the sediment. Desorption sends back the metal to the water column where recirculation and bio-assimilation may take place (Conti and Cecchetti 2001). Several researches showed that salinity, pH and solubility product (Ksp) of each metal are main parameters to control concentration of dissolved metals in water column. For example, increased metal concentration may be affected by increase in salinity, decrease in redox potential, and decrease in pH. Elevated salt concentrations create increased competition between cations and metals for binding sites (Nduka and Orisakwe 2011). This is typical in coastal regions and estuaries because of fluctuating river flow inputs and land-based discharges, as seen in Klang Strait coastal water. From this study, the acidity (pH) level seemed to have no effect on the metal concentration because the pH is within acceptable international standard for surface water. Fluctuation of salinity especially in South Port may have affected rate of adsorption and desorption of metals to and from sediments, and have caused the different sequence of contamination factor in water and sediment.

2023

In sediment, the Cf values for Cu, Cr, Ni, and Zn were less than 1 and were found at an unpolluted level at all stations. The contamination factor for Pb appeared moderate at all stations and Cf -value for Hg and As were on the borderline between moderately polluted to high level polluted. The contamination factor for Cd at all stations (except at stations WL100, WL500) was found between high and very highly polluted. Contamination degrees at the WT100, WT1000, SK100 and SK1000 stations were high whereas Cd -value indicates moderate pollution in other stations in the Port Klang. In water, based on the data shown in Table 7, the Cf value for Cu, Ni and Hg was lower than 1, and was observed in unpolluted levels at all stations except at the SK100, SK1000, WT100, and WT1000, which showed moderate pollution. Contamination factors for As, Cr, Cd, and Zn were between considerably polluted to very high level of pollution, while Pb was at a very highly polluted level at all stations. Contamination degrees for stations SL2000, NC1500, and NC700 showed considerable contamination whereas it was in a very high degree of contamination at other stations. In general, the highest contamination degree of all of the metals (except for Mn) were determined at South Port at stations SK100 and SK1000, which are parallel to the mouth of the Klang River, and at station WT100 around the container terminal in the West Port. As a result, the significant contamination degree showed that multiple sources greatly contributed to the contaminant loads in Klang Strait. These sources included industrial inflow, such as the palm oil, cement and food manufacturers that are located along the coastline of North and West Port, vessel-based discharges and Klang River. The contamination factor (Cf) also indicated that all of the metal concentration were influenced by anthropogenic inputs, especially very toxic elements, such as As, Cd, Hg and Pb, which were enriched at high levels at stations close to the berth line and the mouth of the Klang River.

Conclusion Heavy metal pollution in Port Klang water and sediments has increased because of the rapid industrialization and urbanization in recent decades. The study area was divided into different stations, with different metal contamination degrees. The results indicate that in South Port, stations are located in the riparian zone of the Klang River which predominantly flowed through South Port. It could be an indication that the high level contamination of metals in these stations comes from an anthropogenic source because high concentrations of metals were released continuously into the Klang River from chemical factories, urban

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effluents due to high density of human settlements, and agriculture activities. Moreover, in West Port, stations close to container terminal showed the high level of contamination because these stations are influenced by industrial discharge along the coastline, leakage or emissions of petrol due to busy marine transport, and atmospheric depositions. The study indicates that the potential contamination of Cd, As, Pb, and Hg were between moderate and high contamination in sediments while the rest of the metals were at an unpolluted level in the sediments at all stations. Metals with above normal concentrations in sediments can be considered as a serious threat to marine organisms and human health, especially As, because its concentration is significantly greater than effect range medium value. In addition, these data revealed that some elements such as As, Cd, Cr, Zn, and Pb, were enriched in water and their level of contamination varied between considerable and very high levels at all stations. In summary, the present study provides baseline data for interpretation of variations in heavy metal concentration in water and sediment and traces contamination routes of metal in the Port Klang. These data can also be used as a contribution to long-term monitoring of heavy metal pollutants in Port Klang. Acknowledgments This study was supported by the University Malaya Research grant (UMRG) with project number RG174/12SUS and by the University Malaya Postgraduate Research Grant (PPP).

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