Electro-coagulation of reactive textile dyes and textile wastewater

Chemical Engineering and Processing 44 (2005) 461–470

Electro-coagulation of reactive textile dyes and textile wastewater A. Alinsafia,b , M. Khemisa , M.N. Ponsa,∗ , J.P. Leclerca , A. Yaacoubib , A. Benhammouc , A. Nejmeddined a

Laboratoire des Sciences du G´enie Chimique, CNRS-ENSIC-INPL, 1, rue Grandville, BP 451, F-54001 Nancy Cedex, France b D´ epartement de Chimie, Semlalia Faculty of Sciences, Cadi Ayyad University, Boulevard Prince Moulay Abdellah, BP 2390, 40000 Marrakech, Morocco c Laboratoire d’Automatique et d’Etudes des Proc´ ed´es, Semlalia Faculty of Sciences, Cadi Ayyad University, Boulevard Prince Moulay Abdellah, BP 2390, 40000 Marrakech, Morocco d D´ epartement de Biologie, Semlalia Faculty of Sciences, Cadi Ayyad University, Boulevard Prince Moulay Abdellah, BP 2390, 40000 Marrakech, Morocco Received 20 November 2003; received in revised form 17 February 2004; accepted 10 June 2004 Available online 25 August 2004

Abstract Electro-coagulation of a blue reactive dye (Drimarene K2LR CDG Blue) solution has been optimised by experimental design and surface response analysis in terms of colour removal and chemical oxygen demand (COD) decrease. The optimal conditions (pH, current density, reaction time) have then been applied to other reactive dyes solutions as well as synthetic and real textile wastewater samples. The biodegradability before and after electro-coagulation has been assessed by short-term respirometry and is increased by this type of treatment. © 2004 Elsevier B.V. All rights reserved. Keywords: Electro-coagulation; Reactive dye; Colour removal; Experimental design; Biodegradability

1. Introduction Wastewater from textile dyeing and finishing factories is a significant source of environmental pollution [1]. Reactive dyes are extensively used in textile industry, fundamentally due to the ability of their reactive groups to bind to textile fibres by covalent bonds formation [2]. These characteristics facilitate the interaction with the fibre and reduce energy consumption [3]. The major environmental problem associated with the use of the reactive dyes is their loss in the dyeing process. The fixation efficiency is in the range 60–90% [3]. Consequently, substantial amounts of unfixed dyes are released in wastewater. Textile wastewater is characterized by high chemical oxygen demand (COD), low biodegradability, high-salt content and is the source of aesthetic pollution related to colour. EU directive 91/271 imposes limits on colour, as it reduces light penetration in receiving water bodies. ∗

Corresponding author. Tel.: +33 3 83 175277; fax: +33 3 83 175326. E-mail address: [email protected] (M.N. Pons).

0255-2701/$ – see front matter © 2004 Elsevier B.V. All rights reserved. doi:10.1016/j.cep.2004.06.010

A wide range of wastewater treatment techniques have been tested. Biological processes (aerobic and anaerobic) [4–6] are probably the most inexpensive ones but dyes are inhibiting bacterial development [7]. A pre-treatment is often necessary to increase the biodegradability. A large range of physico-chemical processes have been proposed: coagulation with alum, ferric chloride, magnesium chloride and lime or polymers [4], adsorption on activated carbon, polymer and mineral sorbents or biosorbents [8,9], chemical oxidation [1,10,11], photolysis [11,12], suspended [13,14] or supported photocatalysis [15], electrophotocatalysis [16] but, except in the two last cases, they require the addition of chemicals. Electro-coagulation has been successfully used to treat a variety of industrial wastewaters [17–22]. The goal is to form flocs of metal hydroxides within the effluent to be cleaned by electro-dissolution of soluble anodes. Three main processes occur during electro-coagulation: electrolytic reactions at the surface of electrodes, formation of coagulants in aqueous phase, adsorption of soluble or colloidal pollutants on coagulants, and removal by sedimentation and floatation. The

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main reactions at the electrodes are: Al → Al

3+

−

+ 3e (at anode)

(1)

3H2 O + 3e− → 23 H2 + 3OH− (at cathode)

(2)

The destabilized particles then aggregate to form flocs. In the meantime, the tiny hydrogen bubbles produced at the cathode induce the floatation of most flocs, helping to effectively separate particles from wastewater. In addition, the cathode may be chemically attacked by OH− ions generated together with H2 at high pH values [23]. 2Al + 6H2 O + 2OH− → 2Al(OH4 )− + 3H2

(3)

Al(aq) 3+ and OH− ions generated by electrode reactions (1) and (2) react to form various monomeric species which transform finally into Al(OH)3 according to complex precipitation kinetics [24]. Several interaction mechanisms are possible between dye molecules and hydrolysis by-products. Two major mechanisms are generally considered: precipitation (for pH lower than 6.5) and adsorption (for higher pH) [24,25]. Precipitation: Dye + monomeric Al → [Dye-monomeric Al](s)

pH 4–5 (4)

Dye + polymeric Al → [Dye-polymeric Al](s)

pH 5–6 (5)

Adsorption: Dye + Al(OH)3 (s) →→ [particle]

(6)

[Dye-polymeric Al](s) + Al(OH)3 (s) →→→ [particle] (7) These flocs polymerise as :

n Al (OH)3 → Aln (OH)3n (8)

Compared with traditional flocculation and coagulation, electro-coagulation has, in theory, the advantage of removing small colloidal particles; they have a larger probability of being coagulated because of the electric field that sets them in motion. Addition of excessive amount of coagulants can be avoided, due to their direct generation by electro-oxidation of a sacrificial anode. Electro-coagulation equipment is simple and easy to operate. Short reaction time and low sludge production [26] are two other advantages of the technique. There are, however, several parameters such as size, shape and distance between electrodes, current density, conductivity, pH, reaction time that should be selected with care to optimise the process efficiency. G¨urses [24] have investigated the effect of electrode nature, mixing, cell voltage, electrolysis time and current density on aqueous solutions of reactive dyes. The present study aims at evaluating the influence of the key process variables such as current density, electrolysis time and initial pH on the efficiency of treatment (or pretreatment) of textile wastewater containing reactive dyes. Textile wastewater exhibit usually high pH and contains

large amounts of substances such as sizing agents, surfactants, volatile organic compounds, salts that can interfere with electro-coagulation. The experiments were carried out according to a 23 full factorial experimental design. Then, the process was optimised according to a 22 factorial experimental design to improve the efficiency of decolourisation and the abatement of organic matter. Finally the effect of electro-coagulation performed under optimal conditions on the biodegradability of the effluents has been investigated. 2. Materials and methods Aluminum (composition: C: 0.45–0.5%; Mn: 0.5–0.8%; Si: 0.4%; Al: 98.3–98.61%) flat electrodes of rectangular shape (height = 100 mm; width = 50 mm and distance between electrodes = 20 mm) were used in a 100 ml electrocoagulator made out of Pyrex glass. The solution to be treated is stored in a magnetically stirred reservoir. The experimental set-up is given in Fig. 1. Sodium chloride was added in all runs so to have a conductivity of the solution of 4.7 mS/cm. Cell voltage and current were measured by digital voltmeter and ampmeter, respectively. The solution (total volume = 500 ml) was continuously circulated in the system with the help of a peristaltic pump at a flowrate of 370 ml/min. This corresponds to a Reynolds number of about 220 in the reaction chamber. The flow regime is laminar and favours the growth of large flocs that are easier to remove. The current efficiency (φ) for the production of dissolved Al3+ was calculated by comparison of the weight loss of the aluminium electrodes during the experiment (mexp ) with the theoretical amount of aluminium consumed according to Faraday’s law (mtheo ). φ=

mexp mtheo

(9)

where mtheo = ItMAl /3F with I (A) is the current intensity, t (s) the experiment duration, MAl (g/mol) the molar mass of aluminium and F the Faraday constant.

Fig. 1. Experimental set-up. 1: DC power supply, 2: Digital Ampermeter, 3: Digital Voltmeter, 4: Anode and cathode, 5: Sample of wastewater, 6: Peristaltic pump, 7: Magnetic stirring controller.

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The specific electrical energy consumption (seec) was calculated as a function of the applied cell voltage (U in volts) [27]. seec (kWh/kg Al) =

3FU 3.6 × 103 MAl φ

(10)

Solutions of reactive textile dyes (at a concentration of 50 mg/l) were prepared by dissolution in de-ionised water of Drimarene (Clariant, Mutenz, Switzerland) K2LR CDG Blue, Drimarene Black and Yellow Procion Hexl (Dystar, Frankfurt, Germany). Synthetic textile wastewater was obtained by dissolution of hydrolysed reactive dyes (Drimarene K2LR CDG Blue (2.78 mg/l); Drimarene KG Orange (3 mg/l); Drimarene K8B CDG Red (24.3 mg/l)), hydrolysed starch (2.78 mg/l), (NH4 )2 SO4 (5.56 mg/l) and Na2 HPO4 (5.56 mg/l) in de-ionised water. Hydrolysis was performed by heating the solutions at 80 ◦ C for 1.5 h after adjustment at pH 12. Synthetic textile wastewater pH was adjusted at 10 and conductivity at 4.7 mS/cm. Two real textile wastewater samples from a knit cotton factory (Marrakech, Morocco) (global effluent), which is using the same type of dyes were also tested. Dyes concentrations were estimated from their absorbance characteristics in the UV–vis range (200–800 nm). A SECOMAM (Domont, France) Anthelie Light spectrophotometer connected to a PC was used. Each dye is associated to a main absorbance band at a characteristic wavelength: in the concentration range used throughout this study, linear relations between dye concentration and absorbance at the dye characteristic wavelength were obtained. Dissolved organic carbon (DOC) measurements were carried out on an APOLLO 9000 total organic carbon analyser after filtration (10 ␮m). Chemical oxygen demand (COD) was measured on a Hach 2400 (Loveland, Colorado, USA) (Method 8000). pH and conductivity were measured using respectively a PHM 220 pHmeter and a CDM 210 conductimeter (Radiometer Analytical SAS, Villeurbanne, France). To compare the efficiency of electro-coagulation with respect to wastewater biodegradability short-term respirometry

463

batch tests were performed [28]. Activated sludge (1.6 l ) from the local domestic wastewater treatment plant was placed into the 2 l-respirometer, equipped with an air-sparger and a mechanical stirrer. The dissolved oxygen concentration was monitored with Orbisphere (Marin, Switzerland) electrodes connected to a PC for data logging. Activated sludge was successively spiked with a sodium acetate solution, which acts as a reference carbon source, the wastewater sample to be tested and again the sodium acetate solution (Fig. 2). The dissolved oxygen (S0 ) mass balance in the liquid phase is given by: dS0 = KL a(S0∗ − S0 ) − OURexo − OURend dt

(11)

where S0∗ is the dissolved oxygen concentration at saturation, KL a is the oxygen mass transfer coefficient, OURend , the oxygen uptake rate for slowly biodegradable substances and OURexo the oxygen uptake rate for rapidly biodegradable substances. When recalcitrant and/or toxic substances (with respect to the activated sludge bacteria) are present in the wastewater sample, the oxygen uptake rates decrease. The respirograms were characterized by the maximal value taken by OUR (OURmax ) and the volume of oxygen consumed for 20 min after the injection of the wastewater sample. Fig. 2 presents a typical respirogram.

3. Experimental design Statistical calculations were done using NEMRODW version 2000 (LPRAI, Marseille, France). In a first stage, the effect of three electrochemical variables (current density, electrolysis time and initial pH of the solution) on the decolourisation was investigated according to a 23 full factorial experimental design with five replicates of the centre point. Before statistical analysis, the original variables X1 (electrolysis time), X2 (current density) and X3 (initial pH of the solution) were reduced. The levels for the three main variables were chosen from previous know-how. The original and reduced levels are given in Table 1.

Fig. 2. Typical protocol of biodegradability analysis by respirometry.

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Table 1 Original and reduced levels Parameters

Electrolysis time (min) pH Current density (mA/cm2 )

Original variable (X)

Reduced variable (x) −1

0

+1

X1 X2 X3

60 7 10

90 8.5 25

120 10 40

The choice of pH in the range 7–10 is on one hand due to the good efficiency of the electrocoagulation treatment at pH between 4 and 9 with aluminium electrodes [19,29,30] and on the other hand to the alkaline character of the real textile wastewater discharged on the industrial site related to the present study. The choice of an electrolysis time in the range 60–120 min may appear large compared to what is described in literature. It is due mainly to the important sample volume (500 ml) compared to the capacity of cell (100 ml). In a second stage, the main objective was to select the current density and the electrolysis time in order to achieve optimal COD removal and decolourisation. We considered a 22 Doehlert matrix for investigating the effect of current density and electrolysis time, while the initial pH of the solution was set to 10, as this value is close to the real textile wastewater pH. Uniform Doehlert networks were generated from a Simplex (Table 2). Fig. 3. Absorbance spectra (A) and kinetic curves of colour and dissolved organic carbon (B) of Drimarene K2LR CDG Blue dye vs. reaction time for an initial pH 10 and current density = 10 mA/cm2 .

4. Results and discussion 4.1. Decolourisation kinetics Colour is effectively removed by electro-coagulation, as depicted in Fig. 3 for a solution of Drimarene K2LR CDG Blue. A global decrease of the UV–vis absorbance is observed. Simultaneously DOC decreases. DOC abatement in this case is about 46% and can reach up 54% in some experiments. 4.2. Statistical analysis and modelling The objective is to provide a predictive model able to explain the influence of operational parameters on product quality. The dimension of the model is very much reduced compared to the dimension of the concerned data group. The results obtained for the 23 full factorial design are given in Table 3 for Drimarene K2LR CDG Blue, which decolourisation yield varies between 72 and 98% (average value 92%). Table 2 The coordinates of the initial Simplex Number

X1 (electrolysis time)

X2 (current density)

1 2 3

0 1 0.5

0 0 0.866

The experimental error (2.8%) due to uncontrolled factors is calculated from the replicates of the centre point. The decolourisation yield (Y1 ) can be predicted by Eq. (12) using the coefficients listed in Table 4. Y1 = b0 + b1 X1 + b2 X2 + b3 X3 + b12 (X1 X2 ) + b13 (X1 X3 ) + b23 (X2 X3 ) + b123 (X1 X2 X3 )

(12)

From the experimental values taken by the Student coefficient texp , an experimental significance level is calculated. b0 , b1 and b3 are significant at a level less than 5%, when the interaction coefficient b13 is significant at a level less than 10%. Therefore the reaction time (coefficient b1 ), the current density (coefficient b3 ) and their interaction (coefficient b13 ) are the most influential factors. In fact, the decolourisation is occurring by adsorption [25] on Al(OH)3 (s) or on the monomeric anion Al(OH)4 − depending upon the dye chemical structure, which is unfortunately unknown for most commercial dyes. In the present case no adjustment is needed for pH: on the contrary to what is observed for the current density and the reaction time, its significance level is very high (85%), which means that pH is not an influential parameter. The effects of operational variables on process performance may be explored with wastewater as discharged from the textile dyeing plant. The analysis of variance (Table 5) shows that

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465

Table 3 23 full factorial design with 5 repetitions of the centre point Run

x1 (electrolysis time)

x2 (initial pH)

x3 (current density)

Y1 (decolourisation) (%)

1 2 3 4 5 6 7 8 9 10 11 12 13

−1 1 −1 1 −1 1 −1 1 0 0 0 0 0

−1 −1 1 1 −1 −1 1 1 0 0 0 0 0

−1 −1 −1 −1 1 1 1 1 0 0 0 0 0

72.16 97.83 80.58 88.18 94.13 94.64 96.26 96.26 95.54 95.14 94.66 94.35 98.41

Table 4 Model coefficients

Table 6 Doehlert matrix

Coefficient

Value

Standard deviation

texp

Significance level (%)

Run

X1 (electrolysis time)

X2 (current density)

Y1 (decolourisation)

Y2 (COD removal)

b0 b1 b2 b3 b12 b13 b23 b123

92.165 4.223 0.315 5.317 −2.322 −4.095 0.623 2.195

1.286 1.640 1.640 1.640 1.640 1.640 1.640 1.640

71.64 2.57 0.19 3.24 −1.42 −2.50 0.38 1.34

<0.01 4.92 84.9 2.31 21.5 5.4 71.8 23.8

1 2 3 4 5 6 7 8 9

1 −1 0.5 −0.5 0.5 −0.5 0. 0 0

0 0 0.866 −0.866 −0.866 0.866 0 0 0

97.77 94.79+ 97.23 93.80 90.98 96.07 94.66 94.35 98.41

16.22 16.22 11.36 27.27 36.36 13.64 18.18 16.22 12.12

the predictive model insured a representativity of the experimental data of about 92%, as the significance level calculated from the ratio of the mean square errors due to the regression and to the residues is 7.7. 4.3. Process optimisation The surface response methodology helps to develop a statistical model of a reaction by performing the minimum number of well-chosen experiments and to determine the optimal values of process parameters. This approach is particularly suitable when a given variable depends on the settings of another one (interaction effects). This methodology is here applied to the decolourisation yield and the abatement of COD. The considered factors are the current density in the cell and the electrolysis time. A 22 full factorial design with three replicates of the centre point (Table 6) was applied. Figs. 4 and 5 show the contour plots obtained from the linear models built from the experimental results. These plots

Regression 588 Residues 107 Total

696

Degrees of Mean freedom square error 7 5 12

84 21

Ratio of mean Significance square errors level (%) 3.9

Coefficient

Value

Standard deviation

texp

Significance level (%)

b0 b1 b2 b11 b22 b12

95.807 0.717 2.460 0.473 −1.873 2.298

1.238 1.238 1.238 1.958 1.958 2.477

77.36 0.58 1.99 0.24 −0.96 0.93

<0.01 60.5 14.0 81.7 41.1 42.4

were obtained by calculating the coefficients of Eq. (13) and drawing subsequently the contour for the electrolysis time—density current variable pair for Y1 (Table 7) and Y2 (Table 8): Y = b0 + b1 X1 + b2 X2 + b11 X12 + b22 X22 + b12 X1 X2 (13) Table 8 Coefficients of the predictive model of Y2 (% COD removal)

Table 5 Analysis of variance for decolourisation percentage Sum of square errors

Table 7 Coefficients of the predictive model of Y1 (% decolourisation)

7.7

Coefficient

Value

Standard deviation

texp

Significance level (%)

b0 b1 b2 b11 b22 b12

15.507 1.135 −11.152 0.713 8.631 −6.565

1.727 1.727 1.727 2.731 2.731 3.455

8.98 0.66 −6.46 0.26 3.16 −1.90

0.212 56.0 0.622 80.4 4.95 15.3

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Fig. 4. Two dimensional contour plot obtained from the experimental data of COD removal vs. electrolysis time (X1 ) and current density (X2 ).

Fig. 4 shows that COD removal is maximal in the region where the electrolysis time is between 90 and 120 min and for a current density of about 12 mA/cm2 . In fact, when the current density increases, there are an increase of the amount of aluminium dissolved in the liquid phase and an increase of the production of hydroxide Al(OH)3 . For long electrolysis times, the structure of the sludge may change, altering the efficiency of pollution removal and the settle-ability and floatability properties of the flocs. In Fig. 5, the decolourisation yield is up to 98% in the global experimental plan: high values

of both variables maximize the decolourisation yield due to the good adsorption of dye on sludge. The objective is to determine the optimal pair current density—electrolysis time to achieve both a good decolourisation yield and a good abatement of organic matter expressed as COD. Several scenarios can be examined in order to find the optimal conditions. The objectives for each scenario are transformed into functions di , which give the percentage of satisfaction obtained with respect to the fullfillness of the targets that have been set in terms of decolourisation and COD

Fig. 5. Two dimensional contour plot obtained from the experimental data of decolourisation yield vs. current (X2 ) and electrolysis time (X1 ).

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Table 10 Characteristics of optimal pair (D = desirability) Response

Value

D (%)

Weight

Dmin (%)

Dmax (%)

Y1 (decolourisation) Y2 (COD removal) Global desirability

91.75 35.23

35 87 55.3

1 1

0.0 37.3 0

78 100 88.3

4.4. Treatment efficiency at optimal conditions

Fig. 6. Desirability function.

removal (Fig. 6). The values of di are combined in a geometric mean: D = (d1 × d2 · · · dm )1/m with m is the number of functions di involved in the computation of the total desirability D to be optimised. A minimal efficiency in terms of decolourisation (90%) and COD removal (30%) is required. Two scenarios were tested (Table 9). In Scenario 1, the target for decolourisation was set at 95% and for COD removal at 36%. In Scenario 2, the target for decolourisation was increased but the target for COD was decreased. In both cases, COD removal targets are almost reached but colour removal cannot be achieved as efficiently as expected. To select between both scenarios, another criterion should be incorporated. It could be the cost of electrodes or the energy consumption. Energy consumption could be estimated by the product X1 × X2 . In the present case Scenario 1 was preferred for its lower energy requirement. The optimum is obtained for X1 = 105 min and X2 = 12 mA/cm2 that insures 92% on decolourisation and 35% on COD removal. It is characterised by an average desirability about 55.3% and maximum desirability about 88.3% as shown in Table 10. In this case, the specific electrical energy consumption is about 13.5 kWh/kg Al and the apparent current efficiency is around 1.1, slightly above 1 as in the experiments of Jiang et al. [27], who explained such a discrepancy by the occurrence of secondary reactions. Table 9 Optimal sets for the two scenarios Scenario 1

Decolourisation (%) COD removal (%) Optimal electrolysis time (min) Optimal current density (mA/cm2 ) Y1,theor Y2,theor

Scenario 2

Minimum

Target

Minimum

Target

90 30

95 36

90 30

98 35

104.95

105.68

12

12.21

91.73 35.27

91.82 35

The optimal electro-coagulation conditions found in the previous section (electrolysis time = 105 min and current density = 12 mA/cm2 ) were applied to other reactive dyes as well as synthetic and industrial textile wastewater samples. In industrial environment it is difficult to determine the optimal values of the operation parameters, as the characteristics of the wastewater are changing daily in function of the textile production program. The results show that the electrocoagulation efficiency differs very much according to the dyes. For the blue dye the experimental responses Y1 and Y2 (Table 11) are close to the theoretical ones (Table 9) obtained by the desirability study and validate the choice of the electrolysis time and the current density. For the two simple dye solutions (Yellow Procion and Drimarene Black) high COD removal yields were achieved, in spite of very different initial COD concentration. High decolourisation yields were also observed. In the case of the synthetic wastewater, COD removal was medium in spite of a low initial COD concentration. This synthetic wastewater attempts to mimic the effect of textile dyeing, which is performed at a relatively high temperature, on the dyes and other additives (starch, salts). The two industrial wastewater samples have higher initial COD than the other tested solutions. However the electro-coagulation remains very efficient with respect to COD removal and decolourisation. Those two samples were collected on two successive days, giving another example of the high variability degree of textile wastewater. In any case large variations of DOC are also observed. 4.5. Biodegradability assessment To estimate the level of biodegradability of textile wastewater by the activated sludge before and after the electrocoagulation treatment, batch respirometry tests with activated sludge have been performed. Table 12 shows a summary of the estimated parameters. KL a and OURend were calculated for each experiment. Depending upon the type of sample, the observed behaviour differed. The Drimarene Black sample was slightly biodegradable before electro-coagulation as shown in Fig. 7a by the reduced oxygen uptake rate in spite of a high COD (255 mg/l). Its biodegradability increased after electrocoagulation, which decreases also strongly its COD content. For Textile I wastewater much larger values of oxygen uptake

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Table 11 Efficiency of treatment at optimal conditions (COD0 = initial solution COD) Sample

DOC removal (%)

Y2 (% COD removal)

Y1 (% decolourisation)

Drimarene Blue DR K2LR CDG (COD0 = 154 mg O2 /l) Yellow Procion hexl (COD0 = 95 mg O2 /l) Drimarene Black (COD0 = 255 mg O2 /l) Real wastewater I (COD0 = 450 mg O2 /l) Real wastewater II (COD0 = 620 mg O2 /l) Synthetic wastewater (COD0 = 70 mg O2 /l)

72.8 61.6 18.6 22.8 34.2 51.2

38.2 88.2 81.3 65.2 74.8 76.0

90.7 92.6 94.3 83.3a 98.6a 83.9

a

Average value at three wavelength 620, 525 and 436 nm.

rates were observed before than after electro-coagulation (Fig. 7b), although this treatment decreases strongly also the COD content. Finally in the case of Textile II wastewater, almost no change can be seen in the respirometry patterns (Fig. 7c). Similar behaviours occurred for the yellow and the blue dyes solutions as well as for the synthetic wastewater.

To conclude about an eventual biodegradability improvement after pre-treatment the biodegradability yield is calculated as: YB =

(VO2 /COD)after electro-coagulation (VO2 /COD)before electro-coagulation

Fig. 7. Oxygen uptake rate vs. time for (a) Drimarene Black solution, (b) Textile I wastewater and (c) Textile II wastewater, before and after electro-coagulation.

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Table 12 Summary of the estimated parameters during respiromety tests Before electro-coagulation

Yellow Procion hexl Drimarene K2LR CDG Blue Drimarene Black Synthetic textile wastewater Textile wastewater I Textile wastewater II

After electro-coagulation

YB

OURexomax (mg/l/s)

VO2 (mg/l)

OURexomax (mg/l/s)

VO2 (mg/l)

0.0052 0.0046 0.0037 0.0054 0.016 0.009

3.0 3.3 2. 3.1 13.8 5

0.0055 0.0043 0.0066 0.0054 0.013 0.009

3.0 2.5 2.9 3.2 6.5 4.2

In all tested cases, an increase of the biodegradability was observed but, as for COD and colour removal efficiency, it depends very much upon the sample composition. 5. Conclusions Electro-coagulation is an efficient process, even at high pH, for the removal of colour and total organic carbon in reactive dyes textile wastewater. The efficiency of the process is influenced strongly by the current and the time of the reaction. Optimal electrolysis time and current density were determined to achieve a decolourisation yield between 90 and 95% and COD removal between 30 and 36% for a reactive blue dye. Although these operational parameters were applied to other reactive dyes solutions as well as synthetic and real textile wastewater and led to satisfactory colour removal and increase of biodegradability, the effect of the wastewater nature, which is highly time-variable in an industrial environment, could be pointed out. Acknowledgements The authors are thankful to the textile industry Tenmar and to the French-Moroccan Committee (project MA/02/49). They wish also to thank Professor J.P. Corriou for his helpful comments. References [1] E.G. Solozhenko, N.M. Soboleva, V.V. Goncharut, Decolourization of azo dye solutions by Fenton’s oxidation, Water Res. 29 (1995) 2206–2210. [2] J. Weber, V.C. Stickney, Hydrolysis kinetics of reactive Blue 19-vinyl sulfone, Water Res. 27 (1993) 63–67. [3] R. Camp, P.E. Sturrock, The identification of the derivatives of CI reactive Blue 19 in textile wastewater, Water Res. 24 (1990) 1275–1278. [4] M.T. Kennedy, J.M. Morgan, L.K. Benefield, A.F. McFadden, Color removal from textile dye wastewater: a case study, in: Proceedings of the 47th Ind. Waste Conference, West Lafayette, IN, Lewis Pub, Chelsea, MF, 1992, pp. 727–741. [5] Y.K. Park, C.H. Lee, Dyeing wastewater treatment by activated sludge process with a polyurethane fluidised bed biofilm, Water Sci. Technol. 34 (5–6) (1996) 193–200.

9 1.5 9.5 4.4 2 4

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