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                    Marine Pollution Bulletin 171 (2021) 112723

Contents lists available at ScienceDirect

Marine Pollution Bulletin
journal homepage: www.elsevier.com/locate/marpolbul

Oil impact on the environment and aquatic organisms on the coasts of the
states of Alagoas and Sergipe, Brazil - A preliminary evaluation
Emerson Carlos Soares a, *, Mozart Daltro Bispo b, Vivian Costa Vasconcelos a,
João Inácio Soletti b, Sandra Helena Vieira Carvalho b, Maria Janaína de Oliveira c,
Mayara Costa dos Santos c, Emerson dos Santos Freire c, Aryanna Sany Pinto Nogueira c,
Francisco Antônio da Silva Cunha c, Rafael Donizete Dutra Sandes d,
Raquel Anne Ribeiro dos Santos d, Maria Terezinha Santos Leite Neta d, Narendra Narain d,
Carlos Alexandre Borges Garcia e, Silvânio Silvério Lopes da Costa e,
Josué Carinhanha Caldas Santos c, *
a

Laboratory of Water Analyzes and Aquaculture (LAQUA), Agricultural Science Center, Federal University of Alagoas (UFAL), CECA, 57100-000 Rio Largo, Brazil.
Laboratory of Separation System and Process Optimization (LASSOP), Research Laboratory in Chemistry of Natural Products (LPQPN), Technology Center, Federal
University of Alagoas (UFAL), Maceió, Alagoas 57072-970, Brazil
c
Laboratory of Instrumentation and Development in Analytical Chemistry (LINQA), Institute of Chemistry and Biotechnology, Federal University of Alagoas (UFAL),
Campus A.C. Simões, 57072-900 Maceió, Alagoas, Brazil
d
Laboratory of Flavor and Cromatographic Analysis (LAF), Federal University of Sergipe (UFS), São Cristóvão, Sergipe 49100-000, Brazil
e
Laboratory of Technology and Environmental Monitoring (LTMA), Federal University of Sergipe (UFS), São Cristóvão, Sergipe 49100-000, Brazil
b

A R T I C L E I N F O

A B S T R A C T

Keywords:
Oil contamination
Brazilian northeast
Environmental impact
Polycyclic aromatic hydrocarbons

The oil spill off the coast of the Brazilian Northeast region is one of the most significant global events regarding
contamination and environmental impact in recent years. This work evaluates the effects of oil spills on the
Northeast coasts between Alagoas and Sergipe states from October 2019 to January 2020. Analysis of some
sampling points of seawater revealed the presence of Hg, Cd, Pb, and Cu in levels above the maximum con­
centration limits established by the Brazilian legislation. For water quality parameters, phosphorus, nitrite, and
turbidity showed statistically different values. However, the chromatographic profiles of oil obtained from
different beaches were quite similar. Seawater, fishes, and massunins (bivalve) presented the main polycyclic
aromatic hydrocarbons: naphthalene, phenanthrene, fluoranthene, fluorene, and acenaphthalene. Therefore, the
concentration of organic and inorganic contaminants determined in different environmental locations served as a
subsidy to assess the effect of the preliminary oil spill on the Brazilian coast.

1. Introduction
In the year 2019, the most significant environmental disaster in
Brazilian coastal waters was recorded worldwide. However, the myste­
rious oil spills on Brazilian beaches still produce their effects on a
smaller scale, such as seafood contamination causing damage to the
region's economy (Leduc et al., 2020). The spill may have occurred in
the area covered by the south-equatorial current, which is located be­
tween 500 and 700 km off the northeast coast of Brazil. Initially, several
hypotheses were conceived to explain the origin of the contamination,
such as Venezuelan or other oil spills or leaks from ships that sank during

World War II (Soares et al., 2020a, 2020b).
The disaster management is more challenging than for a typical oil
spill because the dense crude oil is not observed on the ocean surface; it
only appears when it washes up on coastal zones such as sandy beaches
and intertidal reefs. Furthermore, since this oil is more dense and rigid,
its perception by satellite images is impracticable, and containment
systems were not very efficient, decreasing its predictability and causing
high environmental impacts (Brazil, 2020).
From August 2019 to January 2020, more than 5000 tons of oil were
removed from the beaches’ sand, swamps, and coral reefs, from the State
of Maranhão (upper north coast of Brazil) to the shores of southeastern

* Corresponding authors.
E-mail addresses: emerson.soares@ceca.ufal.br (E.C. Soares), josue@iqb.ufal.br (J.C.C. Santos).
https://doi.org/10.1016/j.marpolbul.2021.112723
Received 11 July 2020; Received in revised form 8 July 2021; Accepted 11 July 2021
0025-326X/© 2021 Published by Elsevier Ltd.

E.C. Soares et al.

Marine Pollution Bulletin 171 (2021) 112723

states, affecting about 1000 locations (Soares et al., 2020a, 2020b;
Brazil, 2020). However, the Brazilian Northeast was the most affected
area, with oil slicks affecting all the states in the region, including the
states of Alagoas and Sergipe. The oil may have reached the northeast
coast via the Guyana current, and the Brazilian current spread the oil.
Alagoas and Sergipe states have a coastline of 228 and 163 km,
respectively. Alagoas stands out with the Mundaú-Manguaba lagoon
complex, which is considered one of the essential lagoon systems in the
country, producing an estimated 6773 tons of the bivalve sururu
(Mytella charruana) (Coutinho et al., 2014), which is very much used in
the traditional culinary. Besides, the Coral Coast, located in the North
seaside of Alagoas, is a federally protected area covering 135 km of
coastline, with 413,563 ha of terrestrial and marine regions (Steiner
et al., 2015). In turn, the State of Sergipe hosts an extensive mangrove
area, with more than 25,000 ha (Almeida and Barbieri, 2008), and the
largest nursery of olive turtle (Lepidochelys olivacea) in Brazil, located in
the area of the Biological Reserve of Santa Isabel (Oliveira et al., 2014).
Thus, these are the areas of high environmental importance. Due to the
wealth of aquatic ecosystems, alterations caused by the oil spill can last
for years, with immeasurable effects on the coral reefs and in abundant
swamp areas in the region, which could damage coastal biodiversity, job
generation, and income related to tourism and fishing (de Paula et al.,
2018).
Marine-protected areas and tropical ecosystems are currently
affected by chemical pollution. These areas are necessary for nutrient
cycling, animal reproduction and nurseries, recreation, and cultural
endeavors (Costanza et al., 2014). According to Lourenço et al. (2020),
some oil quantities may still be trapped in coastal and shallow marine
sediments. Thus, energetic meteorological events can suspend oil back
into the water column, carrying it towards the coast.
This work evaluates the effects of crude oil on the Brazilian coast,
mainly on the Northeast region, to trace a profile of the environmental
impact caused due to the contaminants present in this ecosystem.
Among the coordinated activities highlighted in this work are the
collection of water, crude oil, sand, and specimens, bioprospecting
through diving in coral environments, and socioeconomic data collec­
tion. The spectrometry analytical techniques were performed such as
graphite furnace atomic absorption spectrometry (GF AAS), cold vapor
atomic fluorescence spectroscopy (CV AFS), hydride generation atomic
fluorescence spectrometry (HG AFS), and gas chromatography coupled
with mass spectrometry (GC–MS), among others techniques to assess
physicochemical parameters, the presence of potentially toxic elements,
fatty oil contents, and the presence of hydrocarbons in animal species to
determine the effects on organisms and the environment. The results
allowed us to understand how the oil spill, in an uncontrolled way, can
impact society and nature.

microwave (Ethos One, Milestone, Italy). The measurements were car­
ried out using a Shimadzu AA 6800 atomic absorption spectrometer
equipped with an ASC-6100 autosampler. Pyrolytic graphite-coated
graphite tubes with transversal heating were used for all experiments.
Integrated absorbance values were used exclusively for signal evaluation
and a deuterium lamp for background correction. The analytical lines
(nm) used were: 228.8 (Cd), 283.3 (Pb), 357.9 (Cr), 324.8 (Cu), 213.9
(Zn), and 232.0 (Ni), all with a spectral bandpass of 0.7 nm. Ultrapure
argon (99.999%) (White Martins, www.praxair.com.br) was used as the
carrier gas. The autosampler was configured to introduce 20 μL of the
sample and 5.0 μL of the chemical modifier into the graphite furnace for
measurements. A cold vapor and hydride generation atomic fluores­
cence spectrophotometers (Millennium Merlin and Excalibur, PSA
Analytical, U.K.) were used to measure total mercury and arsenic con­
tents with high-intensity hollow cathode lamps (Hg: 253.7 nm, and As:
194.7 nm) and a drying system. Hg0 vapor was generated through
chemical reduction of inorganic mercury with SnCl2.2H2O and trans­
ported into a gas-liquid separator by an argon flow (0.25 L min-1). Arsine
(AsH3) was generated from the chemical reduction of As(III) with NaBH4
in an acidic medium (HCl) and transported to the gas-liquid separator by
an argon flow (0.25 L min-1). Carrier gas humidity was removed by a
Perma Purer® device, reducing interference by quenching with a dryer
gas. Ultrapure synthetic air (Linde gas, Brazil) was employed as a dryer
purge gas (2.5 L min-1).
2.3. Seawater samples from Alagoas
All seawater samples were obtained from ten different locations in
Alagoas, always at high tide during the periods from October 2019 to
January 2020: four beaches on the north coast, Maragogi (P01,
9.045278 S, 35.236528 W), Japaratinga (P02, 9.088806 S, 35.256389
W) São Miguel dos Milagres (P03, 9.266917 S, 35.35151 W), and Ipioca
(P04, 9.498472 S, 35.573639 W); one beach in Maceió, capital of the
State of Alagoas (P05, Sete Coqueiros beach, 9.663900 S, 35.703200 W,
urban beach in the central area of Alagoas state coast, which had min­
imum contact with oil, and hence can be considered a negative reference
point); and five beaches on the south coast, Francês – in the Marechal
Deodoro municipality, (P06, 9.770861 S, 35.839991 W), Barra de São
Miguel (P07, 9.838886 S, 35.88868 W), the estuary of Coruripe river/
Barreiras beach, Coruripe municipality (P08, 10.161553 S, 36.15859
W), Toco beach, Feliz Deserto municipality (P09 10.299444 S,
36.290806 W), and Pontal do Peba beach, Piaçabuçú municipality (P10,
10.339139 S, 10.339139 W) (Fig. 1).
2.4. Seawater samples from Sergipe
Samples were also collected from nine different locations in Sergipe:
Saco beach (P20, 11.2545361 S, 37.2028364 W), Men de Sá island (P19,
11.728502 S, 37.923450 W), Viral beach (P18, 11.615609 S, 37.134597
W), Artist's beach (P17, 10.5710853 S, 37.31628 W), Sementeira Park
(P16, 10.5631647 S, 37.31397 W), Japaratuba River (P15, 10.3722429
S, 36.3947707 W), Ponta of Mangues (P14, 10.3452420 S, 36.3628141
W), Santa Isabel Reserve (P13, 10.4432801 S, 36.5148535 W), São
Francisco River (P12, 10.2511546 S, 36.3344526 W), and the mouth of
the São Francisco River (P11, 10.2922023 S, 36.2451894 W) (Fig. 1).

2. Experimental
2.1. Reagents and solutions
All chemicals used were of analytical grade (Merck or SigmaAldrich) and prepared with ultrapure water with a specific resistivity
of 18.2 MΩ × cm, from a Master System MS2000 purification system
(Gehaka, Brazil).
The elements Hg, As, Cd, Pb, Cr, Cu, Zn, and Ni standard solutions
were prepared by serial dilutions of a 1000 mg L-1 stock solution. Diluted
nitric and hydrochloric acids were used to prepare the standard solu­
tions. In addition, a solution of Pd(NO3)2 at 5.0 μg L-1 was used as a
chemical modifier after dilution from the stock solution (5 mg L-1). The
reagents and solutions used in determinations by CV AFS and HG AFS
are described in Table S1 (Supplementary material).

2.5. Sampling procedures
The collection included forty seawater samples with three replicates
each, ten samples of crude oil, thirty-five fish samples of the Gerreidae
family - mojarra species, Diapterus rhombeus, and seventy bivalves
samples (massunin, Anomalocardia brasiliana). The crude oil, seawater,
fish, and bivalves samples were collected from the Alagoas and Sergipe
(Brazil) coasts (Fig. 1) between October 2019 and January 2020.
Seawater samples (250 mL) for total metal and metalloid analysis
were collected in polyethylene and glass containers, previously

2.2. Instrumentation
Microwave-assisted digestion of samples was performed using a
2

E.C. Soares et al.

Marine Pollution Bulletin 171 (2021) 112723

Fig. 1. Location of sampling sites in Alagoas and Sergipe States, Brazil. The internal graphics refer to the main ocean currents present in the sampling region.

decontaminated, containing 5 mL of 65% HNO3 (m/m) for sample
conservation. Before the analysis, the seawater samples were filtered
using a 0.45 μm cellulose acetate membrane. Sampling points consid­
ered locations where crude oil was found in the beach water or sand,
except for P05.
The crude oil samples were collected with stainless steel spatulas,
separated from the sand (when necessary), and placed in glass con­
tainers. Finally, seawater and crude oil samples were stored at 4 ◦ C, and,
to analyze physicochemical parameters, seawater samples were
collected and preserved in bottles (500 mL) at 8 ◦ C.
Fish livers were removed to determine the enzymatic analysis of
catalase (CAT). Each organ was homogenized at 1:10 (w/v) with phos­
phate buffer 0.1 M (pH 7.5). The organs were weighed and wrapped in
foil, frozen in liquid nitrogen (VOLTA 5), and stored in an ultra-freezer
at -80 ◦ C (Thermo Scientific).

Digestions were performed in triplicate (n = 3) for each sample,
including the analytical blank. For each crude oil sample, 250 mg was
introduced into the reaction vessels; later, 7.0 mL of 65% HNO3 (m/m)
and 1.0 mL of 30% H2O2 (m/m) were added at pre-digestion stage
lasting 1 h. The heating program conditions are described in Table S3,
according to the recommendations of Camera et al. (2015) and Mello
et al. (2012), with adaptations. The digested samples were diluted to 25
mL with ultrapure water, and residual acidity was determined by acidbase titration using NaOH standard solution (0.0901 M) and phenol­
phthalein 1% (m/v) as a visual indicator. The compatibility of the
acidity of the medium was carried out with HNO3 5 M.
2.8. Physico-chemical parameters of seawater analyses
The water quality parameters analyzed were sulfate (mg L-1), total
ammonia‑nitrogen (mg L-1), phosphate (mg L-1), dissolved oxygen (mg
L-1), salinity (PSU), pH, nitrite (mg L-1), total iron (mg L-1), aluminum
(mg L-1), total dissolved solids (TDS, μ cm-1), and turbidity (NTU). The
physicochemical parameters were determined using well-established
spectrophotometric assays, micro-Kjeldahl determination of nitrogen
(Ma and Zuazaga, 1942), multiparameter probe (YSI, USA), and HANNA
(HI9829).

2.6. Procedures for metal and metalloid determinations in seawater
samples
In GF AAS analysis, analytical curves were constructed (Cd, Pb, Cu,
and Zn: 1.0 - 10 μg L-1; and Cr and Ni: 0.1 - 10 μg L-1) using standard
solutions, and HNO3 was used for matrix compatibilization. The
experimental conditions for Hg (CV AFS) and As (HG AFS) de­
terminations are described in Table S1 (Supplementary material) while
the main figures of merit for determining metals and metalloid are
presented in Table S2.

2.9. Quantification analysis – Total oil and grease (TOG)
To measure and quantify the concentration of oil and grease in the
waters, described by environmental agencies such as Total Oil and
Grease (TOG), a Horiba® model OCMA-350 oil analyzer was used. This
technique represents a quick and direct approach commonly used in the
literature (Klemz et al., 2020). The measurements were based on the
absorption in the infrared in the range of 3.4 - 3.6 μm. For TOG
extraction from the PW sample, the poly-trichlorofluoroethylene solvent

2.7. Digestion of crude oil total metal and metalloid determinations
The digestion procedure of the crude oil samples was carried out in a
closed and pressurized microwave digestion system, equipped with 10
rotors (SK-10) and sensors for temperature and pressure control.
3

E.C. Soares et al.

Marine Pollution Bulletin 171 (2021) 112723

(S-316, Horiba®) was used in a 1:1 s solvent to sample ratio, according
to the Instruction manual HORIBA OCMA-350). For greater reliability,
the equipment was calibrated using B-heavy oil as a standard reference
having a concentration of 200 mg L-1. From these analyses, it was
possible to determine significant quantities of oils present in the waters,
reaching concentrations of 31.6 mg L-1 of contamination and correlating
with the perspective of CONAMA resolution no 393/2007.

metals and metalloid standards were purchased from the Specsol®
(Brazil) with traceability to the National Institute of Standards and
Technology (NIST, USA). Results from blanks demonstrated that the
analysis process was free of contamination, as well as the reagents and
procedures employed. The procedures applied to determine metals and
metalloids are free of matrix effect (oil and seawater) since the recovery
assays for the determined elements remained in the range of 80 to 120%
(Tables 1 and 2). All the samples analyzed (P01 to P10, metal and
metalloid determinations) were randomly selected as parallel samples
for repeatability checking. The main parameters from figures of merit
are described in Table S2 (relative standard deviations (RSD), LOD,
LOQ, among others).
The water analysis regarding the physicochemical parameters was
determined by applying spectrophotometric assays from Merck's Spec­
troquant® system, which supports the safe analysis with easy-to-use test
kits and certificates, ensuring that results are measured correctly. Ni­
trogen determination was based on the micro-Kjeldahl procedure
(method TKN). This wet oxidation procedure consists of complete ni­
trogen sample conversion to N-NH+
4 , determined spectrophotometry in
medium acid (after ammonia distillation). Multiparameter probe (YSI)
was used to check the instrument casing periodically looseness of con­
nections (Table S4). The calibration certificate is always required when
determining field measurement values. The multiparameter probe
HANNA (HI9829) was certificated, calibrated, and tested using stan­
dards and reference instruments, the accuracy of which is traceable to
the National Institute of Standards (NIST) in the USA or internationally
acceptable national physical standards. The procedures and calibration
system have been performed according to the manufacturer's in­
structions and the requirements of ISO 9001, respectively. All the sam­
ples analyzed were randomly selected as parallel samples for
repeatability checking.
For the analysis of Polycyclic Aromatic Hydrocarbons (PAH),
aliphatic hydrocarbons, and BTEX standards were purchased from
Sigma Aldrich (USA), and analytical curves were constructed. In each
solution of the analytical curve for PAH analysis, deuterated internal
standards were also present (naphthalene-d8, acenaphthene-d10,
phenanthrene-d10, chrysene-d12, and perylene-d12), each at a fixed
concentration of 30 ng mL-1. A blank in each batch of analyzed samples
(n = 10) was also analyzed for quality control.

2.10. Gas chromatography and mass spectrometry (GC–MS)
2.10.1. Organic crude oil general composition
The organic composition of general crude oil from 5 beaches in
Alagoas (P01, P02, P08, P09, P10) was chosen to compare along the
coast. In addition, an adaptation of the SARA methodology, responsible
for separating oil fractions, was performed to give the name to the
method (saturated, aromatic, resins, and asphaltenes). This fraction­
ation and the subsequent analysis of the SARA fractions are of great
importance in the characterization of oil. However, the currently used
method, ASTM D2007-93, uses the classical open column chromatog­
raphy procedure, making the analysis irreproducible and expensive.
2.10.2. Extraction and quantification of polycyclic aromatic hydrocarbons
(PAH), aliphatic hydrocarbons (HA), and BTEX
Seawater samples were processed for PAH and HA determinations
using liquid-liquid extraction, a procedure recommended by the United
States Environmental Protection Agency – EPA 3510C (US-EPA, 1996)
while BTEX (Benzene, Toluene, Ethylbenzene, m-p-xylene, o-xylene)
followed methodology developed and validated by Gebara et al. (2013).
In fish and oysters samples, the PAH was extracted by the MSPD method
(Matrix Solid-Phase Dispersion), according to the methodology
described by Pensado et al. (2005). The limit of quantification (LOQ) for
the determination of PAH and BTEX in seawater was 2.0 ng L-1. For fish
samples, the LOQ was 1.0 ng g-1 for PAH quantification, while in oysters
it was 0.2 ng g-1. Finally, for the quantification of BTEX in biological
samples, the LOQ was 0.1 ng kg-1.
Instrumental analysis, using gas chromatography coupled to mass
spectrometry (GC–MS: M.S. Agilent model 5975; G.C. Agilent model
7820 A), followed the conditions of the DB-5 ms MSD chromatographic
column (30 m, 0.25 mm of i.d., and 0.25 μm of the film), temperature
program 40 ◦ C for 3 min, 7 ◦ C min− 1 up to 305 ◦ C for 10 min, carrier gas
Helium at 1.0 mL min-1 and injection volume of 1.0 μL. The analyses
were performed in linear scanning (SCAN) and the (SIM) mode for ar­
omatic compounds using a range of 57 m/z.

3. Results and discussion
3.1. Crude oil and seawater: Metals, metalloids, and physicochemical
parameters

2.11. Liver extract preparation and catalase activity

The analysis of crude oil samples collected from different locations
with high deposition incidence (P01, P02, and P03, Fig. 1) was per­
formed to assess the profile of the mineral composition (Table 1). In this
previous evaluation, the elements Hg (94 - 134 μg kg-1), As (54 - 90 μg

Liver crude extracts were suspended in 20 mM potassium phosphate
buffer (pH 7.4, Triton X100 0.1% (m/v), and NaCl 150 mM, 1:20 dilu­
tion) and further homogenized in a Potter-Elvejhem glass homogenizer.
Catalase activity in the liver extract was analyzed spectrophotometri­
cally at 240 nm (wavelength of maximum absorption of hydrogen
peroxide) using H2O2 as a substrate (Moraes et al., 2007). Finally, oneUnit (U) of CAT activity was calculated in terms of μmol H2O2 consumed
min-1.

Table 1
Metals and metalloids (n = 3) in crude oil samples from the Alagoas coasts
(Brazil).
Sampling
points

2.12. Statistical analyses

P01

The data were submitted to the analysis of variance homogeneity
with the Shapiro-Wilk test. Parametric data submitted to analysis of
variance (ANOVA) followed by Tukey's test. Statistical analyses of
enzyme activity were performed using GrapPAHd Prism software
(version 6.0, GrapPAHd Software Inc., San Diego, CA, USA).

P02

2.13. Quality assurance and quality control (QA/QC)

Total concentrations (μg kg-1)
Hg

As

Cd

Pb

Cr

Cu

Zn

104 ±
11
134 ±
16

72
±9
90
±1
54
±8
91
±7

151 ±
13
230 ±
10
204 ±
18

149 ±
19
120 ±
11
336 ±
28
105 ±
8

48 ±
3
48 ±
3
44 ±
4
101
±3

28 ±
1
26 ±
2
39 ±
2
108
±6

175
±5
159
±5
235
±9
98 ±
4

P03

94 ± 7

Recovery
(%)a

88 ± 5

85 ± 4

a
Recovery assays (n = 3) were performed from the following concentrations
for each element: Hg and As (25 μg kg-1), while Cd, Pb, Cr, Cu, and Zn (50 μg kg1
).

QA and QC strictly monitored all analytical procedures. The selected
4

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Marine Pollution Bulletin 171 (2021) 112723

Table 2
Metals and metalloids (n = 3) in seawater from the Alagoas coasts (Brazil) in October 2019.
Sampling points
P01
P02
P03
P04
P05
P06
P07
P08
P09
P10
Recovery (%)a
Maximum limitb
a
b

Total concentrations (μg L-1)
Hg

As

Cd

Pb

Cr

Cu

Zn

Ni

0.303 ± 0.025
< 0.05
< 0.05
< 0.05
2.28 ± 0.024
0.117 ± 0.007
0.199 ± 0.001
0.254 ± 0.011
0.225 ± 0.004
0.388 ± 0.006
82 ± 7
0.2

0.72 ± 0.03
3.98 ± 0.14
0.46 ± 0.02
2.49 ± 0.07
0.52 ± 0.04
0.57 ± 0.05
0.21 ± 0.01
0.47 ± 0.06
0.49 ± 0.07
0.35 ± 0.02
86 ± 4
10

3.88 ± 0.10
5.34 ± 0.07
3.36 ± 0.06
2.78 ± 0.09
5.76 ± 0.11
4.75 ± 0.12
6.31 ± 0.14
2.19 ± 0.08
1.89 ± 0.05
5.52 ± 0.10
91 ± 6
5

7.92 ± 0.24
8.64 ± 0.51
10.23 ± 0.42
8.78 ± 0.45
10.69 ± 0.32
9.83 ± 0.23
8.17 ± 0.31
7.38 ± 0.47
7.24 ± 0.26
1.62 ± 0.08
109 ± 11
10

2.70 ± 0.10
2.94 ± 0.51
0.46 ± 0.20
4.73 ± 1.18
10.0 ± 2.0
< 0.10
< 0.10
< 0.10
0.16 ± 0.10
< 0.10
95 ± 8
50

4.46 ± 0.04
5.61 ± 0.13
3.91 ± 0.10
4.04 ± 0.09
4.20 ± 0.05
1.33 ± 0.07
5.20 ± 0.05
3.83 ± 0.06
4.32 ± 0.05
5.75 ± 0.12
112 ± 10
5

28.4 ± 1.9
67.7 ± 2.3
19.9 ± 5.3
24.9 ± 4.6
62.3 ± 2.5
2.00 ± 0.20
22.1 ± 3.8
29.4 ± 5.4
23.1 ± 4.6
9.92 ± 1.62
94 ± 7
90

< 0.10
< 0.10
< 0.10
< 0.10
< 0.10
< 0.10
< 0.10
< 0.10
< 0.10
< 0.10
106 ± 8
25

Recovery assays (n = 3) were performed from the following concentrations for each element: Hg and As (1 μg L-1), while Cd, Pb, Cr, Cu, Zn, and Ni (5 μg L-1).
Reference values according to CONAMA resolution no 357/2005 (Brazil) for saltwater.

kg-1), Cd (151 - 204 μg kg-1), Pb (120 - 336 μg kg-1), and Zn (159 - 235 μg
kg-1) had the highest concentrations in the crude oil samples, compared
to Cr (44 - 48 μg kg-1) and Cu (26 - 39 μg kg-1). However, the variation in
the concentration level between crude oil samples for each element can
be associated with the time of exposure and environmental degradation
of the analyzed fraction; still, samples P01 and P02 showed greater
similarity. However, all three samples had similar results for Cr. The
results obtained are consistent with a concentration in similar matrices
and fractions derived from petroleum (Camera et al., 2015; Hardaway
et al., 2004; Luz et al., 2013; Walkner et al., 2017).
The seawater samples (P01 - P10, Fig. 1) were analyzed to determine
the total contents of the following elements: Hg, As, Cd, Pb, Cr, Cu, Zn,
and Ni (Table 2). According to the maximum limit of concentration of
metals and metalloids in saltwater established by the National Envi­
ronment Council of Brazil (CONAMA) (Brazil, 2005), the elements As,
Cr, Zn, and Ni presented concentrations below the maximum reference
values in all samples. Nevertheless, for metals Hg (< 0.05–2.28 μg L-1),
Cd (1.89–6.31 μg L-1), Pb (1.62–10.69 μg L-1), and Cu (1.33–5.75 μg L-1),
there were sampling points above the maximum concentration limit
established by the national legislation. The evaluated region, referring
to the different sampling points on the coast of Alagoas, presented a
limitation due to the lack of previous results concerning the concen­
trations of these elements since there is no history of environmental
monitoring in this region. Thus, it is not yet possible to infer whether the
values above the legislation for the elements Hg, Cd, Pb, and Cu are
related to the environmental contamination of crude oil due to the lack
of information from the period before the oil spill. Finally, it is observed
that, in general, the levels of metals and metalloid determined in
seawater samples are lower than in the water samples impacted or used
in the crude oil treatment process (Afzal et al., 2019; Erakhrumen, 2015;
Hardi et al., 2019; Owamah, 2013).

After the period of the greatest oil spill on the coast of Alagoas, the
crude oil deposited on the beaches began to suffer mechanical degra­
dation due to environmental action (waves and the wind, for example).
A new collection was carried out in this period to analyze the water
samples (Table 3). As noted, Hg (0.099 - 0.885 μg L-1), As (0.51 - 45.46
μg L-1), Pb (1.47 - 14.32 μg L-1), and Cu (2.07 - 23.76 μg L-1) presented
systematic concentration values above what is allowed by the legisla­
tion. The Zn concentration (< 1.0 - 25.5 μg L-1) was slightly below that
previously found, indicating that the concentration of this element
changed a little during the period. For Cr, only the concentration of
point P09 (53.20 μg L-1) was above the value allowed by legislation.
Concentrations for Cd (2.79 - 5.11 μg L-1) remained below that allowed
by law, except for sample P10.
In comparison to other potentially toxic metals (Ag, Zn, Cd, for
example), Hg and As exhibit higher levels of bioaccumulation and
toxicity in marine phytoplankton, seaweeds, zooplankton, and benthic
animals, and especially in animals such as marine mammals, seabirds,
and sea turtles (Wang et al., 2020). These results may indicate that the
mechanical degradation of crude oil on the coast of Alagoas caused an
increase in the concentrations of some elements. However, a more
extended investigation period would be necessary to confirm this pos­
sibility. Oil contamination signatures can persist for many years after an
oil spill. However, in most cases, environmental recovery is relatively
quick, complete within 2 - 10 years (Kingston, 2002).
The variations in water quality parameters like ammonia (p =
0.087), dissolved oxygen (p = 0.840), pH (p = 0.612), TDS – Total dis­
solved solids (p = 0.113), salinity (p = 0.713), and aluminum (p =
0.075) between collection points, were not significant (p > 0.05). Only
sulfate samples presented a significant difference (p < 0.05) concerning
sample points. Maceió – Sete Coqueiros beach (P05) presented a higher
sulfate value, different from every other point. In contrast, São Miguel

Table 3
Metals and metalloids (n = 3) in seawater from the Alagoas coasts (Brazil) after the contamination (January 2020).
Sampling points
P01
P02
P03
P04
P05
P06
P07
P08
P09
P10
Maximum limita
a

Total concentrations (μg L-1)
Hg

As

Cd

Pb

Cr

Cu

Zn

Ni

0.756 ± 0.021
0.150 ± 0.007
0.101 ± 0.010
0.242 ± 0.040
0.998 ± 0.166
0.885 ± 0.188
0.154 ± 0.011
0.133 ± 0.013
0.099 ± 0.005
0.258 ± 0.024
0.2

45.46 ± 3.33
21.60 ± 1.08
16.05 ± 1.92
0.73 ± 0.03
1.22 ± 0.011
0.48 ± 0.03
0.51 ± 0.08
0.52 ± 0.08
0.91 ± 0.11
1.13 ± 0.14
10

2.79 ± 0.77
2.92 ± 0.51
4.21 ± 0.33
3.41 ± 0.88
4.54 ± 1.05
3.30 ± 0.90
4.81 ± 0.80
3.25 ± 0.32
3.31 ± 0.66
5.11 ± 0.38
5

10.95 ± 1.46
7.95 ± 0.86
8.75 ± 1.14
2.45 ± 0.32
14.32 ± 2.25
5.41 ± 0.71
4.05 ± 0.50
6.51 ± 0.81
2.35 ± 0.69
1.47 ± 0.36
10

3.81 ± 1.18
2.26 ± 2.50
1.48 ± 1.37
0.23 ± 0.16
0.29 ± 0.34
7.14 ± 1.81
23.33 ± 2.36
40.49 ± 5.38
53.20 ± 1.74
< 0.10
50

12.45 ± 1.55
23.76 ± 2.24
10.15 ± 1.91
2.07 ± 0.33
9.41 ± 2.57
6.21 ± 1.12
5.48 ± 1.25
4.31 ± 0.78
9.19 ± 2.25
7.11 ± 2.15
5

25.50 ± 3.12
1.55 ± 0.52
19.25 ± 2.81
< 1.0
15.52 ± 4.21
13.02 ± 1.46
9.25 ± 2.29
8.11 ± 2.13
< 1.0
11.75 ± 3.18
90

5.17 ± 1.31
12.53 ± 0.82
10.8 ± 1.64
7.51 ± 0.58
9.34 ± 0.92
2.53 ± 0.75
8.84 ± 1.05
6.32 ± 0.42
3.12 ± 0.28
4.83 ± 0.17
25

Reference values according to CONAMA resolution no 357/2005 (Brazil) for saltwater.
5

E.C. Soares et al.

Marine Pollution Bulletin 171 (2021) 112723

dos Milagres beach (P03) and Barra de São Miguel beach (P07), pre­
sented the lower values (Tukey test, p < 0.05). We can observe that
nitrite, phosphorus, and turbidity obtained significant differences (p <
0.05) concerning the months (Fig. 2), and in some cases, relative to the
collection areas.
Seawater physicochemical parameters in November 2019 presented
higher levels compared to data in October 2019 and January 2020.
Maragogi and Japaratinga beaches were the most affected, with a higher
amount of crude oil, while Ipioca and São Miguel dos Milagres beaches
showed the lowest impact. The results from Chen et al. (2017) indicated
that the indices of polycyclic aromatics hydrocarbon (PAH), ammonia,
turbidity, and nutrient concentrations increased but decreased during an
oil spill event due to the action of microorganisms. According to the
maximum limit in saltwater established by the World Health Organi­
zation (WHO) (2003) and CONAMA (Brazil, 2005), total phosphorus
and nitrite values are 0.062 and 0.07 mg L-1, respectively. In this study,
the two nutrients levels on the three months analyzed were: 0.60 ± 0.33
and 1.02 ± 0.56 mg L-1, therefore much above the established limits.

Table 4
Total quantification of oil and grease (TOG) in seawater samples.
Sampling point
P01
P02
P03
P04
P05
P06
P07
P08
P09
P10

Parameter
pH

TOG (mg L-1)

7.60
7.48
7.78
7.90
7.57
7.59
7.44
7.78
7.51
7.45

20.7
8.49
4.86
5.22
31.6
11.7
13.8
16.8
15.7
24.7

3.3. Gas chromatography–mass spectrometry (GC–MS)
3.3.1. Organic crude oil general composition
The oils from five different seawaters in Alagoas (P01, P02, P08, P09,
and P10) were analyzed by GC–MS (Fig. 3). The chromatographic pro­
files are quite similar (Fig. 3), and the main difference is regarding the
area and intensities of the compound. This difference may be associated
with physicochemical processes such as evaporation, emulsification,
dissolution, and biodegradation, caused by weathering due to the action
of winds, water, sun, and tides. Weathering can reduce the number of
different compounds classes present in the samples, changing their
physicochemical properties (Al-Hawash et al., 2018; Han et al., 2018).
This behavior was noticed since the naphthalenes and phenanthrenes in
the oil collected on the first day decreased by 82% and 58%, respec­
tively. Table 5 shows the main compounds classes identified, indicating
the percentage of the sampling point.
It is possible to observe that most samples' area predominates hy­
drocarbons, except for the sample P09, in which carboxylic acids were
predominant (Table 5). Ethers were identified in small amounts,
emphasizing the P02 sample since there was no presence of this func­
tional group. Finally, a relationship was observed between the hydro­
carbons and ethers content, with P08 and P09, which present higher
ether levels and lower concentrations of hydrocarbons (P01 and P02).
Since the sample compositions were similar, it was decided to
analyze the most complex sample (P10) using the GC–MS solution
software. It was possible to integrate 329 compounds, of which 83%
were considered contaminants. This contamination was mainly due to
silica derivatives, algae, shellfish, and plastics in the oil sample. Fortyone compounds were identified, 9 polychromatic hydrocarbons (naph­
thalene, dibenzothiophene, phenanthrene), 18 aliphatic hydrocarbons
(from dodecane to triacontane), 13 aromatic hydrocarbons (benzene,
vinyl-benzene), and toluene. Weathering may have been responsible for
the non-detection of o-xylene, m-xylene, and p-xylene compounds in the
samples. Based on these results, it was possible to identify some toxic,
persistent, and highly pollutant compounds (naphthalene,

3.2. Quantification analysis of total oil and grease (TOG)
From the data obtained (Table 4), variable contamination levels in
the collected water samples were observed. In this analysis, the direct
relationship between the pH and the level of contamination (TOG
values) was absent since the samples with similar pH were obtained at
different TOG concentrations. In general, TOG analyses present a me­
dian value of 15.34 ± 8.57 mg L-1.
Points P01, P05, P10 had the highest registered concentrations of
TOGs among the samples of water collected, exclusively pointing to P05.
According to the resolution, this point exceeded the average concen­
tration stipulated by World Health Organization (WHO) (2003) and
CONAMA resolution no 393/2007; according to the resolution, it deals
with wastewater in oil production in Brazil, with its disposal concen­
trations of 29.0 mg L-1. Although it is a simple monthly arithmetic
average value of oils and greases for production waters, it shows the
concentrations present in coastal waters as irregular. Therefore, it can
cause several environmental and human health problems since crude oil
is a complex mixture that contains various species of proven toxicity,
including volatile organic compounds (VOCs), PAH, hydrogen sulfide,
and potentially toxic metals. The severity of the exposure occurs by
ingestion, absorption through the intact skin, and inhalation. The toxi­
cological risks involved are severe, acute, and chronic, with particular
attention to toxic fractions of oil that can lead to death from poisoning,
primarily when associated with aromatic compounds (PENA, 2020).
Such concentrations must be considered, as we know that the samples
are not water from oil production fields.
Finally, regarding the pH analysis, the average pH value was 7.90,
and it is within limits established by CONAMA resolution 274/2001 for
saline waters (pH between 6.5 and 8.5).

Fig. 2. Total concentrations of (a) phosphorus, (b) nitrite, and (c) turbidity were evaluated in seawater from Alagoas State between October 2019 and January 2020.
6

E.C. Soares et al.

Marine Pollution Bulletin 171 (2021) 112723

Fig. 3. (a) Chromatographic profiles of the oils collected from the coasts of Alagoas (57 m/z). In (b) are show the respective expansions from 12 to 24 min.

dibenzothiophene, phenanthrene) in different Alagoas coast regions that
can cause serious environmental and health problems (Wu et al., 2021).
Thus, we are facing an environmental impact that can be related to these
oil spills. According to Farrington et al. (2020), in 1969, ~ 600 tons of
oil were spilled in Buzzards Bay, Massachusetts. Two years later, hy­
drocarbons derived from the oil persisted in the swamp and offshore
sediments. This fact suggests that the environmental impact caused by
these compounds can persist for several years.
Chromatographic analyses of the Sergipe oil were compared with
those identified in the oil spill on the Alagoas coast. It was possible to
identify mainly hydrocarbons from n-C10 to n-C20, compounds such as
eicosane (C20H42) and hexadecane (C16H34), among other hydrocarbons
in this range, were found in oils in Alagoas. The oils samples charac­
terized in Sergipe state have a range of hydrocarbons slightly similar to

Table 5
Percentage of the area referring to the compounds identified in the main
chemical classes.
Samples

Classes (%)

P01
P02
P08
P09
P10

Hydrocarbon

Carboxylic acid

Ether

86.8
94.9
66.9
43.8
73.9

10.7
5.13
25.1
46.4
22.0

2.49
N.I.
8.00
9.78
4.06

N.I. = Not identified.

Table 6
Quantification of polycyclic aromatic hydrocarbons (PAH) in samples of water, fish, and massunin from the Alagoas and Sergipe coasts (Brazil).
Sample

Naf

Aftil

Aft

Flu

Fen

Ant

Flut

Pir

B(a)
an

Cri

B(b)fl

B(k)fl

B(a)
pir

I[1,2,3cd]

B[ghi]
per

D(a,h)
a

ΣPAH

Seawater (ng L-1)
P18
49.92
P11
9.94
P12
15.38

7.95
n.d.
n.d.

10.57
n.d.
n.d.

12.55
n.d.
n.d.

18.33
n.d.
2.58

12.64
n.d.
n.d.

4.12
n.d.
n.d.

2.07
n.d.
n.d.

< LOQ
n.d.
n.d.

2.84
n.d.
n.d.

2.35
n.d.
n.d.

178.07
9.94
17.96

n.d.

n.d.

n.d.

7.48

2.24

n.d.

n.d.

n.d.

n.d.

n.d.

n.d.

38.47

P14
P15
P16
P17
P19
P20

5.58
32.51
n.d
38.96
26.01
29.31

n.d.
n.d.
n.d
13.37
n.d.
n.d.

n.d.
n.d.
n.d
15.79
n.d.
n.d.

n.d.
n.d.
n.d
15.47
n.d.
n.d.

3
9.18
n.d
20.52
2.61
3.15

n.d.
n.d.
n.d.
19.34
n.d.
n.d.

12.4
n.d.
n.d.
<
LOQ
n.d.
n.d.
n.d.
18.87
n.d.
n.d.

4.03
n.d.
n.d.

25.11

8.71
n.d.
n.d.
<
LOQ
n.d.
n.d.
n.d.
18.5
n.d.
n.d.

12.6
n.d.
n.d.

P13

16.99
n.d.
n.d.
<
LOQ
n.d.
n.d.
n.d
17.87
n.d.
n.d.

n.d.
n.d.
n.d.
16.28
n.d.
n.d.

n.d.
n.d.
n.d.
14.49
n.d.
n.d.

n.d.
n.d.
n.d.
13.34
n.d.
n.d.

n.d.
n.d.
n.d.
12.91
n.d.
n.d.

n.d.
n.d.
n.d.
12.64
n.d.
n.d.

n.d.
n.d.
n.d.
14.36
n.d.
n.d.

n.d.
n.d.
n.d.
12.78
n.d.
n.d.

8.58
41.69
n.d.
275.49
28.62
32.46

n.d.

0.98

n.d.

n.d.

n.d.

33.4

0.83

1.23

<
LOQ
6.54

n.d.

n.d.

n.d.

114.63

n.d.

n.d.

n.d.

28.62

n.d.
n.d.

n.d.
n.d.

n.d.
n.d.

<
LOQ
n.d.
n.d.

3.64

Massunin (ng L-1)
P09

8.28

4.4

1.05

7.22

7.04

0.95

1.26

2.21

n.d.

P10

13.99

8.56

n.d.

18.59

22.44

18.55

4.81

8.85

8.93

<
LOQ
1.28

-1

Fish (ng L )
P11

4.81

1.64

2.84

1.83

4.72

1.5

8.29

n.d.

1.23

1.76

n.d.

P12
P15

1.82
6.28

1.45
2.74

2.99
1.66

5.64
5.49

3.5
1.38

1.56
7.44

n.d.
4.35

n.d.
n.d.

n.d.
n.d.

n.d.
n.d.

P16

2.94

1.38

n.d.

3.74

1.51

2.52
2.71
<
LOQ

<
LOQ
n.d.
n.d.

3.29

1.41

n.d.

n.d.

n.d.

n.d.

n.d.

n.d.

n.d.

n.d.

14.28

P17

3.18

4.54

2.85

4.18

2.5

2.37

2.29

2.11

n.d.

n.d.

n.d.

<
LOQ

n.d.

n.d.

n.d.

n.d.

24.01

19.47
32.06

n.d.: not detected; < LOQ - less than the limit of quantification.
ΣPAH - total sum of 16 PAH analyzed.
Naf: Naphthalene; Aftil: Acenafitlene; Aft: Acenaftene; Flu: Fluorene; Fen: Phenanthrene; Ant: Anthracene; Flut: Fluoranthene; Pir: Pyrene; B (a) an: Benzo (a)
Anthracene; Cri: Chrysene; B (b) fl: Benzo (b) Fluoranthene; B (k) fl: Benzo (k) Fluoranthene; B (a) pir: Benzo (a) Pyrene; I [1,2,3-cd]: Indene (1,2,3-cd) pyrene; B [ghi]
per: Benzo (ghi) Perylene; D (a, h) a: Dibenzo (a, h) anthracene (a,h)anthracene.
7

E.C. Soares et al.

Marine Pollution Bulletin 171 (2021) 112723

contaminated); 100 to 1000 μg kg-1 (moderately contaminated) and >
1000 μg kg-1 (highly contaminated), suggesting that the samples of fish
and massunins analyzed were minimally contaminated, and P10, can be
considered moderately contaminated.
Another classification for fish and oysters analyzed may be based on
European standards for fish consumption (EC 1881/2006) (European
Community, 2011). This standard has already been updated (EC 835/
2011) to remove fresh fish from regulation (European Community,
2011). In the new regulation (EC835/2011), there is the inclusion of the
limit of 30 ng g-1 for the sum of four PAH (benzo(a)pyrene, benzo(a)
anthracene, benzo(b)fluoranthene, and chrysene). Therefore, consid­
ering the initial recommendation, the maximum allowed concentration
of BaP (benzo(a)pyrene) is 2.0 ng g-1 for fresh fish, crustaceans, and
mollusks; it is 5.0 ng g-1. In the samples analyzed, the presence of these
compounds was not detected.
It should be noted that these values are for quality control of fish sold
on the market under normal conditions, without accidents. This way,
considering the amount mentioned above for 4 PAH, only the P11
sample showed a concentration of 2.99 ng g-1, a value well below the
limit, so the 5 samples analyzed had the PAH level below the recom­
mended level. Thus, considering the samples of massunins, the com­
pound's presence was not detected in the sample P09. Only P10
presented a concentration of BaP (benzo(a)pyrene) of 6.54 ng g-1, a
value above the permitted in the legislation. Finally, the sum for 4 PAH,
none of the oyster samples analyzed, showed an amount above the limit
established by European law. However, despite the results showing little
accumulation of the analyzed PAH, we recommend continuous analysis
in the affected areas, considering that it was a recent episode. These
compounds have accumulative character regarding their concentrations
and may increase over time of exposure, increasing the risks of envi­
ronmental issues.

those found on the Alagoas coast, where the compounds were in the
range from n-C19 to n-C33, which are gammaceran (C30H52) and C33H58
isomers. However, there was no difference between the oils found in the
two states, although regional factors such as climate action on oil spilled
off the coast of both states and contamination caused by oil degradation
on beaches may influence the chemical profile.
3.3.2. Analyses of PAH in samples of seawater, fish, and massunins
(bivalves)
The PAH determination was made in the 10 seawater samples, 5 fish
muscle samples from different points of the Sergipe coast, and 2 mas­
sunins samples collected from the Alagoas (Table 6). The total PAH
concentrations (ΣPAH) per seawater sample collected varied from
<0.01 ng L-1 (P16) to 275.49 ng L-1 (P17). Naphthalene was the major
contributor to the total concentration of 16 PAH, except in sample P16,
where the presence of none of the 16 PAH analyzed was detected.
Phenanthrene was found in all samples except in sample P11. The
analysis revealed that 5 samples showed only two PAH, naphthalene and
phenanthrene. The total concentrations of PAH (Σ3-4 rings) ranged from
<0.01 ng L-1 to 138.89 ng L-1. Samples P18 and P17 showed the highest
total concentrations of PAH of 5 and 6 rings, with values of 15.41 and
80.52 ng L-1. In these regions, a higher proportion of oil was found on the
Sergipe coast. These 2 samples also showed the presence of all PAH
analyzed.
Total PAH concentrations (ΣPAH) per fish sample ranged from 14.28
(P16) to 32.06 ng g-1 (P15). Fluoranthene was the major contributor to
the total concentration of 16 PAH for samples P15 and P11, with 7.44
and 8.29 ng g-1, respectively. Fluorene was the major contributor in the
samples of P16 and P12, with values of 3.74 and 5.74 ng g-1, respec­
tively, while acenaftilene presented the highest contributor in the P17,
the value being 4.54 ng g-1.
Total PAH concentrations (ΣPAH) per massunins sample ranged from
29.88 (P09) to 114.63 ng g-1 (P10). For the P09 sample, the main con­
tributors to the total PAH concentration were naphthalene (8.28 ng g-1),
fluorine (7.22 ng g-1), and phenanthrene (7.04 ng g-1), while for the P10
sample, the major contributors were phenanthrene (6.03 ng g-1),
naphthalene (4.58 ng g-1), and pyrene (4.52 ng g-1). Phenanthrene was
the major contributor for sample P10 (22.44 ng g-1), followed by fluo­
rene (18.59 ng g-1).
BTEX concentrations were below the LOQ (0.1 μg L-1) in all seawater
samples analyzed. Therefore, none of the samples was above the
maximum limit (51 μg L-1) established by the National Environment
Council of Brazil (Brazil, 2005).
Cao et al. (2010) reported that PAH contamination in water could be
classified in four degrees: micro polluted (10 to 50 ng L-1), slightly
polluted (50 to 250 ng L-1), moderately polluted (250 to 1000 ng L-1),
and highly polluted (> 1000 ng L-1). In this work, the PAH concentra­
tions showed that most analyzed samples could be classified as micro
polluted. However, two samples, which showed all 16 PAH, according to
their total concentrations, can be classified as follows: P18 (ΣPAH =
178.07 ng L-1), slightly polluted, and P17 (ΣPAH = 275.49 ng L-1),
moderately polluted.
The CONAMA resolution no 357/2005, only determines the
maximum concentration, 0.018 μg L-1, of PAH benzo(a)anthracene,
benzo(a)pyrene, benzo(b)fluoranthene, benzo(k)fluoranthene, chrys­
ene, dibenzo(a, h)anthracene and indene(1,2,3-cd)pyrene. In the ana­
lyses performed, only benzo(a)anthracene, with a concentration of
18.87 ng L-1 (0.1857 μg L-1), was found above the established limit in
sample P17.
In Brazil, there is no legislation which establishes PAH levels in fish,
shellfish, and mollusks. The limits for fish used in this work were
established by the National Oceanic and Atmospheric Administration
(NOAA), in 1993, due to the disaster caused by the Exxon Valdez spill
(NOAA, 1993), in which the following concentrations of PAH, for
assessment of contamination in fish samples (wet weight), were set at
<10 μg kg-1 (free of contamination); 10 to 99 μg kg-1 (minimally

3.4. Catalase activity in the fish liver
Liver catalase in D. rhombeus showed a significant (p < 0.05)
reduction in samples from the Ipioca beach (P04) (6.50 ± 1.83 U CAT
mg-1) compared to Pontal do Peba beach (P10) (11.81 ± 2.37 U CAT mg1
), and Japaratinga beach (P02) with higher value (20.76 ± 5.15 U CAT
mg-1). Antioxidant enzyme activities are considered useful markers for
oxidative stress (Cheng et al., 2015). Several studies have shown dif­
ferences in liver catalase of fish exposed to pesticides, and this enzyme
has been considered a useful liver marker for damage by toxic sub­
stances (Clasen et al., 2018).
The present study showed changes in CAT activity in the liver of
D. rhombeus, followed by an increase in this enzyme, suggesting a role
for catalase in the defense mechanism to reduce oxidative stress. The
Japaratinga and Pontal do Peba beaches were the locations most
affected by petroleum in Alagoas and are where the individuals present a
higher level of catalase activity. The catalase activity changes under
polycyclic aromatic hydrocarbons and metals in water (Peters et al.,
1994).
4. Conclusion
In this work, it was possible to evaluate the impact caused by the oil
spill in the coastal region of Northeastern Brazil between the states of
Alagoas and Sergipe. In the analysis of the collected crude oil samples,
the elements Hg, As, Cd, Pb, and Zn presented the highest concentrations
compared to Cr and Cu. However, the variation in the concentration
level between crude oil samples for each element may be associated with
exposure and environmental degradation of the analyzed fraction. After
the oil spill on the Alagoas coast, the elements Hg, As, Pb, and Cu pre­
sented concentration values above those allowed by Brazilian legisla­
tion. For oil from five different seawaters in Alagoas, the
chromatographic profiles were quite similar, with the main difference
being in the area and intensities of the compound. This difference may
8

E.C. Soares et al.

Marine Pollution Bulletin 171 (2021) 112723

be associated with physicochemical processes such as evaporation,
emulsification, dissolution, and biodegradation caused by weathering
due to winds, water, sun, and tides. Total PAH concentrations per
seawater sample ranged from <0.01 to 275.49 ng L-1. Naphthalene was
the main contributor to the total concentration of 16 PAH. Phenanthrene
was found in all samples except in sample P11. Fluoranthene was the
main contributor to the total concentration of 16 PAH for two samples
(P15 and P11), while fluorene in samples P16 and P12 and phenan­
threne for P10 sample by fluorene. Concentrations of BTEX in all
seawater samples analyzed were below the limit established by
CONAMA.
Hepatic catalase in D. rhombeus showed a reduction in activity in
samples from Ipioca beach (P04) compared to samples from Pontal do
Peba beach (P10) and Japaratinga beach (P02). The coasts of Alagoas
and Sergipe (Brazil) do not have a history of environmental monitoring.
The oil-related disaster in the coastal region of northeastern Brazil has
impacted nature, the local economy, and the population's health. These
residues can remain for a long time in water, sand, and corals, impacting
nature, causing health-related problems for the residents of these re­
gions due to the continuous exposure of biota and harming the local
economy. Thus, it is necessary to monitor the coast of northeastern
Brazil to help local and federal governments take the necessary actions
to reduce environmental contamination.

60030.0000000747/2019).
Appendix A. Supplementary data
Supplementary data to this article can be found online at https://doi.
org/10.1016/j.marpolbul.2021.112723.
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CRediT authorship contribution statement
All authors have seen and approved the final version of the manu­
script submitted. E.C. Soares (Methodology, Formal analysis, Investi­
gation, Resources, Data curation, Writing – original draft, Writing –
review & editing, Visualization, Supervision), M.D. Bispo (Methodol­
ogy, Writing – original draft, Writing – review & editing), V.C. Vas­
concelos (Methodology, Writing – original draft), J.I. Soletti
(Methodology, Formal analysis, Investigation, Resources, Data curation,
Writing – original draft, Writing – review & editing, Visualization), S.H.
V. Carvalho (Methodology, Formal analysis, Investigation, Resources,
Data curation, Writing – original draft, Writing – review & editing,
Visualization), M.J. Oliveira (Methodology, Writing – original draft),
M.C. dos Santos (Methodology, Writing – original draft), E.S. Santos
Freire (Methodology, Writing – original draft), A.S.P. Nogueira
(Methodology, Writing – original draft), F.A.S. Cunha (Methodology,
Writing – original draft, Writing – review & editing), R.D.D. Sandes
(Methodology, Writing – original draft), R.A.R. dos Santos (Method­
ology, Writing – original draft), M.T.S.L. Neta (Methodology, Investi­
gation, Writing – original draft, Writing – review & editing), N. Narain
(Methodology, Investigation, Writing – original draft, Writing – review
& editing; English verification and corrections), C.A.B. Garcia (Meth­
odology, Investigation, Writing – original draft, Writing – review &
editing), S.S.L. da Costa (Methodology, Investigation, Writing – original
draft, Writing – review & editing, Visualization), J.C.C. Santos (Meth­
odology, Formal analysis, Investigation, Resources, Data curation,
Writing – original draft, Writing – review & editing, Visualization,
Supervision).
Declaration of competing interest
The authors declare that they have no known competing financial
interests or personal relationships that could have influenced the work
reported in this paper.
Acknowledgments
The authors thank Coordenação de Aperfeiçoamento de Pessoal de
Nível Superior - Brazil (CAPES) - Finance Code 001, Conselho Nacional
de Desenvolvimento Científico e Tecnológico (CNPq) for financial sup­
port and fellowships (JCCS, JIS, SHVC, NN, and CABG), and Fundação
de Amparo à Pesquisa do Estado de Alagoas (FAPEAL, process number:
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