Ecological pathways of heavy metal pollution in Solakli River ... - NOPR

3 downloads 0 Views 260KB Size Report
[Keywords: Black Sea, Sediment, Metal pollution, Anthropogenic effect, .... sediment quality guideline, ERL effect range low, ERM effect range median, TEL ...
Indian Journal of Geo-Marine Sciences Vol. 45(1), January, 2016, pp. 62-69

Ecological pathways of heavy metal pollution in Solakli River Basin (River Bed, Uzungol Lake and Estuary) sediment of southeastern Black Sea region, Turkey Koray OZSEKER*1 & Coskun ERUZ2 1

Karadeniz Technical University, Institute of Marine Sciences and Technology, 61080, Center-Trabzon/Turkey 2 Karadeniz Technical University, Faculty of Marine Sciences, 61530, Camburnu-Trabzon/Turkey [E-mail: [email protected]] Received 17 July 2014; revised 06 July 2015

In this study, the natural and anthropogenic heavy metal (Cr, Pb, Cu, Zn, Ni and As) pollution in Solakli river basin (river bed, Uzungol lake and estuary) investigated spatially and temporally. The highest metal concentrations were measured in the section influenced by estuary of Solakli. Highest metal concentrations were observed in winter. Metal concentrations were determined using an inductively coupled plasma-mass spectrometer (ICP-MS). Based upon the result of this study and according to Sediment Enrichment Factor (SEF), Pollution Load Index (PLI) and Geoaccumulation Index (IGEO) and SQG (Sediment Quality Guideline), Cu and As are the major contributor to toxicity in the Solakli river basin. [Keywords: Black Sea, Sediment, Metal pollution, Anthropogenic effect, Toxicity, SQG]

Introduction There are lots of factors such as human activities; water’s being in with air and soil ecological systems that cause water pollution, one of the most significant problems among environmental issues1. The most important factor causing inorganic pollution in water is heavy metals. Due to their toxic effects, they pose environmental significance2. Heavy metals are regarded as one of the main environmental pollutants in that they affect environmental quality substantially3. Heavy metals like chromium (Cr), lead (Pb), zinc (Zn), copper (Cu), nickel (Ni), arsenic (As), cadmium (Cd) are most important among the frequently observed contaminants in sediments. Both industrial activities and urbanization have greatly increased the heavy metal burden in the environment4. Heavy metals are transported to water sources by erosion, transportation of metals to seas via rivers, subaqueous and terrestrial volcanism, geological abrasion and disintegration, mining and processing, industrial wastes, and as metal entries formed by domestic wastes, urban flood waters and agricultural activities5. Heavy metal entries, which are encountered in natural wetlands out of control, accumulate not only in water mass but also in sediment structures of wetlands. Heavy metals, which can accumulate their present environment, have negative effects on living organisms. They join

food chain by being added to micro and macro livings present in water mass and sediment structure. Due to their inorganic structures, they are permanent in water environments. While improving natural water quality, their rise in water has bad effects on living organisms. The fact that heavy metals are seen in different regions owing to the moving effect of sediment structure shows the contaminating feature of sediment structure6. As sediment is an important place for heavy metals to accumulate, it is used to measure the metal pollution of aquatic environments7. Different methods have been employed to determine the pollution load in sediment. The most commonly used methods are the Sediment Enrichment Factor (SEF), Pollution Load Index (PLI) and Geoaccumulation Index (IGEO). The SEF is an effective tool for evaluating the magnitude of contaminants in the environment. SEF values computed relative to reference values associated with expected concentrations in un-impacted aquatic ecosystems. Although phenomena naturally occurring can introduce elevated metals concentrations, in most cases, high SEF values indicate an anthropogenic source of trace elements, mainly from activities such as industrialization, urbanization and deposition of industrial wastes8. PLI can provide the public useful information about the quality of the local and nearby environments. It can also provide valuable data to

OZSEKER AND ERUZ: ECOLOGICAL PATHWAYS OF HEAVY METAL POLLUTION IN SOLAKLI RIVER BASIN (RIVER BED, UZUNGOL LAKE AND ESTUARY) SEDIMENT OF SOUTHEASTERN BLACK SEA REGION, TURKEY

policy and decision makers who are developing regulations and policies to improve environmental conditions9. IGEO, which was evaluated following Muller’s proposal10, is a useful metric to quantify the degree of anthropogenic contamination and compare different metals that appear at different environmental concentrations in the sediment. In this study, the Sediment Quality Guideline (SQG), which is a tool for assessing the biological significance of individual chemicals, were used to determine ecological risk of Cu11. Goal of this research was to determine the environmental variation in the natural and anthropogenic heavy metal pollution found in sediments of the study area located along the Black Sea of Solakliriver basin, which has rich metallic mineral reserves and intense industrial activity in the region12. For many years, the river has received point and nonpoint source flows containing elevated heavy metal concentrations originating from various natural and anthropogenic outputs. Materials and Methods Sediment sampling was conducted in the Solakli river basin (river bed, Uzungol lake and estuary) inTrabzon city of the Southeastern Black Sea Region (Fig. 1).

Figure 1—Map of the sampling area

An orange peel bucket sampler was used to collect sediment samples from the upper (0–5 cm) layer at twenty different stations at Solakli river basin in 201313. Samples were placed in polyethylene bags using a clean plastic spatula to prevent contamination. Samples were placed in a cooler with ice, and transported to the laboratory where they were stored at -18 °C until being analyzed14. Prior to the analysis, samples were dried at 45 °C. For grain size

distribution, sediment samples were sieved using distilled water in an AS 200 vibratory sieve shaker (Retsch, Germany). For the metal analysis, sediment samples were sieved to pass < 63 µm because metals exhibit usually a higher affinity to small grains15. Metal concentrations were determined using an inductively coupled plasma-mass spectrometer (ICPMS) analysis in ACME Lab., (Vancouver, BC. Canada). Accuracy of the analysis was ranged from 95.81 % to 103.50 %. The detection limits for metals were 1 for Cr, 0.1 for Pb, 1 for Zn, 0.1 for Cu, 0.1 Ni, 0.5 As, µg g-1 and 0.01 % for Al. A combination of SEF, PLI and IGEO methods was performed to determine the pollution level based on Cu concentration according to the formula below. Classification of SEF was made according to mean shale data16. The following equation was used to calculate the SEF: SEF = (CM/CAl) Sample / (CM/CAl) Earth’scrust

(1)

Where (CM / CAl) Sample is the ratio of the concentration of trace metal (CM) to that of Al (CAl) in the sediment sample, and (CM / CAl) Earth’s crust is the same reference ratio in the Earth’s crust17. Acevedo-Figueroa et al.18 interpreted SEF values of 1 to 3 as indicating minor enrichment; 3 to 5 indicating moderate enrichment; 5 to 10 indicating moderately severe enrichment; 10 to 25 indicating severe enrichment; 25 to 50 indicating very severe enrichment; and values over 50 indicating extremely severe enrichment. PLI is another effective tool to evaluate the severity of contamination in the environment9. The PLI for a single site is calculated as the root of n number of contamination factor (CF) values, multiplied together. The CF for a particular metal is that metal’s concentration as a proportion (or quotient) of the back ground concentration of the same metal, as indicated in the following equations: CF=CMetalconcentration/CBackground concentration of the same metal (2) PLI = (CF1 x CF2 x CF3 x CFn)1/n

(3)

The formula for Igeo was proposed by Muller (1981). IGEO = log2[Cn / (1.5 x Bn)]

(4)

Where Cn is the measured concentration of element

63

INDIAN J. MAR. SCI., VOL. 45, NO. 1 JANUARY 2016

64

(n) in the sediment and Bn is the geochemical background concentration for element (n) which is either directly measured in un-impacted sediment of the area or taken from the literature16. Muller10 identified seven grades (or classes) for the IGEO, Class 0 (practically uncontaminated), IGEO ≤ 0; Class 1; (uncontaminated to moderately contaminated), 0 < IGEO< 1; Class 2 (moderately contaminated), 1 < IGEO< 2; Class 3 (moderately to heavily contaminated), 2 < IGEO< 3; Class 4 (heavily contaminated), 3 < IGEO< 4; Class 5 (heavily to extremely contaminated), 4 < IGEO< 5; Class 6 (extremely contaminated), 5 < IGEO. Elemental concentrations in Class 6 may be orders of magnitude greater than the geochemical background value. Whether the values belonging to season for each variation are different or not was investigated with “paired t test”. The relation between the metal values belonging to study area was evaluated with correlation analysis19. With the aim of easier understanding of the relations between the concepts

regarding data set achieved, the basic factors associated with data set were determined by applying factor analysis20. Statistical analysis was performed using SPSS 15. Results and Discussion Rates of clay and clay-top material were given Table 1 as a percentage in surface sediment of regions. Because the size of clay material is containing highs and homogeneous metal concentrations, metal analysis were performed in this size of material. The highest clay content was determined in S20 station. In addition, a strong temporal trend was observed displaying the highest clay content in winter (Table 1). Spatially and temporally metal concentrations (Cr, Pb, Zn, Cu, Ni and As) in samples collected from the study area were given Fig. 2.

Season

General proporties

Winter

Table 1— General properties of the sediment around Solakli river basin

≤ 0,63 µm % ≥ 0,63 µm %

Summer

pH ≤ 0,63 µm % ≥ 0,63 µm %

Summer

Winter

pH

≤ 0,63 µm % ≥ 0,63 µm % pH ≤ 0,63 µm % ≥ 0,63 µm % pH

Station number S6 S7

S1

S2

S3

S4

S5

S8

S9

S10

S11

10

12

14

12

17

31

33

27

16

17

15

90

88

86

88

83

69

67

73

84

83

85

7.40

7.38

7.37

7.38

7.26

7.32

7.30

7.29

7.22

7.25

7.31

8

11

13

14

15

27

34

24

17

14

16

92

89

87

86

85

73

66

76

83

86

84

7.46

7.39

7.40

7.40

7.35

7.36

7.33

7.30

7.27

7.33

7.35

S12

S13

S14

S15

S16

Station number S17 S18

S19

S20

S21

S22

13

18

16

18

32

29

26

31

35

22

25

87

82

84

82

68

71

74

69

65

78

75

7.27

7.41

7.55

7.57

7.34

7.31

7.32

7.20

7.12

7.23

7.25

11

19

15

16

28

25

24

30

34

20

23

89

81

85

84

72

75

76

70

66

80

77

7.31

7.45

7.59

7.54

7.43

7.36

7.34

7.23

7.20

7.25

7.29

OZSEKER AND ERUZ: ECOLOGICAL PATHWAYS OF HEAVY METAL POLLUTION IN SOLAKLI RIVER BASIN (RIVER BED, UZUNGOL LAKE AND ESTUARY) SEDIMENT OF SOUTHEASTERN BLACK SEA REGION, TURKEY

Fig.2 —Seasonal change of the metal concentrations belong to stations WASV worldwide average shale value, CCV continental crust values

Highest metal concentrations were measured in the S20 station, which is the deepest and highest clay content station in the study area. The determined

seasonal mean values which belong to stations generally appeared higher than the reference values (Table 2).

Table 2—Metal content (µg g-1) of surface sediments around Solakli river basin and its comparisons with reference values

Referances values

Season

SQGd

Present study Metal

Winter

Summer

WASVa

CCVb

TRVc

ERL

ERM

TEL

PEL

Cr

32.4 ± 10.6

32.5 ± 9.2

90

100

26

81

370

52.3

160

Pb

36.8 ± 13.2

37.1 ± 11.2

20

12.5

31

46.7

218.0

30.2

112.2

Zn

108.1 ± 17.9

121.1 ± 25.7

95

70

110

150

410

124

271

Cu

59.8 ± 12.4

64.3 ± 29.3

45

55

16

34

270

18.7

108.2

Ni

24.2 ± 4.8

23.4 ± 4.4

68

75

16

20.9

51.6

15.9

42.8

As

11.9 ± 3.7

13.9 ± 3.7

13

1.8

6

8.2

70.0

7.2

41.6

WASV worldwide average shale value, CCV continental crust values, TRV toxicity reference values, SOG sediment quality guideline, ERL effect range low, ERM effect range median, TEL threshold effect level, PEL probable effect level, aTurekian and Wedpohl16, bTaylor21, cUS EPA22, dLong et al.23

65

INDIAN J. MAR. SCI., VOL. 45, NO. 1 JANUARY 2016

66

According to the SQG proposed by US EPA, sediment was classified into three classes, nonpolluted, moderately polluted and heavily polluted24 (Table 3). According to this classification, Cr, Zn and Ni were determined as moderately polluted both winter and summer seasons. Cu and As were determined as heavily polluted while Pb was determined none polluted both winter and summer seasons. Table 3—Classification of metal concentration according to pollution limits Limits of metal value (SQG US EPA*)

Pollution limits None polluted Moderately polluted Heavily polluted

Cr

Pb

Zn

Cu

Ni

As

< 25

< 40

< 90

< 25

< 20

75

> 60

90200 > 200

> 50

> 50

>8

24

*Pekeyet al.

It is searched for each variable by “paired t” test whether the rates regarding winter and summer seasons are different. As a result., it is found that for only p