Accumulation of PBDEs and MeO-PBDEs in notothenioid fish from the
South Shetland Islands, Antarctica: An interspecies comparative study
Juan Manuel Ríos a,i
, Sabrina B. Mammana a,b,h
, Eugenia Moreira c,d
, Giulia Poma e
Govindan Malarvannan e
, Esteban Barrera-Oro c,f
, Adrian Covaci e
, Nestor F. Ciocco b,g
, Jorgelina
C. Altamirano a,b,*
a Laboratorio de Química Ambiental, Instituto Argentino de Nivología, Glaciología y Ciencias Ambientales (IANIGLA, CCT-CONICET), Mendoza 5500, Argentina b Facultad de Ciencias Exactas y Naturales, Universidad Nacional de Cuyo, Mendoza, Argentina c Instituto Antartico ´ Argentino (IAA), Buenos Aires, Argentina d Laboratorio de Biología Funcional y Biotecnología (BIOLAB), INBIOTEC-CONICET, Facultad de Agronomía, UNCPBA, Azul 7300, Buenos Aires, Argentina e Toxicological Centre, Department of Pharmaceutical Sciences, University of Antwerp, Universiteitsplein 1, 2610 Wilrijk, Belgium f Museo Argentino de Ciencias Naturales Bernardino Rivadavia and CONICET, Buenos Aires, Argentina g Instituto Argentino de Investigaciones de las Zonas Aridas ´ (IADIZA, CCT-CONICET), Mendoza 5500, Argentina h Instituto de Biología Agrícola de Mendoza (IBAM, CCT-CONICET), Mendoza 5505, Argentina i Instituto de Medicina y Biología Experimental de Cuyo (IMBECU, CCT-CONICET), Mendoza 5505, Argentina
ARTICLE INFO
Keywords:
Antarctic fish
MeO-PBDEs
PBDEs
Notothenioidei
Species-specific accumulation
ABSTRACT
Concentrations of polybrominated diphenyl ethers (PBDEs) and methoxylated polybrominated diphenyl ethers
(MeO-PBDEs); are reported in specimens of fish notothenioids Chaenocephalus aceratus (SSI), Trematomus ber￾nacchii (ERN), and Nototheniops nudifrons (NOD) from the South Shetland Islands, Antarctica. Significant dif￾ferences in the accumulation of 2′
-MeO-BDE-68 and 6-MeO-BDE-47 were detected among the analysed species.
MeO-BDEs were significantly higher in SSI (11.7, 8.6, and 14.1 ng g− 1 lw) than in NOD (1.63, 1.63, and 3.0 ng
g− 1 lw) in muscle, liver, and gill, respectively. Feeding ecology traits explain the accumulation patterns of MeO￾PBDEs. SSI has a higher feeding activity with a broader diet, followed by ERN, whereas NOD is a benthic/
sedentary fish with a narrower diet. The accumulation of PBDEs was neither species-, nor tissue-specific. The
current study expands the knowledge concerning the accumulation of PBDEs and MeO-PBDEs in Antarctic
marine fish and supports the importance of species-specificity in the accumulation of MeO-PBDEs.
1. Introduction
Brominated flame retardants (BFRs), such as polybrominated
diphenyl ethers (PBDEs); have been widely used in commercial and
household products to prevent the spreading of fire (Choo et al., 2019).
Once released into the environment, PBDEs represent a risk for wildlife
and human health due to their persistence, bioaccumulation potential,
and toxic effects on reproductive, endocrine, and nervous systems (De
Wit et al., 2010). PBDEs can be spread away from emission sources
through long-range atmospheric and/or water transport as a gas phase,
dissolved, and/or associated with particulate matter (Gouin et al.,
2006). Cold-condensation and cold-trapping are the main mechanisms
whereby organic chemicals reach polar regions (Wania and Westgate,
2008; Ko et al., 2018). Due to their physicochemical properties, PBDEs
can accumulate in the biota and biomagnify through the food web in
polar regions (De Wit et al., 2010; Ríos et al., 2017).
Experimental research on PBDE metabolism suggests that methoxy￾lated polybrominated diphenyl ethers (MeO-PBDEs) are formed by
microsomal methylation of the hydroxylated polybrominated diphenyl
ethers (OH-PBDEs) in hepatocytes (Liu et al., 2012; Kim et al., 2015). On
the other hand, reports suggest that MeO-PBDEs are also naturally
produced by marine biota (Wan et al., 2009). The predominant MeO￾PBDEs in the environment and marine-biota are the tetrabrominated
6-MeO-BDE-47 and 2′
-MeO-BDE-68 (Sinkkonen et al., 2004; Vetter
et al., 2007; Covaci et al., 2008; Ríos et al., 2017). Their toxicity is still
under investigation, although adverse effects on biota cannot be ruled
* Corresponding author at: Laboratorio de Química Ambiental, Instituto Argentino de Nivología, Glaciología y Ciencias Ambientales (IANIGLA, CCT-CONICET),
Mendoza 5500, Argentina.
E-mail address: [email protected] (J.C. Altamirano).
Contents lists available at ScienceDirect
Marine Pollution Bulletin
journal homepage: www.elsevier.com/locate/marpolbul

https://doi.org/10.1016/j.marpolbul.2021.112453

Received 11 February 2021; Received in revised form 28 April 2021; Accepted 1 May 2021
Marine Pollution Bulletin 168 (2021) 112453
out since their chemical structure only differs from the PBDEs on by one
methoxy substituent (Dirtu et al., 2013). Consequently, studies on the
transport, bioaccumulation, and biomagnification of MeO-PBDEs are of
interest for environmental and toxicological sciences.
The perciform suborder Notothenioidei is the dominant group of the
Antarctic ichthyofauna (i.e., 129 species) in terms of diversity (35%),
abundance, and biomass, comprising 97% of endemic species (Near
et al., 2015). Notothenioid fish are mostly demersal and have developed
a variety of feeding behaviours, including a wide range of prey and di￾versity of benthic, epibenthic, nektonic, and planktonic organisms
(Daniels, 1982; Barrera-Oro, 2002; Ko et al., 2018). The Antarctic
notothenioids, blackfin icefish Chaenocephalus aceratus [(Lonnberg ¨
1906), acronym: SSI], emerald rockcod Trematomus bernacchii [(Bou￾lenger 1902), acronym: ERN], and yellowfin notie Nototheniops nudifrons
[(Lonnberg ¨ 1905), acronym: NOD] are demersal and typical represen￾tatives of the western Antarctic Peninsula ichthyofauna (Kock, 1992).
They have similar habits in the fjords, living commonly in shallow
inshore waters from 20 to 25 m deep on rocky bottoms with macroalgae
beds to offshore shelf waters down to depths of 450 m (DeWitt, 1971;
Eastman, 2017), yet they differ in diet and feeding activity (Barrera-Oro,
2002; Casaux et al., 2003; Casaux and Barrera-Oro, 2013). The wide
Antarctic distribution, relative abundance, and feeding habits of these
species make them suitable sentinels of pollution in the Antarctic marine
environment.
Considering the feeding ecology of the fish species studied in this
work, we hypothesize that PBDEs and MeO-PBDEs have a species￾specific pattern of accumulation. We aimed to determine and compare
the occurrence and profiles of these contaminants in different tissues
(muscle, liver, and gill) of specimens from the three aforementioned
species.
2. Materials and methods
2.1. Fish sampling and storage
Fish samples (n = 17) were collected at Potter Cove, King George
Island/Isla 25 de Mayo, South Shetland Islands, close to the Scientific
Station Carlini (62◦14′ S; 58◦40′ W) in the austral summer from
November 2014 to January 2015. The low number of collected in￾dividuals was mainly affected by the rigid environmental conditions of
Antarctic sea and the severe restrictions in the permits regarding the
number of fish specimens that can be collected from the Antarctic
continent. Specimens of Chaenocephalus aceratus (n = 6), Trematomus
bernacchii (n = 5), and Nototheniops nudifrons (n = 6) were collected with
trammel nets (length 25 and 35 m; width 1.5 m; inner mesh 2.5 cm;
outer mesh 12 cm) set for 6–96 h at 5–50 m depths in sites where the
seabed is a uniform rocky bottom covered mainly with red and brown
macroalgae. The abiotic and biotic characteristics of Potter Cove are
detailed in Barrera-Oro et al. (2019). The fish samples were wrapped
and kept in single aluminum foils and transported to the laboratory
where they were measured (total length in cm), weighed (g), and
dissected before freezing at − 20 ◦C until further analysis.
2.2. Reagents
The following compounds were included in the analysis: 7 PBDE
congeners (BDE-28, -47, -99, -100, -153, -154, and -183), and 2 MeO￾PBDEs (6-MeO-BDE-47 and 2′
-MeO-BDE-68). PBDE and MeO-PBDE
commercial standards were purchased from Wellington Laboratories
(Guelph, Ontario, Canada). BDE-77 and CB-207 at 25 and 50 pg μL− 1 in
isooctane were used as internal standard (IS) and recovery standard
(RS), respectively. Acetone, n-hexane, dichloromethane (DCM), isooc￾tane (all pesticide grade), and sulfuric acid (analytical grade) were
purchased from Merck (Darmstadt, Germany). Silica gel 60 (63–230
mesh) and anhydrous sodium sulfate (Na2SO4, Merck) were of analytical
grade, pre-washed with n-hexane aliquots and dried at 140 ◦C for 24 h
before use. Solid-phase cartridges were prepared using acidified silica
(H2SO4, 44% w/w) before use.
2.3. Sample preparation
Dissected tissues (muscle, liver, and gills) were weighed, lyophilized
and stored at − 18 ◦C until analysis. The analytical methodology used for
determining PBDEs and MeO-PBDEs in the analysed tissues was reported
previously (Malarvannan et al., 2014). Briefly, dry-tissue aliquots (liver
ca. 0.8 g, muscle and gills, ca. 1 g each) were homogenized in an agate
mortar, transferred to a 15 mL polypropylene tube, mixed with Na2SO4,
and spiked with 50 μL of IS solution. A 3 mL aliquot of n-hexane: acetone
(3:1, v/v) was added to the tube containing the sample, vortexed for 1
min, sonicated for 10 min, and centrifuged at 3500 rpm for 3 min. The
process was repeated once more with fresh solvent. An aliquot of the
supernatant (ca. 1/8) was taken and used for the gravimetrical deter￾mination of the lipid content (Malarvannan et al., 2014). The remaining
supernatant was transferred to an empty glass tube and evaporated to
near 100 μL by a gentle nitrogen stream at 32 ◦C. The concentrated
extract was cleaned-up on ~6 g acidified silica (H2SO4 44%, w/w)
column pre-washed with 15 mL of n-hexane. The analytes were eluted
with 20 mL n-hexane and 15 mL DCM from the column. The eluent was
rotary evaporated to ca.1 mL, further evaporated to ca. 50 μL in a glass
tube under a gentle nitrogen stream at 32 ◦C, and finally reconstituted
with 50 μL of isooctane and 50 μL of RS.
2.4. Analysis of PBDEs and MeO-PBDEs
Determination of PBDEs and MeO-PBDEs was carried out on an
Agilent 6890 (Palo Alto, CA, USA) gas chromatograph (GC) equipped
with mass spectrometry (Agilent 5973 MS) operated in electron capture
negative ionization (ECNI) source. A DB-5 capillary GC column (30 m ×
0.25 mm × 0.25 μm; J&W Scientific, Folsom, USA) was used. The GC
system was equipped with electronic pressure control and a program￾mable temperature vaporizer (PTV) inlet. The injection temperature was
set at 92 ◦C, held 0.03 min, ramped at 700 ◦C/min to 300 ◦C, held 30
min. The injection (1 μL) was performed under a pressure of 10.06 psi
until 1.25 min and purge flow to split vent of 50 mL/min after 1.25 min.
The GC temperature ramp started from 92 ◦C, held 1.25 min, ramped at
10 ◦C/min to 300 ◦C, held 1 min, ramped at 40 ◦C/min to 310 ◦C, held
9.5 min. Helium was used as carrier gas with a flow rate of 1.0 mL/min
until 25 min, then increased to 1.5 mL/min. The ion source and quad￾rupole temperatures were set at 170 ◦C and 150 ◦C, respectively. The
mass spectrometer was operated in selected ion monitoring (SIM) for the
quantification of BDE-28, -47, -99, -100, -153, -154, and -183 and 6-
MeO-BDE-47, and 2′
-MeO-BDE-6 with ions m/z 79 and 81 monitored
for each compound.
2.5. Quality assurance and quality control
Multi-level calibration curves in the linear response interval of the
detector were created for the quantification, and good correlation (r >
0.999) was achieved. The identification of analytes was based on the
relative retention times to the IS used for quantification, ion chro￾matograms, and intensity ratios of the monitored ions (Malarvannan
et al., 2014). The peaks were identified as target analytes if their
retention time matched that of the corresponding reference standard
within ±0.1 min and their signal/noise ratio (S/N) was >3:1. Procedural
blanks were included in every batch to control interferences and/or
contamination from solvents and/or glassware. The procedural blanks
(n = 7) were stable (relative standard deviation: RSD < 17%, Table S1),
and therefore, if there was a positive detection of the analytes in the
procedural blanks, those levels were afterwards subtracted from the
ones measured in the samples. The limit of quantification (LOQ) of the
methodology was calculated as 3*SD of the mean of the procedural
blank. The LOQ for the 7 PBDEs and the 2 MeO-PBDE was 1.5 ng g− 1
J.M. Ríos et al.
Marine Pollution Bulletin 168 (2021) 112453
lipid weight (lw) [30 pg g− 1 wet weight (ww)]. The analysis was further
validated by determining the targeted analytes in the certified material
SRM 1945 (organic contaminants in whale blubber). The concentrations
of target PBDEs and MeO-PBDEs in the analysed SRM 1945 were satis￾factory, showing a deviation lower than 10% of the certified values
(Table S1). The mean ± SD recovery of the internal standard BDE-77 was
101 ± 17%.
2.6. Data analysis
For calculating sums, median, and means, a value of f * LOQ was
assigned to concentrations of compounds ˂ LOQ, where ‘f’ is the detec￾tion frequency (James et al., 2002). Contaminant concentrations data
were log-transformed (Zar, 2013) to fit normal distribution (Shapiro￾Wilks W test P < 0.05). A generalized linear model (GLM) with a full
factorial design was performed to detect differences in the contaminant
concentrations among the analysed fish species and tissues. In partic￾ular, full-factorial designs represent all possible combinations of the
levels of the categorical predictors (e.g., in the present study the cate￾gorical predictors, are “species” and “tissues”). Therefore, the full￾factorial design provides more information about the relationships be￾tween categorical predictor variables and responses on the dependent
variables than is provided by corresponding one-way or main effect
designs (Rutherford, 2011). Fisher’s LSD (Least Significant Difference) a
posteriori tests were used to make multiple comparisons. To verify our
hypothesis, a significant effect in the categorical predictor factor “spe￾cies” is expected from this GLM approach. The non-parametric Spear￾man’s Rho correlations were used to explore for possible intraspecific
associations between fish morphometry (total weight and length) and
contaminants body burden. Since the lipid content in tissues is usually
associated with accumulation of PBDEs in fish (Ondarza et al., 2011;
Gewurtz et al., 2011a, 2011b; Ríos et al., 2019), intraspecific correla￾tions between lipid content and PBDE and MeO-PBDE levels (on a wet
weight basis) were used to explore for possible (positive) associations
using Spearman’s Rho correlations. Statistical analyses were carried out
using the InfoStat 2011 software (Di Rienzo et al., 2008). A p value
<0.05 was considered significant, except for Spearman’s correlations
adjusted by Bonferroni correction (Zar, 2013), and the α error was
divided by the number of comparisons (i.e., three fish species). Thus,
correlations were considered significant for p < 0.016.
3. Results and discussion
3.1. Concentrations of PBDEs and MeO-PBDEs in fish specimens
Mean and median values along with standard errors of all com￾pounds measured in muscle, liver, and gill tissues of the three fish spe￾cies here considered are presented in Table 1. The measured median
BDE-47 concentrations found in muscle tissue of SSI, ERN and NOD were
2.93, 2.22, and 8.32 ng g− 1 lw, respectively, while in liver tissue were
<LOQ, 1.36, and <LOQ, respectively (Table 1). The measured median
BDE-47 concentrations found in gill tissue of SSI, ERN, and NOD, were
2.57, 2.28, 6.06 ng g− 1 lw, respectively. BDE-100 was only detected in
muscle tissue of ERN (2.25 ng g− 1 lw). For the remaining species and
tissues here analysed, BDE-100 concentrations were <LOQ. The
measured median BDE-99 concentrations found in muscle tissue of SSI,
ERN and NOD, were 3.77, 8.26, and 3.10 ng g− 1 lw, respectively. BDE-
99 was only detected in gill tissue of ERN (4.98 ng g− 1 lw). For the
remaining species and tissues analysed, BDE-99 concentrations were
<LOQ. BDE-154 was only found in gill tissue of SSI (2.07 ng g− 1 lw), and
BDE-183 was only found in muscle tissue of NOD (5.84 ng g− 1 lw). BDE
3.17 (1.00) 1.97 12.6 (14.0) 1.31 5.67 (5.50) 0.33 1.22 (1.00) 0.48 15.6 (20.0) 4.20 4.26 (3.30) 0.78 1.38 (1.00) 0.39 13.0 (13.0) 1.00 3.50 (3.50) 0.50
BDE-28 <LOQ a <LOQ a <LOQ a <LOQ a <LOQ a <LOQ <LOQ a <LOQ a <LOQ a
BDE-47 3.23 (2.93) 0.71 <LOQ a 3.35 (2.57) 0.98 5.75 (2.22) 2.90 1.36 (1.36) 0.16 2.28 (2.28) 0.34 8.96 (8.32) 3.29 <LOQ a 6.06 (6.06) 3.99
BDE-100 <LOQ a <LOQ a <LOQ a 2.25 (2.25) a <LOQ a <LOQ a <LOQ a <LOQ a <LOQ a
BDE-99 3.60 (3.77) 0.72 <LOQ a <LOQ a 6.23 (8.26) 2.12 <LOQ a 4.98 (4.98) 3.06 2.92 (3.10) 0.80 <LOQ a <LOQ a
BDE-154 <LOQ a <LOQ a 2.07 (2.07) a <LOQ a <LOQ a <LOQ a <LOQ a <LOQ a <LOQ a
BDE-153 <LOQ a <LOQ a <LOQ a <LOQ a <LOQ a <LOQ a <LOQ a <LOQ a <LOQ a
BDE-183 <LOQ a <LOQ a <LOQ a <LOQ a <LOQ a <LOQ a 5.84 (5.84) a <LOQ a <LOQ a
PBDEs 6.83 (6.70) 5.42 (4.64) 14.2 (12.7) 1.36 (1.36) 7.26 (7.26) 17.7 (17.2) 6.06 (6.06)
2-MeO￾BDE68 0.74 (0.40) 0.34 1.33 (1.41) 0.35 1.84 (1.93) 0.52 0.40 (0.40) a 1.07 (0.40) 0.41 0.40 (0.40) 0.00 0.40 (0.40) 0.00 0.40 (0.40) 0.00 0.40 (0.40) 0.00
6-MeO￾BDE47 11.0 (10.9) 2.35 7.28 (7.29) 0.75 12.3 (12.5) 1.52 9.09 (9.36) 1.20 6.96 (6.08) 1.09 7.42 (6.19) 1.28 1.23 (1.23) 0.00 1.23 (1.23) 0.00 2.62 (2.62) 0.70
MeO-BDE 11.7 (11.3) 8.61 (8.70) 14.1 (14.4) 9.49 (9.77) 8.03 (6.48) 7.82 (6.59) 1.63 (1.63) 1.63 (1.63) 3.02 (3.02)
Total (in bold)
= sum of PBDEs (#28, 47, 100, 99, 154, 153, 183); sum of MeO-BDE (2-MeO-BDE-68, and 6-MeO-BDE-47). <LOQ: below the limit of quantification. a: no standard error could be calculated since only one
value was available or values are <LOQ. a Due to limitations in the sample size, liver and gill tissues of NOD were pooled in two groups of three specimens each (n = 2) to perform their analysis.
J.M. Ríos et al.
Marine Pollution Bulletin 168 (2021) 112453
4
major congener in the total load. The contribution of 7 PBDEs and 2
MeO-PBDEs assessed in the target tissues of each analysed species is
shown in Figs. S1 and S2 of the Supplementary section, respectively. A
plausible explanation regarding the predominant accumulation of
PBDEs in gill and muscle tissues, and to a lesser extent in liver, could be
due to differences in the specific metabolism for each congener. For
example, the accumulation pattern of PBDEs found in gill could be
linked to the morpho-physiological functions of this organ. Gills have a
wide diffusion surface for gaseous exchange, osmotic and ionic regula￾tion, acid-base balance, and nitrogenous waste excretion (Ahmad et al.,
2008). Therefore, gills are in continuous contact with the external me￾dium and thus are an uptake route of pollutants from the water column
as well as seabed (Playle, 1998). On the other hand, the liver is the organ
where xenobiotics are metabolized by detoxifying enzymes, resulting in
a lower PBDE concentration comparing it against gills and muscles
(Borghesi et al., 2008).
In the present study, the sum of BDE-47 and BDE-99 contributed to
ca. 83% of the total PBDE load. The levels of BDE-47, -100, and -99
found in muscle, liver, and gill tissues of the three species were similar to
those previously reported for other three notothenioid fish species
(Notothenia coriiceps, Notothenia rossii, and Trematomus newnesi) from the
same sampling site (Lana et al., 2014). This pattern is comparable to
commercial mixtures (e.g. 70-5DE Bromkal), in which BDE-47 and -99
are ca. 70% of the formulation (Ikonomou et al., 2002). Additionally, the
relative abundance of BDE-47 was consistent with previous reports of
fish from other regions of the world (Voorspoels et al., 2003; Vives et al.,
2004; Corsolini et al., 2008). The high levels found may be either due to
an elevated uptake rate or a debromination of BDE-99 (Stapleton et al.,
2004). The results suggest that PBDE burden in this Antarctic area could
have reached a steady state (Lana et al., 2014). However, it cannot be
ruled out that there are still reservoirs of PBDEs (soils and snow/ices) in
this Polar region which could be remobilized due to climate change￾driven warmer conditions (Cabrerizo et al., 2013).
Regarding the analysed MeO-PBDEs (2′
-MeO-BDE-68, 6-MeO-BDE-
47), both were consistently detected at variable concentrations in all
tissue samples of the studied species (Table 1). The measured median 2′
MeO-BDE-68 concentrations found in muscle tissue of SSI, ERN, and
NOD were the same (0.40 ng g− 1 lw); while in liver tissue they were
1.41, 0.40, and 0.40 ng g− 1 lw, respectively. Regarding the gill tissue,
median levels of 2′
-MeO-BDE-68 found for SSI, ERN, and NOD were
1.93, 0.40, and 0.40 ng g− 1 lw, respectively (Table 1). The measured
median 6-MeO-BDE-47 concentrations found in muscle tissue of SSI,
ERN, and NOD were 10.9, 9.36, and 1.23 ng g− 1 lw, respectively, while
in liver tissue they were 7.29, 6.08, and 1.23 ng g− 1 lw, respectively.
Finally, the measured median 6-MeO-BDE-47 concentrations found in
gill tissue of SSI, ERN and NOD were 12.5, 6.19, and 2.62 ng g− 1 lw,
respectively. Likewise, as stated above for PBDEs, MeO-PBDE tissue
concentrations found in the three species were similar to those previ￾ously reported for other two notothenioid fish species (N. rossii and
T. newnesi) from the same sampling site (Ríos et al., 2017). The contri￾bution of each MeO-PBDE congener to the total contamination load
(when considering all tissues and species combined) was 90% and 10%
for 6-MeO-BDE-47 and 2′
-MeO-BDE-68, respectively. A similar profile
with a predominance of 6-MeO-BDE-47 was also reported in the Ant￾arctic notothenioid species N. rossii and T. newnesi (Ríos et al., 2017). In
other marine fish species, with a different position in the food web,
including hollowsnout grenadier Trachyrinchus trachyrinchus, rough￾snout grenadier Coelorhynchus coelorhynchus, Atlantic salmon Salmo
salar, and arctic cod Cadus callarias, the predominance of 6-MeO-BDE-47
was also reported (Sinkkonen et al., 2004; Vetter et al., 2007; Covaci
et al., 2008).
3.2. Testing for interspecific differences in contaminants burden in fish
The GLM approach showed significant statistical differences in the
accumulation of 2′
-MeO-BDE-68 and 6-MeO-BDE-47 among the
analysed fish species (Table 2). Besides, the GLM approach showed that
there were no significant statistical differences among the tissues ana￾lysed within each species (Table 2). The highest levels of 2′
-MeO-BDE-68
and 6-MeO-BDE-47 were found for SSI followed by ERN, while the
lowest levels were found for NOD specimens (Table 1). Multiple inter￾specific comparisons (A posteriori Fisher’s LSD tests) revealed that the
burden of 2′
-MeO-BDE-68 and 6-MeO-BDE-47 in tissues of SSI were
statistically different from those found in NOD specimens. No significant
differences were detected (A posteriori Fisher’s LSD tests) between SSI
and ERN, neither between ERN and NOD specimens when comparing 2′
MeO-BDE-68, nor 6-MeO-BDE-47 tissue levels. On the other hand, there
were no significant differences for the levels of BDE-47 among species in
all tissues (Table 2). The statistical GLM full-factorial approach used to
test the hypothesis requires homogeneous data set regarding the cate￾gorical predictors (factors: species and tissues) among the cases
considered. Therefore, the concentrations of BDE-28, -100, -99, -154,
-153, and -183 were omitted from this statistical analysis because they
could not be quantified in all the tissues of the three species considered
(Table 1).
The source of MeO-PBDEs in fish occurs mainly through two path￾ways: direct uptake of these contaminants through diet (i.e., from the
prey they eat) and the uptake of PBDEs followed by biotransformation to
HO-PBDEs; and then reversible biotransformation of HO-PBDEs to MeO￾PBDEs (Weijs et al., 2015; Liu et al., 2012). The observed differences
between the SSI and NOD for the concentration of the major MeO￾PBDEs, 6-MeO-BDE-47 (Fig. 1) could be attributed to the species￾specific feeding ecology, as suggested in previous reports on other
notothenioid species (Ríos et al., 2017), and marine fish from South
Korean (Choo et al., 2019). This scenario is discussed below.
A compilation of literature information on the trophic ecology of the
studied species at the western Antarctic Peninsula area, including
feeding type categories, feeding strategies/behaviour and diet compo￾sition, is shown in Table 3. It is known that in the Antarctic marine
ecosystem fish and krill are preys of higher energetic value compared to
other invertebrates (Table S3). Among the notothenioids considered, SSI
is the largest species and feeds in the water column on large prey like fish
and cephalopods, and also on krill and mysids. In contrast, NOD is a
smaller and benthic species that inhabit on the bottom-feeding on small
invertebrates that are in a lower food web level. Regarding ERN, it is an
epibenthic species with size and diet breadth intermediate between the
other two species (Table 3). In summary, SSI exhibits higher feeding
activity with a diet constituted by invertebrates and vertebrates –fish,
followed by ERN, whereas NOD is the least active feeder –a more
sedentary fish species– with a narrower diet that only includes in￾vertebrates (Table 3). Consequently, a higher predation activity on or￾ganisms with a higher position in the food web would plausibly involve a
Table 2
Output of the GLM used to detect differences among species in the accumulation
of BDE-47, 2-MeO-BDE-68, 6-MeO-BDE-47 in fish tissue.
Variable F df p-Value
BDE-47 (ng g− 1 lw)
Species 1.138 2 0.336
TissueA 1.759 1 0.197
Interaction 1.070 2 0.358
2-MeO-BDE68 (ng g− 1 lw)
Species 6.033 2 0.005*
Tissue 1.702 2 0.197
Interaction 1.287 4 0.294
6-MeO-BDE47 (ng g− 1 lw)
Species 41.146 2 <0.001*
Tissue 2.304 2 0.115
Interaction 1.124 4 0.361
Significant effects are denoted with an asterisk*. ASince BDE-47 in liver tissue
was only detected and quantified for ERN specimens, only muscle and gill tissue
of the three fish species were included as categorical factors in GLM.
F: Fisher statistic; df: degrees of freedom.
J.M. Ríos et al.
Marine Pollution Bulletin 168 (2021) 112453
5
higher intake of pollutants through diet. Recently, Choo et al. (2019)
found species-specific differences in the accumulation of BFR and PBDE
metabolites, in marine organisms from South Korea. Interestingly,
higher concentrations of MeO-PBDEs in fish with higher trophic position
than in benthic fish were detected, suggesting biomagnification of these
chemicals through the food web. This assumption is reasonable since, for
example, the estimation of lipophilic character identified by the octanol￾water partition coefficient (log Kow) for 6-MeO-BDE-47 is 5.9 (Yu et al.,
2008). Accordingly, MeO-PBDEs are lipophilic enough to be excreted
through the fish kidney function, and therefore these compounds have a
high bioaccumulation and biomagnification potential (Weijs et al.,
2015).
Another plausible scenario could be due to species-specific
biotransformation capacity linked to food habits (e.g., differences in
the activity of the xenobiotic-metabolizing enzyme between SSI and
NOD). It has been demonstrated that a broad diet exposed fish to the
intake of a high diversity of xenobiotics, such as PBDEs and their ana￾logues MeO-PBDEs (Choo et al., 2019). In this sense, the computed
interspecific differences in the 2′
-MeO-BDE-68 and 6-MeO-BDE-47 level
profiles could plausibly be explained by the feeding ecology of the fish
species here considered. Few studies directly testing whether differences
in diet breadth lead to differences in xenobiotics detoxification have
been conducted in fish. For example, Sol´e et al. (2009) and Ribalta et al.
(2015) reported species-specific differences in the xenobiotic￾metabolizing enzymes linked with fish diet type. They suggest that
Mediterranean fish species with an omnivorous diet had a higher intake
of pollutants through diet (Sol´e et al., 2009; Ribalta et al., 2015).
Specifically, marked differences were found between the fish with a
broader (Trachyrhynchus scabrus) and narrower (Alepocehalus rostratus)
diet (Ribalta et al., 2015).
3.3. Exploring associations among fish body size, lipid content and
contaminant accumulation capability
It has been previously reported that PBDE congeners (e.g., BDE-28,
-47, -100, and -99), as well as 6-MeO-BDE-47, were linked to the body
size (total weight and length) of the notothenioid fish Notothenia rossii
and Trematomus newnesi (Ríos et al., 2017). The lipid content of tissues
could also be associated with the accumulation of PBDEs, as showed in
several studies focusing on other fish species (Kuo et al., 2010; Gewurtz
et al., 2011a; Ríos et al., 2019). Therefore, intraspecific correlations
were performed to explore possible associations between fish biological
characteristics (including body size and lipid content) and the PBDE and
MeO-PBDE burden in the considered fish specimens. Since there were no
significant differences between muscle, liver, and gill tissue for each
analysed fish species (Table 2), all intraspecific correlations were per￾formed considering the levels of BDE-47, BDE-99, 2′
-MeO-BDE-68, and
6-MeO-BDE-47 for all tissues combined. Spearman correlation co￾efficients (rho) indicated that there were no significant associations
between the concentration levels of the targeted compounds and fish
biological characteristics (i.e., total weight, length, and lipid content)
for any of the analysed specimens (Table S2). It is worthwhile to mention
that findings related to correlations between PBDE levels and fish size or
lipid content are controversial; while several studies found positive re￾lationships between these factors (Kuo et al., 2010; Gewurtz et al.,
2011a; Ríos et al., 2019), other authors reported no clear correlation
(reviewed in Ríos et al., 2015), highlighting species-specificity when
using this approach.
The increased concentration of PBDEs with the size of the specimen
could be due to differences in food habits, pollutants uptake, as well as to
pollutant exposure over time (Gewurtz et al., 2011a, 2011b). Fish tend
to consume only what they can swallow, so larger fish will usually eat
larger prey and thus may feed at a higher trophic level than smaller fish
(Daniels, 1982; Kock, 1992). However, the correlational approach per￾formed in the present study could not detect any association that sup￾ports this statement. Lipid content in tissues is another factor associated
with the accumulation of PBDE concentrations in fish (Gewurtz et al.,
2011a. b; Ríos et al., 2019). PBDEs concentration reported in lipid-rich
tissues were generally higher than those reported in other tissues owing
to the lipophilic character of these compounds [log Kow > 5.5, (Goutte
et al., 2013)]. However, the lipid content in tissues is dynamic and
therefore could differ among seasons and habitats in terms of food
availability and environmental characteristics (Gewurtz et al., 2011a).
In this sense, another scenario, such as the fish feeding ecology, could
help to explain the lack of correlations in the present study. Studies that
directly test whether differences in trophic position of Antarctic fish lead
to differences in xenobiotics biotransformation are needed to extend the
above generalizations.
Fig. 1. Accumulation of 6-MeO-BDE-47 (ng g− 1 lw) in muscle, liver and gill
tissues of the notothenioid fish species collected at Potter Cove, South Shetland
Islands: Chaenocephalus aceratus (SSI), Trematomus bernacchii (ERN), and
Nototheniops nudifrons (NOD). Different capital letters indicate significant dif￾ferences in the 6-MeO-BDE-47 concentration levels among the fish species (full
factorial GLM, followed by Fisher’s LSD a posteriori multiple comparisons, p
< 0.05).
Table 3
Morphometric data of Chaenocephalus aceratus (SSI), Trematomus bernacchii (ERN), and Nototheniops nudifrons (NOD) collected at Potter Cove, South Shetland Islands,
linked with feeding habits information of these notothenioid species at the western Antarctic Peninsula.
Species Total weight
(g)
Total length
(cm)
n Feeding categoriesa Diet itemsa Feeding behavioura
SSI 2206 ± 95.5
(1852–2426)
62.4 ± 0.80
(59.4–63.9)
6 Nekton and plankton
feeder
Fish, krill, cephalopods, mysids Water column
ERN 138 ± 30.1
(64.6–248)
21.6 ± 1.60
(16.9–26.8)
5 Benthos and plankton
feeder
Algae, polychaetes, gastropods, gammarideans,
isopods, krill, hyperiids
Water column, ambush and grazing
near bottom
NOD 47.9 ± 3.64
(38.0–64.1)
16.1 ± 0.31
(15.2–17.4)
6 Benthos feeder Polychaetes, gammarideans, isopods, krill (occasional
in summer)
Ambush on bottom
Morphometric values for fish size is mean ± standard error, and range (in brackets). a Feeding categories, diet items, and feeding behaviour information was taken from the compilation in Barrera-Oro (2002, Tables 2 and 3) and from Casaux et al.
(2003).
J.M. Ríos et al.
Marine Pollution Bulletin 168 (2021) 112453
4. Conclusions
Results showed marked interspecific differences in 2′
-MeO-BDE-68
and 6-MeO-BDE-47 accumulation levels among the analysed fish spe￾cies. Such differences were significant between SSI (the most active
species with a broader diet) and NOD (the less active species with a
narrower diet), which showed the highest and lowest MeO-PBDE levels,
respectively. The current study supports the importance of the feeding
habits of fish and the species-specificity to explain the accumulation
patterns found here for MeO-PBDEs. Our results add new information to
the scarce data on MeO-PBDEs concentrations in Antarctic marine or￾ganisms and can be taken as baseline for Antarctic notothenioids fish
species.
CRediT authorship contribution statement
Juan Manuel Ríos: Writing – original draft, Formal analysis,
Conceptualization. Sabrina B. Mammana: Investigation, Writing –
original draft. Eugenia Moreira: Investigation, Writing – original draft.
Giulia Poma: Writing – review & editing, Supervision, Validation.
Govindan Malarvannan: Writing – review & editing. Esteban Barrera￾Oro: Resources, Investigation, Validation, Project administration, Su￾pervision, Writing – review & editing, Funding acquisition. Adrian
Covaci: Resources, Methodology, Validation, Project administration,
Supervision, Writing – review & editing, Funding acquisition. Nestor F.
Ciocco: Resources, Writing – review & editing, Funding acquisition.
Jorgelina C. Altamirano: Conceptualization, Project administration,
Supervision, Writing – review & editing, Funding acquisition.
Declaration of competing interest
The authors declare that they have no known competing financial
interests or personal relationships that could have appeared to influence
the work reported in this paper.
Acknowledgements
This work was supported by Consejo Nacional de Investigaciones
Científicas y T´ecnicas (CONICET), Direccion ´ Nacional del Ant´
artico,
Agencia Nacional de Promocion ´ Científica y Tecnologica ´ [ANPCyT PICT
2016:0093, PICT 2017:1091, and PICT 2018:03310]; W911NF1910423,
EU H2020 INTERWASTE ID# 734522 and SIIP-UNCuyo 06/M062.
Additional financial support was provided by the EU H2020 INTER￾WASTE project (grant agreement, 734522), for the secondment of S.
Mammana to the University of Antwerp.
Appendix A. Supplementary data
Supplementary data to this article can be found online at https://doi.
org/10.1016/j.marpolbul.2021.112453.
References
Ahmad, I., Maria, V.L., Oliveira, M., Serafim, A., Bebianno, M.J., Pacheco, M., et al.,
2008. DNA damage and lipid peroxidation vs. protection responses in the gill of
Dicentrarchus labrax L. from contaminated coastal lagoon (Ria de Aveiro, Portugal).
Sci. Total Environ. 406, 298–307. https://doi.org/10.1016/j.scitotenv.2008.06.027.
Barrera-Oro, E., 2002. The role of fish in the Antarctic marine food web: differences
between inshore and offshore waters in the southern Scotia Arc and west Antarctic
Peninsula. Antarct. Sci. 14, 293–309. https://doi.org/10.1017/
S0954102002000111.
Barrera-Oro, E., Moreira, E., Seefeldt, M., Valli, Francione M., Quartino, M.L., 2019. The
importance of macroalgae and associated amphipods in the selective benthic feeding
of sister rockcod species Notothenia rossii and N. coriiceps (Nototheniidae) in West
Antarctica. Polar Biol. 42, 317–334. https://doi.org/10.1007/s00300-018-2424-0.
Borghesi, N., Corsolini, S., Focardi, S., 2008. Levels of polybrominated diphenyl ethers
(PBDEs) and organochlorine pollutants in two species of Antarctic fish (Chionodraco
hamatus and Trematomus bernacchii). Chemosphere 73, 155–160. https://doi.org/
10.1016/j.chemosphere.2008.06.031.
Cabrerizo, A., Dachs, J., Barcelo, ´ D., Jones, K.C., 2013. Climatic and biogeochemical
controls on the remobilization and reservoirs of persistent organic pollutants in
Antarctica. Environ. Sci. Technol. 47 (9), 4299–4306. https://doi.org/10.1021/
es400471c.
Casaux, R., Barrera-Oro, E., 2013. Dietary overlap in inshore notothenioid fish from the
Danco Coast, western Antarctic Peninsula. Polar Res. 32, 21319. https://doi.org/
10.3402/polar.v32i0.21319.
Casaux, R., Barrera, Oro E., Baroni, A., Ramon, ´ A., 2003. Ecology of inshore notothenioid
fish from the Danco Coast, Antarctic Peninsula. Polar Biol. 26, 157–165. https://doi.
org/10.1007/s00300-002-0463-y.
Choo, G., Lee, I.S., Oh, J.E., 2019. Species and habitat-dependent accumulation and
biomagnification of brominated flame retardants and PBDE metabolites. J. Hazard.
Mater. 371, 175–182. https://doi.org/10.1016/j.jhazmat.2019.02.106.
Corsolini, S., Guerranti, C., Perra, G., Focardi, S., 2008. Polybrominated diphenyl ethers,
perfluorinated compounds and chlorinated pesticides in swordfish (Xiphias gladius)
from the Mediterranean Sea. Environ. Sci. Technol. 42, 4344–4349. https://doi.org/
10.1021/es703057f.
Covaci, A., Losada, S., Roosens, L., Vetter, W., Santos, F.J., Neels, H., et al., 2008.
Anthropogenic and naturally occurring organobrominated compounds in two
deepsea fish species from the Mediterranean Sea. Environ. Sci. Technol. 42,
8654–8660. https://doi.org/10.1021/es8016528.
Daniels, R.A., 1982. Feeding ecology of some fishes of the Antarctic Peninsula. Fish. Bull.
80, 575–588.
De Wit, C.A., Herzke, D., Vorkamp, K., 2010. Brominated flame retardants in the Arctic
environment-trends and new candidates. Sci. Total Environ. 408, 2885–2918.

https://doi.org/10.1016/j.scitotenv.2009.08.037.

DeWitt, H.H., 1971 Coastal and deep-water benthic fishes of the Antarctic. In: Bushnell
VC (ed). Antarctic Map Foilio Series. Folio 15. American Geographical Society, New
York, pp. 1–10. doi:10.14430/arctic3075.
Di Rienzo, J.A., Casanoves, F., Balzarini, M.G., Gonzalez, L., Tablada, M., Robledo, C.W.,
2008. InfoStat version ´ 2008. Grupo InfoStat, FCA, Universidad Nacional de Cordoba, ´
Argentina.
Dirtu, A.C., Covaci, A., Abdallah, M., 2013. Advances in the sample preparation of
brominated flame retardants and other brominated compounds. TrAC Trends Anal.
Chem. 43, 189–203. https://doi.org/10.1016/j.trac.2012.10.004.
Eastman, J.T., 2017. Bathymetric distributions of notothenioid fishes. Polar Biol. 40,
2077–2095. https://doi.org/10.1007/s00300-017-2128-x.
Gewurtz, S.B., McGoldrick, D.J., Clark, M.G., Keir, M.J., et al., 2011a. Spatial trends of
polybrominateddiphenyl ethers in Canadian fish and implications for long￾termmonitoring. Environ. Toxicol. Chem. 30, 1564–1575. https://doi.org/10.1002/
etc.555.
Gewurtz, S.B., Backus, S.M., Bhavsar, S.P., McGoldrick, D.J., et al., 2011b. Contaminant
biomonitoring programs in the Great Lakes region: review of approaches and critical
factors. Environ. Rev. 19, 162–184. https://doi.org/10.1139/a11-005.
Gouin, T., Thomas, G.O., Chaemfa, C., Harner, T., Mackay, D., Jones, K.C., 2006.
Concentrations of decabromodiphenyl ether in air from Southern Ontario:
implications for particle-bound transport. Chemosphere. 64, 256–261. https://doi.
org/10.1016/j.chemosphere.2005.12.071.
Goutte, A., Chevreuil, M., Alliot, F., Chastel, O., Cherel, Y., El´eaume, M., et al., 2013.
Persistent organic pollutants in benthic and pelagic organisms off Ad´elie Land,
Antarctica. Mar. Pollut. Bull. 77, 82–89. https://doi.org/10.1016/j.
marpolbul.2013.10.027.
Ikonomou, M.G., Rayne, S., Fischer, M., Fernandez, M.P., Cretney, W., 2002. Occurrence
and congener profiles of polybrominated diphenyl ethers (PBDEs) in environmental
samples from coastal British Columbia, Canada. Chemosphere 46, 649–663. https://
doi.org/10.1016/S0045-6535(01)00229-6.
James, R.A., Hertz-Picciotto, I., Willman, E., Keller, J.A., Charles, M.J., 2002.
Determinants of serum polychlorinated biphenyls and organochlorine pesticides
measured in women from the child health and development study cohort, 1963-
1967. Environ. Health Perspect. 110, 617–624. https://doi.org/10.1289/
ehp.02110617.
Kim, U.J., Jo, H., Lee, I.S., Joo, G.J., Oh, J.E., 2015. Investigation of bioaccumulation and
biotransformation of polybrominated diphenyl ethers, hydroxylated and
methoxylated derivatives in varying trophic level freshwater fishes. Chemosphere
137, 108–114. https://doi.org/10.1016/j.chemosphere.2015.05.104.
Ko, F.C., Pan, W.L., Cheng, J.O., Chen, T.H., Kuo, F.W., et al., 2018. Persistent organic
pollutants in Antarctic notothenioid fish and invertebrates associated with trophic
levels. PLoS One 13 (4), e0194147. https://doi.org/10.1371/journal.pone.0194147.
Kock, K.H., 1992. Antarctic Fish and Fisheries. Cambridge University Press.
Kuo, Y.M., Sepúlveda, M., Hua, I., Ochoa-Acuna, ˜ H., Sutton, T., 2010. Bioaccumulation
and biomagnification of polybrominated diphenyl ethers in a food web of Lake
Michigan. Ecotoxicology 19, 623–634. https://doi.org/10.1007/s10646-009-0431-
Lana, N.B., Berton, P., Covaci, A., Ciocco, N.F., Barrera-Oro, E., Atencio, A.,
Altamirano, J.C., 2014. Fingerprint of persistent organic pollutants in tissues of
Antarctic notothenioid fish. Sci. Total Environ. 499, 89–98. https://doi.org/
10.1016/j.scitotenv.2014.08.033.
Liu, F., Wiseman, S., Wan, Y., Doering, J.A., Hecker, M., Lam, M.H., Giesy, J.P, 2012.
Multi-species comparison of the mechanism of biotransformation of MeO-BDEs to
OH-BDEs in fish. Aquat. Toxicol. 114, 182–188. doi:https://doi.org/10.1016/j.
aquatox.2012.02.024.
Malarvannan, G., Belpaire, C., Geeraerts, C., Eulaers, I., Neels, H., Covaci, A., 2014.
Assessment of persistent brominated and chlorinated organic contaminants in the
European eel (Anguilla Anguilla) in Flanders, Belgium: levels, profiles and health risk.
Sci. Total Environ. 482, 222–233. https://doi.org/10.1016/j.scitotenv.2014.02.127.
J.M. Ríos et al.
Marine Pollution Bulletin 168 (2021) 112453
Near, T.J., Dornburg, A., Harrington, et al., 2015. Identification of the notothenioid sister
lineage illuminates the biogeographic history of an Antarctic adaptive radiation.
BMC Evol. Biol. 15, 109. https://doi.org/10.1186/s12862-015-0362-9.
Ondarza, P.M., Gonzalez, M., Fillmann, G., Miglioranza, K.S.M., 2011. Polybrominated
diphenyl ethers and organochlorine compound levels in brown trout (Salmo trutta)
from Andean Patagonia, Argentina. Chemosphere 83 (11), 597–1602. https://doi.
org/10.1016/j.chemosphere.2011.01.005.
Playle, R.C., 1998. Modelling metal interactions at fish gills. Sci. Total Environ. 219,
147–163. https://doi.org/10.1016/S0048-9697(98)00232-0.
Ribalta, C., Sanchez-Hernandez, J.C., Sol´e, M., 2015. Hepatic biotransformation and
antioxidant enzyme activities in Mediterranean fish from different habitat depths.
Sci. Total Environ. 532, 176–183. https://doi.org/10.1016/j.scitotenv.2015.06.001.
Ríos, J.M., Lana, N.B., Berton, P., Ciocco, N.F., Altamirano, J.C., 2015. Use of wild trout
for PBDE assessment in freshwater environments: review and summary of critical
factors. Emerg. Contam. 1, 54–63. https://doi.org/10.1016/j.emcon.2015.08.002.
Ríos, J.M., Lana, N.B., Ciocco, N.F., Covaci, A., Barrera-Oro, E., Moreira, E., et al., 2017.
Implications of biological factors on accumulation of persistent organic pollutants in
Antarctic notothenioid fish. Ecotoxicol. Environ. Saf. 145, 630–639. https://doi.org/
10.1016/j.ecoenv.2017.08.009.
Ríos, J.M., Ruggeri, F., Poma, G., Malarvannan, G., et al., 2019. Occurrence of
organochlorine compounds in fish from freshwater environments of the central LW 6
Andes, Argentina. Sci. Total Environ. 693, 133389. https://doi.org/10.1016/j.
scitotenv.2019.07.195.
Rutherford, A., 2011. ANOVA and ANCOVA: A GLM Approach. John Wiley & Sons.
Sinkkonen, S., Rantalainen, A.L., Paasivirta, J., Lahtiper¨
a, M., 2004. Polybrominated
methoxy diphenyl ethers (MeO-PBDEs) in fish and guillemot of Baltic, Atlantic and
Arctic environments. Chemosphere 56, 767–775. https://doi.org/10.1016/j.
chemosphere.2004.02.007.
Sol´e, M., Rodríguez, S., Papiol, V., Maynou, F., Cartes, J.E., 2009. Xenobiotic metabolism
markers in marine fish with different trophic strategies and their relationship to
ecological variables. Comp. Biochem. Physiol. C 149, 83–89. https://doi.org/
10.1016/j.cbpc.2008.07.008.
Stapleton, H.M., Alaee, M., Letcher, R.J., Baker, J.E., 2004. Debromination of the flame
retardant decabromodiphenyl ether by juvenile carp (Cyrprinus carpio) following
dietary exposure. Environ. Sci. Technol. 38, 112–119. https://doi.org/10.1021/
es034746j.
Vetter, W., von der Recke, R., Herzke, D., Nygård, T., 2007. Natural and man-made
organobromine compounds in marine biota from Central Norway. Environ. Int. 33,
17–26. https://doi.org/10.1016/j.envint.2006.06.019.
Vives, I., Grimalt, J.O., Lacorte, S., Guillamon, ´ M., Barcelo, ´ D., Rosseland, B.O., 2004.
Polybromodiphenyl ether flame retardants in fish from lakes in European high
mountains and Greenland. Environ. Sci. Technol. 38, 2338–2344. https://doi.org/
10.1021/es030107x.
Voorspoels, S., Covaci, A., Schepens, P., 2003. Polybrominated diphenyl ethers in marine
species from the Belgian North Sea and the Western Scheldt Estuary: levels, profiles,
and distribution. Environ. Sci. Technol. 37, 4348–4357. https://doi.org/10.1021/
es034503r.
Wan, Y., Wiseman, S., Chang, H., Zhang, X., et al., 2009. Origin of hydroxylated
brominated diphenyl ethers: natural compounds or man-made flame retardants?
Environ. Sci. Technol. 43 (19), 7536–7542. https://doi.org/10.1021/es901357u.
Wania, F., Westgate, J.N., 2008. On the mechanism of mountain cold-trapping of organic
chemicals. Environ. Sci. Technol. 42, 9092–9098. https://doi.org/10.1021/
es8013198.
Weijs, L., Dirtu, A.C., Malarvannan, G., Covaci, A., 2015. Bioaccumulation and
biotransformation of brominated flame retardants. In Comprehensive Analytical
Chemistry (vol. 67, pp. 433–491). Elsevier. doi:https://doi.org/10.1016/B978-0-
444-63299-9.00014-4.
Yu, Y., Yang, W., Gao, Z., Lam, M.H., Liu, X., Wang, L., Yu, H., 2008. RP-HPLC
measurement and quantitative structure–property relationship analysis of the n￾octanol–water partitioning coefficients of selected metabolites of polybrominated
diphenyl ethers. Environ. Chem. 5 (5), 332–339. https://doi.org/10.1071/EN08036.
Zar, J., 2013. Biostatistical Analysis: Pearson New International Edition. Pearson Higher
Ed.
J.M. Ríos et al.