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Experimental design of wastewater treatment with electro-coagulation
Article  in  Management of Environmental Quality An International Journal · January 2014
DOI: 10.1108/MEQ-03-2013-0020
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For Peer Review
 
 
 
 
 
 
Experimental Design of Wastewater Treatment with Electro-
coagulation 
 
 
Journal: Management of Environmental Quality 
Manuscript ID: MEQ-03-2013-0020.R2 
Manuscript Type: Research Paper 
Keywords: 
paper mill wastewaters, electro-coagulation, Response Surface 
Methodology (RSM), statistical experimental design 
 
 
 
Management of Enviromental Quality
For Peer Review
Experimental Design of Wastewater Treatment with 
Electro-coagulation 
 
 
Abstract 
Purpose – The purpose of this study is to investigate the batch treatment of pulp and paper mill 
wastewater using electro-coagulation. 
Design/methodology/approach – Statistical experimental design was used to investigate the effect 
of initial pH, current density and temperature. Experiments were planned to obtain the maximum 
amount of information in the fewest number of runs. Minimum-maximum values of current density, 
initial pH, temperature of medium were selected as 9-25 mA cm
-2
, 5-9, 25-50 
o
C respectively. A 
total number of 20 experiments including 8 factorial points, 6 axial points and 6 replicates in centre 
points were carried out and experimental data were collected. Optimum operating parameters were 
determined by evaluating experimental results in MATLAB 7.9
®
. 
Findings – According to the results, the optimum values of current density, initial pH and 
temperature of medium are determined as 14.12 mA cm
-2
, 8.22, and 34.21 
o
C respectively. 
 
Practical implications – Many researches about different techniques including physical, chemical 
and biological methods have been done on the subject of pulp and paper wastewater treatment. In 
Physical and chemical processes low molecular weight compounds are not removed efficiently, also 
these methods are quite expensive. Electrochemical degradation has an advantage of removing even 
the smallest colloidal particles compared with traditional flocculation and coagulation. 
Originality/value – Complete removal of pollutants, less sludge generation, simple process design 
and easy operation are standard features of the electro-coagulation (EC) and it comes forward as 
one of the promising techniques. 
Keywords: Paper mill wastewaters, electro-coagulation, Response Surface Methodology (RSM), statistical experimental design. 
Paper type: Research paper 
 
 
Introduction 
 
High consumption of water is one of the most important environmental apprehensions in pulp and 
paper industry. It is the third major water consuming process after the primary metals and the 
chemical industries. Contents and properties of the wastewater depends upon the types of raw 
material used, process technology applied, recycle of the recovered effluent inside the process and 
the amount of water to be used in the particular process (Sridhar et al., 2011). Different 
combinations of unit processes used in pulp and paper manufacturing causes differences on 
characteristics of the wastewater and this leads to a complication about treatment methods. (Wong 
et al., 2006). Pollutant content of wastewater is characterized by biochemical oxygen demand 
(BOD), chemical oxygen demand (COD), suspended solids (SS), toxicity and colorants. These 
parameters cause some effects on microorganismgrowth in sludge, thermal impacts, colour 
problems and a loss of both natural balance and aesthetic beauty in the environment (Khansorthong 
and Hunsom, 2009). 
 
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Many researches which apply different techniques by using physical, chemical and biological 
methods have been realized for pulp and paper wastewater treatment systems and these techniques 
have been applied with variety of shortcomings. Physical and chemical processes are only able to 
remove high molecular weight chlorinated lignin, colour, toxicants, SS and COD. Both BOD and 
low molecular weight compounds are not removed efficiently, besides these methods are quite 
expensive (El-Ashtoukhy et al., 2009). Although different methods such as biological treatment, 
wet oxidation, ozone treatment and chemical coagulation was carried out for pulp and paper mills 
wastewater treatment in many studies, there are some drawbacks about these processes. 
In the biological processes, the lignin and its derivatives show high resistance to degradation. The 
inhibition potential of phenol and the presence of other organic and inorganic compounds are also 
major drawbacks of the process. Despite it is found that catalytic and non-catalytic wet air oxidation 
reduces COD in a large extent, high energy requirement and the use of high-pressure reactors and 
associated equipment make the wet air oxidation wastewater unviable and uneconomical as a 
treatment method for large volume of wastewaters. Chemical coagulation is also studied using 
alum, ferric chloride, ferric sulphate and lime. Alternatively, electrochemical technologies can be 
efficiently applied to the treatment of pulp and paper mills wastewater and shows improved 
performance over conventional coagulation method. Electrochemical degradation has an advantage 
of removing even the smallest colloidal particles compared with traditional flocculation and 
coagulation. The small particles have a greater probability of being coagulated due to the electric 
field that sets them in motion (Ma et al., 2007). Complete removal of pollutants, less sludge 
generation, simple process design and easy operation are standard features of the EC and it appears 
as one of the promising techniques (Sridhar et al., 2011). Anodic dissolution of a metal electrode 
(usually made of iron or aluminium), with the simultaneous formation of hydroxyl ions and 
hydrogen gas, coagulation and flocculation of suspended solids and colloidal particles by hydroxyl 
ions take place during EC process (Terrazas et al., 2010). 
 
Response Surface Methodology (RSM) is a combination of mathematical and statistical techniques 
based on the fit of a polynomial equation to the experimental data. The polynomial equation must 
describe the behaviour of a data set with the objective of making statistical predictions. When a 
response or a set of responses of interest are influenced by several variables RSM can be used 
efficiently for the objective of simultaneous optimization of the levels of these variables for 
attaining the best system performance (Bezerra et al., 2008). 
 
In the present work, treatment of pulp and paper mill wastewaters with electro-coagulation was 
investigated. A plan was made for experiments in order to extract the maximum amount of 
knowledge in the fewest number of runs. Statistical experimental design was used to investigate the 
effect of initial pH, current density and temperature. 
 
 
Theory of Electro-coagulation 
 
Electro-coagulation is a complex process involving many chemical and physical phenomena that 
use anodic dissolution of consumable metal electrodes to supply ions into the wastewater stream 
(Mollah et al., 2004). Coagulant is generated by the electro-dissolution of a sacrificial anode, 
typically made of aluminium or iron in the EC process. Suspended pollutants are effectively 
destabilized by the introduction of metal ions. Besides, in the proper pH range, aluminium cations 
polymerizes into Aln(OH)3n by the generation of hydroxide species and this results in entrapment or 
adsorption of the pollutants. Finally, these solids are separated by sedimentation or by flotation. 
Another advantage of this method is the possibility of using the hydrogen gas generated on the 
cathode for latter purposes as well as for agitation (Meas et al., 2010). 
 
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Generally, EC can be summarised in six main process steps occurring: (i) migration to an oppositely 
charged electrode (electrophoresis) and accumulation due to charge neutralization; (ii) formation of 
precipitate by the cation or hydroxyl ion (OH
−
) and the pollutant; (iii) formation of hydroxide by the 
interaction of the metallic cation with OH
−
, which has high adsorption properties thus bonding to 
the pollutant (bridge coagulation); (iv) formation of larger lattice-like structures by the hydroxides 
and sweeps through the water (sweep coagulation); (v) oxidation of pollutants; (vi) removal by 
electro-flotation or sedimentation and adhesion to bubbles (Katal and Pahlavanzadeh, 2011). 
 
EC mechanism is highly influenced by the contents of the aqueous medium, especially conductivity 
is essential. Furthermore, EC process depends on other characteristics such as pH, particle size, and 
chemical constituent concentrations (Mollah et al., 2001). 
 
At low pH values, the electrolytic dissolution of the aluminium anode produces the cationic 
monomer species such as Al
3+
 and Al(OH)
2+
.At proper pH values are transformed initially into 
Al(OH)3 and finally polymerized to Aln(OH)3n according to the following reactions: 
 
 ( )
 - (1) 
 ( )
 ( ) 
 
 (2) 
 
 
 (3) 
 
However, pH of the aqueous medium may affect the system with the presence of other ionic 
species, such as Al(OH)
2+
, Al2(OH)2
4+
 and Al(OH)4 
−
. 
 
Iron upon oxidation in an electrolytic system produces iron hydroxide, Fe (OH)2 or Fe (OH)3. Two 
mechanisms have been proposed for the production of Fe(OH)n (Mollah et al., 2001). 
 
 Mechanism 1 
Anode: 
4Fe(s) 4Fe
2+
 (aq) + 8e
-
 (4) 
 ( )
 ( ) ( ) 
 
 (5) 
Cathode: 
 
 
 
- (6) 
Overall: 
 ( ) ( ) (7) 
 
 Mechanism 2 
Anode: 
 ( ) ( )
 - (8) 
 ( )
 ( )
-
 ( ) ( ) (9) 
 
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Cathode: 
 
- ( ) 
-
 (10) 
Overall: 
 ( ) ( ) (11) 
 
 
Experimental Design 
 
RSM is a statistical technique for experimental designs, model developments, evaluating the effects 
of several independent variables on dependent variables and searching optimum conditions for 
desirable responses. The interactions of possible effective parameters can be evaluated with a 
limited number of designed experiments with RSM (Wang et al., 2007). RSM can be used as an 
optimization technique with the following application stages: (1) Carrying out screening studies and 
delimitation of the experimental region according to theobjective of the study and the experience of 
the researcher and the selection of independent variables which have major effects on the system; 
(2) carrying out the experiments in accordance with the chosen experimental design method and 
the experimental matrix generated; (3) fitting of a polynomial function to the experimental data 
obtained by the mathematic– t ti tic tr tm t; th v u tio of th mod ’ fitness to the 
data; (5) investigation of the necessity and possibility of performing a displacement through the 
direction of the optimal region; and (6) obtaining the optimum values of each studied independent 
variable (Bezerra et al., 2008). 
 
The central composite design (CCD), which is a form of RSM, was selected for the optimization of 
the parameters. CCD contains inserted factorial or fractional factorial designs with centre points that 
are enhanced with a group of axial (star) points that allow estimation of curvature. CCD constantly 
contains star points two times more that the factors in the design. The star points represent new low 
and high limit values (low and high) for each factor in the design (Hanrahan and Lu, 2006). 
 
To analyze a process or system which has a response y, depends on the input factors x1, x2,..., xk, the 
relationship between the response and the input process parameters (independent variables) are 
described as 
 
y = f (x1, x2, . . . , xk) + ε (12) 
 
Where f is the real response function which has an unknown format, and ε is the residual error 
which describes the differentiation that can be included by the function f. Coefficient of 
determination (R
2
), analysis of variance (ANOVA) and response plots were used for analysing the 
results. The second-order polynomial Equation (13) was fitted to the experimental data using a non-
linear regression method and to identify the relevant model terms using a statistical software, 
Design-expert V7.0. Taking into consideration all the linear terms, square terms and linear by linear 
interaction points, the quadratic response model can be expressed as 
 
 ∑ ∑ 
 ∑ (13) 
 
where β0 represents offset , βi is the linear effect coefficient of the input factor xi, βii symbolize the 
quadratic effect of input factor xi and βij characterizes the linear by linear interaction effect between 
the input factor xi and xj (Kumar et al., 2009) . 
 
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Material and Method 
 
Experiments were conducted in batch process using a 2 L electro-coagulation reactor made up of 
flex-glass. Dimensions of electrodes were 45 mm x 53 mm x 3 mm. Four electrodes with 69 cm
2
 
active surface area were positioned in mono-polar parallel arrangement with a gap separation 
between them of 10 mm. In parallel connected anodes and cathodes the current is divided between 
all the electrodes in regard to the resistance of the individual cells. In parallel connections, a lower 
potential difference is required than the serial connections (Kobya et al., 2007). The electrodes were 
connected to a DC power supply (EMGE 2012) and the experiments were carried out under 
constant current conditions. NaCl was added to the wastewater as supporting electrolyte. In each 
run, 1000 mL of real wastewater solution was fed into the electrochemical reactor. The 
characteristics of the wastewater are shown in Table 1. A magnetic stirrer (Chiltern Hotplate 
Magnetic Stirrer HS31) was used to maintain uniform concentration condition in the reactor. The 
electrode plates were cleaned with HCl and distilled water solution prior to each experiment. 
 
 
 
Figure 1. Schematic diagram of the experimental set-up 
 
Table 1. Characteristics of the wastewater 
Characteristics Value 
Turbidity (FTU) 130.15 
pH 7.23 
Suspended Solids (mg/L) 48.8 
Conductivity (mS/cm) 3.51 
 
All experiments were performed under 1.2 gL
-1
 supporting electrolyte concentration and 25 minutes 
electrolysis time conditions. In order to optimize parameters, the experiments were carried out at 
varying current density, initial pH and temperature. Samples were taken at the end of the electro-
coagulation process and analyzed for turbidity removal with water analysis system (Orbeco-Hellige 
Model 975-MP). Schematic diagram of the experimental set-up is shown in Figure 1. 
 
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RSM was used to determine the relation between turbidity removal and operating parameters such 
as current density (x1), pH0 (x2) and temperature (x3). CCD of RSM with 3 factors was applied 
using Design-Expert 7.0
®
 statistical software. Operating ranges of the parameters are presented in 
Table 2. 
 
Table 2. Operating ranges of parameters for electro-coagulation process 
Parameter Minimum Value Maximum Value Centre Point 
x1 Current density (mA cm
-2
) 9 25 17 
x2 pH0 5 9 7 
x3 Temperature (
o
C) 25 50 37.5 
 
A total number of 20 experiments including 8 factorial points, 6 axial points and 6 replicates in 
centre points were performed using minimum, centre and maximum values of the operating 
parameters in order to obtain the model that gives the relationship between dependent variable 
turbidity removal and the independent variables current density, initial pH, temperature and also to 
find the optimum values of operating parameters for maximum turbidity removal. 
 
 
Results and Discussion 
 
According to CCD of experiments using Design-Expert 7.0
®
 software, an experimental scheme was 
obtained and the turbidity removal result of performed experiments was given with experimental 
conditions of operating parameters in Table 3. 
 
A nonlinear regression method was used to fit the experimental data by a second-order polynomial 
equation to determine model terms using Minitab 14.0 package program. The second order 
polynomial equation for turbidity removal is given by Equation (14). 
 
 - 7 . 7 7 . .9 - . 
 - .79 
 - . 
 (14) 
 
The statistical significance of the models was justified through ANOVA for polynomial model with 
95 % confidence level (α . . The quality of the fit polynomial model was expressed by the 
coefficient of determination R
2
. The value of the correlation coefficient (R
2
 = 0.917) indicates that 
only 8.3 % of the total variation could not be explained by the empirical model. The P value (P = 
0.000) of Equation (14) according to the regression analysis results of ANOVA implies that the 
second-order polynomial model fitted the experimental results well. Results of Minitab regression 
analysis are shown in Table 4. 
 
Optimum operating parameters were determined by evaluating experimental results in 
MATLAB7.9
®
. According to this study, the optimum values of current density, initial pH and 
temperature for 98.48 % turbidity removal are found as 14.12 mA cm
-2
, 8.22, 34.21 
o
C respectively. 
 
 
 
 
 
 
 
 
 
 
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Table 3. Design of experiments and results for electro-coagulation treatment 
 
Run 
x1 x2 x3 y 
Current density 
(mA cm
-2
) 
pHo Temperature 
(
o
C) 
Turbidity removal 
(%) 
1 17.00 7.00 37.50 88.78 
2 25.00 5.00 50.00 12.38 
3 9.00 9.00 25.00 86.47 
4 17.00 7.00 37.50 86.32 
5 17.00 7.00 37.50 87.62 
6 9.009.00 50.00 73.10 
7 9.00 5.00 25.00 57.96 
8 9.00 5.00 50.00 10.07 
9 25.00 9.00 50.00 58.80 
10 17.00 7.00 37.50 91.31 
11 25.00 9.00 25.00 75.33 
12 25.00 5.00 25.00 13.14 
13 17.00 7.00 37.50 92.77 
14 17.00 3.64 37.50 3.92 
15 17.00 7.00 16.48 58.80 
16 30.45 7.00 37.50 90.08 
17 17.00 7.00 37.50 93.19 
18 3.55 7.00 37.50 74.02 
19 17.00 7.00 58.52 40.20 
20 17.00 10.36 37.50 76.02 
 
 
Table 4. Regression analysis results 
Predictor Coef SE Coef T P 
Constant -357.10000 47.51000 -7.52 0.000 
x1 1.87400 1.55200 1.21 0.249 
x2 78.80000 10.06000 7.84 0.000 
x3 6.91300 1.38200 5.00 0.000 
x1
2
 -0.06616 0.04437 -1.49 0.160 
x2
2
 -4.78790 0.71070 -6.74 0.000 
x3
2
 -0.10075 0.01817 -5.55 0.000 
Analysis of Variance 
Source DF SS MS F P 
Regression 6 16649.3 2774.9 23.90 0.000 
Residual Error 13 1509.2 116.1 
Total 19 18158.6 
 
 
Based on the results obtained, the graphical representation (Figure 2, 3 and 4) was constructed. 
 
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Figure 2. Surface and contour plot for turbidity removal as a function of current density and pHo at 34.21 
o
C. 
 
 
Figure 3. Surface and contour plot for turbidity removal as a function of current density and temperature at 
pH 8.22. 
 
 
 
Figure 4. Surface and contour plot for turbidity removal as a function of pHo and temperature at 14.12 mA 
cm
-2
. 
 
T
u
rb
id
it
y
 r
em
o
v
al
 (
%
) 
pHo 
Current density (mA cm
-2
) 
T
u
rb
id
it
y
 r
em
o
v
al
 (
%
) 
Current density (mA cm
-2
) 
Temperature (
o
C) 
T
u
rb
id
it
y
 r
em
o
v
al
 (
%
) 
Temperature (
o
C) 
pHo 
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Conclusion 
 
CCD for RSM with 3 factors was applied to the electro-coagulation process successfully. Three 
dimensional second-order polynomial model accurately describes the effects of the factors on the 
process response. The efficiency of the process is influenced highly by the current density, 
temperature and initial pH values of the medium. Optimal value of these parameters were 
determined as 14.12 mA cm
-2
, 8.22, 34.21 
o
C respectively, and applied to the wastewater for 
98.48% turbidity removal. 
 
 
References 
 
Bezerra, A., M., Santelli, R., E., Oliveira, E., P., Villar, L. and S., Escaleira, L.A. (2008), “Response surface methodology 
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El-Ashtoukhy, E.-S.Z., Amin, N.K. and Abdelwahab, . 9 , “Tr tm t of p p r mi ff u t i b tch-stirred 
 ctroch mic t k r ctor”, Chemical Engineering Journal, Vol. 146, pp. 205-210. 
Hanrahan, G. d Lu, K. , “ pp ic tio of f ctori d r po urf c m thodo o i mod r p rim t d i 
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K t , R., P h v z d h, . , “I f u c of diff r t combinations of aluminum and iron electrode on 
 ctroco u tio ffici : pp ic tio to th tr tm t of p p r mi w t w t r”, Desalination, Vol. 265, pp. 199-205. 
Kh ortho , S. d u om, M. 9 , “R m di tio of w t w t r from pu p d p p r mill industry by the 
 ctroch mic t ch i u ”, Chemical Engineering Journal, Vol. 151, pp. 228-234. 
Kobya, M., Bayramoglu, M. And Eyvaz, M. 7 , “T ch o-economical evaluation of electrocoagulation for the textile 
w t w t r u i diff r t ctrod co ctio ”, Journal of Hazardous Materials, Vol. 148, pp. 311-318. 
Kumar, M., Ponselvan, F.I.A., Malviya, J.R., Srivastava, V.C. and Mal , I.D. 9 , “Tr tm t of bio-digestereffluent by 
 ctroco u tio u i iro ctrod ”, Journal of Hazardous Materials, Vol. 165, pp. 345-352. 
M , ., W , B. d W , Y. 7 , “ pp ic tio of mo bd um d pho ph t modifi d k o i i ctrochemical 
tr tm t of p p r mi w t w t r”, Journal of Hazardous Materials, Vol. 145, pp. 417-423. 
M , Y., R mir z, J. ., Vi o , M. . d Ch pm , T.W. , “I du tri w t w t r tr t d b ctroco u tio ”, 
Electrochimica Acta, Vol. 55, pp. 8165-8171. 
Mo h, M.Y. ., Sch ch, R., P r , J.R. d Cock , D.L. , “E ctroco u tio EC – ci c d pp ic tio ”, 
Journal of Hazardous Materials, B84, pp. 29-41. 
Mollah, M.Y.A., Morkovsky, P., Gomes, J.A.G., Kesmez, M., Parga, J. and Cock , D.,L. . “ u d m t , pr t d 
futur p r p ctiv of ctroco u tio ”, Journal of Hazardous Materials, B114, pp. 199-210. 
Sridhar, R., Sivakumar, V., Imm u , V.P. d M r , J. P. , “Treatment of pulp and paper industry bleaching effluent 
b ctroco u t proc ”, Journal of Hazardous Materials, Vol. 186, pp. 1495–1502. 
T rr z , E., Váz u z, ., Brio , R., Láz ro, I. d Rodrí u z, I. , “EC tr tm t for r u of ti u p p r w t w t r: 
Aspects that affect energy con umptio ”, Journal of Hazardous Materials, Vol. 181, pp. 809–816. 
W , J.P., Ch , Y.Z., G , X.W. d Yu, .Q. 7 , “ ptimiz tio of co u tio -flocculation process for a paper-
r c c i w t w t r tr tm t u i r po urf c m thodo o ”, Colloids and Surfaces A: Physicochem. Eng. Aspects, Vol. 
302, pp. 204-210. 
Wo , S.S., T , T.T., hm d, .L., Zuh iri, . d N j fpour, G. , “Tr tm t of pu p d p p r mi w t w t r b 
po cr mid P M i po m r i duc d f occu tio ”, Journal of Hazardous Materials, B135, pp. 378-388. 
 
 
Bionotes 
 
Sule Camcioglu is working as a research assistant in the Chemical Engineering Department, Faculty 
of Engineering, Ankara University, Turkey since 2009. She is a PhD student since 2010 and she 
holds the B.Sc. and M.Sc. from that department. Her research fields are treatment of various 
industrial wastewater, optimization and process control. 
 
Canan Pekel is a PhD student in the Chemical Engineering Department, Faculty of Engineering, 
Ankara University, Turkey. She holds the M.Sc. from that department and the B.Sc. from Gazi 
University, Turkey. Her research fields are wastewater treatment and process control. 
 
K mr Po t w bor i Gör m , Türki i 9 . work t k r U iv r it , where he has 
been on the faculty of science, department of chemistry since 1988. He received a Ph.D. in Organic 
Chemistry at Ankara University in 1997. He continues research in Ankara University as 
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Assoc.Professor since 2004. His research has dealt with various aspects of practical organic and 
electro chemistry, particularly industrial organic synthesis, organic electroorganic sythesis, electro 
kinetic and electrode reaction mechanism and spectroscopy of organic compounds. Professor Polat 
currently runs a research group of four master students. 
 
Hale Hapoglu is a professor in the Chemical Engineering Department, Faculty of Engineering, 
Ankara University, Turkey. She holds the B.Sc. and M.Sc. from that department and a Ph.D. from 
the Chemical Engineering Department of Wales University, U.K. She has written over 100 articles 
on modelling, simulation, and process control. 
 
 
 
 
 
 
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