Electrochemical technique for paper mill effluent degradation using concentric aluminum tube electrodes (CATE)

Abstract

In this study, Taguchi experimental design was used to the optimize operating parameters for the degradation of paper mill effluent using electrochemical (EC) process with two-dimensional concentric aluminum tube electrodes (CATE). For this purpose, four significant experimental factors were used in four levels pH (6–9), electrolysis time (10–40 min), voltage (6–12 V) and surface area (357–624 cm²). The process parameters were optimized, through performing L16 orthogonal array of Taguchi technique, for the removal of chemical oxygen demand (COD) and turbidity. The percent COD and turbidity reductions were transferred into an accurate S/N ratio for a larger value is the better (LBT) response. The study presents a unique method of finding optimum combination of process parameters to illustrate their effect on the turbidity and COD reduction. The treatment conditions for the maximum elimination of the pollutants were second level of pH (7), third level of ET (30 min), fourth level of voltage (12 V) and second level of surface area (446 cm²). The confirmation experiment results were within the confidence intervals (CI) indicating an acceptable agreement between predicted and observed values. Based on the p-values, the electrolysis time and voltages were found to be the most significant factors for both COD and turbidity reduction. The findings of research indicated, that the Taguchi method can be used successfully for the treatment of paper industry effluent by electrochemical technique.

Introduction

Industrialization in recent decades has left its negative effects on the environment. Paper industries are important because of their broad application in various streams of printing, packaging, newspaper, tissue paper and other printed material. The paper industry is the 3rd major wastewater producer in the world generating about 42% of global industrial wastewater. India is also a leading global contributor of paper and its products with installed production capacity of fifteen million tons [1]. Pulp and paper mill (P&P) industries use different types of raw materials such as hardwood, agro-based wastes, bagasse, and jute rags etc., based on their availability [2–4]. Pulping, bleaching and paper-making are the three major phases commonly adopted in Indian paper industries. Indian paper industries produce approximately 75–225 m³ of effluent per one ton of paper production [5]. The type and amount of wastewater produced is purely based on the raw materials used and techniques adopted for paper production. The wastewater from various processing units consist of organic and inorganic pollutants, and color [6, 7]. Further the paper mill effluent is a complicated blend of more than 700 inorganic and 250 organic chemicals [8, 9]. The discharge of untreated wastewater has many negative impacts on the receiving water bodies such as, low dissolved oxygen (DO), scum formation, thermal impact and slime growth. Thus continuous discharge of untreated wastewater may harm the aesthetic and scenic beauty of water environment, finally leading to totally disturbed ecosystem. As P&P mill wastewater is rich in toxic chemicals, it causes harmful effect on fishes and zooplankton also [10, 11]. Therefore, there is a need to develop a cost-effective treatment method for removal of these pollutants from the P&P industry wastewater. In this context, several physicochemical and biological techniques were attempted for handling paper industry effluent. Depending on the working principle and mechanism, each treatment method has its own advantages and disadvantages. There are many problems associated with physicochemical, biological and integrated treatment processes like large space requirement, long duration of treatment, and sensitivity for shock loading [12–14]. However, EC process has attracted many investigators, in recent years, because of its relative advantages compared to physicochemical and biological methods. Electrocoagulation is a compact, fast, inexpensive, easily operable, efficient and ecofriendly process having automation convenience and high efficiency in the removal of pollutants. A clean treated water with no color and smell with little sludge can be obtained by this process [15–17]. It is also reported that, for a large-operations EC methods are more technologically and economically feasible compared to other physico-chemical and biological treatment techniques. Further, chemical coagulation costs are found to be 3.2 times higher than electrocoagulation operating costs [18].

Electrocoagulation mechanism

Electrocoagulation (EC) is a separation technique involving both physical and chemical mechanisms. A simplest EC unit includes pair of anode-cathode submerged in water or wastewater. The electrodes used in EC reactor are prepared by different materials including aluminum and iron, such metal electrodes are placed in reactor vertically or horizontally with various configurations by considering all design aspects of EC. Three successive steps involved in the process are 1) in-situ coagulant production by electrolytic anode corrosion, 2) destabilization of contaminants and particulate matter 3) adsorption of destabilized contaminants to form flocs. Aluminum is cheap and readily available metal and has an ability to form multivalent ions and various hydrolysis [19, 20]. Hence aluminum is the most commonly used anode materials. During EC process in a reactor with aluminum electrodes the important electrochemical reactions that take place are given below (Eqs. 1 and 2):

At anode:

$${\mathit{\text{Al}}}_{\left(s\right)}\to {{\mathit{\text{Al}}}^{\mathit{3}+}}_{\left(\mathit{aq}\right)}+{\mathit{\text{3e}}}^{-}$$ 1

At cathode:

$${\mathit{\text{3H}}}_{\mathit{2}}{O^{+}}_{\left(\mathit{aq}\right)}+\mathit{3}{e}^{-}\to \mathit{3}/\mathit{2}{\mathit{\text{H}}}_{\mathit{2}}\left(g\right)+{\mathit{\text{3OH}}}^{-}$$ 2

The metal cations liberated by sacrificial anode undergo sequence of hydrolyzing reactions based on pH of solution forming monomeric and polymeric hydroxide species finally transforming into Al (OH)₃. The so formed aluminum hydroxide with large specific surface area helps in trapping of colloids and fast adsorption of compounds. Micro bubbles of hydrogen and oxygen liberated at the electrode layers adhere to the agglomerates and carry to the surface of the water by electrofloatation [21–26].

Design of experiments (DOE)

The performance of EC method is significantly influenced by the process parameters which includes wastewater pH, electrolysis time (ET), applied voltage and temperature. Generally optimization of parameters is carried out by varying one parameter keeping all other parameters constant. This procedure requires running large number of experiments to test all the combinations making it time consuming and an extremely costly in industrial settings. Therefore, experimental design (DOE) approaches were used to address these practical difficulties [27–29]. To minimize the inadequacy and limitations of conventional methods researchers have attempted different process optimization techniques. These include response surface methodology (RSM) [30], central composite design (CCD) [31], hybrid central composite design [32] and artificial neural networks (ANN) [33] etc. These designs have limitation of expanded number of runs, if the number of variable increases were chosen for process optimization [34]. Taguchi technique is commonly adopted DOE method which uses the orthogonal array (OA) structure to minimize the number of experiments [35]. Simultaneously, experimental trials are also reduced by varying process parameters. The result of the studies are examined with signal to noise (S/N) ratio, which defines mean response and standard deviation of output responses. Further, ANOVA was employed to assess the statistically significant impact of the factors on each response parameters [36, 37]. However, Taguchi method with L16 orthogonal array was used for process optimization for the maximum removal of pollutants. Further, ANOVA analyses also been conducted to identify the factors that strongly contribute for output responses.

Therefore EC technique is attempted for the treatment of varieties of industrial effluents like dairy, tannery, steel manufacturing plant, slaughterhouse, poultry, olive oil mill, pickle, distillery, textile, dye, pharmaceutical, automobile, electroplating, photograph processing and oil refinery [38, 39]. In addition to these investigations, recent studies on treatment of pulp and paper wastewater using electrocoagulation process have been reported [40–44]. The Taguchi technique of optimization is applied for treatment using EC process for many industrial wastewaters such as: textile industry [45], tanneries [46], carwash [47], landfill leachate [48], distilleries [49], metal plating wastewater [50] and synthetic wastewaters [51–54]. However, Taguchi technique is applied to EC process having plate aluminum electrodes [55]. Further, majority of the electrocoagulation studies are performed with the plate shape electrodes. However, changing and maintenance of these electrodes are time consuming and impractical. In addition, a limited number of plate electrodes can be put into the EC reactors. The shape of electrode is also a key parameter that decides effectiveness of the EC system [56]. Hence electrodes of different shapes have been attempted by some investigators and these shapes include: iron ball electrode for arsenic removal from ground water [57], helical shape of electrode for chromium removal [58], concentric tube electrodes for lead removal [59], holed ferrum electrode (HFE) for separation of copper [60], punched electrode for dye removal [61], spiral-wound woven-wire meshes for separation of manganese ions (Mn²⁺) from wastewater [62] and flat sheet asymmetrical aluminum electrodes for municipal wastewater treatment [63].

However, there have been no reports on treatment of actual pulp and paper mill wastewater by electrocoagulation using concentric aluminum tube electrodes (CATE). The unique features of concentric tube electrodes, such as compact in size, uniform potential and current distribution and homogeneity of electrode surface can improve the overall performance of EC system [64, 65]. Such novel concentric tube electrodes are not attempted so far for the treatment of actual pulp and paper mill wastewater. In view of all these factors, an experimental investigation on treatment actual pulp and paper mill wastewater using EC process with CATE electrodes was carried out applying taguchi technique of optimization.

Materials and methods

Paper industry wastewater

The grab samples of effluent were collected from an equalization tank of a nearby paper production unit located in the eastern part of Karnataka, India, having paper production capacity more than 20,000 ton per annum (TPA). These samples were preserved in refrigerator at 4 °C until use. The samples were analyzed using standard methods [66] and the average characteristics of paper industry effluents are summarized in Table 1.

Table 1.

Characteristic of paper industry effluent

Parameters	Values	Unit
pH	5 ±0.42	–
Temperature	28 ± 2	(oC)
COD	6000 ± 2	mg/L
Turbidity	264 ± 4	NTU
Conductivity	2.83 ± 0.02	mS/cm
TDS	3871 ± 4	mg/L
BOD	1040 ± 2	mg/L
TOC	1300 ± 2	mg/L

Electrocoagulation (EC) system

The flat bottom cylindrical EC reactor having 11.5 cm diameter and 12 cm height with a total volume of 1.2 l was fabricated using acrylic material. The asymmetrical configuration of electrode consisted of three cylindrical aluminum tubes with varying diameter and uniform thickness. The total active surface area of anodes was 446 cm² and the detailed description of electrodes is given in Table 2. The electrodes mounted on a holding unit were immersed in wastewater. The height of wastewater in the EC cell was maintained at 9.7 cm to give 1 L working volume for the studies. The electrode were placed in the reactor in a vertical manner and secured by plastic screws to maintain a constant gap of 10 mm. The electrodes were wired to direct current power supply (APLAB 0-30 V, 0-10 A) in such a manner that outer and inner electrodes acted like anodes and the middle one as cathode. The monopolar arrangement of triple concentric aluminum tube electrodes (CATE) employed in EC system for the study is shown in Fig. 1. The geometry of the reactor and electrodes permits better distribution of applied direct current (DC) field into wastewater solution.

Table 2.

Description of concentric aluminum tubes electrodes(CATE)

Tubes	Classification of electrodes	Height (cm)	Wet height (cm)	Tube thickness (cm)	Outer diameter (cm)	Inner diameter (cm)	Surface area (cm2)
Outer	Anode	8	5	0.2	9.2	9	286
Middle	Cathode	8	5	0.2	7.2	7	–
Inner	Anode	8	5	0.2	5.2	5	160

Fig. 1.

Experimental setup and electrode configuration 1) DC power supply, 2) electrode holding unit, 3) cylindrical shape reactor, 4) outer tube (anode), 5) middle tube (cathode), 6) inner tube (anode), 7) magnetic stirrer

Experimental procedure and analytical techniques

Experiments were carried out in a batch reactor at room temerature of 28 ± 2 °C. With the help of 0.5 M sodium hydroxide the effluent pH was adjusted to required value. The contents of reactor were continuously stirred with a magnetic stirrer at 100 rpm, in order to maintain homogeneity the reactor. After each batch experiment the vessel and electrodes were washed thoroughly by using 0.1 N HCl and cleaned 2 to 3 times with distilled water to avoid the passivation of the electrode surface. During the experiments the samples were collected at regular intervals of 10 min for chemical analyses. All the experiments of EC studies were performed in duplicate and average values were used. The properties of raw effluent were given in the Table 1. The efficiency (η) of the reactor was computed as below Eq. (3):

$$\left(\eta \%\right)=\left(\frac{C_o-C_f}{C_o}\right)\times 100$$ 3

where

C_o

influent concentration.

C_f

effluent concentration.

Design of experiment (DOE) - Taguchi approach

The experiments were formulated with Taguchi technique. The impact of the four main process parameters at four levels was investigated. The selected process parameters and their levels include: pH (A), 6–9; electrolysis time (B), 10–40 min; voltage (C), 6–12 V and surface area (D), 357–624 cm². The COD and turbidity reductions were chosen as response factors to assess the overall performance of electrocoagulation system. The orthogonal array (OA) of L16 was used which includes 16 trials for four factors, with 4 assigned levels. The planning of experiments for OA of L16 along with assigned levels are given in Table 3.

Table 3.

Selected process parameters and assigned levels

Parameters	Designation	Levels
		1	2	3	4
pH	A	6	7	8	9
Electrolysis time (minutes)	B	10	20	30	40
Voltage (volts)	C	6	8	10	12
Surface area (cm2)	D	357	446	535	624

Taguchi technique uses the S/N ratio, to statistically analyze experimental findings for performance evaluation [67]. In Taguchi method signal to noise ratio is expressed in three basic forms 1) maximum the better, 2) smaller the better and 3) nominal the better. The larger-the-better approach adopted as maximum reduction of pollutants was major objective of the investigation.

The following Eq. (4) was used to calculate S/N ratio:

$$\frac{\mathrm{S}}{\mathrm{N}}=-10log\left(\frac{1}{\mathrm{n}}\sum _{\mathrm{i}=1}^{\mathrm{n}}\frac{1}{{\mathrm{Y}}_{\mathrm{i}}^2}\right)$$ 4

where n: number of iterations, y_i: performance value of i^th experiment.

In this study, Minitab 17 was used for the planning, designing and analysis of experiments.The following Eq. (5), was used to predict performance value for optimum experimental conditions not based on experimental design.

$${\mathrm{Y}}_{\mathrm{opt}}=\frac{\mathrm{T}}{\mathrm{N}}+\left(\overline{{\mathrm{A}}_{\mathrm{i}}}-\frac{\mathrm{T}}{\mathrm{N}}\right)+\left(\overline{{\mathrm{B}}_{\mathrm{j}}}-\frac{\mathrm{T}}{\mathrm{N}}\right)+\left({\overline{\mathrm{C}}}_{\mathrm{k}}-\frac{\mathrm{T}}{\mathrm{N}}\right)+\left({\overline{\mathrm{D}}}_{\mathrm{l}}-\frac{\mathrm{T}}{\mathrm{N}}\right)$$ 5

where,

N

number of measurments,

T

sum of all measurments, and

${\overline{A}}_i$, ${\overline{B}}_j$, ${\overline{C}}_k$ and ${\overline{D}}_l$

average of responses at different phases i, j, k and l.

The Eq. (6), is used to findout the confidence interval and details are given below:

$$\mathrm{CI}=\sqrt{{\mathrm{F}}_{\mathrm{\alpha };1,{\mathrm{DOF}}_{\mathrm{e}}}\times {\mathrm{MS}}_{\mathrm{e}}\times \left[\left(\frac{1+\mathrm{m}}{\mathrm{N}}\right)+\left(\frac{1}{\mathrm{S}}\right)\right]}$$ 6

where,

F

value of F table at desired CI at degree of freedom of one and

DOF_e

degree of freedom of error,

α

confidence interval,

MS_e

mean of square varience of error,

m

DOF used in the prediction of Y_opt,

N

total number of observation, and

S

number of trials in confirmation test.

Analysis of variance (ANOVA)

ANOVA statistical method was used to understand whether the controlling parameters were important or not [68, 69]. The ANOVA statistical tool is used to compute design parameters such as mean of square, sum of square, and total sum of square, degrees of freedom and error variance [28, 47]. The calculation details are given in (Eqs. 7–11):

$${\mathrm{SS}}_{\mathrm{A}}=\left(\sum _{\mathrm{i}=1}^{{\mathrm{k}}_{\mathrm{A}}}\frac{{\mathrm{A}}_{\mathrm{i}}^2}{{\mathrm{n}}_{{\mathrm{A}}_{\mathrm{i}}}}\right)-\frac{{\mathrm{T}}^2}{\mathrm{N}}$$ 7

where

k_A

range of variables,

${\mathrm{n}}_{{\mathrm{A}}_{\mathrm{i}}}$

number of all measurements at level i of factor A,

A_i

sum of all observations of level i of factor A, and

T

sum of all measurements.

SS of error was calculated by following Eq. (8):

$${\mathrm{S}\mathrm{S}}_e={\mathrm{S}\mathrm{S}}_T-({\mathrm{S}\mathrm{S}}_A+{\mathrm{S}\mathrm{S}}_B+\dots )$$ 8

SS_T

total SS and computed by Eq. (9):

$${\mathrm{SS}}_{\mathrm{T}}=\sum _{\mathrm{i}=1}^{\mathrm{N}}{\mathrm{Y}}_{\mathrm{i}}^2-\frac{{\mathrm{T}}^2}{\mathrm{N}}$$ 9

Y_i

experiment observation of i.

Mean of square (MS) is the ratio of sum of squares and DOF_.

DOF_A is estimated as DOF_A = k_A − 1.

F-value computed by using Eq. (10):

$${\mathrm{F}}_{\mathrm{A}}=\frac{{\mathrm{MS}}_{\mathrm{A}}}{{\mathrm{MS}}_{\mathrm{e}}}$$ 10

MS_e

variance of error.

The percent contributions (P) of the process parameters were calculated using the Eq. (11):

$$\mathrm{P}\left(\mathrm{\%}\right)=\frac{{\mathrm{S}\mathrm{S}}_{\mathrm{A}}}{{\mathrm{S}\mathrm{S}}_{\mathrm{T}}}$$ 11

Results and discussion

Results of Taguchi method

The efficiencies of COD and turbidity reduction were determined from the experiments conducted using Taguchi’s design as indicated in Table 4. The experimental results were evaluated converting results in Taguchi system to S/N ratio. Table 4 represents the performance of both COD and turbidity reduction obtained from experimental findings and the signal to noise ratios. The maximum efficiency in reduction was obtained for COD (91.60%) in Trial 7 and turbidity (95%) in Trial 8.

Table 4.

Reduction efficiencies and signal to noise ratios

	Factors and their levels				RE (%)		S/N ratio
Trial number	A	B	C	D	COD	Turbidity	COD	Turbidity
1	1	1	1	1	62.00	74.20	35.84	37.41
2	1	2	2	2	70.05	82.10	36.90	38.29
3	1	3	3	3	82.80	88.70	38.36	38.96
4	1	4	4	4	82.90	92.00	38.37	39.28
5	2	1	2	3	65.80	80.90	36.36	38.16
6	2	2	1	4	68.60	81.60	36.72	38.23
7	2	3	4	1	91.60	93.90	39.23	39.45
8	2	4	3	2	84.10	95.00	38.49	39.55
9	3	1	3	4	68.20	80.30	36.67	38.09
10	3	2	4	3	79.90	84.00	38.05	38.49
11	3	3	1	2	76.80	87.00	37.70	38.79
12	3	4	2	1	78.00	85.65	37.84	38.65
13	4	1	4	2	75.10	81.00	37.51	38.17
14	4	2	3	1	71.80	84.90	37.12	38.58
15	4	3	2	4	69.90	85.00	36.88	38.59
16	4	4	1	3	73.20	82.00	37.29	38.28

By averaging the S/N ratio at 4 levels the mean S/N ratio was computed, which was used to evaluate effect of all the four factors on COD and turbidity reduction. The response graphs for COD and turbidity removal based on mean S/N ratio are given in Figs. 2 and 3. Short horizontal dot lines in these figures indicate the whole mean S/N ratio for COD and turbidity removals respectively. These values were 39.24 for COD and 39.45 for turbidity. From these figures it is evident that the factor of electrolysis time caused maximum deviation from average S/N ratio value for COD and turbidity removals. Hence it can be said that electrolysis time influenced more than the other factors in pollutant removal. These highest deviations found to be 3.39 and 2.15 for COD and turbidity reductions respectively. The highest S/N ratios in the respective figures indicate the maximum of COD and turbidity reductions. Hence, the levels which gave highest S/N ratios were considered to be the optimum operating conditions. Thus, maximum reduction efficiencies for both COD and turbidity were obtained at pH: 7 (second level), ET: 30 min (third level), 12 V (forth level) and SA:446 cm² (second level).

Fig. 2.

Response graphs for COD removal

Fig. 3.

Response graphs for turbidity removal

Further, the controlling parameters of EC process were optimized based on S/N ratio. The S/N ratios for the controlling parameters of EC process at four levels for COD and turbidity removals are given in the Tables 5 and 6. Greater the signal to noise ratio higher the percentage COD or turbidity removal efficiencies and vice versa. Hence the level with highest S/N ratio gives optimum level of controlling factors. As given in Table 5 the maximum COD removal efficiencies were achieved at second level of pH (7), third level of ET (30 min), fourth level of voltage (12 V) and second level of SA (446 cm²). Similarly from the Table 6, it is evident that maximum turbidity removal efficiencies were gained at second level of pH (7), fourth level of ET (40 min), third or fourth level of voltage (10 or 12 V) and second level of SA (446 cm²).

Table 5.

S/N ratio of control parameters for COD reduction

Level	S/N ratio for COD reduction
	(A) pH	(B) ET	(C) Voltage	(D) Surface area
1	37.37	36.60	36.89	37.51
2	37.71	37.20	37.00	37.66
3	37.57	38.05	37.66	37.52
4	37.20	38.00	38.29	37.17

Table 6.

S/N ratio of control parameters for turbidity reduction

Level	S/N ratio for turbidity reduction
	(A) pH	(B) ET	(C) Voltage	(D) Surface area
1	38.48	37.96	38.18	38.52
2	38.85	38.4	38.42	38.70
3	38.51	38.95	38.80	38.47
4	38.40	38.94	38.85	38.55

Operating parameters and their effect on COD and turbidity reduction

Initial pH

The pH of the solution greatly affects the chemical dissolution of metal ions and its species. Therefore pH of solution is important operating factor in the EC process. Based on the pH of the solution the complexed metal hydroxides are formed during the process. In present study initial pH ranged between 6 to 9 during optimization of parameters. The influence of wastewater pH on COD and turbidity removal is shown in Figs. 2 and 3 as their response graphs. It can be observed from these figures that when pH was raised from 6 to 7 the S/N ratio increased, but further increase in pH value up to 9 resulted in its decrease, thus giving maximum S/N ratio at pH 7 and minimum at 9. The maximum removals of both the pollutants were obtained at neutral pH; and the same was considered as optimum condition as the maximum S/N ratio was obtained for this pH. These higher removals at neutral pH value could be explained from the fact that at neutral pH formation of Al(OH)₃ is maximum as its polymeric species are converted to Al(OH)₃. Further these Al(OH)₃ flocs having wide surface area with gelatinous structure helped for faster adsorption of soluble organic compounds as well as colloidal particles trapping. In addition finest hydrogen gas bubbles were formed at neutral pH [70, 71], which support the aggregation of tiny destabilized particles and colloidal.

Effect of electrolysis time

Electrolysis time is significant parameter that influences the performance of EC process as metal ions and their hydroxide flocs increase with the time [24, 72]. From the Figs. 2 and 3 it can be observed that highest S/N ratio was obtained at 30 min. Hence ET of 30 min was considered as an optimum condition that resulted in the maximum removal of both the pollutants.

Effect of voltage

The voltage is one of important process parameter and it depends upon surface area, spacing between electrodes and conductivity of solution. In fact metal ion dissociation is directly proportional to the applied voltage leading to increased metal hydroxide formations resulting in enhanced pollutants removal at higher voltages [73]. The effect of varying voltages (between 6 to 12 V) for COD and turbidity removals are illustrated in Figs. 2 and 3. It can be observed that signal to noise ratio increased with rise in voltages and maximum S/N ratio was obtained at 12 V. Hence maximum removal efficiencies for both the pollutants were obtained at optimum voltage of 12 V. At higher voltages larger amount of Al(OH)₃ was generated, by means of anode dissolution and generated aluminum hydroxides helps for the coagulation. At the same time at cathode more numbers of bubbles are formed such bubbles are leads to floatation [74].

Effect of surface area

The surface area (SA) is an main parameter which decides coagulant formation, pollutant removal rate and overall efficiency of reactor. Therefore to investigate effect of electrode SA on EC performance CATE reactor was used. The surface areas were applied in the range of 357–624 cm² by changing depth of immersion of electrodes. From the Figs. 2 and 3 it can be observed that maximum signal to noise ratio was achieved at electrode SA of 446 cm² which was optimal for maximum removal of the contaminants. Mass variations of CATE electrodes were observed, from which it appeared that the anode and the cathode were consumed during the electrolysis. The decrease in weight of anode was observed due to the release of ions into the solution. At the same time, negligible amount of ions were released by cathode due to corrosion. The cathodic material undergoes some deposition due to the reduction taking place on the surface.However surface morphology study of CATE reactor for the treatment of actual pulp and paper mill wastewater could be an interesting for future study.

Results of ANOVA

ANOVA analyses was applied to find out the factors that influence the responses output parameters. It was also used to asses their contributions in COD and turbidity reductions. The ANOVA results for COD and turbidity in reductions are summarized in Table 7. The F Value is used qualitatively to evaluate the influence of factors on output parameters. It gives factors having statistically significant influence on output parameters. The calculated F value for each factor was compared with the critical F value (F_cr), which was found in experimental design books having DOF values, for the errors and factors [75]. The F_cr with appropriate DOFs for the error and factors (F_{0.05; 3; 3}) was determined as 9.28 at a CI of 95%. As seen from the Table 7, F value of the factors ET and Voltage were greater than F_cr value for both COD and turbidity removal efficiencies. Thus, these results indicated that ET and voltage significantly influenced on COD and turbidity removals, whereas pH and SA were statistically less significant for COD and turbidity removals.

Table 7.

Results of ANOVA for COD and turbidity reduction

Response parameter	Factors	Degree of freedom	Adj. SS	Adj. MS	F value	p value	P(%)
COD removal (%)	pH	3	53.84	17.945	4.02	0.141	5.83
	ET	3	426.16	142.053	31.86	0.009	46.19
	Voltage	3	389.54	129.845	29.12	0.010	42.22
	SA	3	39.77	13.256	2.97	0.197	4.31
	Error	3	13.38	4.459			1.45
	Total	15	922.68
Turbidity removal (%)
	pH	3	49.477	16.492	5.25	0.103	11.05
	ET	3	259.684	86.561	27.55	0.011	58.01
	Voltage	3	117.154	39.051	12.43	0.034	26.17
	SA	3	11.909	3.970	1.26	0.426	2.66
	Error	3	9.427	3.142			2.11
	Total	15	447.651

The p value (probability value) is another key indicator of the impact of each factor on the response. The p value for any factor lower than 0.05, indicates that the parameter is most significant [76]. Hence, depending upon the p –value results (95% CI) ET and voltage were found to be the most significant factors for both pollutants. The percent contributions of all the factor for COD and turbidity removal are presented Fig. 4. Since the percent contributions of the errors were below 50% for both COD (1.45%) and turbidity removal (2.11%) it can be concluded that errors of the experiments were not significant [28]. Further, based on their percent contributions (P), the most significant factors that influence the COD removal efficiency were in the order: ET > Voltage>SA > pH. Similarly for the turbidity removal the order of significant factors was: ET > Voltage>pH > SA. The percent contributions of ET were 46.19% and 58.01% for COD and turbidity removal efficiencies respectively. However, voltage was another factor having greater effect with 42.22% contribution on COD removal. Hence it can be concluded that the key factor which had highest effect on both COD and turbidity removal efficiencies was electrolysis duration. These findings showed that the removal of pollutants depended on the formation of metal hydroxides and liberation of H₂ gas. These findings are similar to those of earlier researcher [77, 78]. However pH and surface area showed little effect on COD and turbidity reductions. The percent contribution of surface area in removal of both COD and turbidity was not significant (less 10%). Similar kind of observations were made in removal of arsenic [57] and treatment of textile wastewater [45] using EC process with plate electrodes.

Fig. 4.

Percent contributions of all factors on COD and turbidity reduction

Findings of confirmation experiments

Conducting confirmation experiments with a combination of optimum level is necessary to evaluate as well as to verify the predicted results of the Taguchi design. Hence experiments were conducted with optimum operating conditions: pH: 7, ET: 30 min, voltage: 12 V and SA:446 cm². The observed results of COD, turbidity reductions, predicted results at 95% confidence intervals are given in Table 8. The predicted results of COD and turbidity removal efficiencies were close to those obtained from confirmation experiments in the Taguchi design. The observed experimental reductions were within the CI. It can thus be concluded that there is strong agreement among predicted and observed experimental findings of Taguchi technique. Similarly in the literature there is evidence of successful application of Taguchi technique for electrocoagulation treatment of various industrial effluents such as textile, tannery and distilleries [46, 49, 79, 80].

Table 8.

Findings of confirmation experiments

Parameter	Observed reductions (%)	Predicted results (%)	CI (%)
Chemical oxygen demand	92.40	91.57	85–96
Turbidity	97	95.83	91–99

Conclusions

The present investigation is the first lab-scale attempt of EC process with concentric aluminum tube electrodes (CATE) for real paper mill effluent, where Taguchi technique was employed for the optimization of experimental conditions. The optimum treatment conditions so obtained to attain highest reduction of the pollution were pH: 7 (second level), ET: 30 min (third level), Voltage: 12 V (forth level) and SA:446 cm² (second level). The confirmation experiments were carried out with optimum experimental conditions for COD and turbidity removal. The predicted and observed results of these pollutants were in good agreement with each other. Hence the model was satisfactory in explaining the influence of these factors on the performance of EC process. Further, application of ANOVA proved that electrolysis time (ET) was the key parameter that greatly influenced the EC performance. The maximum reduction of COD and turbidity were 92.40% and 97% respectively under optimized working conditions determined through Taguchi technique. From the findings of the present investigation one can conclude that Taguchi method of DOE can be successfully employed for the degradation of paper mill effluent using EC process. For concentrated wastewater EC technique can be cost effective pre-treatment method. However, to meet limit of disposal standards of regulatory authority a post treatment method may be employed. However, surface morphology study of CATE reactor for the treatment of actual pulp and paper mill wastewater could be an interesting for future study.

Declarations

Conflict of Interest

The authors would like to declare that there is no conflicts of interest regarding the publication of this paper.