Article

Pre‐deposited dynamic membrane adsorber formed of microscale conventional iron oxide‐based adsorbents to remove arsenic from water: Application study and mathematical modeling

Abstract

BACKGROUND: This study reports the development of a dynamic membrane (DM) adsorber by the pre‐depositing powdered‐sized fraction of iron oxide‐based adsorptive material on the surface of a microfiltration(MF) membrane. The aim is to use the developed DM adsorber for arsenate (As(V)) remediation from water by a combined mechanism of adsorptive and membrane filtration. The two applied iron oxide‐based adsorptive materials are micro‐sized granular ferric hydroxide and micro‐sized tetravalent manganese feroxyhyte, and are available at an affordable price. RESULTS: The results show that As(V) removal efficiency strongly depends on the physicochemical properties of the depositing material such as specific surface area, isoelectric point, and particle size of the pre‐depositing material. The experimentally determined As(V) removal rates were mathematically modeled using a homogeneous surface diffusion model (HSDM) that incorporates the equilibrium parameters and mass transport coefficients of the adsorption process. The simulations showed that the mathematical model could describe the As(V) removal rates accurately over a broad range of operating conditions. The results further showed that the longer filtration times with very low normalized As(V) permeate concentration (C/Cf = 0.1 for example) can be prolonged by operating DM adsorber at lowermost membrane water flux of 31 L/(m2·h) and large amount of pre‐depositing material on MF membrane surface (Ma= 14 mg/cm2). CONCLUSION: The results presented in this study confirm that use of these inexpensive materials (side‐product of granular iron‐oxide‐based adsorbents) in treating As(V) polluted water would enhance the sustainability of the industrial production process of conventional granular adsorbents by utilizing the wastes created during the process of adsorbent production.
Research Article
Received: 18 December 2020 Revised: 4 March 2021 Accepted article published: 5 March 2021 Published online in Wiley Online Library:
(wileyonlinelibrary.com) DOI 10.1002/jctb.6728
Pre-deposited dynamic membrane adsorber
formed of microscale conventional iron oxide-
based adsorbents to remove arsenic from
water: application study and mathematical
modeling
Muhammad Usman,a
*
Aida Idrissi Belkasmi,aIoannis A Kastoyiannisband
Mathias Ernsta
Abstract
BACKGROUND: This study reports the development of a dynamic membrane (DM) adsorber by pre-depositing powdered-sized-
fraction of iron oxide-based adsorptive material on the surface of a microltration(MF) membrane. The aim is to use the devel-
oped DM adsorber for arsenate (As(V)) remediation from water by a combined mechanism of adsorptive and membrane
ltration. The two applied iron oxide-based adsorptive materials are micro-sized granular ferric hydroxide and micro-sized tet-
ravalent manganese feroxyhyte, and are available at affordable price.
RESULTS: The results show that As(V) removal efciency strongly depends on the physicochemical properties of the depositing
material such as specic surface area, isoelectric point and particle size of the pre-depositing material. The experimentally
determined As(V) removal rates were mathematically modeled using a homogeneous surface diffusion model, which incorpo-
rates the equilibrium parameters and mass transport coefcients of the adsorption process. The simulations showed that the
mathematical model could describe the As(V) removal rates accurately over a broad range of operating conditions. The results
further showed that the longer ltration times with very low normalized As(V) permeate concentration (C/C
f
=0.1, for example)
can be prolonged by operating the DM adsorber at the lowermost membrane water ux of 31 L m
2
h
1
and a large amount of
pre-depositing material on the MF membrane surface (M
a
=14 mg cm
2
).
CONCLUSION: The results presented in this study conrm that use of these inexpensive materials (side-product of granular iron
oxide-based adsorbents) in treating As(V)-polluted water would enhance the sustainability of the industrial production process
of conventional granular adsorbents by utilizing the wastes created during the process of adsorbent production.
© 2021 The Authors. Journal of Chemical Technology and Biotechnology published by John Wiley & Sons Ltd on behalf of Society
of Chemical Industry (SCI).
Supporting information may be found in the online version of this article.
Keywords: arsenate; adsorption; granular ferric hydroxide; membrane adsorber; homogenous surface diffusion model; water treatment
INTRODUCTION
Dynamic membranes (DMs) were rst narrated in 1965 by a
research group from the Oak Ridge National Laboratory.
1
Unlike
a membrane manufactured through a casting membrane solution
or melting spinning technique, a DM lter, which is referred to as a
secondary membrane, can be developed in situ. The DM lter
builds up as a layer of particles such as metal oxides, soil-based
compounds and powdered activated carbon (PAC) deposited
via permeation drag onto surfaces of meshes, nylon, polyethersul-
fone (PES) and ceramic-based microltration (MF) and ultraltra-
tion (UF).
24
This suggests that a DM lter technology
predominantly involves two layers, namely the primary
membrane as a supporting layer and the deposited cake layer of
microparticles as the secondary membrane. The primary mem-
brane offers the foundation to the deposited layer, while the
*Correspondence to: M Usman, Institute for Water Resources and Water Supply,
Hamburg University of Technology, Am Schwarzenberg-Campus 3, 20173
Hamburg, Germany. E-mail: muhammad.usman@tuhh.de
aInstitute for Water Resources and Water Supply, Hamburg University of Tech-
nology, Hamburg, Germany
bLaboratory of Chemical and Environmental Technology, Department of
Chemistry, Aristotle University of Thessaloniki, Thessaloniki, Greece
© 2021 The Authors. Journal of Chemical Technology and Biotechnology published by John Wiley & Sons Ltd on behalf of Society of Chemical
Industry (SCI).
This is an open access article under the terms of the Creative Commons Attribution-NonCommercial License, which permits use, distribution and
reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.
1
deposited layer, consisting of nano- and microparticles, acts as
the dominant functional part for decontamination of water.
5
The
deposited layer of particles then determines the removal rates
and efciency of the DM lter towards a target trace pollutant,
2,6
when the primary membrane does not have a rejection capacity
towards the specic target pollutant.
2
For example, dissolved
inorganic trace contaminants such as arsenic and antimony are
not retained by a typical MF or UF membrane.
7
Modication of
such a membrane, i.e. by iron oxides, can remove the trace con-
taminant by adsorption onto the secondary membrane, while
the primary membrane achieves high overall water quality by l-
tering out suspended particles.
8
The DM lter with diverse separating functions can be devel-
oped by opting suitable pre-depositing materials. The DM lter
made on loosened support materials such as MF and mesh has
an advantage over traditional membranes of operating under
gravity-driven mode.
5
A driving force by means of a 10 cm water
head was sufcient during DM ltration of secondary wastewater
efuent to achieve 200 L m
2
h
1
when a nylon mesh with an cor-
responding aperture of 25 μm was applied as a DM support mate-
rial.
9
Furthermore, once the DM lter is fouled or exhausted, the
deposited cake layer can be displaced by backwashing either with
water or air,
10
and a new cake layer of depositing material can be
readily redeposited. The use of water has proved to be an effec-
tive cleaning approach for the exhausted DM lter. More than
90% of the primary membrane permeability could be restored
after four ltration cycles.
11,12
DM lters are categorized into two main types: self-forming DM
lters and pre-deposited DM lters. In the rst case, the feed con-
stituents are those which form the DM lter, whereas the pre-
deposited DM lter are developed as a result of deposition of par-
ticles other than the feed solution at the top surface of the pri-
mary membrane prior to the inow of the polluted water.
2,4,5
The pre-deposited DM lter offers the exibility of selecting
appropriate and affordable materials which might be used to
develop the membrane lter. Irrespective of DM lter category,
the DM either: (a) expands the capability of the primary mem-
brane to remove contaminants that otherwise would not be
removed; (b) enhances the overall performance of the conven-
tional primary membrane; or (c) conserves the primary membrane
from fouling.
4
According to the formation mechanism, DM lters can be classi-
ed into two classes. Class I DM lters are those whereby the pore
size of the primary membrane is really small, to completely retain
the DM lter-forming material. In this case, the dominant mecha-
nism that governs DM formation is the concentration polariza-
tion.
13
When the primary membrane's pore diameter is
signicantly larger than the size of the particles (e.g. dust or bac-
teria) to be deposited, these types of DM lters are referred to
as class II DM lters. The depositing materials can form a bridge-
like structure over the pores and may build occulation centers.
The pore constriction and cake ltration are membrane-forming
mechanisms that are involved in the formation of class II DM l-
ters.
4
Generally, in DM ltration technology a cake layer of specic
thickness is explicitly formed as more and more particles are
deposited on the surface of the primary membrane. As a result,
resistance might not be as badly affected during the formation
of class I DM lters compared to class II DM lters.
4,13
Therefore,
class I DM lters have recently gained popularity in water treat-
ment for removal of organics.
14,15
The most popular materials used in DM ltration technology are
polymers, hydrous Zr(IV) oxide polymer, metal oxides, soil-based
materials such as kaolin and diatomite, PAC and nanoparticles.
Among these materials, PAC and oxides of iron, aluminum and
titanium were the rst to be applied, whereas nanoparticles are
gaining popularity and are now widely accepted as DM-forming
materials.
4
Iron oxide-based adsorbents (e.g. Fe
2
O
3
) have been
used as pre-depositing material not only for fouling mitigation
of the primary membrane in UF applications
12,16
but also for puri-
cation purposes.
16
ADMlter formed by pre-depositing PAC
particles onto a primary membrane showed excellent efciency
in adsorbing organic pollutants from diluted textile wastewater.
17
Soil-based materials have also been tested as DM lter-forming
materials, examples of which are clay in treating domestic waste-
water,
18
clay for color removal
19
and arsenic removal
20
through
adsorption.
On a global scale, arsenic is considered to be a main environ-
mental issue because of its presence in the groundwater and sur-
face water sources; this is of great relevance to environmentalists
because of its toxicity and carcinogenicity, and the number of
affected people worldwide.
2123
It enters the food chain either
through drinking water or by consuming arsenic-containing food,
e.g. rice.
24
Arsenic in polluted environments primarily exists as
arsenite and arsenate, abbreviated as As(III) and As(V), respec-
tively. Arsenic naturally occurs in over 200 different mineral forms,
of which approximately 60% are arsenates, 20% suldes and sul-
fosalts and the remaining 20% include arsenides, arsenites,
oxides, silicates and elemental arsenic.
25
As(V) anions prevail in
oxygenated water, whereas As(III) anions occur in moderately
reduced environments (e.g. anoxic groundwater). Under oxidizing
conditions, H
3
AsO
4
is the more stable species between pH 2 and
7, whereas H
2
AsO
42
is the more stable species above pH 7 in nat-
ural waters.
26,27
Several treatment technologies for arsenic
removal from drinking water have been applied worldwide,
28
and the most commonly used are chemical coagulation using
metal (iron) salts,
2931
sorption on activated alumina,
3234
iron
oxides and iron oxyhydroxides,
3540
electrocoagulation with Fe/
Al electrodes,
41
preliminary arsenic oxidation by ozonation or bio-
logical oxidation,
42
ion exchange using polymer resins
43
and pres-
sure-driven membrane processes, such as nanoltration
44
and
reverse osmosis.
4547
Among the several existing arsenic removal
technologies, chemical precipitation by ferric coagulation fol-
lowed by ltration and adsorption onto iron oxides and iron oxy-
hydroxides appear to be cost effective for large-scale arsenic
treatment plants to comply with established WHO guideline value
of 10 μgL
1
.
35,40,48
Chemical precipitation by ferric coagulation
has signicantly higher arsenic removal efciencies compared to
iron-based adsorbent materials, including iron oxyhydroxides.
However, the efforts required for handling the wastes from coag-
ulationltration prevent its application when the treatable vol-
ume of product water corresponds to the one produced for a
small town.
35,48
Adsorption technology using iron oxyhydroxides
is considered to be an economical and effective technique for
arsenic removal because of its lower cost and availability of suit-
able commercial adsorbents and their regeneration.
49,50
It is gen-
erally believed that arsenic adsorption by porous iron hydroxides
takes place not only due to Coulombic and/or Lewis acidbase
interactions but also because of formation of monodentate and
bidentate inner-sphere complexes.
51,52
It is widely acknowledged
that the porous character of iron (oxy)hydroxides adsorbs As(V) at
internal iron complexation sites.
53
In the present work, the main objective was to create a pre-
deposited DM lter based on the utilization of micro-sized pow-
dered fractions of iron oxide-based adsorbents, namely micro-
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sized granular ferric hydroxide (μGFH) and micro-sized tetravalent
manganese feroxyhyte (μTMF). μGFH comprises the by-products
(waste) of the industrial production process of the commercially
available granular GFH and which is currently discarded, whereas
μTMF is generated during the production of TMF at the laboratory
scale. Both adsorbent materials are excellent arsenic adsorbents
and exhibit remarkable adsorption afnity towards As(V). A previ-
ous study of our group indicated that the adsorption capacities of
μGFH at an equilibrium arsenic concentration of 10 μgL
1
and
pH 8 were found to be 6.9 μg As(V) mg
1
and 3.5 μgAs
(III) mg
1
, respectively; whereas for μTMF the adsorption capaci-
ties were 5.5 μg As(V) mg
1
and 4.8 μg As(III) mg
1
under the
same experimental conditions.
54
Further, a recent study of our
group has shown that side-products of iron oxide-based adsor-
bents might be employed in an adsorptionMF hybrid system
wherein the adsorption take place in a slurry reactor simulating
a completely mixed stirred tank reactor. This study also concluded
that the powdered-sized fractions of the studied adsorbents have
an overwhelming inuence on As(V) adsorption rate compared to
larger-sized fractions (>63 μm).
8
Accordingly, the micro-sized
powdered fractions of iron (oxy)hydroxides might be applied as
pre-depositing materials for in situ preparation of DM lters. In
the present study, we moved forward the research by applying
the powdered-sized fractions of iron oxide-based adsorbents as
DM lter-forming materials and a novel modeling approach to
describe in more detail the efciency of As(V) removal and the
parameters that inuence the effectiveness of the process. We
applied a mass transfer model to describe As(V) removal in the
permeate of the pre-deposited DM adsorber. Furthermore, this
study aims at identifying the best operating conditions for opti-
mum As(V) removal from groundwaters. Application of the
modeling approach will support the optimization and facilitate
the application of DM ltration technology in real arsenic treat-
ment systems.
Until now, all reported pre-deposited DM lters were focused on
factors affecting the formation and mechanisms by which the DM
lters are formed. In the present work, we investigated for the rst
time the performance potential of two powdered-sized conven-
tional iron hydroxides (μGFH and μTMF) as pre-depositing mate-
rials of DM lter to remove As(V) from water in the MF process
and proposed a mathematical model to describe the overall per-
formance of the presented process.
MATERIALS AND METHODS
Materials
In the present work, the pre-deposited layer of applied adsor-
bents on the primary MF membrane was made by powdered-
sized fractions (163 μm) of GFH and TMF. The chosen pollutant
was As(V), as iron-based adsorbents such as GFH and TMF are cus-
tomarily applied to the treatment of arsenic-polluted waters in a
natural environment. Flat sheet PES-based MF membranes (DUR-
APES200) with a nominal size of 0.2 μm used a primary membrane
were purchased from Membrana GmbH (Wuppertal, Germany).
The industrial-scale production of μGFH (GEH Wasserchemie
GmbH & Co., Osnabrück, Germany) involves the neutralization of
an FeCl
3
solution and precipitation with NaOH. It mainly com-
prises of akagenéite mineral.
55
The lab-scale synthesis of μTMF
includes co-precipitation of FeSO
4
and KMnO
4
. It is identied as
feroxyhyte.
56
The important physicochemical properties of the
applied adsorbents were determined in our former studies
54,57
and are reported in Table 1. Table 1 lists the specic surface area
which were estimated according to Brunauere-Emmette-Teller
(BET) model and details on BET surface area measurements can
be found in our previous work.
57
A sieve having a mesh size of 63 μm was applied to separate
powdered-sized μGFH (163 μm) from air-dried μGFH (1
250 μm). The same sieve was applied to acquire powdered-sized
μTMF (163 μm) from μTMF (1250 μm). The individual particle
size of the majority (>98%) of μGFH (163 μm) particles was smal-
ler than 5 μm, while 100% particles of μTMF (163 μm) were smal-
ler than 5 μm. Consequently, the mean particle size of the
powdered-sized μGFH and μTMF materials was 3.5 and 2.8 μm,
respectively. The particle size distribution of powdered-sized μGFH
and μTMF is provided in Supporting Information Figs S1 and S2).
Arsenic-polluted water was obtained by spiking an appropriate
aliquot of As(V) standard solution (Merck Chemicals GmbH, Ger-
many) in deionized (DI) water. A buffer (N,N-bis(2-hydroxyethyl)-
2-aminoethanesulfonic acid (BES; 2 mmol L
1
) was carefully sup-
plemented to prepare As(V)-polluted water (Carl Roth GmbH +
Co. KG, Germany) to promote pH control for longer periods.
Before continuous feeding tests, a target pH of 8 ±0.1 was set
by addition of either NaOH or HCl.
Experimental setup
Each dead-end DM ltration experiment was divided into three
stages: preparation of primary MF membrane as a porous support
material, pre-deposition of adsorbent particles (DM lter forma-
tion) and ltration experiments employing pre-deposited DM
adsorber.
To prepare for the employment of the primary MF membrane as
porous support material for the deposition of powdered-sized
iron oxide-based adsorbents, the primary MF membrane was rst
rinsed with at least 1 L of pure water to remove residual sub-
stances. An Amicon® 8200 ltration cell constructed by Millipore
(USA) was used for the formation of the pre-deposited MD lter
as well as for the continuous dead-end ltration experiments.
The top-end piece of ltration cell contains the feed inlet, while
the bottom of the cell contains a porous insert that holds a mem-
brane with an active surface of 28.7 cm
2
.
AμGFH and μTMF pre-deposited DM adsorber was formed
according to the following procedure: the suspension formed
from mixing powdered-sized fractions of applied adsorbents
(300 or 400 mg in 150 mL pure water) was transferred to a ltra-
tion cell housing the primary MF membrane. The cell was then
sealed with an upper cap and O-ring. The pure water (~0.5 L)
was ltered at 0.5 bar applied ltration pressure through each
membrane and a new membrane was applied to all experiments.
A uniform thin cake layer of adsorbent particles was formed at the
surface of the primary MF membrane by permeation drag, which
is the convective force dragging the particles towards the primary
membrane.
Once the DM adsorber was formed by pre-depositing the pow-
dered-sized fractions of applied adsorbents at the primary mem-
brane surface, feed solution containing different concentration
levels of As(V) (either 190 or 380 μgL
1
) at room temperature
(20 ±2°C) was introduced using a peristaltic pump from a solu-
tion reservoir through the membrane ltration cell (Fig. 1). Exper-
iments using constant ux ltration, which is mainly used in plant
practice ltration, rather than constant pressure, were carried out
by keeping the water ux constant while changes in the operating
ltration pressure were continuously monitored. A signal-condi-
tioned pressure gauge (Sensortechnics GmbH, Germany) col-
lected the operating pressure data automatically. As(V)
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3
concentration levels in the efuent of a pre-deposited DM
adsorber were monitored by collecting samples at different time
intervals. The performance pre-deposited DM adsorber was eval-
uated under different operating conditions. The recorded As(V)
removal rates were then modeled using a mathematical model
based on a mass transfer model called the homogeneous surface
diffusion model (HSDM).
Arsenic analysis
Collected permeate samples were measured for total arsenic at
pH 2 using HCl. Measurement of arsenic concentration in the feed
and permeate samples was carried out by graphite furnace
atomic absorption spectrophotometry (GFAAS; 4110 ZL instru-
ment, PerkinElmer, Germany). GFAAS was operated with a graph-
ite furnace tube atomizer. The arsenic samples were atomized
using argon gas. GFAAS was set up with a lamp current of
380 mA, wavelength 193.7 nm for arsenic detection, and a slit
width of 0.7 nm. The peak area was selected as a measurement
mode. The arsenic limit of detection of this method was 0.5 μg
L
1
. The maximum standard deviation of the analysis was 5%.
Mathematical modeling of permeate As(V) concentration
A mathematical model incorporating the HSDM has been applied
to describe the concentration proles of arsenic adsorption sys-
tems,
8,5861
These studies have demonstrated that the HSDM
allows the simulation of the dynamic behavior of a variety of
adsorbates (phosphate, arsenic, chloroform and vanadium) onto
porous adsorbents (e.g. activated carbon, GFH and μGFH), as long
as the mass transfer from the solution to the adsorption sites
within the adsorbent particles is constrained by mass transfer
resistances such as surface diffusion and external lm mass trans-
fer, as depicted in Fig. 2.
The HSDM model assumes that the adsorbate (e.g. As(V)) dif-
fuses through a stagnant liquid lm layer developed around an
adsorbent particle into a homogeneous adsorbent sphere. The
Table 1. Physicochemical properties of applied iron oxide-based adsorbents
54, 57
Material
Iron
content
(wt%)
Mean particle
diameter (μm)
Moisture
content (%)
BET surface
area (m
2
g
1
)
Pore
volume
(mL g
1
)
Pore
diameter
(nm)
Isoelectric
point
Particle
density
(g cm
3
)
μGFH 60 3.5 ~50 283 ±3 0.28 2.6 7.8 ±0.2 1.550
μTMF 44 2.8 <5 178 ±8 0.35 3.2 7.2 ±0.1 0.642
Figure 1. Schematic representation of the laboratory installations for dead-end ltration. Inset demonstrates the pre-deposited cake layer of applied iron
oxide-based adsorbent material.
Figure 2. Schematic diagram of arsenic ion mass transport from the bulk
solution into a particle of porous iron oxide.
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surface diffusion and the external lm diffusion are the mass
transfer resistances incorporated into the HSDM controlling arse-
nic adsorption.
62
The mass transfer resistance arises from surface
diffusion (D
s
) and the external lm diffusion (k
f
).
The HSDM is an adsorption model that comprises two partial
differential equations. Equation (1) (referred to as the lter mass
balance equation) describes the mass transport through the
adsorbent layer, whereas the mass transfer into the adsorbent
particle is represented by Eqn (2) (intra-particle mass transfer
equation). The assumptions made in the HSDM are: (i) plugow
conditions in the deposited cake layer; (ii) the adsorbent particles
are spherical; (iii) local adsorption equilibrium occurs within the
adsorbent particle; (iv) instantaneous adsorption takes place on
active adsorption sites; (v) intra-particle surface diffusion is pre-
dominately mass transfer resistance; (vi) solid-phase mass transfer
owing to surface diffusion remains constant for an adsorbent. A
detailed description of the model has been reported elsewhere.
58
The As(V) mass balance over the pre-deposited DM lter in lin-
ear coordinates (z)is
εB
C
t+vf
C
z31εB
ðÞ
RkfCCs
ðÞ=0ð1Þ
here tis time, v
f
is lter velocity, ε
B
is cake layer porosity, Ris par-
ticle radius, k
f
is mass transfer coefcient due to the external lm
diffusion, and Cand C
s
are adsorbate liquid-phase concentration
in the pre-deposited iron oxyhydroxides layer and at the solidliq-
uid interface, respectively.
The intra-particle mass transfer equation indicates adsorbate
transfer in the adsorbent particle in radial coordinates (r) in pro-
portion to Fick's second law of diffusion:
qr,tðÞ
t=Ds
2qr,tðÞ
r2+2qr,tðÞ
rr

ð2Þ
where qis adsorbate solid-phase concentration and D
s
is mass
transfer caused by surface diffusion. The initial condition and
boundary conditions of the Eqn (2) can be found in the Support-
ing Information.
For model solution, desktop software (FAST 2.1) developed by
Sperlich et al.
58
was applied. The parameters to solve Eqns (1)
and (2) include readily measurable mass- and volume-related
parameters, i.e. mass of adsorbent applied, mean particle diame-
ter, particle density, cake layer density, inuent adsorbate concen-
tration) and indirectly quantiable parameters such as adsorption
equilibrium and kinetic parameters. It has been proven that the
mathematical model based on the HSDM has the capacity to
describe the impact of water chemistry (e.g. pH and water matrix)
on adsorbate dynamic behavior if the adsorption equilibrium and
kinetic parameters under changed water quality conditions are
available (have been derived).
60,61
This software (FAST 2.1) pro-
vides a numerical solution of Eqns (1) and (2) to simulate the con-
centration prole of anions over time of a xed-bed adsorption
lter packed with an adsorbent used in water treatment.
RESULTS AND DISCUSSION
Pre-deposited DM adsorber for As(V) removal
Figure 3 shows the normalized As(V) concentration with respect
to feed As(V) concentration in the permeate of primary MF mem-
brane and pre-deposited DM adsorber as a function of the specic
throughput volume, expressed as volume of treated water per
unit area of primary membrane, for the two applied adsorbents
applied as DM lter-forming materials at pH 8 ±0.1.
The results demonstrate that the primary MF membrane did not
lead to a reduction in normalized As(V) permeate concentration
(Fig. 3) because the nominal pore size of the primary MF mem-
brane is 0.2 nm, which is one order of magnitude larger than
the dominant As(V) species at pH 8 (ionic radius of HAsO
2
is
0.397 nm
63
). Additionally, the PES-based membrane is negatively
charged at pH 8,
64
and consequently the As(V) removal by elec-
trostatic attractive forces is not imaginable. On the other hand,
at constant water ux of 125 L m
2
h
1
and adsorbent dosage
(M
a
), expressed as amount of As(V) adsorptive material pre-depos-
ited per unit area of primary MF membrane, of 10.4 mg cm
2
, the
pre-deposited DM adsorber results in an immediate decrease in
normalized As(V) permeate concentration, with the As(V) concen-
tration reaching a minimum value. The DM adsorber achieved
very high As(V) removal efciency (90%, which corresponds to
C/C
f
=0.1) for the rst 0.15 L cm
2
specic throughput volume.
Subsequently, the normalized As(V) permeate concentration
started to increase as the volume of treated water was increasing
further (Fig. 3). This was due to the saturation of the deposited
adsorbent layer caused by the continuous inow of As(V)-contam-
inated feed solution. In the case of μTMF pre-deposited DM
adsorber, the rise in normalized As(V) permeate concentration
was slower than when using the μGFH deposited layer, even
though the achieved As(V) adsorption capacity of μTMF (15.4 μg
mg
1
) was lower than that achieved by using the μGFH (22.4 μg
mg
1
) at 380 μgL
1
and at pH 8.
8
This is most likely due to the
smaller particle size of μTMF, even though the BET surface area
and isoelectric point of μTMF is lower than μGFH (Table 1). The
second explanation might be the large pore diameter of μTMF,
which is causing a more rapid As(V) diffusion inside the adsorptive
material. A similar trend of As(V) removal rates by μTMF and μGFH
was observed during As(V) batch adsorption tests carried out in
the slurry reactor setup.
8
As the volume of treated water
increased, the normalized As(V) permeate concentration started
to increase. Interestingly, an increase in normalized As(V) concen-
tration was rapid in the case of the μTMF pre-deposited layer after
0.8 L cm
2
specic throughput volume (Fig. 3). This can be
ascribed to the fact that the adsorption process is restricted to
Figure 3. Normalized permeate concentrations of As(V) as a function of
specic throughput volume by primary MF membrane and pre-deposited
DM adsorber formed of μGFH and μTMF at 125 L m
2
h
1
, amount of
adsorbent at 10.4 mg cm
2
, feed As(V) concentration =380 μgL
1
and pH 8.
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5
the number of available active sites on the adsorbent surface. As
the process continues, the more active sites are more rapidly con-
sumed in the case of μTMF as compared to μGFH and thus, at the
nal stage of the process, remaining active sites of μTMF were
consumed by As(V) at a faster rate than μGFH. Moreover, the
adsorption capacity of μTMF is smaller than μGFH, due to which
recorded normalized concentration of As(V) 1 has occurred at
the end of the experiment (~0.9 in the case of μGFH) when spe-
cic throughput volume was 1.25 L cm
2
. Moreover, the repro-
ducibility of the pre-deposited DMs was also tested in order to
increase the acceptability of these lters in water treatment, and
the As(V) removal rates for the two developed DM adsorbers were
nearly identical under the same operating conditions (Supporting
Information Fig. S4).
The presented results indicate that the lifetime of the pre-
deposited DM adsorber largely depends on the type of pre-
depositing material, micro-pores and particle size of the depos-
ited material as well as on the specic surface area, which deter-
mines the number of active energy sites and the accessibility of
the pollutant to the adsorbent material.
65
Mathematical modeling of As(V) removal rates in a
dynamic membrane adsorber
The Freundlich constants (K
F
and n) and D
s
values are based on
our previous batch adsorption experiments.
8
Freundlich parame-
ters were derived from batch adsorption equilibrium, whereas D
s
values were determined by tting the kinetic data derived from
batch adsorption kinetic experiments in the slurry reactor setup
with model solution. The values of Freundlich parameters for
μGFH adsorption are K
F
=4.5 μgmg
1
and n=0.268. In the case
of μTMF adsorption, the values of K
F
and nare 3.5 μgmg
1
and
n=0.249, respectively. At an applied As(V) concentration
380 μgL
1
and pH 8, adsorption loadings determined through
batch isotherm equilibrium tests in deionized water were found
to be 22.4 and 15.4 μgmg
1
for μGFH and μTMF, respectively.
8
The values of adsorption equilibrium parameters and D
s
are used
as inputs to mathematically model As(V) removal rates.
The optimum k
f
values are evaluated through a constant opti-
mization procedure until the sum of square of error (SSE,
Eqn (3)) is minimized. The SSE reects the bias between the
experimental and the simulated results. An SSE value close to
zero describes the low bias, whereas larger values indicate rela-
tively higher bias between the experimental data and model
output:
Sum of square of error=
m
i=1
Cmodel iðÞCexperiment iðÞ
Cf

2
ð3Þ
Figure 4 shows permeate As(V) concentration proles along
with the model predictions expressed as C/C
f
over the ltration
time. This gure shows the model t to the experimental data,
which is considered to be satisfactory, evidenced from the high
correlation (R
2
) values and SSE values <1 (Table 2).
The measured model parameters at varying operating condi-
tions are provided in Table 2. Using the D
s
values determined at
an As(V) concentration of 380 μgL
1
and the same pH in deio-
nized water, it is evident that the model can accurately predict
the As(V) removal rates at varying amounts of adsorbent material
pre-deposited per unit area of primary membrane and membrane
uxes, which determine the contact time between the adsorbent
pre-deposited layer and feed water. This is most likely due to the
same concentration of As(V) applied in batch and continuous
mode experiments. However, at a lower feed As(V) concentration
of 190 μgL
1
, the model simulations slightly over-predict the As
Figure 4. Experiments versus model prediction of As(V) removal rates
representing inuence of (A) amount of μTMF and μGFH pre-deposited
per unit area of primary membrane at water ux =125 L m
2
h
1
, feed
As(V) concentration =380 μgL
1
and pH =8; (B) membrane water
ux for μGFH pre-deposited DM adsorber at adsorbent dose (M
a
)=
10.4 mg cm
2
, feed As(V) concentration =380 μgL
1
and pH =8; (C) feed
As(V) concentration onto μTMF pre-deposited DM adsorber at adsorbent
dose (M
a
)=10.4 mg cm
2
, water ux =125 L m
2
h
1
and pH 8. Solid
symbols reect experimental data points, whereas model predictions are
represented by solid lines under corresponding operating conditions.
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6
(V) removal rates, as evidenced by low correlation coefcient (R
2
)
and high SSE values.
The tted k
f
values decreased signicantly with decreasing
membrane ux for both adsorbent materials. Since the lter
velocity has a direct inuence on the boundary layer thickness,
the lm diffusion rate was reduced with decreasing membrane
ux. Moreover, the k
f
values were found to be higher for μGFH
than μTMF under the same operating conditions. Large tted k
f
values for μGFH might be due to its higher adsorption loading
towards As(V) than μTMF. These ndings are consistent with pre-
vious studies,
59
in which larger k
f
values for adsorbents were
achieved with higher adsorbent capacity, during adsorption of
nitrate onto commercially available and laboratory-prepared
anion exchange resins in an adsorptionmembrane hybrid pro-
cess. A higher mass transfer at the external surface of the material
provides a higher degree of adsorption for the target pollutant.
For the lower feed As(V) concentration of 190 μgL
1
, data in
Table 2 show that the SSE value was 0.142 for μGFH and 0.169
for μTMF, demonstrating that the mathematical model is fairly
consistent with the experimental data but unable to describe
accurately the experimentally determined As(V) removal rates.
The possible reason for higher SSE values between experimental
and model results at different feed As(V) concentrations could
be that the D
s
value applied in the modeling approach was deter-
mined at the higher As(V) concentration of 380 μgL
1
in batch
mode experiments. When optimum values of D
s
and k
f
are applied
in the modeling approach, a strong agreement was observed, as
indicated by improved goodness-of-t parameters (R
2
=0. 99
and SSE =0.043 for μGFH pre-deposited DM adsorber and
R
2
=0.996 and SSE =0.028 for μTMF pre-deposited DM adsorber).
Several model simulations are shown in Fig. 5 employing values of
D
s
up to an order of magnitude lower. As can be clearly seen,
model simulations captured the experimental data points much
better when the tted values of D
s
were decreased from
2.26 ×10
18
to 1 ×10
18
m
2
s
1
and from 1.09 ×10
18
to
0.9 ×10
18
m
2
s
1
for μTMF and μGFH, respectively. The variation
in D
s
values might be due to dependence on the surface loadings.
D
s
dependence may exist for energetically heterogeneous adsor-
bents such as μGFH and μTMF, and could be explicated by the
reduced adsorption energy with increasing surface loading that
results in increased adsorbate mobility.
66
In summary, the presented results indicate that a pre-deposited
DM adsorber can be developed by pre-deposition of variable
amounts of the powdered-sized fractions of applied adsorbents
Table 2. Measured model parameters under varying operational conditions
Material
Water ux
(L m
2
h
1
)
M
a
(mg cm
2
)
C
f
(μgL
1
)
Volume of
water
treated (L)
Final As(V)
concentration C/
C
f
()D
s
(×10
18
m
2
s
1
)k
f
(×10
6
ms
1
)R
2
SSE
μGFH 31 10.4 380 9 0.15 1.09 0.3 0.963 0.016
62.5 10.4 380 18 0.67 1.09 1.0 0.995 0.042
125 10.4 380 36 0.87 1.09 1.7 0.998 0.031
125 14.0 380 36 0.83 1.09 1.6 0.993 0.027
125 10.4 190 36 0.77 1.09 1.0 0.977 0.142
μTMF 31 10.4 380 9 0.21 2.26 0.07 0.980 0.019
62.5 10.4 380 18 0.85 2.26 0.2 0.995 0.046
125 10.4 380 36 0.98 2.26 1.0 0.998 0.029
125 14.0 380 36 0.95 2.26 1.0 0.994 0.054
125 10.4 190 36 0.90 2.26 0.3 0.974 0.169
M
a
is the amount of pre-deposited adsorbent material per unit area of the primary membrane.
Figure 5. Model simulations of normalized As(V) concentrations employ-
ing different values of D
s
for (A) μTMF pre-deposited DM adsorber;
(B) μGFH pre-deposited DM adsorber at adsorbent dose (M
a
)=
10.4 mg cm
2
, water ux =125 L m
2
h
1
and pH 8.
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7
on the primary membrane surface, which reveals that it is possible
to regulate the thickness of the DM lter to treat the arsenic-pol-
luted waters and achieve an As(V) removal efciency of >90%,
which corresponds to C/C
f
=0.1, as long as the best operating
conditions such as lowermost membrane ux of 31 L m
2
h
1
and higher amount of pre-deposited adsorbent per unit area of
primary membrane (14 mg cm
2
) were provided. Further, a
higher ux governing shorter contact time has signicantly
improved the As(V) ux through the stagnant boundary layer sur-
rounding an adsorbent particle, as indicated by large k
f
values. A
respective increase of one and two orders of magnitude for μGFH
and μTMF pre-deposited DM adsorber was computed when
membrane ux was increased from 31 to 125 L m
2
h
1
. Hence it
can be concluded that k
f
is related directly to the membrane
water ux (contact time). Conversely, the surface diffusion coef-
cient (D
s
) value is unique and not a function of membrane water
ux and amount of adsorbent applied for DM lter formation,
but is a function of feed As(V) concentration. We therefore pro-
pose investigating the effect of As(V) concentration on the D
s
values to derive the relationship between As(V) concentration
and D
s
values to increase the acceptability of the applied mathe-
matical model in the real water treatment system.
In this work, the size of individual adsorbent particle-forming
DM adsorbers are signicantly larger (one order of magnitude)
than the primary membrane pores. Therefore, the pore size of
the primary membrane is not anticipated to have a substantial
inuence on formation of the pre-deposited DM lter. However,
more investigations are proposed to study the effect of the
depositing particles on the surface morphology and strength of
the primary membrane. These investigations would provide more
insights into the repeating use of the primary membrane for for-
mation and deformation of the DM lter.
Operating pressure
Long-term variations in operating pressure were monitored using
a signal-conditioned pressure gauge. A stable operating pressure
was recorded for 100 h constant ux dead-end ow experiments
(data not shown here). This was possibly due to ltration of
organic-free feed water. The operating pressure was in the range
of 618 mbar for μTMF pre-deposited DM adsorber at
M
a
=10.4 mg cm
2
, while for μGFH pre-deposited DM adsorber
the range of operating pressure was 410.5 mbar (Figure 6). The
operating pressure was higher for the higher water ux. This trend
was attributed to the compression of deposited adsorbent cake
layer on the membrane surface at higher membrane ux.
67
This
trend was almost linear to the permeate water ux. At a higher
M
a
of 14 mg cm
2
, the operating pressure was 20 and 12 mbar
for μTMF and μGFH pre-deposited DM adsorber, respectively. This
is explained by a large volume of deposited cake layer on the sur-
face of the primary MF membrane, which offers greater resistance
to water owing through the cake layer.
The operating pressures recorded for μGFH pre-deposited DM
adsorber at all water uxes were low when compared to μGFH
pre-deposited DM adsorber possibly due to a lower volume of
adsorbent cake layer (0.2 mL μGFH vs. 0.7 mL μTMF at
M
a
=10.4 mg cm
2
).
Performance comparison of pre-deposited DM adsorber
The adsorption capacity of the powdered-sized adsorbents
applied as pre-depositing materials for the formation of DM
adsorber was calculated by integrating the breakthrough curve
until C/C
f
=1 (referred to as Q
1.0
) at a water ux of
125 L m
2
h
1
and adsorbent dosage of 10.4 mg cm
2
. The calcu-
lated Q
1.0
value of μGFH recorded through continuous-ow pre-
deposited DM adsorber is 22.8 μg As(V) mg
1
, while the Q
1.0
value
of μTMF is 15.8 μg As(V) mg
1
. Similar Q
1.0
values of μGFH and
μTMF for As(V) were calculated when As(V) adsorption onto pow-
dered-sized μGFH and μTMF in a slurry reactor was combined with
MF at the same pH 8 (Fig. 7).
8
In our previous study, the As(V) adsorption capacities of pow-
dered-sized μGFH and μTMF were estimated to be 22.4 μgAs
(V) mg
1
and 15.4 μg As(V) mg
1
, respectively, which were deter-
mined through batch adsorption equilibrium experiments at a
residual concentration of 380 μgL
1
and at pH 8. It can be con-
cluded that adsorption capacities of powdered-sized μGFH and
μTMF are the same when applied in three different experimental
setups (Fig. 7).
For the applied iron oxide-based adsorptive materials, the As(V)
adsorption capacities and bed volume treated (equivalent to a
volume of water treated) the different water uxes studied and
Figure 7. As(V) adsorption capacities achieved through pre-deposited
DM adsorber compared to the adsorption capacities by the Freundlich iso-
therm model (obtained through batch adsorption experiments) and
adsorption of As(V) onto micro-sized iron oxide-based adsorbents (μGFH
and μTMF) in the slurry reactor of adsorptionMF hybrid system at
C
0
=380 μgL
1
and pH 8.
Figure 6. Operating pressure for the μGFH and μTMF pre-deposited DM
lter at M
a
=10.4 mg cm
2
.
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J Chem Technol Biotechnol 2021
8
amount adsorbed applied to develop a DM adsorber are summa-
rized in Table 3. The results demonstrate increasing As(V) adsorp-
tion capacities and bed volumes treated at decreasing water ux,
which is explained by increasing contact time between adsorbent
cake layer and As(V) species. Similarly, improved As(V) adsorption
capacities were estimated at larger adsorbent dosages, which is
attributed to a large number of available adsorption sites at
higher M
a
=14 mg cm
2
relative to M
a
=10.4 mg cm
2
. These
observations lead to the conclusion that implementing lower-
most water ux (31 L m
2
h
1
) and large amounts of adsorptive
materials (M
a
=14 mg cm
2
) to form pre-deposited DM adsorber
are benecial in treating As(V)-contaminated waters.
The adsorption capacities of powdered-sized μGFH and μTMF
acquired through a pre-deposited DM lter can be compared with
similar studies employing highly efcient commercial adsorbents
for As(V) removal from water.
35,57,68,69
Although these studies
have been executed under different experimental conditions
(e.g. water matrix, inuent As(V) concentration, pH and experi-
mental setup), so the results of these studies cannot be directly
compared. However, when the As(V) adsorption capacities and
bed volumes treated are compared (Table 3), the studied pow-
dered-sized iron oxide-based adsorptive materials are superior
in remediating As(V) contaminated water even at very little con-
tact time (7 and 2 s for μTMF and μGFH, respectively, because of
extremely fast As(V) adsorption kinetics.
8
CONCLUSIONS
In this study, a pre-deposited DM adsorber was developed in situ
at low pressure (0.5 bar) by depositing the powdered-sized frac-
tions of iron oxide-based adsorbents on the primary MF mem-
brane, wherein the adsorbent deposited layer has acted as an
adsorptive ltration barrier to remove As(V) from water applied
in the MF process under varying operating conditions. Experimen-
tally determined As(V) removal rates were described by a mathe-
matical model incorporating surface diffusion and external lm
diffusion. The main ndings are as follows:
(1) Applied adsorbents with individual particle size in the range
of 23μm were pre-deposited on the primary MF membrane
to form a DM adsorber. The developed pre-deposited DM
Table 3. Comparison of adsorption capacities of some adsorbents for As(V) reported in the literature with the adsorption capacities evaluated in this
work (pH is shown in parentheses where reported)
Material Type of experiment Operating conditions Bed volumes treated at C/C
in
=0.1
Adsorption
capacity
(μgmg
1
)
at C/C
in
=0.1 Reference
GFH Lab-scale column
adsorber
Arizona groundwater
As(V) =100 μgL
1
,
pH =8.6,
Mass of GFH =2.78 g
3 000 at EBCT =0.5 min
8 000 at EBCT =2.5 min
11 000 at EBCT =4.0 min
0.50
1.45
2.01
Westerhoff et
al.
68
Granular
TiO
2
Lab-scale column
adsorber
Groundwater
As(V) =400 μgL
1
,
pH =8.2,
EBCT =1.1 min
1 500 Cui et al.
69
Bayoxide
(E33)
Lab-scale column
adsorber
Thessaloniki
groundwater
As(V) =100 μgL
1
pH =7.3,
EBCT =1.2 min,
mass of bayoxide =8g
3.09 Tresintsi et
al.
35
μTMF Pre-deposited DM
adsorber
Synthetic water
As(V) =380 μgL
1
,
pH =8.0,
M
a
=10.4 mg cm
2
7 560 at 125 L m
2
h
1
(EBCT =7s)
9 050 at 62.5 L m
2
h
1
(EBCT =14 s)
9 900 at 31 L m
2
h
1
(EBCT =28 s)
6.66
7.88
8.30
This work
μTMF Pre-deposited DM
adsorber
Synthetic water
As(V) =380 μgL
1
,
pH =8.0,
M
a
=14 mg cm
2
9 450 at125 L m
2
h
1
(EBCT =7 s) 8.12 This work
μGFH Pre-deposited DM
adsorber
Synthetic water
As(V) =380 μgL
1
,
pH =8.0,
M
a
=10.4 mg cm
2
14 400 at 125 L m
2
h
1
(EBCT =2s)
21 600 at 62.5 L m
2
h
1
(EBCT =4s)
36 450 at 31 L m
2
h
1
(EBCT =8s)
3.55
5.32
8.77
This work
μGF Pre-deposited DM
adsorber
Synthetic water
As(V) =380 μgL
1
,
pH =8.0,
M
a
=14 mg cm
2
22 320 at 125 L m
2
h
1
(EBCT =2 s) 5.19 This work
ECBT is the empty-bed contact time and expressed as adsorbent bed volume to the ow rate.
M
a
is the adsorbent dose, expressed as amount of adsorptive material deposited per unit area of the primary MF membrane.
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9
adsorber shows remarkable As(V) removal efciencies (as high
as ~99%) with excellent reproducibility.
(2) μGFH and μTMF proved to be promising as emerging pre-
depositing material for a DM lter and equally good for appli-
cation in water treatment systems targeting As(V) removal.
(3) Parametric study indicates that As(V) removal rates of pre-
deposited DM adsorbers can be controlled by changing the
membrane water ux and amount of pre-depositing material
per unit area of the primary membrane. Longer times of 90%
As(V) removal can be achieved by increasing pre-depositing
material over the primary membrane and lowering mem-
brane water ux.
(4) As(V) removal rates of a pre-deposited DM adsorber can be
accurately predicted using the applied mathematical model
relying on the HSDM.
(5) The surface diffusion parameter of the HSDM can be consid-
ered as independent of membrane water ux and the amount
of applied adsorbents used to form pre-deposited DM
adsorber.
(6) Under the same operating conditions, the magnitude of the
mass transfer due to external lm diffusion was affected by
the type of adsorbent material having different As(V) adsorp-
tion capacities. The k
f
value was linearly related to the adsorp-
tion capacity of applied adsorbent material towards As(V).
(7) Low-pressure DM ltration technology is a sustainable and
practicable approach that can be applied to remediation of
arsenic-contaminated waters. The DM ltration technology
may be further extended with repeated use of the exhausted
iron oxide-based adsorbent materials to reduce the quantity
of produced waste for environmental sustainability and to
obtain more information on practical applications.
ACKNOWLEDGEMENTS
The authors are obliged to the German Academic Exchange
Service (DAAD) for the fellowship of Mr Usman and the Hamburg
University of Technology for resources. Professor Mitrakas,
Department of Chemical Engineering, Aristotle University of Thes-
saloniki, Greece, and GEH Wasserchemie GmbH & Co., Osnabrück,
Germany, are thanked for offering tetravalent manganese feroxy-
hyte and the micro-sized granular ferric hydroxide materials for
the purposes of research. Open access funding enabled and orga-
nized by Projekt DEAL.
CONFLICTS OF INTEREST
The authors declare no conict of interest.
SUPPORTING INFORMATION
Supporting information may be found in the online version of this
article.
REFERENCES
1 Marcinkowsky AE, Kraus KA, Phillips HO, Johnson JS and Shor AJ,
Hyperltration studies. IV. Salt rejection by dynamically formed
hydrous oxide membranes. J Am Chem Soc 88:57445746 (1966).
2 Ersahin ME, Ozgun H, Dereli RK, Ozturk I, Roest K and van Lier JB, A
review on dynamic membrane ltration: materials, applications
and future perspectives. Bioresour Technol 122:196206 (2012).
3 Matsuyama H, Shimomura T and Teramoto M, Formation and charac-
teristics of dynamic membrane for ultraltration of protein in binary
protein system. J Membr Sci 92:107115 (1994).
4 Anantharaman A, Chun Y, Hua T, Chew JW and Wang R, Pre-deposited
dynamic membrane ltration: a review. Water Res 173:115558
(2020).
5 Li L, Xu G and Yu H, Dynamic membrane ltration: formation, ltration,
cleaning, and applications. Chem Eng Technol 41:718 (2018).
6 Zhang X, Wang Z, Wu Z, Lu F, Tong J and Zang L, Formation of dynamic
membrane in an anaerobic membrane bioreactor for municipal
wastewater treatment. Chem Eng Technol 165:175183 (2010).
7 Katsoyiannis IA, Gkotsis P, Castellana M, Cartechini F and Zouboulis AI,
Production of demineralized water for use in thermal power stations
by advanced treatment of secondary wastewater efuent. J Environ
Manage 190:132139 (2017).
8 Usman M, Zarebanadkouki M, Waseem M, Katsoyiannis IA and Ernst M,
Mathematical modeling of arsenic(V) adsorption onto iron oxyhydr-
oxides in an adsorption-submerged membrane hybrid system. J
Hazard Mater 400:123221 (2020). https://doi.org/10.1016/j.jhazmat.
2020.123221.
9 Hu Y, Wang XC, Tian W, Ngo HH and Chen R, Towards stable operation
of a dynamic membrane bioreactor (DMBR): operational process,
behavior and retention effect of dynamic membrane. J Membr Sci
498:2029 (2016).
10 H-q C, D-w C, Jin W and Dong B-Z, Characteristics of bio-diatomite
dynamic membrane process for municipal wastewater treatment. J
Membr Sci 325:271276 (2008).
11 Aghili F, Ghoreyshi AA, Rahimpour A and Rahimnejad M, Coating of
mixed-matrix membranes with powdered activated carbon for foul-
ing control and treatment of dairy efuent. Process Saf Environ 107:
528539 (2017).
12 Lu D, Cheng W, Zhang T, Lu X, Liu Q, Jiang J et al., Hydrophilic Fe
2
O
3
dynamic membrane mitigating fouling of support ceramic mem-
brane in ultraltration of oil/water emulsion. Sep Purif Technol 165:
19 (2016).
13 Tanny GB and Johnson JS, The structure of hydrous Zr(IV) oxidepoly-
acrylate membranes: poly(acrylic acid) deposition. J Appl Polym Sci
22:289297 (1978).
14 Cai Z and Benjamin MM, NOM fractionation and fouling of low-pres-
sure membranes in microgranular adsorptive ltration. Environ Sci
Technol 45:89358940 (2011).
15 Huang H, Schwab K and Jacangelo JG, Pretreatment for low pressure
membranes in water treatment: a review. Environ Sci Technol 43:
30113019 (2009).
16 Tian H, Sun L, Duan X, Chen X, Yu T, Feng C et al., Effect of phosphate on
ultraltration membrane performance after predeposition of Fe
3
O
4
.
Environ Eng Sci 35:654661 (2018).
17 Nyobe D, Ye J, Tang B, Bin L, Huang S, Fu F et al., Build-up of a contin-
uous ow pre-coated dynamic membrane lter to treat diluted tex-
tile wastewater and identify its dynamic membrane fouling. J
Environ Manage 252:109647 (2019).
18 Noor MJMM, Ahmadun FR, Mohamed TA, Muyibi SA and Pescod MB,
Performance of exible membrane using kaolin dynamic
membrane in treating domestic wastewater. Desalination 147:263
268 (2002).
19 Wang JY, Chou KS and Lee CJ, Dead-end ow ltration of solid suspen-
sion in polymer uid through an active kaolin dynamic membrane.
Sep Sci Technol 33:25132529 (1998).
20 O'Day PA, Vlassopoulos D, Meng X and Benning LG eds, Advances in
Arsenic Research. ACS Symposium Series. American Chemical Soci-
ety, Washington, DC (2005).
21 Smith AH, Hopenhayn-Rich C, Bates MN, Goeden HM, Hertz-Picciotto I,
Duggan H et al., Cancer risks from arsenic in drinking water. Environ
Health Perspect 97:259267 (1992).
22 Hindmarsh JT and McCurdy RF, Clinical and environmental aspects of
arsenic toxicity. Crit Rev Clin 23:315347 (1986).
23 Podgorski J and Berg M, Global threat of arsenic in groundwater. Sci-
ence 368:845850 (2020).
24 Pal BN, Granular ferric hydroxide for elimination of arsenic from drink-
ing water. Technologies for arsenic removal from drinking water:59
68 (2001).
25 Wedepohl KH, Correns CW, Shaw DM, Turekian KK and Zemann J,
Handbook of Geochemistry. Springer, Berlin (1969).
26 Ferguson JF and Gavis J, A review of the arsenic cycle in natural waters.
Water Res 6:12591274 (1972).
www.soci.org M Usman et al.
wileyonlinelibrary.com/jctb © 2021 The Authors.
Journal of Chemical Technology and Biotechnology published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry (SCI).
J Chem Technol Biotechnol 2021
10
27 Masscheleyn PH, Delaune RD and Patrick WH, Effect of redox potential
and pH on arsenic speciation and solubility in a contaminated soil.
Environ Sci Technol 25:14141419 (1991).
28 Alka S, Shahir S, Ibrahim N, Ndejiko MJ, Vo D-VN and Manan FA, Arsenic
removal technologies and future trends: a mini review. J Clean Prod
278:123805 (2021).
29 Mitrakas MG, Panteliadis PC, Keramidas VZ, Tzimou-Tsitouridou RD and
Sikalidis CA, Predicting Fe
3+
dose for As(V) removal at pHs and tem-
peratures commonly encountered in natural waters. Chem Eng J
155:716721 (2009).
30 Zouboulis A and Katsoyiannis I, Removal of arsenate from contami-
nated water by coagulation-direct ltration. Sep Sci Technol 37:
28592873 (2002).
31 TubićA, Agbaba J, Dalmacija B, Ivancev-Tumbas I and Dalmacija M,
Removal of arsenic and natural organic matter from groundwater
using ferric and alum salts: a case study of central Banat region (Ser-
bia). J Environ Sci Health Part A 45:363369 (2010).
32 Tripathy SS and Raichur AM, Enhanced adsorption capacity of acti-
vated alumina by impregnation with alum for removal of As(V) from
water. Chem Eng Technol 138:179186 (2008).
33 Chwirka JD, Thomson BM and Stomp JM, Removing arsenic from
groundwater. J Am Water Works Assoc 92:7988 (2000).
34 Wang L, Chen ASC, Sorg TJ and Fields KA, Field evaluation of As
removal by IX and AA. J Am Water Works Assoc 94:161173 (2002).
35 Tresintsi S, Simeonidis K, Zouboulis A and Mitrakas M, Comparative
study of As(V) removal by ferric coagulation and oxy-hydroxides
adsorption: laboratory and full-scale case studies. Desalin Water
Treat 51:28722880 (2013).
36 Mohan D and Pittman CU, Arsenic removal from water/wastewater
using adsorbents: a critical review. J Hazard Mater 142:153 (2007).
37 Tresintsi S, Simeonidis K, Vourlias G, Stavropoulos G and Mitrakas M,
Kilogram-scale synthesis of iron oxy-hydroxides with improved arse-
nic removal capacity: study of Fe(II) oxidationprecipitation parame-
ters. Water Res 46:52555267 (2012).
38 Amy GL, Adsorbent Treatment Technologies for Arsenic Removal. AWWA
Research Foundation and American Water Works Association,
Denver, CO (2005).
39 Ćurko J, MatošićM, Crnek V, StulićV and MijatovićI, Adsorption char-
acteristics of different adsorbents and Iron(III) salt for removing As
(V) from water. Food Technol Biotechnol 54:250255 (2016).
40 Bretzler A, Nikiema J, Lalanne F, Hoffmann L, Biswakarma J,
Siebenaller L et al., Arsenic removal with zero-valent iron lters in
Burkina Faso: eld and laboratory insights. Sci Total Environ 737:
139466 (2020).
41 Khan SU, Farooqi IH, Usman M and Basheer F, Energy efcient rapid
removal of arsenic in an electrocoagulation reactor with hybrid
Fe/Al electrodes: process optimization using CCD and kinetic model-
ing. Water 12:2876 (2020). https://doi.org/10.3390/w12102876.
42 Katsoyiannis IA, Mitrakas M and Zouboulis AI, Arsenic occurrence in
Europe: emphasis in Greece and description of the applied full-scale
treatment plants. Desalin Water Treat 54:21002107 (2015).
43 Ghurye GL, Clifford DA and Tripp AR, Combined arsenic and nitrate
removal by ion exchange. J Am Water Works Assoc 91:8596 (1999).
44 Sato Y, Kang M, Kamei T and Magara Y, Performance of nanoltration
for arsenic removal. Water Res 36:33713377 (2002).
45 Kang M, Kawasaki M, Tamada S, Kamei T and Magara Y, Effect of pH on
the removal of arsenic and antimony using reverse osmosis mem-
branes. Desalination 131:293298 (2000).
46 Abejón A, Garea A and Irabien A, Arsenic removal from drinking water
by reverse osmosis: minimization of costs and energy consumption.
Sep Purif Technol 144:4653 (2015).
47 Víctor-Ortega MD and Ratnaweera HC, Double ltration as an effective
system for removal of arsenate and arsenite from drinking water
through reverse osmosis. Process Saf Environ 111:399408 (2017).
48 Wang L, Chen ASC, Sorg TJ and Supply W, Costs of arsenic removal tech-
nologies for small water systems: US EPA arsenic removal technology
demonstration program. United States Environmental Protection
Agency, Cincinnati, OH, p. 92 (2011).
49 Chen ASC, Sorg TJ and Wang L, Regeneration of iron-based adsorptive
media used for removing arsenic from groundwater. Water Res 77:
8597 (2015).
50 Hering JG, Katsoyiannis IA, Theoduloz GA, Berg M and Hug SJ, Arsenic
removal from drinking water: experiences with technologies and
constraints in practice. J Environ Eng 143:3117002 (2017).
51 Zhang J and Stanforth R, Slow adsorption reaction between arsenic
species and goethite (-FeOOH): diffusion or heterogeneous surface
reaction control. Langmuir 21:28952901 (2005).
52 Banerjee K, Amy GL, Prevost M, Nour S, Jekel M, Gallagher PM et al.,
Kinetic and thermodynamic aspects of adsorption of arsenic onto
granular ferric hydroxide (GFH). Water Res 42:33713378 (2008).
53 Sinha S, Lee N, Amy G, Innovative technologies for arsenic removal, in
Water Quality and Treatment Conference, Seattle, WA (2002).
54 Usman M, Katsoyiannis I, Mitrakas M, Zouboulis A and Ernst M,
Performance evaluation of small sized powdered ferric hydroxide
as arsenic adsorbent. Water 10:957 (2018). https://doi.org/10.3390/
w10070957.
55 Driehaus W, Jekel M and Hildebrandt U, Granular ferric hydroxide: a
new adsorbent for the removal of arsenic from natural water. J Water
Supply Res Technol 47:3035 (1998).
56 Tresintsi S, Simeonidis K, Estradé S, Martinez-Boubeta C, Vourlias G,
Pinakidou F et al., Tetravalent manganese feroxyhyte: a novel
nanoadsorbent equally selective for As(III) and As(V) removal from
drinking water. Environ Sci Technol 47:96999705 (2013).
57 Usman M, Katsoyiannis I, Rodrigues JH and Ernst M, Arsenate removal
from drinking water using by-products from conventional iron oxy-
hydroxides production as adsorbents coupled with submerged
microltration unit. Environ Sci Pollut Res (2020). https://doi.org/10.
1007/s11356-020-08327-w.
58 Sperlich A, Schimmelpfennig S, Baumgarten B, Genz A, Amy G, Worch E
et al., Predicting anion breakthrough in granular ferric hydroxide
(GFH) adsorption lters. Water Res 42:20732082 (2008).
59 Kalaruban M, Loganathan P, Shim W, Kandasamy J and Vigneswaran S,
Mathematical modelling of nitrate removal from water using a sub-
merged membrane adsorption hybrid system with four adsorbents.
Appl Sci 8:194 (2018).
60 Piazzoli A and Antonelli M, Application of the homogeneous surface
diffusion model for the prediction of the breakthrough in full-scale
GAC lters fed on groundwater. Process Saf Environ 117:286295
(2018).
61 Dabizha A, Bahr C and Kersten M, Predicting breakthrough of vana-
dium in xed-bed absorbent columns with complex groundwater
chemistries: a multi-component granular ferric hydroxidevana-
datearsenatephosphatesilicic acid system. Water Res X 9:
100061 (2020).
62 Zheng M, Xu C, Hu H, Ye Z and Chen X, A modied homogeneous sur-
face diffusion model for the xed-bed adsorption of 4,6-DMDBT on
AgCeO
x
/TiO
2
SiO
2
.RSC Adv 6:112899112907 (2016).
63 Kim Y, Kim C, Choi I, Rengaraj S and Yi J, Arsenic removal using meso-
porous alumina prepared via a templating method. Environ Sci Tech-
nol 38:924931 (2004).
64 Mantel T, Benne P, Parsin S and Ernst M, Electro-conductive composite
goldpolyethersulfoneultraltrationmembrane: characterization
of membrane and natural organic matter (NOM) ltration perfor-
mance at different in-situ applied surface potentials. Membranes 8:
64 (2018).
65 Crittenden JC, Trussell RR, Hand DW, Howe KJ and Tchobanoglous G,
MWH's Water Treatment: Principles and Design. John Wiley & Sons,
Third Edition, Hoboken, NJ (2012). https://doi.org/10.1002/9781118
131473.
66 Worch E, Adsorption Technology in Water Treatment: Fundamentals,
Processes, and Modeling. De Gruyter, Berlin (2012). https://doi.org/
10.1515/9783110240238.
67 Derlon N, Grütter A, Brandenberger F, Sutter A, Kuhlicke U, Neu TR et
al., The composition and compression of biolms developed on
ultraltration membranes determine hydraulic biolm resistance.
Water Res 102:6372 (2016).
68 Westerhoff P, Higheld D, Badruzzaman M and Yoon Y, Rapid small-
scale column tests for arsenate removal in iron oxide packed bed
columns. J Environ Eng 131:262271 (2005).
69 Cui J, Du J, Yu S, Jing C and Chan T, Groundwater arsenic removal using
granular TiO
2
: integrated laboratory and eld study. Environ Sci Pol-
lut Res 22:82248234 (2015).
Pre-deposited dynamic membrane adsorber www.soci.org
J Chem Technol Biotechnol 2021 © 2021 The Authors.
Journal of Chemical Technology and Biotechnology published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry (SCI).
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... However, scientific progress has expanded notice of water contaminant types and reawakened the necessity for comprehensive water treatment. Oxyanions (or oxoanions) (As, V, B, W, and Mo) are formed by a number of redox-sensitive metalloids and metals, including titanium dioxide, iron oxides, manganese dioxide, aluminum oxides, and numerous oxide minerals [14,15]. Due to their toxicity, non-degradability, and movement in aquatic habitats, these species are detrimental to living organisms. ...
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... Some of these adsorbents are as follows: an aluminium mining by-product (4.51 mg/g) [37], PBGC-Fe/C (4.83 mg/g) [20], organo-modified natural zeolite materials (6.7 mg/g) [38], biochar-magnetite composite (5.49 mg/g) [14], Chinese red soil (0.936 mg/g) [39], ironcoated seaweeds (7.3 mg/g) [40], goethite-P (AAm) composite (1.22 mg/g) [13], iron-oxidebased adsorbents µGFH (22.4 mg/g) and µTMF (15.4 mg/g) [41], Fe-sericite composite beads (5.78 mg/g) [42], and red mud-modified biochar (5.923 mg/g) [43]. ...
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Granular ferric hydroxide (GFH) is often used for fixed bed adsorbent (FBA) columns in groundwater purification units around the world to remove arsenate contaminations. Groundwater can contain also other toxic (e.g., antimonite and vanadate) and non-toxic oxo-anions (phosphate and silicic acid) that are known to affect FBA lifetimes. Therefore, understanding the breakthrough of toxic compounds intended for removal by FBA is essential to their design, and is important to predict accurately breakthrough curves (BTCs) for FBAs in waterworks to plan future operating costs. Rapid small-scale column tests (RSCCT) and pilot-scale FBA were used to simulate vanadate BTCs for complex groundwater chemistries. The BTCs were simulated successfully using a homogeneous surface diffusion model (HSDM) combining equilibrium chemical adsorption and kinetic mass transfer. Adsorption parameters for various groundwater compositions were predicted using the CD-MUSIC surface complexation model, which was set up for the first time for akaganéite-based granular ferric hydroxide with a competitive multi-solute system. The results indicated that V(V) is less prone to competitive adsorption effects, and use of the homogeneous surface diffusion model to predict the BTCs requires then the kinetic mass transfer Biot number to be used as the only fitting parameter. On the other hand, a concentration overshoot could be observed for the two weaker absorbed oxo-anions arsenate and phosphate because of displacement by the vanadate. Results of pilot scale test column BTCs of vanadate for three waterworks with different groundwater compositions could be favorably extrapolated with a unique Freundlich constant kF of 3.2 derived on basis of the multi-solute CD-MUSIC model, and a unique Biot number of 37 fixed for all three different test sites.
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Adsorption processes have played a central role in water treatment for many years but their importance is on the rise with the continuous discoveries of new micropollutants in the water cycle (pharmaceuticals for example). In addition to the classical application in drinking water treatment, other application fields are attracting increasing interest, such as wastewater treatment, groundwater remediation, treatment of landfill leachate, and so on. Based on the author's long-term experience in adsorption research, the scientific monograph treats the theoretical fundamentals of adsorption technology for water treatment from a practical perspective. It presents all the basics needed for experimental adsorption studies as well as for process modelling and adsorber design. Topics discussed in the monograph include: introduction into basic concepts and practical applications of adsorption processes; adsorbents and their characterisation, single and multi-solute adsorption equilibria, adsorption kinetics, adsorption dynamics in fixed-bed adsorbers and fixed-bed adsorber design, regeneration and reactivation of adsorbents, introduction into geosorption processes in bank filtration and groundwater recharge. According to the increasing importance of micropollutants in the water cycle, particular attention is paid to their competitive adsorption in presence of background organic matter. Clear illustrations, extensive literature references and a useful index make this work indispensible for both scientists and technicians involved in water treatment. © 2021 Walter de Gruyter GmbH, Berlin/Boston. All rights reserved.
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