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Journal of Environmental Pollution and Control

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Heavy Element Accumulation in Aquatic Beetles of the Genus Enochrus (Coleoptera: Hydrophilidae) in Erzurum Province

Received Date: January 22, 2018 Accepted Date: September 11, 2018 Published Date: September 13, 2018

Copyright: © 2018 Aydogan Z. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

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Abstract

In the present study, fourteen heavy elements (Ti, V, Cr, Mn, Fe, Co, Ni, Cu, Zn, As, Se, Br, Sr, Pb) accumulation in sediment, water and Enochrus spp. species organs (total body) were evaluated. For this purpose, water, sediment and Enochrus spp. were collected from nine wetland sites in Erzurum province (Turkey). Measurements of heavy elements were made with Energy Dispersive X-Ray Fluorescence (EDXRF) spectrometer. The results showed that there are differences in element concentrations between species and stations. Insects were mostly found in industrialized areas. The water samples’ heavy element levels were compared with national water quality standards. The values of some heavy elements found at higher concentration than the acceptable limits.

Keywords: Aquatic Coleoptera; EDXRF; Pollution; Wetland

Introduction

All matters (living and non-living) are made up of elements and almost every manufactured product involves the elements. Elements including heavy metals and metalloids are all occur naturally in the Earth’s crust and are usually present certain degree in all environments. They are form of inorganic and organic compounds and their natural and man-made sources continuously enter the ecosystem and pose a serious damage because of their long time persistence, toxicity and tendency to bioaccumulation, bioconcentration and biomagnification in the food chain [1]. This element accumulation in the food chain creates increasing pressure on all living things every passing day. In the future, it seems that the situation will become more dramatic. Like other ecosystems pollutions, aquatic ecosystems pollution with these contaminants has become a matter of great concern over the last decades. Accumulation occurs in all aquatic invertebrates’ tissues, whether or not these elements are essential to metabolism and if the certain threshold concentrations are exceeded, it becomes toxic [2,3].

The terms bioindicator and biological monitor have significant variation in meaning. Bioindicator generally refers to organisms or molecules that provide significant information in regard to quality of environment or environmental changes, whereas biomonitors are the organisms that provide quantitative information about the environment. In this regard, a biomonitor always acts as a bioindicator but a bioindicator does not always a biomonitor [4]. According to Witting, Markert and Rainbow [2,5,6], there are some basic criteria for a suitable biomonitor that it should; have large numbers all over the studying area, have cosmopolitan geographical distribution, be easy and inexpensive to sampling and have well known taxonomy. Today to evaluate ecosystem condition and its quality, biological monitoring methods have been applied widely in ecological research [6-8].

Like other organisms in the ecosystems, insects are exposed to various anthropogenic chemicals and some of them accumulate these chemicals in their body. Insects are largest group of organisms, and have numerous effects on human health because of diversity in their morphology and physiology, their abundance, economic importance [9]. Aquatic insects live or spend a part of their life cycle in different kind of water bodies [10]. Aquatic insects are good indicators of water qualities since they have various environmental tolerant levels [11]. Some of them such as midge and blackfly larva etc. indicate poor water quality and can live in moderately or extremely polluted waters, whereas some of them such as mayfly, stonefly nymph very vulnerable and sensitive to pollution and indicates good water quality [12-14] investigated metal contamination ability of the Odonata larvae and the study suggests that they have an ability to take up metals and appropriate indicator for ecosystem health. Boyd (2009) studied Ni hyper-accumulator insects which feed on Ni hyper-accumulator plants showed that Ni hyper-accumulator insects accumulate more Ni than other insects. Aydoğan et al. (2017) [8] studied heavy metal accumulation in some aquatic insects and tissues of Chondrostoma regium in the same habitat showed that insects accumulated more metals than their environment and due to food of studied fish the metals could be transfer from insect to along the food web.

Hydrophilidae is one of the largest families of Coleoptera, and some feature of Hydrophilidae make them good biomonitor for heavy element such as it has worldwide distribution, well known taxonomy and larvae and adults live in different environmental conditions. Hydrophilidae are water scavenger beetles and generally occur in shallower regions of wetland with abundant macrophytes and feed mainly on detritus, algae and decaying organic matter in contrast to adults, larvae are predaceous, preying on various invertebrates [15]. Hydrophilidae are present in low dissolved oxygen content water indicating the hardy nature of these beetles [16]. The aquatic Coleoptera of the genus Enochrus Thomson 1859 are among the commonest species of the European hydrophilids, and also is the third largest genus in the Hydrophilinae with 223 species placed in six subgenera worldwide [17]. This research attempted to evaluate the potential use of adults Enochrus spp. samples as biomonitor of heavy element pollution, as well as classify and compare the health status of freshwater in Erzurum province, Turkey.

Materials and Methods

Erzurum is the biggest city of the Eastern Anatolia Region in Turkey. In addition, it is one of the highest and coldest cities in Turkey. It is very rich in terms of water resources. Industrialization has not improved but economy mostly based on agricultural and livestock activities, trade and winter tourism. In this study, nine different locations (i.e; industrial, roadside, urban, suburban and rural area) were selected. These localities are described in Table 1 and given in Figure 1.

To determine the extent of element accumulation in nine sites of Erzurum, all samples (Enochrus spp. and their abiotic environment) were collected in June, July and August 2014. The samples were collected, identified and analyzed as described in Aydoğan et al. (2016; 2017 [8,18]). 1 mm mesh aperture sieve and mouth aspirator was used to collect insect samples and they were preserved in 70% alcohol. Identification was made under stereomicroscope by using male genitalia of insects. The aquatic insects were identified with using taxonomical key to the species level [19,20]. The sediments were taken from 30 cm depth benthic zone. The water samples were taken from 0.5 m depth of stream. 15 cc for water and 3 gr for sediment was enough to analyze in EDXRF. Water and sediment samples were kept in the refrigerator until analysis.

After identification, samples were dried in an oven at 80 ˚C during 36 h. Concentrations of 14 elements in the samples measured by EDXRF spectrometry. To determine heavy elements, 1 Ci 241Am radioactive source and an HPGe detector with resolution ~180 eV at 59.5 keV was used. All samples were excited by using 59.5 keV photons, emitted from 241Am radioactive source. All measurements were carried out under vacuum. Water and sediments samples were put in Al sample holder with Mylar films on both sides. Measurement time for water and sediment samples was 4 h. Insects were pulverized, and then, cellulose was added as a binder. Five tons of pressure was applied to make 13 mm diameter pellets of each species. WinAXIL program is used for determinate the concentration of elements in each sample. The model parameters are optimized by means of a nonlinear least squares strategy, using a modified Marquardt algorithm to minimize the weighted (optional choice) sum of differences χ2 between the experimental data and the mathematical model. The concentration presented in this table has some uncertainties due to EDXRF (maximum ~5%). Possible error sources for these uncertainties are given in Table 2, and the typical spectrum of samples in EDXRF shown in Figure 2. Chemical parameters of the insects, water and sediment samples are given in Table 3.

Results

In total, 191 individuals of Hydrophilidae (Coleoptera), belonging to genus Enochrus spp. were collected from 9 stations. Six species of genus Enochrus Thomson 1859 were determined. Determined species are as follows; Enochrus (Lumetus) ater (Kuwert 1888), Enochrus (L.) segmentinotatus (Kuwert 1888), Enochrus(L.) bicolor (Fabricius 1792), Enochrus (L.) quadripunctatus (Herbst 1797), Enochrus (L.) fuscipennis (Thomson 1884), Enochrus (L.) halophilus (Bedel 1878).

In general, values of some elements like Ti, Cr and Pb are higher in almost all the samples. In all stations of water and sediment samples Ti, Fe, Ni, Br, and Pb were measured. In all Enochrus species Fe, Ni, Se, and Pb were measured. The most abundant elements in Enochrus spp. were Ti, Cr, Mn, Fe, Ni, Cu, Zn, As, Se, Br, and Pb.

Sediment concentration results show that, in all stations Ti, Fe, Ni, Zn, As, Se, Br, Sr, and Pb were measured. Besides, the highest concentration of Cr was measured in stations 1, 2, 3, 4, and 9; the highest concentration of Fe was measured in stations 5, 6, 7, 8 and 9; the highest concentration of Ti was in stations 8; the highest concentration of Mn was in stations 3. V measured only stations 1 and 7. Heavy element levels in water indicated that Ti, and V had the highest concentration in all stations. Only station 7 had Sr concentration, but there is no Se and Sr concentration in water of all rest stations. In water, the rest of the heavy elements were in lowest concentration. The element concentration in water samples are arranged as Ti> V > Cr >Mn> Fe >Pb> Co > Ni > Cu >As > Zn > Br >Sr> Se and in sediment samples Cr > Fe >Mn> Ni > Co > Se >Sr> As > Cu > Br > Zn >Pb>Ti> V. Results of this study indicates that E. quadripunctatus is the best accumulator for certain elements, and followed by E. fuscipennis and E. segmentinotatus. Compared to the other Enochrus species, it appears that E. quadripunctatus accumulated the highest level of Ti, Fe, Ni, Cu, Zn, As, Se, Br, Sr, and Pb. The highest concentrations of rest of the elements; in E. bicolor was V, in E. halophilus Co, in E. ater Cr, in E. segmentinotatus Mn.

The water quality levels were compared according to Turkish Water Pollution and Control Regulations (TWPCR 2004) [21]. There are four quality classes according to TWPCR: high quality water (I), weakly polluted water (II), polluted water (III), and highly polluted water (IV). According to TWPCR, water in all stations have highly polluted (IV) and polluted (III) water quality in terms of Pb, As, Cr, Co, Ni, Mn, and Se; weakly polluted water quality (II) in regard to Fe, third and fourth stations except to this; high quality water (I) in regard to Zn and Ba. Only the fourth station has Se concentration and has IV water quality. According to the results it was determined that these concentrations adversely affected water quality. The stations 1, 2, 3, 5, 7, and 9 have III and IV water quality in regard to Pb, As, Cr, Co, Ni, and Mn; this can be due to cement factory spreading ash emission, traffic pollution due to highways, and agriculture activities in Gökçeyamaç village. Station 4, 6, and 8 has II water quality in regard to Fe and restsof the stations have IV and III water quality degree. These results are given in Table 4. Determination of Pb, As, Cr, Co, Ni, and Mn residues in water samples at the stations 7, and 8 where human activity is limited, reveals the extent of the spread. Because in these stations, there are no intensive agriculture or traffic. Ce, Pd, Ba, In, Sn, Nb, Pm, La, and Mo were below the detection limit of EDXRF spectrometry (ppm).

Discussion

Aquatic insects are inseparable part of freshwater ecosystems. When food chain is considered, pollutions are able to reach to another organism from one to another, and also at the end human beings. Therefore, protecting the wetlands in turn can protect our safety and welfare. Thus, this research attempted to determine the potential use of aquatic insect communities as biomonitor as well as assess the health status of wetlands in Erzurum province and surrounding.

The concentrations of the fourteen elements were measured different level in insects, water and sediment. The highest pollution levels were found in the samples taken from the industrial sites (1, 2, 4, 5). In field study it was observed that insect samples have abundance in industrial sites and same results were obtained by Pakulnicka et al. (2015) [22]. The element concentrations were found to increase from water to insects in general (water<sediment<Enochrus spp.). Thus, it can be said that, heavy elements would be transported to organisms on the higher position from water to insects and along food chains. The studies of Boyd (2009) [23] and Aydoğan et al. (2017) [8] support that result.

In the present study it can be seen that, contaminants residues in Enochrus spp. are reflective of environmental quality. The measured element concentrations reflect a clear influence of anthropogenic activities. Element concentration in the Enochrus spp. showed differences in accordance to the sediment contamination of each station. High concentrations of the elements in sediment and water samples cause high level of heavy elements in Enochrus spp. The heavy element concentrations varied significantly by the sampling sites and species. Station 2, 3, and 4, where anthropogenic activities are intense, have the highest number of individuals. Enochrus spp. can survive even the locations which they live in low environmental quality. Therefore, it can be thought that they are tolerant to metal pollution. The results also show that it is possible to analyze element concentrations in these aquatic insects. Enochrus spp. fulfill the aforementioned biomonitor criteria like represented in large numbers all over the monitoring area, have numerical abundance, cosmopolitan distribution and easy identifiable.

It is known that proportion to the volume of traffic and close distance from the road lead contribution of Pb level environment and carried by aerial deposition alongside the road [24]. Besides to traffic pollution, industrial activity is major source of heavy metals/metalloids [3]. But some of the stations are away from anthropogenic sources and this can be explained by only atmospheric transportation [25].

To summarize, the data given in this study showed that Enochrus spp. are capable of reflecting element bioaccumulation with different levels and embodies all these criteria, thus Enochrus spp. can be used in environmental quality monitoring studies. For more information to assess health of environment, long-term biomonitoring must be regularly done. Because long-term biomonitoring of aquatic insect communities may provide insight into how human induced alterations are affecting community structure, ecosystem functions and water quality. It is hoped that the results from this study will provide baseline information in Erzurum province.

Acknowledgements

This research, has been supported by project of the Atatürk University Scientific Research Project SRP-2012/162, and is a part of first author’s Ph. D thesis. The authors express their sincere gratitude Assist. Prof. Dr. Buğrahan EMSEN of the department of Biology at the University Of Karamanoğlu Mehmet Bey, for statistical analysis of samples.

3 Depledge MH, Weeks JM, Bjerregaard P (1994) Heavy metals. In: Handbook of ecotoxicology, Blackwell Scientific, London: UK.
4 Breure AM, Markert BA, Zechmeister HG (2003) Bioindicators & Biomonitors: Principles, Concepts and Applications. Elsevier.
5 Wittig R (1993) General aspects of biomonitoring heavy metals by plants. In: Markert B (ed) Plants as biomonitors: indicators for heavy metals in the terrestrial environment. Weinheim VCH Publisher, 3-27.
9 Tardiff RG, Goldstein BD (1991) Methods for assessing exposure of human and non-human biota.
10 Pennak RW (1978) Freshwater invertebrates of the United States, 2nd ed. John Wiley and Sons, New York, 810.
12Merritt RW, Cummins KW (1996) An introduction to the aquatic insects of North America. 3rd ed. Kendall-Hunt, Dubuque, IOWA, 862.
13 Eugenia López-López, Jacinto Elías Sedeño-Díaz (2015) Biological indicators of water quality: The role of fish and macroinvertebrates as indicators of water quality. Environmental Indicators. Springer, Dordrecht
15 Fikáček M, Gentili E, Short AEZ (2010) Order Coleoptera, family Hydrophilidae. Arthropod fauna of the UAE 3: 135-65.
19 Hansen M (1987) The Hydrophilidae (Coleoptera) of Fennoscandia and Denmark, 18. Fauna Entomologica Scandinavica, EJ Brill, Denmark, 253.
20 Hansen M (1991) The Hydrophiloid beetles phylogeny, classification and a revision of the genera (Coleoptera, Hydrophiloidea). Biol Skr, 40, 365.
21 TWPCR (2004) Turkish water pollution control regulations-25684 (in Turkish). Ministry of environment and urbanization, 25684 oficial gazette, Ankara.
22 Pakulnicka J, Buczyńska E, Buczyński P, Czachorowski S, Kurzątkowska A, et al. (2015) Are beetles good indicators of insect diversity in freshwater lakes?. Oceanological and Hydrobiological Studies 44: 487-99.

Journal of Environmental Pollution and Control

Tables at a glance
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Table 1
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Table 2
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Table 3
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Table 4
Figures at a glance
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Figure 1
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Figure 2
Figure 1: Photos of the nine sampling sites and location in Erzurum province
Figure 2: The typical spectrum of a sample in EDXRF
Station Number Altitude (m) Coordinates Station information Notes on near environment

1

1636

39°54'19''N 40°41'01''E

500 m Western front of Cement factory

Traffic and ash emission from cement factory

2

1669

39°54'38''N 40°41'41''E

500 m Eastern front of Cement factory

Ash emission from cement factory

3

1636

39°56'41''N 40°39'44''E

Aşkale-Trabzon Highway

Traffic pollution, limited human activities

4

1759

39°56'03''N 41°04'24''E

Sugar factory  Drainage channel

Sugar factory waste

5

1754

39°57'04''N 41°04'39''E

Erzurum-Ilıca Highway

Sugar factory waste and traffic pollution

6

1765

40°02'31''N 41°21'05''E

Erzurum-Tortum Highway

Traffic and domestic pollution

7

1819

40°04'35''N 41°21'38''E

Gökçeyamaç Village

Agriculture, livestock and domestic pollution

8

1826

40°06'05''N 41°21'36''E

Akdağ Village (Erzurum)

Contamination due to livestock

9

1766

39°55'59''N 41°08'56''E

Dadaşkent (Erzurum)

Heavy traffic pollution

Table 1: Description of the nine sampling sites in Erzurum province

Nature of Uncertainty

Uncertainty (%)

Counting Statistics

~ 1.00

Systematic errors

~2.00

Peak evaluation procedure

~3.00

Fundamental parameter methods

~3.00

Table 2: Error sources in the experimental results

Stations Samples Mean ± SD

Ti

V

Cr

Mn

Fe

Co

Ni

Cu

Zn

As

Se

Br

Sr

Pb

1

Water

436±6.55

82.6±4.5

22±2.6

6.2±0.26

2.9±0.15

1±0.1

0.3±0.2

0.36±0.15

0±0

0.2±0.1

0±0

0.34±0.1

0±0

1.7±0.25

Sediment

1.7±0.25

0.32±0.11

849±6.02

0±0

0.13±0.06

0±0

22.3±2.5

9.23±0.25

4.9±0.65

9.5±0.4

10.06±0.5

5.03±0.4

9.6±0.36

10.8±1.04

E. quadripunctatus

127±5.5

23.3±3.05

18.1±2.8

6.8±1.2

2.8±0.41

2.33±0.41

0.41±0.2

0.42±0.06

0.2±0.1

0±0

0.24±0.1

0±0

320.6±6.1

602±7.21

E. halophilus

307±8.18

55.3±3.5

46.6±3.5

19±2

1.2±0.2

5.2±0.2

5.1±0.4

1.03±0.14

0.47±0.3

0±0

1.2±0.2

0.6±0.3

0.14±0.05

0.2±0.01

2

Water

321.8±20

63.8±2.7

14.6±2.5

4.9±0.6

2.2±0.2

0.03±0.02

0.5±0.1

0.13±0.05

0.2±0.1

0.2±0.1

0±0

0.25±0.1

0±0

1.9±0.2

Sediment

1.2±0.25

0±0

663.6±13

231.3±12

244±4.5

8.8±0.4

15±3

7.5±0.4

3.7±0.3

7.3±0.7

8.2±0.3

3.6±0.5

9.5±0.5

2.5±0.5

E. ater

1.1±0.16

0±0

434±6.1

0±0

185.3±4.1

0±0

9.4±0.3

0±0

2.2±0.2

4±0.4

4.4±0.7

10.1±0.8

0.5±0.3

175.6±5.5

E. bicolor

0.1±0.02

0±0

73.6±3.5

0±0

87.6±2.5

0±0

1.5±0.3

0.6±0.2

0.5±0.3

1.5±0.1

0.5±0.4

1.9±0.2

0.2±0.1

10.4±1.05

E. halophilus

147±4.53

0±0

0±0

0±0

3.1±0.4

0±0

0.13±0.05

0.2±0.17

0±0

0.1±0.5

0.130.05

0.14±0.05

0.06±0.02

1.8±0.4

E. segmentinotatus

173±3.8

0±0

7.2±0.2

2.2±0.2

3.1±0.2

0±0

0.13±0.05

0.2±0.1

0±0

0.2±0.1

0.1±0.05

0.1±0.05

0.01±0.003

2.3±0.2

E. fuscipennis

0.2±0.06

0±0

0±0

0±0

190±10.4

0±0

2.2±0.2

1.4±0.2

4.2±0.2

1.6±0.1

1.03±0.1

4.1±0.3

1.1±0.1

11.4±0.9

E. quadripunctatus

783±4.3

0±0

32±2.08

10.1±0.8

30.6±3.5

0±0

0.4±0.3

0.2±0.1

1.1±0.17

0.2±0.1

0.26±0.15

0.5±0.2

0.1±0.05

6.2±0.2

3

Water

796.8±5

140.5±8

10.3±0.2

10.1±0.7

4.8±0.4

1.8±0.2

0.7±0.2

0.2±0.1

0.2±0.1

0.2±0.1

0±0

0.2±0.05

0±0

3.23±0.2

Sediment

1.2±0.2

0±0

662±14.8

240.3±3

245±4.5

9.9±1.1

16.6±1.5

7.8±0.2

3.9±0.6

6.5±1.3

7.5±0.4

4.3±0.3

10±0.8

2.4±0.5

E. halophilus

3.6±0.4

0±0

0.1±0.02

494.5±13

557.3±11

72±2.2

30.3±1.5

0±0

8.6±0.5

11±1.8

15.6±0.7

16±0.7

2.2±0.3

128.6±3.2

E. fuscipennis

0.1±0.02

0±0

42.6±2.5

12.3±2.5

20±2

0±0

0.5±0.4

0.33±0.2

0.2±0.07

0.2±0.1

0.3±0.2

0.5±0.06

0.13±0.05

4.4±0.1

E. bicolor

0±0

0.5±0.1

0.1±0.02

463.6±13

755.6±4

0±0

29.8±0.7

15.3±0.2

8.3±0.3

13±0.7

15±0.5

28.3±1.5

3.2±0.2

108.6±3.2

4

Water

239±3.6

45±3

10.2±0.6

3.3±0.2

2.1±0.4

0.3±0.1

0.2±0.1

0.1±0.05

0.1±0

0.1±0.5

0.1±0.1

0.1±0.04

0±0

0.9±0.05

Sediment

1±0.1

0±0

467±18.5

0±0

0.1±0.01

0±0

11±1.05

0±0

3.1±0.1

6.2±0.2

6.4±0.4

3.3±0.2

12.5±0.5

2.03±0.05

E. quadripunctatus

13.9±1.6

3.2±0.2

0.5±0.1

0.1±0.05

0.1±0.01

0±0

125±3

60.6±4.04

45±4.04

56±1.7

67.5±2.2

167±3.6

5.7±0.2

250.3±1.5

E. bicolor

390±2.5

72±2

15.6±0.7

4.9±0.2

3±0.3

0.5±0.1

0.2±0.1

0.1±0.05

0.6±0.2

0.2±0.1

0.1±0.05

0.5±0.1

0±0

3.2±0.2

E. segmentinotatus

4.2±0.2

0.7±0.2

0.1±0.05

589.3±4

467.3±2.5

0±0

57.3±2.5

19.2±0.2

50.6±1.1

15.3±1

18.8±0.7

41.3±1.5

2±0.1

134.6±2.5

5

Water

402±3.2

80.6±0.5

17.5±1.3

5.8±0.2

2.2±0.2

0.6±0.2

0.4±0.1

0.13±0.05

0±0

0.1±0.05

0±0

0.12±0.03

0±0

1.9±0.11

Sediment

0.3±0.05

0±0

0±0

0±0

657.6±2.5

0±0

4.9±0.6

2.2±0.2

1±0.05

1.9±0.2

2.2±0.2

1.2±0.2

1.6±0.5

0.5±0.2

E. quadripunctatus

0±0

0.4±0.09

0±0

453.6±5

904±5.2

0±0

32.3±2.5

12.3±2.5

11.6±1.1

13±0.2

15.5±0.5

24.1±0.8

3.8±0.3

100±2

6

Water

260±3

0±0

11±1

3.5±0.5

1.23±0.25

0.5±0.1

0.2±0.1

0.13±0.05

0.16±0.1

0.2±0.1

0±0

0.18±0.1

0±0

1.26±0.2

Sediment

0.5±0.1

0±0

0±0

0±0

857.6±2.5

20.5±0.5

8.2±0.2

2.9±0.15

2.03±0.3

3.7±0.2

3.6±0.2

2.3±0.2

4.6±0.4

1.36±0.15

E. quadripunctatus

7.5±0.4

0±0

0.2±0.08

0.1±0.05

0.14±0.05

0±0

74.5±1.3

0±0

142±2.5

25±0.7

40.6±1.1

432.6±15

3.2±0.2

504.6±5

E. fuscipennis

5.2±0.25

0±0

0.1±0.07

0±0

655±5

0±0

49.3±2

0±0

35.3±3.5

20.8±1

25±2

59.3±2

2.2±0.2

230.3±2.5

7

Water

573±3.5

0±0

25.6±0.7

6.9±2

3.9±0.2

1.2±0.2

0.6±0.2

0.2±0.1

0±0

0.2±0.1

0±0

0.27±0.06

0.23±0.05

2.9±0.36

Sediment

0.4±0.2

0.1±0.01

0±0

69.6±1.5

949±6.5

0±0

5.7±1.1

0±0

1.4±0.2

3.2±0.2

3.5±0.5

2.9±0.55

5.3±0.15

1.03±0.05

E. bicolor

439±4.5

0±0

15±3

0±0

3.9±0.2

0.6±0.2

0.2±0.15

0.13±0.05

0.1±0.05

0±0

0.1±0.05

0.2±0.09

0±0

3.7±0.25

E. fuscipennis

0.1±0.05

0±0

74±1.8

22±2

19.6±1.5

0±0

1.9±0.1

0.6±0.1

0.4±0.2

0.6±0.1

0.6±0.15

0.9±0.17

0.06±0.02

8.9±0.25

8

Water

203±3.6

35.6±3

0.3±0.1

2.9±0.17

1.2±0.25

0.3±0.15

0.1±0.05

0.1±0

0±0

0±0

0±0

0.07±0.02

0±0

0.7±0.1

Sediment

70±1

0±0

321±1.5

0±0

855±5

18±2

6.8±1.6

4±0.4

2.1±0.2

3.7±0.2

4.06±0.6

2.5±0.4

7.2±0.25

1.16±0.2

E. fuscipennis

5.8±0.3

0±0

0.1±0.07

0±0

0.1±0.07

0±0

54.1±1.8

26±1.6

22±2

23±1.8

26.3±1.8

54.5±3.2

4.16±0.2

343.3±4.1

9

Water

390±5.5

0±0

16.2±1.5

5.5±0.5

2.9±0.15

0.7±0.2

0.2±0.15

0.16±0.05

0.1±0

0.2±0.05

0±0

0.16±0.05

0±0

1.8±0.3

Sediment

0.5±0.2

0±0

290±3

0±0

927.3±2.5

17±2

7.5±0.1

0±0

1.6±0.5

3.7±0.2

2.8±0.7

2.5±0.3

3.5±0.5

0.9±0.17

E. quadripunctatus

47±2

8.3±0.2

5.7±0.2

1.7±0.3

0.7±0.12

0.5±0.2

0.1±0.04

952±6.2

531.3±7

0±0

100.3±2.5

62.3±2.5

72.3±2.5

166.3±3.2

Table 3: Heavy element concentration of (Mean ± SD) in water, sediment and Enochrus spp. (ppm)

Heavy Elements Station 1 Station 2 Station 3 Station 4 Station 5 Station 6 Station 7 Station 8 Station 9 TWPCR (µg/L)

I

II

III

IV

Pb

 1.7±0.25

1.9±0.2

3.23±0.2

0.9±0.05

1.9±0.11

1.26±0.2

2.9±0.36

0.7±0.1

1.8±0.3

10

20

50

>50

As

0.2±0.1

0.2±0.1

0.2±0.1

0.1±0.5

0.1±0.05

0.2±0.1

0.2±0.1

0±0

0.2±0.05

20

50

100

>100

Cu

0.36±0.15

0.13±0.05

0.2±0.1

0.1±0.05

0.13±0.05

0.13±0.05

0.2±0.1

0.1±0

0.16±0.05

20

50

200

>200

Cr

22±2.6

14.6±2.5

10.3±0.2

10.2±0.6

17.5±1.3

11±1

25.6±0.7

0.3±0.1

16.2±1.5

20

50

200

>200

Co

1±0.1

0.03±0.02

1.8±0.2

0.3±0.1

0.6±0.2

0.5±0.1

1.2±0.2

0.3±0.15

0.7±0.2

10

20

200

>200

Ni

0.3±0.2

0.5±0.1

0.7±0.2

0.2±0.1

0.4±0.1

0.2±0.1

0.6±0.2

0.16±0.05

0.23±0.15

20

50

200

>200

Zn

0±0

0.2±0.1

0.2±0.1

0.1±0

0±0

0.16±0.1

0±0

0±0

0.1±0

200

500

2000

>2000

Fe

2.9±0.15

2.2±0.2

4.8±0.4

2.1±0.4

2.2±0.2

1.23±0.25

3.9±0.2

1.2±0.25

2.9±0.15

300

1000

5000

>5000

Mn

6.2±0.26

4.9±0.6

10.1±0.7

3.3±0.2

5.8±0.2

3.5±0.5

6.9±2

2.9±0.17

5.5±0.5

100

500

3000

>3000

Se

0±0

0±0

0±0

0.1±0.1

0±0

0±0

0±0

0±0

0±0

10

10

20

>20

Ba

0,0071

0,0053

0,0114

0,0039

0,0062

0,0004

0,0093

0,0031

0,0063

1000

2000

2000

>2000

Table 4: The results for water were compared with national water regulation (TWPCR) (ppm)