This is an open access article under the CC BY license: 

 

   

   

Al-Khwarizmi 

Engineering 

Journal 
 

Al-Khwarizmi Engineering Journal, Vol. 19, No. 4, December, (2023) 

P. P. 16- 28 

 

 

 

The Remediation of Congo Red-Contaminated Groundwater by  

using a Permeable Reactive Barrier Through Modified  

Waterworks Sludge MgAl-LDH   
 

Sudad Adil Salih*                    Tariq M. Naife** 
*,** Department of Chemical Engineering/ University of Baghdad/ Baghdad/ Iraq 

                   Corresponding Author *Email: Sudad.Saleh1607m@coeng.uobaghdad.edu.iq 
 **Email: tariq.mohammed@coeng.uobaghdad.edu.iq 

 
 (Received 16 May 2023; accepted 5 July 2023) 

https://doi.org/10.22153/kej.2023.07.001 
 

 

Abstract  

 
This investigation aims to explore the potential of waterworks sludge (WS), low-cost byproduct of water treatment 

processes, as a sorbent for removing Congo Red (CR) dyes. This will be achieved by precipitating nano-sized (MgAl-

LDH)-layered double hydroxide onto the surface of the sludge. The efficiency of utilizing MgAl-LDH to modify 

waterworks sludge (MWS) for use in permeable reactive barrier technology was confirmed through analysis with Fourier 
transform infrared and X-ray diffraction. The isotherm model was employed to elucidate the adsorption mechanisms 

involved in the process. Furthermore, the COMSOL model was utilized to establish a continuous testing model for the 

analysis of contaminant transport under diverse conditions. A strong correlation was indicated, with a coefficient of 

determination (R2) ≥ 0.97, when the model's predictions were compared to experimental values, indicating the accuracy 

of the model. Continuous transport exhibited earlier breakthrough points when the bed depth decreased and the initial 

concentration and flow rate increased. 

 

Keywords: Layered Double Hydroxide, Waterworks Sludge, Congo Red.  

 
 

1. Introduction  

 
Groundwater, being one of the most abundant 

water sources, is often regarded as a more 

dependable option compared to surface water for a 
variety of applications [1]–[3]. The contamination 

of this valuable resource is a significant 

environmental concern, as the majority of 
pollutants resulting from human activities or 

unnatural sources can have long-lasting and 

detrimental effects [4]–[7]. Aromatic molecular 

structures present in dyes pose a considerable 
challenge for biodegradation into environmentally 

benign compounds and can have severe toxicity 

towards various microorganisms [8], [9]. With its 
anionic and acidic properties, CR can act as an 

antifungal therapeutic agent in various fields, such 

as commercial fish hatcheries and animal 

husbandry [10]–[12]. However, it can have adverse 

effects on humans, such as amyloidosis [13]; As a 

result, it has been banned in Europe, the United 
States, Canada, and other parts of the world [14]. 

To guarantee the safe disposal of wastewater, it is 

essential to eliminate CR from it. Several physical 
and chemical methods have been employed for this 

purpose, such as coagulation and flocculation, 

which are used for removing dyes from wastewater  

[15], biological degradation[14], adsorption [16], 
membrane filtration [17], [18], and ultra-chemical 

filtration [1], [19]. Although these methods are 

effective, they have technical limitations such as 
high costs, low processing capacity, and the 

potential for secondary pollution.  

The effectiveness, simplicity, and versatility of 
adsorption make it widely recognized as the 

optimal method for the removal of CR dye. While 

mailto:Sudad.Saleh1607m@coeng.uobaghdad.edu.iq
mailto:tariq.mohammed@coeng.uobaghdad.edu.iq
https://doi.org/10.22153/kej.2023.07.001


Sudad Adil Salih                                          Al-Khwarizmi Engineering Journal, Vol. 19, No. 4, P.P. 16- 28 (2023) 

 

17 

various adsorbents have been explored, including 

activated carbons [20] and natural biosorbents [21], 
they often fail to meet the requirements for CR dye 

removal due to low adsorption capacity, long 

diffusion times, or poor structural stability. 

Investigating advanced adsorbents that can 
efficiently capture CR dye is crucial. Permeable 

reactive barriers (PRBs) have demonstrated the 

potential to restrict and contain contaminant 
migration, protecting water resources. Choosing 

the appropriate material for PRBs is crucial, as it 

must be reactive and possess permeability that 

matches or surpasses that of the surrounding 
aquifer. Furthermore, innovative remediation 

techniques are required to treat groundwater 

contaminated with heavy metals and other 
pollutants [22]–[24].  

Millions of tons of waterworks sludge (WS) are 

generated annually in Europe [8], [9], with the 
potential for a significant increase in the future. 

Although classified as "non-hazardous" under EU 

regulations, sludge disposal in sanitary landfills 

can result in increased costs in some countries. 
Conversely, in other countries, the direct discharge 

of sludge into rivers has caused a significant rise in 

surface water turbidity. This study aims to address 
this issue by developing a novel sorbent. The 

sorbent will be created by coating WS with layered 

double hydroxide (MWS) to efficiently remove CR 
dyes. The efficacy of the composite material will 

be assessed through two main steps: first, by 

determining the mechanisms involved in dye 

removal using XRD and FT-IR analysis, and 
second, by tracking the migration of the dye front 

through a physical column filled with the prepared 

sorbent and mathematically describing this 
movement using solute transport equations. 

 

 

2. Mathematical Model 

2.1 Adsorption Isotherms 

 
The adsorbate concentration in the state of the 

liquid and its concentration on the adsorbent 
surface at a particular temperature are related by 

the isotherm model, which is frequently utilized to 

explain adsorption. The equilibrium concentration 

of the adsorbate in solution (Ce) (mg/L) is shown 
against the amount of adsorbate per unit mass of 

adsorb (qe) (mg/g). This number is typically 

uniformed by the quantity of adsorbent to make 
comparisons with various substances simple. 

Adsorbent concentration is not increasing 

proportionally to the amount of adsorbed material 
per unit mass of adsorbent.This research utilized 

various adsorption isotherm models, and a brief 

overview of these models is presented below. A 
favorable isotherm is one that is upwardly convex, 

indicating that the solid content remains relatively 

high even at low concentrations in the liquid. The 

first non-linear isotherm was introduced by 
Freundlich and Kuster.In order to characterize the 

dispersion of chemicals between the two states of 

matter, Irving Langmuir developed a non-linear 
model in 1916. [25]: 

qe = KfCe

1
n⁄

                                                     … (1) 
 

qe =
qmbCe

1+bCe
                                                    …  (2) 

Where Kf (mg/g)(L/mg)1/n and n are Freundlich 

constants related to adsorption capacity and 

adsorption intensity, respectively. qm (mg/g) and b 
(L/mg) are used to describe the maximum 

adsorption capacity and energy of adsorption, 

respectively. 

 

2.2 Modeling of dissolved contaminants 

 
Three fundamental processes govern the 

transportation of contaminants in the subsurface 
environment, as stated by [26]: molecular 

diffusion, advection, and mechanical dispersion. 

1. Molecular diffusion: Fick's first law defines the 

diffusion of solutes, where the movement of solutes 
is from high concentration regions to low 

concentration regions. The quantity of transported 

solute is proportional to its concentration and can 
be mathematically expressed in one dimension 

[27]. 

F = −Dd (
dC

dx
)                                                  …(3) 

where F refers to solute mass flow per unit area (kg 

/(m2 s)), Dd for diffusion coefficient (m2/s), C for 
solute concentration (mg/L), and dC/dx for 

concentration gradient per unit length. 

Fick's second law [28] should always be applied 

in situations where concentration may evolve over 
time:  

 
∂C

∂t
= Dd

∂2C

∂x2                                                   …  (4) 

Diffusion in porous media is slower than in water 

because the ions must travel along longer paths as 

they pass through mineral-solid grains. 

Furthermore, diffusion can only occur through pore 
holes. To address this, an efficient diffusion 

coefficient can be used [27]:  

D∗ = τDd                                                        … (5) 
where τ is a tortuosity factor and its values ranged 

from 0.01 to 0.5 [27]. 

 

2. Advection: is the process that moves 
contaminants through the groundwater. The rate of 



Sudad Adil Salih                                          Al-Khwarizmi Engineering Journal, Vol. 19, No. 4, P.P. 16- 28 (2023) 

 

18 

advection and the flow rate of groundwater are the 

same. The Darcy velocity (V) (m/s) is the same as 
the actual velocity (Va) (m/s), which is related to 

porosity (n). The advictive flux (Fa) is calculated 

as follows [27]:  

 Fa = VaC =
V

n
C                                             … (6) 

Mechanical dispersion: occurs when water 

containing the chemical(s) flows around the soil 

grains in the aquifer, resulting in mixing. 

Molecules of water actually move more quickly 
and slower than the average linear velocity due to 

three factors: fluid moves faster in the centre of 

pores than at the edges, some molecules follow 
longer discrete paths, and several voids are larger 

than others, allowing faster flow. Mechanical 

mixing appears to happen along the flow path 
because water molecules don’t move at the same 

velocity. This mixing (or dispersion) can dilute the 

solute at the propagating edge of flow through 

longitudinal and transverse dispersions. 
Separating the mechanisms of mechanical 

dispersion and diffusion in swirling groundwater is 

unfeasible. They're categorized together and 
referred to as "hydrodynamic dispersion" as 

follows [27]: 

DL =  αLVL +  D∗                                          … (7) 

Where L  and T stand for longitudinal and 
transverse dispersivities, respectively, the 

coefficients of longitudinal and transverse 

hydrodynamic dispersions are denoted as DL and 
DT(m2/s). 

In the subsurface environment, chemical reactions 

can lead to changes in a compound's properties, 
conversion into a different form, or reaction with 

other chemicals. Isotherms, which consider how 

the concentrations of the reactants impact the 

reaction rate, are widely used to explain these 
processes [29]. Sorption is the most valuable 

chemical reaction in the subsurface environment 

for the transport of inorganic and organic 
impurities. Sorption represents the solute adhering 

to the surfaces of solid particles, causing it to take 

longer to arrive.  

The flow of an individual dissolved component 
into and out of a MWS elemental control volume, 

F, is taken into account by the mass conservation 

equation, which is provided by: 

 −(
∂F

∂x
+

∂F

∂y
+

∂F

∂z
) ∓ r =

∂m

∂t
=

∂(nC)

∂t
                …(8) 

where r is the reaction term, which may be either a 

(+) source or a (-) sink for the solute and m is the 
mass per unit volume.  

Eq. 9 can be written as follows after substitution of 

advective flux (=Vx n C) and dispersive flux                      

(=-nDx
∂C

∂x
): − [

∂

∂x
(VxnC − nDx

∂C

∂x
)] − [

∂

∂y
(VynC −

nDy
∂C

∂y
)] − [

∂

∂z
(VznC − nDz

∂C

∂z
)] ± r =

∂(nC)

∂t
       …(9)                 

By considering a steady flow velocity, dispersion 

coefficient, and porosity, the well-known 

advection-dispersion formula  could potentially be 
utilized to determine the 1 D mass transport of a 

solute in the saturated zone [27]. 

 Dz
∂2C

∂z2 − Vz
∂C

∂z
±

r

n
=

∂C

∂t
                               … (10) 

The specific form of Eq. 11 is determined by the 

outcome term's shape. Perhaps the most frequent 

mass transfer process what occurs in the 
transportation of mass is adsorption, which tends to 

be the main mechanism for the operation of PRBS 

The following equation can be used to determine 
r's value [30]: 

  r = ρb
∂q

∂t
                                                     … (11) 

Eq.11 can be integrated with Eq.15 to obtain the 

following equation [31]: 

 Dz
∂2C

∂z2 − Vz
∂C

∂z
=

∂C

∂t
+

ρb

n

∂(q)

∂t
                      … (12) 

Where ρb is the dry bulk density and q is the solute 
concentration sorbed on the sorbent. The Langmuir 

or Freundlich isotherm model can be used to 

describe the values of q (mg/g) as a function of 

concentration. Eq.12 can be rewritten as follows: 

 Dz
∂2C

∂z2 − Vz
∂C

∂z
= R

∂C

∂t
                                    …(13) 

The retardation factor (R) is used to describe the 
decrease in solute transport in relation to advection. 

The advection-dispersion equation (ADE) can be 

used to determine the one-dimensional mass 

transport of solute in the saturated zone, assuming 
constant flow velocity, dispersion coefficient, and 

porosity. Boundary and initial conditions that 

describe the physical state of the process must be 
provided to fully define the equation. The boundary 

conditions represent the geometry of the flow 

domain and the values of the dependent variable or 

its derivative [32]. 
Numerical models for solute transport are 

useful in designing remedial programs as they 

provide valuable information about mass transport. 
These models divide the flow region into finite 

elements or grid cells, with each element 

representing a bounded portion of the flow region. 
The solution obtained for each element depends on 

adjacent segments as well as a set of auxiliary 

conditions that describe the domain geometry, 

variables, boundary conditions, and initial values. 
Numerous numerical techniques, including the 

boundary element technique,the finite difference 

method, and finite element procedure, are currently 
being produced. Groundwater transport formulas 

are discretized utilizing the finite element method 



Sudad Adil Salih                                          Al-Khwarizmi Engineering Journal, Vol. 19, No. 4, P.P. 16- 28 (2023) 

 

19 

(FEM), which produces a set of algebraic 

differential equations. Mathematical techniques are 
able to be utilized to solve these types of issues 

[33]. In the current work, a partial-differential 

equation (PDE) governing the transient transport of 

CR in the saturated zone (Eq. 13) has been 
calculated using the finite element method 

followed by a solution with COMSOL 

Multiphysics 3.5a. The PDE was solved using the 
"Earth Science module" of the software in the 

"saturated solute transport" option. 

 

2.3 Coefficient of dispersion  

 
To measure the coefficient of hydraulic 

conductivity in the direction of flow, a tracer 

experiment was conducted on a column packed 

with 0.5 m of dry reactive material. Water was 
injected in an upward direction to avoid entrapping 

air in the voids between solid grains. For the tracer 

experiment, one gram of NaCl was dissolved in 
deionized water (1 L), which was subsequently 

injected at flow rates between 5 and 20 mL/min 

into the packed column. NaCl was selected because 

of its accessibility, safety, and simplicity of 
detection.  Electrical conductivities corresponding 

to NaCl concentrations were measured at certain 

time intervals during the experiment, and these 
values were used to determine the coefficient of 

dispersion in the longitudinal direction (DL) using 

the following equation  [34]: 

DL =
1

8
[

(zo−Vt0.16)

(t0.16)0.5 −
(zo−Vt0.84)

(t0.84)0.5
]

2

                  …(14) 

Here, zo represents the bed depth (0.5 m), V is the 

velocity in the voids, and t0.84 and t0.16 are times 
corresponding to 84% and 16% of C/Co, 

respectively. 

 

 

3. Experimental Work 

3.1 Materials and Methods 
 

The research concentrated on CR dyes that were 

procured from the HIMEDIA company in India. To 
prepare the initial dye solution, a specific amount 

of CR was mixed with distilled water (1 liter), 

resulting in a solution with an CR concentration 
(1000 mg/L). A dilution was employed to obtain 

various concentrations of the dye in the water 

samples. To adjust the pH of the samples, drops of 

HCl or NaOH(1 M) were added. The sludge was 
obtained from the Water Treatment (AL-Weihdaa) 

in Baghdad, Iraq. During treatment, alum salts 

were added to the sedimentation tank. The sludge 
was dried for several days and then ground into a 

fine powder.  In addition to characterization using 

FTIR, the hydraulic conductivity of the sludge was 
also measured and found to be low at 0.0245 cm/s. 

This low hydraulic conductivity may result in 

blockages during continuous flow in a PRB. Coarse 

sand was employed in various proportions along 
with the sludge to enhance hydraulic conductivity, 

aiming to overcome the inherent low hydraulic 

conductivity of the sludge. The sand used in the 
experiment had a particle size ranging between 1.7 

and 3.15 mm. 

 

3.2 Modification of WS 

 
To create an affordable sorbent with enhanced 

reactivity, WS was employed as a matrix for 

immobilization, and its surface was subsequently 

coated with nanoparticles of layered double 
hydroxide (Mg/Al-LDH). The procedure involved 

mixing 25 mL each of Magnesium nitrate 

hexahydrate (0.1 M) and Aluminium nitrate 
nonahydrate (0.05 M) and adjusting the pH to 11 

using 1 M NH4OH. WS was added to synthetic 

new functional groups, and the resulting sorbent 

was washed with water until the pH reached 6.5-7. 
Through the application of (Mg/Al)-layered double 

hydroxide (LDH) nanoparticles, the WS underwent 

a transformation, resulting in the formation of 
modified WS (MWS) with a coated surface. XRD 

and FT-IR were utilized to analyze the coating 

method and to find any functional groups in the 
MWS. The efficacy of the MWS in removing CR 

dyes from contaminated water was evaluated 

through analysis of the dye concentration, with the 

experimental methods and setup described in detail 
to ensure accurate measurements. 

 

3.3 Characterization 
 

XRD analysis was conducted using the D/MAX 

2500 V/PC from Rigaku, Japan, to identify the 
coated and virgin WS crystal structures. FT-IR 

analysis was conducted to identify the functional 

groups that improve the sorption capacity of the 
prepared sorbent. The analysis was carried out 

using a Bruker Tensor 27 spectrophotometer with 

the KBr pellet technique, and the spectra were 

recorded in the range of 4000 to 400 cm-1. 

 

3.4 Continuous Study 

 
The reactivity of the filler material in removing 

CR from contaminated water was evaluated using 

a number of column tests. The sorbent's efficiency 

was evaluated based on its ability to eliminate 



Sudad Adil Salih                                          Al-Khwarizmi Engineering Journal, Vol. 19, No. 4, P.P. 16- 28 (2023) 

 

20 

pollutants. A column experiment was performed to 

evaluate the reactivity and hydraulic performance 
of MWS. The column was 2 and 50 cm in diameter 

and height, respectively, with sampling ports (P1 to 

P6) located every 5 cm from the bottom, covered 

by plastic valves. In order to prevent the trapping 
of air between the particles, the MWS was 

carefully introduced into the column, and distilled 

water was slowly introduced from the bottom using 
a peristaltic pump. The tests performed in the 

column lasted 90 hours and throughout that time 

the amount of CR in the effluent water was 

continuously monitored. The samples of water 
were promptly analyzed with the help of a UV-

spectrophotometer [4].  

 

 
Fig. 1.  Details of Continuous Study. 

 

 

4. Results and Discussion 

4.1 Adsorbent characteristics 

 
The XRD spectrum in Fig. 2 shows the crystal 

structure of MWS. In order to compare the 

crystalline structures of the composite sorbent and 
sludge, XRD analysis was conducted on both 

materials, and their profiles are depicted in Fig. 2 

alongside the Joint Committee on Powder 
Diffraction Standards (JCPDSs). The analysis 

indicated that iron oxide, calcite, and silica oxide 

are the primary components of WS. However, the 

MWS XRD pattern showed a new peak at 18.01, 
26.6, and 34.1°, suggesting the existence of Mg/Fe 

crystals. The findings indicate that the MWS 

sorbent's synthesis was successful [35]–[40].  Fig. 
2 displays the infrared spectra of WS, MWS, CR 

dye, and the sorbent after adsorption within the 400 

to 4000 cm-1 range. The significant peak at 3491 

cm1 represents the stretching vibration of inter-

lamellar water-linked -OH groups, O-H groups of 
adjacent layers, and physically adsorbed water. 

Bound H2O has been detected demonstrated by the 

shift at 1648 cm-1. 

 The relationship with CR is confirmed by the 
Raman spectra of -OH at 3491 cm-1. O-M-O and 

M-O (where M is a metal) vibrations in the lattice 

frequently correspond to the peak that is nearest to 
531 cm-1. The effective modification of WS is 

further demonstrated by the identification of a new 

peak at 1348 cm1 in the MWS compared with WS, 

that corresponds to the CO32's in-of-plane 
vibration band with an asymmetric stretch 

absorption band. After CR adsorption, two separate 

peak shapes near 1080 and 1159 cm-1, that relate 
to the vibrations of the S=O and aromatic ring 

structures of the CR, accordingly, were observed. 

These results indicate that coated WS surfaces are 
successful in adsorbing CR.  

 

4.2 Sorption Isotherm Models 

  
When equilibrium occurs in the procedure of 

adsorption, the adsorption isotherm can potentially 
be utilized to determine how CR are distributed 

throughout the MWS and water phases. Moreover, 

this isotherm can also be used to find out the 
highest amount of adsorbate that can be adsorbed 

and the attraction of the adsorbent towards the 

adsorbate  [41], [42]. In the present study, two 
commonly utilized sorption isotherm models—

Langmuir and Freundlich—were utilized to 

correlate with the experimental data from research 

on adsorption on MWS. The experiments were 
conducted under optimal conditions with selected 

contaminants at varying concentrations. During the 

preparation process, mixing speed and time were 
critical factors that influenced the hydraulic 

conductivity of the sorbent and its suitability for 

continuous use. The appropriate isotherm model 

was utilized to determine the retardation factor in 
the advection-dispersion formula that clarifies the 

movement of CR along PRB. For nonlinear 

regression calculations, the Freundlich and 
Langmuir isotherm models were utilized, and the 

parameter values obtained from these models are 

displayed in Table 2. Depending on the R2 and SSE 
numbers, it was found that the Langmuir model 

was more appropriate compared to the Freundlich 

model.  

The Langmuir constants have been determined 
to be 0.08 L/mg. The match between the 

experimental results and the sorption equilibrium 

models can be observed in Fig. 3. The highest 



Sudad Adil Salih                                          Al-Khwarizmi Engineering Journal, Vol. 19, No. 4, P.P. 16- 28 (2023) 

 

21 

adsorption capacity of MWS for CR was found to 

be 23.57 mg/g. This finding indicates higher 

adsorption capacity due to CR bind with the 

MSW more effectively. 
 

 
 

 
20 (Degree) 

 
  

Fig. 2.  X-ray diffraction (A) and FT-IR analysis pattern (B) for crystalline structure of WS, MWS, CR, and 

sorbent after adsorption. 

 

 

4.3 Longitudinal Dispersion Coefficient  

 
In columns packed with a 1:15 proportion of 

sludge and sand, the aim of the present 

investigation was to explore the relationship 
between average pore velocity (V) and longitudinal 

dispersion coefficient (DL). To attain laminar flow 

conditions, flow rates were adjusted to 5, 10, 15, 

and 20 mL/min, ensuring that Reynolds numbers 

(Re) were maintained below 1-10. Based on the 
data obtained from the experiment, as shown in 

Fig. 3, it was observed that there exists a linear 

association between DL and V. 

 𝐷𝐿 = 13.953𝑉 + 0.046                             … (15) 

 

 

0

0.5

1

1.5

2

2.5

3

0 20 40 60 80 100 120 140 160

S
o
rb

ed
 q

u
a
n

ti
ty

 (
q

t,
 m

g
/g

)

Ce (mg/L)

(A)

 Langmuir model

Freundlich model



Sudad Adil Salih                                           Al-Khwarizmi Engineering Journal, Vol. 19, No. 4, P.P. 16- 28 (2023) 

 

22 

 
 

Fig. 3. The experimental results of MWS and specifically the sand ratio (1:15), were compared with various 

isotherm models (A), and the longitudinal dispersion coefficient (B). 

 

 
The relationship between DL and V found in 

this study agrees with the relationship expressed in 

Equation 16. In this equation, the  

The proportionality factor αL links dispersion and 
velocity in the longitudinal direction and has a 

dimension of length. This relationship is 

additionally influenced by the tortuosity (𝜏), which 
evaluates the impact of the water transition across 

a porous mediam which is influenced by the 

porosity of the medium (n). 

𝜏 = 𝑛𝑚−1                                                     …  (16) 

The value of the parameter tortuosity (𝜏), that is                    

affected by the material's porosity (n), is essential 

in explaining how the shape of the flow route 
influences the movement of water  in a porous 

medium. Eq. 16, where the constant value of m 

relies on the medium's aggregation phase, 
illustrates the connection between and n. In a 

laboratory experiment, Archie (1942) found a 

value of 1.3 for unpacked sand, 1.8-2 for 

consolidated sandstone, and 1.3-2 for partly 
established sand. Using the similarity between Eq. 

15 and Eq. 16, the longitudinal dispersivity (αL)                

can be calculated for the PRB medium 
(Sludge:sand (1:15)). 

 

4.4 Column Tests 
  

A permeable reactive barrier (PRB) made of a 
sludge-sand (1:15) mixture was evaluated for its 

ability to remove CR contaminants from aqueous 

solutions while maintaining an acceptable 

hydraulic conductivity coefficient. The study             
utilized a column setup (Fig. 1) and considered the 

rate of flow, concentration of chemical species, and 

bed depth. The study observed the normalized 
concentration (C/Co) of the adopted contaminants 

with time at ports P1-P6 for a duration of up to 100 

hours, as well as the variation in hydraulic 

conductivity coefficient (K) during the operation 

time. The advection-dispersion-sorption equation, 

which was numerically solved using the finite 
element method and the COMSOL program, was 

used to theoretically approximate the experimental 

breakthrough curves. 
 

Table 2, 

Isotherm model constants with statistical analysis for 

sorption CR. 

 

 
Figure 4 depicts the outcomes of evaluating the 

normalized concentrations of CR at effluent ports 

P1 to P6 for up to 100 hours at a flow rate of 5 
mL/min.  

 

y = 13.953x + 0.046

R² = 0.9898

0

0.2

0.4

0.6

0.8

1

1.2

0 0.02 0.04 0.06 0.08

D
L

 (
c
m

2
/s

) 

velocity (cm/sec) 

(B)

               Adsorbent MWS  : sand 

(1:15) Model Parameter 

 

 

Langmuir 

 

 

naxq 2.604 

b 0.068 
2R 0.976 

SSE 0.075 

 

 

Freundlich 

 

 

fk 0.456 

N 2.810 
2R 0.909 

SSE 0.298 



Sudad Adil Salih                                           Al-Khwarizmi Engineering Journal, Vol. 19, No. 4, P.P. 16- 28 (2023) 

 

23 

 

 

 
 
 

Fig. 4. Relationship between experimental findings 

and COMSOL results for the normalized 

concentration of CR under the influence of the initial 

concentration at various ports. 

 

 
The research discovered that the permeable 

reactive barrier (PRB) impedes the spread of CR, 
and the concentration gradient has the potential to 

impact the saturation rate of the bed. The curve's 

shape is less prominent at lower influent 
concentrations due to sluggish sorption, while 

raising the influent concentration causes a steeper 

slope, leading to saturation of the sorbent in a 

shorter period. A low concentration gradient 
prolongs the propagation of chemical species 

through the pores, extending the time to reach 

saturation.  
The investigation revealed that the 

breakthrough time (tb) of 5% and saturation time 

(ts) of 90% rise with decreasing normalized 
concentration (C/Co), affecting the adsorbed 

quantities of the contaminant at breakthrough and 

saturation points within the bed. With higher 

influent concentrations, the saturation of the 
adsorption process occurs more rapidly, leading to 

a decrease in breakthrough time. This phenomenon 

can be attributed to the presence of a larger 

concentration gradient, which intensifies the 
driving force for mass transfer of contaminant 

molecules. Consequently, the adsorption sites 

become covered more quickly. Additionally, the 
study observed that the adsorption capacity did not 

exhibit a proportional increase with rising influent 

concentration [43]–[45]. 

The purpose of the study was to examine how 
varying water flow rates affect the ability of a 

sorbent barrier to adsorb CR. By accounting for 

normalized concentrations at various points in the 
column using a variety of flow rates (5, 10, and 15 

mL/min) and a fixed CR concentration of 10 mg/L, 

breakthrough curves were obtained. The findings 
demonstrated that with an increase in flow rate, the 

breakthrough time decreased and the curves 

exhibited a steeper slope. These observations 

suggested that the contaminated solution had not 
reached equilibrium within the column due to the 

reduced residence time caused by the higher flow 

rate. The faster flow rate also improved solute 
transport and increased sorption by creating a 

concentration gradient at the interface between the 

liquid and sorbent. However, the higher flow rate 
resulted in reduced solute adhesion to the sorbent 

and lower sorption efficiency, which could cause 

desorption of some adsorbed contaminant 

molecules, leading to an earlier breakthrough time. 
As a result, a lower flow rate was found to be more 

effective in adsorbing contaminants in the fixed 

bed due to its higher adsorption capacity. The study 
concluded that optimizing the water flow rate is 

critical for achieving maximum sorption efficiency 

in fixed bed adsorption systems [44], [46]–[48]. 

 

 
 

 



Sudad Adil Salih                                           Al-Khwarizmi Engineering Journal, Vol. 19, No. 4, P.P. 16- 28 (2023) 

 

24 

 
 
Fig. 5. Relationship of experimental data and 

COMSOL results indicates a normalized 

concentration of CR with the impact of flow rate at 

various ports . 

 

 

In order to examine the impact of bed depth on 

sorption capacity, Figures 4 and 5 were used. The 
findings demonstrated the same influent 

concentration and flow rate, adding more sorbent 

increased sorption capacity. The usual S-shaped 
breakthrough curves for CR adsorption indicate 

that as the bed depth increased the breakthrough 

time decreased and the effluent quantity increased. 
In continuous adsorption experiments, the sorbent 

reached an exhaust time at which it could no longer 

adsorb solute molecules, represented by a C/Co of 

0.9. The exhaust time was found to increase with 
increasing bed height, indicating that higher bed 

depths provided more active sites for adsorption. 

More time was provided for the adsorbate 
molecules to diffuse into the pores of the adsorbent 

particles, resulting in more contaminant molecules 

being adsorbed. As a result, the effluent volume 

increased with increasing exhaust time due to the 
higher bed depth. However, the adsorption capacity 

for contaminants decreased with increasing bed 

height due to two reasons: firstly, at higher bed 
heights, all binding sites become inaccessible to 

adsorbate molecules because of the overlap of 

active sites, resulting in some particles being 
inadequately utilized. Secondly, lower bed depths 

were found to be more favorable for contaminant 

adsorption capacity, which is consistent with the 

findings of previous studies. Therefore, it is crucial 
to use the entire capacity of an adsorbent for it to 

be effectively utilized in industrial applications 

[48]. 

 

4.5 Numerical Modelling 

 
The study employed COMSOL Multiphysics 

3.5a (2008) software to solve the advection-
dispersion equation. The software incorporates 

several modules, such as Earth Science, Solute 

Transport, Saturated Porous Media, and Transient 
Analysis. Simulation processes were established by 

inputting system dimensions and attributes, 

including boundary and initial conditions, as 

specified in Table 3. One-dimensional 
measurements of column bed parameters and 

constants were used to characterize solute 

transport. The comparison between simulated 
results of contaminant transport and experimental 

measurements taken at different time intervals for 

a specific influent concentration and flow rate, 

revealed a high level of consistency. The 
coefficient of determination (R2) exceeded 0.97, 

indicating strong agreement between the model 

predictions and experimental data. 
 
Table 3. 

Adopted data used for simulating CR transport in 

columns. 
Item Parameter Value 

Aquifer 

characteristics 

Aquifer bed depth  (cm) 50 

)AnPorosity of aquifer ( 0.38 

Longitudinal dispersivity 

), cmLα( 
13.953 

)3Bulk density (g/cm 1.677 

Initial 

condition 

Initial concentration 

(mg/l) 
zero 

 

 

5. Conclusions  
 

This study aimed to investigate utilizing WS as 

a low-cost byproduct for water treatment 

procedures and decontaminating groundwater from 

CR. To achieve this goal, the WS sludge was 
modified using MgAl-LDH-sand to create a 

permeable reactive barrier. The tests demonstrated 

successful remediation of the CR. Langmuir 
modeling revealed that the modified sludge had 

exceptional sorption capacity, with a maximum 

adsorption capacity of 23.575mg/g. To accurately 
predict the behavior of different CR concentrations 

and bed depths, a mathematical model was utilized. 

The model was solved using the COMSOL 

software, and the accuracy of the results was 
confirmed with an R2 value greater than or equal 

to 0.97. These findings suggest that modified WS 

has the potential to be a cost-effective and efficient 
solution for treating groundwater contaminated 

with CR dye. 

 

 



Sudad Adil Salih                                           Al-Khwarizmi Engineering Journal, Vol. 19, No. 4, P.P. 16- 28 (2023) 

 

25 

Acknowledgements  

 
We would like to express our gratitude for the 

technical assistance and support provided by the 

Chemical Engineering Department at the 

University of Baghdad, Iraq, during the course of 
this research. 

 

 

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 (2023) 16-28، صفحة 2، العدد19مجلة الخوارزمي الهندسية المجلد                               سداد عادل صالح                              

 

28 

 

 

 

تحقيق تنقية مياه الجوف الملوثة بمادة الكونغو الحمراء باستخدام حاجز مرشح نافذ بواسطة 

 الحمأة المعدلة من محطات المياه
 

 سداد عادل صالح*            طارق محمد نايف **
 الهندسة / جامعة بغداد *،**قسم الهندسة الكيمياوية / كلية

  Sudad.Saleh1607m@coeng.uobaghdad.edu.iq*البريد االلكتروني:
  tariq.mohammed@coeng.uobaghdad.edu.iq**البريد االلكتروني:                                                         

 

 
 

 الخالصة 
 

، وهي (CR) كمادة امتزازية إلزالة صبغة الكونغو الحمراء (WS) تهدف هذه الدراسة إلى استكشاف إمكانية استخدام الحمأة المستخدمة في محطات المياه

ئي الطبقات بحجم مادة رخيصة تتولد كنتيجة فرعية لعمليات معالجة المياه. سيتم تحقيق ذلك من خالل ترسيب مركب هيدروكسيد المغنيسيوم واأللومنيوم الثنا
أة المستخدمة في تقنية الحاجز المرشح نانو على سطح الحمأة. تم تأكيد كفاءة استخدام مركب هيدروكسيد المغنيسيوم واأللومنيوم الثنائي الطبقات لتعديل الحم

. تم استخدام نموذج إيزوثيرما النجمير لتوضيح آليات االمتزاز المشاركة في العملية. باإلضافة إلى ذلك، تم  XRDو FTIR النافذ من خالل تحليلها باستخدام 

 (R2) متنوعة. أشارت النتائج إلى ترابط قوي، مع معامل تحديدإلنشاء نموذج اختبار مستمر لتحليل نقل الملوثات تحت ظروف  COMSOL استخدام نموذج

مق السرير، وتزيد ، عند مقارنة توقعات النموذج بالقيم التجريبية، مما يشير إلى دقة النموذج. أظهر نقل المستمر نقاط اختراق أّولية سابقة عندما تقل ع0.97 ≤

 . التركيز األولي ومعدل التدفق

 
 

 

 

 
 

 

 
 

 

 

 
 

 

 
 

mailto:Sudad.Saleh1607m@coeng.uobaghdad.edu.iq
mailto:tariq.mohammed@coeng.uobaghdad.edu.iq