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Environmental Modeling

Polybrominated diphenyl ether (PBDE) accumulation in farmed salmon evaluated using a dynamic sea-cage production model. Carla Ng, Amélie Ritscher, Konrad Hungerbuehler, and Natalie von Goetz Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/acs.est.8b00146 • Publication Date (Web): 26 Apr 2018 Downloaded from http://pubs.acs.org on April 27, 2018

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Environmental Science & Technology

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Polybrominated diphenyl ether (PBDE) accumulation in farmed salmon evaluated

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using a dynamic sea-cage production model.

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Carla A. Ng1*, Amélie Ritscher2, Konrad Hungerbuehler2, and Natalie von Goetz2*

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O’Hara St, Pittsburgh, PA, USA 15261.

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2

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Zurich, Switzerland.

Department of Civil and Environmental Engineering, University of Pittsburgh, 3700

Institute for Chemical and Bioengineering, ETH Zurich, Vladimir-Prelog-Weg 1, 8093

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*corresponding authors:

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Carla A. Ng, +1 412 383 4075, [email protected]

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Natalie von Goetz, +41 44 632 0975, [email protected]

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ACS Paragon Plus Environment

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Abstract

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Food is an important source of human exposure to hazardous chemicals. Chemical

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concentration in a food item depends on local environmental contamination, production

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conditions, and, for animal-derived foods, on feed. Here, we investigate these influences

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on the accumulation of individual polybrominated diphenyl ether congeners (PBDEs) in

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farmed Atlantic salmon (Salmo salar). We develop a dynamic model over a full sea-cage

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salmon production cycle. To assess the influence of metabolic debromination on PBDE

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congener profiles, in vitro measurements of debromination rates in fish liver cells were

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extrapolated to whole-body metabolic rate constants. Model results indicate that the

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dominant factors governing PBDE concentration in Atlantic salmon fillet are uptake via

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contaminated feed and fish growth, while the influence of metabolic debromination is

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minor. PBDE concentrations in fish feed depend on several factors, including the

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geographic origin of fish feed ingredients, which are produced and traded globally.

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Human exposure to PBDE via salmon consumption is less influenced by environmental

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concentrations at the location of salmon farming than by environmental concentrations

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influencing feed components. This dependence of PBDE concentrations in salmon on the

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origin and composition of feed reveals the complexity of predicting contaminant

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concentrations in globally traded food.

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Introduction

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Polybrominated diphenyl ethers (PBDEs) are a class of synthetic flame retardants which

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have been extensively used to increase the fire resistance of consumer products, such as

50

foam paddings, textiles, and plastics1. PBDEs can be released into the environment

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during production, use and disposal of treated products, leading to their detection in a

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variety of environmental and biological samples2,3, including human tissues4–6. PBDEs

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comprise 209 different with different numbers of bromines attached to their diphenyl

54

ether structure. There are three major commercial mixtures: Penta-, Octa- and Deca-BDE,

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named for the degree of bromination of the dominant congener in the mixture. Deca-

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BDE, the most widely used mixture,3 is added to polymeric materials such as

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polystyrene, polybutylene, nylon, polypropylene and other thermoelastic plastics, and

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contains more than 96% BDE-209, the highest-brominated congener. Fire-protected

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polypropylene can contain up to 23% Deca-BDE by weight7.

60 61

Due to environmental and public health concerns, Penta- and Octa-BDE mixtures were

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banned in Europe and the United States in 2004. Some PBDEs are disruptive of thyroid

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hormone homeostasis and some are associated with neurodevelopmental and behavioral

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effects in rodents8. In 2009, tetra- and pentabromodiphenyl ethers were listed under the

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Stockholm Convention as persistent organic pollutants9. In the United States,

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manufacturers agreed to voluntarily phase out Deca-BDE by the end of 2013, and in

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August 2014, the European Chemicals Agency (ECHA) submitted a proposal to restrict

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the use of Deca-BDE in the European Union10,11. Following these actions, PBDE

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manufacturing moved to less developed countries such as China, India, Indonesia,


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Thailand and Vietnam12. As products containing PBDE flame retardants have a relatively

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long lifetime, emissions to the environment will most likely continue despite increasing

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regulations. Due to their hydrophobicity and preferential partitioning into particulate

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phases, large environmental reservoirs are being created in sediments, which might

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present a long-term threat to biota13.

75 76

The dominant pathway for human exposure to PBDEs is consumption of contaminated

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food8. To estimate human exposure to such potentially hazardous chemicals, modeling

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approaches are often applied that rely on measured levels in the foods of interest14.

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However, data on food origin is normally not addressed and, due to the global nature and

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interconnectedness of the international food trade system, local environmental emissions

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or regulations can influence human exposure to a contaminant on a much larger scale.

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Although there are already human exposure models in place that account for local

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emissions, chemical fate, and bioaccumulation, existing models do not account for the

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global transport of chemicals via food trade15. Such consideration can be particularly

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problematic for the consumption of animal products, as the food sources of the animals

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themselves come into play. A particularly salient example is that of farmed predatory

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fish. Both fish consumption and aquaculture have increased rapidly over the last forty

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years. Salmon is one of the most widely consumed fish, and more than 50% of salmon

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sold globally—mostly Atlantic salmon, Salmo salar—is farmed16.

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Halogenated organic contaminants in aquaculture fish, including PBDEs, have gained

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considerable attention during the last decade16–19. Most of this work has focused on


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polychlorinated biphenyls and dioxins. However, a few studies have also investigated

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PBDEs. Feed is generally considered to be the most important source for persistent

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organic pollutants in farmed fish, with 35-59% of the total PBDE intake via feed

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accumulating in the salmon fillet over 8-12 months trial periods20–22. Reducing PBDE

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concentrations in feed can result in lower PBDE concentrations in fish fillet23,24. On the

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other hand, Meng et al. (2008)25 highlighted the importance of the surrounding

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environment, finding higher concentrations of PBDEs in seawater-farmed fish than in

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freshwater-farmed fish fed with the same fish feed. They hypothesized this concentration

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difference was caused by higher concentrations of PBDE in coastal waters from riverine

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discharge. However, no direct comparison of the influence of feed versus environmental

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concentrations in a single study has been made.

104 105

The role of metabolic debromination on PBDE congener profiles in fish also remains

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unclear. Most studies have identified BDE-47 as the dominant PBDE congener in salmon

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fillet. While congener profiles in commercially available fish feed can be very similar to

108

those measured in salmon fillet16,18, Isosaari et al. (2005)20 hypothesized that the high

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concentrations of BDE-47 found in salmon fillet could be caused by metabolic

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debromination of higher brominated congeners. In a feeding study of Atlantic salmon

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with fish feed cleaned of persistent organic pollutants, Olli et al. (2010)23 found BDE-209

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in considerable concentrations in the control group of Salmon fed with conventional fish

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feed. This indicates that BDE-209 might have the potential to accumulate in salmon

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fillets. However, Hites et al. (2004)16 and Montory and Barra (2006)18 found very low

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concentrations of higher brominated congeners in salmon fillets, and BDE-209 was not


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detected, despite being present in the analyzed samples of fish feed. The authors

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hypothesized the absence of BDE-209 in fillet samples to be caused either by low

118

bioavailability or by metabolic transformation of the substance to lower brominated

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congeners. Neither the feeding study conducted by Isosaari et al. (2005)20 nor Berntssen

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et al. (2010)24 included higher brominated congeners than BDE-183.

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Metabolic debromination of PBDEs in fish has been demonstrated by a number of

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studies26,27. However, a recent in vitro assessment of metabolic PBDE debromination in

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liver sub-fractions of common carp, rainbow trout and Chinook salmon revealed

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considerable inter-species differences in metabolic debromination capacities28, and the

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products of debromination reactions of individual PBDE congeners differed between

127

common carp and the other two species. It is therefore unclear to what extent the

128

metabolic debromination of PBDEs influences their concentrations in individual fish

129

species.

130 131

The aim of this work is twofold: first, to investigate how local environmental

132

concentrations and production conditions—including choices about feed composition and

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origin—influence concentrations of PBDE in farmed salmon, and second, to consider the

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influence of metabolic debromination on congener profiles in farmed fish. For these

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purposes, we have developed a dynamic multi-chemical bioaccumulation model for a

136

complete sea-cage production period. This approach allows us to evaluate the

137

contributions of the most important sources, and to assess the importance of other factors,

138

such as metabolic debromination, to PBDE concentrations in Atlantic salmon fillets.


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Finally, we discuss the implications of these factors for the transport of PBDEs via global

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food trade.

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Materials and Methods

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Mass balance model framework

144

Our dynamic, one-compartment fugacity-based box model for PBDE uptake in an

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individual salmon is based on the dynamic bioaccumulation model for PBDEs in lake

146

trout developed by Bhavsar et al. (2008)29. Tissue-specific properties and processes

147

related to the gills, fish body, and gastrointestinal (GI) tract are used to parameterize

148

PBDE uptake and loss to the whole body compartment (Figure S1). Details on the

149

process equations, variables, and their sources are provided in SI section S1. Here, we

150

briefly describe the overall structure of the multi-chemical mass balance.

151 152

The complete PBDE mass balance in the fish body includes uptake of a congener from

153

water and food, excretion via respiration and fecal egestion, and biotransformation29

154

expressions that describe the change in the fugacity of a congener in the fish body due to

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metabolic reactions (including debromination (loss) of the modeled congener, y, and

156

inputs due to the debromination of its parent congener, x): ௗ௠೤

157

158

ௗ௧

=

௏ಷ ⋅௓ಷ,೤ ⋅ௗ௙ಷ,೤ ௗ௧

= ‫ܧ‬ௐ,଴,௬ ⋅ ‫ܦ‬௏,௬ ⋅ ݂ௐ,௬ + ‫ܧ‬஽,଴,௬ ⋅ ‫ܦ‬஽,௬ ⋅ ݂஽,௬ + ߥ௫௬ ⋅ ‫ܦ‬ெ,௫ ⋅ ݂ி,௫

− ቀ൫‫ܧ‬ௐ,଴,௬ ⋅ ‫ܦ‬௏,௬ ൯ + ൫‫ܧ‬஽,଴,௬ ⋅ ‫ܦ‬ொ,௬ ൯ + ‫ܦ‬ெ,௬ ቁ ⋅ ݂ி,௬

Equation 1

159 160

The change in mass of a particular PBDE congener y in the fish, dmy/dt, is given by the


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product of the fish volume (VF), its fugacity capacity for congener y (ZF,y) and the change

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in the fugacity of congener y in the fish as a function of time, dfF,y/dt. The product EW,0,y ·

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DV,y · fW,y describes the uptake of congener y from water, while ED,0,y · DD,y · fD,y is the

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uptake of congener y from food. EW,0,y and ED,0,y describe the initial chemical uptake

165

efficiencies from water and food, respectively (at time 0) and DV,y and DD,y are the

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transport parameters, or D-values, for respiratory and dietary uptake (see SI section S1).

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EW,0,y · DV,y · fF,y describes the loss of chemical via the gills and ED,0,y · DQ,y · fF,y is the loss

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via fecal elimination. DM,x and DM,y are the D-values for the debromination of congeners x

169

and y, fF,x is the fugacity of congener x in the fish body, fF,y is the fugacity of the

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debromination product y in the fish body, and vxy is the fraction of the parent congener x,

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that is debrominated to the product y. The model is solved numerically using Matlab

172

(MATLAB 8.3.0.532, The MathWorks Inc., Natick, MA, 2014) to produce the

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concentration of each modeled congener in each compartment as a function of time.

174 175

PBDE congeners

176

Specific PBDE congeners are considered in the model if concentration data in fish feed

177

were available (see PBDE concentrations in feed, below) or if it was part of the

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debromination pathway of a congener present in feed (see PBDE biotransformation,

179

below).

180 181

The octanol-water partition coefficient (KOW) and Henry's law constant (H) are used to

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calculate each congener's fugacity capacity, Z, for lipid, non-lipid organic matter, and

183

water. For all PBDE congeners used in the model, we used the KOW for homologue


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structures estimated by Wania and Dugani (2003)30 (Table S1). Henry's law constants

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were calculated according to the regression equation derived by Tittlemeier et al. (2002)31

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for the sub-cooled liquid phase.

187 188

Sea-cage life cycle simulations

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The production and life cycle of aquaculture salmon consists of several stages. Eggs are

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stripped from broodstock fish, fertilized, and hatched in freshwater facilities. The young

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fish are kept in freshwater tanks on land for up to 12 months until they undergo a so-

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called parr-smolt transformation. During this transformation, the metabolic system of the

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salmon adapts to saltwater conditions. Smolted fish are then transferred to sea sites and

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further grown in large net cages in coastal waters for another 12 to 18 months until they

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reach a slaughter weight of 4-5 kg. Due to deterioration of flesh quality, the salmon are

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usually harvested before sexual maturation32. We consider the fish life cycle from the

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time smolted fish are transferred to the sea site until harvest, corresponding to a model

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run of 500 days. Two independent simulations were run to evaluate the influence of

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production conditions and biotransformation. The first simulation was parameterized

200

according to the feeding study of Olli et al. (2010)23, hereafter referred to as model run A.

201

The second was parameterized according to the study of Berntssen et al. (2010)24,

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hereafter referred to as model run B. These independent simulations were necessary to

203

reduce uncertainties in the evaluation of simulation performance, because the Olli et al.

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study had higher resolution physiological and feeding data, but no PBDE concentrations

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reported in feed, whereas the Berntssen et al. study had only average feeding data but

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specified PBDE concentrations in feed.


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Fish physiology and feeding rates

209

In the feeding study conducted by Olli et al. (2010)23, used as the basis for model run A,

210

the authors collected a variety of physiological parameters, including fish weight,

211

volume, proximate composition (including lipids, non-lipid organic matter, and water),

212

and respiration rates over the course of a complete seawater production cycle, starting

213

from July 2007 to December 2008. Physiological parameters derived from this study are

214

detailed in SI section S3.

215 216

Feeding rates for model run A were based on actual feeding data recorded for the Olli et

217

al. (2010)23 study (SI Figure S5). These data were generously provided to us (Harald

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Breivik, Neperdo Biomarine, Norway, 2016, personal communication). The average daily

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ration per fish was calculated for cages fed with conventional fish feed. Where there were

220

missing data for an individual cage, it was omitted from the calculation of average daily

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intake. For days where there were no feeding data for any cage available, daily ration was

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linearly interpolated from measurements from the previous and following days. There

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were feeding data available for 479 out of 498 days of the study (96%, see section S3.7).

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Variability in reported feeding rates was propagated to model results by calculating

225

PBDE concentrations based on the 25th percentile, 75th percentile, and mean daily rations.

226 227

For model run B, values for fish body weight were fitted to a power function based on the

228

values given by Berntssen et al. (2010). The fitted function compared to the

229

measurements by Berntssen et al. (2010) is shown in Figure S6. Berntssen et al. (2010)


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do not provide any information on proximate composition of the fish used for the trial. It

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was therefore assumed that the proximate composition of a fish at the beginning and the

232

end of model run B is equal to the composition of a fish in the model run A with the same

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weight. Berntssen et al. (2010) only report daily average feed data from three

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experimental periods, comprising 8 of the 12 months of the trial. We interpolate daily

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feed intakes for model run B from these average daily feed intakes as described in SI

236

section S3.8.

237 238

For both model runs, comparison of predicted to measured concentrations required

239

conversion from whole body (predicted by the model) to fillet (provided in the feeding

240

studies) concentrations. This was done by multiplying lipid-based whole-body

241

concentrations by the ratio of fillet to whole-body lipid contents (see SI section S3.11).

242 243

PBDE concentrations in water

244

Few measurements of dissolved PBDE concentrations in coastal seawater are available.

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Here, the concentrations of PBDEs in the dissolved fraction measured by Möller et al.

246

(2012)33 on three different cruises in the marine coastal environment of the North Sea

247

from March to July 2010 were averaged and used as model input (Table 1). These were

248

assumed to be representative of the concentrations found in the coastal region of a

249

Norwegian fjord (see SI section S4.1). For BDE-203, no measurements in sea- or

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freshwater are available in literature. However, in the debromination pathway of Chinook

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salmon28, this congener is an important “upstream” parent compound. In order to

252

investigate the influence of BDE-203 on the PBDE concentrations in the fish body


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compartment, its concentration in seawater was estimated. In commercial PBDE

254

mixtures, BDE-203 is only present in the technical Octa-BDE mixture, where its

255

concentrations range from 5-35%. BDE-183 is also present only in the technical mixture,

256

where it constitutes 40% of all PBDE congeners10. It was assumed that the ratio of BDE-

257

183 to BDE-203 in the water is the same as the ratio found in the Octa-BDE, selecting

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35% as an upper bound for BDE-203 (Table 1).

259 260

PBDE concentrations in feed

261

Olli et al. (2010)23 did not report the concentration of individual PBDE congeners in the

262

feed used in their study. Therefore, average concentrations reported by the Norwegian

263

public monitoring and mapping program for fish food were used as inputs for model run

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A for the indicator PBDEs (BDE-183, -154, -153, -100, -99, -47, -28)34. Concentration

265

data for higher brominated PBDE congeners in fish feed are also scarce. Hites et al.

266

(2004)16 reported concentrations for sum of PBDE in fish feed purchased in Scotland,

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British Columbia, eastern Canada, and Chile. In these feed samples, BDE-209 was

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reported to average 15 ± 5% of the total PBDE measured. Based on this, the

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concentration of BDE- 209 in fish feed was modelled as 15% of the averaged total PBDE

270

concentration reported by Hites et al. (2004)16. In order to maintain consistency between

271

the two data sources, the earliest values reported by Sanden (2014)34 (from the year 2004)

272

were used for the concentrations of all other PBDE congeners. No measurements of

273

BDE-203 in feed were available in literature. For model run A, we assumed that the ratio

274

of BDE-183 to BDE- 203 in the fish feed is the same as the ratio found in Octa-BDE

275

(Table 1). The concentrations of individual PBDE congeners in fish feed as reported by


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Berntssen et al. (2010) were used directly as input for model run B (Table 1).

277 278

PBDE Biotransformation

279

The metabolic degradation of PBDE in fish is generally considered to occur via reductive

280

debromination28,35–39. Roberts et al. (2011)28 examined the nature and amounts of

281

metabolites of in vitro debromination of various BDE congeners (28, 47, 49, 99, 100,

282

153, 154, 183, 203, 208 and 209) by microsomal fractions of adult rainbow trout

283

(Oncorhynchus mykiss), adult carp (Cyprinus carpio) and juvenile Chinook salmon

284

(Oncorhynchus tschwatcha). Based on the results of individual incubations of BDE

285

congeners, the authors constructed a metabolic pathway for each fish species. These

286

pathways were markedly different between the species, with carp liver fractions having

287

significantly higher metabolic capacities, both in terms of reaction rate and

288

debromination products formed, compared to rainbow trout and Chinook salmon. The

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debromination pathways found for rainbow trout and Chinook salmon are shown in

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Figure S8. Based on the amount of debromination products after 24 hours incubation

291

time, Roberts et al. (2011)28 calculated in vitro metabolite formation rates. Due to the

292

lack of any further data on rate constants for metabolic reductive debromination in fish,

293

we extrapolated these product formation rates to whole-body, in vivo first-order

294

biotransformation rate constants (kM) for salmon using a four-step process: (1) intrinsic

295

hepatic in vitro clearance rates were calculated from the depletion rate of the parent

296

metabolite in Chinook salmon28; (2) this in vitro clearance was extrapolated to in vivo

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clearance using the average measured hepatosomatic index (HSI) of the fish in the Olli et

298

al. (2010)23 study and the amount of microsomal protein in the liver estimated for trout by


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Nichols et al. (2006)40; (3) the intrinsic hepatic in vivo clearance rate was extrapolated to

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total hepatic clearance based on the rate of liver blood flow, fish weight, and the blood-

301

water partition coefficient of individual PBDE congeners; (4) finally, the whole body

302

biotransformation rate constant (kM) was determined using the volume of distribution of

303

the chemical between the blood and other tissues. Details of these four steps, including all

304

equations and parameters used, are given in SI section S5.

305 306

In order to investigate the influence of debromination on model performance, each

307

feeding study was run with and without biotransformation. Simulations run with

308

biotransformation are referred to as model run A1 and B1 for the Olli et al. (2010)23 and

309

Berntssen et al. (2010)24 studies, respectively. Model runs without biotransformation, in

310

which kM for all congeners is set to zero, are referred to as A2 and B2.

311 312

Sensitivity and Uncertainty

313

Many parameters used in the model are based on estimated values and therefore are

314

associated with considerable uncertainty. In order to understand the influence of this

315

uncertainty on model predictions, model sensitivity to all input parameters was

316

investigated using a factor-at-a-time approach. Each model parameter was varied by 10%

317

of its value, while all other parameters were kept at their nominal value. Normalized

318

sensitivity coefficients for each parameter (ܰܵ‫ܥ‬௉ ) were calculated as follows (MacLeod

319

et al., 2002):

320

ܰܵ‫ܥ‬௉ =

ఏିఏబ ௉ି௉బ

⋅

௉బ

ఏబ

Equation 2


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321

where ܲ is the varied parameter value, ܲ଴ is the nominal value of the parameter used in

322

the model, ߠ଴ is the nominal model output and ߠ is the model output calculated with the

323

varied parameter. As some of the congeners are debrominated metabolically or formed

324

via metabolic debromination and other congeners are solely taken up via food and water,

325

the model structure for these congeners is different. Therefore the sensitivity analysis was

326

carried out for each individual congener considered in the mass balance. The endpoint

327

evaluated was the concentration of each congener in the fish body at the end of a 500-day

328

production period, based on model run A1.

329 330

Results

331

In the following sections, the concentration dynamics and PBDE fluxes predicted by the

332

model are first illustrated for selected congeners using model run A1. Predicted

333

concentrations and congener distributions are then compared to available data23,24 for all

334

four model runs.

335

Concentration Dynamics

336

The modeled concentrations of different PBDEs in the fish body predicted by model run

337

A1 span more than three orders of magnitude. Most congeners show similar dynamics

338

with time. In Figure 1, we illustrate these concentration dynamics with the results for

339

model run A1 for congeners BDE-47, 99 and 209.

340 341

The concentration of BDE-47 predicted by the model is one order of magnitude higher

342

than BDE-99 and -209, which are similar. For these and most other congeners,

343

concentrations increase steeply for the first 100 days of production, then decrease again.


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344

Around day 250 of the production period, most congeners reach a quasi-steady state and

345

their concentrations remain constant for the next 100 days. Concentrations then increase

346

again for the last 150 days of production. Differences among congeners are largely driven

347

by differences in uptake and loss fluxes, as discussed below, which in turn are strongly

348

dependent on the KOW, which affects dietary and gill uptake efficiencies as well as

349

elimination rates. The shape of the concentration curve with time is largely driven by the

350

balance of changing consumption rates with fish size, growth dilution, temperature

351

(which seasonally affects rates of consumption), and metabolic capacity. Of these, the

352

influence of size and growth is particularly strong. Small fish have relatively high

353

consumption rates, leading to rapid uptake at the beginning of the modeling period.

354

Dietary uptake (absolute, not normalized to size) increases with size. The highest growth

355

period for the modeled fish begins around day 125, and the dilution associated with

356

strong growth drives the decline between days 100 and 200, before approaching steady

357

state.

358 359

Input and Output Fluxes

360

Figure 2 shows PBDE mass fluxes into and out of the fish body compartment for each

361

day of the production period for BDE-47, -99 and -209, based on model run A1 (see SI

362

Figures S11 to S21 for remaining congeners). For all congeners except BDE-187, -149, -

363

101, -66 and -49, the dominant input flux of BDE into the fish body is dietary uptake.

364

The variability in modeled fluxes corresponds to the scatter of simulated daily feed intake

365

(see Figure S5). Only BDE-209 is also taken up via respiration. However, compared to

366

dietary intake, this mass flux is small.


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367 368

The importance of different output fluxes is more variable: for most metabolically

369

inactive congeners (BDE-209, -187, -154, -101, -100, -66, -49 and -47) the dominant

370

output flux from the fish body compartment is fecal egestion. For the lowest brominated

371

(and therefore most water soluble) congener, BDE-28, loss via respiration is equal to loss

372

via fecal egestion. For all congeners that undergo metabolic debromination (BDE-203, -

373

183, -153 and -99), this process is the dominant loss flux.

374 375

Model Evaluation

376

To evaluate our model, predicted concentrations of individual PBDE congeners in the

377

simulated salmon fillet at the end of the production cycle were compared to measured

378

concentrations (Figure 3). Olli et al. (2010)23 were not able to analytically separate BDE-

379

49 and -71, therefore the cumulative concentration of these congeners is shown in Figure

380

3A. They did not measure BDE-101, -149, -187 and -203, therefore no measured values

381

for these congeners are available. Both model runs A1 and A2 underestimate the total

382

PBDE concentration in the fish fillet, but by less than a factor of 2, except for BDE-66,

383

which is underestimated by a factor of 45. In both model runs, the dominant congener in

384

the simulated fish fillet is BDE-47, and predicted concentrations correspond well with

385

measurements. The modeled concentrations of BDE-149, -183, -187 and -203, which

386

were not measured, were very low at the end of the simulated production period. Model

387

run A1 in particular underestimates the concentrations of BDE-99 and -209, though in

388

both cases predictions are within a factor of 2 of the measured values.

389


17


Page 18 of 36

390

In model run A2, without biotransformation, the calculated concentrations of the parent

391

congeners BDE-99 and BDE-153 are within 2% and 15%, respectively, of the values

392

measured by Olli et al. (2010)23. The predicted concentrations of the product congeners

393

BDE-49, -66, -101, -149 and -187, whose concentration in feed is unknown, and for

394

which inputs are only via debromination, are consequently 0. The significantly better

395

predictions for BDE-99 and -153 by model run A2 suggest that kM derived from in vitro

396

experiments for these congeners is too high, while the substantial underestimation for

397

BDE-66 (21 times lower than the measurements for model run A1 and predicted to be

398

zero for model run A2) suggests an as yet unaccounted for source in the feed, including

399

debromination of other congeners. Predictions for these simulations are based on

400

assumed concentrations in water and feed (shown in Table 1), as Olli et al. (2010) did not

401

specifically report these concentrations. Neither the water nor the feed concentrations

402

profiles used included BDE-66. Yet substantial BDE-66 was found in salmon fillet by

403

Olli et al. (2010), indicating that BDE-66 was indeed present in water and/or feed.

404

Alternatively, it is possible that an additional pathway for formation of BDE-66 via

405

debromination of other congeners may exist, or that the efficiency of transformation from

406

BDE-99 is substantially higher than estimated in the debromination pathways used (see

407

SI figure S8). Here the simulation of the Berntssen et al. (2010) study (model runs B1 and

408

B2, Figure 3B) provides additional insight, as they specifically reported measured PBDE

409

concentrations in the feed.

410 411

In contrast with simulations A1 and A2 for the Olli et al (2010) feeding study, model runs

412

B1 and B2 generally overestimate the concentrations of BDE-47, -100, -66 and -154


18

Page 19 of 36


413

measured by Berntssen et al. (2010)24. However, predicted concentrations are again well

414

within a factor of 2 of measured values, except for BDE-99 for model run B1. We again

415

see discrepancies driven by biotransformation. While the concentrations of parent

416

congeners BDE-99 and -153 are underestimated by model run B1, model run B2

417

overestimates their fillet concentrations. This suggests biotransformation of these

418

congeners does occur, but at a rate that is somewhat lower than those based on our in

419

vitro extrapolation method.

420 421

Sensitivity and Uncertainty

422

Based on our sensitivity analysis, model sensitivity for specific BDE congeners can be

423

categorized into two groups. The first group consists of all congeners that are not

424

metabolically active (BDE-209, BDE-100, BDE-47 and BDE-28, see 3.7). The

425

normalized sensitivity coefficients (NSC) calculated for a 10% increase in parameter

426

values for BDE-209, representative for the first group of congeners, are shown in Figure

427

S9 for model run A1. The model output is most sensitive to the congener concentration in

428

feed, the fish weight, the daily feed ration, and the KOW, in decreasing order. The feed

429

concentration is particularly critical, because the estimated concentrations of PBDE in

430

feed for model runs A1 and A2 are among the most uncertain parameters. For KOW, an

431

increase in the parameter leads to a decrease in dietary uptake efficiency and therefore in

432

the final PBDE concentration in the body. The model is relatively insensitive to

433

parameters governing uptake and elimination via the gills.

434 435

The second group is of those congeners influenced by metabolic debromination. The


19


Page 20 of 36

436

sensitivities for BDE-99, which are representative for this group, are shown in SI Figure

437

S10. Here the most important parameters are the concentration in feed, daily feed ration,

438

and fish weight. These three all have NSC with absolute values between 0.8 and 1. The

439

next most important parameters, with NSC > ±0.5, include those associated with

440

metabolism (in vitro microsomal protein content, in vitro assay volume, in vitro

441

degradation rate, microsomal protein content, hepatosomatic index, and fractional water

442

content of blood), and lipid assimilation efficiency, all with similar sensitivity indices.

443

Similarly to the congeners of the first group, the model is relatively insensitive to

444

parameters governing uptake and elimination via the gills. However for this group of

445

congeners, in contrast with the first, the model is also relatively less sensitive to KOW.

446 447

We use three parameters to illustrate how the impacts of uncertainty can be evaluated

448

using our sensitivity analysis. It has been previously shown that high uncertainties are

449

associated with the KOW, solubility, and vapor pressures30,31,41of PBDEs. Our sensitivity

450

analysis shows that the model is insensitive to both solubility and the Henry’s law

451

coefficient (which includes both solubility and vapor pressure contributions). Thus high

452

uncertainty in their values would not change the predictions of the model. For KOW, on

453

the other hand, the model is relatively sensitive (NSCKOW = − 0.73), for the first group of

454

congeners (represented by BDE-209, see figure S9), and less so (NSCKOW = − 0.19) for

455

the second group of congeners (represented by BDE-99, see figure S10). In both cases,

456

increasing the KOW will decrease the predicted whole body concentration due to

457

decreasing dietary uptake efficiency (see Figure S7). Assuming a one order of magnitude

458

difference in KOW, we can use Equation 2 to calculate a decrease in predicted PBDE


20

Page 21 of 36

459


concentration of a factor of 2 at most.

460 461

As our model exhibits certain non-linear characteristics, these normalized sensitivity

462

coefficients should be treated with caution. More elaborate methods, such as Monte

463

Carlo-based global sensitivity and uncertainty analysis, might be needed to fully assess

464

the model sensitivity over a wider range of parameter values.

465 466 467

Discussion

468

The concentrations of PBDEs in salmon fillet are well predicted by our model—typically

469

within a factor of 2—despite substantial uncertainties associated with the input

470

parameters. Nevertheless, differences in model performance with and without

471

debromination can provide some useful insights. For model runs A1 and A2,

472

underestimates for specific PBDE congeners could result from assuming concentrations

473

in the modeled feed that are too low compared to those used in the feed by Olli et al.

474

(2010)23. This is most likely the case for BDE-66, where the modeled final concentration

475

in fillet is more than 45 times lower than the measured values. As Sanden (2014)34, which

476

we used to parameterize feed concentrations for these model runs, did not measure BDE-

477

66, we set the model feed concentration to 0 for this congener. Thus, the only input flux

478

for BDE-66 stemmed from metabolic debromination of BDE-99. Measurements by

479

Isosaari et al. (2005)20 and Berntssen et al. (2010)24 indicate, however, that BDE-66 is

480

also found in fish oil and meal used for the production of fish feed.

481


21


Page 22 of 36

482

A second factor that could cause underestimation of the final PBDE concentrations for

483

some congeners is that extrapolated full-body metabolic rate constants for debromination

484

are too high. This would result in an overestimation of the loss of parent congeners,

485

which could explain the low fillet concentrations of BDE-99 and BDE-153 predicted by

486

model run A1, and is further supported by the overestimation of BDE-49 (the

487

debromination product of BDE-99). The systematic underestimation of the parent

488

congeners BDE-153 and -99 by model run B1, and the fact that the concentration profile

489

for model run B2 is more similar to Berntssen et al. (2010)24, also supports this

490

hypothesis.

491 492

The model we present here supports dietary uptake as the dominant pathway for PBDE

493

into salmon compared to the uptake via gills from local environmental contamination for

494

all congeners. Previous empirical work has highlighted the importance of dietary

495

uptake16–20. Our model shows that this is due to PBDE concentrations in fish feed being

496

significantly higher compared to environmental concentrations in the seawater. As Meng

497

et al. (2008)25 suggested, however, uptake from water could be important for fish farmed

498

in waters with higher contaminant loads.

499 500

In all model runs BDE-47 is calculated to be the dominant congener in the fish fillet, in

501

good agreement with previous studies16,19,20,23,42,43. Isosaari et al. (2005)20 hypothesized

502

the dominance of BDE-47 to be caused by the debromination of higher brominated

503

congeners and the stability of BDE-47 towards further debromination reactions.

504

According to Roberts et al. (2011)28, however, BDE-47 is not part of the debromination


22

Page 23 of 36


505

pathway of either Chinook salmon or rainbow trout (both salmonids). While it is unclear

506

to what extent the debromination pathway for Chinook salmon also holds for Atlantic

507

salmon, our model reproduced the measured fillet concentrations of BDE-47 rather well

508

when only intake via dietary uptake and water were considered. This supports the

509

hypothesis that BDE-47 in salmonids is not part of the debromination pathway, and that

510

high fillet concentrations in Atlantic salmon fillet are likely from feed.

511 512

For BDE-209, the influence of metabolic debromination on the concentration in the fish

513

fillet is difficult to assess. Previous observations of BDE-209 accumulation in Salmo

514

salar have been inconclusive. Some authors hypothesize that low concentrations of BDE-

515

209 found in salmon fillet are due to metabolic debromination to lower brominated

516

congeners16,18,43. These findings stand in contrast to measurements by Olli et al. (2010)23,

517

which indicate that uptake of BDE-209 in Atlantic salmon from feed is possible and that

518

the metabolic potential of the salmon was not sufficient to fully debrominate the BDE-

519

209. In contrast to rainbow trout and common carp, Roberts et al. (2011)28 found no

520

degradation of BDE-209 in liver fractions of Chinook salmon. To conclusively assess the

521

metabolic potential of Atlantic salmon for BDE-209, an exposure trial needs to be

522

conducted. Our model assumes that Atlantic salmon, like Chinook salmon, do not

523

debrominate BDE-209, and demonstrates that concentrations in the range of the measured

524

values by Olli et al. (2010)23 could be reached by exposure via feed and water. A recent

525

study44 found highly variable concentrations of PBDE in fish meal, fish oil and fish feed

526

of various European origins, ranging from total PBDE concentrations below the limit of

527

detection up to 2.2 µg/kg. Additionally, the congener profiles of the examined samples


23


Page 24 of 36

528

varied markedly. While the authors found no BDE-209 in the two samples of fish oil and

529

complete fish feed, 5 out of 10 samples of fish meal contained BDE-209 concentrations

530

varying between 1 and 15 µg/kg lipid. Assuming a fish meal content of 35%23, fish feed

531

would contain between 0.07 and 0.52 µg/kg BDE-209, which is comparable to the

532

concentrations found by Hites et al. (2004)16.

533 534

Our model has the following limitations. First, it is a single-compartment model, which

535

does not account for the distribution of PBDEs to different organs, such as the liver or

536

muscle. For some higher brominated PBDE congeners, preferential distribution to liver

537

tissues has been observed for wild common dab (Limanda limanda), whiting (Merlangius

538

merlangus) and pouting (Trisopterus luscus)45. Furthermore, the preferential

539

accumulation of BDE-209 has been observed in the liver of juvenile rainbow trout

540

(Oncorhynchus mykiss)37 and Chinese sturgeon (Acipenser sinensis)46. The reason for

541

preferential distribution of these congeners to liver is currently unclear. However, it could

542

cause PBDE concentrations of higher brominated PBDE congeners in fillet to be lower

543

than calculated by the model. Modeling the fish body as a single compartment further

544

neglects the effects of differential organ growth and lipid accumulation. Berntssen et al.

545

(2005)21 found muscle fat deposition in Atlantic salmon to rapidly increase compared to

546

the rest of the body when the fish reached a weight of approximately 1 kg. Such

547

differences in relative growth rates of the lipid compartment could significantly influence

548

the uptake and distribution kinetics of PBDE in Atlantic salmon, which is primarily lipid

549

driven. A third limitation of the model is the missing link between temperature, salmon

550

growth and feed intake. It has generally been observed that salmon feed intake in


24

Page 25 of 36


551

aquaculture conditions decreases with temperature47. However, the growth rate of the fish

552

does not necessarily change accordingly48. This can also be observed in the feeding data

553

used as input for the model: during cold water periods, feed intake decreases, while the

554

growth rate remains approximately constant. Furthermore, in warmer months of the

555

production periods, feed intake increased, while growth rates did not increase by the

556

same order of magnitude. By linking temperature, feed intake and growth of farmed

557

Atlantic salmon, the PBDE fillet concentrations could be predicted independent of a

558

specific aquaculture scenario. This could be achieved by implementing a bioenergetic

559

model for aquaculture salmon into the bioaccumulation model.

560 561

If diet is the most important uptake route for PBDEs into salmon, the final concentrations

562

reached in the fillet are strongly influenced by the ratio of growth and feeding rate. This

563

so-called feed-conversion ratio (i.e. the ratio of total amount of weight gained to amount

564

of feed fed) is a parameter closely monitored in aquaculture practices and strongly

565

depends on the salmon strain and animal husbandry. By using strains of salmon with a

566

maximum feed-conversion ratio (which promotes growth dilution) and by optimizing

567

farming practices, the concentration of PBDEs in fillet of farmed salmon can be reduced.

568

The consumption of salmon raised under such optimal production conditions would

569

therefore lead to a lower exposure to PBDEs.

570 571

The limited influences of local sources of pollution on the concentration of PBDEs in

572

farmed salmon has implications for how hazardous chemicals are transported via food

573

trade15. In the case of farmed salmon, it is not necessarily the origin of the farmed fish but


25


Page 26 of 36

574

of the feed or feed ingredients used in its production that must be taken into account to

575

accurately trace the origins of human dietary exposure to PBDEs. Fish oils in particular

576

have been found to contain high concentrations of persistent organic pollutants, promptim

577

decontamination studies such as those by Olli et al. (2010) and Berntssen et al.

578

(2010).23,48 The model we developed in this work seeks to make explicit the competing

579

contributions of feed concentrations, water concentrations, biotransformation, and fish

580

physiology (including also fish growth and feed conversion efficiency). By making these

581

links, the model could be extended and modified to assess the influence of environmental

582

and production-specific conditions of other fish with high global trading volumes, such as

583

Tilapia or red snapper. Particular attention should be given to food species or feeds

584

produced in the contamination "hot-spots" of densely populated areas. The model could

585

similarly be used to evaluate contaminant control strategies such as replacing fish oils

586

with plant-based materials in feed or decontamination of fish oil.

587 588

The model developed here performed well in predicting congener-specific PBDE

589

concentrations in farmed salmon. The major strength of the model is its ability to

590

simultaneously treat multiple congeners in a dynamic way. This includes the tracking of

591

lower brominated congeners that accumulate from direct uptake and the debromination of

592

higher brominated congeners. Moreover, the mechanistic approach of the model allows

593

us to discern the relative contributions of different uptake routes, and notably the

594

influence of feed. This model framework could be readily adapted to other metabolizable

595

compounds and their transformation products.

596


26

Page 27 of 36

597


Table 1. Concentrations of PBDEs in Water and Feed Used as Model Input. Congener

Water

Feed Concentration

Concentration

[µg /kg]

[mol / m3]

A1, A2

B1, B2

BDE-209

4.36×10-13

4.72

0

BDE-203

1.93×10-14

0.026

0

BDE-183

2.21×10-14

0.03

0

BDE-154

0

0.19

0.78

BDE-153

1.31×10-14

0.08

0.24

BDE-100

1.97×10-14

0.35

0.87

BDE-99

2.37×10-13

0.31

0.93

BDE-66

0

0

0.31

BDE-47

3.33×10-13

2.07

4.5

BDE-28

0

0.09

0.18

598 599

FIGURE CAPTIONS

600 601

Figure 1. Concentration of BDE-47, -99, and -209 in the fish whole-body compartment

602

over an entire sea-cage cycle for model run A1.

603 604 605

Figure 2. Daily mass intake and loss of (A) BDE-47, (B) BDE-99, and (C) BDE-209 into

606

farmed Atlantic salmon (whole body) over 500-day sea-cage growth cycle (model run


27


607

Page 28 of 36

A1). Scatter in predicted dietary uptake reflects variability in daily feed intake.

608 609

Figure 3. Comparisons between (A) Olli et al. (2010) data and model runs A1 and A2,

610

with and without biotransformation, respectively, and (B) Berntseen et al. (2010) data

611

and model runs B1 and B2, with and without biotransformation, respectively. Error bars

612

for Olli et al. and Berntssen et al. data indicate reported variability. Error bars in model

613

run A1 indicate predictions using the 25th and 75th percentile of reported feeding rates.

614

Stars indicate that the congener was not measured in that study.

615 616

ACKNOWLEDGMENT

617

We thank Harald Breivik of Neperdo Biomarine, Norway, for kindly providing the

618

feeding rate data used in this study.

619 620

ASSOCIATED CONTENT

621

Supporting Information

622

Details on model parameterization and sensitivity analysis are available in the Supporting

623

Information (SI). This material is available free of charge via the Internet at

624

http://pubs.acs.org/.

625 626

AUTHOR INFORMATION

627

Corresponding Authors

628

Carla A. Ng, +1 412 383 4075, [email protected]

629

Natalie von Goetz, +41 44 632 0975, [email protected]


28

Page 29 of 36


630 631

Notes

632

The authors declare no competing financial interest.

633 634

References Cited

635 636 637 638 639 640 641 642 643 644 645 646 647 648 649 650 651 652 653 654 655 656 657 658 659 660 661 662 663 664 665 666 667 668 669 670

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Page 33 of 36 4

Concentration [pg/g fish]

10


103

102

101

100 0

BDE- 209 BDE-99 BDE-47 100

200Plus Environment 300 ACS Paragon Time [day]

400

500

70


A: BDE-47

60

Page 34 of 36

ng/day

50 40 30 20 10 0

0

10

100

150

200

250

300

350

400

450

500

200

250

300

350

400

450

500

200

250

300

350

400

450

500

B: BDE-99

8

ng/day

50

dietary uptake waterborne uptake loss via egestion loss via gills biotrasformation (loss) bioformation (input)

6 4 2 0

0

4

50

100

150

100

150

C: BDE-209

ng/day

3

2

1

0

0

50


Day

1.5

2.0

1.0 0.5 0.4

1.0 0.5 0.4

0.3

0.3

0.2

0.2

0.0

*

*

* * *

0.1

Model no metabolism

* *

0.0


Congener

Model with metabolism

*

28

0.1

Berntssen et al. (2010)

3.0

* * *

99 10 0 10 1 14 9 15 3 15 4 18 3 18 7 20 3 20 9 To ta l

Model with metabolism Model no metabolism

66

Olli et al. (2010)

49

2.0

A

47

2.5

Environmental Science & Technology 4.0 B

28 49 47 (+ 71 ) 66 99 10 0 10 9 11 9 14 9 15 3 15 4 18 3 18 7 20 3 20 9 To ta l

Concentration [ng/g fillet]

Page 35 of 36 3.0

Congener

PBDEs: globally-sourced feed Environmental Science & Technology Page 36 of 36 or local environment? Br

Br

Br Br

Br Br

Br

O Br

Br

deca-BDE

Br


Role of debromination?

1 Polybrominated diphenyl ether (PBDE) - ACS Publications

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