Sorption of chromium from aqueous solutions using Fucus vesiculosus algae biosorbent

Abstract

The presence of heavy metals in wastewater is an environmental concern and the current treatment procedures are very expensive so it is necessary to find effective and inexpensive biosorbents. In this study, Fucus vesiculosus was used as a biosorbent for the biosorption of Cr(III) ions from the aqueous solutions. Biosorption parameters, such as pH, adsorbent dose, contact time, and initial concentrations of Cr(III) had the most impact on the sorption process. The required pH value for sorption was 5, the biosorbent dose was 4.0 g/L, the contact time was seen to occur after 90 min, and the Cr(III) removal decreased from 98.9 to 92%. The maximum biosorption capacity of chromium was 14.12 mg/g. FTIR analysis of Fucus vesiculosus biomass before the sorption process contains carboxyl, amino, hydroxyl, alkyne, and carbonyl groups, and according to the analysis after the sorption process, it was found that Cr(III) metal ions were incorporated within the sorbent during the interaction with (=C–H) active functional groups. The biosorption data were found to be perfectly suited by Langmuir equilibrium isotherm model. According to the results of this study, Fucus vesiculosus is an effective biosorbent for the removal of Cr(III) from aqueous solutions.

Full text

Asaad BMC Chemistry (2024) 18:145
https://doi.org/10.1186/s13065-024-01252-w
RESEARCH
Sorption ofchromium fromaqueous
solutions using Fucus vesiculosus algae
biosorbent
Amany A. Asaad1*
Abstract
The presence of heavy metals in wastewater is an environmental concern and the current treatment procedures are
very expensive so it is necessary to find effective and inexpensive biosorbents. In this study, Fucus vesiculosus was used
as a biosorbent for the biosorption of Cr(III) ions from the aqueous solutions. Biosorption parameters, such as pH,
adsorbent dose, contact time, and initial concentrations of Cr(III) had the most impact on the sorption process. The
required pH value for sorption was 5, the biosorbent dose was 4.0 g/L, the contact time was seen to occur after 90
min, and the Cr(III) removal decreased from 98.9 to 92%. The maximum biosorption capacity of chromium was 14.12
mg/g. FTIR analysis of Fucus vesiculosus biomass before the sorption process contains carboxyl, amino, hydroxyl,
alkyne, and carbonyl groups, and according to the analysis after the sorption process, it was found that Cr(III) metal
ions were incorporated within the sorbent during the interaction with (=C–H) active functional groups. The biosorp‑
tion data were found to be perfectly suited by Langmuir equilibrium isotherm model. According to the results of this
study, Fucus vesiculosus is an effective biosorbent for the removal of Cr(III) from aqueous solutions.
Keywords Fucus vesiclosus, Biosorption, Heavy metals, Chromium, Water treatment
Introduction
Heavy metals are toxic and carcinogenic, and cannot be
biodegraded. Heavy metals such as zinc, copper, nickel,
mercury, cadmium, lead, chromium, and arsenic have
a tendency to build up in living organisms and cause a
decrease in species diversity [1–3]. Metal contamina-
tion is a global environmental problem that persists and
should be addressed with sufficient measures to pre-
vent its exposure to the public. Heavy metals deposited
because of industrial processes should be removed before
they are received into the water since they are particu-
larly baleful to aquatic habitats. Among these metals,
chromium is one of the worthy environmental troubles
that continue to cause contamination of aqueous systems
and it is present in various oxidation states such as Cr(III)
and Cr(VI). Chromium is used in several industries
such as iron, steel, leather, metal coating, textile indus-
try, electric power plants, coil coating, electroplating,
film, photography, galvanometer, and automotive bat-
tery manufacturing industries [4–7]. e disposal of this
commonly used metal in the environment causes criti-
cal pollution [8]. Moreover, searching for an important
approach to remove such contaminants is an indispensa-
ble task for researchers. In this regard, various biological,
physical, and chemical methods have been adopted for
eliminating such heavy metals from industrial effluents
such as chemical precipitation, ion exchange, and mem-
brane separation techniques. It is preferable to use bio-
logical materials (sorbents) as an alternative method for
removing chromium from aqueous solutions because the
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BMC Chemistry
*Correspondence:
Amany A. Asaad
amany_mahgob@hotmail.com
1 Central Laboratory for Environmental Quality Monitoring, National Water
Research Center, El‑Qanater‑Qalubeya 13621, Egypt
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Page 2 of 11
Asaad BMC Chemistry (2024) 18:145
commonly used procedures for removing Cr(III) from
effluents include chemical precipitation, lime coagula-
tion, ion exchange, reverse osmosis and solvent extrac-
tion were apart from being economically expensive have
disadvantages like incomplete metal removal, high rea-
gent and energy requirements, and generation of toxic
sludge or other waste products that require disposal. Effi-
cient and environment friendly methods are thus needed
to be developed to reduce heavy metal content. In this
context, considerable attention has been focused in
recent years upon the field of biosorption for the removal
of heavy metal ions from aqueous effluents. Biosorp-
tion is a property of certain types of inactive, non-living
microbial biomass to bind and concentrate heavy metals
from even very dilute aqueous solution. Biomass exhibits
this property, acting just as chemical substance, as an ion
exchanger of biological origin [9]. Due to some benefits
over conventional methods, the use of sorption materials
in the removal and accumulation of heavy metals from
aqueous solutions has recently received a lot of attention.
Several adsorbents have been used to remove Cr(VI)
from water over the last few years, including commercial
inorganic materials such as clay, silica gel, zeolite, alu-
mina, and activated carbon, as well as bio products [10,
11] which may be alive or dead, and their effectiveness is
determined by their loading capacity, selectivity, affinity,
and rate of ion adsorption [12]. Lignocelluloses materials,
in general, are piquing researchers’ interest due to their
simple design, ease of handling, cheap operating costs,
ease of availability, eco-friendliness, efficiency, and pro-
duction of minimal toxic chemicals and biological sludge
[13]. Furthermore, these materials are abundant in poly
functional groups, which can contribute significantly to
the selective adsorption of Cr(VI) from aqueous solutions
[14]. Another notable property of biosorbents is their
ability to convert Cr(VI) to Cr(III) at lower pH values
and to totally remove Cr(VI) at moderate concentrations
[15]. e removal ability of the biosorbents is affected by
parameters such as pH, adsorbent dose, size, concentra-
tion, and contact time during the process.
Various studies indicate that non-living sorbents are
more effective for binding metals than biological sorbents
[7]. Marine algae are known to possess excellent mineral
binding capacity in different bio-selective procedures.
e cell membranes of brown algae are usually com-
posed of cellulose and algal acid, which is a straight-chain
polysaccharide with a carboxyl group (–COOH) primar-
ily responsible for binding to minerals, while sulfated
polysaccharide algae bind to ion salts.. Because of these
properties, algae (sorbents) are a good choice for adsorb-
ing metal ions from the aqueous solutions in a short
period and reducing heavy metal concentricity to the ppb
range [16]. e sorption mechanism of heavy metals on
biosorbents is thought to involve one or more of these:
ion exchange, biosorption, complexation, partial precipi-
tation formation, chelation, and electrostatic interaction.
However, the most significant way that heavy metal ions
are adsorbed by algae is through the ion exchange pro-
cess [17]. e presence of sulfate groups, as well as a large
number of carboxylic groups in brown marine algae, has
been attributed to the biosorption of trivalent metal cati-
ons [18]. e characterization of the biosorbent structure
and exploration of the reaction mechanism of sorbate
ions and biosorbents can be identified with the help of
FTIR (Fourier transform infrared) spectroscopy and SEM
(A scanning electron microscope coupled with an energy
dispersive spectrometer) is important to determine the
structure of the Fucus vesiculosus [19, 20]. e reports
on this kind of biosorbents and their utilization in elimi-
nating heavy metals are few [21].
is paper investigates the biosorption capacity of
Fucus vesiculosus (algae known by different common
names such as bladder wrack, black tang, rockweed, sea
grapes, sea oak, cut weed, and rock wrack) and the chro-
mium affinity toward it. To determine the best conditions
for biosorption, the effects of pH, equilibrium time, and
initial concentrations were examined. FTIR spectroscopy
is used to determine the specific functions involved in the
association of chromium with this type of algae.
Experimental methods
Preparation andanalysis ofbiomass
Sun-dried Fucus vesiculosus brown algae were brought
from a local market in Cairo and then dried and
grounded by an electrical grinder to conduct the biosorp-
tion procedures. FTIR spectroscopy was used to deter-
mine the effective groups that chromium can occupy
before and after the biosorption. e spectra ranges were
600–4000 cm−1 using “ermo Fisher Nicolet 50 spec-
troscopy” [22]. A scanning electron microscope (SEM) is
one of the common methods for imaging the microstruc-
ture and morphology of the materials [23].
Preparation ofmetal solution
e preparation of 20 mg/L Cr(III) solution was carried
out by diluting the working standard solution 1000 mg/L
(CrCl2 Merck) to different concentrations from 10 to 50
mg/L. e pH values of those prepared solutions were
adjusted using 1N NaOH and/or 1N HCl.
Biosorption experiment
Biosorption of chromium by (Fucus) was performed by
contacting 4g/L of Fucus with chromium concentration(20
mg/L) in a 1000 cm3 Pyrex conical flask intermittently for
90 min on the stirrer at 300 rpm. e mixture was filtered,
and the residual concentration of the filtrate was analyzed
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Page 3 of 11
Asaad BMC Chemistry (2024) 18:145
using Inductively coupled plasma optical emission spec-
trometry (ICP-OES) which is well suited for such analy-
sis because it is precise for lower concentrations [24]. e
adsorbed amount of chromium (mg/g) was calculated
using the following formula:
where the equilibrium biosorption capacity of Fucus for
chromium is denoted by qe (mg/g), the weight of the
biosorbent is symbolized by M(g), and the sorbate vol-
ume is symbolized by V(L). Co and Ce represent the metal
concentration before and after sorption (mg/L). Hence
the chromium uptake ratio can be evaluated by the next
equation:
Eects ofoperational parameters
e determination of the optimal adsorption parameters
such as pH of the biosorption solution, dose of biosorbent,
biosorption time, and concentration of the adsorbate solu-
tion were essential in knowing the biosorption efficiency
of the biosorbent under equilibrium condition [25]. e
optimal effective adsorption parameters determined when
equilibrium occurs can be achieved by preparing a series
of a series of chromium solutions with pH values from 2
to 7 at a concentration of 20 mg/L, a shaking speed of 300
rpm, and a doses of (0.5, 0.1, 0.2 and 0.3) g of the adsor-
bent (Fucus vesiculosus ) at 25 °C. e pH adjustment was
performed using 1 N NaOH and/or 1 N HCl solutions. To
establish the optimal contact time for biosorption stud-
ies, 0.2 g of Fucus vesiculosus powder was added to 50
mL of chromium solution at a concentration of 20 mg/L
for 10–120 min at 25°C. After the sorption process, the
samples were filtered off through 0.45μm membrane filter
paper. Also the effect of biosorbent dose was investigated
in the 0.05–0.3 g range. is was performed by adding a
specific dose of 50 mL of chromium solution (20 mg/L) and
shaking it for 90 min. After that, the sorption capacity of
Fucus vesiculosus was calculated using the aforementioned
equations. e impact of chromium initial concentration
on the biosorption capacity of the biosorbent was studied
by utilizing 0.2 g of Fucus powder and various concentra-
tions of chromium solution (10, 20, 30, 40, and 50 mg/L)
for 90 min at 25°C and pH 5.
Biosorption isotherm models
Biosorption isotherms were employed to determine
the biosorption behavior of the biosorbent and to pro-
vide a connection between the sorbate concentration
(1)
q
e=
(C
o−
C
e
)V
M,
(2)
R
%=
Co
−
Ce
Co
×
100.
Ce and the biosorption capacity qe per mass unit of the
biosorbent at equilibrium. Langmuir isotherm shows
that the biosorption occurs on a homogeneous mon-
olayer containing large biosorption sites [26]. e lin-
ear form of the Langmuir equation is presented as the
following:
where qe is the adsorption capacity at equilibrium, Ce
represents the equilibrium concentrations of chromium,
qm is the maximum adsorption capacity at equilibrium
and KL is Langmuir constant which indicates the adsorp-
tion energy. e basic characteristics of the Langmuir
isotherm can be described in terms of dimensionless fac-
tor RL, which is assumed by:
Co is the initial concentration of adsorbate and RL
explains the adsorption preference of this isotherm and
indicates whether the adsorption is irreversible if RL = 0,
linear if RL = 1, or unfavorable if RL > 1.
Freundlich isotherm postulates that biosorption
occurs at the available locations on heterogeneous sur-
faces [27]. e correlation factor R2 is used to evaluate
the applicability of an isothermal model. e known
logarithmic form of the Freundlich model is presented
in Eq.(5).
where qe and Ce are the capacity of biosorption (mg/g)
and the concentration of sorbate (mg/L) at equilibrium,
1/n is related to the intensity of biosorption, KF, and n are
constants.
Temkin model postulates the interactions of adsor-
bent-sorbate. It exhibits that the heat of an adsorbed
substance is reduced linearly than logarithmically
[28]. is model is characterized by a uniform binding
energy distribution up to maximum binding energy and
it is implemented by plotting qe against lnCe and then
the constants can be calculated from their slope and
intercept.
where qe denotes the quantity of adsorbed molecules that
reach a state of equilibrium (mg/g); Co is related to the
concentration of the metal (mg/L). β constant is linked to
the heat of biosorption, while R is the gas constant (8.314
J/mol K), and K represents the Temkin isotherm constant
(L/g) [29].
(3)
C
e
qe
=
1
qmKL
+
C
e
qm
,
(4)
R
L=
1
(
1+
bCo)
(5)
ln
qe=lnqK F+
1
n
lnCe
,
(6)
qe
=
βTlnKT
+
βTlnCe,
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Asaad BMC Chemistry (2024) 18:145
Biosorption kinetic models
Normally, the simulation of biosorption kinetics and evalu-
ation of the reaction rates involve the utilization of the
pseudo-first-order, pseudo-second-order, and Elovich
kinetic models. e pseudo-first-order kinetic model clari-
fies the correlation between the adsorbent sorption sites
that are occupied and the number of unoccupied sites
but e relation between the adsorption capacity of the
adsorbent and the time established by the pseudo-second-
order kinetic model [30]. Equations(7) and (8) provide the
mathematical expressions for the pseudo-first-order and
pseudo-second-order, respectively [31].
where qe is the amount of chromium adsorbed onto
adsorbent at equilibrium in (mg/g), qt is the amount
chromium adsorbed onto adsorbent at any time in
(mg/g), and K1 is the kinetics rate constant of the pseudo-
first-order model (min−1). K2 is the kinetics rate constant
of the pseudo-second-order model (g mg−1 min−1).
Elovich model is utilized to explain the kinetics of chemi-
cal biosorption of gas onto solid adsorbents, but it has
been proven to be effective in describing various types of
biosorption [32]. e following equation illustrates the
Elovich model:
(7)
log
(qe−qt)=logqe−

K1
2.303
,
(8)
t
qt
=
1
K2qe
2+
t
qe
,
(9)
q
t=
1
b
ln(ab)+
1
b
lnt
,
where qt (mg/g) is the adsorbate quantity at time t, a is a
chemisorption rate constant and b is a constant that rep-
resents the amplitude of surface coverage and they can
be calculated from the relation between their slope and
intercept by plotting qt versus lnt. a (mg/g min−1) repre-
sents the initial rate of sorption, and b (g/mg) represents
the desorption constant.
Results anddiscussion
SEM analysis
e surface morphology and initial formation of this spe-
cies of algae have been found to have rough surfaces with
pores of various sizes and shapes, increasing the surface
area for metal ions to interact as shown in Fig.1.
FT‑IR analysis
Fucus vesiculosus dried biomass before and after the
sorption of chromium was analyzed using Fourier
transform infrared (FTIR) spectroscopy to identify
how metal ions and surface biomass interact. Fucus
vesiculosus algae contain polysaccharides that include
many negative charges and functional groups that
can interact with chromium, and these functional
groups include carboxylate, hydroxyl, amino, and
nitro groups [33]. The spectra of adsorbents before
and after chromium uptake were measured from 600
to 4000 cm−1 wavenumber [34]. The spectra of Fucus
vesiculosus before the biosorption process showed
different absorption bands at 3280, 2922, 2318, 1259,
and1080 cm−1 were shifted to 3287, 2944, 1625, 1220,
and 1029 cm−1, respectively, after biosorption of chro-
mium. This result indicated chemical bonding among
binding sites on Fucus biomass and the chromium
[35]. The sorption bands of the sorbent at 1535 and
Fig. 1 Scanning electron micrograph of dried Fucus vesiculosus brown algae
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Page 5 of 11
Asaad BMC Chemistry (2024) 18:145
1416 cm−1 remain unchanged after the sorption pro-
cess while those at 1013 and 872 cm−1 disappeared
(Fig.2a, b). The vibrational bands in the pure biomass
of Fucus vesiculosus before chromium sorption at 3280
cm−1 and 2922 cm−1 are assigned to (C–H stretching)
alkyne and alkene groups [36]. The vibrational band at
2318cm−1 is related to carbon dioxide (O=C=O). The
band at 1535 cm−1 is due to N–O functional group
[37]. The sharp band at 1416 cm−1 is probably due to
the bending vibration of the hydroxyl group (O–H)
[38]. The vibrational band at 1259 cm−1 is restricted
to (C–O) stretching [39]. The band at 1080 cm−1
relates to the (C–N) stretching mode [40]. The bands
between the wavenumbers of 1800–750 cm−1 (finger-
print regions) reflected the biochemical compositions,
especially the moieties of carbohydrate, lipid, protein
secondary and polyphenols [41] The band at 860cm−1
is due to =C–H bending disappeared in the FTIR spec-
trum for the biomass sample of Fucus vesiculosus after
the chromium sorption process [42]. Figure2b dem-
onstrated that the chromium was incorporated within
the sorbent during the interaction with the active
functional groups (=C–H) [43].
Biosorption studies
e pH of the contact solution is an important parameter
controlling the biosorption process. e variation of pH
values changes the solution acidity or basicity and affects
the Fucus surface charge. e pH of the initial chromium
concentration (20 mg/L) varied from 2.0 to 9.0 at a con-
stant dose (4 g/L) and the stirring rate at 300 rpm for 90
min at room temperature (25 °C), as shown in Fig.3. e
sorption of chromium was raised by increasing pH ranges
from 2.0 to 5.0 where the capacity removal percentage of
chromium reached 96.15%. It may be due to the active
functional groups in the sorbent that facilitate biosorp-
tion by participating in metal ion binding [44]. is was
followed by a gradual decrease in the chromium removal
% at pH values greater than 5.0. e sorbent mass was
then varied (0.05–0.3 g/50mL) for an initial Cr(III) con-
centration of 20 mg/L at 25 °C and pH 5.0 for 90 min as
shown in Fig.4. e sorption of Cr(III) increased with
an increase in sorbent mass at an equilibrium time of
90 min from 46 to 96% and the equilibrium biosorption
capacity reached 29 mg/g. is is because the higher the
initial concentration of the metal ions, the higher the
chance of collisions with adsorption sites on the surface
of the adsorbent. Moreover, the driving force of mass
80
82
84
86
88
90
92
94
96
98
100
64010401440184022402640304034403840
Transmittance (a.u.)
Wave number (cm-1)
(a)
C-H Alkyne-
C-H Alkene-
C-N-
O-H-
N
-
O
-
C-O-
O=C=O-
=C-H-
80
82
84
86
88
90
92
94
96
98
100
64010401440184022402640304034403840
Transmittance (a.u.)
Wave number (cm-1)
(b)
N-O-
CH(Alkyne)-
C-O-
CH(Alkene)-
O-H-
O=C=O-
C-N-
Fig. 2 a, b FT‑IR spectrum of Fucus vesiculosus before and after Cr(III) sorption
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Page 6 of 11
Asaad BMC Chemistry (2024) 18:145
transfer is better, which is conducive to reduce the mass
transfer resistance and increase the biosorption capac-
ity [45]. Figure5 shows the removal of Cr(III) which was
accomplished within 90 min so there is no any additional
sorption and an equilibrium state is reached. e rate of
the biosorption process will increase significantly with
increasing contact time so that it reaches the equilibrium
point. Where, the longer the contact time, the greater the
adsorption capacity. Figure6 explains the effect of Cr(III)
concentrations on the sorption process under study in
which the higher uptake occurred at 90 min under equi-
librium [46]. It may be imputed to the consumption of
the available sites of the sorbent stable amount at equi-
librium. erefore, 90 min is the time required time for
the sorption process. e sorption of Cr(III) declined
from 10 mg/L to 50 mg/L and there was a significant ris-
ing in qe of Cr(III) at the Fucus surface when the Cr(III)
concentration ascents from 2.5 to 11.5 mg respectively.
0
10
20
30
40
50
60
70
80
90
100
012345678
Removal efficiency %
pH
Fig. 3 Effect of pH on Cr(III) sorption
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
020406080 100 120
Adsorption efficiency (%)
Tim(min)
Fig. 4 Effect of contact time on Cr(III) sorption
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Asaad BMC Chemistry (2024) 18:145
Hence the decrease in percentage removal from 98.9% to
92% may be attributed to the lack of other available sites
of the sorbent and there is a repulsion force between the
sorbate and bulk phase which reduces the uptake of the
chromium [47, 48].
Biosorption isotherms
e biosorption isotherms are commonly used to reflect
the performance of biosorbents in biosorption processes.
Langmuir isotherm is useful for monolayer adsorption,
the Freundlich isotherm shows adsorption on the het-
erogeneous surfaces of adsorbate-adsorbent systems and
the Temkin isotherm model assumes that the adsorption
energy of all molecules decreases linearly with increas-
ing adsorbent surface occupancy. In this research, the
biosorption isotherms were achieved for chromium solu-
tions of different initial concentrations from 10 to 50
mg/L, an algae dose of 4 g/L at 300 rpm for 90 min, and
0
10
20
30
40
50
60
70
80
90
100
0 0.05 0.1 0.15 0.2 0.25
qe (mg/g)
Adsorbent Mass (gm).
qe
Cr Removal %
Fig. 5 Effect of biosorbent mass on Cr(III) sorption
0
2
4
6
8
10
12
14
0102030405060
qe (mg/g)
Co (mg/l)
Fig. 6 Effect of initial concentration Cr(III) sorption
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Page 8 of 11
Asaad BMC Chemistry (2024) 18:145
at pH 5 [49–51]. e concentration of adsorbed chro-
mium was determined according to Eq.(3). Figure7a–c
represented the biosorption isotherms of Cr(III) by the
Fucus surface at pH 5 using the Langmuir, Freundlich,
and Temkin models, respectively. Isotherm parameters
are reported in Table 1. e Langmuir constant val-
ues (KL) show that strong interactions between metal
ions and apparent functional groups are involved in the
biosorption processes, regardless of the nature of metal
ions or biosorbent. e separation factor in Langmuir
isotherm (RL) was less than one and the correlation factor
(R2) was 99%, which showed that the biosorption process
was favorable [52]. e parameter 1/n in the Freundlich
model is less than unity indicating that all biosorption
processes are favourable. Moreover, the obtained values
have better performance in biosorption of chromium(III)
metal ions. ese observations are also supported by the
Temkin model parameters (Table 1), which show that
in the biosorption process, the retention of metal ions
is achieved through strong interactions, confirming the
removal efficiency trend.
Biosorption kinetics
e kinetics of the Cr(III) biosorption process was evalu-
ated using different kinetic models. Pseudo-first, second-
order kinetics, and Elovich models were applied as shown
in (Fig.8a–c) and the estimated kinetic parameters have
been illustrated in Table2. e appropriate kinetic model
of Cr(III) biosorption was governed by the linear cor-
relation coefficient (R2) values taken from model plots.
e value of R2 in the pseudo-second-order kinetic
model (0.991) was higher than the value of R2 in the
pseudo-first-order (0.933), hence it may be attributed
to chemically induced biosorption kinetics including
valence strength via ion exchange or through the elec-
tron interactions between adsorbed molecules on the
Fucus surface and the adsorbent [53, 54]. It has been
achieved that the high correlation coefficient indicate
y = 0.0708x + 0.0778
R² = 0.93
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.4
0246
Ce/qe
Ce
(a)
y = 0.4413x + 1.8138
R² = 0.9804
0
0.5
1
1.5
2
2.5
3
-3 -2 -1 012
ln qe
ln Ce
(b)
y = 0.3605x -2.5229
R² = 0.8944
-2.5
-2
-1.5
-1
-0.5
0
0.5
1
1.5
2
0.0 10.0 20.0
qe
ln Ce
(c)
Fig. 7 a–c Langmuir, Freundlich and Temkin Isotherms for the sorption of Cr(III) on the Fucus vesiculosus
Table 1 Fitting parameters of isotherm models for the
biosorption of Cr(III) on the Fucus vesiculosus biosorbent
Models Parameters Values
qmax 17.06 mg/g
KL0.52 L/mg
Langmuir RL0.16
R20.99
Kf5.39 mg/g
Freundlich n 1.7
R20.98
βT0.27
Temkin KT1.97 L/g
R20.97
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Page 9 of 11
Asaad BMC Chemistry (2024) 18:145
a good fit of experimental data to the pseudo-second-
order model [55]. Also, this indicated that the rate con-
stant (K2) of Cr(III) was 0.062 g/mg min, which reveals
that the pseudo-second-order kinetic model is based
on the assumption that the rate-limiting step is chemi-
cal sorption or chemisorption and predicts the behavior
over the whole range of adsorption. In this condition, the
adsorption rate is dependent on adsorption capacity not
on concentration of adsorbate [56]. Moreover, in order
to comprehend the characteristics of chemisorption, the
Elovich model has been utilized. e amounts of (1/b)
and (1/b) ln (ab) have been evaluated by the slope and
intercept of the linear correlation [57, 58]. e value of
(1/b) represents the number of available sites required for
biosorption, while the biosorption quantity is indicated
by the value of (1/b) ln (ab). Elovich model data has been
demonstrated in (Table2).
Conclusions
is study presents a new approach using Fucus vesicu-
losus algae to remove chromium from aqueous solutions
in a safe and environmental manner. e maximum chro-
mium removal capacity was 96.15% at pH 5, and dose
(4.0 g/L) in 90 min. e biosorption models described
the biosorption equilibrium of chromium with Fucus
vesiculosus, the maximum biosorption capacity of chro-
mium was 14.12 mg/g and the isothermal constants were
determined. e obtained results confirmed that the
biosorption equilibrium data are excellently integrated
into the Langmuir model and also the pseudo-second-
order equation gave an excellent correlation between the
experimental and the calculated data in the biosorption
of Cr(III). Finally, it was concluded that Fucus vesiculosus
is an effective and environmentally friendly biosorbent
and a suitable candidate for the removal of Cr(III) from
aqueous solutions.
Acknowledgements
The author would like to thank Professor Mohsen Mahmoud Yousry (Director
of Central Laboratory for Environmental Quality Monitoring, National Water
Research Center, El‑Qanater El‑Khiria, Egypt) for his valuable supports during
y = -0.0195x + 1.4377
R² = 0.9332
-1
-0.5
0
0.5
1
1.5
2
050100
log (qe-qt)
t (min.)
(a)
y = 0.2058x + 0.686
R² = 0.9918
0
2
4
6
8
10
12
14
16
18
20
050 100
t/qt
t (min.)
(b)
y = 4.317x + 0.3098
R² = 0.9925
0
5
10
15
20
25
0510
qt(mg/g)
ln t
(c)
Fig. 8 a–c Pseudo first order, pseudo second order and Elovich kinetic models for the sorption of Cr(III) on the Fucus vesiculosus biosorbent
Table 2 Kinetic parameters for the biosorption of Cr(III) on the
Fucus vesiculosus biosorbent
Models Parameters Values
qe20.30 mg/g
Pseudo‑Frist‑Order K10.0449 min−1
R20.93
qe23.62 mg/g
Pseudo‑Second‑Order K20.062 g/mg. min
R20.99
qt14.80 mg/g
Elovich a 4.63 mg/g min−1
b 0.23 g/mg
R20.99
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Page 10 of 11
Asaad BMC Chemistry (2024) 18:145
the experimental work. Also the author would like to thank Dr Doaa M.
Hammad (Assistant Professor in the biological and Environmental Indicators
Department in Central Laboratory for Environmental Quality Monitoring) for
her advice and guidance.
Author contributions
A.A. wrote the main manuscript text and prepared all figures, data collection,
analysis, and interpretation of results, and reviewed the manuscript.
Funding
Open access funding provided by The Science, Technology & Innovation
Funding Authority (STDF) in cooperation with The Egyptian Knowledge Bank
(EKB). The author confirms no funding is involved.
Data availability
The datasets generated during and/or analyzed during the current study are
available from the corresponding author on reasonable request.
Declarations
Ethics approval and consent to participate
Not applicable.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
Received: 9 September 2023 Accepted: 19 July 2024
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