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Assessment of temporal variation and sources of PCBs in the sediments of Mediterranean Sea, Mersin Bay, Turkey
Marine Pollution Bulletin 62 (2011) 173–177
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Marine Pollution Bulletin journal homepage: www.elsevier.com/locate/marpolbul
Baseline
Edited by Bruce J. Richardson The objective of BASELINE is to publish short communications on different aspects of pollution of the marine environment. Only those papers which clearly identify the quality of the data will be considered for publication. Contributors to Baseline should refer to ‘Baseline—The New Format and Content’ (Mar. Pollut. Bull. 60, 1–2).
Assessment of temporal variation and sources of PCBs in the sediments of Mediterranean Sea, Mersin Bay, Turkey _ _ ˘ lu a,⇑ Kadir Gedik a,b, Ipek Imamog a b
Department of Environmental Engineering, Middle East Technical University, 06531 Ankara, Turkey Department of Environmental Engineering, Akdeniz University, 07058 Antalya, Turkey
a r t i c l e
i n f o
Keywords: Polychlorinated biphenyls Aroclors Receptor models Chemical mass balance
a b s t r a c t Information on temporal distribution of polychlorinated biphenyls (PCBs) in the coastal sediments of Mediterranean Sea, Mersin was compiled using data published between 1980 and 2009, and the present study. The first congener specific PCB results from the region yield concentration levels of R41PCBs in sediments ranging from 0.61 to 1.04 ng g 1. Sediment profiles show penta-, hexa- and hepta-chlorobiphenyls, specifically, #149 and 153 as the most abundant congeners in all samples. Comparison of total PCB concentrations over time suggests no recent PCB input to the region. Using congener specific PCB data for the region, identity and contribution of PCB sources were also predicted using a chemical mass balance -based (CMB) receptor model. The CMB model identified Aroclor 1260 to be the major PCB source in coastal sediments. The potential sources for the PCBs were briefly discussed in terms of their use in various industrial applications. Ó 2010 Elsevier Ltd. All rights reserved.
The program for the assessment and control of pollution in the Mediterranean region (MEDPOL) was adopted within the scope of Barcelona Convention to protect and effective environmental management of Mediterranean Sea in 1975. Over the past decades, many studies were performed for the assessment of organic and inorganic pollutants in biotic and abiotic compartments of the Mediterranean Sea (Albaiges, 2005; Basturk et al., 1980; Dogan-Saglamtimur and Kumbur, 2010; Gomez-Gutierrez et al., 2007; Karakoc et al., 1997; Sanin et al., 1992). Uncertainties still exist about the impact of point and non-point sources containing persistent pollutants in the Mediterranean basin (Albaiges, 2005) for many riparian countries. Polychlorinated biphenyls (PCBs) are xenobiotic compounds of anthropogenic origin that are ubiquitous, toxic and persistent in
⇑ Corresponding author. Tel.: +90 312 210 5861; fax: +90 312 210 2646. _ E-mail addresses: [email protected] (K. Gedik), [email protected] (I. _ ˘ lu). Imamog 0025-326X/$ - see front matter Ó 2010 Elsevier Ltd. All rights reserved. doi:10.1016/j.marpolbul.2010.11.014
the environment (Erickson, 1997). A substantial amount of information on the presence of PCBs in sediments and marine biota of the Mediterranean coasts of Turkey was obtained from MEDPOL monitoring studies between 1975 and 1980 (UNEP, 1986a,b), and from 2003 to present date (Tug˘rul et al., 2005, 2007, 2008, 2009; Yemeniciog˘lu, 2003; Yemeniciog˘lu et al., 2004, 2006). PCBs were analyzed on Aroclor basis and there is no individual PCB congener data reported for the Mediterranean coasts of Turkey (Gomez-Gutierrez et al., 2007). Thus, the objective of this study is to assess the current state of PCB levels and their sources in the sediments of Mersin Bay. Identity and contribution of PCB sources are investigated using chemical mass balance (CMB) receptor model which is recently used for quantitative identification of PCB sources in sediments (Honda et al., 2008; Imamoglu and Christensen, 2002; Imamoglu et al., 2002; Ogura et al., 2005) to preclude any legislative steps for prevention of further pollution. Sampling locations including points along the coast and within the Bay were chosen in parallel to MEDPOL sea quality monitoring
174
_ Imamog _ ˘ lu / Marine Pollution Bulletin 62 (2011) 173–177 K. Gedik, I.
Fig. 1. Sampling sites in coastal sediments of Mediterranean Sea, Mersin.
stations in the Northeastern Mediterranean. Mersin is a touristic, an industrial and heavily urbanized city with a shoreline of 321 km in the south of Turkey. The Mersin Bay system receives freshwater from Seyhan, Tarsus, Efrenk, Lamas, and Göksu Rivers carrying most of the domestic, agricultural and industrial wastes into the Bay (Ozsoy et al., 2008). Accordingly, surface sediments (upper 10 cm) were taken in January, 2009 using a grab sampler (Fig. 1). Samples were homogenized and placed into clean amber glass jars with Teflonlined lids and kept in coolers during sampling. Upon return to the laboratory, samples were split into two fractions of which, in the first fraction, moisture and organic matter content were determined gravimetrically by drying for 24 h at 105 °C and for 4 h at 550 °C (Heiri et al., 2001), respectively. The other fraction was stored at 20 °C until extraction for PCB analysis. The detailed procedure including extraction, cleanup and instrumental analysis is given elsewhere (Gedik et al., 2010). Briefly, after spiking with 2,4,5,6-tetrachloro-m-xylene surrogate standard, freeze dried samples (20 g, <1 mm size fraction) were soxhlet extracted with 300 mL of n-hexane/acetone (1:1 v/v) mixture for 17 h. Sulfur was eliminated by the addition of acid activated granular copper into solvent flask. After solvent concentration by Kuderna–Danish (KD) evaporator, extract was mixed with sulfuric acid (1:1) to remove interfering substances. Then, top clear extract was charged on a column packed with 3.05 g of silica gel (activated for 16 h at 130 °C and deactivated to 4.5% with deionized water), and topped with 3 cm of purified sodium sulfate. A total of 125 mL hexane was then added to elute the PCBs retained in the column. Finally, the extract was concentrated to 5–6 mL via KD evaporator and then to 1 mL using a gentle stream of nitrogen. The final concentrated extracts in n-hexane were analyzed on congener basis using an Agilent 6890N series Gas Chromatograph (GC) coupled with an Agilent 5973 inert mass selective detector (MSD) working at electron impact ionization mode. Congeners were separated on a HP-5MS capillary column (30 m length 0.25 mm internal diameter, 0.25 lm film thickness). Aroclor-based analysis was carried out with a Varian CP-3800 series Gas Chromatograph (GC) coupled with an electron capture detector (ECD). Chromatographic separation was performed on a WCOT fused silica CP-Sil 8 CB Varian capillary column (30 m length 0.32 mm internal diameter, 0.25 lm film thickness). Quality control/assurance protocols include regular check of blanks, analysis of laboratory control samples, matrix spike/matrix
spike duplicates (MS/MSD), and the certified reference material concurrently with the environmental samples. A target analyte peak was reported only if the signal exceeded three times the baseline noise. For 1 lL injection, instrument detection limit (IDL) was calculated as 0.1 pg and 0.4 pg for congener specific and Aroclorbased (Aroclor 1016 + Aroclor 1260) analysis, respectively. A total of 41 individual PCB congeners were analyzed (IUPAC Nos. 17, 18, 28, 31, 33, 44, 49, 52, 70, 74, 82, 87, 95, 99, 101, 105, 110, 118, 128, 132, 138, 149, 151, 153, 158, 169, 170, 171, 177, 180, 183, 187, 191, 194, 195, 199, 201, 205, 206, 208, and 209). In cases where the compounds were not detected in any of the samples, they were removed from the data set. Congeners that were not detected in more than 20% of the samples were replaced by one-half the corresponding detection limit due to small sample size (Clarke, 1998). The recoveries of surrogate standard were 88 ± 14% in all samples. A method blank was analyzed every 10 samples of the same batch. The relative percent difference on MS/MSD samples was typically lower than 5%. The analytical procedure was further validated by analyzing a certified reference material, which is a natural sandy loamy sediment containing PAHs, pesticides, and seven indicator PCBs (CRM141-050; RTC, USA). The results of individual PCB congeners (#28, 52, 101, 118, 138, 153, and 180) deviated less than 13% from the target values. Summary results are presented in Table 1 for the individual congeners and total PCB levels together with organic matter content and depth data for the sediments of Mersin Bay. Samples show PCB levels ranging from 0.61 to 1.04 ng g 1 on congener basis, and from 0.92 to 4.97 ng g 1 on Aroclor basis. No particular trend could be observed for RPCB distribution between offshore sediments, those collected close to the shoreline or far from the industrial region (M1 and M11). The total PCB levels in samples were not correlated with organic matter content (r2 6 0.03). Compared to PCB concentrations reported in coastal environments, the levels in marine sediments of Mersin Bay are at the low end of ranges of PCBs observed in sediments within an area of 10 km from the principal Mediterranean urban (>100,000 inhabitants) centers (Gomez-Gutierrez et al., 2007). The results of this study, on the other hand, are lower than those observed in marine sediments of Turkey (Gedik and Imamoglu, 2010) and those reported values for other industrial regions around the world (Ashley and Baker, 1999; Frignani et al., 2001; Hartmann et al., 2004; Hong et al., 2005; Howell et al., 2008). Lastly, an assessment of the ecotoxicological aspect of PCB contamination
_ Imamog _ ˘ lu / Marine Pollution Bulletin 62 (2011) 173–177 K. Gedik, I.
175
Table 1 Congener specific PCBs in coastal sediments of Mediterranean Sea, Mersin Bay. Sample
a b
Depth (m)
OMa (%)
PCBs (ng g
1
dry weight)
#95
#101
#110
#132
#138
#149
#153
#180
#187
RConb
RAroclor
M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11
14 9.8 6.5 7 8 7 11 10 9 5.5 20
7.9 8.4 6.4 7.5 2.7 4.0 10.8 7.1 3.8 3.8 3.5
0.081 <0.003 <0.003 <0.003 0.071 0.082 <0.003 <0.003 0.073 <0.003 0.093
0.110 0.128 0.152 <0.003 0.073 0.148 <0.003 <0.003 0.073 0.114 0.112
<0.003 0.132 0.160 <0.003 <0.003 <0.003 <0.003 <0.003 0.076 0.104 <0.003
<0.003 0.161 <0.003 <0.003 0.038 <0.003 <0.003 0.134 0.065 0.115 <0.003
0.113 <0.003 <0.003 <0.003 0.151 0.141 <0.003 0.205 0.120 <0.003 0.095
0.115 0.114 0.126 0.170 0.124 0.171 0.343 0.184 0.119 0.117 0.157
0.114 0.277 0.199 0.240 0.125 0.158 0.384 0.289 0.194 0.139 0.247
0.091 0.149 <0.003 0.132 0.141 0.094 <0.003 <0.003 0.129 0.086 0.100
0.064 0.076 0.066 0.054 0.055 0.063 0.130 0.089 0.075 0.069 0.043
0.691 1.040 0.712 0.607 0.778 0.860 0.871 0.910 0.923 0.747 0.850
1.916 2.028 0.920 1.050 2.934 3.697 4.967 3.538 3.260 2.683 1.030
Mean Median
9.8 9.0
6.0 6.4
0.038 0.003
0.083 0.110
0.044 0.003
0.048 0.003
0.076 0.095
0.158 0.126
0.215 0.199
0.084 0.094
0.071 0.066
0.817 0.850
2.547 2.683
Organic matter content. Values below detection limits were considered to be equal to one-half the detection limit.
in the region may be performed by sediment quality guidelines developed by Long et al. (1995), namely, the effect range low (ERL, 22.7 ng g 1) and effect range median (ERM, 180 ng g 1). The aim of this guideline is to evaluate the potential toxicity of a particular chemical to benthic organisms in marine and estuarine sediments. Accordingly, the concentrations observed in Mersin Bay are below these guidelines, indicating no major ecotoxicological risk from PCBs in these sediments. Concentrations of individual PCB congeners were lower than 0.5 ng g 1 (Table 1). Among the 41 congeners analyzed, only a few of them were consistently detected and processed (Clarke, 1998) in samples. These are the members of penta-, hexa- and hepta-chlorobiphenyls, which are the major homolog groups in most environmental samples (Gomez-Gutierrez et al., 2007). PCBs #149 and 153 are the most abundant congeners, followed by PCBs #101, 138, 180, 187. Typically, the weight percent of these PCB congeners are in the range of 2–11% in Aroclor 1254 and 1260 formulations (Frame et al., 1996) which were widely used as dielectric fluids in transformers and capacitors. Gomez-Gutierrez et al. (2007) compiled information on the levels of persistent organic pollutants including PCBs in the Mediterranean sediments. In comparison to their study, the concentration of PCBs #153 and 180 in this study was about two orders of magnitude smaller than the median concentrations observed in harbor sediments in the Mediterranean Sea.
Fig. 2. Temporal PCB levels in the coastal sediments of Mediterranean Sea in Mersin compiled from Basturk et al. (1980), Tug˘rul et al. (2005, 2007, 2009), Yemeniciog˘lu (2003), Yemeniciog˘lu et al. (2004, 2006) and the present study*.
The temporal variation of PCB levels in sediments around the study area is given in Fig. 2 by introducing concentrations as they appear in the respective studies. As seen from Fig. 2, the results of this study are generally in good agreement with the total PCB concentrations observed 30 years ago in sediments along the Mersin Bay (Basturk et al., 1980). The level of PCBs in the Mediterranean coasts of Turkey has been monitored systematically since 2003. PCBs were not detected above the limit of detection at the beginning of the monitoring program and following year (2004). The findings of 2005 showed some unexpectedly high concentrations for which the reason is unknown, and no PCB data was reported in 2008 survey for the region (Tug˘rul et al., 2008). Comparing concentrations of PCBs (e.g. Aroclors, homologs, or individual congeners) even of the same unit (e.g. ng g 1 dry weight) may become difficult with PCB data. On the other hand, use of surface sediment rather than dated cores as temporal indicators may complicate data comparison due to influence of sedimentation on pollutant concentrations (Gomez-Gutierrez et al., 2007). Accordingly, the temporal trend of RPCB levels in sediment samples collected in the period from 1978 to 2009 showed decreasing trend for the region (r = 0.17 at all points excluding 2005 data in Fig. 2 using the linear model considering log-transformed data at 95% significance level). Considering the half-lives of PCBs estimated in the range of 6–30 years (Ritter et al., 1995) in soils or sediments, an overview of temporal variation of PCBs in sediments of Mersin Bay suggests no recent PCB input to the region. Moreover, the concentrations observed in Mersin Bay are consistent with typical background values established in the interval of 1–5 ng g 1 R7PCBs with a median of 2 ng g 1 for Mediterranean sediments (Gomez-Gutierrez et al., 2007). Acquisition of the first congener specific PCB data for the region enabled investigation of the potential sources of these pollutants using a receptor model, namely chemical mass balance (CMB). In CMB modeling, Aroclor formulations (Frame et al., 1996) were used as fingerprints of sources with justification for the selection of PCB sources (e.g. Clophen, Phenoclor) and modeling details are given elsewhere (Gedik et al., 2010). The apportionment results together with the uncertainties and goodness of fit statistics for samples around the Mersin Bay are presented in Table 2. The overall average of goodness of fit parameters, R2 and R.E. is 0.943 and 0.224, respectively, for the modeled samples. Both measures indicate satisfactory prediction of environmental PCB profiles. Furthermore, VIF values calculated for the corresponding sample–source pairs were in the range of 1.18–4.09 with a median of 1.60, indicating insignificant collinearity among source profiles. The major PCB source identified by the model at marine sediments is Aroclor 1260 with percent contributions ranging from 60.4 to 87.9. This can be explained by the identity of congeners
_ Imamog _ ˘ lu / Marine Pollution Bulletin 62 (2011) 173–177 K. Gedik, I.
176 Table 2 Chemical mass balance model results and statistics. Samplea
Apportionment results (%) Ar1016
M1 M2 M3 M5 M6 M8 M9 M10 M11 a b c
Ar1242
Model statistics Ar1248
Ar1254
19.6 ± 6.00 35.7 ± 13.7 40.3 ± 9.10 12.1 ± 4.10 9.10 ± 8.60 39.6 ± 18.7 2.90 ± 1.50
27.0 ± 17.1 20.0 ± 5.00 38.9 ± 13.2
24.9 ± 9.10
Ar1260
v2b
R2
R.E.c
80.4 ± 13.1 64.3 ± 18.6 59.7 ± 10.8 87.9 ± 12.8 63.8 ± 18.9 60.4 ± 21.3 77.1 ± 10.9 61.1 ± 16.2 75.1 ± 16.2
6 5 3 6 5 3 6 5 6
0.950 0.900 0.972 0.962 0.937 0.959 0.976 0.917 0.915
0.197 0.338 0.133 0.148 0.281 0.215 0.107 0.302 0.293
Some of the samples were not included into model due to df P 3 constraint. v2 = df. Relative error corresponding to v2 = df.
observed in coastal sediments and also, in general, PCB profiles in sediments resemble to that of Aroclor 1260 formulation (Burns and Villeneuve, 1987). Aroclor 1260 is known to be extensively used in transformers, hydraulic fluids, synthetic resins and dedusting agents (Durfee et al., 1976). Such applications may find many uses in Mersin Organized Industrial District in the Bay. Relatively high contributions from Aroclor 1254 were also predicted, with minor contribution from Aroclor 1248, 1242 and 1016 to a small number of samples. Aroclor 1242 is identified only in M3, M5 and M11, which are located close to Deliçay creek and Göksu River, reflecting the dissimilar nature of wastes potentially transported by the aquatic systems from the nearby industries. Aroclor 1242 is known to find use in many partially open/open applications such as plasticizers, carbonless copy paper production, adhesives. For samples off the Port of Mersin, on the other hand, Aroclor 1254 and to some extent Aroclor 1248 contribution is revealed in addition to Aroclor 1260. Although no record or chemical inventory for industries located throughout the coast line in Mersin Bay is present, these mixtures having a variety of uses in open as well as closed applications reflects potential polluting sources in the area. Yet, low concentrations of PCBs point to minor use of these chemicals by industries. CMB findings also showed the influence of rivers in terms of PCB loads into the marine system by point and diffuse land-based sources in the region. In most model calculations, the PCB pattern can be reproduced using Aroclors to a good extent, excluding the deviations in congeners #132, 153, 180 and 187 in general. The disagreement between measured and predicted congeners may indicate modification of PCB profiles from source to receptor. This may be due to a number of environmental mechanisms acting on the compounds as well as the samples, i.e. differential solubilization/desorption of low chlorinated PCBs, enrichment of highly chlorinated congeners in the sediments, loss through air–water exchange, etc. A depth-wise investigation of PCB levels, such as using dated sediment cores can enable a more thorough understanding of past contamination in the region.
Acknowledgements This study is funded by the Turkish Scientific and Research _ Council (TÜBITAK: CAREER Project No. 104I126), and also supported by the Turkish Prime Ministry-State Planning Organization and METU Research Fund (BAP-DPT 2002K120510). We would like to thank Dr. Mustafa Odabasßı (Department of Environmental Engineering, Dokuz Eylul University) for his valuable support in GC/MS analysis and Dr. Süleyman Tug˘rul (Institute of Marine Sciences, METU) for his help during sampling of marine sediments.
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Contents lists available at ScienceDirect
Marine Pollution Bulletin journal homepage: www.elsevier.com/locate/marpolbul
Baseline
Edited by Bruce J. Richardson The objective of BASELINE is to publish short communications on different aspects of pollution of the marine environment. Only those papers which clearly identify the quality of the data will be considered for publication. Contributors to Baseline should refer to ‘Baseline—The New Format and Content’ (Mar. Pollut. Bull. 60, 1–2).
Assessment of temporal variation and sources of PCBs in the sediments of Mediterranean Sea, Mersin Bay, Turkey _ _ ˘ lu a,⇑ Kadir Gedik a,b, Ipek Imamog a b
Department of Environmental Engineering, Middle East Technical University, 06531 Ankara, Turkey Department of Environmental Engineering, Akdeniz University, 07058 Antalya, Turkey
a r t i c l e
i n f o
Keywords: Polychlorinated biphenyls Aroclors Receptor models Chemical mass balance
a b s t r a c t Information on temporal distribution of polychlorinated biphenyls (PCBs) in the coastal sediments of Mediterranean Sea, Mersin was compiled using data published between 1980 and 2009, and the present study. The first congener specific PCB results from the region yield concentration levels of R41PCBs in sediments ranging from 0.61 to 1.04 ng g 1. Sediment profiles show penta-, hexa- and hepta-chlorobiphenyls, specifically, #149 and 153 as the most abundant congeners in all samples. Comparison of total PCB concentrations over time suggests no recent PCB input to the region. Using congener specific PCB data for the region, identity and contribution of PCB sources were also predicted using a chemical mass balance -based (CMB) receptor model. The CMB model identified Aroclor 1260 to be the major PCB source in coastal sediments. The potential sources for the PCBs were briefly discussed in terms of their use in various industrial applications. Ó 2010 Elsevier Ltd. All rights reserved.
The program for the assessment and control of pollution in the Mediterranean region (MEDPOL) was adopted within the scope of Barcelona Convention to protect and effective environmental management of Mediterranean Sea in 1975. Over the past decades, many studies were performed for the assessment of organic and inorganic pollutants in biotic and abiotic compartments of the Mediterranean Sea (Albaiges, 2005; Basturk et al., 1980; Dogan-Saglamtimur and Kumbur, 2010; Gomez-Gutierrez et al., 2007; Karakoc et al., 1997; Sanin et al., 1992). Uncertainties still exist about the impact of point and non-point sources containing persistent pollutants in the Mediterranean basin (Albaiges, 2005) for many riparian countries. Polychlorinated biphenyls (PCBs) are xenobiotic compounds of anthropogenic origin that are ubiquitous, toxic and persistent in
⇑ Corresponding author. Tel.: +90 312 210 5861; fax: +90 312 210 2646. _ E-mail addresses: [email protected] (K. Gedik), [email protected] (I. _ ˘ lu). Imamog 0025-326X/$ - see front matter Ó 2010 Elsevier Ltd. All rights reserved. doi:10.1016/j.marpolbul.2010.11.014
the environment (Erickson, 1997). A substantial amount of information on the presence of PCBs in sediments and marine biota of the Mediterranean coasts of Turkey was obtained from MEDPOL monitoring studies between 1975 and 1980 (UNEP, 1986a,b), and from 2003 to present date (Tug˘rul et al., 2005, 2007, 2008, 2009; Yemeniciog˘lu, 2003; Yemeniciog˘lu et al., 2004, 2006). PCBs were analyzed on Aroclor basis and there is no individual PCB congener data reported for the Mediterranean coasts of Turkey (Gomez-Gutierrez et al., 2007). Thus, the objective of this study is to assess the current state of PCB levels and their sources in the sediments of Mersin Bay. Identity and contribution of PCB sources are investigated using chemical mass balance (CMB) receptor model which is recently used for quantitative identification of PCB sources in sediments (Honda et al., 2008; Imamoglu and Christensen, 2002; Imamoglu et al., 2002; Ogura et al., 2005) to preclude any legislative steps for prevention of further pollution. Sampling locations including points along the coast and within the Bay were chosen in parallel to MEDPOL sea quality monitoring
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_ Imamog _ ˘ lu / Marine Pollution Bulletin 62 (2011) 173–177 K. Gedik, I.
Fig. 1. Sampling sites in coastal sediments of Mediterranean Sea, Mersin.
stations in the Northeastern Mediterranean. Mersin is a touristic, an industrial and heavily urbanized city with a shoreline of 321 km in the south of Turkey. The Mersin Bay system receives freshwater from Seyhan, Tarsus, Efrenk, Lamas, and Göksu Rivers carrying most of the domestic, agricultural and industrial wastes into the Bay (Ozsoy et al., 2008). Accordingly, surface sediments (upper 10 cm) were taken in January, 2009 using a grab sampler (Fig. 1). Samples were homogenized and placed into clean amber glass jars with Teflonlined lids and kept in coolers during sampling. Upon return to the laboratory, samples were split into two fractions of which, in the first fraction, moisture and organic matter content were determined gravimetrically by drying for 24 h at 105 °C and for 4 h at 550 °C (Heiri et al., 2001), respectively. The other fraction was stored at 20 °C until extraction for PCB analysis. The detailed procedure including extraction, cleanup and instrumental analysis is given elsewhere (Gedik et al., 2010). Briefly, after spiking with 2,4,5,6-tetrachloro-m-xylene surrogate standard, freeze dried samples (20 g, <1 mm size fraction) were soxhlet extracted with 300 mL of n-hexane/acetone (1:1 v/v) mixture for 17 h. Sulfur was eliminated by the addition of acid activated granular copper into solvent flask. After solvent concentration by Kuderna–Danish (KD) evaporator, extract was mixed with sulfuric acid (1:1) to remove interfering substances. Then, top clear extract was charged on a column packed with 3.05 g of silica gel (activated for 16 h at 130 °C and deactivated to 4.5% with deionized water), and topped with 3 cm of purified sodium sulfate. A total of 125 mL hexane was then added to elute the PCBs retained in the column. Finally, the extract was concentrated to 5–6 mL via KD evaporator and then to 1 mL using a gentle stream of nitrogen. The final concentrated extracts in n-hexane were analyzed on congener basis using an Agilent 6890N series Gas Chromatograph (GC) coupled with an Agilent 5973 inert mass selective detector (MSD) working at electron impact ionization mode. Congeners were separated on a HP-5MS capillary column (30 m length 0.25 mm internal diameter, 0.25 lm film thickness). Aroclor-based analysis was carried out with a Varian CP-3800 series Gas Chromatograph (GC) coupled with an electron capture detector (ECD). Chromatographic separation was performed on a WCOT fused silica CP-Sil 8 CB Varian capillary column (30 m length 0.32 mm internal diameter, 0.25 lm film thickness). Quality control/assurance protocols include regular check of blanks, analysis of laboratory control samples, matrix spike/matrix
spike duplicates (MS/MSD), and the certified reference material concurrently with the environmental samples. A target analyte peak was reported only if the signal exceeded three times the baseline noise. For 1 lL injection, instrument detection limit (IDL) was calculated as 0.1 pg and 0.4 pg for congener specific and Aroclorbased (Aroclor 1016 + Aroclor 1260) analysis, respectively. A total of 41 individual PCB congeners were analyzed (IUPAC Nos. 17, 18, 28, 31, 33, 44, 49, 52, 70, 74, 82, 87, 95, 99, 101, 105, 110, 118, 128, 132, 138, 149, 151, 153, 158, 169, 170, 171, 177, 180, 183, 187, 191, 194, 195, 199, 201, 205, 206, 208, and 209). In cases where the compounds were not detected in any of the samples, they were removed from the data set. Congeners that were not detected in more than 20% of the samples were replaced by one-half the corresponding detection limit due to small sample size (Clarke, 1998). The recoveries of surrogate standard were 88 ± 14% in all samples. A method blank was analyzed every 10 samples of the same batch. The relative percent difference on MS/MSD samples was typically lower than 5%. The analytical procedure was further validated by analyzing a certified reference material, which is a natural sandy loamy sediment containing PAHs, pesticides, and seven indicator PCBs (CRM141-050; RTC, USA). The results of individual PCB congeners (#28, 52, 101, 118, 138, 153, and 180) deviated less than 13% from the target values. Summary results are presented in Table 1 for the individual congeners and total PCB levels together with organic matter content and depth data for the sediments of Mersin Bay. Samples show PCB levels ranging from 0.61 to 1.04 ng g 1 on congener basis, and from 0.92 to 4.97 ng g 1 on Aroclor basis. No particular trend could be observed for RPCB distribution between offshore sediments, those collected close to the shoreline or far from the industrial region (M1 and M11). The total PCB levels in samples were not correlated with organic matter content (r2 6 0.03). Compared to PCB concentrations reported in coastal environments, the levels in marine sediments of Mersin Bay are at the low end of ranges of PCBs observed in sediments within an area of 10 km from the principal Mediterranean urban (>100,000 inhabitants) centers (Gomez-Gutierrez et al., 2007). The results of this study, on the other hand, are lower than those observed in marine sediments of Turkey (Gedik and Imamoglu, 2010) and those reported values for other industrial regions around the world (Ashley and Baker, 1999; Frignani et al., 2001; Hartmann et al., 2004; Hong et al., 2005; Howell et al., 2008). Lastly, an assessment of the ecotoxicological aspect of PCB contamination
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175
Table 1 Congener specific PCBs in coastal sediments of Mediterranean Sea, Mersin Bay. Sample
a b
Depth (m)
OMa (%)
PCBs (ng g
1
dry weight)
#95
#101
#110
#132
#138
#149
#153
#180
#187
RConb
RAroclor
M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11
14 9.8 6.5 7 8 7 11 10 9 5.5 20
7.9 8.4 6.4 7.5 2.7 4.0 10.8 7.1 3.8 3.8 3.5
0.081 <0.003 <0.003 <0.003 0.071 0.082 <0.003 <0.003 0.073 <0.003 0.093
0.110 0.128 0.152 <0.003 0.073 0.148 <0.003 <0.003 0.073 0.114 0.112
<0.003 0.132 0.160 <0.003 <0.003 <0.003 <0.003 <0.003 0.076 0.104 <0.003
<0.003 0.161 <0.003 <0.003 0.038 <0.003 <0.003 0.134 0.065 0.115 <0.003
0.113 <0.003 <0.003 <0.003 0.151 0.141 <0.003 0.205 0.120 <0.003 0.095
0.115 0.114 0.126 0.170 0.124 0.171 0.343 0.184 0.119 0.117 0.157
0.114 0.277 0.199 0.240 0.125 0.158 0.384 0.289 0.194 0.139 0.247
0.091 0.149 <0.003 0.132 0.141 0.094 <0.003 <0.003 0.129 0.086 0.100
0.064 0.076 0.066 0.054 0.055 0.063 0.130 0.089 0.075 0.069 0.043
0.691 1.040 0.712 0.607 0.778 0.860 0.871 0.910 0.923 0.747 0.850
1.916 2.028 0.920 1.050 2.934 3.697 4.967 3.538 3.260 2.683 1.030
Mean Median
9.8 9.0
6.0 6.4
0.038 0.003
0.083 0.110
0.044 0.003
0.048 0.003
0.076 0.095
0.158 0.126
0.215 0.199
0.084 0.094
0.071 0.066
0.817 0.850
2.547 2.683
Organic matter content. Values below detection limits were considered to be equal to one-half the detection limit.
in the region may be performed by sediment quality guidelines developed by Long et al. (1995), namely, the effect range low (ERL, 22.7 ng g 1) and effect range median (ERM, 180 ng g 1). The aim of this guideline is to evaluate the potential toxicity of a particular chemical to benthic organisms in marine and estuarine sediments. Accordingly, the concentrations observed in Mersin Bay are below these guidelines, indicating no major ecotoxicological risk from PCBs in these sediments. Concentrations of individual PCB congeners were lower than 0.5 ng g 1 (Table 1). Among the 41 congeners analyzed, only a few of them were consistently detected and processed (Clarke, 1998) in samples. These are the members of penta-, hexa- and hepta-chlorobiphenyls, which are the major homolog groups in most environmental samples (Gomez-Gutierrez et al., 2007). PCBs #149 and 153 are the most abundant congeners, followed by PCBs #101, 138, 180, 187. Typically, the weight percent of these PCB congeners are in the range of 2–11% in Aroclor 1254 and 1260 formulations (Frame et al., 1996) which were widely used as dielectric fluids in transformers and capacitors. Gomez-Gutierrez et al. (2007) compiled information on the levels of persistent organic pollutants including PCBs in the Mediterranean sediments. In comparison to their study, the concentration of PCBs #153 and 180 in this study was about two orders of magnitude smaller than the median concentrations observed in harbor sediments in the Mediterranean Sea.
Fig. 2. Temporal PCB levels in the coastal sediments of Mediterranean Sea in Mersin compiled from Basturk et al. (1980), Tug˘rul et al. (2005, 2007, 2009), Yemeniciog˘lu (2003), Yemeniciog˘lu et al. (2004, 2006) and the present study*.
The temporal variation of PCB levels in sediments around the study area is given in Fig. 2 by introducing concentrations as they appear in the respective studies. As seen from Fig. 2, the results of this study are generally in good agreement with the total PCB concentrations observed 30 years ago in sediments along the Mersin Bay (Basturk et al., 1980). The level of PCBs in the Mediterranean coasts of Turkey has been monitored systematically since 2003. PCBs were not detected above the limit of detection at the beginning of the monitoring program and following year (2004). The findings of 2005 showed some unexpectedly high concentrations for which the reason is unknown, and no PCB data was reported in 2008 survey for the region (Tug˘rul et al., 2008). Comparing concentrations of PCBs (e.g. Aroclors, homologs, or individual congeners) even of the same unit (e.g. ng g 1 dry weight) may become difficult with PCB data. On the other hand, use of surface sediment rather than dated cores as temporal indicators may complicate data comparison due to influence of sedimentation on pollutant concentrations (Gomez-Gutierrez et al., 2007). Accordingly, the temporal trend of RPCB levels in sediment samples collected in the period from 1978 to 2009 showed decreasing trend for the region (r = 0.17 at all points excluding 2005 data in Fig. 2 using the linear model considering log-transformed data at 95% significance level). Considering the half-lives of PCBs estimated in the range of 6–30 years (Ritter et al., 1995) in soils or sediments, an overview of temporal variation of PCBs in sediments of Mersin Bay suggests no recent PCB input to the region. Moreover, the concentrations observed in Mersin Bay are consistent with typical background values established in the interval of 1–5 ng g 1 R7PCBs with a median of 2 ng g 1 for Mediterranean sediments (Gomez-Gutierrez et al., 2007). Acquisition of the first congener specific PCB data for the region enabled investigation of the potential sources of these pollutants using a receptor model, namely chemical mass balance (CMB). In CMB modeling, Aroclor formulations (Frame et al., 1996) were used as fingerprints of sources with justification for the selection of PCB sources (e.g. Clophen, Phenoclor) and modeling details are given elsewhere (Gedik et al., 2010). The apportionment results together with the uncertainties and goodness of fit statistics for samples around the Mersin Bay are presented in Table 2. The overall average of goodness of fit parameters, R2 and R.E. is 0.943 and 0.224, respectively, for the modeled samples. Both measures indicate satisfactory prediction of environmental PCB profiles. Furthermore, VIF values calculated for the corresponding sample–source pairs were in the range of 1.18–4.09 with a median of 1.60, indicating insignificant collinearity among source profiles. The major PCB source identified by the model at marine sediments is Aroclor 1260 with percent contributions ranging from 60.4 to 87.9. This can be explained by the identity of congeners
_ Imamog _ ˘ lu / Marine Pollution Bulletin 62 (2011) 173–177 K. Gedik, I.
176 Table 2 Chemical mass balance model results and statistics. Samplea
Apportionment results (%) Ar1016
M1 M2 M3 M5 M6 M8 M9 M10 M11 a b c
Ar1242
Model statistics Ar1248
Ar1254
19.6 ± 6.00 35.7 ± 13.7 40.3 ± 9.10 12.1 ± 4.10 9.10 ± 8.60 39.6 ± 18.7 2.90 ± 1.50
27.0 ± 17.1 20.0 ± 5.00 38.9 ± 13.2
24.9 ± 9.10
Ar1260
v2b
R2
R.E.c
80.4 ± 13.1 64.3 ± 18.6 59.7 ± 10.8 87.9 ± 12.8 63.8 ± 18.9 60.4 ± 21.3 77.1 ± 10.9 61.1 ± 16.2 75.1 ± 16.2
6 5 3 6 5 3 6 5 6
0.950 0.900 0.972 0.962 0.937 0.959 0.976 0.917 0.915
0.197 0.338 0.133 0.148 0.281 0.215 0.107 0.302 0.293
Some of the samples were not included into model due to df P 3 constraint. v2 = df. Relative error corresponding to v2 = df.
observed in coastal sediments and also, in general, PCB profiles in sediments resemble to that of Aroclor 1260 formulation (Burns and Villeneuve, 1987). Aroclor 1260 is known to be extensively used in transformers, hydraulic fluids, synthetic resins and dedusting agents (Durfee et al., 1976). Such applications may find many uses in Mersin Organized Industrial District in the Bay. Relatively high contributions from Aroclor 1254 were also predicted, with minor contribution from Aroclor 1248, 1242 and 1016 to a small number of samples. Aroclor 1242 is identified only in M3, M5 and M11, which are located close to Deliçay creek and Göksu River, reflecting the dissimilar nature of wastes potentially transported by the aquatic systems from the nearby industries. Aroclor 1242 is known to find use in many partially open/open applications such as plasticizers, carbonless copy paper production, adhesives. For samples off the Port of Mersin, on the other hand, Aroclor 1254 and to some extent Aroclor 1248 contribution is revealed in addition to Aroclor 1260. Although no record or chemical inventory for industries located throughout the coast line in Mersin Bay is present, these mixtures having a variety of uses in open as well as closed applications reflects potential polluting sources in the area. Yet, low concentrations of PCBs point to minor use of these chemicals by industries. CMB findings also showed the influence of rivers in terms of PCB loads into the marine system by point and diffuse land-based sources in the region. In most model calculations, the PCB pattern can be reproduced using Aroclors to a good extent, excluding the deviations in congeners #132, 153, 180 and 187 in general. The disagreement between measured and predicted congeners may indicate modification of PCB profiles from source to receptor. This may be due to a number of environmental mechanisms acting on the compounds as well as the samples, i.e. differential solubilization/desorption of low chlorinated PCBs, enrichment of highly chlorinated congeners in the sediments, loss through air–water exchange, etc. A depth-wise investigation of PCB levels, such as using dated sediment cores can enable a more thorough understanding of past contamination in the region.
Acknowledgements This study is funded by the Turkish Scientific and Research _ Council (TÜBITAK: CAREER Project No. 104I126), and also supported by the Turkish Prime Ministry-State Planning Organization and METU Research Fund (BAP-DPT 2002K120510). We would like to thank Dr. Mustafa Odabasßı (Department of Environmental Engineering, Dokuz Eylul University) for his valuable support in GC/MS analysis and Dr. Süleyman Tug˘rul (Institute of Marine Sciences, METU) for his help during sampling of marine sediments.
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