Article pubs.acs.org/est
Consistency in Trophic Magnification Factors of Cyclic Methyl Siloxanes in Pelagic Freshwater Food Webs Leading to Brown Trout Katrine Borgå,*,†,§ Eirik Fjeld,† Amelie Kierkegaard,‡ and Michael S. McLachlan‡ †
Norwegian Institute for Water Research (NIVA), Gaustadallèen 21, N-0349 Oslo, Norway Department of Applied Environmental Science (ITM), Stockholm University, SE-106 91 Stockholm, Sweden
‡
S Supporting Information *
ABSTRACT: Cyclic volatile methyl siloxanes (cVMS) concentrations were analyzed in the pelagic food web of two Norwegian lakes (Mjøsa, Randsfjorden), and in brown trout (Salmo trutta) and Arctic char (Salvelinus alpinus) collected in a reference lake (Femunden), in 2012. Lakes receiving discharge from wastewater treatment plants (Mjøsa and Randsfjorden) had cVMS concentrations in trout that were up to 2 orders of magnitude higher than those in Femunden, where most samples were close to the limit of quantification (LOQ). Food web biomagnification of cVMS in Mjøsa and Randsfjorden was quantified by estimation of trophic magnification factors (TMFs). TMF for legacy persistent organic pollutants (POPs) were analyzed for comparison. Both decamethylcyclopentasiloxane (D5) and dodecamethylcyclohexasiloxane (D6) biomagnified with TMFs of 2.9 (2.1−4.0) and 2.3 (1.8−3.0), respectively. Octamethylcyclotetrasiloxane (D4) was below the LOQ in the majority of samples and had substantially lower biomagnification than for D5 and D6. The cVMS TMFs did not differ between the lakes, whereas the legacy POP TMFs were higher in Mjøsa than inRandsfjorden. Whitefish had lower cVMS bioaccumulation compared to legacy POPs, and affected the TMF significance for cVMS, but not for POPs. TMFs of D5 and legacy contaminants in Lake Mjøsa were consistent with those previously measured in Mjøsa.
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INTRODUCTION Cyclic volatile methylsiloxanes (cVMS) have been identified as emerging contaminants of concern due to their predicted persistence and bioaccumulative characteristics.1 Siloxanes are produced in high volumes and have several uses such as in personal care products, biomedical products, and consumer products such as car polish and waxes.2 The three cVMS octamethylcyclotetrasiloxane (D4 CAS No. 556-67-2), decamethylcyclopentasiloxane (D5 CAS No. 541-02-6), and dodecamethylcyclohexasiloxane (D6 CAS No. 540-97-6) have been found to accumulate in biota,3−5 but to a varying degree depending on chemical and organism, and with large variation between studies.6 Based on the criteria of the European Community Regulation on chemicals and their safe use (REACH),7 D4 and D5 are classified as very bioaccumulative (vB),8,9 whereas D6 does not meet the criteria to be classified as bioaccumulative (B) or vB.10 Recent development of analytical methods has resulted in an increasing number of measurements of these chemicals in environmental matrices, including biota.11,12 Whereas previous assessment of cVMS behavior in the environment was based on model predictions1,13 and laboratory tests,8,9 recent studies allow for © 2013 American Chemical Society
characterization of the persistence and bioaccumulation based on environmental samples.3,14 The bioaccumulation of chemicals in an organism from, and relative to, the diet is currently assessed by biomagnification factors (BMFs) or trophic magnification factors (TMFs).15,16 Whereas the BMF considers specific predator−prey relationships, the TMF is an estimation of the average change in contaminant concentrations, normalized for fugacity capacity, when moving from one trophic level up to the next in the food web.17 For biomagnifying chemicals, these metrics are above 1. For contaminants with a high octanol−water partitioning coefficient (KOW) such as cVMS (log KOW 6.98 for D4, 8.07 for D5, and 8.87 for D618), lipid normalization is the method employed for deriving the fugacity capacity normalized concentrations. TMF has been suggested to be the most conclusive measure of bioaccumulation of chemicals in biota that have a multitude of food choices and subsequent exposures Received: Revised: Accepted: Published: 14394
June 16, 2013 November 15, 2013 November 19, 2013 November 26, 2013 dx.doi.org/10.1021/es404374j | Environ. Sci. Technol. 2013, 47, 14394−14402
Environmental Science & Technology
Article
to contaminants.15 REACH recently added BMF and TMF as metrics that can be used in a weight of evidence based assessment of bioaccumulation.7 TMFs are currently estimated from empirical data,17 but there is still need for improvement of the scientific understanding of TMF, in particular how it varies within and between ecosystems.17,19,20 To date, there have been few empirical studies of food web magnification (TMF) of cVMS.6,21,22 So far, only one study is published in the peer-reviewed literature,6 which reported a TMF of 2.3 for D5, that is, significant food web biomagnification.6 A TMF > 1 is consistent with previous predator−prey studies of D5 biomagnification,3 but it stands in contrast to the silicon producing industry’s own studies of other food webs and ecosystems, which report TMFs < 1 for D5.21,22 This discrepancy in results between studies motivates further assessment of D5 TMF. In particular, it is important to establish whether the reported case of D5 TMF > 1, which was measured in the pelagic food web of Lake Mjøsa in Norway,6 is indicative of D5 food web biomagnification in other lakes and in other years, or whether it was an anomaly that cannot be generalized in space and time. This is an objective that is not only of importance for further understanding cVMS bioaccumulation but also for broadening the understanding of TMFs variability in general.19 Furthermore, there is a clear need for the assessment of the TMF of the other cVMS, D4 and D6, for which no food web measurements are available in the peerreviewed literature. In the previous Lake Mjøsa study,6 D4 and D6 were below the limit of quantification (LOQ) in all invertebrate samples, and this biased uncertainty in the data set meant that their TMFs could not be estimated. The aim of the present study was to determine if cVMS food web biomagnification assessed by TMF is consistent across lakes and years in pelagic food webs with brown trout (Salmo trutta) as a piscivorous top predator. To this end, the pelagic food web of Lake Mjøsa was resampled, as was the pelagic food web in Lake Randsfjorden, another large lake in Norway with trout as a piscivorous top predator. The food web samples were analyzed for D4, D5, and D6, and their TMFs were calculated. To assess the representativeness of the food webs sampled, the cVMS TMFs were compared to the TMFs of the well-known biomagnifying legacy persistent organic pollutants (POPs) dichlorodiphenyldichloroethylene (p,p′-DDE), polychlorinated biphenyls (PCBs), and polybrominated diphenyl ethers (PBDEs). The study addresses both chemical specific questions of cVMS biomagnification as well as understanding of TMF variability in time and among ecosystems.
opossum shrimp Mysis relicta in the invertebrate community and vendace (Coregonus albula) among the planktivorous fish and excludes Arctic char (Salvelinus alpinus) as a top predator, whereas in Randsfjorden and Femunden whitefish (Coregonus lavaretus) is a member of the pelagic food web, largely feeding on crustacean plankton. Representatives of the pelagic food web of the respective lakes (zooplankton and fish) and field blanks (passive samplers: polyester pouches containing ∼60 mg ENV+) were collected as detailed in the Supporting Information according to protocols previously described.6 Zooplankton and Mysis were collected with vertical net hauls, and fish were caught using surface and bottom gill nets, traps, and angling. Although the trout in Mjøsa were sampled close to the Gjøvik area, and the rest of the food web was sampled closer to Gillundstranda/Ottestad (Figure S1), they are considered members of the same food web since trout are known to roam a large geographic area and uses the whole of Mjøsa in their search for food.24 Fish samples consisted of skinless filets from one individual fish, with the exception of small smelt from Mjøsa and Randsfjorden, where 5−6 skinless filets were pooled. Immediately after collection, the material was divided into subsamples for analysis of cVMS, legacy contaminants (halogenated POPs) and stable isotopic ratios of nitrogen (δ15N) and carbon (δ 13C) for food web characterization. Chemical Analysis of cVMS. The samples were analyzed for cVMS (D4, D5, and D6) at Stockholm University using a modified version of a published purge and trap method.11 To improve the repeatability and analyte recovery of this method, the samples were first extracted using an organic solvent after which the extract was purified using the purge and trap method. The purified extract was analyzed using GC/MS and quantified using 13C-labeled internal standards, as described in Kierkegaard et al.11 Extraction and sample preparation were performed in a clean air cabinet under a laminar flow of filtered air. A detailed description of the method is provided in the Supporting Information (text and Tables S4−S7). In addition to procedural blanks and field blanks, an internal matrix control (homogenate of herring from the Baltic Sea) was analyzed with each batch of 8 samples. The limit of quantification (LOQ) was set to the mean plus 10 times the standard deviation of the procedural blanks (Supporting Information Table S8). The cVMS results were not blank corrected. Chemical Analysis of Halogenated POPs. The samples from Lake Mjøsa and Lake Randsfjorden were analyzed for PCBs and chlorinated pesticides. The Lake Mjøsa samples were also analyzed for PBDEs. The analyses were conducted at the Norwegian Institute for Water Research based on established methods.25 A detailed description is found in the Supporting Information (text and Tables S9 and S10). The extraction of total lipids by cyclohexane and isopropanol followed the recommended method for the revised OECD 305 guideline for determination of bioconcentration factor in fish,26 with results well within the acceptable criteria for the Quasimeme ringtest for lipid determination (Supporting Information Table S9). Analysis of Trophic Descriptors. The samples were analyzed for stable nitrogen (δ15N) and carbon (δ13C) isotopic ratios at the Institute for Energy Technology (IFE-Kjeller) according to standard protocols.27 δ15N and δ13C were determined to assess the relative trophic level and the dominant dietary carbon source of the organisms, respectively.19 Lipids
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MATERIALS AND METHODS Selected Lakes and Sampling Description. Zooplankton and fish were collected in Lake Mjøsa and Lake Randsfjorden in Norway July−September 2012 (Supporting Information, Figure S1, Tables S1−S3). Based on the estimated pollution load (person equivalents, PE) Mjøsa is subject to high to moderate human impact (206 000 PE) and Randsfjorden to moderate human impact (28 500 PE).23 As a control, fish were also collected from a remote lake (Femunden) with low human activity (200 PE)23 that was expected to have low cVMS contamination. All three study lakes are deep and contain welldefined pelagic food webs including zooplankton, planktivorous fish, and piscivorous fish with brown trout as a top predator; see the description of food web relations in the Supporting Information. The main differences in food web structure between the lakes is that Lake Mjøsa includes the pelagic 14395
dx.doi.org/10.1021/es404374j | Environ. Sci. Technol. 2013, 47, 14394−14402
Environmental Science & Technology
Article
Table 1. Trophic Position, Lipid Content, and Concentrations of Cyclic Volatile Methylsiloxanes (cVMS, ng/g Lipid Weight) in Food Web Compartments of Norwegian Lakes in 2012a,b,c trophic position
lipid %
n
mean ± SE
mean ± SE
zoopl. epi zoopl. hypo mysis vendace smelt. small smelt. large brown trout
4 5 5 7 5 5 5
2±0 2.6 ± 0.2 2.8 ± 0.1 3.9 ± 0 3.8 ± 0.1 4.4 ± 0 4.4 ± 0
0.72 ± 0.04 3.5 ± 1.4 2.5 ± 0.6 1.2 ± 0.1 1±0 1.3 ± 0.2 2.9 ± 0.6
zoopl. epi zoopl. hypo whitefish smelt brown trout
4 3 9 5 5
2±0 3.0 ± 0.3 3.2 ± 0.1 3.5 ± 0.1 3.8 ± 0.1
Arctic char brown trout
1 6
n
D4
D5
D6
mean ± SE
mean ± SE
mean ± SE
340 ± 33 1660 ± 300 930 ± 120 14160 ± 2450 3530 ± 220 5260 ± 740 5630 ± 1040
