TRACE METALS IN MUSCLE TISSUE FROM SOUTHERN BRAZILIAN COAST FISH.

 

Carvalho,C.E.V.; Rezende,C.E.; Ferreira,A.G.; Faria,V.V.; Gomes, M.P. & Cavalcante, M.P.O. (Laboratório de Ciências Ambientais, CBB, Universidade Estadual do Norte Fluminense, Av. Alberto Lamego, 2000, Horto, Campos dos Goytacazes, R.J., CEP: 28015-620, Brazil. Tel: +55 24 726-3709 Fax: +55 24 726-3720, E-mail: carvalho@cbb.uenf.br ).

 

Abstract

 

As part of the Marine Environmental Monitoring Program (MoMAM) of the Brazilian Coast, fish samples were collected from five sites along the Southern Brazilian Coast. The present work reports the concentration of Al, Cd, Cr, Cu, Fe, Mn, Ni, Pb and Zn in fish species. Al and Cd presented the highest concentrations in Zapteryx brevirostris (158 and 7 mg.g-1d.w.) in Macaé and Barra de Guaratiba (respectively) both sites located in the coast of Rio de Janeiro State (RJ); Mn concentrated mainly in Porichthys porosissimus (7.7 mg.g-1 d.w.) from São Sebastião, São Paulo State (SP); Cr, Cu and Ni presented the highest concentration in Dasyatis guttata (0.5, 5.3 and 20 mg.g-1 d.w. respectively) from Atafona (RJ); Pb and Zn showed the highest concentration in Lophius gastrophysus (5,8 and 34 mg.g-1 d.w. respectively) from Arraial do Cabo (RJ); Fe concentrated mainly in Merluccius hubbsi and Prionotus punctatus (116 mg.g-1 d.w.) from Arraial do Cabo (RJ) and Ubatuba (SP). Most of the concentrations were close to that described at the literature for areas under low contamination impact.

 

Introduction

 

            Heavy metals generally are present in small amounts in natural aquatic environments. Industrial activities have raised natural concentrations causing serious environmental problems. The biota that inhabit contaminated sites are generally exposed  to very high concentrations of these pollutants, and/or to distinct chemical formula from the natural undisturbed ecosystems (Woo et al., 1993).

The main pathway to human contamination by organic and inorganic pollutants associated to aquatic systems is consumption of contaminated food (Mackay & Clark, 1991). The potential risk to human health associated to the consumption of contaminated food is 20 to 40 times higher than the ingestion of contaminated water (Foran, 1990). This fact is due to the capacity of some aquatic organisms to concentrate heavy metals up to 105  times the concentration present in the water (Guimarães et al., 1985).

 

Material and Methods

 

            The sampling was performed on board of the research vessel Batelão “Miguel dos Santos” from the Brazilian Navy. A total of four samplings cruises were done in different areas, Macaé (M), Arraial do Cabo (AC), Atafona (A), Barra de Guaratiba (BG), Baía de Guanabara (GB) and Parati (P) in the Rio de Janeiro State and Ubatuba (U), São Sebastião (SS) and Santos (S) in São Paulo State. The sampling was performed  with an otter-trawl (10 meters large) in a 20 minutes drag, mesh net was 1 cm.

            Each sampled individual was identified following the procedure described by Figueiredo (1977), Compagno & Springer (1978) and Spilman (1992). All the samples were measured, weighted and reproductive condition and sex was observed. All the samples were freeze in the ship to be transported  to the laboratory.

In the laboratory 20 grams of muscle tissue was removed with the help of a stainless steel surgery knife and oven dried (80°C/48h) and powdered in a porcelain mortar. One gram of sample in triplicate was submitted to a strong acid digestion (HCl + HNO3 conc. 3:1) in a glass tube block digester. After complete dissolution the acid was evaporated to almost dryness and dissolved in 0.5N HCl (Páez-Osuna, et al., 1995). Metal determination (Al, Fe, Cd, Cr, Cu, Mn, Ni, Pb and Zn) was performed with an ICP-AES (Varian, Liberty II), and  the results expressed in mg.g-1 of dry weight (dw).

 

Results and Discussion

 

The metal average abundance observed in fish tissue was the following Al>Fe>Zn>Cd>Cu>Ni>Mn>Pb>Cr, although the standard deviation was generally very high (table1). The high standard deviation is probably due to the several biological and environmental characteristics (e.g. metal essentiality, size, age, sex, feed habits, water quality, distance from pollution source, etc) that will determine the availability, intake and adsorption of the element by the local biota (Fostner & Wittmann 1983).  

Al and Cd presented the highest concentrations in Zapteryx brevirostris (158 and 7 mg.g-1d.w.) in Macaé and Barra de Guaratiba (respectively) located in the Rio de Janeiro State (RJ); Mn concentrated mainly in Porichthys porosissimus (7.7 mg.g-1 d.w.) from São Sebastião in São Paulo State (SP); Cr, Cu and Ni presented the highest concentration in Dasyatis guttata (0.5, 5.3 and 20 mg.g-1 d.w. respectively) from Atafona (RJ); Pb and Zn showed the highest concentration in Lophius gastrophysus (5,8 and 34 mg.g-1 d.w. respectively) from Arraial do Cabo (RJ); Fe concentrated mainly in Merluccius hubbsi and Prionotus punctatus (116 mg.g-1 d.w.) from Arraial do Cabo (RJ) and Ubatuba (SP).

It is very important to mention that only Porichthys porosissimus and Zapteryx brevirostris were collected in most of all the sampling areas, this fact implies difficulties in comparing the sampled regions. Based on heavy metal distribution in these two species it was possible to indicate some of the areas that presented the highest metal concentrations. For Porichtys porosissimus the highest Al, Cu and Mn concentrations were observed in the São Sebastião region (SP), Cd and Zn were higher in the Rio de Janeiro Coast (station near Guanabara Bay), Fe presented it's highest concentration in Ubatuba Region (SP) and Pb in the Parati/Ubatuba region in the board from Rio and São Paulo States. For Zapteryx brevirostris the highest Zn, Pb and Ni concentrations were observed in the Cabo Frio region (North of RJ State), Mn, Fe and Cr were higher in the Parati/Ubatuba region and Cu and Cd higher at Rio de Janeiro Coast (Baía de Guanabara and Barra de Guaratiba). Although the two species did not show the same metallic distribution pattern, some of the above mentioned areas presented high metal concentrations, showing that some attention must be taken in order to avoid future metal contamination.   

            Comparing our results with previous works and literature data it is possible to observe that although a large variability was observed, the average of all studied fish presented values similar to the values described by Pfeiffer et al. (1985) in a study developed in Sepetiba Bay, in Rio de Janeiro State Coast. Furthermore, the majority of the samples presented concentration below the maximum permissible concentration determined by the Brazilian Health Ministry (Table 1). It is important to mention that the study performed by Pffeifer (1985) and the maximum permissible values determined by the BHM  the concentrations are expressed in wet weight. Considering that our values are in dry weight it is clear that our results are lower than both studies.  

 

Conclusions

                Although some of the studied areas presented strong human activities (e.g. Harbor, contaminated river inputs, etc) the observed metal values in almost all samples could be considered as unpolluted or with low levels of contamination. Notwithstanding the fact that a minority of the samples presented high concentration. This observation strengthen the importance of study the fish biology and how it could influence the metal uptake, and also alarm the authorities in order to begin to investigate coastal environmental contamination.

 

References

Compagno, LJV, Springer S (1978), FAO Species Identification Sheets for Fishery Purposes, Western Central Atlantic (Fishing Area 31). Roma: Ed. Fisher, W.

Figueiredo JL (1977), Manual de Peixes Marinhos do Sudeste do Brasil. I. Introdução. Cações, raias e quimeras. São Paulo, Museu de Zoologia da USP.

Foran JA (1990). Environm. Sci. Technol. (24): 604-608.

Förstner U, Wittmann GTW (1983),  Metal Pollution in the Aquatic Environment. Berlin, Springer Verlag.

Guimarães JRD, Lacerda LD, Teixeira VL (1982), Rev. Brasil. Biol. 42: 553-557.

Mackay D, Clarck KE (1991), Predicting the environmental partitioning of organic contaminants and their transfer to biota. In: Jones KC (ed) Organic Contaminants in the Environment. Environm. Managem. Series, New York, Elsevier Science Pub.

Páez-Osuna P,  Frias-Espericueta MG, Osuna-López JI (1995), Mar. Environ. Res. 40(17): 133-141.

Pfeiffer WC, Lacerda LD, Fiszman M, Lima NRW (1985), Ciênc. e Cult., 37 (2): 297-301.

Szpilman M (1992), Aqualung Guide of Fishes - A Practical Guide to The Identification of Brazilian Coastal Fishes. Aqualung Confecção Ltda.

Woo P T K, Sin YM, & Wong MK (1993). Environ. Biol. of Fishes, 37: 67-74.

 

Acknowledgement

            The authors would like to express their gratitude to IEAPM (Project Coordination),  FENORTE and the Brazilian Navy Ministry for financial and logistic support. The technicians Arizoli A.R. Gobo, Cristina B. Siqueira, and Denise N. de Souza for the laboratory support. The crew of the R.V. Batelão Miguel dos Santos. And M.Sc. Eduardo Barros Fagundes Netto and M.Sc. Luiz Ricardo Gaelzer for species identification. It is important to mention that this work is part of the Marine Environmental Monitoring Program (MoMAM);that have the participation of the following institutions: IEAPM, CTM, IO-USP, IRD, UFSC, UERJ, UFRJ and UENF.

 

 

 


Table 1. Average metal concentrations  in all sampling sites in each of the analyzed species (mg.g-1, dry weight).

Species (sampling areas)

Al

Cd

Cr

Cu

Fe

Mn

Ni

Pb

Zn

Myliobatis freminuillei (AC)

22.1

8.33

0.14

4.03

23.2

< 0.02

0.50

0.56

24.5

Zapteryx brevirostris (M, GB, BG, AC, P, U)

52.1

3.03

0.12

1.03

22.9

1.02

0.18

0.78

14.6

Psammobatis extenta (AC)

99.0

2.49

< 0.01

1.40

24.0

< 0.02

0.66

2.77

17.3

Raja agassizi (M, AC)

20.3

4.17

0.54

0.36

19.6

1.04

1.65

0.71

17.7

Raja castelnaui (AC)

31.3

2.09

0.11

< 0.05

21.5

< 0.02

0.25

2.07

19.2

Raja sp (AC)

2.4

2.42

0.42

< 0.05

1.00

< 0.02

0.70

1.70

11.8

Sympterigya acuta (M)

4.1

2.48

< 0.01

0.91

1.00

< 0.02

< 0.03

< 0.05

19.1

Sympterigya bonapartei (M)

2.0

4.36

0.37

0.36

89.8

< 0.02

0.37

1.65

13.8

Dasyatis guttata (A)

36.6

0.30

0.50

5.30

27.3

< 0.02

20.0

0.40

16.4

Pellona sp (A)

109

0.10

0.40

3.40

67.6

< 0.02

< 0.03

0.10

15.4

Porichthys porosissimus (GB, M, U, P, SS)

24.0

0.65

0.14

0.40

34.9

1.67

< 0.03

< 0.05

17.6

Lophius gastrophysus   (AC, P, U )

71.0

0.69

1.15

1.02

49.8

1.86

0.73

2.28

26.1

Merluccius hubbsi  (AC)

52.1

10.7

1.00

1.28

75.2

1.87

0.37

1.57

19.0

Prionotus punctatus (U, P, A)

54.0

0.06

0.27

1.85

66.3

1.07

< 0.03

0.47

17.0

Dules auriga (P, U)

19.7

0.15

0.10

0.40

38.1

1.21

< 0.03

0.07

17.7

Conodon nobilis (A)

156

0.00

0.26

3.46

75.4

< 0.02

2.30

0.51

16.2

Pagrus pagrus (P,U)

21.4

0.46

< 0.01

0.30

21.7

0.36

< 0.03

0.09

11.1

Cynoscion sp (M)

29.0

< 0.02

< 0.01

0.81

18.0

< 0.02

< 0.03

< 0.05

10.7

Macrodon ancylodon (M)

27.0

< 0.02

< 0.01

0.76

16.2

< 0.02

< 0.03

< 0.05

8.69

Menticirrhus littoralis (M)

20.0

< 0.02

< 0.01

0.58

8.80

< 0.02

< 0.03

< 0.05

8.53

Micropogonias furnieri (U)

23.6

0.18

< 0.01

0.50

21.8

1.40

< 0.03

0.23

12.6

Ophioscion punctatissimus (M)

34.0

< 0.02

< 0.01

0.85

12.8

< 0.02

< 0.03

< 0.05

9.88

Stellifer rastrifer (M, A)

Paralichthys patagonicus (P,U, SS, S)

94.8

17.2

0.06

0.28

0.42

0.17

1.91

0.19

49.5

32.8

< 0.02

2.14

< 0.03

< 0.03

0.05

0.08

11.1

11.1

Symphurus trewavasae (U)

21.4

0.29

0.08

0.41

26.2

0.68

< 0.03

< 0.05

15.1

Symphurus sp (M)

47.0

< 0.02

< 0.01

0.63

31.7

< 0.02

< 0.03

< 0.05

13.6

Paralonchurus brasiliensis (S, A, M)

61.3

0.13

0.35

1.59

34.7

0.69

< 0.03

0.41

11.4

Syacium sp (S)

26.8

0.19

0.27

0.25

23.6

2.50

< 0.03

0.07

13.9

Pfeifer et al. 1985   (wet weight)

-

0.03

0.53

0.53

-

0.65

-

0.93

11.8

Maximum Permissible BHM (wet weight)

-

1.0

0.1

30

-

-

-

8.00

100

Average

44.1

1.46

0.33

1.29

35.0

0.92

1.17

0.61

15.0

Standard deviation

38.3

2.51

0.28

1.33

26.2

0.66

3.96

0.75

4.82

Sampling sites along Rio de Janeiro State: Atafona (A); Arraial do Cabo (AC); Macaé (M); Parati(P); Baía de Guanabara (GB); Barra de Guaratiba (BG). Sampling sites in São Paulo State: Ubatuba (U); São Sebastião (SS) and Santos (S).