Polybrominated Diphenyl Ether (PBDE) Accumulation in Farmed

Article pubs.acs.org/est

Cite This: Environ. Sci. Technol. XXXX, XXX, XXX−XXX

Polybrominated Diphenyl Ether (PBDE) Accumulation in Farmed Salmon Evaluated Using a Dynamic Sea-Cage Production Model Carla A. Ng,*,† Amélie Ritscher,‡ Konrad Hungerbuehler,‡ and Natalie von Goetz*,‡ †

Department of Civil and Environmental Engineering, University of Pittsburgh, 3700 O’Hara Street, Pittsburgh, Pennsylvania 15261, United States ‡ Institute for Chemical and Bioengineering, ETH Zurich, Vladimir-Prelog-Weg 1, 8093 Zurich, Switzerland S Supporting Information *

ABSTRACT: Food is an important source of human exposure to hazardous chemicals. Chemical concentration in a food item depends on local environmental contamination, production conditions, and, for animal-derived foods, on feed. Here, we investigate these influences on the accumulation of individual polybrominated diphenyl ether congeners (PBDEs) in farmed Atlantic salmon (Salmo salar). We develop a dynamic model over a full sea-cage salmon production cycle. To assess the influence of metabolic debromination on PBDE congener profiles, in vitro measurements of debromination rates in fish liver cells were extrapolated to whole-body metabolic rate constants. Model results indicate that the dominant factors governing PBDE concentration in Atlantic salmon fillet are uptake via contaminated feed and fish growth, whereas the influence of metabolic debromination is minor. PBDE concentrations in fish feed depend on several factors, including the geographic origin of fish feed ingredients, which are produced and traded globally. Human exposure to PBDE via salmon consumption is less influenced by environmental concentrations at the location of salmon farming than by environmental concentrations influencing feed components. This dependence of PBDE concentrations in salmon on the origin and composition of feed reveals the complexity of predicting contaminant concentrations in globally traded food.

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INTRODUCTION Polybrominated diphenyl ethers (PBDEs) are a class of synthetic flame retardants which have been extensively used to increase the fire resistance of consumer products, such as foam paddings, textiles, and plastics.1 PBDEs can be released into the environment during production, use, and disposal of treated products, leading to their detection in a variety of environmental and biological samples,2,3 including human tissues.4−6 PBDEs comprise 209 different congeners with different numbers of bromines attached to their diphenyl ether structure. There are three major commercial mixtures: penta-, octa-, and deca-BDE, named for the degree of bromination of the dominant congener in the mixture. Deca-BDE, the most widely used mixture,3 is added to polymeric materials such as polystyrene, polybutylene, nylon, polypropylene, and other thermoelastic plastics, and contains more than 96% BDE-209, the highest-brominated congener. Fire-protected polypropylene can contain up to 23% deca-BDE by weight.7 Due to environmental and public health concerns, penta- and octa-BDE mixtures were banned in Europe and the United States in 2004. Some PBDEs are disruptive of thyroid hormone homeostasis and some are associated with neurodevelopmental and behavioral effects in rodents.8 In 2009, tetra- and pentabromodiphenyl ethers were listed under the Stockholm Convention as persistent organic pollutants.9 In the United © XXXX American Chemical Society

States, manufacturers agreed to voluntarily phase out deca-BDE by the end of 2013, and in August 2014, the European Chemicals Agency (ECHA) submitted a proposal to restrict the use of deca-BDE in the European Union.10,11 Following these actions, PBDE manufacturing moved to less developed countries such as China, India, Indonesia, Thailand, and Vietnam.12 As products containing PBDE flame retardants have a relatively long lifetime, emissions to the environment will most likely continue despite increasing regulations. Due to their hydrophobicity and preferential partitioning into particulate phases, large environmental reservoirs are being created in sediments, which might present a long-term threat to biota.13 The dominant pathway for human exposure to PBDEs is consumption of contaminated food.8 To estimate human exposure to such potentially hazardous chemicals, modeling approaches are often applied that rely on measured levels in the foods of interest.14 However, data on food origin is normally not addressed and, due to the global nature and interconnectedness of the international food trade system, local environmental emissions or regulations can influence human exposure Received: Revised: Accepted: Published: A

January 9, 2018 April 10, 2018 April 26, 2018 April 26, 2018 DOI: 10.1021/acs.est.8b00146 Environ. Sci. Technol. XXXX, XXX, XXX−XXX

Article

Environmental Science & Technology

The aim of this work is 2-fold: first, to investigate how local environmental concentrations and production conditions including choices about feed composition and origin influence concentrations of PBDE in farmed salmon, and second, to consider the influence of metabolic debromination on congener profiles in farmed fish. For these purposes, we have developed a dynamic multichemical bioaccumulation model for a complete sea-cage production period. This approach allows us to evaluate the contributions of the most important sources, and to assess the importance of other factors, such as metabolic debromination, to PBDE concentrations in Atlantic salmon fillets. Finally, we discuss the implications of these factors for the transport of PBDEs via global food trade.

to a contaminant on a much larger scale. Although there are already human exposure models in place that account for local emissions, chemical fate, and bioaccumulation, existing models do not account for the global transport of chemicals via food trade.15 Such consideration can be particularly problematic for the consumption of animal products, as the food sources of the animals themselves come into play. A particularly salient example is that of farmed predatory fish. Both fish consumption and aquaculture have increased rapidly over the last 40 years. Salmon is one of the most widely consumed fish, and more than 50% of salmon sold globallymostly Atlantic salmon, Salmo salaris farmed.16 Halogenated organic contaminants in aquaculture fish, including PBDEs, have gained considerable attention during the past decade.16−19 Most of this work has focused on polychlorinated biphenyls and dioxins. However, a few studies have also investigated PBDEs. Feed is generally considered to be the most important source for persistent organic pollutants in farmed fish, with 35−59% of the total PBDE intake via feed accumulating in the salmon fillet over 8−12 months.20−22 Reducing PBDE concentrations in feed can result in lower PBDE concentrations in fish fillet.23,24 On the other hand, Meng et al. (2008)25 highlighted the importance of the surrounding environment, finding higher concentrations of PBDEs in seawater-farmed fish than in freshwater-farmed fish fed with the same fish feed. They hypothesized this concentration difference was caused by higher concentrations of PBDE in coastal waters from riverine discharge. However, no direct comparison of the influence of feed versus environmental concentrations in a single study has been made. The role of metabolic debromination on PBDE congener profiles in fish also remains unclear. Most studies have identified BDE-47 as the dominant PBDE congener in salmon fillet. While congener profiles in commercially available fish feed can be very similar to those measured in salmon fillet,16,18 Isosaari et al. (2005)20 hypothesized that the high concentrations of BDE-47 found in salmon fillet could be caused by metabolic debromination of higher brominated congeners. In a feeding study of Atlantic salmon with fish feed cleaned of persistent organic pollutants, Olli et al. (2010)23 found BDE209 in considerable concentrations in the control group of salmon fed with conventional fish feed. This indicates that BDE-209 might have the potential to accumulate in salmon fillets. However, Hites et al. (2004)16 and Montory and Barra (2006)18 found very low concentrations of higher brominated congeners in salmon fillets, and BDE-209 was not detected, despite being present in the analyzed samples of fish feed. The authors hypothesized the absence of BDE-209 in fillet samples to be caused either by low bioavailability or by metabolic transformation of the substance to lower brominated congeners. Neither the feeding study conducted by Isosaari et al. (2005)20 nor Berntssen et al. (2010)24 included higher brominated congeners than BDE-183. Metabolic debromination of PBDEs in fish has been demonstrated by a number of studies.26,27 However, a recent in vitro assessment of metabolic PBDE debromination in liver subfractions of common carp, rainbow trout and Chinook salmon revealed considerable interspecies differences in metabolic debromination capacities,28 and the products of debromination reactions of individual PBDE congeners differed between common carp and the other two species. It is therefore unclear to what extent the metabolic debromination of PBDEs influences their concentrations in individual fish species.

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MATERIALS AND METHODS Mass Balance Model Framework. Our dynamic, onecompartment fugacity-based box model for PBDE uptake in an individual salmon is based on the dynamic bioaccumulation model for PBDEs in lake trout developed by Bhavsar et al. (2008).29 Tissue-specific properties and processes related to the gills, fish body, and gastrointestinal (GI) tract are used to parametrize PBDE uptake and loss to the whole body compartment (Supporting Information (SI) Figure S1). Details on the process equations, variables, and their sources are provided in SI section S1. Here, we briefly describe the overall structure of the multichemical mass balance. The complete PBDE mass balance in the fish body includes uptake of a congener from water and food, excretion via respiration and fecal egestion, and biotransformation29 expressions that describe the change in the fugacity of a congener in the fish body due to metabolic reactions (including debromination (loss) of the modeled congener, y, and inputs due to the debromination of its parent congener, x): dm y dt

=

VF·Z F,y ·dfF,y dt

= E W,0,y ·D V, y ·fW,y + E D,0,y ·DD, y ·fD,y + νxy ·DM, x ·fF,x

− ((E W,0, y ·D V,y ) + (E D,0, y ·DQ,y ) + DM, y)·fF,y

(1)

The change in mass (in moles) of a particular PBDE congener y in the fish, dmy/dt, is given by the product of the fish volume (VF), its fugacity capacity for congener y (ZF,y) and the change in the fugacity of congener y in the fish as a function of time, df F,y/dt. The product EW,0,y × DV,y × f W,y describes the uptake of congener y from water, while ED,0,y × DD,y × f D,y is the uptake of congener y from food. EW,0,y and ED,0,y describe the initial chemical uptake efficiencies from water and food, respectively (at time 0) and DV,y and DD,y are the transport parameters, or D-values, for respiratory and dietary uptake (see SI section S1). EW,0,y × DV,y × f F,y describes the loss of chemical via the gills and ED,0,y × DQ,y × f F,y is the loss via fecal elimination. D M,x and D M,y are the D-values for the debromination of congeners x and y, f F,x is the fugacity of congener x in the fish body, f F,y is the fugacity of the debromination product y in the fish body, and vxy is the fraction of the parent congener x, that is debrominated to the product y. The model is solved numerically using Matlab (MATLAB 8.3.0.532, The MathWorks Inc., Natick, MA, 2014) to produce the concentration of each modeled congener in each compartment as a function of time. PBDE Congeners. Specific PBDE congeners are considered in the model if concentration data in fish feed were available (see PBDE Concentrations in Feed, below) or if it was part of B

DOI: 10.1021/acs.est.8b00146 Environ. Sci. Technol. XXXX, XXX, XXX−XXX

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Berntssen et al. (2010) is shown in SI Figure S6. Berntssen et al. (2010) do not provide any information on proximate composition of the fish used for the trial. It was therefore assumed that the proximate composition of a fish at the beginning and the end of model run B is equal to the composition of a fish in model run A with the same weight. Berntssen et al. (2010) only report daily average feed data from three experimental periods, comprising 8 of the 12 months of the trial. We interpolate daily feed intakes for model run B from these average daily feed intakes as described in SI section S3.8. For both model runs, comparison of predicted to measured concentrations required conversion from whole body (predicted by the model) to fillet (provided in the feeding studies) concentrations. This was done by multiplying lipid-based whole-body concentrations by the ratio of fillet to whole-body lipid contents (see SI section S3.11). PBDE Concentrations in Water. Few measurements of dissolved PBDE concentrations in coastal seawater are available. Here, the concentrations of PBDEs in the dissolved fraction measured by Möller et al. (2012)33 on three different cruises in the marine coastal environment of the North Sea from March to July 2010 were averaged and used as model input (Table 1). These were assumed to be representative of

the debromination pathway of a congener present in feed (see PBDE Biotransformation, below). The octanol−water partition coefficient (KOW) and Henry’s law constant (H) are used to calculate each congener’s fugacity capacity, Z, for lipid, nonlipid organic matter, and water. For all PBDE congeners used in the model, we used the KOW for homologue structures estimated by Wania and Dugani (2003)30 (SI Table S1). Henry’s law constants were calculated according to the regression equation derived by Tittlemeier et al. (2002)31 for the subcooled liquid phase. Sea-Cage Life Cycle Simulations. The production and life cycle of aquaculture salmon consists of several stages. Eggs are stripped from broodstock fish, fertilized, and hatched in freshwater facilities. The young fish are kept in freshwater tanks on land for up to 12 months until they undergo a so-called parrsmolt transformation. During this transformation, the metabolic system of the salmon adapts to saltwater conditions. Smolted fish are then transferred to sea sites and further grown in large net cages in coastal waters for another 12−18 months until they reach a slaughter weight of 4−5 kg. Due to deterioration of flesh quality, the salmon are usually harvested before sexual maturation.32 We consider the fish life cycle from the time smolted fish are transferred to the sea site until harvest, corresponding to a model run of 500 days. Two independent simulations were run to evaluate the influence of production conditions and biotransformation. The first simulation was parametrized according to the feeding study of Olli et al. (2010),23 hereafter referred to as model run A. The second was parametrized according to the study of Berntssen et al. (2010),24 hereafter referred to as model run B. These independent simulations were necessary to reduce uncertainties in the evaluation of simulation performance, because the Olli et al. study had higher resolution physiological and feeding data, but no PBDE concentrations reported in feed, whereas the Berntssen et al. study had only average feeding data but specified PBDE concentrations in feed. Fish Physiology and Feeding Rates. In the feeding study conducted by Olli et al. (2010),23 used as the basis for model run A, the authors collected a variety of physiological parameters, including fish weight, volume, proximate composition (including lipids, nonlipid organic matter, and water), and respiration rates over the course of a complete seawater production cycle, starting from July 2007 to December 2008. Physiological parameters derived from this study are detailed in SI section S3. Feeding rates for model run A were based on actual feeding data recorded for the Olli et al. (2010)23 study (SI Figure S5). These data were generously provided to us (Harald Breivik, Neperdo Biomarine, Norway, 2016, personal communication). The average daily ration per fish was calculated for cages fed with conventional fish feed. Where there were missing data for an individual cage, it was omitted from the calculation of average daily intake. For days where there were no feeding data for any cage available, daily ration was linearly interpolated from measurements from the previous and following days. There were feeding data available for 479 out of 498 days of the study (96%, see SI section S3.7). Variability in reported feeding rates was propagated to model results by calculating PBDE concentrations based on the 25th percentile, 75th percentile, and mean daily rations. For model run B, values for fish body weight were fitted to a power function based on the values given by Berntssen et al. (2010). The fitted function compared to the measurements by

Table 1. Concentrations of PBDEs in Water and Feed Used as Model Input water concentration congener BDE-209 BDE-203 BDE-183 BDE-154 BDE-153 BDE-100 BDE-99 BDE-66 BDE-47 BDE-28

3

[mol/m ] 4.36 1.93 2.21 0 1.31 1.97 2.37 0 3.33 0

× 10−13 × 10−14 × 10−14 × 10−14 × 10−14 × 10−13 × 10−13

feed concentration [μg/kg] A1, A2

B1, B2

4.72 0.026 0.03 0.19 0.08 0.35 0.31 0 2.07 0.09

0 0 0 0.78 0.24 0.87 0.93 0.31 4.5 0.18

the concentrations found in the coastal region of a Norwegian fjord (see SI section S4.1). For BDE-203, no measurements in sea- or freshwater are available in literature. However, in the debromination pathway of Chinook salmon,28 this congener is an important “upstream” parent compound. In order to investigate the influence of BDE-203 on the PBDE concentrations in the fish body compartment, its concentration in seawater was estimated. In commercial PBDE mixtures, BDE-203 is only present in the technical octa-BDE mixture, where its concentrations range from 5 to 35%. BDE-183 is also present only in the technical mixture, where it constitutes 40% of all PBDE congeners.10 It was assumed that the ratio of BDE183 to BDE-203 in the water is the same as the ratio found in the octa-BDE, selecting 35% as an upper bound for BDE-203 (Table 1). PBDE Concentrations in Feed. Olli et al. (2010)23 did not report the concentration of individual PBDE congeners in the feed used in their study. Therefore, average concentrations reported by the Norwegian public monitoring and mapping program for fish food were used as inputs for model run A for the indicator PBDEs (BDE-183, -154, -153, -100, -99, -47, -28).34 Concentration data for higher brominated PBDE congeners in fish feed are also scarce. Hites et al. (2004)16 C


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Environmental Science & Technology reported concentrations for the sum of PBDEs in fish feed purchased in Scotland, British Columbia, eastern Canada, and Chile. In these feed samples, BDE-209 was reported to average 15 ± 5% of the total PBDE measured. Based on this, the concentration of BDE- 209 in fish feed was modeled as 15% of the averaged total PBDE concentration reported by Hites et al. (2004).16 In order to maintain consistency between the two data sources, the earliest values reported by Sanden (2014)34 (from the year 2004) were used for the concentrations of all other PBDE congeners. No measurements of BDE-203 in feed were available in literature. For model run A, we assumed that the ratio of BDE-183 to BDE- 203 in the fish feed is the same as the ratio found in Octa-BDE (Table 1). The concentrations of individual PBDE congeners in fish feed as reported by Berntssen et al. (2010) were used directly as input for model run B (Table 1). PBDE Biotransformation. The metabolic degradation of PBDE in fish is generally considered to occur via reductive debromination.28,35−39 Roberts et al. (2011)28 examined the nature and amounts of metabolites of in vitro debromination of various BDE congeners (28, 47, 49, 99, 100, 153, 154, 183, 203, 208, and 209) by microsomal fractions of adult rainbow trout (Oncorhynchus mykiss), adult carp (Cyprinus carpio) and juvenile Chinook salmon (Oncorhynchus tschwatcha). Based on the results of individual incubations of BDE congeners, the authors constructed a metabolic pathway for each fish species. These pathways were markedly different between the species, with carp liver fractions having significantly higher metabolic capacities, both in terms of reaction rate and debromination products formed, compared to rainbow trout and Chinook salmon. The debromination pathways found for rainbow trout and Chinook salmon are shown in SI Figure S8. Based on the amount of debromination products after 24 h incubation time, Roberts et al. (2011)28 calculated in vitro metabolite formation rates. Due to the lack of any further data on rate constants for metabolic reductive debromination in fish, we extrapolated these product formation rates to whole-body, in vivo first-order biotransformation rate constants (kM) for salmon using a fourstep process: (1) intrinsic hepatic in vitro clearance rates were calculated from the depletion rate of the parent metabolite in Chinook salmon;28 (2) this in vitro clearance was extrapolated to in vivo clearance using the average measured hepatosomatic index (HSI) of the fish in the Olli et al. (2010)23 study and the amount of microsomal protein in the liver estimated for trout by Nichols et al. (2006);40 (3) the intrinsic hepatic in vivo clearance rate was extrapolated to total hepatic clearance based on the rate of liver blood flow, fish weight, and the blood-water partition coefficient of individual PBDE congeners; (4) finally, the whole body biotransformation rate constant (kM) was determined using the volume of distribution of the chemical between the blood and other tissues. Details of these four steps, including all equations and parameters used, are given in SI section S5. In order to investigate the influence of debromination on model performance, each feeding study was run with and without biotransformation. Simulations run with biotransformation are referred to as model run A1 and B1 for the Olli et al. (2010)23 and Berntssen et al. (2010)24 studies, respectively. Model runs without biotransformation, in which kM for all congeners is set to zero, are referred to as A2 and B2. Sensitivity and Uncertainty. Many parameters used in the model are based on estimated values and therefore are associated with considerable uncertainty. In order to under-

stand the influence of this uncertainty on model predictions, model sensitivity to all input parameters was investigated using a factor-at-a-time approach. Each model parameter was varied by 10% of its value, while all other parameters were kept at their nominal value. Normalized sensitivity coefficients for each parameter (NSCP) were calculated as follows (MacLeod et al., 2002): NSCP =

θ − θ0 P0 · P − P0 θ0

(2)

where P is the varied parameter value, P0 is the nominal value of the parameter used in the model, θ0 is the nominal model output, and θ is the model output calculated with the varied parameter. As some of the congeners are debrominated metabolically or formed via metabolic debromination and other congeners are solely taken up via food and water, the model structure for these congeners is different. Therefore, the sensitivity analysis was carried out for each individual congener considered in the mass balance. The end point evaluated was the concentration of each congener in the fish body at the end of a 500-day production period, based on model run A1.

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RESULTS In the following sections, the concentration dynamics and PBDE fluxes predicted by the model are first illustrated for selected congeners using model run A1. Predicted concentrations and congener distributions are then compared to available data23,24 for all four model runs. Concentration Dynamics. The modeled concentrations of different PBDEs in the fish body predicted by model run A1 span more than 3 orders of magnitude. Most congeners show similar dynamics with time. In Figure 1, we illustrate these concentration dynamics with the results for model run A1 for congeners BDE-47, -99, and -209.

Figure 1. Concentration of BDE-47, -99, and -209 in the fish wholebody compartment over an entire sea-cage cycle for model run A1.

The concentration of BDE-47 predicted by the model is 1 order of magnitude higher than BDE-99 and -209, which are similar. For these and most other congeners, concentrations increase steeply for the first 100 days of production, then decrease again. Around day 250 of the production period, most congeners reach a quasi-steady state and their concentrations remain constant for the next 100 days. Concentrations then increase again for the last 150 days of production. Differences among congeners are largely driven by differences in uptake D


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Environmental Science & Technology and loss fluxes, as discussed below, which in turn are strongly dependent on the KOW, which affects dietary and gill uptake efficiencies as well as elimination rates. The shape of the concentration curve with time is largely driven by the balance of changing consumption rates with fish size, growth dilution, temperature (which seasonally affects rates of consumption), and metabolic capacity. Of these, the influence of size and growth is particularly strong. Small fish have relatively high consumption rates, leading to rapid uptake at the beginning of the modeling period. Dietary uptake (absolute, not normalized to size) increases with size. The highest growth period for the modeled fish begins around day 125, and the dilution associated with strong growth drives the decline between days 100 and 200, before approaching steady state. Input and Output Fluxes. Figure 2 shows PBDE mass fluxes into and out of the fish body compartment for each day of the production period for BDE-47, -99, and -209, based on model run A1 (see SI Figures S11 to S21 for remaining congeners). For all congeners except BDE-187, -149, -101, -66, and -49, the dominant input flux of BDE into the fish body is

dietary uptake. The variability in modeled fluxes corresponds to the scatter of simulated daily feed intake (see SI Figure S5). Only BDE-209 is also taken up via respiration. However, compared to dietary intake, this mass flux is small. The importance of different output fluxes is more variable: for most metabolically inactive congeners (BDE-209, -187, -154, -101, -100, -66, -49, and -47) the dominant output flux from the fish body compartment is fecal egestion. For the lowest brominated (and therefore most water-soluble) congener, BDE-28, loss via respiration is equal to loss via fecal egestion. For all congeners that undergo metabolic debromination (BDE-203, -183, -153, and -99), this process is the dominant loss flux. Model Evaluation. To evaluate our model, predicted concentrations of individual PBDE congeners in the simulated salmon fillet at the end of the production cycle were compared to measured concentrations (Figure 3). Olli et al. (2010)23 were not able to analytically separate BDE-49 and -71, therefore the cumulative concentration of these congeners is shown in Figure 3A. They did not measure BDE-101, -149, -187, and -203, therefore no measured values for these congeners are available. Both model runs A1 and A2 underestimate the total PBDE concentration in the fish fillet, but by less than a factor of 2, except for BDE-66, which is underestimated by a factor of 45. In both model runs, the dominant congener in the simulated fish fillet is BDE-47, and predicted concentrations correspond well with measurements. The modeled concentrations of BDE149, -183, -187, and -203, which were not measured, were very low at the end of the simulated production period. Model run A1 in particular underestimates the concentrations of BDE-99 and -209, though in both cases predictions are within a factor of 2 of the measured values. In model run A2, without biotransformation, the calculated concentrations of the parent congeners BDE-99 and BDE-153 are within 2% and 15%, respectively, of the values measured by Olli et al. (2010).23 The predicted concentrations of the product congeners BDE-49, -66, -101, -149, and -187, whose concentration in feed is unknown, and for which inputs are only via debromination, are consequently 0. The significantly better predictions for BDE-99 and -153 by model run A2 suggest that kM derived from in vitro experiments for these congeners is too high, while the substantial underestimation for BDE-66 (21 times lower than the measurements for model run A1 and predicted to be zero for model run A2) suggests an as yet unaccounted for source in the feed, including debromination of other congeners. Predictions for these simulations are based on assumed concentrations in water and feed (shown in Table 1), as Olli et al. (2010) did not specifically report these concentrations. Neither the water nor the feed concentrations profiles used included BDE-66. Yet substantial BDE-66 was found in salmon fillet by Olli et al. (2010), indicating that BDE66 was indeed present in water and/or feed. Alternatively, it is possible that an additional pathway for formation of BDE-66 via debromination of other congeners may exist, or that the efficiency of transformation from BDE-99 is substantially higher than estimated in the debromination pathways used (see SI Figure S8). Here the simulation of the Berntssen et al. (2010) study (model runs B1 and B2, Figure 3B) provides additional insight, as they specifically reported measured PBDE concentrations in the feed. In contrast with simulations A1 and A2 for the Olli et al. (2010) feeding study, model runs B1 and B2 generally overestimate the concentrations of BDE-47, -100, -66, and

Figure 2. Daily mass intake and loss of (A) BDE-47, (B) BDE-99, and (C) BDE-209 into farmed Atlantic salmon (whole body) over 500-day sea-cage growth cycle (model run A1). Scatter in predicted dietary uptake reflects variability in daily feed intake. E


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Figure 3. Comparisons between (A) Olli et al. (2010) data and model runs A1 and A2, with and without biotransformation, respectively, and (B) Berntseen et al. (2010) data and model runs B1 and B2, with and without biotransformation, respectively. Error bars for Olli et al. and Berntssen et al. data indicate reported variability. Error bars in model run A1 indicate predictions using the 25th and 75th percentile of reported feeding rates. Stars indicate that the congener was not measured in that study.

-154 measured by Berntssen et al. (2010).24 However, predicted concentrations are again well within a factor of 2 of measured values, except for BDE-99 for model run B1. We again see discrepancies driven by biotransformation. While the concentrations of parent congeners BDE-99 and -153 are underestimated by model run B1, model run B2 overestimates their fillet concentrations. This suggests biotransformation of these congeners does occur, but at a rate that is somewhat lower than those based on our in vitro extrapolation method. Sensitivity and Uncertainty. Based on our sensitivity analysis, model sensitivity for specific BDE congeners can be categorized into two groups. The first group consists of all congeners that are not metabolically active (BDE-209, BDE100, BDE-47, and BDE-28, see SI section S6). The normalized sensitivity coefficients (NSC) calculated for a 10% increase in parameter values for BDE-209, representative for the first group of congeners, are shown in SI Figure S9 for model run A1. The model output is most sensitive to the congener concentration in feed, the fish weight, the daily feed ration, and the KOW, in decreasing order. The feed concentration is particularly critical, because the estimated concentrations of PBDE in feed for model runs A1 and A2 are among the most uncertain parameters. For KOW, an increase in the parameter leads to a decrease in dietary uptake efficiency and therefore in the final PBDE concentration in the body. The model is relatively insensitive to parameters governing uptake and elimination via the gills. The second group is of those congeners influenced by metabolic debromination. The sensitivities for BDE-99, which are representative for this group, are shown in SI Figure S10. Here the most important parameters are the concentration in feed, daily feed ration, and fish weight. These three all have NSC with absolute values between 0.8 and 1. The next most important parameters, with NSC > ± 0.5, include those associated with metabolism (in vitro microsomal protein content, in vitro assay volume, in vitro degradation rate, microsomal protein content, hepatosomatic index, and fractional water content of blood), and lipid assimilation efficiency, all with similar sensitivity indices. Similarly to the congeners of the first group, the model is relatively insensitive to parameters governing uptake and elimination via the gills. However, for this group of congeners, in contrast with the first, the model is also relatively less sensitive to KOW.

We use three parameters to illustrate how the impacts of uncertainty can be evaluated using our sensitivity analysis. It has been previously shown that high uncertainties are associated with the KOW, solubility, and vapor pressures30,31,41of PBDEs. Our sensitivity analysis shows that the model is insensitive to both solubility and the Henry’s law coefficient (which includes both solubility and vapor pressure contributions). Thus, high uncertainty in their values would not change the predictions of the model. For KOW, on the other hand, the model is relatively sensitive (NSCKOW = −0.73), for the first group of congeners (represented by BDE-209, see SI Figure S9), and less so (NSCKOW = −0.19) for the second group of congeners (represented by BDE-99, see SI Figure S10). In both cases, increasing the KOW will decrease the predicted whole body concentration due to decreasing dietary uptake efficiency (see SI Figure S7). Assuming a 1 order of magnitude difference in KOW, we can use eq 2 to calculate a decrease in predicted PBDE concentration of a factor of 2 at most. As our model exhibits certain nonlinear characteristics, these normalized sensitivity coefficients should be treated with caution. More elaborate methods, such as Monte Carlo-based global sensitivity and uncertainty analysis, might be needed to fully assess the model sensitivity over a wider range of parameter values.

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DISCUSSION The concentrations of PBDEs in salmon fillet are well predicted by our modeltypically within a factor of 2despite substantial uncertainties associated with the input parameters. Nevertheless, differences in model performance with and without debromination can provide some useful insights. For model runs A1 and A2, underestimates for specific PBDE congeners could result from assuming concentrations in the modeled feed that are too low compared to those used in the feed by Olli et al. (2010).23 This is most likely the case for BDE-66, where the modeled final concentration in fillet is more than 45 times lower than the measured values. As Sanden (2014),34 which we used to parametrize feed concentrations for these model runs, did not measure BDE-66, we set the model feed concentration to 0 for this congener. Thus, the only input flux for BDE-66 stemmed from metabolic debromination of BDE-99. Measurements by Isosaari et al. (2005)20 and Berntssen et al. (2010)24 indicate, however, that BDE-66 is F


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Environmental Science & Technology also found in fish oil and meal used for the production of fish feed. A second factor that could cause underestimation of the final PBDE concentrations for some congeners is that extrapolated full-body metabolic rate constants for debromination are too high. This would result in an overestimation of the loss of parent congeners, which could explain the low fillet concentrations of BDE-99 and BDE-153 predicted by model run A1, and is further supported by the overestimation of BDE49 (the debromination product of BDE-99). The systematic underestimation of the parent congeners BDE-153 and -99 by model run B1, and the fact that the concentration profile for model run B2 is more similar to Berntssen et al. (2010),24 also supports this hypothesis. The model we present here supports dietary uptake as the dominant pathway for PBDE into salmon compared to the uptake via gills from local environmental contamination for all congeners. Previous empirical work has highlighted the importance of dietary uptake.16−20 Our model shows that this is due to PBDE concentrations in fish feed being significantly higher compared to environmental concentrations in the seawater. As Meng et al. (2008)25 suggested, however, uptake from water could be important for fish farmed in waters with higher contaminant loads. In all model runs BDE-47 is calculated to be the dominant congener in the fish fillet, in good agreement with previous studies.16,19,20,23,42,43 Isosaari et al. (2005)20 hypothesized the dominance of BDE-47 to be caused by the debromination of higher brominated congeners and the stability of BDE-47 toward further debromination reactions. According to Roberts et al. (2011),28 however, BDE-47 is not part of the debromination pathway of either Chinook salmon or rainbow trout (both salmonids). While it is unclear to what extent the debromination pathway for Chinook salmon also holds for Atlantic salmon, our model reproduced the measured fillet concentrations of BDE-47 rather well when only intake via dietary uptake and water were considered. This supports the hypothesis that BDE-47 in salmonids is not part of the debromination pathway, and that high fillet concentrations in Atlantic salmon fillet are likely from feed. For BDE-209, the influence of metabolic debromination on the concentration in the fish fillet is difficult to assess. Previous observations of BDE-209 accumulation in Salmo salar have been inconclusive. Some authors hypothesize that low concentrations of BDE-209 found in salmon fillet are due to metabolic debromination to lower brominated congeners.16,18,43 These findings stand in contrast to measurements by Olli et al. (2010),23 which indicate that uptake of BDE-209 in Atlantic salmon from feed is possible and that the metabolic potential of the salmon was not sufficient to fully debrominate the BDE-209. In contrast to rainbow trout and common carp, Roberts et al. (2011)28 found no degradation of BDE-209 in liver fractions of Chinook salmon. To conclusively assess the metabolic potential of Atlantic salmon for BDE-209, an exposure trial needs to be conducted. Our model assumes that Atlantic salmon, like Chinook salmon, do not debrominate BDE-209, and demonstrates that concentrations in the range of the measured values by Olli et al. (2010)23 could be reached by exposure via feed and water. A recent study44 found highly variable concentrations of PBDE in fish meal, fish oil, and fish feed of various European origins, ranging from total PBDE concentrations below the limit of detection up to 2.2 μg/kg. Additionally, the congener profiles of the examined samples

varied markedly. While the authors found no BDE-209 in the two samples of fish oil and complete fish feed, 5 out of 10 samples of fish meal contained BDE-209 concentrations varying between 1 and 15 μg/kg lipid. Assuming a fish meal content of 35%,23 fish feed would contain between 0.07 and 0.52 μg/kg BDE-209, which is comparable to the concentrations found by Hites et al. (2004).16 Our model has the following limitations. First, it is a singlecompartment model, which does not account for the distribution of PBDEs to different organs, such as the liver or muscle. For some higher brominated PBDE congeners, preferential distribution to liver tissues has been observed for wild common dab (Limanda limanda), whiting (Merlangius merlangus), and pouting (Trisopterus luscus).45 Furthermore, the preferential accumulation of BDE-209 has been observed in the liver of juvenile rainbow trout (Oncorhynchus mykiss)37 and Chinese sturgeon (Acipenser sinensis).46 The reason for preferential distribution of these congeners to liver is currently unclear. However, it could cause PBDE concentrations of higher brominated PBDE congeners in fillet to be lower than calculated by the model. Modeling the fish body as a single compartment further neglects the effects of differential organ growth and lipid accumulation. Berntssen et al. (2005)21 found muscle fat deposition in Atlantic salmon to rapidly increase compared to the rest of the body when the fish reached a weight of approximately 1 kg. Such differences in relative growth rates of the lipid compartment could significantly influence the uptake and distribution kinetics of PBDE in Atlantic salmon, which is primarily lipid driven. A third limitation of the model is the missing link between temperature, salmon growth and feed intake. It has generally been observed that salmon feed intake in aquaculture conditions decreases with temperature.47 However, the growth rate of the fish does not necessarily change accordingly.48 This can also be observed in the feeding data used as input for the model: during cold water periods, feed intake decreases, whereas the growth rate remains approximately constant. Furthermore, in warmer months of the production periods, feed intake increased, while growth rates did not increase by the same order of magnitude. By linking temperature, feed intake and growth of farmed Atlantic salmon, the PBDE fillet concentrations could be predicted independent of a specific aquaculture scenario. This could be achieved by implementing a bioenergetic model for aquaculture salmon into the bioaccumulation model. If diet is the most important uptake route for PBDEs into salmon, the final concentrations reached in the fillet are strongly influenced by the ratio of growth and feeding rate. This so-called feed-conversion ratio (i.e., the ratio of total amount of weight gained to amount of feed fed) is a parameter closely monitored in aquaculture practices and strongly depends on the salmon strain and animal husbandry. By using strains of salmon with a maximum feed-conversion ratio (which promotes growth dilution) and by optimizing farming practices, the concentration of PBDEs in fillet of farmed salmon can be reduced. The consumption of salmon raised under such optimal production conditions would therefore lead to a lower exposure to PBDEs. The limited influences of local sources of pollution on the concentration of PBDEs in farmed salmon has implications for how hazardous chemicals are transported via food trade.15 In the case of farmed salmon, it is not necessarily the origin of the farmed fish but of the feed or feed ingredients used in its G


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(4) Watanabe, I.; Sakai, S. Environmental Release and Behavior of Brominated Flame Retardants. Environ. Int. 2003, 29 (6), 665−682. (5) Alaee, M.; Arias, P.; Sjödin, A.; Bergman, Åke. An Overview of Commercially Used Brominated Flame Retardants, Their Applications, Their Use Patterns in Different Countries/Regions and Possible Modes of Release. Environ. Int. 2003, 29 (6), 683−689. (6) Wang, Y.; Jiang, G.; Lam, P. K. S.; Li, A. Polybrominated Diphenyl Ether in the East Asian Environment: A Critical Review. Environ. Int. 2007, 33, 963−973. (7) Centers for Disease Control and Prevention. Biomonitoring Summary Polybrominated Diphenyl Ethers, 2013. (8) European Food Safety Authority. Scientific Opinion on Polybrominated Diphenyl Ethers (PBDEs) in Food. EFSA J. 2011, 9 (5), 1−274. (9) UNEP. The 9 New POPs; 2010. (10) USEPA. Action Plan Fact Sheet April 2011. 2011. (11) ECHA. ECHA Proposes a Restriction on DecaBDE, a Brominated Flame Retardant Used in Plastics and Textiles 2014, 69 (6), 1−4. (12) Li, Y.; Lin, T.; Hu, L.; Feng, J.; Guo, Z. Time Trends of Polybrominated Diphenyl Ethers in East China Seas: Response to the Booming of PBDE Pollution Industry in China. Environ. Int. 2016, 92−93, 507−514. (13) Ross, P. S.; Couillard, C. M.; Ikonomou, M. G.; Johannessen, S. C.; Lebeuf, M.; Macdonald, R. W.; Tomy, G. T. Large and Growing Environmental Reservoirs of Deca-BDE Present an Emerging Health Risk for Fish and Marine Mammals. Mar. Pollut. Bull. 2009, 58 (1), 7− 10. (14) Trudel, D.; Tlustos, C.; Von Goetz, N.; Scheringer, M.; Hungerbühler, K. PBDE Exposure from Food in Ireland: Optimising Data Exploitation in Probabilistic Exposure Modelling. J. Exposure Sci. Environ. Epidemiol. 2011, 21 (6), 565−575. (15) Ng, C. A.; von Goetz, N. The Global Food System as a Transport Pathway for Hazardous Chemicals: The Missing Link between Emissions and Exposure. Environ. Health Perspect. 2017, 125 (1), 1−7. (16) Hites, R. A.; Foran, J. A.; Schwager, S. J.; Knuth, B. A.; Hamilton, M. C.; Carpenter, D. O. Global Assessment of Polybrominated Diphenyl Ethers in Farmed and Wild Salmon. Environ. Sci. Technol. 2004, 38 (19), 4945−4949. (17) Jacobs, M. N.; Covaci, A.; Schepens, P. Investigation of Selected Persistent Organic Pollutants in Farmed Atlantic Salmon (Salmo Salar), Salmon Aquaculture Feed, and Fish Oil Components of the Feed. Environ. Sci. Technol. 2002, 36 (13), 2797−805. (18) Montory, M.; Barra, R. Preliminary Data on Polybrominated Diphenyl Ethers (PBDEs) in Farmed Fish Tissues (Salmo Salar) and Fish Feed in Southern Chile. Chemosphere 2006, 63 (8), 1252−1260. (19) Shaw, S. D.; Berger, M. L.; Brenner, D.; Carpenter, D. O.; Tao, L.; Hong, C. S.; Kannan, K. Polybrominated Diphenyl Ethers (PBDEs) in Farmed and Wild Salmon Marketed in the Northeastern United States. Chemosphere 2008, 71 (8), 1422−1431. (20) Isosaari, P.; Lundebye, A.; Ritchie, G.; Lie, Ø.; Kiviranta, H.; Vartiainen, T.; Lundebye, A.; Ritchie, G.; Lie, Ø.; Kiviranta, H.; et al. Dietary Accumulation Efficiencies and Biotransformation of Polybrominated Diphenyl Ethers in Farmed Atlantic Salmon (Salmo Salar). Food Addit. Contam. 2005, 22 (9), 829−837. (21) Berntssen, M. H. G.; Lundebye, A. K.; Torstensen, B. E. Reducing the Levels of Dioxins and Dioxin-like PCBs in Farmed Atlantic Salmon by Substitution of Fish Oil with Vegetable Oil in the Feed. Aquacult. Nutr. 2005, 11 (3), 219−231. (22) Berntssen, M. H. G.; Valdersnes, S.; Rosenlund, G.; Torstensen, B. E.; Zeilmaker, M. J.; van Eijkeren, J. C. H. Toxicokinetics and Carryover Model of Alpha-Hexabromocyclododecane (HBCD) from Feed to Consumption-Sized Atlantic Salmon (Salmo Salar). Food Addit. Contam., Part A 2011, 28 (9), 1274−1286. (23) Olli, J. J.; Breivik, H.; Mørkøre, T.; Ruyter, B.; Johansen, J.; Reynolds, P.; Thorstad, O.; Berge, G. Removal of Persistent Organic Pollutants from Atlantic Salmon (Salmo Salar L.) Diets: Influence on Growth, Feed Utilization Efficiency and Product Quality. Aquaculture 2010, 310 (1−2), 145−155.

production that must be taken into account to accurately trace the origins of human dietary exposure to PBDEs. Fish oils in particular have been found to contain high concentrations of persistent organic pollutants, prompting decontamination studies such as those by Olli et al. (2010) and Berntssen et al. (2010).23,48 The model we developed in this work seeks to make explicit the competing contributions of feed concentrations, water concentrations, biotransformation, and fish physiology (including also fish growth and feed conversion efficiency). By making these links, the model could be extended and modified to assess the influence of environmental and production-specific conditions of other fish with high global trading volumes, such as Tilapia or red snapper. Particular attention should be given to food species or feeds produced in the contamination “hot-spots” of densely populated areas. The model could similarly be used to evaluate contaminant control strategies such as replacing fish oils with plant-based materials in feed or decontamination of fish oil. The model developed here performed well in predicting congener-specific PBDE concentrations in farmed salmon. The major strength of the model is its ability to simultaneously treat multiple congeners in a dynamic way. This includes the tracking of lower brominated congeners that accumulate from direct uptake and the debromination of higher brominated congeners. Moreover, the mechanistic approach of the model allows us to discern the relative contributions of different uptake routes, and notably the influence of feed. This model framework could be readily adapted to other metabolizable compounds and their transformation products.

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ASSOCIATED CONTENT

S Supporting Information *

The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acs.est.8b00146. Details on model parametrization and sensitivity analysis (PDF)

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AUTHOR INFORMATION

Corresponding Authors

*(C.A.N.) Phone: +1 412 383 4075; e-mail: [email protected]. *(N.v.G.) Phone: +41 44 632 0975; e-mail: natalie.von.goetz@ chem.ethz.ch. ORCID

Natalie von Goetz: 0000-0001-5257-4573 Notes

The authors declare no competing financial interest.

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ACKNOWLEDGMENTS We thank Harald Breivik of Neperdo Biomarine, Norway, for kindly providing the feeding rate data used in this study.

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REFERENCES

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Polybrominated Diphenyl Ether (PBDE) Accumulation in Farmed

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