The presence of refractory contaminants in textile wastewater is one of the major concerns while handling them with the biological processes at common effluent treatment. Electro-oxidation (EO) as a standalone process is an insufficient treatment method for the abolition of inorganic contaminants (carbon and non-carbon). By incorporating electrocoagulation (EC) as an associated treatment method after EO, removal of such contaminants becomes easy, which not only makes the treated wastewater fit for biological remediation but also reduces load on biological units. The removal of non-carbonic impurities was assessed in terms of improvement in the chemical oxygen demand (COD) post EC. L25 orthogonal array of experiments was obtained using the Taguchi method. From the S/N ratio plot, the optimal process combination was obtained as, EO with current density = 25 mA/cm2, electrolysis time = 50 min followed by EC with current density = 18 mA/cm2, speed of rotation = 50 rpm and electrolysis time = 40 min. The enhancement in COD and total organic carbon removal efficiencies after EC were 65.11 and 63.57%, respectively, over EO. The biodegradability index also improved from an initial value of 0.098–0.737 post-hybrid treatment. Inorganic carbon reduced from a value of 36.37 mg/L after EO to 0.1 mg/L post EC.

  • The combined process removes inorganic pollutants in addition to dissolved persistent compounds.

  • The wastewater becomes fit for biological treatment in common effluent treatment plants post EO + EC.

  • The hybrid process improves the biodegradability of the wastewater.

  • A notable improvement in the COD and TOC removal efficiencies was observed after electrocoagulation.

The textile industries contribute significantly to the contamination of the surface water bodies by the release of effluents that are laden with complex and persistent dyes and chemicals (Behera et al. 2021; Wang et al. 2022; Jorge et al. 2023). Of various operations such as mercerization, sizing, dyeing, finishing, bleaching, printing performed in these industries, the process of dyeing and finishing produces a majority of contaminants (Wang et al. 2022; Jorge et al. 2023; Kallawar & Bhanvase 2024). The textile industries utilize a variety of hazardous dyes such as vat, acidic, reactive, azo, disperse that do not fully adhere to the fabric and are released into the aquatic ecosystem with wastewater (Yaseen & Scholz 2019; Kishor et al. 2021; Jorge et al. 2023). In addition, the textile effluent contains a huge quantity of binders, salts, dispersants, surfactants, dioxins, phthalates, detergents, heavy metals (Bakaraki Turan et al. 2021; Kishor et al. 2021; Islam et al. 2023). The effluent from textile industries is characterized by the presence of high salinity, inorganic solids content, chemical oxygen demand (COD), total organic carbon (TOC), low biodegradability, and variable pH (Gilpavas et al. 2018b; Zazou et al. 2019; Kuleyin et al. 2022). The highly pigmented effluent generated by these industries also contains a variety of toxic persistent organic pollutants that can travel large distances without degradation, which results in the deterioration of the aquatic ecosystem. Hence, the effluent from these units should be treated prior to discharging into aquatic sources (Badmus et al. 2018; Kishor et al. 2021; Selvaraj & Arivazhagan 2024). Recent technologies such as electrochemical processes are emerging as promising techniques for the remediation of wastewater that contains an extensive amount of non-biodegradable organics (Gunawan et al. 2018; Yakamercan et al. 2023; Barcelos et al. 2024). The electrocoagulation (EC), electro-oxidation (EO) and a combination of these processes with other physical, chemical and biological processes are considered as the most efficient techniques for the treatment of difficult wastewater (Asfaha et al. 2022a; Tokay Yilmaz et al. 2023; Babu Ponnusami et al. 2023).

The EO process is gaining prominence as a robust technology for the remediation of intricate and persistent organic compounds (Gilpavas et al. 2018a; Yao et al. 2022; Navarro-franco et al. 2022). This can be accomplished either through complete mineralization or by transforming them into less toxic substances (Zhu et al. 2011; Song Sun et al. 2022; Navarro-franco et al. 2022). In this process, hydroxyl radicals (●OH), an extremely reactive species, are produced when water at the anodic surface oxidizes. These radicals mineralize organic pollutants indiscriminately. However, complete mineralization of the complex pollutants requires a lot of energy, thus making it impossible to apply the EO process practically (Navarro-franco et al. 2021; Yakamercan et al. 2023; Barcelos et al. 2024). To overcome this challenge, researchers have combined EO with different biological processes. The EO process is used to enhance the biodegradability of the toxic waste so as to prepare it for treatment by biological means (Lindholm-lehto & Knuutinen 2015; Yakamercan et al. 2023; Barcelos et al. 2024). The combination synergises the capability of EO to oxidize recalcitrant and non-biodegradable organic pollutants with the capacity of biological processes to decompose any remaining biodegradable organic matter (Paździor et al. 2019; Navarro-franco et al. 2021; Babu Ponnusami et al. 2023).

Wre et al. (2017) investigated the concentrated stream collected at four different time intervals from the dyeing industry, which consists mostly of effluents from bleaching and dyeing units. The process of ozonation in conjunction with a sequential batch reactor with a 48-h hydraulic retention timewas used to remediate the dyeing effluent. For the four different samples, the combination yielded an overall COD and color removal efficiency ranging between 59–62% and 47–88%, respectively. In their research, Santhanam et al. (2017) explored the treatment of textile dyeing wastewater obtained from a Common effluent treatment plant through a combination of EO and bioprocess. A RuO2–TiO2/Ti mesh anode and a bacterial consortium were used for EO and biological processing, respectively. No visible was discovered following EO, and the combined treatment resulted in a COD removal efficiency of 73%.

However, efficient removal of inorganic particles alongside the organic pollutants is crucial for comprehensive wastewater treatment, particularly in textile wastewater where suspended solids are in abundance. These inorganic particles are inert and are not biodegradable. While the EO process effectively targets recalcitrant organic contaminants, it often falls short in addressing the inorganic suspended impurities (Chakchouk et al. 2017; Abbar & Alkurdi 2021; Asfaha et al. 2021). These impurities are also not effectively removed by biological treatment units. Prior to biological processes, wastewater must undergo treatment to eliminate these suspended inorganic particles. Zhu et al. (2011) utilized the dye effluent that had been processed to electrochemically oxidize the organic components. Zero-valent iron and coagulation were used as on-site pretreatments, followed up by up-flow anaerobic sludge blanket treatment. Ling et al. (2016) employed primary sedimentation and activated sludge processes before subjecting the wastewater to electrolysis for refractory organic removal.

EC has developed as an efficient technique for getting rid of various organic and inorganic suspended and colloidal pollutants to reduce the turbidity of various wastewater types (Chakchouk et al. 2017; Bener et al. 2019; Al-Raad & Hanafiah 2021). During the EC process, the in-situ formation of metal hydroxides takes place when a system of electrodes is subjected to an electric current (Chakchouk et al. 2017; Bener et al. 2019; Al-Raad & Hanafiah 2021). These metal hydroxides cause the destabilization of colloidal and suspended particles, allowing attachment when the contact occurs. The gelatinous nature of these hydroxides enables them to entrap the undesirable constituents, which can be further removed from the system through the mechanism of sweep coagulation.

Bener et al. (2019) addressed the pretreated textile wastewater through the EC process. With aluminum electrodes, a maximum COD, color, TOC, turbidity, and total suspended particle removal efficiency of 18.6, 90.3–94.9, 42.5, 83.5, and 64.7% were obtained, respectively, at an optimal current density of 25 mA/cm2, pH of 5, and reaction duration of 120 min. Selvaraj & Arivazhagan (2024) treated a lung-producing textile industry effluent that contains turquoise blue dye with EC, followed by an adsorption process. The studies were carried out with aluminum electrodes for EC and algal activated carbon (AAC) adsorbents for adsorption. After EC, under the optimal conditions of current density as 1.5 A/dm2 and treatment time of 36 min, a maximum COD removal of 79.97%, color removal of 54.12%, total dissolved solid removal of 14.60% and turbidity removal of 85.91% were achieved, which increased to 91.28, 68.82, 16.04, and 90.96%, respectively, after 12.8 g/L dosage of AAC and time of 44 min.

Despite considerable advances in textile wastewater treatment technologies, there is a substantial gap in the existing literature that discusses the implementation of the EC process as a treatment method post-advanced oxidation process (AOP) to remove suspended pollutants in both carbon and non-carbon forms. While a number of studies have looked into using AOPs in conjunction with other biological processes to address refractory organic pollutants, there has been little investigation into using EC as a sequential treatment step that particularly targets inorganic suspended particles. Given the abundance of inorganic contaminants in textile wastewater and the difficulties in successfully treating them with AOPs and biological processes, investigating the viability as a post-AOP treatment of the EC process might provide a feasible approach for enhancing overall treatment efficiency. By coagulating inorganic particles, EC may reduce the strain on downstream biological processes, filling a critical gap in complete wastewater treatment techniques for the textile sector.

The present study presents a unique approach to the management of organic and inorganic toxic contaminants from textile wastewater. It involves the use of three-dimensional (3D) electrodes for the treatment of wastewater by a hybrid process that involves a combination of EO and EC. The effectiveness of the combination was assessed in terms of color, COD, and TOC removal. The fate of the persistent organic contaminants was analyzed in terms of the biodegradability index (BI). The removal of non-carbonic impurities post EO-EC was assessed in terms of the improvement in COD removal efficiency obtained after EO. In addition, the removal of inorganic carbon from wastewater after the combination was also determined to make sure the complete removal of the inorganic impurities.

Preparation of simulated wastewater

The textile wastewater was synthetically prepared in the laboratory using azo red 3BL dye. The azo dyes have the capability to persist in the aquatic ecosystem (Camargo & Morales 2013; Selvaraj et al. 2021; Shi et al. 2021). A variety of chemicals, as reported by many researchers (Mountassir et al. 2015; Punzi et al. 2015; Yaseen & Scholz 2019), including dye, disodium hydrogen phosphate, sodium chloride, and starch were mixed together in the distilled water to prepare the synthetic textile effluent. The characteristics of synthetic textile wastewater are as follows: color – 5015 PCU (Platinum Cobalt Unit), pH – 8.31, conductivity – 7.36 mS/cm, COD – 1010 mg/L, TOC – 320 mg/L and inorganic carbon – 36.37 mg/L.

Experimental procedures and set up for the hybrid process

A schematic layout depicting the experimental setup for the treatment of synthetic wastewater by the EO-EC process in batch mode is presented in Table 1: L25 experimental design for EO + EC process Figure 1. The EO and EC processes were conducted in reactors of capacity 4.5 L each. For the EO and EC processes, a concentrically connected 3D system of cylindrical anodes and cathodes was used. The anodes made of graphite and aluminum with an effective area of 150 cm2 each were used for EO and EC processes, respectively. A dual output DC power supply was attached to the electrode system in both reactors. During the EO process, fish aerators were used to produce an adequate quantity of oxygen to facilitate the process of oxidation. The electrodes used for the EC process were connected to a rotating mechanism that imparts continuous rotation to the anode so as to allow the uniform mixing of the coagulating species formed within the reactor. The pH of the solution was adjusted with the use of 0.1 N HCl (Hydrochloric Acid) and 0.1 N NaOH. Before initiating the EO and EC processes, the pH of the wastewater was brought closer to 3 and 6, respectively. After every experiment, the electrodes were properly washed with acetone solution to get rid of undesired contaminants.
Table 1

L25 experimental design for EO + EC process

Set no.JEO (mA/cm2)tEO (min)JEC (mA/cm2)tEC (min)NEC (rpm)
10 20 14 30 40 
15 30 14 35 45 
20 40 14 40 50 
25 50 14 45 55 
30 60 14 50 60 
20 50 16 30 45 
25 60 16 35 50 
30 20 16 40 55 
10 30 16 45 60 
10 15 40 16 50 40 
11 30 30 18 30 50 
12 10 40 18 35 55 
13 15 50 18 40 60 
14 20 60 18 45 40 
15 25 20 18 50 45 
16 15 60 20 30 55 
17 20 20 20 35 60 
18 25 30 20 40 40 
19 30 40 20 45 45 
20 10 50 20 50 50 
21 25 40 22 30 60 
22 30 50 22 35 40 
23 10 60 22 40 45 
24 15 20 22 45 50 
25 20 30 22 50 55 
Set no.JEO (mA/cm2)tEO (min)JEC (mA/cm2)tEC (min)NEC (rpm)
10 20 14 30 40 
15 30 14 35 45 
20 40 14 40 50 
25 50 14 45 55 
30 60 14 50 60 
20 50 16 30 45 
25 60 16 35 50 
30 20 16 40 55 
10 30 16 45 60 
10 15 40 16 50 40 
11 30 30 18 30 50 
12 10 40 18 35 55 
13 15 50 18 40 60 
14 20 60 18 45 40 
15 25 20 18 50 45 
16 15 60 20 30 55 
17 20 20 20 35 60 
18 25 30 20 40 40 
19 30 40 20 45 45 
20 10 50 20 50 50 
21 25 40 22 30 60 
22 30 50 22 35 40 
23 10 60 22 40 45 
24 15 20 22 45 50 
25 20 30 22 50 55 
Figure 1

The schematic layout of the setup for EO + EC: (1) reactor for EO; (2) 3D graphite electrode; (3) DC supply with dual output; and (4) 3D aluminum electrode.

Figure 1

The schematic layout of the setup for EO + EC: (1) reactor for EO; (2) 3D graphite electrode; (3) DC supply with dual output; and (4) 3D aluminum electrode.

Close modal

Methods of analysis

The electrical conductivity and pH were determined using Hanna pH and EC combo devices. A handheld colorimetric device was used to determine the color in the platinum cobalt unit (PCU). The COD was measured using Standard Methods of Examination of Water and Wastewater (5220 D) with the help of a Shimadzu UV Spectrophotometer at an absorbance of 600 nm. The TOC was determined using the Shimadzu TOC-L analyser. The percentage removal of color, COD, and TOC was determined using the following equation.
(1)
where Ci and Co represent the inlet and outlet values of color (PCU), COD and TOC (mg/L), respectively, in the reactor.
The total energy consumption (E) in KWh/m3 after EO and EC processes was calculated using the following equation.
(2)
where U, I, t, and V are the values of electric potential (V), electric current (A), electrolysis time (min), and volume of the wastewater to be treated (m3), respectively.

Experimental design and optimization

The Taguchi method of optimization was used to study the effect of various operating variables on the color, COD, and TOC abatement efficiency. Five levels of the operating variables, as shown in the Supplementary Table S1, were identified on the basis of the preliminary investigations. A set of 25 experiments for the combined process was determined in MINITAB 17 software using the L25 (55) orthogonal array, as shown in Table 1. The optimal process variable setting is determined using the Taguchi technique using a parameter identified as the signal-to-noise ratio (S/N). The signal and noise represent the desirable and undesirable values, respectively. This approach uses three kinds of S/N ratios: smaller is better, larger is better, and nominal is better. The ‘Larger is better’ (Equation (3)) approach was employed since maximizing the abatement of color, COD, and TOC from the wastewater is the primary goal of this study.
(3)
where n is the number of trials and Yi is the value of the response.
The percentage contribution of each operating variable to the efficiency of COD, color, and TOC removal was determined using the following equations.
(4)
where i is the operating variable
(5)
(6)
(7)
where m, number of sets; n, number of levels; and j, number of operating variables.

The major operating parameters for the EO and EC processes were identified from the literature. A preliminary analysis was conducted on simulated textile wastewater to determine an appropriate range of values for these parameters. This range of values was used to design the experiments for the combined process.

Effect of operating parameters on the EO process

Low pH favors the production of hydroxyl radicals by inhibiting the synthesis of oxygen via side reaction (Equation (8)) (Wang et al. 2016; Yao et al. 2019; Guvenc et al. 2024). Because of the presence of sodium chloride, Cl-assisted oxidation of the organic matter also occurs at pH near 3 due to the formation of chlorine gas in the aqueous phase. Therefore, the initial pH for all the experimental sets was kept fixed at 3.
(8)

Current density

Current density is calculated as current per unit area of the anode. Using current density as an operating parameter accounted for the distribution of current throughout the anodic surface, allowing for consistent comparisons and optimization of the electrochemical processes. For the treatment of wastewater by electrochemical methods, current density is regarded as a key operating variable as it considerably affects both the pollutant removal and cost of capital (Zheng et al. 2016; Sun et al. 2022; Guvenc et al. 2024). For determining the influence of current density on the COD abatement efficiency, the experiments were performed for current densities ranging between 5 and 35 mA/cm2, keeping the time of electrolysis constant at 50 min. As illustrated in Figure 2(a), the efficiency of COD removal increases with current density. This is because increased current densities cause more ions to form, which in turn causes the system to produce more hydroxyl radicals (Equation (9)) (Jawad & Najim; Yao et al. 2019; Guvenc et al. 2024). These readily formed radicals react indiscriminately with the organic impurities present in wastewater. Also, the values of COD removal efficiencies exhibit a declining trend after the current density of 25 mA/cm2. This is on account of the consumption of ●OH through side reactions that produce an excess of O2 and H2 (Equation (8)) (Wang et al. 2016; Sandhwar 2020; Guvenc et al. 2024).
(9)
Figure 2

Effect of (a) current density at electrolysis time of 50 min and (b) electrolysis time at constant current density of 30 mA/cm2 during EO on COD removal efficiency.

Figure 2

Effect of (a) current density at electrolysis time of 50 min and (b) electrolysis time at constant current density of 30 mA/cm2 during EO on COD removal efficiency.

Close modal

Electrolysis time

In addition to the current density, the electrolysis time has a substantial role in the electrical energy consumed (Sandhwar 2020; Navarro-franco et al. 2021; Saleh et al. 2021). The impact of electrolysis time on the efficiency of COD removal was determined by conducting experiments for a constant current density of 30 mA/cm2 at different electrolysis times between 10 and 70 min. The efficiency of COD removal increases with time, as can be seen from Figure 2(b), but after reaching a particular value, i.e., 50 min, it shows a declining trend. More hydroxyl radicals will be produced as the electrolysis time increases, but beyond a certain point, they will be destroyed because at higher electrolysis time, side reactions will take over the system as more oxygen and hydrogen are produced within the reactor at larger electrolysis time, which convert hydroxyl radicals into water (Equation (10)) (Sandhwar 2020). Therefore, the hydroxyl radicals available for the oxidation of organic matter decrease with time. Additionally, with the increasing electrolysis time, the energy consumption of the process increases.
(10)

Effect of operating parameters on EC

After the EO process, the wastewater was treated with the EC process, for which the preliminary investigations were done to find ranges of the variables. The experiments for EC were performed on wastewater treated with EO, keeping the current density and electrolysis time during EO constant at 30 mA/cm2 and 50 min. During EC, the precipitation of insoluble aluminum hydroxide flocs occurs predominantly near pH 6 (Adeogun & Balakrishnan 2016; Naje et al. 2016; Fajardo et al. 2017). The pH of the wastewater rises to 4.75 after the EO process, which was further increased to 6 before carrying out the EC process to allow the maximum precipitation of the flocs to take place.

Current density

During the EC process, the flow of current through the system of electrodes dissolves the sacrificial aluminum electrode, resulting in the generation of coagulant species within the system. Current density is a crucial factor that affects the formation and growth of metal hydroxide flocs (Khorram & Fallah 2018; Bener et al. 2019; Asfaha et al. 2022a, b). It directly affects the quantity of metallic cations generated within the system. Figure 3(a) shows the variation in the efficiency of COD removal with current density at constant reaction time (40 min) and speed of rotation of the anode (60 rpm). The experiments were conducted for current densities between 12 and 24 mA/cm2. As depicted in Figure 3(a), on increasing the values of current density up to 20 mA/cm2, the efficiency of COD removal increases. This is due to the creation of a large number of Al(OH)3 flocs that promote sweep coagulation. On further raising the values of current density, the COD removal efficiency gives uprising due to restricted particle transport caused by coagulant accumulation at the surface of the electrode (Nepo et al. 2017; Özyurt & Camcıoğlu 2018; Asfaha et al. 2022a, b).
Figure 3

Effect of (a) current density at electrolysis time of 40 min and rotational speed of 60 rpm, (b) electrolysis time at current density of 18 mA/cm2 and rotational speed of 60 rpm, and (c) speed of rotation at current density of 18 mA/cm2 and electrolysis time of 40 min during EC on COD removal efficiency by keeping the current density and electrolysis time during EO constant as 30 mA/cm2 and 50 min.

Figure 3

Effect of (a) current density at electrolysis time of 40 min and rotational speed of 60 rpm, (b) electrolysis time at current density of 18 mA/cm2 and rotational speed of 60 rpm, and (c) speed of rotation at current density of 18 mA/cm2 and electrolysis time of 40 min during EC on COD removal efficiency by keeping the current density and electrolysis time during EO constant as 30 mA/cm2 and 50 min.

Close modal

Electrolysis time

With a constant current density and rotational speed of 18 mA/cm2 and 60 rpm, respectively, experiments were carried out to evaluate the effect of electrolysis duration on COD removal efficiency for the EC method. The electrolysis duration was changed from 10 to 60 min. From Figure 3(b), it is apparent that the efficiency of COD removal increases up to 40 min and drops thereafter. This is a result of the production of more ions in the system, which subsequently leads to the release of more Al(OH)3 flocs for pollutant removal (Ehsani et al. 2020; Mariah & Pak 2020; Boinpally et al. 2023). The development of monomeric species and the passivation of cathode were the causes of the efficiency decline that was observed (Bhagawan et al. 2016; Mousazadeh et al. 2021; Asfaha et al. 2022a, b).

Rotational speed

A proper mixing inside the reactor is necessary for the mass transfer of the electrocoagulated species formed at the anodic surface. The speed at which the rotation is given is also a crucial factor to consider as too high a speed can cause the disruption of flocs (Tahreen et al. 2020; Al-Raad & Hanafiah 2021; Villalobos-Lara et al. 2021). The impact of different rotating speeds was analyzed by performing experiments keeping the current density and electrolysis time constant as 18 mA/cm2 and 40 min, respectively. As evident from Figure 3(c), the efficiency of COD removal rises up to a particular value of agitation speed. This is because when the motion of the produced cations and anions increases, the flocs form significantly earlier, resulting in a higher pollutant removal (Khandegar & Saroha 2013; Tahreen et al. 2020; Manikandan & Saraswathi 2022). Furthermore, rotational speeds beyond a particular value inhibit the increase in pollutant removal due to the disintegration of the flocs at high speeds (Tahreen et al. 2020; Al-Raad & Hanafiah 2021; Villalobos-Lara et al. 2021).

The pH of the treated wastewater after EO + EC ranges between 8 and 8.5.

Experimental analysis and optimization of the EO + EC process by the Taguchi method

The preliminary experimental investigation helps in determining the ranges of the operating parameters, based on which the experimental design was constructed using the Taguchi method in Minitab. The design was constructed considering five parameters of five levels each. The experiments were performed in duplicates, and an average of the two values was considered. COD, color, and TOC were considered as the three major responses to study the performance of the hybrid process. Table 2 depicts the experimental design matrix and the values of corresponding responses.

Table 2

Experimental design matrix and corresponding responses

Set no.Operating parameters
Responses
JEO (mA/cm2)tEO (min)JEC (mA/cm2)tEC (min)NEC (rpm)COD (%)Color (%)TOC (%)
10 20 14 30 40 19.07 91.90 45.21 
15 30 14 35 45 40.21 99.08 50.01 
20 40 14 40 50 60.53 99.31 82.01 
25 50 14 45 55 68.31 99.49 80.63 
30 60 14 50 60 46.60 99.17 55.50 
20 50 16 30 45 47.41 99.40 60.51 
25 60 16 35 50 65.21 99.87 76.99 
30 20 16 40 55 67.86 99.23 63.39 
10 30 16 45 60 55.97 97.60 60.77 
10 15 40 16 50 40 63.24 98.79 79.97 
11 30 30 18 30 50 55.45 99.65 75.40 
12 10 40 18 35 55 54.49 98.64 60.79 
13 15 50 18 40 60 61.45 99.45 75.15 
14 20 60 18 45 40 68.37 99.78 69.00 
15 25 20 18 50 45 68.19 99.03 79.85 
16 15 60 20 30 55 52.39 99.07 50.09 
17 20 20 20 35 60 59.23 98.75 66.79 
18 25 30 20 40 40 72.00 99.60 73.31 
19 30 40 20 45 45 50.50 99.54 80.32 
20 10 50 20 50 50 55.78 99.09 73.59 
21 25 40 22 30 60 44.95 99.65 49.33 
22 30 50 22 35 40 62.44 99.43 62.49 
23 10 60 22 40 45 59.98 98.91 77.67 
24 15 20 22 45 50 58.64 98.90 66.43 
25 20 30 22 50 55 46.22 98.62 65.33 
Set no.Operating parameters
Responses
JEO (mA/cm2)tEO (min)JEC (mA/cm2)tEC (min)NEC (rpm)COD (%)Color (%)TOC (%)
10 20 14 30 40 19.07 91.90 45.21 
15 30 14 35 45 40.21 99.08 50.01 
20 40 14 40 50 60.53 99.31 82.01 
25 50 14 45 55 68.31 99.49 80.63 
30 60 14 50 60 46.60 99.17 55.50 
20 50 16 30 45 47.41 99.40 60.51 
25 60 16 35 50 65.21 99.87 76.99 
30 20 16 40 55 67.86 99.23 63.39 
10 30 16 45 60 55.97 97.60 60.77 
10 15 40 16 50 40 63.24 98.79 79.97 
11 30 30 18 30 50 55.45 99.65 75.40 
12 10 40 18 35 55 54.49 98.64 60.79 
13 15 50 18 40 60 61.45 99.45 75.15 
14 20 60 18 45 40 68.37 99.78 69.00 
15 25 20 18 50 45 68.19 99.03 79.85 
16 15 60 20 30 55 52.39 99.07 50.09 
17 20 20 20 35 60 59.23 98.75 66.79 
18 25 30 20 40 40 72.00 99.60 73.31 
19 30 40 20 45 45 50.50 99.54 80.32 
20 10 50 20 50 50 55.78 99.09 73.59 
21 25 40 22 30 60 44.95 99.65 49.33 
22 30 50 22 35 40 62.44 99.43 62.49 
23 10 60 22 40 45 59.98 98.91 77.67 
24 15 20 22 45 50 58.64 98.90 66.43 
25 20 30 22 50 55 46.22 98.62 65.33 

Response analysis

The Taguchi ‘Larger is better’ function was used to maximize the COD, color, and TOC removal efficiencies. To determine the optimum setting of the parameters for the combined process, the experimental results obtained for different response variables were analyzed in MINITAB 17. The S/N ratio plots depicting the interaction between the operating variables (JEO, tEO, JEC, NEC, and tEC) and the responses, COD, color, and TOC removal efficiency, are shown in Figure 4(a)–4(c), respectively. The optimum experimental set for maximum removal efficiencies is identified by the values of the operating variables corresponding to the maximum points in the plots (Ozyonar 2016; Gokkus et al. 2018; Ibrahim & Salman 2022). Therefore, for maximum COD, color, and TOC removal, the favorable combination of the operating variables is: for EO, current density = 25 mA/cm2, electrolysis time = 50 min; for EC, current density = 18 mA/cm2, speed of rotation = 50 rpm and electrolysis time = 40 min. The optimal conditions obtained for maximum COD, color, and TOC removal efficiency are the same.
Figure 4

S/N ratio plot after EO + EC for efficiency of (a) COD removal, (b) color removal, and (c) TOC removal for 25 experimental sets.

Figure 4

S/N ratio plot after EO + EC for efficiency of (a) COD removal, (b) color removal, and (c) TOC removal for 25 experimental sets.

Close modal

Furthermore, the contribution of each operating variable in COD, color, and TOC abatement is determined using Equations (4)–(7) and shown in Table 3. From Table 3, it is evident that the current density and electrolysis time during the EC process have the greatest impact on COD and TOC elimination. This can be due to the reason that the wastewater has a high percentage of suspended particles, which are majorly removed during the EC process as EO is ineffective against suspended impurities (Chakchouk et al. 2017; Özyurt & Camcıoğlu 2018; Asfaha et al. 2021). However, from Table 3, it can also be seen that the color removal depends largely on the operating variables at the time of EO. After EO, almost 97.5–99.5% of the color is removed from the wastewater in all the experimental combinations.

Table 3

Percentage contribution of operating variables on COD, color, and TOC abatement

Operating variablesResponseMean SNR (Signal to noise ratio)hihContribution (%)
EO process 
 Current density COD 34.749 4.094 21.199 19.31 
 Current density Color 39.9 0.029 0.084 35.55 
 Current density TOC 36.426 0.859 8.939 9.61 
 Electrolysis time Color 39.9 0.019 0.084 23.07 
 Electrolysis time TOC 36.426 0.629 8.939 7.04 
 Electrolysis time COD 34.749 1.353 21.199 6.38 
EC process 
 Current density Color 39.9 0.013 0.084 15.46 
 Current density TOC 36.426 1.243 8.939 13.9 
 Current density COD 34.749 6.032 21.199 28.45 
 Electrolysis time COD 34.749 8.699 21.199 41.03 
 Electrolysis time Color 39.9 0.011 0.084 13.19 
 Electrolysis time TOC 36.426 4.3 8.939 48.11 
 Speed of rotation COD 34.749 1.019 21.199 4.8 
 Speed of rotation Color 39.9 0.01 0.084 12.73 
 Speed of rotation TOC 36.426 1.908 8.939 21.34 
Operating variablesResponseMean SNR (Signal to noise ratio)hihContribution (%)
EO process 
 Current density COD 34.749 4.094 21.199 19.31 
 Current density Color 39.9 0.029 0.084 35.55 
 Current density TOC 36.426 0.859 8.939 9.61 
 Electrolysis time Color 39.9 0.019 0.084 23.07 
 Electrolysis time TOC 36.426 0.629 8.939 7.04 
 Electrolysis time COD 34.749 1.353 21.199 6.38 
EC process 
 Current density Color 39.9 0.013 0.084 15.46 
 Current density TOC 36.426 1.243 8.939 13.9 
 Current density COD 34.749 6.032 21.199 28.45 
 Electrolysis time COD 34.749 8.699 21.199 41.03 
 Electrolysis time Color 39.9 0.011 0.084 13.19 
 Electrolysis time TOC 36.426 4.3 8.939 48.11 
 Speed of rotation COD 34.749 1.019 21.199 4.8 
 Speed of rotation Color 39.9 0.01 0.084 12.73 
 Speed of rotation TOC 36.426 1.908 8.939 21.34 

Enhancement in the pollutant removal efficiencies over EO after EC

The significance of conducting the EC process post EO process was determined by the improvement in pollutant removal obtained over EO after EC in the hybrid process. The efficiency of color removal after EO for all the experiments ranges between 97 and 99.5%, not leaving significant space for the EC process to deliver. However, the EC process has shown appreciable improvement in COD and TOC removal. Therefore, percentage enhancement in color removal is not considered as a major response parameter after EC. Figure 5 shows the percentage improvement in COD and TOC removal efficiency over EO after EC. After EC, the maximum percentage enhancement in the efficiency of COD and TOC removal over EO were obtained as 65.11 and 63.57%, respectively. This implies that EC post EO is capable of removing a significant fraction of COD and TOC from the wastewater, which will reduce the load on the biological treatment units. This massive improvement in the COD and TOC abatement efficiencies indicates that the suspended and colloidal carbonic and non-carbonic pollutants are getting removed during the EC process. However, a minimum percentage increase in the efficiency of COD and TOC removal after EC over EO was obtained as 15.50 and 13.64% for the experimental conditions where the values of current density and electrolysis time are the lowest for both the processes. This suggests that current density and electrolysis time are the major operating variable for both processes for better pollutant removal (Sen et al. 2019; Sandhwar 2020; Boinpally et al. 2023).
Figure 5

Enhancement in removal efficiency of COD and TOC over EO after EC.

Figure 5

Enhancement in removal efficiency of COD and TOC over EO after EC.

Close modal

Removal of inorganic carbon after EC process

For a comprehensive wastewater treatment, inorganic impurities must also be removed alongside the organic contaminants. It was observed after every experimental set that the inorganic carbon content of wastewater after treatment with EO is approximately identical to the inorganic carbon content of the raw wastewater, i.e., 36.37 mg/L which is an average of 25 sets. This indicates that little or no removal of inorganic carbon is taking place during EO. This is owing to the fact that EO is only efficient against dissolved contaminants and cannot remove substantial volumes of suspended particles from wastewater (Chakchouk et al. 2017; Özyurt & Camcıoğlu 2018; Asfaha et al. 2021). To determine the amount of inorganic carbon removed in the EC process post EO process, the experiments for EC were performed after EO at a constant speed of rotation of 50 rpm and varying current density and electrolysis time between 14–22 mA/cm2 and 30–50 min. For all the experiments, the operating parameters during EO were kept fixed as: current density = 25 mA/cm2, electrolysis time = 50 min.

Figure 6 shows the variation of inorganic carbon after EC with electrolysis time at different current densities. It can be seen from Figure 6 that the inorganic content of the sample decreases with time at all the current densities. This is because longer electrolysis times result in a higher rate of production of metal hydroxide floc and bubbles, which are necessary for the coagulation of suspended contaminants (Ehsani et al. 2020; Manikandan & Saraswathi 2022; Boinpally et al. 2023). These sticky flocs catch inorganic contaminants, forming larger flocs that can be further eliminated from the system through sedimentation (Kuokkanen Kuokkanen et al. 2013; Asfaha et al. 2021; Tegladza et al. 2021). It is also evident from Figure 6 that the slope of reduction of inorganic carbon tends to reduce after a certain time duration for all the current densities. This trend at high electrolysis times is a result of the formation of a non-pervious coating on the surface of the anode due to passivation of the anode (Bhagawan et al. 2016; Mousazadeh et al. 2021; Manikandan & Saraswathi 2022). Figure 6 also indicates that the removal of inorganic carbon increases as the current density increases due to the production of more metal hydroxide flocs. However, the little difference in inorganic carbon removal was observed at high current densities owing to the passivation of anodic surfaces (Miriam et al. 2021; Manikandan & Saraswathi 2022; Xu et al. 2022). After EC post EO, the residual inorganic carbon content of the wastewater after 50 min electrolysis for current densities 14, 16, 18, 20, and 22 mA/cm2 was 10.11, 2.13, 0.1, 0.32 m, and 8.11 mg/L, respectively. The maximum inorganic carbon removal of 99.72% was observed at 18 mA/cm2 after electrolysis of 50 min.
Figure 6

Variation of inorganic carbon after EC with electrolysis time at different current densities at a speed of rotation of 50 rpm by keeping operating parameters during EO fixed as: current density = 25 mA/cm2, electrolysis time = 50 min.

Figure 6

Variation of inorganic carbon after EC with electrolysis time at different current densities at a speed of rotation of 50 rpm by keeping operating parameters during EO fixed as: current density = 25 mA/cm2, electrolysis time = 50 min.

Close modal

Optimization of EO + EC process

From the S/N ratio plot (Figure 4), the optimal combination of the operational variables for the maximum COD, color, and TOC removal is: For EO, current density = 25 mA/cm2, electrolysis time = 50 min; for EC, current density = 18 mA/cm2, speed of rotation = 50 rpm, and electrolysis time = 40 min. An experimental run by configuring this combination of operating variables for EO + EC was conducted. The efficiencies of COD, color, and TOC removal during sequential EO and EC treatment of the simulated textile wastewater at the optimum experimental conditions are depicted in Figure 7(a). It can be seen that 50 min EO, if followed sequentially by 60 min EC, resulted in the COD, color, and TOC abatement of 74.69, 99.64, and 75.49%, respectively. When EO is employed as the first step in treating textile effluent, persistent organics and other dissolved chemicals are degraded. Furthermore, a rise in the electrolysis time and current density during EO for better pollutant removal significantly increases the energy consumption of the process (Özyurt & Camcıoğlu 2018; Song Sun et al. 2022; Guvenc et al. 2024). The inorganic carbon content of the wastewater has decreased from 35.95 to 7.98 mg/L after 40 min EC, which further reduces to 0.1 mgl/L after 50 min. From Figure 7(a), it can also be seen that a significant portion of the color is removed during EO. The percentage of COD, color, and TOC removal becomes nearly constant after 40 min electrolysis time during EC.
Figure 7

(a) Abatement of COD, color, and TOC after 50 min EO and 60 min EC, (b) total energy consumption and improvement in BI at different durations for the conditions: for EO, current density = 25 mA/cm2, electrolysis time = 50 min; for EC, current density = 18 mA/cm2, speed of rotation = 50 rpm and electrolysis time = 40 min.

Figure 7

(a) Abatement of COD, color, and TOC after 50 min EO and 60 min EC, (b) total energy consumption and improvement in BI at different durations for the conditions: for EO, current density = 25 mA/cm2, electrolysis time = 50 min; for EC, current density = 18 mA/cm2, speed of rotation = 50 rpm and electrolysis time = 40 min.

Close modal

The improvement in the BI and total energy consumption during EO + EC treatment of the textile wastewater is presented in Figure 7(b). For 50 min electrolysis during EO and 60 min electrolysis during EC, the energy consumption was 32.28 and 6.25 KWh/m3, respectively. This indicates that the EO process alone to achieve a greater removal is not a cost-effective method of remediation. Also, it falls short of addressing the suspended impurities (Chakchouk et al. 2017; Özyurt & Camcıoğlu 2018; Asfaha et al. 2021). However, EC as a sequential step after EO resulted in a greater pollutant removal (both dissolved and suspended) without a significant rise in energy consumption (Özyurt & Camcıoğlu 2018; Asfaha et al. 2021; Tanti & Patel 2023). The total energy consumption for the combined EC + EO at the optimum condition was 36.52 KWh/m3. It is also indicated by Figure 7(b) that following hybrid treatment, the BI of wastewater considerably increases. The BI determines the toxicity of the wastewater. The effluent with BI less than 0.3 is toxic and cannot be remediated biologically (Nagar & Devra 2019; Dhanke & Wagh 2020; Bader et al. 2022). During EO, the BI improved significantly from an initial value of 0.098–0.350. However, for complete biodegradation to take place, the wastewater must have a BI of more than 0.4 (Selvakumar et al. 2010; Rudaru et al. 2022; Yakamercan et al. 2023). From Figure 7(b), it can be seen that the BI increased progressively during the EC process to 0.737 after 40 min of electrolysis. This increase can be accounted for by the elimination of inorganic suspended particles during EC (Chakchouk et al. 2017; Al-Raad & Hanafiah 2021; Asfaha et al. 2021). This suggests that EC after EO eliminated the inorganic suspended contaminants to enhance the BI of the wastewater and make it amenable for biological processes that EO alone cannot.

The efficacy of the EO process in eliminating inorganic pollutants from the wastewater is limited. These pollutants are also inert to biological degradation. Consequently, to prepare the wastewater for biological treatment, a secondary treatment post EO is necessary to eliminate inorganic pollutants (carbon and non-carbon). The efficiency of the combined EO + EC process is accessed in terms of COD, color, and TOC removal. L25 experimental design was obtained by performing a parametric analysis to identify the proper ranges for the operational variables. This design was analyzed in Minitab to obtain the optimal combination of the operating variables. According to the S/N ratio plot, for maximum pollutant removal, the optimal combination for EO is current density = 25 mA/cm2, electrolysis time = 50 min followed by EC with current density = 18 mA/cm2, speed of rotation = 50 rpm ,and electrolysis time = 40 min. A maximum enhancement in the removal efficiencies of COD and TOC were obtained as 65.11 and 63.57%, respectively, post EC over EO, indicating the efficiency of the EC process in eliminating non-carbonic suspended impurities. The inorganic carbon content also decreased from its value of 36.37 mg/L after EO to 0.1 mg/L post EC, and the BI has improved from an initial value of 0.098–0.737 post EO + EC. The quality of treated wastewater has improved significantly in terms of refractory organic and inorganic pollutant removal. The improved biodegradability made the wastewater fit for further biological treatment. Therefore, it becomes necessary to incorporate EC as an additional treatment process post EO to lessen the load on the biological treatment units. The maximum percentage removal efficiencies of COD, color, and TOC after EO + EC at the optimal conditions were 74.69, 99.64, and 75.49%, respectively.

The authors gratefully acknowledge the Public Health Engineering (PHE) lab of MNIT Jaipur for fulfilling our requirements timely.

P.A. developed methodology, performed experimental analysis and investigation, wrote the original draft, reviewed and edited. B.G. performed experiments, experimental analysis and investigation, reviewed and edited the original draft. S.M. conceptualized, supervised reviewed and edited the original draft.

All relevant data are included in the paper or its Supplementary Information.

The authors declare there is no conflict.

Abbar
A. H.
&
Alkurdi
S. S.
(
2021
)
Performance evaluation of a combined electrocoagulation – Electrooxidation process for the treatment of petroleum refinery wastewater
,
IOP Conference Series: Materials Science and Engineering
,
1076
(
1
),
012027
.
Adeogun
A. I.
&
Balakrishnan
R. B.
(
2016
)
Electrocoagulation removal of anthraquinone dye Alizarin Red S from aqueous solution using aluminum electrodes: Kinetics, isothermal and thermodynamics studies
,
Journal of Electrochemical Science and Engineering
, (
April
), 6(2)1 199–213. 10.5599/jese.290.
Al-Raad
A. A.
&
Hanafiah
M. M.
(
2021
)
Removal of inorganic pollutants using electrocoagulation technology: A review of emerging applications and mechanisms
,
Journal of Environmental Management
,
300
(
February
),
113696
.
https://doi.org/10.1016/j.jenvman.2021.113696
.
Asfaha
Y. G.
,
Tekile
A. K.
&
Zewge
F.
(
2021
)
Hybrid process of electrocoagulation and electrooxidation system for wastewater treatment: A review
,
Cleaner Engineering and Technology
,
4
,
100261
.
https://doi.org/10.1016/j.clet.2021.100261
.
Asfaha
Y. G.
,
Zewge
F.
,
Yohannes
T.
&
Kebede
S.
(
2022a
)
Application of hybrid electrocoagulation and electrooxidation process for treatment of wastewater from the cotton textile industry
,
Chemosphere
,
302
(
April
),
134706
.
https://doi.org/10.1016/j.chemosphere.2022.134706
.
Babu Ponnusami
A.
,
Sinha
S.
,
Ashokan
H.
,
V Paul
M.
,
Hariharan
S. P.
,
Arun
J.
,
Gopinath
K. P.
,
Hoang Le
Q.
&
Pugazhendhi
A.
(
2023
)
Advanced oxidation process (AOP) combined biological process for wastewater treatment: A review on advancements, feasibility and practicability of combined techniques
,
Environmental Research
,
237
(
P1
),
116944
.
https://doi.org/10.1016/j.envres.2023.116944
.
Bader
A. C.
,
Hussein
H. J.
&
Jabar
M. T.
(
2022
)
BOD: COD ratio as indicator for wastewater and industrial water pollution
,
International Journal of Special Education
,
37
(
3
),
2164
2171
.
Badmus
K. O.
,
Tijani
J. O.
,
Massima
E.
&
Petrik
L.
(
2018
)
Treatment of persistent organic pollutants in wastewater using hydrodynamic cavitation in synergy with advanced oxidation process
,
Environmental Science and Pollution Research
, 25, 7299–7314. https://doi.org/10.1007/s11356-017-1171-z.
Barcelos
T.
,
Antonelli
R.
&
Martins
J.
(
2024
)
Electrochemical processes for the treatment of contaminant-rich wastewater: A comprehensive review
,
Chemosphere
,
355
(
February
), 141884. https://doi.org/10.1016/j.chemosphere.2024.141884.
Behera
M.
,
Nayak
J.
,
Banerjee
S.
&
Chakrabortty
S.
(
2021
)
A review on the treatment of textile industry waste effluents towards the development of efficient mitigation strategy: An integrated system design approach
,
Journal of Environmental Chemical Engineering
,
9
(
4
),
105277
.
https://doi.org/10.1016/j.jece.2021.105277
.
Bener
S.
,
Bulca
Ö.
,
Palas
B.
,
Tekin
G.
,
Atalay
S.
&
Ersöz
G.
(
2019
)
Electrocoagulation process for the treatment of real textile wastewater: Effect of operative conditions on the organic carbon removal and kinetic study
,
Process Safety and Environmental Protection
,
129
,
47
54
.
https://doi.org/10.1016/j.psep.2019.06.010.
Bhagawan
D.
,
Poodari
S.
,
Golla
S.
,
Himabindu
V.
&
Vidyavathi
S.
(
2016
)
Treatment of the petroleum refinery wastewater using combined electrochemical methods
,
Desalination and Water Treatment
,
57
(
8
),
3387
3394
.
Boinpally
S.
,
Kolla
A.
,
Kainthola
J.
,
Kodali
R.
&
Vemuri
J.
(
2023
)
A state-of-the-art review of the electrocoagulation technology for wastewater treatment
,
Water Cycle
,
4
(
January
),
26
36
.
https://doi.org/10.1016/j.watcyc.2023.01.001
.
Camargo
B. d. C. V.
&
Morales
M. A. M.
(
2013
)
Azo dyes: Characterization and toxicity – A review
,
Textiles and Light Industrial Science and Technology
,
2
(
2
),
85
103
.
Chakchouk
I.
,
Elloumi
N.
,
Belaid
C.
,
Mseddi
S.
,
Chaari
L.
&
Kallel
M.
(
2017
)
A combined electrocoagulation-Electrooxidation treatment for dairy wastewater
,
Brazilian Journal of Chemical Engineering
,
34
(
01
),
109
117
.
Dhanke
P.
&
Wagh
S.
(
2020
)
Treatment of vegetable oil refinery wastewater with biodegradability index improvement
,
Materials Today: Proceedings
,
27
,
181
187
.
https://doi.org/10.1016/j.matpr.2019.10.004
.
Ehsani
H.
,
Mehrdadi
N.
,
Asadollahfardi
G.
,
Bidhendi
G. N.
&
Azarian
G.
(
2020
)
A new combined electrocoagulation-electroflotation process for pretreatment of synthetic and real Moquette-manufacturing industry wastewater: Optimization of operating conditions
,
Journal of Environmental Chemical Engineering
,
8
(
5
),
104263
.
https://doi.org/10.1016/j.jece.2020.104263
.
Fajardo
A. S.
,
Martins
R. C.
,
Silva
D. R.
,
Martínez-huitle
C. A.
&
Quinta-ferreira
R. M.
(
2017
)
Dye wastewaters treatment using batch and recirculation flow electrocoagulation systems
,
Journal of Electroanalytical Chemistry
,
801
(
July
),
30
37
.
http://dx.doi.org/10.1016/j.jelechem.2017.07.015
.
Gilpavas
E.
,
Dobrosz-gómez
I.
&
Gómez-garcía
M. Á
. (
2018a
)
Optimization of sequential chemical coagulation – Electro-oxidation process for the treatment of an industrial textile wastewater
,
Journal of Water Process Engineering
,
22
(
January
),
73
79
.
https://doi.org/10.1016/j.jwpe.2018.01.005
.
Gilpavas
E.
,
Dobrosz-gómez
I.
&
Gómez-garcía
M. Á
. (
2018b
)
Optimization of solar-driven photo-electro-Fenton process for the treatment of textile industrial wastewater
,
Journal of Water Process Engineering
,
24
(
May
),
49
55
.
https://doi.org/10.1016/j.jwpe.2018.05.007
.
Gokkus, O., Yıldız, N., Koparal, A.S. & Yıldız, Y. Ş.
(
2018
)
Evaluation of the effect of oxygen on electro-Fenton treatment performance for real textile wastewater using the Taguchi approach
,
International Journal of Environmental Science and Technology
, 15,
449
460
.
Gunawan
D.
,
Kuswadi
V. B.
,
Sapei
L.
&
Riadi
L.
(
2018
)
Yarn dyed wastewater treatment using hybrid electrocoagulation-fenton method in a continuous system: Technical and economical viewpoint
,
Environmental Engineering Research
,
23
(
1
),
114
119
.
Guvenc
S. Y.
,
Bayat
M. E.
,
Can-güven
E.
&
Varank
G.
(
2024
)
Hybrid and combined electro-oxidation and peroxi-coagulation processes in effective treatment of textile reverse osmosis concentrate
,
Chemical Engineering Science
,
298
(
February
),
120365
.
https://doi.org/10.1016/j.ces.2024.120365
.
Ibrahim
H. M.
&
Salman
R. H.
(
2022
)
Study the optimization of petroleum refinery wastewater treatment by successive electrocoagulation and electro-oxidation systems
,
Iraqi Journal of Chemical and Petroleum Engineering
,
23
(
1
),
31
41
.
Islam
T.
,
Repon
M. R.
,
Islam
T.
,
Sarwar
Z.
&
Rahman
M. M.
(
2023
)
Impact of Textile Dyes on Health and Ecosystem: A Review of Structure, Causes, and Potential Solutions
.
Berlin, Heidelberg
:
Springer
.
https://doi.org/10.1007/s11356-022-24398-3
.
Jawad
N. H.
&
Najim
S. T.
(
2018
) ‘
Removal of methylene blue by direct electrochemical oxidation method using a graphite anode removal of methylene blue by direct electrochemical oxidation method using a graphite anode
’,
International Conference on Materials Engineering and Science
.
Jorge
A. M. S.
,
Athira
K. K.
,
Alves
M. B.
,
Gardas
R. L.
&
Pereira
J. F. B.
(
2023
)
Textile dyes effluents: A current scenario and the use of aqueous biphasic systems for the recovery of dyes
,
Journal of Water Process Engineering
,
55
,
104125
.
https://doi.org/10.1016/j.jwpe.2023.104125
.
Kallawar
G. A.
&
Bhanvase
B. A.
(
2024
)
A review on existing and emerging approaches for textile wastewater treatments: Challenges and future perspectives
,
Environmental Science and Pollution Research International
,
31
(
2
),
1748
1789
.
https://doi.org/10.1007/s11356-023-31175-3
.
Khandegar
V.
&
Saroha
A. K.
(
2013
)
Electrocoagulation for the treatment of textile industry effluent – A review
,
Journal of Environmental Management
,
128
,
949
963
.
http://dx.doi.org/10.1016/j.jenvman.2013.06.043
.
Kishor
R.
,
Purchase
D.
,
Saratale
G. D.
,
Saratale
R. G.
,
Ferreira
L. F. R.
,
Bilal
M.
,
Chandra
R.
&
Bharagava
R. N.
(
2021
)
Ecotoxicological and health concerns of persistent coloring pollutants of textile industry wastewater and treatment approaches for environmental safety
,
Journal of Environmental Chemical Engineering
,
9
(
2
),
105012
.
https://doi.org/10.1016/j.jece.2020.105012
.
Kuleyin
A.
,
Gök
A.
,
Atalay Eroğlu
H.
,
Özkaraova
E. B.
,
Akbal
F.
,
Jada
A.
&
Duply
J.
(
2022
)
Combining Electro-Fenton and adsorption processes for reclamation of textile industry wastewater and modeling by artificial neural networks
,
Journal of Electroanalytical Chemistry
,
921
,
116652
.
Kuokkanen
V.
,
Kuokkanen
T.
,
Rämö
J.
&
Lassi
U.
(
2013
)
Recent applications of electrocoagulation in treatment of water and wastewater – A review
,
Green and Sustainable Chemistry
,
03
(
02
),
89
121
.
Lindholm-lehto
P. C.
&
Knuutinen
J. S.
(
2015
)
Refractory organic pollutants and toxicity in pulp and paper mill wastewaters
,
Environmental Science and Pollution Research
,
22
,
6473
6499
.
Ling
Y.
,
Hu
J.
,
Qian
Z.
,
Zhu
L.
&
Chen
X.
(
2016
)
Continuous treatment of biologically treated textile effluent using a multi-cell electrochemical reactor
,
Chemical Engineering Journal Journal
,
286
,
571
577
.
Mariah
G. K.
&
Pak
K. S.
(
2020
)
Removal of brilliant green dye from aqueous solution by electrocoagulation using response surface methodology
,
Materials Today: Proceedings
,
20
(
xxxx
),
488
492
.
https://doi.org/10.1016/j.matpr.2019.09.175
.
Miriam
L.
,
Flores-hidalgo
M. A.
&
Reynoso-cuevas
L.
(
2021
)
Electrocoagulation process: An approach to continuous processes, reactors design
,
Pharmaceuticals Removal, and Hybrid systems-A Review, Processes, 9, 1831
. https://doi.org/10.3390/pr9101831.
Mountassir
Y.
,
Benyaich
A.
,
Berçot
P.
&
Rezrazi
M.
(
2015
)
Potential use of clay in electrocoagulation process of textile wastewater: Treatment performance and flocs characterization
,
Journal of Environmental Chemical Engineering
,
3
(
4
),
2900
2908
.
http://dx.doi.org/10.1016/j.jece.2015.10.004
.
Mousazadeh
M.
,
Niaragh
E. K.
,
Usman
M.
,
Khan
S. U.
&
Sandoval
M. A.
(
2021
)
A critical review of state-of-the-art electrocoagulation technique applied to COD-rich industrial wastewaters
,
Environmental Science and Pollution Research
, 28,
43143
43172
.
Nagar
N.
&
Devra
V.
(
2019
)
A kinetic study on the degradation and biodegradability of silver nanoparticles catalyzed methyl orange and textile effluents
,
Heliyon
, (
January
),
e01356
.
https://doi.org/10.1016/j.heliyon.2019.e01356
.
Naje
A. S.
,
Chelliapan
S.
,
Zakaria
Z.
&
Abbas
S. A.
(
2016
)
Electrocoagulation using a rotated anode: A novel reactor design for textile wastewater treatment
,
Journal of Environmental Management
,
176
,
34
44
.
http://dx.doi.org/10.1016/j.jenvman.2016.03.034
.
Navarro-franco
J. A.
,
Garzón-zúñiga
M. A.
,
Drogui
P.
&
Buelna
G.
(
2021
)
Electro-oxidation in combination with biological processes for removal of persistent pollutants in wastewater: A review
,
Journal of Electrochemical Science and Technology
,
13
(
November
),
1
18
.
Navarro-franco
J. A.
,
Garzón-zúñiga
M. A.
,
Drogui
P.
,
Buelna
G.
,
Gortares-moroyoqui
P.
,
Barragán-huerta
B. E.
,
Vigueras-cortés
J. M.
,
Politécnico
I.
,
Ipn
N.
,
Fraccionamiento
S.
,
Ii
D. N.
&
Durango
C. P.
(
2022
)
Electro-oxidation in combination with biological processes for removal of persistent pollutants in wastewater: A review
,
J. Electrochem. Sci. Technol.
,
13
(
1
),
1
18
.
Nepo
J.
,
Gourich
B.
,
Cha
M.
,
Stiriba
Y.
,
Vial
C.
,
Drogui
P.
&
Naja
J.
(
2017
)
Electrocoagulation process in water treatment: A review of electrocoagulation modeling approaches
,
Desalination
,
404
,
1
21
.
Özyurt
B.
&
Camcıoğlu
Ş
. (
2018
) ‘
Applications of combined electrocoagulation and electrooxidation treatment to industrial wastewaters
’,
Wastewater and Water Quality
.
Paździor
K.
,
Bilińska
L.
&
Ledakowicz
S.
(
2019
)
A review of the existing and emerging technologies in the combination of AOPs and biological processes in industrial textile wastewater treatment
,
Chemical Engineering Journal
,
376
(
December 2018
),
120597
.
https://doi.org/10.1016/j.cej.2018.12.057
.
Punzi
M.
,
Nilsson
F.
,
Anbalagan
A.
,
Svensson
B.
,
Jönsson
K.
,
Mattiasson
B.
&
Jonstrup
M.
(
2015
)
Combined anaerobic – Ozonation process for treatment of textile wastewater: Removal of acute toxicity and mutagenicity
,
Journal of Hazardous Materials
,
292
,
52
60
.
http://dx.doi.org/10.1016/j.jhazmat.2015.03.018
.
Rudaru
D.
,
Lucaciu
I. E.
&
Fulgheci
A.
(
2022
)
Correlation between BOD5 and COD – Biodegradability indicator of wastewater
,
Romanian Journal of Ecology & Environmental Chemistry
,
4
(
2
),
80
86
.
Saleh
M.
,
Yildirim
R.
,
Isik
Z.
,
Karagunduz
A.
,
Keskinler
B.
&
Dizge
N.
(
2021
)
Optimization of the electrochemical oxidation of textile wastewater by graphite electrodes by response surface methodology and artificial neural network
,
Water Science and Technology
,
84
(
5
),
1245
1256
.
Sandhwar
V. K.
(
2020
)
Comparison of COD removal from petrochemical wastewater by electro-fenton and electro oxidation processes: Optimization and kinetic analyses
,
Separation Science and Technology
,
00
(
00
),
1
10
.
https://doi.org/10.1080/01496395.2020.1823414
.
Santhanam
M.
,
Selvaraj
R.
&
Annamalai
S.
(
2017
)
Chemosphere combined electrochemical, sunlight-induced oxidation and biological process for the treatment of chloride containing textile ef fl uent
,
Chemosphere
,
186
,
1026
1032
.
http://dx.doi.org/10.1016/j.chemosphere.2017.08.066
.
Selvakumar
K. V.
,
Basha
C. A.
,
Prabhu
H. J.
,
Narayanan
A.
&
Nagarajan
J.
(
2010
)
Electro oxidation and biodegradation of textile dye effluent containing procion blue 2G using fungal strain phanerochate chrysosporium MTCC 787
,
International Journal of Chemical Reactor Engineering
,
8
, A147. https://doi.org/10.2202/1542-6580.2328.
Selvaraj
D.
&
Arivazhagan
M.
(
2024
)
An integrated (electrocoagulation and adsorption) approach for the treatment of textile industrial wastewater: RSM and ANN based optimization
,
Water, Air, and Soil Pollution
,
235
(
1
),
1
16
.
https://doi.org/10.1007/s11270-023-06840-5
.
Selvaraj
V.
,
Karthika
T. S.
,
Mansiya
C.
&
Alagar
M.
(
2021
)
An over review on recently developed techniques, mechanisms and intermediate involved in the advanced azo dye degradation for industrial applications
,
Journal of Molecular Structure
,
1224
, 129195. https://doi.org/10.1016/j.molstruc.2020.129195.
Sen
S.
,
Prajapati
A. K.
,
Bannatwala
A.
&
Pal
D.
(
2019
)
Electrocoagulation treatment of industrial wastewater including textile dyeing effluent – A review
,
Desalination and Water Treatment
,
161
,
21
34
.
Shi
Y.
,
Yang
Z.
,
Xing
L.
,
Zhang
X.
,
Li
X.
&
Zhang
D.
(
2021
)
Recent advances in the biodegradation of azo dyes
,
World Journal of Microbiology and Biotechnology
,
37
(
8
),
1
18
.
https://doi.org/10.1007/s11274-021-03110-6
.
Song
P.
,
Sun
C.
,
Wang
J.
,
Ai
S.
,
Dong
S.
,
Sun
J.
&
Sun
S.
(
2022
)
Efficient removal of Cu-EDTA complexes from wastewater by combined electrooxidation and electrocoagulation process: Performance and mechanism study
,
Chemosphere
,
287
(
P1
),
131971
.
https://doi.org/10.1016/j.chemosphere.2021.131971
.
Sun
X.
,
Wang
X.
,
Liu
Y.
,
Lian
Y.
,
Meng
L.
&
Su
Z.
(
2022
)
Removing refractory organic matter from nanofiltration concentrated landfill leachate by electrooxidation combined with electrocoagulation: Characteristics and implication for leachate management
,
Journal of Water Process Engineering
,
47
(
March
),
102747
.
https://doi.org/10.1016/j.jwpe.2022.102747
.
Tahreen
A.
,
Jami
M. S.
&
Ali
F.
(
2020
)
Role of electrocoagulation in wastewater treatment: A developmental review
,
Journal of Water Process Engineering
,
37
(
May
),
101440
.
https://doi.org/10.1016/j.jwpe.2020.101440
.
Tanti
M.
&
Patel
U. D.
(
2023
)
A synergistic application of simultaneous electrocoagulation-electrooxidation process for the treatment of floor-wash wastewater containing rhodamine B dye
,
Journal of Water Process Engineering
,
56
(
September
),
104290
.
https://doi.org/10.1016/j.jwpe.2023.104290
.
Tegladza
I. D.
,
Xu
Q.
,
Xu
K.
,
Lv
G.
&
Lu
J.
(
2021
)
Electrocoagulation processes: A general review about role of electro-generated flocs in pollutant removal
,
Process Safety and Environmental Protection
,
146
,
169
189
.
https://doi.org/10.1016/j.psep.2020.08.048
.
Tokay Yılmaz
F. G.
,
Tekin
G.
,
Ersöz
G.
&
and Atalay
S.
(
2023
)
Reclamation of real textile wastewater by sequential advanced oxidation and adsorption processes using corn-cob based materials
,
Environmental Pollution
,
335
(
March
), 122196. https://doi.org/10.1016/j.envpol.2023.122196.
Villalobos-Lara
A. D.
,
Álvarez
F.
,
Gamiño-Arroyo
Z.
,
Navarro
R.
,
Peralta-Hernández
J. M.
,
Fuentes
R.
&
Pérez
T.
(
2021
)
Electrocoagulation treatment of industrial tannery wastewater employing a modified rotating cylinder electrode reactor
,
Chemosphere
,
264
,
128491
.
Wang
Y.
,
Shen
C.
,
Zhang
M.
,
Zhang
B.
&
Yu
Y.
(
2016
)
The electrochemical degradation of ciprofloxacin using a SnO2-Sb/Ti anode: Influencing factors, reaction pathways and energy demand
,
Chemical Engineering Journal Journal
,
296
,
79
89
.
http://dx.doi.org/10.1016/j.cej.2016.03.093
.
Wre
J.
,
Klepacz-sm
A.
&
Bili
L.
(
2017
)
Influence of ozonation and biodegradation on toxicity of industrial textile wastewater
,
Journal of Environmental Management
,
195
,
166
173
.
Yakamercan
E.
,
Bhatt
P.
,
Aygun
A.
,
Adesope
A. W.
&
Simsek
H.
(
2023
)
Comprehensive understanding of electrochemical treatment systems combined with biological processes for wastewater remediation ⋆
,
Environmental Pollution
,
330
(
May
),
121680
.
https://doi.org/10.1016/j.envpol.2023.121680
.
Yao
Y.
,
Teng
G.
,
Yang
Y.
,
Huang
C.
,
Liu
B.
&
Guo
L.
(
2019
)
Electrochemical oxidation of acetamiprid using Yb-doped PbO2 electrodes: Electrode characterization, influencing factors and degradation pathways
,
Separation and Purification Technology
,
211
(
October 2018
),
456
466
.
Yao
J.
,
Lv
S.
,
Wang
Z.
,
Hu
L.
&
Chen
J.
(
2022
)
Variation of current density with time as a novel method for efficient electrochemical treatment of real dyeing wastewater with energy savings
,
Environmental Science and Pollution Research
,
29
(
33
),
49976
49984
.
https://doi.org/10.1007/s11356-022-18927-3
.
Yaseen
D. A.
&
Scholz
M.
(
2019
)
Textile dye wastewater characteristics and constituents of synthetic effluents: A critical review
,
International Journal of Environmental Science and Technology
,
16
(
2
),
1193
1226
.
Zazou
H.
,
Afanga
H.
,
Akhouairi
S.
,
Ouchtak
H.
,
Addi
A. A.
,
Akbour
R. A.
,
Assabbane
A.
,
Douch
J.
,
Elmchaouri
A.
,
Duplay
J.
,
Jada
A.
&
Hamdani
M.
(
2019
)
Treatment of textile industry wastewater by electrocoagulation coupled with electrochemical advanced oxidation process
,
Journal of Water Process Engineering
,
28
,
214
221
.
https://doi.org/10.1016/j.jwpe.2019.02.006
.
Zheng
T.
,
Wang
Q.
,
Shi
Z.
,
Fang
Y.
,
Shi
S.
,
Wang
J.
&
Wu
C.
(
2016
)
Advanced treatment of wet-spun acrylic fiber manufacturing wastewater using three-dimensional electrochemical oxidation
,
Journal of Environmental Sciences
,
50
,
21
31
.
Zhu
X.
,
Ni
J.
,
Wei
J.
,
Xing
X.
&
Li
H.
(
2011
)
Destination of organic pollutants during electrochemical oxidation of biologically-pretreated dye wastewater using boron-doped diamond anode
,
Journal of Hazardous Materials
,
189
(
1–2
),
127
133
.
http://dx.doi.org/10.1016/j.jhazmat.2011.02.008
.
This is an Open Access article distributed under the terms of the Creative Commons Attribution Licence (CC BY-NC-ND 4.0), which permits copying and redistribution for non-commercial purposes with no derivatives, provided the original work is properly cited (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Supplementary data