Anal. Methods Environ. Chem. J. 4 (4) (2021) 49-63
Research Article, Issue 4
Analytical Methods in Environmental Chemistry Journal
Journal home page: www.amecj.com/ir
AMECJ
Adsorption of nitrate from aqueous solution with ZSM-5/Fe
nanosorbent based on optimizing of the isotherms conditions
before determination by UV-Vis Spectrophotometry
Mostafa Hassania, Mohsen Zeeba,*, Amirhossein Monzavib, Zahra Khodadadi a and Mohammad Reza Kalaeec
aDepartment of Applied Chemistry, Faculty of Science, Islamic Azad University, South Tehran Branch,Tehran, Iran
bDepartment of Polymer and Textile Engineering,Islamic Azad University,South Tehran Branch,Tehran, Iran
cDepartment of Polymer and Chemical Engineering,Islamic Azad University,South Tehran Branch,Tehran, Iran
ABSTRACT
The life-threatening nature of high nitrate concentrations in various
water resources motivated the present study to investigate the nitrate
adsorption by ZSM-5 nanozeolite and the feasibility of increasing
nitrate removal efciency using iron-doped ZSM-5 (ZSM-5/Fe)
nanoadsorbent. The optimal adsorption conditions were determined
rst by modeling the central composite design (CCD) using Design
Expert.7 software based on four inuential factors of contact time,
pH, adsorbent dosage and initial nitrate concentration. Then, the
isotherms of nitrate adsorption under optimized conditions were
investigated using the degree of t of experimental data with
Langmuir and Freundlich models for mathematical modelling of
the nitrate adsorption process. Based on the test design results, the
highest nitrate removal efciency (%93.1) was determined with UV-
Vis spectrophotometry at the contact time of 150 min, pH value of
3, the adsorbent dosage of 4 g L-1 and initial concentration of 40 mg
L-1. Analysis of adsorption isotherms also conrmed the greater t
of the experimental data with the Freundlich equation, so that the
correction factor of the Freundlich equation was greater than the
Langmuir equation, due to the heterogeneous distribution of active
sites for adsorption on the ZSM-5/Fe nanosorbent surface. Therefore,
it can be concluded that ZSM-5/Fe is a high efciency nanosorbent
for nitrate removal from water resources.
Keywords:
Adsorption,
ZSM-5/Fe nanozeolite,
Freundlich,
Langmuir,
UV-Vis Spectrophotometry
ARTICLE INFO:
Received 28 Jul 2021
Revised form 7 Oct 2021
Accepted 10 Nov 2021
Available online 30 Dec 2021
*Corresponding Author: Mohsen Zeeb
Email: zeeb.mohsen@gmail.com
https://doi.org/10.24200/amecj.v4.i04.154
------------------------
1. Introduction
Nitrate is known to be one of the most serious threats
to human health in the world, which enters the human
body through the penetration into groundwater and
surface water resources following the excessive use
of chemical fertilizers and uncontrolled discharge
without nitrication of municipal and industrial
wastewater in the environment [1-3]. This ion is
relatively non-toxic in nature, but its reduction to
nitrite by microorganisms can pose serious health
risks to humans, including blue baby syndrome,
also known as infant methemoglobinemia [4-7].
Accordingly, the EPA has recommended that the
maximum permissible concentration of nitrate is
10 mg L-1 in drinking water [8]. Hence, various
methods have been previously employed to
remove nitrate from aqueous solutions, such
as adsorption, ion exchange, reverse osmosis,
chemical and biological methods. In recent years,
adsorption methods have attracted much attention
50
in the removal of mineral ions, including uoride,
nitrate, bromate and perchlorate from water and
wastewater. Conventional chemical adsorbents
today include those based on carbon, clay,
zeolite, chitosan, bilayer compounds (hydroxide/
hydrotalcite), agricultural and industrial wastes,
and miscellaneous group [9- 19]. Many researchers
at present are focusing on zeolites as natural
adsorbents of environmental pollutants through
ion exchange or adsorption or both due to large
specic surface area, unique channel structure,
high-temperature hydrothermal stability and high
modiability to enhance adsorption efciency
[20-25]. Kamarehie et al. fabricated a natural
nanosorbent using granular activated carbon
from grape wood coated with iron nanoparticles
to remove nitrate from aqueous solutions.
The adsorption was then investigated by the
Freundlich isotherm model. Their results showed
that more than 99% of nitrate was removed from
the solution with this nanosorbent [26]. Mazarji
et al removed nitrate from the aqueous solution
using modied granular activated carbon. They
modied a commercial granular activated carbon
with sodium hydroxide to increase nitrate removal
efciency, followed by examining parameters such
as adsorbent dosage, solution pH, contact time
and initial nitrate concentration and temperature
in the nitrate adsorption process. They concluded
that the use of two-step treatment could be a
promising method in improving the efciency of
activated carbon to remove nitrate from water [27].
Hafeshjani et al. used sugarcane residues to remove
nitrate from aqueous solutions, and investigated
the physicochemical properties of the adsorbent
such as morphology, element composition, ion
exchange capacity and specic surface area.
They measured parameters such as pH, adsorbent
dosage, contact time, initial nitrate concentration
and temperature using different adsorption kinetic
models such as Freundlich, Langmuir and others.
Their results indicated that the maximum nitrate
removal efciency was achieved at pH value of
4.64, contact time of 60 minutes, adsorbent dosage
of 2 g L-1 and the best models were Langmuir
isotherm model and Pseudo-second-order
kinetic model [28]. Meftah et al modied natural
nanozeolite with 3-aminopropyl triethoxysilane
and investigated the optimal conditions for nitrate
adsorption capacity of modied zeolite in aqueous
solutions. Their results revealed that the best nitrate
removal capacity (80.12 %) was obtained at the
lowest pH value of 3 and nitrate concentration of
50 mg L-1 and adsorbent dosage of 4 g L-1 [29].
Alimohammadi et al optimized the nitrate removal
efciency using magnetic multi-walled carbon
nanotubes by response surface methodology
(RSM). They measured two parameters of pH
and D/C ratio with quadratic models using RSM,
and reported the maximum nitrate removal
efciency (%97.15) at pH = 4 and D/C = 40 mg per
mg L-1. It is worth mentioning that they used the
Freundlich adsorption isotherm to interpret the
adsorption dosage [30]. Azari et al. fabricated a
zeolite modied with hydrochloric acid to remove
nitrate from aqueous solutions, and investigated
the effects of pH, strings speed, contact time, and
optimum adsorbent dosage for this nanosorbent
under isotherm equations. Their results revealed
that the optimum conditions for pH, contact time
and adsorbent dosage for maximum nitrate removal
with this nanosorbent were 5, 180 min and 16 g L-1,
respectively, conrming higher removal efciency
compared to simple unmodied zeolite due to
the presence of larger sites [31]. Sepehri et al.
presented a natural zeolite-supported zero-valent
iron nanoparticles (ze-Nzvi adsorbent) using the
sodium borohydride reduction method with the aim
of removing nitrate from aqueous solution. Then,
they measured the parameters of contact time,
adsorbent dosage, initial nitrate concentration,
initial pH, the results of which showed that the
nitrate removal efciency was decreased with
increasing the initial solution pH and the adsorbent
dosage but elevated with increasing the initial
nitrate concentration [32]. Fataei et al investigated
the effects of iron and sand nanoparticles on nitrate
removal efciency on a laboratory scale. In this
research, they tested the effect of pH, sand and iron
particles parameters on nitrate removal efciency.
Anal. Methods Environ. Chem. J. 4 (4) (2021) 49-63
51
The mixture of iron and sand particles elevated
efciency and specic area. The results showed
that the efciency of iron nanoparticles was 65% in
the rst 20 min and 45% in the next times when the
pH of the reactions increased. Therefore, the results
conrmed that the initial solution pH was important
in the maximum nitrate removal efciency [33].
Bhatnagar et al. introduced nanoalumina to remove
nitrate from aqueous solution. In their study,
they examined the parameters of contact time,
pH, nitrate concentration with a pseudo-second-
order kinetic model. The highest nitrate removal
efciency was achieved at a concentration of 4 mg
g-1, a temperature of 23-27°C and a pH value of
4.4. Langmuir isotherm model was performed to
analyze the nitrate adsorption. The results of this
study veried the nano-alumina as a useful and
effective adsorbent for the nitrate removal from
aqueous solutions [34].
Given that metals such as Al, Sn, Zn, Fe and Ni are
effective agents for remediation of contaminated
groundwater, hence the present study tested iron
metal due to its availability, inexpensiveness, non-
toxicity, high efciency and rapid reaction in the
decomposition of contaminants to functionalize
ZSM-5 nanozeolite with the aim of determining
the optimal conditions and effective factors in
nitrate removal, including pH, contact time and
adsorbent dosage using RSM as well as evaluating
the adsorption isotherms.
2. Experimental
2.1. Material
The ZSM-5 nanocatalyst powder (from the Zeolites
family) was purchased from Sigma Aldrich with a
crystal size of 0.5 μm and a pore size of 5.5A0. Ferric
chloride (FeCl3), sodium hydrocside (NaOH),
Potassium nitrate(KNO3), Hydrocloric acid (HCl)
and %98 sulfuric acid (H2SO4) were also obtained
from Merck Germany.
2.2. Materials characterization
X-ray diffraction (XRD, STADI-P, the USA) and
energy-dispersive X-ray spectroscopy (EDX,
MIRA III SAMX, Czech Republic) was used to
investigate ferrous (Fe) metal in the nanocatalyst
structure functionalized with these metal. Brunauer-
Emmett-Teller (BET) surface area analysis (Belsorb
apparatus, Japan) was used to determine the SSA of
nanocatalyst particles. The concentration of nitrate
was determined by spectrophotometer UV-Vis
(Hach model Dr2800) was used.
2.3. Preparation of ZSM-5/Fe Nanozeolite
To Preparation the functionalized ZSM-5
nanocatalyst, rst 2.5 g of ZSM-5 nanozeolite
powder was placed in the furnace at a temperature
of 500°C for 4 hours and calcined. Then, 0.5 g of
ferric chloride (FeCl3) powder was dissolved in
distilled water twice for one hour, added to the
calcined ZSM-5 nanozeolite powder and mixed
for another 30 minutes, and ltered with a lter
paper. The resulting powder was rinsed three times
with distilled water and placed in an oven at a
temperature of 80°C for 2 hours. Next, the powder
was separated from the lter paper and re-calcined
at a temperature of 500°C for 4 hours. The method
of preparation above nanocatalyst is schematically
illustrated in Fig.1.
2.4. Preparation of solutions
To prepare a standard concentrated potassium
nitrate solution, 7 g of anhydrous KNO3 was dried at
100°C for an hour. After cooling, 1.805 g of KNO3
was dissolved in a volumetric ask and diluted to
250 mL, thus preparing a standard solution of 1000
mg L-1 or 1.0 mg mL-1. HCL and NaOH solutions
were prepared to set the pH values. Then, nitrate
solutions with concentrations of 20, 40, 60, 80,
100 and 120 mg per liter were prepared from the
standard solution of potassium nitrate 1000 mg L-1.
2.5. Procedure
In this research, the experimental design table was
rst provided using the effective variables of pH,
contact time and stirring speed in the intervals
dened to RSM and the central composite design
(CCD) by Design Expert.7 software. Then, the
value of each parameter was provided according
to the experimental design table and nally the
ZSM-5/Fe Nanosorbent for Nitrate Removal in liquid phase Mostafa Hassani et al
52
absorbance values or nitrate concentrations were
measured by UV-Vis spectrophotometry. The
results were analyzed by experimental design
software, and the optimal values of pH, contact
time and stirring speed were determined. In the
next step, the isotherms of nitrate adsorption under
optimized conditions were investigated using the
degree of t of experimental data with Langmuir
and Freundlich models for mathematical modeling
of the nitrate adsorption process.
2.6. Langmuir adsorption model
The mathematical model of this isotherm is shown
in Equation 1and 2 .
qe=qmaxbc/1+bCe (Eq. 1)
1/qe = 1/qmaxbce+1/qmax (Eq. 2)
Where, qmax and b stand for experimental constants,
qe for the amount of substance absorbed per unit
mass of adsorbent (mg g-1) and Ce for the equilibrium
adsorbate concentration in solution (mg L-1).
2.7. Freundlich adsorption model
Equation 3 shows the mathematical model of the
Freundlich isotherm. Where, qe and Ce are similar
to the Langmuir isotherm, and n and K stand for
Freundlich constants. The linear equation of the
Freundlich isotherm is as equation 4.
Anal. Methods Environ. Chem. J. 4 (4) (2021) 49-63
Fig.1. Schematic of ZSM-5/Fe nanosorbent fabrication method
Fig. 2. Energy-dispersive X-ray spectroscopy (EDX) analysis of the ZSM-5 and ZSM-5/Fe
53
qe=KfCe
1/n (Eq. 3)
logqe= logK+1/n logCe (Eq. 4)
3. Results and Discussion
3.1. Investigation of electrode surface
modication by EDX and XRD analysis
According to Figure 2 the presence of iron particles
in the nanosorbent structure is quite evident. The
XRD spectrum for the ZSM-5/Fe nanozeolite
conrms the presence of iron particles doped with
silicate particles(Fig.3).
3.2. BET characterization
By comparing the BET parameter (Fig.4 and Table
1), in each of the four BET analysis curves of the
nanozeolite, the highest SSA was related to the
catalyst functionalized with Fe metal (ZSM-5/Fe,
which was determined to be 408.41 m2 g-1).
ZSM-5/Fe Nanosorbent for Nitrate Removal in liquid phase Mostafa Hassani et al
Fig. 3. Investigation of nickel doping by X-ray diffraction (XRD) analysis
Fig.4. BET curves of prepared nanosorbent
54
3.3. Optimization and experimental design
In this research, the experimental design
using RSM in combination with CCD method
was performed to investigate the effects of
influential variables of pH (in the range of
2-8) (A), contact time (30-180 minutes) (B)
and adsorbent dosage (1-5 g L-1) (C) on nitrate
removal efficiency. Due to the extensive use of
research on (A), (B) and (C) parameters for the
nitrate removal process, these parameters were
selected as effective factors in optimizing nitrate
removal [35-40] [41s,42s, This referenceshowed
in supporting nformation page, SIP]. The RSM
method is a mathematical and statistical method
used for the analysis and empirical modeling of
problems where a given answer is influenced
by several variables and the RSM can be
calculated to determine the optimal conditions.
One advantage of this method is to reduce the
number of empirical tests performed to obtain
statistically valid results. In addition, the RSM
method can also analyze the interactions between
variables. Therefore, the use of this method in
optimization can report more comprehensive and
accurate data by performing the least number of
experiments [43s-44s, SIP]. Table 2 shows the
range of independent variables and design levels
of the experiments examined in this study. The
results of the complete design of the test and the
exact responses of the tests listed in Table 3.
According to the results of the data analysis in
Table 4, a quadratic function model can fit well
to the empirical results. The fit of this model was
evaluated by Analysis of Variance (ANOVA),
normal probability plot and residual analysis.
The quadratic function for nitrate removal
efficiency is expressed as follows:
%Removal Nitrate = 51.29-(11.26× A)+(4.76× B)-(3.64
× C)+(11.90 × D)+(5.41 × A × B)+(3.69× A × C)-(0.062 × A
×D)+(3.16× B × C)+5.76× B × D)- (2.77 ×C × D)+(0.52 ×
A2)+(0.89 × B2)+(3.23 × C2)- (1.75 × D2)
In the Table 4, the ANOVA analysis showed the
importance of each parameter in response to nitrate
removal by P and F values. The smaller the P value,
the higher its impact factor and its contribution to
the response variable. The P values less than 0.05
indicate that the model expressions are signicant.
The P values more than 0.1 indicate that the model
terms are insignicant. Accordingly, the seven
terms of (AC), (BD), and (C2) are signicant
parameters of the model and have the greatest
effect on nitrate removal efciency. The P values
of the other terms were greater than 0.05, which
means that their effect on the response model was
not statistically signicant.
Figure 5 shows the residual curve in terms of the
Anal. Methods Environ. Chem. J. 4 (4) (2021) 49-63
Table 1. The specic surface area of prepared nanozeolite
Unit
BETNanocatalystsRow
m2 g-1
m2 g-1
374.66
408.41
ZSM-5
ZSM-5/Fe
1
2
Table 2. Factors and levels for CCD study.
Level pH Tempture Time
α-
-1
+1
α+
22.4874
3
8
472.487
-4.31981
5
50
59.3198
-13.7046
1
72
86.7046
55
Table 4. Experimental design and actual results of nitrate removal efciency.
Sum of Mean F p-value
Source Squares df Square Value Prob > F
Block 374.47 1 374.47 ----- -----
Model 5147.23 14 367.66 20.32 0.0007
signicant
A-pH 717.07 1 717.07 39.64 0.0007
B-Time 128.00 1 128.00 7.08 0.0375
C-gr nitrate 181.09 1 181.09 10.01 0.0195
D-gr absorbent 801.60 1 801.60 44.31 0.0006
AB 97.08 1 97.08 5.37 0.0597
AC 109.00 1 109.00 6.03 0.0495
AD 0.013 1 0.013 7.024E-004 0.9797
BC 79.70 1 79.70 4.41 0.0806
BD 110.03 1 110.03 6.08 0.0487
CD 61.44 1 61.44 3.40 0.1149
A2 4.23 1 4.23 0.23 0.6457
B2 12.30 1 12.30 0.68 0.4411
C2 160.98 1 160.98 8.90 0.0245
D2 47.05 1 47.05 2.60 0.1579
Residual 108.53 6 18.09
Lack of Fit 87.66 2 43.83 8.40 0.0370
signicant
Pure Error 20.87 4 5.22
Cor Total 5630.23 21
ZSM-5/Fe Nanosorbent for Nitrate Removal in liquid phase Mostafa Hassani et al
Table 3. Experimental range and values of different variables studied.
Std Run Block pH Time nitrate absorbent %Removal
(min) (mgL-1) (grL-1) Nitrate(mgL-1)
5 1 Block 1 7 60 40 4 48.76
7 2 Block 1 3 150 100 4 81.23
11 3 Block 1 5 105 70 3 53.22
8 4 Block 1 3 60 40 2 71.66
12 5 Block 1 5 105 70 3 54.6
1 6 Block 1 7 150 100 2 47.13
10 7 Block 1 5 105 70 3 50.62
3 8 Block 1 7 60 100 4 38.62
9 9 Block 1 5 105 70 3 55.91
6 10 Block 1 3 60 100 2 57.84
2 11 Block 1 7 150 40 2 33.56
4 12 Block 1 3 150 40 4 93.51
14 13 Block 2 8 105 70 3 28.64
17 14 Block 2 5 105 20 3 63.28
20 15 Block 2 5 105 70 5 61.17
22 16 Block 2 5 105 70 3 53.76
21 17 Block 2 5 105 70 3 50.44
15 18 Block 2 5 30 70 3 40.62
18 19 Block 2 5 105 120 3 47.19
13 20 Block 2 2 105 70 3 66.51
19 21 Block 2 5 105 70 1 21.13
16 22 Block 2 5 180 70 3 56.62
56
predicted response for response of nitrate removal
efciency. This Figure shows that all empirical data
are uniformly distributed around the mean response
variable. This indicates that the proposed model is
sufcient and there has been no deviation from the
hypotheses made. As can be seen in Table 5, the
difference between the adjusted R2 and the predicted
R2 is less than 0.2 and the precision of the model is
19.613 (which is greater than 4), indicating the used
model is accurate.
Figure 6 shows a comparison between the actual
Anal. Methods Environ. Chem. J. 4 (4) (2021) 49-63
Table 5. Model equation statistical parameters for ANOVA model
for nitrate removal efciency.
Type of variables Results
Std. Dev. 4.25
R-Squared 0.9793
Mean 53.46
Adj R-Square 0.9312
C.V. % 7.96
Pred R-Squared -4.0544
PRESS 26564.71
Adeq Precision 19.613
Fig.5.The residual value curve in terms of the predicted response
57
response values obtained from the empirical
results and the predicted response values obtained
from the quadratic function model equation. It is
observed that the model describes the empirical
results and data fairly accurately, meaning that it
has been successful in comparing the correlations
between the three variables. In addition, there is
a sufcient correlation with the linear regression
coinciding with the R value of about 0.9793. In
addition, Figure 7 shows the three-dimensional
interaction curves of contact time, pH, adsorbent
dosage and initial nitrate concentration for nitrate
removal efciency. The highest nitrate removal
efciency was reported at the contact time of 150
min, pH value of 3, adsorbent dosage of 4 g L-1
and initial concentration of 40 mg L-1. Analysis of
the diagrams in Figure 7 revealed higher nitrate
removal efciency at lower pH values and longer
contact times.
3.4. Absorption isotherms and measurements
ZSM-5/Fe Nanosorbent for Nitrate Removal in liquid phase Mostafa Hassani et al
Desig n- Expert® Software
%Removal Ni trate
Color points by value of
%Removal Ni trate:
93.51
21.13
Actual
Predicted
Predicted vs. Actual
21.00
39.25
57.50
75.75
94.00
21.13 39.23 57.32 75.42 93.51
Fig. 6. Comparison between predicted and actual empirical values
of nitrate removal efciency
58 Anal. Methods Environ. Chem. J. 4 (4) (2021) 49-63
Desi gn- Expert® Software
%R emoval N i trate
93.51
21.13
X1 = A: pH
X2 = B: Ti me
Actual Factor s
C: g r nitr ate = 70
D: g r absor bent = 3
3
4
5
6
7
60
83
105
127
150
28
37.75
47.5
57.25
67
%Removal Nitrate
A: pH B: Time
Desig n- Expert® Software
%R emoval N i trate
93.51
21.13
X1 = A: pH
X2 = C : g r nitrate
Actual Factor s
B: Ti me = 105
D: g r absorbent = 3
3
4
5
6
7
40
55
70
85
100
28
39.5
51
62.5
74
%Removal Nitrate
A: pH C: gr nitrate
Desi gn- Expert® Software
%R emoval N i trate
93.51
21.13
X1 = B: Ti me
X2 = C : g r nitrate
Actual Factor s
A: pH = 5
D: g r absor bent = 3
60
83
105
127
150
40
55
70
85
100
40
46
52
58
64
%Removal Nitrate
B: Time C: gr nitrate
Desi gn- Expert® Software
%R emoval N i trate
93.51
21.13
X1 = A: pH
X2 = D : g r absor bent
Actual Factor s
B: Ti me = 105
C: g r nitr ate = 70
3
4
5
6
7
2
2
3
4
4
21
34.25
47.5
60.75
74
%Removal Nitrate
A: pH D: gr absorbent
Desig n- Expert® Software
%R emoval N i trate
93.51
21.13
X1 = B: Ti me
X2 = D : g r absor bent
Actual Factor s
A: pH = 5
C: g r nitr ate = 70
60
83
105
127
150
2
2
3
4
4
21
34
47
60
73
%Removal Nitrate
B: Time D: gr absorbent
Desi gn- Expert® Software
%R emoval N i trate
93.51
21.13
X1 = C : g r nitrate
X2 = D : g r absor bent
Actual Factor s
A: pH = 5
B: Ti me = 105
40
55
70
85
100
2
2
3
4
4
21
33.75
46.5
59.25
72
%Removal Nitrate
C: gr nitrate D: gr absorbent
Fig.7. 3D response surface method curves of nitrate removal efciency
A D
B E
C F
59
The nitrate adsorption efciency was measured
by dissolving 4 g of adsorbent in 250 mL of
nitrate solution at the initial concentrations of
20-120 mg at the contact time of 150 min at
laboratory temperature and the stirring speed of
50 rpm. Finally, the equilibrium concentration
of nitrate in solutions was determined by the
UV-Vis spectrophotometry at 220 and 275 nm.
The equilibrium nitrate adsorption capacity was
calculated by the equation 5. Where, qe is the
equilibrium adsorption capacity (mg g-1), Ce is
the equilibrium concentration of nitrate ion (mg
L-1), V is the solution volume (L) and M is the
adsorbent dosage (g).
qe=(C0-Ce )V/M (Eq.5)
3.4.1.Nitrate adsorption isotherm
Nitrate adsorption on ZSM-5/Fe adsorbent was
determined at laboratory temperature in terms
of equilibrium concentration, as shown by the
corresponding adsorption diagrams in Figures
8 and 9. Langmuir and Freundlich adsorption
models were employed to evaluate the adsorption
isotherm data. These models describe the
relationship between the amount of ion adsorption
desired on the adsorbent surface and its equilibrium
concentration in the liquid phase. The Langmuir
and Freundlich isotherms indicate mono-layer and
multi-layer adsorption on surfaces, respectively.
The Langmuir isotherm reveals active sites with
a limited number, while the Freundlich equation
represents heterogeneous surfaces [45s, SIP]. By
procedure, rst the experimental data were tted
with Langmuir and Freundlich equations and then
the constant parameters of the isotherm equations
were calculated. The Langmuir and Freundlich
models are explained by Equations 6 and 7,
respectively.
qe=(qm KLCe)/(1+KLCe ) (Eq. 6)
qe=K_FCe^(1/N) (Eq. 7)
Where, qm stands for the maximum adsorption
capacity (mg g-1), Ce for the equilibrium
concentration of nitrate ion (mg L-1), KL for the
constant of Langmuir isotherm (L mg-1), and KF
(mg g-1) and N are the constants of Freundlich
isotherm.
According to the results, the correction factor for
the Freundlich equation is larger than that for the
Langmuir equation, indicating experimental data
well-described with the Freundlich equation.
This fact is probably due to the heterogeneous
distribution of adsorption active sites on the
adsorbent surface, because the Freundlich model
assumes the adsorbent surface heterogeneity.
The values of parameter N in Freundlich model
are less than unit, which indicates an increase in
bond energy with surface density and shows the
optimal nitrate absorption conditions [46s-47s,
SIP]. The effective parameters of isotherm
models obtained from regression analysis of
experimental data are reported in Table 6.
4. Conclusions
ZSM-5/Fe Nanosorbent for Nitrate Removal in liquid phase Mostafa Hassani et al
Table 6. Parameters of Langmuir and Freundlich adsorption isotherms
for nitrate adsorption on ZSM-5/Fe adsorbent
R2 KL (L mg-1) qm (mg g-1) R2 N KF(mg g-1)
0.9881 0.290 8.072 0.9959 0.642 1.83
60 Anal. Methods Environ. Chem. J. 4 (4) (2021) 49-63
Fig. 8. Langmuir adsorption isotherm for nitrate adsorption on ZSM-5/Fe adsorbent
Fig. 9. Freundlich adsorption isotherm for nitrate adsorption on ZSM-5/Fe adsorbent
61
ZSM-5/Fe Nanosorbent for Nitrate Removal in liquid phase Mostafa Hassani et al
According to the results of the experimental
design table, the pH value, contact time and initial
nitrate concentration optimized for maximum
nitrate removal (%93.51) were reported as 3,
150 minutes and 40 mg L-1, respectively. In the
results of the adsorption isotherms, the correction
factor for the Freundlich equation is larger than
that for the Langmuir equation, which shows
that the experimental data are well described
by the Freundlich equation, probably due to the
heterogeneous distribution of active adsorption sites
on the adsorbent surface because the Freundlich
model assumes the adsorbent surface heterogeneity.
The values of parameter N of the Freundlich model
are less than unit, indicating the increase of bond
energy with surface density and also the optimal
conditions of nitrate adsorption. Therefore, it can
be concluded that ZSM-5/Fe is a high efciency
nanosorbent for nitrate removal from aqueous
solutions. The nitrate concentration in water samples
was determined by UV-Vis spectrophotometry
5. Acknowledgments
The authors would like to thank and appreciate .Hamid
Reza Sardari, Personnel of Chemistry Laboratory at
Islamic Azad University, South Tehran Branch, for
providing laboratory facilities and equipment.
6. References
[1] D.W. Cho, C.M. Chon, B.H. Jeon, Y.
Kim, M.A. Khan, H. Song, The role of
clay minerals in the reduction of nitrate
in groundwater by zero-valent iron,
Chemosphere, 81 (2010) 611-616. https://
doi.org/j.chemosphere.2010.08.005
[2] P. Mishra, R. Patel, Use of agricultural waste for
the removal of nitrate-nitrogen from aqueous
medium, J. Environ. Manage., 90 (2009) 519-22.
https://doi.org/10.1016/j.jenvman.2007.12.003
[3] M. Nikaeen, S. Naseri, Evalution of metallic
iron (Fe0) application to remediate nitrate
contaminated water, Water Wastewater, 17
(2007) 15-21. http://www.wwjournal.ir/
article_2222.html?lang=en
[4] S. Shadkam, F. Ludwig, P. van Oel, C. Kirmit,
P. Kabat, Impacts of climate change and water
resources development on the declining inow
into Iran’s Urmia Lake, J. Great Lakes Res.,
42 (2016) 942-952. https://doi.org/10.1016/j.
jglr.2016.07.033.
[5] Eslami A, Ghadimi M. Study of ve years nitrite
and nitrate content trends of Zanjan groundwater
resources using GIS from 2006 to 2010, J. Health
Field, 1 (2013) 30–6. http://journals.sbmu.ac.ir/jhf
[6] R. Fouladi Fard, M. J. M. Abadi, M. R. Hosseini,
Survey the nitrate concentration in drinking water
distribution systems of Kashan county, Iran, J.
Saf. Environ. Health Res., 1 (2016) 36–39. http://
doi.org/ 10.22053/jsehr.2016.33387
[7] M. Dehghani, E. Haidari, S. Shahsavani, N.
Shamsedini, Removal of nitrate in the aqueous
phase using granular ferric hydroxide, Jundishapur
J. Health Sci., 7(2015) e26419. http://doi.org/
10.5812/jjhs.7(2)2015.26419
[8] J. Rodríguez-Maroto, F. García-Herruzo, A.
García-Rubio, C. Gómez-Lahoz, C.Vereda-
Alonso, Kinetics of the chemical reduction
of nitrate by zero-valent iron, Chemosphere,
74 (2009) 804-809. http://doi.org/10.1016/
jchemosphere.2008.10.020
[9] I.F. Cheng, R. Muftikian, Q. Fernando, N. Korte,
Reduction of nitrate to ammonia by zero valent
iron, Chemosphere, 35 (1997) 2689–2695. http://
doi.org/10.1016/S0045-6535(97)00275-0
[10] Y.H. Huang, T.C. Zhang, Effects of low pH on
nitrate reduction by iron powder, Water Res.,
38 (2004) 2631–2642. https://doi.org/10.1016/j.
watres.2004.03.015
[11] Y.M. Chen, C.W. Li, S.S. Chen, Fluidized zero
valent iron bed reactor for nitrate removal,
Chemosphere, 59 (2005) 753–759. http://doi.
org/10.1016/chemosphere.2004.11.020
[12] Y.H. Liou, S.L. Lo, C.J. Lin, C.Y. Hu, W.H.
Kuan, S.C. Weng, Methods for accelerating
nitrate reduction using zerovalent iron at near-
neutral pH: effects of H2-reducing pretreatment
and copper deposition, Environ. Sci. Technol.,
39 (2005) 9643–9648. http://doi.org/10.1021/
es048038phttps://doi.org/
[13] S.C. Ahn, S.Y. Oh, D.K. Cha, Enhanced
62
reduction of nitrate by zero-valent iron at
elevated temperatures, J. Hazard. Mater.,
156 (2008) 17–22. http://doi.org/10.1016/j.
jhazmat.2007.11.04
[14] M. Dore, Ph. Simon, A. Deguin, J. Victot,
Removal of nitrate in drinking water by ion
exchange-impact on the chemical quality
of treated water, Water Res., 20 (1986)
221–232. http://dx.doi.org/10.1016/0043-
1354(86)90012-6
[15] S. Samatya, N. Kabay, U. Yuksel, M.
Arda, M. Yuksel, Removal of nitrate from
aqueous solution by nitrate selective ion
exchange resins, Reac. Funct. Polym., 66
(2006) 1206–1214. http://doi.org/10.1016/j.
reactfunctpolym.2006.03.009
[16] M. Chabani, A. Amrane, A. Bensmaili,
Kinetic modelling of the adsorption of
nitrates by ion exchange resin, Chem. Eng. J.,
125 (2006) 111–117. http://doi.org/10.1016/j.
cej.2006.08.014
[17] J.J. Schoeman, A. Steyn, Nitrate removal
with reverse osmosis in a rural area in South
Africa, Desalination, 155 (2003)15–26. http://
doi.org/10.1016/S0011-9164(03)00235-2
[18] M.I.M. Soares, Biological denitrication
of groundwater, Water Air Soil
Pollut.,123 (2000) 183–193. https://doi.
org/10.1023/A:1005242600186
[19] A. Bhatnagar, M. Sillanpää, A review of
emerging adsorbents for nitrate removal from
water, Chem. Eng. J., 168 (2011) 493–504.
http://doi.org/10.1016/j.cej.2011.01.103
[20] E.Y. Emori, F.H. Hirashima, C.H. Zandonai,
C.A. Ortiz-Bravo, N.R.C. Fernandes-
Machado, M.H.N. Olsen-Scaliante, Catalytic
cracking of soybean oil using ZSM5 zeolite.
Catal. Today, 279 (2017)168–176. http://doi.
org/10.1016/J.CATTOD.2016.05.052.
[21] Q. Zhang. G. Liu. L. Wang. X. Zhang, G.
Li, Controllable decomposition of methanol
for active fuel cooling technology, Energey
Fuels, 28 (2014) 4431–4439. http://doi.
org/10.1021/ef500668q
[22] W. Li, G. Li, C. Jin, X. Liu, J. Wang, One-step
synthesis of nanorod-aggregated functional
hierarchical iron-containing MFI zeolite
microspheres. J. Mater. Chem. A, 3 (2015) 14786–
14793. http://doi.org/10.1039/C5TA02662H
[23] T.J. Pinnavaia, Intercalated clay catalysts, Sci.,
220 (1983) 365–371. http://doi.org/10.1126/
science.220.4595.365
[24] K.G. Bhattacharyya, S.S. Gupta, Adsorption
of a few heavy metals on natural and modied
kaolinite and montmorillonite: a review, Adv.
Colloid Interface Sci.,140 (2008) 114–131. http://
doi.org/10.1016/j.cis.2007.12.008
[25] S. Wang, Y. Peng, Natural zeolites as effective
adsorbents in water and wastewater treatment,
Chem. Eng. J., 156 (2010) 11–24. https://doi.
org/10.1016/j.cej.2009.10.029
[26] B. Kamarehie, E. Aghaali, S.A. Musavi, S.Y.
Hashemi, A. Jafari, Nitrate removal from
aqueous solutions using granular activated
carbon modied with Iron nanoparticles, Int. J.
Eng. Transactions A, 31 (2018) 554-563. https://
doi.org/10.5829/ije.2018.31.04a.06
[27] M. Mazarji, B. Aminzadeh, M. Baghdadi, A.
Bhatnagar, Removal of nitrate from aqueous
solution using modied granular activated
carbon, J. Mol. Liq., 233 (2017) 139-148. https://
doi.org/10.1016/j.molliq.2017.03.004
[28] L. Divband Hafshejani, A. Hooshmand,
A.A. Naseri, A.S. Mohammadi, F. Abbasi, A.
Bhatnagar, Removal of nitrate from aqueous
solution by modied sugarcanebagasse biochar,
Ecol. Eng., 95 (2016) 101–111. http://dx.doi.
org/10.1016/j.ecoleng.2016.06.035
[29] T. Meftah, M. M. Zerafat, Nitrate removal
from drinking water using organo-silane
modied natural nano-zeolite, Int. J. Nanosci.
Nanotechnol.,12 (2016) 223-232. http://www.
ijnnonline.net/article_22931.html
[30] V. Alimohammadi, M. Sedighi, E. Jabbari,
Response surface modeling and optimization of
nitrate removal from aqueous solutions using
magnetic multi-walled carbon nanotubes, J.
Environ. Chem. Eng., 4 (2016) 4525–4535.
http://dx.doi.org/10.1016/j.jece.2016.10.017
[31] A. Azari, A.H. Mahvi, S. Naseri, R. Rezaei
Anal. Methods Environ. Chem. J. 4 (4) (2021) 49-63
63
Kalantary, M. Saberi, Nitrate removal
from aqueous solution by using nodied
clinoptilolite zeolite, research center for
environmental pollutants, Arch. Hyg. Sci., 3
(2014) 21-29. http://jhygiene.muq.ac.ir
[32] S. Sepehri, M. Heidarpour, J. Abedi, Nitrate
removal from aqueous solution using
natural zeolite-supported zero-valent Iron
nanoparticles, Soil Water Res., 9 (2014):
224–232. https://doi.org/10.17221/11/2014-
SWR
[33] E. Fataei, A. Seyyed Shari, H. Hasan
Pour Kourandeh, A.S. Shari, S.T.S.
Safavyan, Nitrate removal from drinking
water in laboratory-scale using iron and
sand nanoparticles, Int. J. Biosci.,10 (2013)
256-261. http://dx.doi.org/10.12692/
ijb/3.10.256-261
[34] A. Bhatnagar, E. Kumarb, M. Sillanpää,
Nitrate removal from water by nano-alumina:
characterization and sorption studies,
Chem. Eng. J., 163 (2010) 317–323. https//
doi/10.1016/j.cej.2010.08.008
[35] R.M. McKeown, C. Scully, T. Mahony,
G. Collins, V. O’Flaherty, Long-term
(1243 days), low-temperature (4-15C),
anaerobic biotreatment of acidied
wastewaters,bioprocess performance and
physiological characteristics, Water Res., 43
(2009) 1611-1620. http://doi.org/10.1016/j.
watres.2009.01.015
[36] C. Scully, G. Collins, V. O’Flaherty,
Anaerobic biological treatment of phenol
at 9.5-15 C in an expanded granular sludge
bed (EGSB)-based bioreactor, Water Res., 40
(2006) 3737-3744. http://doi.org/10.1016/j.
watres.2006.08.023
[37] J. Lopez, V.M. Monsalvo, D. Puyol,
A.F. Mohedano, J.J. Rodriguez, Low
temperature anaerobic treatment of low-
strength pentachlorophenol-bearing
wastewater. Bioresour.Technol.,140
(2013) 349-356. http://doi.org/10.1016/j.
biortech.2013.04.049
[38] W.M. Bandara, H. Satoh, M. Sasakawa, Y.
Nakahara, M. Takahashi, S. Okabe, Removal
of residual dissolved methane gas in an upow
anaerobic sludge blanket reactor treating
low-strength wastewater at low temperature
with degassing membrane, Water Res.,45
(2011) 3533-3540. http://doi.org/10.1016/j.
watres.2011.04.030
[39] A.J.M. Stams, C.M. Plugge, Electron transfer
in syntrophic communities of anaerobic
bacteria and archaea, Nat. Rev. Microbiol.,
7 (2009) 568-577. http://doi.org/10.038/
nrmicro2166
[40] T. Tian, S. Qiao, C. Yu, Y. Yang, J. Zhou, Low-
temperature anaerobic digestion enhanced
by bioelectrochemical systems equipped
with graphene/PPy and MnO2 nanoparticles/
PPy-modied electrodes, Chemosphere,218
(2019) 119-127. http://doi.org/10.1016/j.
chemosphere.2018.11.001
[SIP] SIP references (41-47s) have showed in
supporting information page, http://journal.
amecj.com/index.php/AMECJ-01
ZSM-5/Fe Nanosorbent for Nitrate Removal in liquid phase Mostafa Hassani et al
