Envpol 2020 2346 Original V0 [612292]

Manuscript Details
Manuscript number ENVPOL_2020_2346
Title Bioaccumulation of Per- and Polyfluoroalkyl substances (PFASs) in a Tropical
Estuarine Food Web
Articletype Research Paper
Abstract
Biomagnification of per- and polyfluoroalkyl substances (PFASs) was investigated in biota from a tropical estuary in
Bahia,Brazil. Brazil is one of the few in the world where a perfluorooctane sulfonate (PFOS)-precursor (the
commercial pesticide Sulfluramid; N-ethyl perfluorooctane sulfonamide; EtFOSA) continues to be used under
manufacture and use exemptions of the United Nations Stockholm Convention on Persistent Organic Pollutants.
Samples of 44 organisms (21 taxa), along with biofilm, leaves, sediment and suspended particulate matter were
analyzed to investigated PFAS bioaccumulation in a tropical mangrove food web. Sum (∑) PFAS concentrations in
biotawere dominated by PFOS (93%; 0.05 to 1.97 ng g-1 ww), followed by perfluorotridecanoate (PFTrDA, 57%; 0.01
to0.28ng g-1 ww). Perfluorooctane sulfonamide (FOSA, 54%; 0.01 to 0.32 ng g-1 ww whole-body (wb)) and EtFOSA
(30%;0.01 to 0.21 ng g-1 ww wb) were also detected. PFAS accumulation profiles revealed clustering amongst
bivalve,crustacean, and fish groups. Trophic magnification factors (TMFs) >1 was observed for PFOS (linear +
branched isomers), EtFOSA (linear + branched isomers), and PFNA, showing dissimilar accumulation patterns among
different trophic levels.
Keywords Perfluoroalkyl acids, EtFOSA, Food chain, POPs, Biomagnification.
Corresponding Author DanieleMiranda
Corresponding Author's
InstitutionUFPE
Orderof Authors DanieleMiranda, Jonathan P Benskin, Raed Awad, Gilles Lepoint, Juliana
Leonel,Vanessa Hatje
Suggested reviewers Caroline Simonnet-Laprade, Jianjie Fu, Alena Celsie, Rosalinda Montone, Katrin
Vorkamp
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UNIVERSIDADE FEDERAL DA BAHIA
CENTRO INTERDISCIPLINAR DE ENERGIA E AMBIENTE (CIEnAm)
PROGRAMA DE PÓS-GRADUAÇÃO EM CIÊNCIAS, ENERGIA E AMBIENTE
______________________________________________________________________________________________________________
Coordenação do Programa de Pós-Graduação em Ciências, Energia e Ambiente/PGENAM/CIEnAm
Rua Barão de Jeremoabo S/N Campus Universitário de Ondina, PAF II. Ao Lado do Pavilhão de Aula Prof. Alceu
Hiltner (Prédio da Petrobras), – CEP: 40170-115, Salvador/Ba Tel: (71) 3283-5654 – E-mail: [anonimizat], April 02, 2020
Dr. Professor Eddy Zeng
Co-Editor-in-Chief, Environmental Pollution
Dr. Zeng:
We are submitting the research article entitled “Bioaccumulation of Per- and
Polyfluoroalkyl substances (PFASs) in a Tropical Estuarine Food Web” to the journal
of Environmental Pollution. The manuscript investigates the trophic biomagnification of
Per- and Polyfluoroalkyl substances (PFASs) through a tropical food chain.
Despite the regulatory initiatives, production of PFOS and other long-chain
PFAAs continues in some parts of the world under regulatory exemptions. In Brazil, the
pesticide Sulfluramid (which contains the PFAS N-ethyl perfluorooctane sulfonamide
as the active ingredient) is still used to combat leaf cutting ants, which is problematic
throughout Latin America. There is very little information on the distribution and risks
of this pesticide as a source of perfluorooctane sulfonate (PFOS) to the environment and
humans. In our paper, PFAS accumulation in a tropical marine food web is discussed,
besides the potential influences of organisms’ trophic position on the contaminant
burden. Risks for human intake of perfluorinated per- and polyfluorinated through
consumption of seafood is considered since the aquatic biota analyzed in the present
study is an important source of protein for the local community. To the best of our
knowledge, this is the first time that food web biomagnification of PFAS has been
investigated in a tropical ecosystem.
This manuscript fits the scope of the journal as it is directly related to environmental
pollution and human health. It has not been published and/or is under consideration for
publication elsewhere. All authors agreed on the final version and submission of this
manuscript.
We look forward to hearing from you.
Sincerely,
Daniele de Almeida Miranda

Highlights
There is a large data gap on trophic transfer of PFASs in tropical ecosystems.
Pollution status and biomagnification of PFASs in a tropical estuary were studied.
Perfluorooctane sulfonate (PFOS) accounted for 93% of Ʃ PFAS in biota.
PFASs levels in biota were low but TMF > 1 for a few compounds.
Biomagnification of EtFOSA was found in a tropical estuarine food chain.

1Bioaccumulation of Per- and Polyfluoroalkyl substances (PFASs) in a
2Tropical Estuarine Food Web
3 Daniele de A. Mirandaa,b*, Jonathan P. Benskinb, Raed Awadb,c, Gilles Lepointd, Juliana
4Leonele, Vanessa Hatjea
5aCentro Interdisciplinar de Energia e Ambiente (CIEnAm) & Inst. de Química, Universidade
6Federal da Bahia, 41170-115, Salvador, BA, Brazil;
7bDepartment of Environmental Science, Stockholm University, Stockholm, Sweden;
8cSwedish Environmental Research Institute (IVL), Stockholm, Sweden;
9dFreshwater and Oceanic sciences Unit of reSearch (FOCUS – Oceanology) University of
10Liege, 4000 Liege, Belgium;
11eDepartamento de Oceanografia, Universidade Federal de Santa Catarina, 88040-900,
12Florianópolis, SC, Brazil.
13
14
15*Corresponding author
16Daniele Miranda ( danielealmeida@ufba.br / Daniele.Miranda@aces.su.se)
17Universidade Federal da Bahia
18CIEnAm I, Campus Ondina
19Salvador, Bahia, Brazil. CEP: 41170-115
20
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31

32Abstract
33Biomagnification of per- and polyfluoroalkyl substances (PFASs) was investigated in biota
34from a tropical estuary in Bahia, Brazil. Brazil is one of the few in the world where a
35perfluorooctane sulfonate (PFOS)-precursor (the commercial pesticide Sulfluramid; N-ethyl
36perfluorooctane sulfonamide; EtFOSA) continues to be used under manufacture and use
37exemptions of the United Nations Stockholm Convention on Persistent Organic Pollutants.
38Samples of 44 organisms (21 taxa), along with biofilm, leaves, sediment and suspended
39particulate matter were analyzed to investigated PFAS bioaccumulation in a tropical mangrove
40food web. Sum (∑) PFAS concentrations in biota were dominated by PFOS (93%; 0.05 to 1.97
41ng g-1 ww), followed by perfluorotridecanoate (PFTrDA, 57%; 0.01 to 0.28 ng g-1 ww).
42Perfluorooctane sulfonamide (FOSA, 54%; 0.01 to 0.32 ng g-1 ww whole-body (wb)) and
43EtFOSA (30%; 0.01 to 0.21 ng g-1 ww wb) were also detected. PFAS accumulation profiles
44revealed clustering amongst bivalve, crustacean, and fish groups. Trophic magnification
45factors (TMFs) >1 was observed for PFOS (linear + branched isomers), EtFOSA (linear +
46branched isomers), and PFNA, showing dissimilar accumulation patterns among different
47trophic levels.
48Summary Note: This paper determines the bioaccumulation of Per- and Polyfluoroalkyl
49substances (PFASs) in a tropical estuarine food web in Brazil.
50Keywords: Perfluoroalkyl acids, EtFOSA, Food chain, POPs, Biomagnification.

51Introduction
52Per- and polyfluoroalkyl substances (PFASs) represent a diverse class of anthropogenic
53chemicals which contain at least one fully fluorinated carbon atom (Buck et al., 2011). The
54unique physical-chemical properties of PFASs, including combined
55hydrophobicity/lipophilicity, make them desirable for a wide range of industrial processes and
56products. Notable applications of PFASs include firefighting foams (Dauchy et al., 2019),
57fluoropolymer manufacturing (Song et al., 2018), textiles (Wang et al., 2017), food packaging
58(Schaider et al., 2018; Schultes et al., 2019), cosmetics (Schultes et al., 2018), and pesticides
59(Nascimento et al., 2018).
60Since the early 2000s, there has been considerable concern over the widespread occurrence of
61these substances, in particular the perfluoroalkyl acids (PFAAs), which display high
62persistence and have been found in the blood of humans (Giesy and Kannan, 2001; Lau et al.,
632007; Wang et al., 2018) and wildlife (Dorneles et al., 2008; Giesy and Kannan, 2001; Hong
64et al., 2015; Houde et al., 2006b, 2011; Leonel et al., 2008; Quinete et al., 2009; Routti et al.,
652017; Sanganyado et al., 2018). In 2009, one of the most widespread PFAAs, perfluorooctane
66sulfonate (PFOS), along with its salts and synthetic precursor perfluorooctane sulfonyl fluoride
67(POSF), were added to Annex B of the Stockholm Convention on Persistent Organic Pollutants
68(UNSCPOPs, 2009). Despite these regulatory initiatives, production of PFOS and other long-
69chain PFAAs continues in some parts of the world under regulatory exemptions. For example,
70Brazil obtained a manufacture and use exemption to continue producing and using Sulfluramid,
71which contains the active ingredient N-ethyl perfluorooctane sulfonamide (EtFOSA), a PFOS-
72precursor (Avendaño and Liu, 2015; Zabaleta et al., 2018). Sulfluramid is a formicide
73extensively introduced as a substitute for the organochlorine pesticide Mirex (Nagamoto et al.,
742004), which is used to combat leaf-cutting ants (Atta sp. and Acromyrmex spp.), particularly
75in eucalyptus and pine plantations. Brazil is among the largest consumers of Sulfluramid in the

76world (MMA, 2015). In the past five years, around 280 t year-1 of Sulfluramid (0.3% EtFOSA)
77was imported, but there are considerable uncertainties with this estimate since the quantities of
78Sulfluramid precursor (i.e. POSF) imported into Brazil are not available (MDIC, 2019). Based
79on increasing production of eucalyptus and pine-derived cellulose (Rossato et al., 2018), it is
80expected that the demand for Sulfluramid will continue in the next years.
81The widespread use of Sulfluramid in forestry is one of the main PFOS sources to the coastal
82waters of Brazil (Nascimento et al., 2018). Recent studies observed a PFAS profile consistent
83with Sulfluramid use (i.e. FOSA/PFOS ratio above 5:1) in Subaé river waters, in the Northeast
84of Brazil (Gilljam et al., 2016), suggesting the use of this pesticide in the region and
85highlighting the potential of Sulfluramid as a source of PFOS for both abiotic and biotic
86compartments.
87Although the process of biomagnification is an important mechanism for micronutrient transfer
88through food chains (Barclay et al., 1994; Gribble et al., 2016), it is also a mechanism that
89promotes accumulation of anthropogenic toxic compounds (Borga et al., 2012; Mackay and
90Boethling, 2000). Despite studies reporting the occurrence of PFASs in organisms globally
91(Becker et al., 2010; Hong et al., 2015; Houde et al., 2011, 2006b; Martin et al., 2003; Munoz
92et al., 2017; Sanganyado et al., 2018), few data are available for South American ecosystems
93(Dorneles et al., 2008; Leonel et al., 2008; Olivero-Verbel et al., 2006; Quinete et al., 2009),
94and there is a lack of PFASs bioaccumulation data for tropical ecosystems. Coastal tropical
95environments concentrate the highest rates of biodiversity and productivity (Brown, 2014).
96Furthermore, several freshwater and marine species use these ecosystems (e.g., mangroves and
97estuaries) as a nursery, shelter and feeding area, highlighting the importance of those
98environments as providers of a myriad of ecosystem services.
99Besides its ecological importance, the Subaé estuary, located in northeastern Brazil (Figure
100S1), has been subject to a high load of domestic and industrial effluents for many years (Hatje

101et al., 2006; Hatje and Barros, 2012; Krull et al., 2014; Tavares et al., 1999). Seafood harvested
102in the Subaé estuary is still the main protein consumed by the local people and may also
103represent a source of contaminant exposure for the locals (Barreto and Freitas, 2017).
104Furthermore, the consumption of contaminated fish and seafood may be a significant pathway
105of exposure for humans in several countries, including Brazil (Pérez et al., 2014).
106The present study addresses the paucity of data on PFAS accumulation in tropical environments
107by examining the transfer of these compounds through an estuarine food web. Samples were
108obtained from the Subaé estuary, in Brazil, and included several species of bivalves,
109crustaceans, polychaete, and fish, along with Suspended Particulate Matter (SPM), sediment,
110leave of mangrove trees, and algal biofilm. To the best of our knowledge this is the first study
111investigating the bioaccumulation of PFASs in a topical food web.
112
113Methodology
114Standards and reagents
115Authentic standards of 3 (N-alkyl substituted) perfluorooctane sulfonamides (MeFOSA,
116EtFOSA and FOSA), 3 perfluoroctane sulfonamidoacetates (MeFOSAA, FOSAA and
117EtFOSAA), 9 perfluoroalkyl carboxylates (C 5-C14 PFCAs), and 4 perfluoroalkyl sulfonates
118(PFSAs; PFBS, PFHxS, PFOS and PFDS), as well as the internal standards 13C-PFHpA, 13C-
119PFOA, 13C-PFNA, 13C-PFDA, 13C-PFUnDA, 13C-PFDoDA, 18O-PFHxS, 13C-PFOS, 13C-
120FOSA, D 5-EtFOSA, D 3-MeFOSAA, D5-EtFOSAA, M 8-PFOA, and M 8-PFOS were purchased
121from Wellington Laboratories (Guelph, ON, Canada). A complete list of chemicals (Table S1)
122and reagents used for sample preparation is provided in the supporting information (SI).
123Study area
124Todos os Santos Bay (BTS) is characterized by a tropical humid climate, with an annual mean
125temperature around 25 șC and precipitation of 2.100 mm, with mesotidal semidiurnal tides that

126control the currents inside the bay (Cirano and Lessa, 2007). The bay has three major
127tributaries: Paraguaçu River (56300 km2), Jaguaripe River (2200 km2), and Subaé River (600
128km2). While Subaé is the smallest of the three rivers and has a low mean monthly discharge (9
129m3 s-1), it is known to be a contamination hotspot, once historically it has been subjected to
130high anthropogenic pressure, especially regarding Pb, Zn, Cd, and Hg (Hatje et al., 2006; Krull
131et al., 2014). The increase in anthropogenic activities over the last decades resulted in
132environmental problems that jeopardize the biodiversity and ecological services of the Subaé
133estuary (Almeida et al., 2018; Gilljam et al., 2016; Hatje and Barros, 2012; Ribeiro et al., 2016).
134
135Sample collection
136Twenty-one species of estuarine organisms were collected, including mangrove cupped oyster
137(Crassostrea rhizophorae, n = 14), mangrove shellfish (Mytella guyanensis, n = 63), blue crab
138(Callinectes sapidus, n = 61), clam (Anomalocardia brasiliana, n = 5), polychaete (pooled),
139mangrove oyster (Crassostrea brasiliana, n = 5), stout tagelus (Tagelus plebeius, n = 60), crab
140(Ucides cordatus, n = 6), shrimp (Litopenaeus sp., n = 18), mangrove tree crab (Goniopsis
141cruentata, n = 12), mullet (Mugil sp., n = 3), torroto grunt (Genyatremus luteus, n = 3), mojarra
142(Diapterus sp., n = 9), silver jenny (Eucinostomus sp., n = 1), madamango sea catfish
143(Cathorops spixii, n = 5), fat snook (Centropomus parallelus, n = 3), drum (Stellifer sp., n =
1446), trevally (Caranx sp., n = 5), catfish (Aspistor luniscutis, n = 3), common snook
145(Centropomus undecimalis, n = 3), and barbel drum (Ctenosciaena gracilicirrhus, n = 1).
146Mangrove tree leaves (Rhizophora mangle, Laguncularia racemosa, and Avicenia sp.), biofilm
147(pool of species), and sediments were collected at the same location as the benthic organisms.
148SPM was sampled during the flood tide at three points nearby where sediments were collected.
149For each organism, biometry information was recorded (Table S2). Samples of muscle,

150liver/hepatopancreas, and soft tissues were collected for fish, crustaceans, and bivalves. After
151dissection, tissue wet weight was recorded and thereafter the samples were freeze-dried.
152
153Targeted PFAS analysis
154Samples were extracted using the method described in Zabaleta et al. (2018). A full description
155of the extraction methods is provided in the SI. Briefly, isotopically labelled internal standards
156(2 ng) were added to 0.5 g of freeze-dried sample (biota or sediment), which were extracted
157with acetonitrile (ACN) aided by sonication. SPM samples were extracted using the same
158method, but with methanol as the extraction solvent. All extracts were stored in the freezer
159prior to instrumental analysis.
160Instrumental analysis was carried out by ultra-performance liquid chromatography-tandem
161mass spectrometry (UPLC-MS/MS) using a Waters Acquity UPLC coupled to a Waters Xevo
162TQ-S triple quadrupole mass spectrometer operated in negative ion electrospray ionization,
163selected reaction monitoring mode. Extracts were chromatographed on a BEH C18 analytical
164column (2.1×50mm, 1.7 µm particle size, Waters) operated at a flow rate of 0.4 mL/min, using
165a mobile phase composition of 90% water/10% acetonitrile containing 2 mM ammonium
166acetate (solvent A) and 100% acetonitrile containing 2 mM ammonium acetate (solvent B).
167The gradient profile is provided in Table S3. A total of two precursor/product ion transitions
168were monitored per analyte, one for quantification and the other for qualification (Table S4).
169Quantitative determination of target compounds was carried out by isotope dilution or an
170internal standard approach using a linear calibration curve with 1/x weighting. Branched
171isomers were determined semi-quantitatively using the calibration curve for the linear isomer.
172
173
174

175Organic Carbon (TOC), Total Nitrogen (TN) and their Stable Isotope Analysis
176Analysis of total organic carbon (TOC), total nitrogen (TN), and stable isotopic composition
177of N and C (δ15N and δ13C) were carried out for sediment, muscle of fish and crustaceans,
178whole body of polychaete, and soft tissues of bivalves. Prior to TOC and δ13C analysis, all
179samples were treated with 0.1 M HCl to remove carbonates. Stable isotope ratios were
180measured using an isotope ratio mass spectrometer (IsoPrime100, Isoprime, Cheadle, UK)
181coupled in continuous flow to an elemental analyser (vario MICRO cube, Elementar
182Analysensysteme GmbH, Hanau, Germany). Carbon and nitrogen isotope ratios were
183expressed as δ values (‰) relative to the Vienna PeeDee Belemnite (vPDB) standard and to
184atmospheric N 2 respectively. We used International Atomic Energy Agency (IAEA, Vienna,
185Austria) certified reference materials sucrose (IAEA-C6, δ13C = – 10.8 ± 0.5 ‰; mean ± SD),
186and ammonium sulfate (IAEA-N2, δ15N = 20.3 ± 0.2 ‰; mean ± SD) as primary standards,
187and sulphanilic acid (δ13C= -25.6 ± 0.4 ‰; δ15N = -0.1 ± 0.5 ‰; mean ± SD in each case) as
188secondary analytical standard.
189
190Quality Control
191Each batch of 16 samples included blanks (n = 2), duplicates (n = 1), and spiked samples (n =
1923; 2 ng). Limits of quantification (LOQs) were estimated as the concentration producing a
193signal-to-noise ratio of 3. Calibration curves (1/x weighting) were prepared from the limit of
194quantification (LOQ) to 250 ng mL-1 and determination coefficients (R2), was always in the
195range of 0.994-0.998.
196

197Data handling and statistical analyses
198δ13C and δ15N values were used to determine the trophic web structure and the trophic position
199(TP) of the organisms analysed. The following equation (Eq. 1) was subsequently used to
200estimate the trophic position (TP):
201 Eq. (1) 𝑇𝑃𝑐𝑜𝑛𝑠𝑢𝑚𝑒𝑟 =2+𝛿15𝑁𝑐𝑜𝑛𝑠𝑢𝑚𝑒𝑟 ‒ 𝛿15𝑁𝑏𝑖𝑣𝑎𝑙𝑣𝑒
2.3‰
202where 2.3‰ is assumed to be the δ15N trophic fractionation factor, according to McCutchan et
203al. (2003). TP of the organisms was achieved by subtracting δ15N of bivalves which displayed
204the lowest δ15N values among animal species (C. rhizophorae; δ15N = 8.05, secondary
205consumer) and are assumed to have a trophic position of 2 (i.e. first consumer level). The
206organic matter source could be predicted by the δ 13C value. To estimate the diet source by
207using δ13C values, Post et al. (2007) suggested correcting it for lipid contents using C/N ratio.
208However, the low values of lipids in the tissues of studied species (~ 5%) did not influence the
209results and, hence this correction was not applied.
210The Trophic Magnification Factor (TMF) was obtained as 10slope by plotting the logarithm-
211transformed concentration of a given PFAS against the TP. TMF calculations were carried out
212using soft tissue PFAS concentrations for bivalves and shrimp and estimated whole-body PFAS
213concentrations (C wb) for fish and crab according to the follow equation:
214 Eq. (2) 𝐶𝑤𝑏=∑𝑛=1𝐶𝑡𝑖𝑠𝑠𝑢𝑒_𝑃𝐹𝐴𝑆 ×𝑓𝑡𝑖𝑠𝑠𝑢𝑒_ 𝑃𝐹𝐴𝑆
215where C tissue_PFAS is the concentration of a given PFAS in a specific tissue and f tissue_PFAS is the
216mass fraction of this tissue in the whole body. Each individual organism was calculated
217separately on the basis of the specific tissue concentration. When the liver concentration was
218not available, it was estimated that the concentrations in liver were a factor of 10 higher than
219those of muscle for each compound (more details in SI). Concentrations below the LOQ were
220imputed by ln-transforming data above the detection limit, fitting them to a cumulative normal

221distribution using a Generalized Reduced Gradient algorithm in the Solver add-in feature of
222Microsoft Excel, and then using the cumulative normal distribution curve to estimate missing
223data at the tail of the curve as described previously (Schultes et al., 2019).
224Statistical analyses were carried out using BioEstat 5.0 (Informer Technologies, Inc.),
225MetaboAnalyst, and R statistical software (R version 3.5.2, 2018-12-20). The critical level of
226significance of the tests was set at α = 0.05. All PFAS concentrations were log-transformed in
227order to fit assumptions of the statistical analyses. Significant relationships between TMF and
228PFAS concentrations were determined with nonparametric Kendall’s τ correlations.
229
230Results & Discussion
231
232Quality Control
233PFAS concentrations in blanks were below LOQ in all instances. Spike/recovery experiments
234showed generally good results, with most compounds displaying recoveries from 80 to 115%.
235For a few targets (e.g. PFPeA, PFTrDA, PFTeDA, and EtFOSA) recoveries were below 60%
236or above 120% in specific batches. PFPeA was infrequently detected (i.e. < 30% of organisms)
237and was not subject to further investigation (e.g. TMF calculations). Concentrations of PFHpA,
238PFTrDA, PFTeDA, and L-EtFOSA, data were used as-is, but these concentrations should be
239considered underreported for some species (see Table S5), due to low spike recoveries for these
240compounds. In addition, L-EtFOSA was not reported in polychaete and SPM due to elevated
241recoveries for these matrices.
242
243Subaé estuary food web dynamics
244 Using the bi-plots of δ15N versus δ13C, and the feeding habits of each species (obtained from
245the literature (Barletta et al., 2019; Ferreira et al., 2019; Lira et al., 2018; Matich et al., 2017;

246Souza et al., 2018; Wellens et al., 2015)) we projected the energy flow across the food web.
247δ15N values increased from mangrove tree leaves to omnivore fish, ranging from 1.06 to 13.8
248‰ (Figure 1) and all species connect to each other within the isotopic mixing space. As
249expected, δ13C in mangroves was typical (-29.3 to -26.6‰) of terrestrial C 3 plants (Minihan,
2501983). A similar δ13C composition was observed in sediment and SPM (-25.4 and -26.9 ‰,
251respectively) indicating an influence of mangrove material on sediment and on SPM. δ 13C
252varied from -25.9 ‰ in bivalve (C. rhizophorae) to -17.4 ‰ in fish (Caranx sp.). Most bivalves
253displayed a close relationship with SPM (i.e. an average of 1.11 ‰ in δ13C enrichment
254compared to SPM), except for M. guyanensis with an enrichment of 3.19 ‰, suggesting an
255additional source of carbon, probably from sediment (1.67 ‰ enrichment). Among crustaceans,
256U. Cordatus displayed lower δ13C values (-24.8 ‰) than other crustaceans, which agrees with
257their restricted leaf-feeder habit (Wellens et al., 2015), and sediment intake associated with
258leaves (average of 3.14 ‰ and 0.58 ‰, for carbon enrichment of leaves and sediment,
259respectively).
260Litopenaeus sp. and G. cruentata displayed similar carbon isotopes ratios. These species
261display generalist feeding habits, but they are found in different locations within the mangrove
262forest. G. cruentata develop an important function in mangroves, recycling carbon in sediments
263in non-flooded areas (Wellens et al., 2015), while Litopenaeus sp. is an important link organism
264in this tropical food web (Lira et al., 2018; Vinagre et al., 2018), being the prey of several
265sampled fish in this study. Among fish, C. undecimalis showed distinctive low values of δ13C
266(-23.8 ‰), even for a carnivore species showing a link to mangrove basal resource. In general,
267fish had an average δ15N and δ13C values of 12.6 ± 0.84 ‰ and -20.7 ± 1.91 ‰ (average ± SD),
268respectively. Polychaete and shrimp represent the main food source for these fish species (Lira
269et al., 2018; Loureiro et al., 2016; Martins et al., 2017; Souza et al., 2018), which was
270corroborated by the C and N isotope composition (Figure 1). However, the large carbon

271variation between fish species may indicate an alternative source of food not considered in the
272present study and the fact they are not resident all the time in the mangrove.
273In the food chain, bivalves represented the lowest TP (TP = 2.0, C. rhizophorae; to TP = 2.6,
274T. plebeius), followed by crustaceans (TP = 2.1, C. sapidus to TP = 3.0, G. cruentata),
275polychaete (TP = 3.6, pool of species) and fish (TP= 3.2, Mugil sp. to TP = 4.5, C.
276gracilicirrhus).
277
278PFAS concentrations in biota
279Sum PFAS concentrations in biota ranged from 0.28 ng g-1 ww wb ( C. rhizophorae; Figure 2,
280Table S6) to 3.72 ng g-1 ww wb (Litopenaeus sp.) which are lower than those range reported
281for biota in subtropical (0.50 to 17.5 ng g-1 ww wb) (Loi et al., 2011), temperate (0.66 to 45.0
282ng g-1 ww wb) (Munoz et al., 2017) and polar areas (2.00 to 43.0 ng g-1 ww wb) (Tomy et al.,
2832009). PFOS was generally the most abundant PFAS, with the exception of 3 bivalve samples
284(which were dominated by FOSA) and 1 fish (in which EtFOSA was dominant). Beyond the
285consistent observation of PFOS, the PFAS profile amongst individual species varied
286considerably. For example, most crustacean, polychaete and bivalve samples, contained
287relatively higher levels of PFCAs compared to fish (Figure 2). Also notable was that PFNA
288was the dominant PFCA across most crustacean, fish and polychaete samples, but was
289generally not detected in bivalve. Differences in feed behavior, niche and protein contents of
290each group of organisms can help to explain this dissimilarity. In Laguncularia racemosa
291(white mangrove) and Rhizophora mangle (red mangrove) mangrove leaves, only FOSAA was
292observed (0.16 and 0.07 ng g-1 ww, respectively) (Table S7). No PFASs were detected in the
293biofilm sample above LOQ.
294The elevated concentrations of PFAS, and in particular L-PFOS in shrimps (1.97 ng g-1 ww
295wb) when compared to other organisms are consistent with the results of Carlsson et al. (2016),

296who proposed that the higher protein content of shrimp compared to fish may lead to higher
297PFAS concentrations in the former species. The detritivore habit of shrimp also helps to explain
298the observed profile, since the SPM showed considerable concentrations of PFAS, and
299associated with sediment it is an important route of organic compounds uptake for aquatic
300epibenthic organisms (Liu et al., 2018). For fish, L-PFOS concentrations were an order of
301magnitude lower than those reported for fish from a subtropical region (Loi et al., 2011), but
302similar to those reported for several species of fish from the Arctic (Butt et al., 2010; Tomy et
303al., 2004) and temperate (Munoz et al., 2018) zones. Fish and bivalve from the present work
304also contained lower PFAS concentrations compared to the highly industrialized Guanabara
305Bay in Rio de Janeiro (Quinete et al., 2009). While PFAS profiles were similar at both
306locations, the Sulfluramid metabolite FOSA was absent in samples of the tributaries and coastal
307water, and bivalves from Guanabara Bay, whereas it was present in liver of a few fish samples.
308This is perhaps unsurprising considering that sales of Sulfluramid in Rio de Janeiro were ~100
309times lower than in Bahia state (i.e. between 2014 and 2017) (IBAMA, 2017), and there are no
310known records of Eucalyptus and Pinus plantations in the area.
311Fish analyzed in the present work generally contained lower concentrations of the major
312PFCAs (PFNA, PFUnDA, PFDoDA, PFTrDA, PFTeDA) compared to other organisms (Figure
3132). The reason for this is unclear, but may indicate that exposure routes and/or PFAS
314accumulation in fish are different. However, significant positive log-linear correlations (Table
315S8) were observed among individual PFCAs (except between PFUnDA and PFTeDA), and
316between the most abundant PFCAs (except for PFTrDA) in fish and PFOS, suggesting the same
317source of contaminants for these organisms.
318

319PFAS concentrations in abiotic samples
320In SPM (n=3), 16 PFASs were detected, including 11 linear and 5 branched isomers. Sum
321PFAS concentrations ranged from 1.85 ng g-1 dw (SPM#1) to 7.25 ng g-1 dw (SPM#2) (Figure
3223, Table S9). PFNA was the predominant PFAS in samples closer to the lower estuary (Figure
323S1), whilst PFUnDA was the prevalent compound in the upper estuary. In comparison, 5 linear
324isomers were detected in sediments (n = 4), with sum PFAS concentrations ranging from 0.10
325ng g-1 dw (#2) to 0.33 ng g-1 dw (#1) (Table S10). L-PFOS and L-PFOA were detected in all
326sediment samples at very low concentrations (L-PFOS: 0.07 – 0.34 ng g-1 ww and L-PFOA:
3270.35 – 0.79 ng g-1 ww), while PFOS was detected in all SPM samples ranging from 0.48 to 1.56
328ng g-1 dw. The presence of L-EtFOSA in sediments and its degradation products (e.g. L-FOSA)
329in SPM suggest that, even though the overall concentrations in Subaé estuary are low, there is
330a source of Sulfluramid in the region. The use of Sulfluramid in this area was previous
331identified based on the high FOSA:PFOS detected in the Subaé river (Gilljam et al., 2016). The
332formicide can be mobilized from plantations to rivers and estuaries due to the leaching of
333contaminated soils. Stahl et al. (2013) and Zabaleta et al. (2018) suggested that leaching of
334soils caused by rainwater can promote the transport of EtFOSA and its degradation products to
335groundwater, rivers, and coastal zones. Previous work indicated that sediments and soils can
336act a sink for PFAS compounds, due to their sediment-water partitioning coefficient
337(Nascimento et al., 2018). Most species investigated in the present study display either benthic
338or demersal habits, which indicates that sediment exposure may represent a secondary source
339of PFASs for those organisms (Munoz et al., 2017), in addition to bioaccumulation through the
340food chain. Nonetheless, estuarine areas are naturally dynamic and dilution of organic matter
341(and consequently PFASs) may occur at the site, thereby lowering observed concentrations in
342abiotic matrices.
343

344Bioaccumulation of PFASs in the food chain
345Only compounds with less than 70% censored observations were considered in the
346determination of TMF, since unreliable statistical values may be obtained below this limit
347(Borga et al., 2012; Helsel, 2011). This included (L+Br) PFOS, PFTrDA, L-FOSA, PFUnDA,
348PFDoDA, PFTeDA, PFNA, and (L+Br) EtFOSA. TMFs and Biomagnification Factors (BMFs)
349greater than 1.0 are both considered reliable indicators of bioaccumulation (Borga et al., 2012).
350However, TMF is considered the most consistent way to characterize biomagnification of
351organic compounds over an entire food web (Franklin, 2016). TMFs were greater than 1 for L-
352and Br-PFOS, L- and Br-EtFOSA, and PFNA, indicating biomagnification across trophic
353levels. Concentration of four PFASs and trophic level were significant (p < 0.05; Table 1,
354Kendell's rank correlation), including bioaccumulation of L-PFOS (n = 44; τ = 0.215, p =
3550.043) and dilution of PFTeDA (n = 44; τ = -0.329, p = 0.002). These data further highlight the
356potential of PFOS to be biomagnified through the tropical food web, which is consistent with
357prior studies in temperate and subtropical zones (Liu et al., 2018; Loi et al., 2011; Munoz et
358al., 2018).
359The absence of TMFs greater than 1 for most PFCAs was initially surprising, since
360bioaccumulation of C 9-C12 PFCAs has been reported elsewhere (Houde et al., 2006a; Munoz
361et al., 2017). However, biodilution has also been reported for C 13-C14 PFCAs (Munoz et al.,
3622017), which may be associated with the limitation of PFCAs with >10 fluorinated carbons to
363penetrate cell membranes due to their large molecular size (Conder et al., 2008; Hong et al.,
3642015). For PFOS, the TMF determined here was lower than previously reported for polar food
365webs, but similar to those in subtropical regions (Table S11) (Boisvert et al., 2019; Munoz et
366al., 2018; Loi et al., 2011; Tomy et al., 2004). Differences in PFAS sources and/or proximity
367to sources may play a role in explaining these differences. For example, it is well known that
368environmental PFAS concentrations are generally higher in the Northern Hemisphere closest

369to point sources (Benskin et al., 2012). Likewise, the ongoing use of EtFOSA in South America
370is unique relative to other parts of the world, and exposure to this substance may have an impact
371on PFOS accumulation in the Subaé estuary wildlife (Gilljam et al., 2016; Nascimento et al.,
3722018). Differences in food webs structure may also play a role. High trophic level of polar food
373chains is occupied by top predator mammals, which means higher energy flow compared to
374tropical environments (Hobson et al., 2002). The lower TMFs in tropical aquatic ecosystems
375possibly reflects not only the lower input of PFASs, but also the structure of food webs that are
376generally larger in number of organisms, which may dilute the energy flows among and
377possibly the contaminants burden (Borga et al., 2012). Also, differences in protein content in
378the blood and tissues of different species can result in variability in the accumulation of
379contaminants (Goeritz et al., 2013). Finally, we cannot rule out the climatic factors (e.g. water
380temperature) and water chemistry, which may also have an impact on PFAS accumulation at
381different trophic levels (Vidal et al., 2019; Xu et al., 2014).
382Surprisingly, the TMF for L-EtFOSA was above 1 (1.80), suggesting that this compound is
383bioaccumulating in the Subaé estuarine food chain. However, since EtFOSA was detected in
384low concentrations throughout the food chain (0.01 to 0.21 ng g-1 ww wb, 30% detection
385frequency), TMFs should be interpreted cautiously, and further studies are warranted to
386corroborate these results. To the best of our knowledge, TMFs for EtFOSA have not been
387previously reported, but Tomy et al. (2004) showed TP-adjusted BMFs for species from the
388Arctic web food and suggested that different species metabolize EtFOSA in distinctive
389proportions. It is well known that EtFOSA is readily biotransformed into FOSA in a few types
390of soil in aerobic conditions (Avendaño and Liu, 2015; Yin et al., 2018; Zabaleta et al., 2018),
391and also in earthworms (Zhao et al., 2018) but no studies were carried out in estuarine
392environments to support our results. Interestingly, when EtFOSA TMFs were re-calculated
393after splitting the organisms in 2 groups based on their trophic level (i.e. group 1: TP 2.00 to

3943.22, and group 2: TP 3.56 to 4.49), a much higher TMF was observed for group 1 (2.65)
395compared to group 2 (0.22), suggesting that dilution of this compound is occurring in top
396organisms (Table S12). Besides the differences in habitats and trophic levels between the
397mentioned groups, the first group consists mainly of filter-feeding organisms, while the second
398group comprises mostly omnivores organisms. The different feeding habits of those organisms
399can imply dissimilar contaminant exposure and hence uptake. Higher TMF for bottom species
400were previously reported for other PFASs, (Munoz et al., 2017) and may point to greater
401efficiency in metabolizing and/or excreting xenobiotics in higher trophic level organisms. A
402different contaminants pathway should not be excluded.
403
404Conclusions
405Bioaccumulation of PFOS was detected in a tropical estuary of northeast Brazil, associated to
406the use of their precursor (i.e. the formicide Sulfluramid) in the region. In addition to PFOS,
407the active ingredient in Sulfluramid, EtFOSA, showed the potential of being magnified through
408the food chain, highlighting the concern about the use of the formicide. Low levels of PFASs
409and different accumulation profiles were generally found in biotic and abiotic matrices when
410compared to subtropical, temperate and polar environments. Nonetheless, EtFOSA was always
411present in different types of samples. The occurrence of PFASs in seafood is particularly
412concerning as this may represent a significant source of human exposure via consumption of
413these organisms. For future work studies stressing the importance of Sulfluramid in the PFOS
414bioaccumulation should be encouraged. But, yet, the data showed in the present study reinforce
415the formicide as a potential contributor to PFOS burden in abiotic matrices and its
416bioaccumulation through the food chain.
417
418

419Acknowledgments
420This work was supported by Fundação de Amparo à Pesquisa do Estado da Bahia, Brazil
421(FAPESB) (PET0034/2012), CNPQ (441829/2014-7), and the Rufford Foundation (nș 2992-
4221). The authors were supported by FAPESB (D. Miranda, nș BOL0122/2017), Coordenação de
423Aperfeiçoamento de Pessoal de Nível Superior, Brazil (Ph.D. Sandwich, D. Miranda, nș
42488881.188589/2018-01), and CNPq (V. Hatje – 304823/2018-0). J. Leonel were sponsored by
425CNPq (401443/2016-7 and 310786/2018-5). G. Lepoint is supported by the F.R.S.-FNRS.
426Thanks to Krishna Das for the collaboration with the Isotope Data. Thanks to Taiana A.
427Guimarães for the sample collection and sample preparation for the isotopic analyses.

4280481216
-35 -30 -25 -20 -15 -1015N (‰)
13C (‰)SPM (n = 3)
Sediment (n = 4)
Leaf (pool)
Biofilm (pool)
Bivalve (n = 5)
Polychaete (pool)
Crustacean (n = 10)
Fish (n = 28)
429Figure 1: Distribution of δ13C and δ15N in biotic and abiotic samples from the Subaé estuary,
430NE Brazil. Where SPM represents the suspended particulate matter and n the number of
431replicates analyzed.
432

433
434 Figure 2: Sum PFAS concentrations (ng g-1 wet weight (ww) for the whole body) measured
435in different organisms from the Subaé estuary (a); and relative PFAS profiles (normalized to
436100%) (b). Number of organisms analyzed is shown in parentheses. EtFOSA was not reported
437for polychaete.
438

439
440Figure 3: Sum of PFAS concentrations in different samples from the Subaé estuary. (a)
441Concentrations are expressed in ng per g dry weight (dw) for sediment and SPM, and ng per g
442wet weight (ww) for leave and biofilm and (b) corresponding composition profiles (relative
443abundance in % of Σ PFAS).

444Table 1: Regressions of Log Concentration (concentrations expressed in ng g-1 ww whole
445body, min-max) vs TP (trophic level) in the whole food web, compounds detection frequency,
446minimum and maximum whole-body wet weight concentrations, Kendall’s τ correlation
447coefficient and Akaike’s Information Criterion (AIC). EtFOSA was not reported for
448polychaete.
CompoundDetection
frequency
(%)Concentration
average (min-
max)TTMF FW
(min– max)AIC
L-PFOS 93 0.49 (0.05 – 1.97) 0.215 1.53 (1.49 – 1.57)-
802.3
Br-PFOS 73 0.09 (0.01 – 0.35) 0.052 1.53 (1.45 – 1.61)-
775.2
PFTrDA 57 0.06 (0.01 – 0.28) -0.386 0.39 (0.38 – 0.40)-
807.5
L-FOSA 54 0.06 (0.01 – 0.32) -0.177 0.64 (0.62 – 0.66)-
794.1
Br-FOSA 27 0.02 (0.01 – 0.24) -0.119 0.83 (0.78 – 0.88)-
768.7
PFUnDA 48 0.04 (0.01 – 0.17) -0.226 0.41 (0.39 – 0.43)-
780.4
PFDoDA 46 0.03 (0.01 – 0.15) -0.075 0.94 (0.88 – 1.00)-
766.3
PFTeDA 46 0.05 (0.01 – 0.26) -0.329 0.62 (0.48 – 0.80) 79.41
PFNA 41 0.03 (0.01 – 0.42) 0.029 1.34 (1.27 – 1.42)-
772.3
L-EtFOSA 30 0.03 (0.01 – 0.21) 0.112 1.80 (1.72 – 1.89)-
777.9
Br-EtFOSA 30 0.09 (0.01 – 0.58) -0.021 1.60 (1.38 – 1.86)-
727.2
449aIt was obtained with the NADA R-package, including Kendall’s τ correlation coefficient, the
450resulting trophic magnification factor (TMF = 10slope) with the confidence interval (min – max),
451and Akaike information criterion. Bold numbers indicate significant regressions (p < 0.05);
452bNote that for detection frequency percentage of individual tissue (muscle, liver, hepatopancreas
453and soft tissue of bivalves and shrimp, n = 56) was used.
454

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Conflict of interest
There are no conflicts of interest to declare.

1Supplementary Information
2
3Bioaccumulation of Per- and Polyfluoroalkyl substances (PFASs) in a Tropical
4Estuarine Food Web
5 Daniele de A. Mirandaa,b*, Jonathan P. Benskinb, Raed Awadb,c, Gilles Lepointd, Juliana
6Leonele, Vanessa Hatjea
7aCentro Interdisciplinar de Energia e Ambiente (CIEnAm) & Inst. de Química, Universidade
8Federal da Bahia, 41170-115, Salvador, BA, Brazil;
9bDepartment of Environmental Science, Stockholm University, Stockholm, Sweden;
10cSwedish Environmental Research Institute (IVL), Stockholm, Sweden;
11dFreshwater and Oceanic sciences Unit of reSearch (FOCUS – Oceanology) University of Liege,
124000 Liege, Belgium;
13eDepartamento de Oceanografia, Universidade Federal de Santa Catarina, 88040-900,
14Florianópolis, SC, Brazil.
15
16
17*Corresponding author: danielemirandaba@gmail.com
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37

38R-Scripts for Kendall correlation between Trophic Position x PFAS, and Trophic
39Magnification Factors
40#kendall correlation
41setwd("C:/Users/DanieleMiranda/Desktop/Bioaccumulation Data/Excel files")
42foodweb<-read.table("8compounds_sum_kendall",h=T)
43library(NADA)
44cor.test(foodweb$TL,foodweb$PFNA, method="kendall")
45Plots
46Library(NADA)
47library("ggpubr")
48ggscatter(foodweb, x = "TL", y = "PFNA",
49 add = "reg.line", conf.int = TRUE,
50cor.coef = TRUE, cor.method = "kendall",
51xlab = "TL", ylab = "PFNA")
52
53#Lmec (Linear Mixed-Effects Models with Censored Responses – LMEC)
54cens = foodweb$L_EtFOSA
55yL = foodweb$L_EtFOSA
56X = cbind(rep(1, length(yL)), foodweb$TL)
57cluster = as.numeric(foodweb$ID)
58Z = matrix(rep(1, length(yL)), ncol = 1)
59fit <- lmec(yL, cens, X, Z, cluster, method = "ML", maxstep = 40)
60res <- cbind.data.frame(lowerbound = fit$beta – 1.96*diag(fit$varFix), estimate=fit$beta,
61upperbound=fit$beta+1.96*diag(fit$varFix))
62TMF = 10^res[2,]
63TMF
64nbparam = length(fit$beta) + length(fit$bi) + 2
65AICmod = -2*fit$loglik + 2*(nbparam)
66AICcens_mod = AICmod + 2*(nbparam)*(nbparam+1)/(length(yL)-nbparam-1)
67AICcens_mod
68cor.test(foodweb$TL,foodweb$L_EtFOSA, method="kendall")
69

70Standards and reagents
71Methanol MeOH (HPLC grade) was purchased from J.T. Baker (Atlantic Labo, Bruges, France).
72Acetonitrile was purchased from Honeywell (Steinheim, Germany). Formic acid and acetic acid
73were purchased from Merck (Darmstadt, Germany). Ammonium formate salts was purchased from
74FLUKA analytical. Ammonium hydroxide salts was purchased from Mallinckrodt chemicals. All
75standards were purchased from Wellington Laboratories (Guelph, ON, Canada). Lastly, water was
76purified with a Millipore water purification system (Millipore, Bedford, MA, USA and had a
77resistance of 18,2 MΩ cm-1.
78Cleaning of materials
79Polypropylene bottles, tubes and spoons were used to handle sediment samples. These materials
80were kept in an Extran® bath (10%) for at least 24h and then washed with water and rinsed with
81Milli-Q® water. The materials were dried at environment temperature and then cleaned three times
82with 1% of NaOH in methanol. Glass materials were calcined at 450 °C for 4 hours and rinsed
83three times with 1% of NaOH in methanol.
84Suspended matter and sediment samples
85Samples of suspended particulate matter were collected using 4-liter glass bottles to collect water.
86In the laboratory, the samples were filtered on a glass fiber filter (25 µm) and the samples were
87then kept frozen until the time of analysis. Sediment samples were collected in the same places
88where the benthic organisms were sampled. The samples were collected with the aid of a stainless-
89steel spoon and then kept frozen until the analysis.
90Extraction of sediments and suspended matter
91Sediment samples were extract using previously published method by Zabaleta et al. (2018). First
92of all, 500 mg of sediment were weighted in a 50 mL polypropylene tube, and then 2 ng of
93isotopically-labelled standards and 8 mL of ACN were added. The mixture was sonicated for 20
94min. The tubes were shaken for 40 minutes and then centrifuged by 2900 rpm for 20 minutes. The
95supernatant was removed and an 8 mL of ACN with 25mM NaOH (7.2 mL ACN + 0.6 mL
96deionized water + 0.2 mL NaOH 1M) was added and the proceeding (ultrasonic, shaken and
97centrifuged) were repeated. The supernatant was put together with the first extract. The final
98extract was dried until dryness by a gently nitrogen (analytical grade, 5.0) flux. The extract was
99resuspended with 400 μL of methanol (MeOH):Milli-Q water (1:1, v/v) with 20 mM formic acid
100and 20 mM ammonium formate. The suspended matter followed the same methodology, but the
101solvent used was pure methanol. Extracts were transferred to an ampoule and sealed.
102Extraction of biotic samples
103Biotic samples were extract using previously published method by Zabaleta et al. (2018) (Zabaleta
104et al., 2017). First of all, 500 mg of samples were weighted in a 50 mL polypropylene tube, and
105then 2 ng of isotopically-labelled standards and 8 mL of ACN were added. The mixture was
106sonicated for 20 min. The tubes were shaken for 40 minutes and then centrifuged by 2900 rpm for
10720 minutes. The supernatant was removed and an 8 mL of ACN with 25mM NaOH (7.2 mL CAN

108+ 0.6 mL deionized water + 0.2 mL NaOH 1M) was added and the proceeding (ultrasonic, shaken
109and centrifuged) were repeated. The supernatant was put together with the first one. The final
110extract was dried until 200 µL by a gently nitrogen flux (analytical grade, 5.0), which was mixed
111with 200 μL of Milli-Q water containing 20 mM formic acid and 20 mM ammonium formate.
112Extracts were transferred to an ampoule and sealed.
113
114Conversion of whole fish contaminant concentration
115Some authors have pointed out a concern about the PFASs whole-body (wb) burden in larger
116species to achieve the TMF of those compounds, in an attempt to avoid bias (Houde et al., 2006;
117Müller et al., 2011). When whole-body concentrations are not available, an alternative is to
118attempt to predict them through the concentration and masses of tissues available for analysis.
119Goeritz et al. (2013) suggested the concentrations of different PFASs found in muscle resemble
120those found in most fish tissues, except for liver and blood which accumulate higher PFAS
121concentrations due to higher protein content. Based on these assumptions the wb concentration
122was calculated for most of the PFASs following the equation below:
123 𝑤𝑏𝑐 =(𝑚𝑢𝑠 𝑔 × [ ] 𝑚𝑢𝑠 𝑛𝑔 𝑔‒1)…+ (𝑐𝑎𝑟𝑐 𝑔 × [ ] 𝑚𝑢𝑠 𝑛𝑔 𝑔‒1)…+ (𝑙𝑖𝑣 𝑔 × [ ] 𝑙𝑖𝑣 𝑛𝑔 𝑔‒1)
𝑇𝑜𝑡𝑎𝑙 𝑤𝑒𝑖𝑔ℎ𝑡
124where wbc is the whole body concentration in ng g-1 (wet weight, ww), mus g represents the mass
125measurement of muscle in grams, mus ng g-1 represents the concentration of each PFASs in muscle
126in ng g-1ww, total weight represents the entire organism weight in grams. When the biometric
127information of the organism was not available, literature was accessed to achieve the percentage
128of each organ represent in the organism, either in the same species or the most similar existing.
129Since gonadal tissue has a higher lipid and protein content as liver, when this first PFASs
130concentration data was not available, the tissue mass was assumed as similar to liver tissue.
131Nania et al. (2009) suggested the concentrations of PFOS in the liver is approximately 10 times
132the one find in muscle. Based on that assumption and in the lack of information, the PFASs
133concentration of muscle was multiplied by 10 when the liver concentrations were not available.
134And then the whole-body concentration was estimated.

135 Table S1: Perfluoroalkyl substances (PFASs) analyzed in the present study.
Acronym Name Formula CAS#
Perfluoroalkyl carboxylic acids (PFCAs)
PFPeA Perfluoropentanoic acid C4F9COOH 2706-90-3
PFHpA Perfluoroheptanoic acid C6F13COOH 375-85-9
PFOA* Perfluorooctanoic acid C7F15COOH 335-67-1
PFNA Perfluorononanoic acid C8F17COOH 375-95-1
PFDA Perfluorodecanoic acid C9F19COOH 335-76-2
PFUnDA Perfluoroundecanoic acid C10F21COOH 2058-94-8
PFDoDA Perfluorododecanoic acid C11F23COOH 307-55-1
PFTrDA Perfluorotridecanoic acid C12F25COOH 72629-94-8
PFTeDA Perfluorotetradecanoic acid C13F27COOH 376-06-7
PFPeDA Perfluoropentadecanoic acid C14F29COOH 1214264-29-
5
Perfluoroalkyl sulfonic acids (PFSAs)
PFBS Perfluorobutanesulfonic acid C4F9SO 3H 375-73-5
PFHxS* Perfluorohexanesulfonic acid C6F13SO 3H 355-46-4
PFOS* Perfluorooctanesulfonic acid C8F17SO 3H 1763-23-1
PFDS* Perfluorodecanesulfonic acid C10F21SO 3H 355-77-3
Perfluoroalkyl sulfonamido acetic derivatives (FASAAs)
MeFOSA N-methylperfluoro-1-octanesulfonamide C11H8F17NO 3S 24448-09-7
FOSAA* Perfluoro-1-octanesulfonamidoacetic acid C8F17SO 2NHCH 2COOH 2806-24-8
MeFOSAA N-methylperfluoro-1-
octanesulfonamidoacetic acidC₁₁H₃D₃F₁₇NO₄S 1400690-70-1
EtFOSAA* N-ethylperfluoro-1-octanesulfonamidoacetic
acidC8F17SO 2NH(C 2H5)CH 2COOH 2991-50-6
Perfluoroalkyl sulfonamide derivatives (FASAs)
FOSA* Perfluorooctanesulfonamide C8F17SO 2NH 2 754-91-6
EtFOSA* N-Ethyl perfluorooctanesulfonamide C8F17SO 2NH(C 2H5) 4151-50-2
136*Compounds analyzed for both linear (L-) and branched (Br-) isomers.

137Table S2: Biometric information of organisms sampled at Subaé estuary. Species are presented with common and
138scientific names. N = number of species measured.
Group Species N TL (cm) TW (g) Mus (g)Hepat/Liv
(g)Food Habit
Mollusk Mangrove cupped oyster
(Crassostrea rhizophorae)14 6.16
(3.85-12.0)41.8
(6.56-585)3.96
(1.13-55.4)Filter-feeder
Mangrove shellfish
(Mytella guyanensis)63 3.59
(2.13-5.50)2.41
(0.74-6.45)0.51
(0.12-1.7)Filter-feeder
Clam
(Anomalocardia brasiliana)61 2.78
(0.74-5.76)6.88
(3.09-10.2)1.05
(0.36-1.54)Filter-feeder
Mangrove oyster
(Crassostrea brasiliana)5 9.98
(8.20-13.2)155
(68.6-255)17.3
(11.6-26.5)Filter-feeder
Stout tagelus
(Tagelus plebeius)60 3.84
(3.14-4.87)2.62
(1.17-4.09)1.39
(0.65-2.26)Filter-feeder
Annelida Polychaete 5.28 Detritivore
Crustacean Blue crab
(Callinectes sapidus)4 8.17
(5.11-10.3)34.4
(25.3-44.0)14.3
(12.2-17.3)Zoobenthivore
Ucides
(Ucides cordatus)6 4.22
(3.86-4.52)109
(76.8-137)18.
1(11.5-27.4)9.53
(7.84-11.1)Herbivore
Whiteleg shrimp
(Litopenaeus sp.)18 9.82
(8.5-11.3)7.89
(4.13-10.3)Detritivore
Mangrove tree crab
(Goniopsis cruentata)12 3.19
(2.53-4.18)24.9
(12.7-44.1)8.30
(3.49-18.7)2.73
(1.41-5.38)Carnivore
Fish Mullet (Mugil sp.) 3 196
(77.1-405)Detritivore
Torroto grunt
(Genyatremus luteus)3 23.7
(22.5-24.9)276
(230-327)72.1
(56.4-85.8)4.08
(2.68-6.73)Zoobenthivore
Mojarra (Diapterus sp.) 9 10.3
(9.30-12.0)15.3
(10.5-26.9)4.08
(2.66-8.47)Omnivore
Silverjenny (Eucinostomus sp.) 1 19.8 9.26 Zoobenthivore
Madamango sea catfish
(Cathorops spixii)5 17.0
(14.3-19.8)46.2
(35.7-64.2)9.55
(6.04-12.5)4.47
(2.97-5.70)Zoobenthivore
Fat snook
(Centropomus parallelus)3 236
(27.4-500)78.2
(9.17-174)1.27
(0.07-2.83)Carnivore
Drum
(Stellifer sp.)6 14.7
(13.6-17.0)40.9
(30.2-62.2)11.0
(8.00-17.4)0.25
(0.10-0.46)Zoobenthivore
Trevally
(Caranx sp.)5 18.4
(13.6-23.5)108
(30.4-214)35.4
(8.85-70.6)1.03
(0.26-1.98)Piscivore
Catfish
(Aspistor luniscutis)3 37.4
(26.8-61.1)204
(174-237)34.8
(28.7-42.2)2.11
(1.57-2.58)Omnivore
Common snook
(Centropomus undecimalis)3 102
(38.4-136)37.5
(10.7-54.7)0.73
(0.16-1.08)Carnivore
Barbel drum
(Ctenosciaena gracilicirrhus)1 25.08 12.7 0.02 Zoobenthivore
139Where: TL: total length, TW: Total weight, Mus: Muscle, Hepat: Hepatopancreas (crab). Liver was sampled for fish.
140

141Table S3: Mobile phase gradient profile used in LC-MS/MS.
LC Gradient Program LC Flow Rate
Time (min)Mobile phase A
(%)1Mobile Phase B
(%)2(mL/min)
0.0 90 10 0.40
0.3 90 10 0.40
4.5 20 80 0.40
4.6 0 100 0.40
7.5 0 100 0.55
9.5 90 10 0.40
1421 Mobile phase A: 90 % water and 10 % acetonitrile containing 2 mM ammonium acetate.
1432 Mobile phase B: 100 % acetonitrile containing 2 mM ammonium acetate.
144

145Table S4: List of retention times, and monitored ions for each compound analyzed in the present study.
146
147Target Retention Time
(min)Quant. Ion
(m/z)Qual Ion
(m/z)Standard Internal
StandardIS Ion Data quality
L-PFPeA 0.99 263/219 263/169 L-PFPeA 13C-PFPeA 266/222 Quantitative
L-PFHpA 2.18 363/319 363/169 L-PFHpA13C-PFHpA 367/322 Quantitative
L-PFOA 2.49 413/369 413/169 L-PFOA13C-PFOA 417/372 Quantitative
Br-PFOA ~2.49 413/369 413/169 L-PFOA13C-PFOA 417/372 Semi-quantitative
L-PFNA 2.76 463/419 463/219 L-PFNA13C-PFNA 468/423 Quantitative
L-PFDA 3.02 513/469 513/269 L-PFDA13C-PFDA 515/470 Quantitative
L-PFUnDA 3.27 563/519 563/269 L-PFUnDA13C-PFUnDA 565/520 Quantitative
L-PFDoDA 3.52 613/569 613/169 L-PFDoDA13C-PFDoA 615/570 Quantitative
L-PFTrDA 3.74 663/619 663/169 L-PFTrDA13C-PFDoA 615/570 Quantitative
L-PFTeDA 3.97 713/669 713/169 L-PFTeDA13C-PFDoA 615/570 Quantitative
L-PFPeDA 4.20 763/719 763/169 L-PFTeDA13C-PFDoA 615/570 Qualitative
L-PFBS 1.69 298.9/80 298.9/99 L-PFBS18O-PFHxS 403/84 Quantitative
L-PFHxS 2.92 399/80 399/99 L-PFHxS18O-PFHxS 403/84 Quantitative
Br-PFHxS 2.50 399/80 399/99 L-PFHxS18O-PFHxS 403/84 Semi-quantitative
L-PFOS 3.07 498.9/80 498.9/99 L-PFOS13C-PFOS 503/80 Quantitative
Br-PFOS ~2.95 498.9/80 498.9/99 L-PFOS13C–PFOS 503/80 Semi-quantitative
L-PFDS 3.57 598.9/80 599/99 L-PFDS13C-PFOS 503/80 Quantitative
Br-PFDS ~3.47 599/80 599/99 L-PFDS13C-PFOS 503/80 Semi-quantitative
L-FOSA 4.17 498/78 498/169 L-FOSA13C-FOSA 506/78 Quantitative
Br-FOSA 4.05 498/78 498/169 L-FOSA13C-FOSA 506/78 Semi-quantitative
L-MeFOSA 3.07 512/169 512/219 L-CH 3FOSA D3-MeFOSAA 515/169 Quantitative
Br- MeFOSA ~3.07 512/169 512/219 L-CH 3FOSA D3-MeFOSAA 515/169 Semi-quantitative
L-EtFOSA 4.91 526/169 526/219 L-EtFOSA D5-EtFOSA 531/219 Quantitative
Br-EtFOSA ~4.91 526/169 526/219 L-EtFOSA D5-EtFOSA 531/219 Semi-quantitative
L-FOSAA 3.07 570/419 570/483 L-MeFOSAA D3-MeFOSAA 573/419 Quantitative
Br-EtFOSA ~3.07 570/419 570/483 L-MeFOSAA D3-MeFOSAA 573/419 Semi-quantitative
L-MeFOSAA 3.10 570/419 570/483 L- MeFOSAA D3- CH3FOSAA 573/419 Quantitative
Br- MeFOSAA 3.00 570/419 570/483 L- MeFOSAA D3- CH3FOSAA 573/419 Semi-quantitative
L-EtFOSAA 3.23 584/419 584/526 L-EtFOSAA D5-EtFOSAA 589/419 Quantitative
Br-EtFOSAA 3.13 584/419 584/526 L-EtFOSAA D5-EtFOSAA 589/419 Semi-quantitative
Recovery standards
TargetRetention Time
(min)Quant. Ion
(m/z)
M8-PFOA 2.49 421/376
M8-PFOS 3.07 506.9/80

148 Table S5: Results of triplicate spike/recovery for leaf, muscle of fish and crab, and sediment samples. Branched compounds are assumed to be associated with their
149respective linear compound. (n.r.: not-reported).
150*Either low recovery or high relative standard deviation;
151**Data were not reported for this compound for this specific batch
152*** There was no data for PFPeDA recovery since there is an absence of native standard. In this case, the data quality was semi-quantitative based on another long-chain
153carboxilated compounds. CompoundBatch 1
(Leaf, Avicennia sp.)Batch 2
(C. sapidus)Batch 3
(G. luteus)Batch 4
(G. luteus)Batch 5
(Mugil sp.)Batch 6
(C. parallelus)Batch 7
(Sediment)Batch 8
(Sediment)
Recovery RSD Recovery RSD Recovery RSD Recovery RSD Recovery RSD Recovery RSD Recovery RSD Recovery RSD
PFPeA 59 18 74 14 91 12 63 6 113 42 59 13 85 11 *180 3
PFHpA 85 13 90 9 91 17 107 7 88 7 93 9 82 14 *28 8
L-PFOA 81 29 91 12 98 9 93 6 99 7 88 7 88 12 89 8
Br-PFOA – – – – – – – – – – – – – – – –
PFNA 84 23 91 9 94 9 95 4 97 10 89 7 86 7 83 7
PFDA 84 18 90 10 91 6 96 4 103 13 89 3 88 5 84 9
PFUnDA 85 21 92 15 99 7 96 1 100 8 88 11 94 7 89 8
PFDoDA 86 13 88 10 97 11 95 3 98 6 90 7 90 10 86 8
PFTrDA *41 10 109 15 120 10 123 6 119 7 102 17 *32 10 *25 55
PFTeDA *14 32 93 25 114 9 124 8 109 7 103 11 *4 3 *4 47
PFPeDA*** – – – – – – – – – – – – – – – –
PFBS 52 24 70 10 83 12 81 12 88 10 81 4 77 11 69 11
L-PFHxS 87 22 82 12 94 14 94 4 101 12 86 2 87 6 89 12
L-PFOS 76 19 76 9 111 6 102 1 110 18 101 10 87 6 88 20
Br-PFOS – – – – – – – – – – – – – – – –
L-PFDS 64 17 74 16 96 10 97 2 111 15 88 12 61 11 49 43
Br-PFDS – – – – – – – – – – – – – – – –
L-FOSA 93 14 83 9 83 13 88 7 93 6 79 6 89 14 109 49
Br-FOSA – – – – – – – – – – – – – – – –
L-CH 3FOSA 72 14 75 14 75 33 96 0 100 10 85 11 *102 43 68 51
Br-CH 3FOSA – – – – – – – – – – – – – – – –
L-EtFOSA 76 21 77 12 63 21 68 1 *32 11 73 3 78 10 nr nr
Br-EtFOSA – – – – – – – – – – – – – – – –
L-FOSAA 104 26 75 9 100 8 108 4 87 13 86 11 92 11 105 16
Br-FOSAA – – – – – – – – – – – – – – – –
L-CH 3FOSAA 109 27 102 5 109 2 105 3 111 1 93 12 96 12 92 11
Br-CH 3FOSAA – – – – – – – – – – – – – – – –
L-EtFOSAA 77 47 87 15 99 15 96 14 105 7 84 6 80 10 71 23
Br-EtFOSAA – – – – – – – – – – – – – – – –

154Table S6: Concentrations of PFASs in biota samples from the Subaé estuary, expressed in ng g-1ww whole body (wb) showed as either average (min-max) when
155more than 3 samples or measured concentration for single sample (n.d. = non-detected, n.r. = not-reported).
VariableCrassostrea
rhizophoraeMytella
guyanensisAnomalocardia
brasilianaCrassostrea
brasilianaTagelus
plebeiusCallinectes
sapidusUcides
cordatusLitopenaeus
sp.Goniopsis
cruentata
Class Bivalve Bivalve Bivalve Bivalve Bivalve Crustacean Crustacean Crustacean Crustacean
N 14 (pool) 63 (pool) 61 (pool) 5 (pool) 60 (pool) 4 6 18 (pool) 12
Trophic Level 2.00 2.04 2.11 2.36 2.54 2.60 2.68 2.96 3.01
Carbon -25.93 -23.71 -25.50 -26.11 -25.61 -22.10 -24.79 -21.70 -19.97
PFPeA n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d.
PFHpA n.d. n.d. n.d. n.d. n.d. 0.08 ± 0.03 0.27 ± 0.38 n.d. n.d.
L-PFOA n.d. n.d. n.d. n.d. n.d. 0.10 ± 0.08 n.d. n.d. 0.20 ± 0.15
Br-PFOA n.d n.d. n.d n.d. n.d n.d. n.d. n.d. n.d.
PFNA n.d. n.d. n.d. n.d. n.d. 0.08 ± 0.01 0.04 ± 0.01 n.d. 0.14 ± 0.04
PFDA n.d. n.d. n.d. n.d. n.d. 0.06 ± 0.02 0.07 ± 0.06 n.d. 0.20 ± 0.05
PFUnDA n.d. n.d. n.d. n.d. 0.09 0.07 ± 0.01 0.07 ± 0.05 0.17 0.13 ± 0.03
PFDoDA n.d. n.d. 0.04 n.d. n.d. 0.11 ± 0.002 0.05 ± 0.04 0.15 0.12 ± 0.02
PFTrDA 0.07 0.07 0.06 0.05 0.06 0.17 ± 0.01 0.08 ± 0.05 0.28 0.15 ± 0.04
PFTeDA 0.07 0.07 0.05 0.06 n.d. 0.16 ± 0.02 0.10 ± 0.08 0.26 0.11 ± 0.07
PFPeDA 0.06 n.d. n.d. n.d. n.d. 0.02 ± 0.01 0.01 ± 0.001 0.14 n.d.
PFBS n.d. n.d. n.d. n.d. n.d. 0.01 ± 0.02 n.d. n.d. 0.08 ± 0.11
L-PFHxS 0.08 0.17 0.11 n.d. n.d. 0.02 ± 0.01 0.03 ± 0.02 n.d. 0.07 ± 0.06
Br-PFHxS 0.12 0.33 0.17 n.d. n.d. 0.01 ± 0.01 0.04 ± 0.004 n.d. 0.09 ± 0.04
L-PFOS n.d. 0.36 0.17 n.d. n.d. 0.27 ± 0.04 0.53 ± 0.12 1.97 0.65 ± 0.12
Br-PFOS n.d. 0.17 n.d. n.d. n.d. 0.02 ± 0.01 0.15 ± 0.06 0.35 0.21 ± 0.08
L-PFDS n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d.
Br-PFDS n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d.
L-FOSA 0.22 0.04 0.04 0.06 0.12 0.02 ± 0.01 0.13 ± 0.14 0.21 0.24 ± 0.04
Br-FOSA 0.24 n.d. n.d. 0.08 0.05 0.01 ± 0.002 0.03 ± 0.01 n.d. 0.06 ± 0.06
L-CH 3FOSA n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d.
Br-CH 3FOSA n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d.
L-EtFOSA n.d. n.d. n.d. n.d. 0.03 0.02 ± 0.01 0.05 ± 0.05 n.d. 0.01 ± 0.004
Br-EtFOSA n.d. n.d. n.d. n.d. n.d. n.d. 0.16 ± 0.22 n.d. 0.01 ± 0.004
L-FOSAA n.d. 0.03 0.02 n.d. n.d. n.d. 0.06 ± 0.07 n.d. 0.08 ± 0.05
Br-FOSAA n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d.
L-CH 3FOSAA n.d. n.d. n.d. n.d. n.d. n.d. 0.01 ± 0.01 n.d. 0.01 ± 0.01
Br-CH3FOSAA n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d.
L-EtFOSAA 0.02 n.d. 0.03 n.d. n.d. n.d. 0.03 ± 0.02 0.18 0.10 ± 0.05
Br-EtFOSAA n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d.
156
157

158Continue…
Variable Polychaete Mugil sp.Genyatremus
luteusDiapterus
sp.Eucinostomus
sp.Cathorops
spixiiCentropomus
parallelusStellifer
sp.Caranx
sp.Aspistor
luniscutisCentropomus
undecimalisCtenosciaena
gracilicirrhus
Class Annelida Fish Fish Fish Fish Fish Fish Fish Fish Fish Fish Fish
N (pool) 3 3 9 1 5 3 6 5 3 3 1
Trophic Level 3.22 3.56 3.59 3.68 3.89 3.97 3.98 4.00 4.15 4.29 4.48 4.49
Carbon -24.67 -20.25 -23.68 -21.85 -19.89 -21.83 -20.77 -22.49 -17.42 -18.09 -23.82 -20.38
PFPeA n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d.0.12 ±
0.01n.d. n.d.
PFHpA n.d. 0.52 ± 0.69 0.01 ± 0.002 n.d. n.d. n.d. n.d.0.11 ±
0.080.15 ±
0.16n.d. n.d. n.d.
L-PFOA n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d.
Br-PFOA n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d.
PFNA n.d. 0.03 ± 0.01 0.01 ± 0.0020.03 ±
0.020.02 ± 0.020.02 ±
0.0020.03 ± 0.0030.01 ±
0.0010.02 ±
0.00050.04 ±
0.0010.03 ± 0.003 0.01
PFDA 0.08 n.d. n.d.0.01 ±
0.010.0490.03 ±
0.020.01 ± 0.0010.01 ±
0.010.01 ±
0.0010.01 ±
0.0010.01 ± 0.001 n.d.
PFUnDA n.d. 0.05 ± 0.03 n.d.0.03 ±
0.010.050.02 ±
0.020.02 ± 0.0020.01 ±
0.010.02 ±
0.010.01 ±
0.0010.02 ± 0.002 0.02
PFDoDA n.d. 0.02 ± 0.01 n.d.0.02 ±
0.010.040.02 ±
0.010.02 ± 0.0020.02 ±
0.010.01 ±
0.00040.02 ±
0.010.02 ± 0.002 0.02
PFTrDA 0.17 0.03 ± 0.02 n.d.0.02 ±
0.020.010.02 ±
0.010.03 ± 0.010.02 ±
0.010.01 ±
0.00050.01 ±
0.00050.02 ± 0.004 0.03
PFTeDA 0.22 0.02 ± 0.01 n.d.0.01 ±
0.0010.010.02 ±
0.0020.03 ± 0.010.01 ±
0.0010.01 ±
0.0040.01 ±
0.0010.03 ± 0.002 n.d.
PFPeDA 0.19 n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d.
PFBS n.d. n.d. n.d. n.d. n.d.0.01 ±
0.01n.d. n.d. n.d. n.d. n.d. n.d.
L-PFHxS 0.07 0.04 ± 0.02 n.d.0.01 ±
0.0010.010.01 ±
0.0010.02 ± 0.0020.01 ±
0.0010.01 ±
0.00030.02 ±
0.0010.02 ± 0.002 n.d.
Br-PFHxS 0.02 0.01 ± 0.01 n.d.0.01 ±
0.010.010.01 ±
0.00040.01 ± 0.01 n.d.0.01 ±
0.0020.02 ±
0.003n.d. n.d.
L-PFOS 0.59 0.53 ± 0.42 0.24 ± 0.170.39 ±
0.100.970.45 ±
0.370.26 ± 0.080.28 ±
0.081.20 ±
0.150.63 ±
0.110.45 ± 0.23 0.86
Br-PFOS 0.05 0.13 ± 0.09 0.09 ± 0.070.09 ±
0.040.110.05 ±
0.040.04 ± 0.020.04 ±
0.010.24 ±
0.030.06 ±
0.030.05 ± 0.02 0.16
L-PFDS n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d.
Br-PFDS n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d.
L-FOSA 0.09 0.03 ± 0.02 0.01 ± 0.010.04 ±
0.040.020.02 ±
0.0020.03 ± 0.0050.03 ±
0.020.03 ±
0.020.01 ±
0.00050.04 ± 0.02 0.04
Br-FOSA 0.09 0.02 ± 0.01 n.d.0.01 ±
0.0010.010.01 ±
0.0010.01 ± 0.0010.01 ±
0.01n.d.0.01 ±
0.00020.01 ± 0.001 n.d.
L-CH3FOSA n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d.
Br-CH3FOSA n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d.
L-EtFOSA n.r.0.01 ±
0.00040.11 ± 0.070.05 ±
0.070.010.04 ±
0.020.07 ± 0.020.03 ±
0.020.02 ±
0.010.01 ±
0.00030.03 ± 0.03 n.d.
Br-EtFOSA n.r. 0.21 ± 0.26 0.35 ± 0.190.21 ±
0.19n.d.0.02 ±
0.030.10 ± 0.08 n.d.0.02 ±
0.030.04 ±
0.050.09 ± 0.12 n.d.
L-FOSAA n.d. 0.01 ± 0.02 n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d.
Br-FOSAA n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d.
L-CH 3FOSAA n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d.
Br-CH 3FOSAA n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d.
L-EtFOSAA 0.04 0.04 ± 0.03 n.d. n.d. n.d. n.d. 0.01 ± 0.01 n.d. n.d. n.d. 0.01 ± 0.01 n.d.
Br-EtFOSAA n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d.

159Table S7: Concentrations in ng g-1ww found in mangrove leaves and biofilm sampled at
160Subaé estuary.
161CompoundWhite
mangroveBlack
mangroveRed
mangroveBiofilm
Perfluoroalkyl carboxylic acids (PFCAs)
PFPeA < 1.06 < 1.06 < 1.06 < 1.06
PFHpA < 0.04 < 0.04 < 0.04 < 0.04
L-PFOA < 0.46 < 0.46 < 0.46 < 0.46
Br-PFOA < 0.02 < 0.02 < 0.02 < 0.02
PFNA < 0.28 < 0.28 < 0.28 < 0.28
PFDA < 0.21 < 0.21 < 0.21 < 0.21
PFUnDA < 0.07 < 0.07 < 0.07 < 0.07
PFDoDA < 0.03 < 0.03 < 0.03 < 0.03
PFTrDA < 0.04 < 0.04 < 0.04 < 0.04
PFTeDA < 0.04 < 0.04 < 0.04 < 0.04
PFPeDA < 0.04 < 0.04 < 0.04 < 0.04
Perfluoroalkyl sulfonic acids (PFSAs)
PFBS < 0.02 < 0.02 < 0.02 < 0.02
L-PFHxS < 0.07 < 0.07 < 0.07 < 0.07
Br-PFHxS < 0.07 < 0.07 < 0.07 < 0.07
L-PFHpS < 0.02 < 0.02 < 0.02 < 0.02
L-PFOS < 0.08 < 0.08 < 0.08 < 0.08
Br-PFOS < 0.08 < 0.08 < 0.08 < 0.08
L-PFNS < 0.02 < 0.02 < 0.02 < 0.02
Br-PFNS < 0.02 < 0.02 < 0.02 < 0.02
L-PFDS < 0.02 < 0.02 < 0.02 < 0.02
Br-PFDS < 0.02 < 0.02 < 0.02 < 0.02
PFUnDS < 0.02 < 0.02 < 0.02 < 0.02
Perfluoroalkyl sulfonamido acetic derivatives (FASAAs)
L-CH 3FOSA < 0.02 < 0.02 < 0.02 < 0.02
Br-CH 3FOSA < 0.02 < 0.02 < 0.02 < 0.02
L-FOSAA 0.16 < 0.02 0.07 < 0.02
Br-FOSAA < 0.02 < 0.02 < 0.02 < 0.02
L-CH 3FOSAA < 0.02 < 0.02 < 0.02 < 0.02
Br-CH 3FOSAA < 0.02 < 0.02 < 0.02 < 0.02
L-EtFOSAA < 0.02 < 0.02 < 0.02 < 0.02
Br-EtFOSAA < 0.02 < 0.02 < 0.02 < 0.02
Perfluoroalkyl sulfonamide derivatives (FASAs)
L-FOSA < 0.02 < 0.02 < 0.02 < 0.02
Br-FOSA < 0.02 < 0.02 < 0.02 < 0.02
L-EtFOSA < 0.02 < 0.02 < 0.02 < 0.02
Br-EtFOSA < 0.02 < 0.02 < 0.02 < 0.02

162Table S8: Pearson correlation and significance of the most found
163PFCAs compounds in faunal samples and PFOS.
164Variable p-valuer
(Pearson)
PFNA x PFUnDA 0.0148 0.5958
PFNA x PFDoDA 0.0039 0.6776
PFNA x PFTrDA < 0.0001 0.8271
PFNA x PFTeDA < 0.0001 0.8407
PFUnDA x PFDoDA 0.0434 0.5103
PFUnDA x PFTrDA 0.0082 0.6353
PFUnDA x PFTeDA 0.0798 0.4505
PFDoDA x PFTrDA 0.001 0.7432
PFDoDA x PFTeDA 0.0204 0.5727
PFTrDA x PFTeDA 0.0009 0.7451
PFNA x L-PFOS 0.0181 0.5815
PFUnDA x L-PFOS 0.0078 0.6376
PFDoDA x L-PFOS 0.042 0.5132
PFTrDA x L-PFOS 0.0823 0.4473
PFTeDA x L-PFOS 0.0172 0.585

166Table S9: Concentrations in ng g-1 dw found in mangrove suspended particulate
167matter (SPM) sampled at Subaé estuary (n.r. = not-reported).
Compound SPM#1 SPM#2 SPM#3
Perfluoroalkyl carboxylic acids (PFCAs)
PFPeA 0.15 0.13 < 0.10
PFHpA < 0.13 0.15 < 0.13
L-PFOA < 0.88 < 0.88 < 0.88
Br-PFOA < 0.05 < 0.05 < 0.05
PFNA < 1.97 3.41 2.49
PFDA 0.08 0.15 0.18
PFUnDA 0.67 1.43 0.90
PFDoDA < 0.26 < 0.26 < 0.26
PFTrDA 0.06 0.08 0.11
PFTeDA < 0.10 < 0.10 < 0.10
PFPeDA < 0.05 < 0.05 < 0.05
Perfluoroalkyl sulfonic acids (PFSAs)
PFBS < 0.05 < 0.05 < 0.05
L-PFHxS 0.07 0.16 0.06
Br-PFHxS < 0.05 < 0.05 0.11
L-PFOS 0.480 1.02 1.56
Br-PFOS 0.10 0.25 0.55
L-PFDS < 0.05 < 0.05 < 0.05
Br-PFDS < 0.05 < 0.05 < 0.05
Perfluoroalkyl sulfonamido acetic derivatives (FASAAs)
L-CH 3FOSA < 0.05 < 0.05 < 0.05
Br-CH 3FOSA < 0.05 < 0.05 < 0.05
L-FOSAA < 0.05 < 0.05 < 0.05
Br-FOSAA < 0.05 < 0.05 < 0.05
L-CH 3FOSAA < 0.05 < 0.05 < 0.05
Br-CH 3FOSAA < 0.05 < 0.05 < 0.05
L-EtFOSAA 0.08 < 0.05 0.45
Br-EtFOSAA < 0.05 < 0.05 0.14
Perfluoroalkyl sulfonamide derivatives (FASAs)
L-FOSA 0.16 0.28 0.14
Br-FOSA < 0.05 0.18 < 0.05
L-EtFOSA n.r. n.r. n.r.
Br-EtFOSA n.r. n.r. n.r.
168
169

170Table S10: Concentrations in ng g-1 w found in mangrove sediment sampled at Subaé estuary in four different sites.
Compound #1 #2 #3 #4
Perfluoroalkyl carboxylic acids (PFCAs)
PFPeA < 0.08 < 0.08 < 0.08 < 0.08
PFHpA 0.045 < 0.04 < 0.04 < 0.04
L-PFOA < 0.92 < 0.92 < 0.92 < 0.92
Br-PFOA < 0.05 < 0.05 < 0.05 < 0.05
PFNA 0.278 < 0.21 < 0.21 < 0.21
PFDA < 0.04 < 0.04 < 0.04 < 0.04
PFUnDA < 0.17 < 0.17 < 0.17 < 0.17
PFDoDA < 0.04 < 0.04 < 0.04 < 0.04
PFTrDA < 0.05 < 0.05 < 0.05 < 0.05
PFTeDA < 0.06 < 0.06 < 0.06 < 0.06
PFPeDA < 0.04 < 0.04 < 0.04 < 0.04
Perfluoroalkyl sulfonic acids (PFSAs)
PFBS < 0.04 < 0.04 < 0.04 < 0.04
L-PFHxS < 0.06 < 0.06 < 0.06 < 0.06
Br-PFHxS < 0.04 < 0.04 < 0.04 < 0.04
L-PFOS < 0.37 < 0.37 < 0.37 < 0.37
Br-PFOS < 0.11 < 0.11 < 0.11 < 0.11
L-PFDS < 0.04 < 0.04 < 0.04 < 0.04
Br-PFDS < 0.04 < 0.04 < 0.04 < 0.04
Perfluoroalkyl sulfonamido acetic derivatives (FASAAs)
L-CH 3FOSA < 0.04 < 0.04 < 0.04 < 0.04
Br-CH 3FOSA < 0.04 < 0.04 < 0.04 < 0.04
L-FOSAA < 0.04 < 0.04 < 0.04 < 0.04
Br-FOSAA < 0.04 < 0.04 < 0.04 < 0.04
L-CH 3FOSAA < 0.04 < 0.04 < 0.04 < 0.04
Br-CH 3FOSAA < 0.04 < 0.04 < 0.04 < 0.04
L-EtFOSAA < 0.04 < 0.04 < 0.04 0.05
Br-EtFOSAA < 0.04 < 0.04 < 0.04 < 0.04
Perfluoroalkyl sulfonamide derivatives (FASAs)
L-FOSA < 0.04 < 0.04 < 0.04 < 0.04
Br-FOSA < 0.04 < 0.04 < 0.04 < 0.04
L-EtFOSA < 0.04 0.10 < 0.04 0.14
Br-EtFOSA < 0.04 < 0.04 < 0.04 < 0.04
171
172

173Table S11: Comparison of trophic magnification factor (TMF) and nitrogen content (%) found in different
174studies worldwide.
PFNA PFUnDA PFTrDA PFTeDA L-PFOS Br-PFOS L-FOSA δ15N Local Ref.
⁻ ⁻ ⁻ ⁻ 4.6 ⁻ ⁻ 8.1-18.3Lake
Ontario
(Canada)(Zhao et al.,
2018)
⁻ ⁻ ⁻ ⁻ 3.1 ⁻ ⁻ ⁻ Arctic(Tomy et al.,
2004)
⁻ ⁻ ⁻ ⁻ 6.3 ⁻ ⁻ 9.3 – 15.6 Arctic(Tomy et al.,
2009)
⁻ 1.74 ⁻ 1.12 1.3 ⁻ ⁻ 9.7 – 22.9 China(Loi et al.,
2011)
1.5 1.1 1.1 0.79 1.5 2.2 1.9 5.1 – 15.4 France(Munoz et
al., 2017)
1.34 0.41 0.39 0.27 1.53 1.53 0.64 8.05 – 13.78 Brazil This study
1.66 1.53 1.41 1.41 1.43 ⁻ ⁻ ⁻Lake
Chaohu
(China)(Liu et al.,
2018)

175Table S12: Details on regressions of Log Concentrations (expressed in ng g-1 ww whole body)
176vs TP (trophic position) in group 1 (trophic positions from 2.00 to 2.83) and group 2 (trophic
177levels from 3.06 to 3.83), obtained with the NADA R-package, including the p-value of the
178regression, Kendall’s τ correlation coefficient.
Compound T TMF group 1TMF FW
RangeAIC
PFNA 0.219 3.95 (1.88 – 8.31) -118.7
PFUnDA 0.233 2.37 (1.34 – 4.16) -123.6
PFDoDA 0.131 3.15 (1.29 – 7.68) -115.4
PFTrDA -0.234 0.53 (0.45 – 0.62) -146.4
PFTeDA -0.225 0.44 (0.27 -0.74) -125.3
L-PFOS 0.374 3.22 (2.40 – 4.33) -135.3
Br-PFOS 0.369 8.82 (5.18 – 15.0) -124.7
L-FOSA 0.959 1.84 (1.33 – 2.54) -133.6
L-EtFOSA 0.226 2.65 (1.85 – 3.78) -131.9
Br-EtFOSA 0.273 5.16 (1.40 – 18.9) -108.6
179
180
181
182
183Compound T TMF group 2TMF FW
RangeAIC
PFNA 0.176 0.99 (0.79 – 1.24) -294.6
PFUnDA 1.787 1.82 (1.53 – 2.15) -301.6
PFDoDA 0.221 2.04 (1.71 – 2.44) -300.5
PFTrDA 0.215 1.5 (1.20 – 1.87) -294.9
PFTeDA 0.192 1.42 (1.07 – 1.88) -288.7
L-PFOS 0.294 2.64 (2.21– 3.16) -300.3
Br-PFOS 0.074 1.31 (1.01 – 1.71) -290.1
L-FOSA 0.179 1.54 (1.26 – 1.88) -297.3
L-EtFOSA -0.313 0.22 (0.15 – 0.32) -281
Br-EtFOSA -0.306 0.08 (0.02 – 0.24) -251.6

184
185
186Figure S1: Sediment and bivalve sampling stations of the Subaé, Todos os Santos Bay, BA, Brazil. Suspended
187particulate matter (SPM) was collected between sediment sampling stations (SPM#1 between #1 and #2, SPM#2
188between #2 and #3, and SPM#3 between #3 and #4). Crustaceans and fishes were sampled between #1 and #4
189sampling stations. Sampling point #1 is the closest station to the lower estuary area, while #4 is the closest sampling
190point to Santo Amaro city.

192
193Figure S2: Relative composition of the L-PFOS, L-FOSA
194and L-EtFOSA in biota based in the median of each group of
195organisms.

197
198Figure S3: Biplot with LogPFASs concentrations that showed Trophic Magnification Factor (TMF) > 1 versus δ15N
199measured in the sampled Subaé estuary biota.

200
201Figure S4: Kendall correlation of log transformed perfluoroalkyl carboxylic acids (PFCAs) and trophic position (TL) organisms
202sampled at Subaé estuary.

203
204Figure S5: Kendall correlation of log transformed perfluoroalkyl sulfonamide derivatives (FASAs) and perfluoroalkyl sulfonic
205acids (PFSAs), and trophic position (TL) organisms sampled at Subaé estuary.

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