Relationship between metal enrichments and a biological adverse effects index in sediments from Todos Santos Bay, northwest coast of Baja California, México

Marine Pollution Bulletin 64 (2012) 405–409

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Relationship between metal enrichments and a biological adverse effects index in sediments from Todos Santos Bay, northwest coast of Baja California, México A. Muñoz-Barbosa ⇑, E.A. Gutiérrez-Galindo, L.W. Daesslé, M.V. Orozco-Borbón, J.A. Segovia-Zavala Instituto de Investigaciones Oceanológicas, Universidad Autónoma de Baja California, Km. 103 Carretera Tijuana-Ensenada, Ensenada, Baja California C.P. 22860, Mexico

a r t i c l e

i n f o

Keywords: Metal Enrichment factor Biological adverse effects index Marine sediment Baja California México

a b s t r a c t In 1992 and 2004, heavy metals concentrations were measured in surficial sediments from Todos Santos Bay, located in Ensenada, Baja California, Mexico. The aim was to search for relationships between metal enrichment factors and a biological adverse effects index. Unlike Ni, the elements Cd, Cu and Zn showed significant correlations (p < 0.05) between enrichment factors and the biological adverse effects index. Cu showed a 0.74:1 relationship, which means that any enrichment above 0.74 could represent biological adverse effects. On the other hand, Cd and Zn enrichments must be >5.5 and >1.5, respectively, in order for the sediments to be considered toxic. In general, data showed that most of the metal concentrations in Todos Santos Bay sediments could not cause adverse effects to biota. Only Ensenada’s harbor and the zone next to a dredging dumping site showed metal enrichments that could be toxic. Ó 2011 Elsevier Ltd. All rights reserved.

The concentration of metals found in sediments is the result of natural phenomena, anthropogenic activities or the combination of both. Therefore, different normalizing techniques have been used to tell the difference between the natural occurrences of metals in sediments from those of anthropogenic sources. Iron (Daskalakis and O’Conner,1995; Schiff and Weisberg, 1999), aluminum (Bruland et al., 1974), grain size (Horowitz and Elrick, 1987) and total organic carbon (Windom et al., 1989) are among the most widely used normalizers. However, the information yielded by these normalizers mostly indicates the degree of enrichment that the metals have in relation to the kind of normalization used. Enrichments calculated by the different normalizations are not necessarily indicators of toxicity levels. Thus, in the absence of toxicity studies along with measurements of heavy metals concentrations and/or enrichments in marine sediments, concentrations by themselves, even enrichments, cannot be used to suggest the probability of adverse effects on benthic biota. The northwest coast of Baja California, México has been extensively studied in many oceanographic aspects; particularly, the biogeochemistry of trace metals has been of great interest. Studies in seawater (Sañudo-Wilhelmy and Flegal, 1991, 1992; SegoviaZavala et al., 1998), organisms (Gutiérrez-Galindo and MuñozBarbosa, 2001; Muñoz-Barbosa et al., 2000; Segovia-Zavala et al., 2004), and sediments (Muñoz-Barbosa et al., 2004; Villaescusa-Celaya et al., 1997), have been carried out during the last two decades. Studies on sediments in this area have included spatial

⇑ Corresponding author. Tel.: +52 646 1744601; fax: +52 646 1745303. E-mail address: [email protected] (A. Muñoz-Barbosa). 0025-326X/$ - see front matter Ó 2011 Elsevier Ltd. All rights reserved. doi:10.1016/j.marpolbul.2011.11.023

distributions at a larger scale level (Muñoz-Barbosa et al., 2004), but also in bays (Gutiérrez-Galindo et al., 2007, 2008) and harbors (Huerta-Díaz et al., 2008). However, of all these studies only one evaluated a toxicity index (Huerta-Díaz et al., 2008); the others have studied only metal partitioning (Villaescusa-Celaya et al., 1997), concentrations and enrichments (Villaescusa-Celaya et al., 1997; Muñoz-Barbosa et al., 2004). Todos Santos Bay (TSB) is located 100 km south of the MexicoUSA border on the northwest coast of Baja California, Mexico. Most of the TSB 330 km2 (90%) is 10–50 m deep (Figs. 1 and 2). The city of Ensenada is located in the inner part of the bay; it has 400,000 inhabitants and the main economic activities are: manufacturing, tourism, fishing, and agriculture. During many years TSB has been environmentally affected by domestic and industrial effluents, fishing and boat traffic, and agricultural runoff (east of the bay). The city of Ensenada is one the few cities in Mexico that has the treatment capacity for the total amount of the water collected by its sewer system. The capacity o the three sewage treatment plants that discharge to TSB is 60, 250 and 500 l s1 for El Sauzal, El Gallo and El Naranjo plants, respectively (Waller-Barrera and MendozaEspinosa, 2009). El Sauzal plant discharges near the town of El Sauzal (Figs. 1 and 2), and El Gallo and El Naranjo plants discharge a combined effluent just outside Ensenada‘s harbor (Fig. 1 and 2). The State Commission of Public Services of Ensenada (CESPE, 2004), reported an average concentration 0.02, 0.2, 0.2, and 0.15 mg l1 of Cd, Cu, Ni, and Zn, respectively, for these sewage outfalls. The aim of the present study is to determine relationships between metal enrichment factors and a biological adverse effects index in surficial sediments from TSB, sampled one decade apart.

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USA

Punta San Miguel

MEXICO

El Sauzal

ic cif Pa

31.90

Oc n ea

22

20 18

17

31.85

Latitude (oN)

14

16

36 32

31

25

4 3 26

28

27

31.75

29 Pu nta Ba nd a

31.70 -116.90

-116.85

7

6 5

30

31.80

N

9

37

33

24

10

12 13 11 8

15

35

34

23

Ensenada`s harbor

19

21

-116.80

-116.75

2 1

-116.70

-116.65

-116.60

Longitude (oW) Fig. 1. Study area and location of sampling sites (filled circles) in 1992. Stars, filled triangle, and filled square indicate dredging dumping sites, El Sauzal treatment plant outfall, and El Gallo and El Naranjo treatment plants outfall, respectively.

USA

Punta San Miguel

MEXICO

16

El Sauzal

ic ci f Pa

31.90

Latitude (oN)

n ea Oc

Ensenada`s harbor

31.85

8

17 14

7

2

12

13 20

1

31.75

21

-116.85

4 3

11

19

N

31.70 -116.90

6

10

18 31.80

5

9

15

-116.80

Pu

nta B

-116.75

an da

-116.70

-116.65

-116.60

Longitude (oW) Fig. 2. Study area and location of sampling sites (filled circles) in 2004. Stars, filled triangle, and filled square indicate dredging dumping sites, El Sauzal treatment plant outfall, and El Gallo and El Naranjo treatment plants outfall, respectively.

During April 1992 and April 2004, sediments were sampled in 37 and 21 sites respectively (Figs. 1 and 2). Due to logistic problems we couldn’t sample as much sites in 2004 as we did in 1992. Consequently, considering that there is only a small sewage discharge (60 l s1) in the coastal zone from Punta San Miguel to Ensenada (Fig. 1 and 2), and knowing that the major heavy metals sources are in the vicinity of Ensenada‘s harbor, we decided to neglect the coastal zone from Punta San Miguel to Ensenada in 2004. The 2004 sampling sites spatial arrangement was designed taking

into account that the major pollution sources are the outfalls of El Gallo and El Naranjo sewage treatment plants, which are located just outside Ensenada‘s harbor (Fig. 1 and 2) and discharge a combined average flow (517 l s1) that is 90% of total sewage discharge to TSB. Therefore, we tried to concentrate a few sampling sites just outside the harbor and placed the remaining sites all over the bay. Samples were collected using a Van Veen grab covered with epoxy resin to prevent contamination. Using acid prewashed plastic spoons, 100 g of sediment were collected from the center of

A. Muñoz-Barbosa et al. / Marine Pollution Bulletin 64 (2012) 405–409

the grab and stored in acid pre-cleaned plastic containers. Approximately 1 g of dry sediment was weighed in a 30 ml prewashed Erlenmeyer flask, and 2.5 ml of HNO3 11 N and 10 ml of HCl 10 N (both trace metal grade) were added. Flask were then heated and maintained at constant reflux at 95 °C for 5 h. After the digestion, samples were placed in prewashed 50 ml polypropylene tubes and 20 ml of deionized water were added. For the 1992 samples, concentrations of metals were measured using a Smith Hieftje 12 Thermo Jarrel Ash (TJA) atomic absorption spectrophotometer. Air-acetylene flame was used for Cu, Ni and Zn and TJA graphite furnace, model CTF 188, equipped with aSmith Hieftje background correction and a FASTAC II deposition module for Cd. For the 2004 samples, Cu, Ni, and Zn analysis were analyzed by air-acetylene flame using a Varian SpectrAA 220 FS equipment. A Varian SpectrAA 880 atomic absorption spectrophotometer equipped with graphite furnace was used for Cd analysis. Marine sediment reference materials PACS-1 and MESS-1 from the National Research Council of Canada were used for quality control for 1992 samples (Table 1) and MESS-3 was used for 2004 samples (Table 2). Metal concentrations were compared with Effects Range-Low (ERL) NOAA sediment quality guidelines (SQG) developed by Long et al. (1995) to obtain an adverse effects index. These ERLs were developed by matching metal concentration in sediments with biological effects. It represents the concentration above which adverse effects on adjacent biota are observed. To obtain the index and know how much the metal concentrations exceeded or fell behind their respective ERL, each metal concentration was divided by the corresponding ERL.

AEI ¼

½Met ERL

where AEI = Adverse Effects Index [Met] = Metal concentration ERL = Effects Range-Low The ERLs 1.2, 34, 20.9, and 150 lg g1 reported by Long et al. (1995), were used for Cd, Cu, Ni, and Zn, respectively. If AEI 6 1 the metal concentration in the sample is not enough to produce ad-

Table 1 Analysis of sediments reference materials for the 1992 study.

Cd Cu Fe Ni Zn a b

PACS-1 Measureda (lg g-1) (n = 3)

Certifiedb (lg g1)

MESS-1 Measureda (lg g1) (n = 3)

Certifiedb (lg g1)

2.04 ± 0.20 467 ± 20 53,199 ± 1100 42.59 ± 3.1 923 ± 25

2.38 ± 0.20 452 ± 16 48,680 ± 839 44.10 ± 2.0 824 ± 22

0.57 ± 0.12 24.3 ± 4.5 30,767 ± 1450 25.3 ± 3.3 218 ± 16

0.59 ± 0.10 25.1 ± 3.8 30,424 ± 1295 29.5 ± 2.7 191 ± 17

Precision expressed as standard deviation. Precision expressed as 95% confidence limits.

Table 2 Analysis of sediments reference materials for the 2004 study.

Cd Cu Fe Ni Zn a b

MESS-3 Measureda (lg g1) (n = 3)

Certified (lg g1)

0.20 ± 0.03 27.2 ± 1.5 39,000 ± 2200 36.4 ± 1.8 140 ± 5

0.24 ± 0.01 33.9 ± 1.6 43,400 ± 1100 46.9 ± 2.2 159 ± 8

Precision expressed as standard deviation. Precision expressed as 95% confidence limits.

b

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verse effects to the biota nearby. If AEI P 1 the metal concentration in the sample could produce adverse effects. On the other hand, the average composition of shale reported by Li and Schoonmaker (2005) was used to estimate metal enrichment factors, which were calculated according to Cevik et al. (2009):

EFMe ¼

Me=FeSample Me=FeShale

If EFMe < 1, sample is impoverished in relation with the average shale composition; if EFMe > 1, sample is enriched in relation with the average shale composition; and if EFMe = 1, sample has the same value as the reference (normalized with iron). It is common practice to calculate metal enrichments using background pre-industrial concentrations, however, since such information in not available for our study region, average shale composition (also widely applied) was used instead (Huerta-Diaz et al., 2008; Li and Schoonmaker, 2005). Iron concentrations were used for the calculation of enrichment factors because Al data was not available for the 1992 study. Nevertheless, significant correlations (p < 0.05) were found between Fe concentrations and grain size in both 1992 (r = 0.75) and 2004 (r = 0.91) studies, this suggest that Fe is a good normalizing element for this region. In order to assess the relationship between a biological adverse effects index and metal enrichments, linear regressions between metal AEI’s and their correspondent EFMe were made for both data sets. Figs. 3 and 4 show the regressions for 1992 and 2004, respectively. The horizontal dotted line intersecting the graphs’ vertical axis indicates the value that corresponds to AEI = 1 for a given metal, and the vertical dotted line intersecting the horizontal axis is its correspondent EFMe value. This means that any point below the horizontal dotted line represents a value which AEI < 1, thus, it could not generate adverse effects. On the other hand, points above the horizontal dotted line represent AEI > 1, thus adverse effects are likely. All the 1992 data for Cd showed AEIs < 1 (Fig. 3a), suggesting that, despite having EFsCd > 3, it is not likely to find adverse biological effects due to the presence of Cd in sediments from TSB for 1992. Regression between EFCd and Cd AEI was significant (r = 0.94, p < 0.05) and indicates that Cd enrichments were not enough to provoke adverse effects in sediments; in order to do so the EFs must be >5.4 (Fig. 3a). Results for 2004 data are similar to those of 1992: most of the AEIs were <1, regression between EFCd and Cd AEI was significant (r = 0.92, p < 0.05), and according to this relationship enrichments should be >5.8 to cause adverse effects. However, in 2004 the AEI for sample 20 was >1 (Fig. 4a). Sampling site 20 is located adjacent to an area where high concentrations of Cd have been found in sediments and organisms which were associated with upwelling processes (Gutiérrez-Galindo and MuñozBarbosa, 2001; Muñoz-Barbosa et al., 2004). The Cd biogeochemical cycle in the oceans is closely linked to that of organic matter. Due to its involvement in a regeneration cycle similar to that of phosphates and nitrates, Cd shows a nutrient-like spatial distribution in the oceans (Bruland, 1983). In Baja California, large amounts of Cd are carried to the surface coastal waters by upwelling events. It has been found that these waters have up to five times more Cd than those 50 km offshore (Segovia-Zavala et al., 1998). Moreover, 99% of the Cd in surface waters (1 m depth) on the northwest coast of Baja California is related to physical processes, such as upwelling and advection, and only 1% is related to anthropogenic sources (Sañudo-Wilhelmy and Flegal, 1991, 1996). Site 20 is very close to a region where upwelling regularly occurs, this suggests that high Cd concentrations and enrichments in sediments in this area could be attributed to upwelling and not to anthropogenic sources.

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(a)

(b) 1.2

4

r=0.94

r=0.93

1.0

3

AEI

AEI

0.8 0.6 0.4

2 1

0.2 0

0.0 0

1

2

3

4

5

6

0.0

0.4

(c)

0.8

1.2

1.6

EF

EF

(d)

1.4

r=0.42

1.4 1.2

1.2

r=0.18

1.0 0.8

AEI

AEI

1.0 0.8

0.6 0.4

0.6

0.2 0.4

0.0

0.2 0.2

0.4

0.6

0.8

1.0

1.2

-0.2 0.4

1.4

0.6

0.8

1.0

1.2

1.4

1.6

1.8

EF

EF

Fig. 3. Relationships between Enrichment Factors (EF) and Adverse Effects Index (AEI) for Cd (a), Cu (b), Ni (c), and Zn (d) in samples collected in 1992.

(a)

(b) 1.4

2.0

r=0.92

1.6

1.2

r=0.73

1.0

AEI

AEI

1.2 0.8

0.8 0.6 0.4

0.4

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0.0

0.0 0

2

4

6

8

0.2

0.4

EF

0.6

0.8

1.0

1.2

EF

(c)

(d) 1.4 1.2

1.2

r=0.26

1.0

0.8

0.8

AEI

AEI

r=0.60

1.0

0.6

0.6

0.4

0.4

0.2

0.2

0.0

0.0 0.4

0.6

0.8

1.0

1.2

1.4

EF

0.8

1.2

1.6

2.0

2.4

EF

Fig. 4. Relationships between Enrichment Factors (EF) and Adverse Effects Index (AEI) for Cd (a), Cu (b), Ni (c), and Zn (d) in samples collected in 2004.

With the exception of sample 9, all the 1992 Cu data showed AEIs < 1 (Fig. 3b). Sampling site 9 is located in the inner part of Ensenada’s harbor (Fig. 1). Huerta-Díaz et al. (2008), also found higher metal concentrations in Ensenada’s harbor and suggested that finer grain size, higher shipping activity and low hydrodynamic energy are responsible for this. Regression between EFCu and Cu AEI was significant (r = 0.93, p < 0.05). However, in contrast to Cd, this relationship showed that it is not necessary for the Cu to be enriched in order to cause adverse effects. According to the 1992 relationship between EFCu and Cu AEI, Cu EF’s lower than 1 (above 0.74) could provoke adverse effects (Fig. 3b). On the other hand, all the 2004 Cu AEIs were <1, which suggests that adverse effects are not probable (Fig. 4b). However it has to be taken into account that in the 2004 study there was no sampling inside the

harbor, which is the most contaminated location of the study area and is the place were the highest Cu concentration was found in 1992. The 2004 EFCu–Cu AEI regression was significant (r = 0.73, p < 0.05). This relationship is the only one of both 1992 and 2004 studies, where an EF = 1 corresponds to an AEI = 1. This suggests that any Cu enrichments (EFCu > 1) in sediment could cause adverse effects. The EFNi–Ni AEI regressions for 1992 and 2004 were not significant (r = 0.42, p < 0.05 and r = 0.26, p < 0.05, respectively) (Figs. 3c and 4c, respectively); this may be due to impoverishment-caused variability of Ni in the sediments. Nickel is known to have a great affinity for Mn-oxides, which can be dissolved in reductive environments. As a consequence of the Mn reductive dissolution, Ni could be released to the overlying water column causing its deple-

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tion in the sediments. Only three sites in 1992 (9, 23 y 33) and two sites in 2004 (19 and 20) showed a Ni AEI > 1. Sample 9 for1992 was taken in the inner part of Ensenada’s Harbor (Fig. 1), in which, as mentioned before, finer grain size, more shipping activity, and less hydrodynamic energy could be responsible of this situation. On the other hand, sites 23 and 33 in 1992 (Fig. 1), and 19 in 2004 (Fig. 2), are in the vicinity of the area where products of harbor’s dredging are disposed. Finally, EFZn–Zn AEI regressions for 1992 and 2004 were significant (r = 0.78, p < 0.05; and r = 0.60, p < 0.05) (Figs. 3d and 4d, respectively). As in the case of Cu, only sample 9 for 1992 showed an AEI > 1(Fig. 3d). These relationships show that Zn enrichments in 1992 and 2004 sediments have to be >1.55 and >2.25, respectively, in order to provoke adverse biological effects. In conclusion, Cd, Cu and Zn showed significant relationships between EFs and AEIs, and Ni did not. Cu showed a 0.74:1 relationship, which means that any enrichment above 0.74 (Fig. 3b), could corresponds to toxicity. On the other hand, Cd and Zn enrichments must be >5.5 and >1.5, respectively (Fig. 3a y d, respectively) in order for the sediments to be considered toxic. In general, the results showed that most of the TSB sediments are free from metal concentrations that could provoke adverse effects to the surrounding fauna and flora. Only Ensenada’s harbor and the zone next to the dredged material dumping site showed metal enrichments that could be toxic.In general, regressions between metal‘s EF’s and AEI’s were very similar between 1992 and 2004. Cadmium showed that for an AEI = 1 the corresponding EF’s were 5.4 and 5.8 for 1992 and 2004, respectively (Figs. 3a and 4a). Similarly, Cu regressions showed EF’s of 0.74 and 1.0, for 1992 and 2004, respectively, corresponding to an AEI = 1 (Figs. 3b and 4b). Moreover, even though Ni correlations were not significant (p < 0.05), both regressions (1992 and 2004) showed very similar enrichment factors (between 1.1 and 1.2, respectively) corresponding to AEI = 1 (Figs. 3c and 4c). On the other hand the enrichment factors of Zn corresponding to an AEI = 1 were 1.5 and 2.6 for 1992 and 2004, respectively (Figs. 3d and 4d). This suggests a relatively lower regression slope for 2004 when comparing with 1992, indicating that higher Zn enrichments would be needed to get to the non toxic–toxic threshold of AEI = 1 in 2004. Acknowledgments This research was supported by Grants from Coordinación de Posgrado e Investigación, Universidad Autónoma de Baja California. References Bruland, K., Bertine, K., Koide, M., Goldberg, E., 1974. History of metal pollution in Southern California Coastal Zone. Environmental Science and Technology 8, 425–432. Bruland, K. W., 1983. Trace elements in sea-water, in: Riley, J. P., Chester, R. (Eds.), Chemical Oceanography, London, England pp. 157-220. CESPE (State Comission of Public Services of Ensenada), 2004. Aprovechamiento de las aguas residuales tratadas en en estado de Baja Californias. Segundo encuentro Nacional de Estados y Municipios por una Cultura del Agua, pp. 52

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