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Demirel and Kayan International Journal of Industrial Chemistry 2012, 3:24http://www.industchem.com/content/3/1/24

RESEARCH Open Access

Application of response surface methodology andcentral composite design for the optimization oftextile dye degradation by wet air oxidationMuhammet Demirel1 and Berkant Kayan2*

Abstract

Background: The present study is aimed at investigating the degradation of azo dye solution of AR 274 by wet airoxidation conditions. The central composite design matrix and response surface methodology were applied indesigning the experiments to evaluate the interactive effects of the three most important operating variables. Thus,the interactive effects of oxygen pressure (3.0 to 5.0 MPa), temperature (100°C to 250°C), and time (30 to 90 min)on the degradation of dye were investigated.

Results: The predicted values were found to be in good agreement with the experimental values (R2 = 0.9981 andAdj-R2 = 0.9965), which define the propriety of the model and the achievement of CCD in the optimization of WAOprocess.

Conclusions: Intermediates of dye degradation were detected by GC-MS, the possible degradation mechanism forthe WAO of dye was discussed, and the probable degradation pathway was deduced.

Keywords: Degradation, Response surface methodology, Central composite design, Wet air oxidation

BackgroundDye pollutants from textile and dyestuff industries are amajor hazardous source of environmental contamin-ation. The large quantity of dye wastewater has becomea serious environmental problem owing to the character-istics of high color, high chemical oxygen demand, andfluctuating pH. The direct discharge of this wastewaterinto water bodies such as lakes and rivers causes pollutionof the water and affects the flora and fauna. Effluent fromtextile industries contains different types of dyes, whichshow very low biodegradability owing to their high molecu-lar weight and complex structures [1-3]. Some dyes, espe-cially azo dyes, are known to be biorefractory pollutantseven with carefully selected microorganism and underfavorable conditions. Azo dyes are characterized by thepresence of one or more azo bonds (−N=N-) and accountfor 60% to 70% of all textile dyes used. It is estimated thatapproximately 8×105 tons (t) of dyes are produced annu-ally worldwide, and about 50% of them are azo dyes [4-8].

* Correspondence: [email protected] of Chemistry, Arts and Sciences Faculty, Aksaray University,Aksaray 68100, TurkeyFull list of author information is available at the end of the article

© 2012 Demirel and Kayan; licensee Springer.Commons Attribution License (http://creativecoreproduction in any medium, provided the orig

Thus, azo dyes constitute a significant portion of dyes thatare used in industries nowadays. The product obtainedfrom dye degradation could be mutagenic and carcinogenic,thereby causing long-term health concerns. Therefore, thetreatment of effluents containing such compounds isimportant for the protection of natural waters as well as theenvironment [9-12]. Conventional methods of dyeingwastewater treatment include adsorption, flocculation, ozo-nation, advanced oxidation using UV/H2O2 or UV/TiO2,and biological oxidation. Other advanced oxidation treat-ments for dyeing wastewater treatment are wet air oxida-tion (WAO) and catalytic wet air oxidation (CWAO),which are operated at subcritical water and pressures ofwater. Previous researches have shown that the treatmentefficiencies for various dyes using WAO and CWAO are inthe range of 50% to 90% at the operating times of 30 to240 min in different types of reactors [13-17].A variety of advanced oxidation process (AOPs) have

been attempted for the degradation of dyes, among whichWAO seems to be a clean method as it does not involvethe use of any harmful chemicals and uses only the cleanreagent of air [7,18]. By using WAO, organic pollutants areeither partially oxidized into biodegradable intermediates

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or mineralized to carbon dioxide, water, and innocuous endproducts under elevated temperatures (100°C to 300°C)and pressures (0.5 to 20 MPa) using an oxidant such asoxygen. The enhanced solubility of oxygen in aqueous solu-tions at elevated temperatures and pressures provides astrong driving force for oxidation. The elevated pressuresare required to keep water in the liquid state. Water alsoacts as a moderant by providing a medium for heat transferand removing excess heat by evaporation. WAO has beendemonstrated to oxidize organic compounds to CO2 andother innocuous end products. Carbon is oxidized to CO2;nitrogen is converted to NH3, NO3, or elemental nitrogen;and halogen and sulfur are converted to inorganic halidesand sulfates. The degree of oxidation is mainly a functionof temperature, oxygen partial pressure, residence time,and the oxidizability of the pollutants under consideration[19-22]. WAO is not only eco friendly but also economicalwhen compared to other AOPs that use harmful andexpensive oxidizing agents like ozone and hydrogenperoxide [23-25]. In this research, the aqueous solution ofAcid Red 274 (AR 274) was selected as a model for textilewastewaters for evaluation under WAO conditions. An-other part of this study involved the use of response surfacemethodology (RSM) and finding an applicable approximat-ing function for predicting and determining the furtherresponse, and studying the optimum working state. Thefactors (variables) of oxygen pressure, temperature, andexperimental time were investigated [26].RSM is a kind of mathematical and statistical technique

for designing experiments, building models, evaluating therelative significance of several independent variables, anddetermining the optimum conditions for desirableresponses [5,27,28]. The two most common designs exten-sively used in RSM are the central composite design (CCD)and the Box-Behnken design (BBD). The CCD is ideal forsequential experimentation and allows a reasonable amountof information for testing lack of fit while not involving anunusually large number of design points [29-31].

MethodsAnalysis methodsIn the present study, AR 274 dye concentration was ana-lyzed spectrophotometrically on a UV–vis spectrometer(Shimadzu UV-160A, Shimadzu Corporation, Kyoto, Japan)at 527 nm by measuring the absorbance of the untreatedsamples at maximum wavelength, and the percentage ofAR 274 degradation efficiency percentage was calculatedusing the following formula:

DE% ¼ Co � Ct

Co100 ð1Þ

where Co and Ct represent the initial and remaining AR274 concentration at given time (t), respectively. The

mineralization of AR 274 solution was monitoredthrough the diminishment of the TOC, measured on aTekmar-Dorhmann Apollo 9000 TOC analyzer (TeledyneTechnologies, Inc., OH, USA).The mass analysis process, which is the same as the

previous method, was performed for intermediates ofdye degradation [9]. The gas chromatography–massspectrometry (GC-MS) analysis was performed usingthe 5890A Agilent model gas chromatograph (AgilentTechnologies, Inc., CA, USA), interfaced with theECD, NPD, and 5975C mass selective detector. Theaqueous solutions were extracted three times with 15 mLdichloromethane. A 3-μL sample was analyzed on GC-MS.A HP5-MS capillary column (30 m×0.25 mm×0.25 μm)was used as the analytical column. Helium was usedas the carrier gas with a flow rate of 2 mL/min. TheGC injection port temperature was set at 250°C (splitmode = 1/5), and the column temperature was fixed at70°C for 5 min. Subsequently, the column was sequen-tially heated at a rate of 5°C/min to 120°C and heldfor 1 min, at a rate of 8°C/min to 200°C and held for5 min, and at a rate of 10°C/min to 280°C and heldfor 10 min. The MS detector was operated in the EImode (70 eV).

Experimental design and optimizationIn this study, RSM was used for the optimization ofprocess variable to enhance the degradation of AR274 dye combined with the factorial experimental de-sign of CCD. RSM is a useful method for studying theeffect of several variables influencing the responses byvarying them simultaneously and carrying out a lim-ited number of experiments. A very limited number ofstudies employing the experimental design andoptimization modeling approach for WAO processhave been reported in the literature [32,33]. The CCDis an effective design that is ideal for sequentialexperimentation and allows a reasonable amount ofinformation for testing the lack of fit while not involv-ing an unusually large number of design points. Itwas first announced by Box and Wilson in 1951, andis well suited for fitting a quadratic surface, whichusually works well for the process optimization[31,34-36].In the present study, a CCD was employed for deter-

mining the optimum conditions for dye removal inWAO. The experimental results were analyzed usingDesign Expert 8.1, and the regression model wasproposed. Oxygen pressure, temperature, and reactiontime were chosen as three independent variables inthe degradation process. Accordingly, the CCDmatrixes of 20 experiments covering the full design offive factors were used for building quadratic models asshown in Table 1 [37]. The experimental data obtained


from the CCD model experiments can be representedin the form of the following equation:

Y ¼ bo þXn

i¼1

bixi

þXn

i¼1

biixi2 þ

Xn�1

i¼1

Xn

j¼iþ1

bijxixj þ ei; ð2Þ

where Y is the predicted response; n is the number offactors; xi and xj are the coded variables; bo is the off-set term; bi, bii, and bij are the first-order, quadratic,and interaction effects, respectively; i and j are theindex numbers for factor; and ei is the residual error[35,38].The quality of the polynomial model was expressed by

the coefficient of determination, namely, R2 and Adj-R2.The statistical significance was verified with adequateprecision ratio and by the F test [26]. According to theobtained experimental data, the levels of the three mainparameters investigated in this study are presented inTable 1. For statistical calculations, the variables Xi (thereal value of an independent variable) were coded as xi(dimensionless value of independent variable) accordingto the following equation:

Xi ¼ Xi � Xoð ÞδX

; ð3Þ

where Xo is the value of Xi at the center point, and δXrepresents the step change [9,30,35].

Results and discussionOptimization of degradation conditions using the RSMapproachIn the present study, RSM was employed for identifyingthe simple and interactive effects of operating variablesof dye degradation for WAO process. On the basis ofthe CCD, there are four important stages for theoptimization of the experiments: (1) to perform statisticallydesigned experiments for the experimental plan, (2)recommend the mathematical model basis of the ex-perimental data and focus on the data of analysis ofvariance, (3) control the efficiency of the model directlywith diagnostic plots, and (4) estimate the responseand verify the model [5,27].

Table 1 Experimental range and levels of theindependent variables

Variables Factor Range and level

−α −1 0 +1 +α

Oxygen pressure (MPa) X1 2.32 3.0 4.0 5.0 5.68

Temperature (°C) X2 48.87 100 175 250 301.13

Time (min) X3 9.55 30 60 90 110.45

Thus, RSM was used for obtaining a relationshipbetween factors and the response and for optimizing theresponse. Table 2 depicts a complete 23 factorial designwith four center points in cube, and six axial points andtwo center points in axial. The experiments were carriedout in three replicates and six blocks in order to fit thesecond-order polynomial model [39].According to the RSM results, polynomial regression

modeling was performed on the responses of the corre-sponding coded values of the three different processvariables, and the results were evaluated. The predictedresponse (Y) for the percent TOC of samples treatedwas obtained using Equation 4:

Y ¼ 40:67þ 5:32X1 þ 23:75X2 þ 3:44X3

þ1:29X1X2 � 0:84X1X3

þ1:06X2X3 � 0:83X12 � 0:069X2

2 þ 0:95X32

ð4ÞA statistical approach using a CCD was used for effi-

ciency degradation of dye and for determining the inter-action between these factors. For the response surfacemethodology involving CCD, a total of 20 experimentswas conducted for three factors at five levels with threereplicates at center point. Table 1 provides a list of inde-pendent variables and coded factor levels. The numberof experiments required (N) is given by the expression:2k (23 = 8; star points) + 2 k (2 × 3 = 6; axial points) + 6

(center points; 6 replications).An RSM is appropriate when the optimal region for

running the process has been identified. The design usedfor the optimization and observed responses for 20experiments are given in Table 2 for WAO [40]. InEquation 4, Y is the TOC removal percent of dye; andx1, x2, and x3 are the corresponding coded variables ofoxygen pressure, temperature, and time, respectively.

Analysis of varianceAnalysis of variance (ANOVA) values for the quadraticregression model obtained from CCD employed in theoptimization of dye degradation are listed in Table 3. Onthe basis of the experimental values, statistical testingwas carried out using Fisher's test for ANOVA. The stat-istical significance of the second-order equation revealedthat the regression is statistically significant (P < 0.0001);however, the lack of fit is not statistically significant at99% confidence level. Table 3 depicts the significance ofthe regression coefficients and ANOVA for the regres-sion model, respectively. The results indicate that theresponse equation proved to be suitable for the CCDexperiment [41,42].The model's F value of 595.49 in these tables implies

that the model is significant for the degradation of thedye. If the model has a very high degree of adequacy for

Table 2 Central composite design experiments and experimental results

Experiment number Experimental design Experimental plan Observed% Y Predicted% Y

O2 (MPa) T (°C) t (min) X1 X2 X3

1 −1 −1 −1 3.0 100 30 7.18 7.82

2 +1 −1 −1 5.0 100 30 16.30 17.57

3 −1 +1 −1 3.0 250 30 50.05 50.63

4 +1 +1 −1 5.0 250 30 65.60 65.52

5 −1 −1 +1 3.0 100 90 12.80 14.25

6 +1 −1 +1 5.0 100 90 19.40 20.64

7 −1 +1 +1 3.0 250 90 61.20 61.31

8 +1 +1 +1 5.0 250 90 72.10 72.84

9 −1.682 0 0 2.32 175 60 30.10 29.38

10 +1.682 0 0 5.68 175 60 48.50 47.28

11 0 −1.682 0 4.0 48.87 60 2.60 0.53

12 0 +1.682 0 4.0 301.1 60 80.30 80.43

13 0 0 −1.682 4.0 175 9.55 32.70 32.20

14 0 0 +1.682 4.0 175 110.4 45.20 43.76

15 0 0 0 4.0 175 60 40.50 40.67

16 0 0 0 4.0 175 60 40.70 40.67

17 0 0 0 4.0 175 60 40.00 40.67

18 0 0 0 4.0 175 60 40.80 40.67

19 0 0 0 4.0 175 60 41.00 40.67

20 0 0 0 4.0 175 60 40.70 40.67


predicting the experimental results, the computed F valueshould be greater than the tabulated F value at a level ofsignificance α. Thus, the calculated F value (Fmodel =595.49) was compared with the tabulated F value (F0.05,df, (n−df + 1)) at a significance level of 0.05, when the df

Table 3 ANOVA regression model for AR 274 degradationusing WAO process

Source Degrees offreedom

Sum ofsquares

Meansquare

F value P value

Model 9 8,302.34 922.48 595.49 <0.0001

X1 1 386.63 386.63 249.58 <0.0001

X2 1 7,705.46 7,705.46 4,974.12 <0.0001

X3 1 161.35 161.35 104.16 <0.0001

X12 1 9.90 9.90 6.39 0.0153

X22 1 0.068 0.068 0.044 0.1523

X32 1 13.08 13.08 8.44 0.0253

X1X2 1 13.21 13.21 8.53 0.9725

X1X3 1 5.64 5.64 3.64 0.6877

X2X3 1 8.99 8.99 5.80 0.7608

Residual 10 15.49 1.55

Lack of fit 5 14.90 2.98 25.33 0.0015

Pure error 5 0.59 0.12

for the model was 9 and n=20. It can be observed thatthe tabular F value (F0.05,9,10 = 3.02) is clearly less than thecalculated F value of 595.49. Adequate precision measuresthe signal to noise ratio, and a ratio value greater than 4 isdesirable. Therefore, in the quadratic model degradationof dye, an adequate precision of 90.78 indicates anadequate signal for WAO. P values less than 0.05 indicatethat the model terms are significant, whereas valuesgreater than 0.1 are not significant. The fit of the modelswere controlled by the coefficient of determination R2.Based on the ANOVA results, the models report high R2

value of 99.81% for dye degradation using WAO. Also, anacceptable agreement with the adjusted determinationcoefficient is necessary. In this study, the Adj-R2 value of99.65% was found. The values of R2 and Adj-R2 are closeto 1.0, which is very high and advocates a high correlationbetween the observed values and the predicted values.This indicates that the regression model provides an excel-lent explanation of the relationship between the independ-ent variables and the response. The diagnostic plots givenin Figures 1, 2, and 3 were used for estimating theadequacy of the regression model. The calculated chi-square value of the model (χ2 = 0.25) was found to be lessthan the tabulated value (χ0.05

2 = 30.14), which revealed thatthere is no significant difference between the observeddata and the model response [5,9,32-37]. The actual and

Figure 1 The actual and predicted TOC removal percentage. Figure 3 The predicted TOC removal (%) of AR 274 andstudentized residual plot.


the predicted TOC removal percentage values are given inFigure 1. It can be observed that there are tendencies inthe linear regression fit, and the model adequately explainsthe experimental range studied. The actual TOC removalpercentage value is the measured result for a specific run,and the predicted value is evaluated from the independentvariables in the CCD model [5,9]. The normal percentageprobability and studentized residual plot are shown inFigure 2. The data points indicate that neither responsetransformation was required nor there was any apparentproblem with normality. Figure 3 depicts the studentizedresidual and predicted TOC removal percentage of dyedegradation.

Figure 2 The studentized and normal percentage probabilityplot of degradation of AR 274.

Interactive effect of processes of independent variablesTo understand the impact of each variable, three dimen-sional (3D) plots were made for the estimated responses,which were the bases of the model polynomial functionfor analysis to investigate the interactive effect of thetwo factors on the TOC removal percentage within theexperimental ranges given in Figures 4, 5, and 6. Theinferences so attained are discussed below [43].

Interactive effect of oxygen pressure and temperatureTo investigate the integrated effect of temperature andoxygen pressure, RSM was used and the result was givenin the form of 3D plots. As indicated in Figure 4, thetemperature and pressure conditions have considerableinfluence on the extent of degradation achieved. Figure 4

Figure 4 3D surface plot of TOC removal versus oxygenpressure (MPa) and experiment temperature (°C). Fixed reactiontime t= 60 min.

Figure 5 3D surface plot of TOC removal versus experimenttemperature (°C) and experiment time (in min). Fixed oxygenpressure (4.0 MPa).


indicates that the increasing pressure of oxygen partiallyspeeded up the dye degradation, and the dye degradationrate increased until the oxygen was exhausted in thereaction medium. The oxygen pressure is part of thedriving force for mass transfer; therefore, the degradationrate increases with the increasing oxygen amount. However,with the oxygen amount below the stoichiometric amount,it contributes little to the concentration of the dissolvedoxygen [4]. The degradation rate is found to be affected bythis situation. The TOC removal percentage of dye is foundto increase with rising temperature for degradationprocesses. At the lowest temperature of 100°C, theremoval of TOC is rather insignificant. At temperaturesabove 150°C, TOC removal after 30 min is almostdependent on temperature. For example, as shown inFigure 4 (at 3.0 MPa oxygen pressure, temperature 100°C),the percentage of TOC removal was 7.18%, whichincreased to 50.0% at 3.0 MPa and 250°C temperaturewhen using the WAO process. The increased percentage

Figure 6 3D plot of TOC removal versus oxygen pressure (MPa)and experiment time (min). Fixed temperature T= 175°C.

TOC removals were also monitored for oxygen pressureranging from 3.0 to 5.0 MPa for the WAO process. Withoxygen pressure reaching up to 5.0 MPa from 3.0 MPa at250°C, the TOC removal percentage was found to increaseuntil to 65.6% from 50.0 using WAO process. Thedegradation of dye would increase if the oxygen pressureis kept high; however, after the stoichiometric quantity isachieved, the oxygen quantity is not an effective factor fordye degradation [4,16]. As can be seen in Figure 4, TOCremoval percentage increased remarkably with increasingtemperature at all applied oxidant concentrations, andtemperature has a significant impact on the dye degrad-ation. Thus, with the increase of temperature, an improve-ment in dye degradation performance was determined [4].At wet air oxidation conditions, the free radical easily

occurs at high temperature and oxygen-rich conditions.The free-radical generation consists of O2 attacking theC-H bond of the organic molecule. The followingreactions could occur by the addition of molecular oxygen[4,44-49].

RHþO2 ! R� þHO2� initiationð Þ ð5ÞR� þO2 ! RO2� propagationð Þ ð6ÞRO2� þ RH ! ROOHþ R� propagationð Þ ð7ÞROOH ! RO� þOH� autocatalytic decompositionð Þ ð8ÞRO� þ RH ! ROH þ R� ðpropagationÞ ð9ÞOH� þ RH ! R� þH2O ðpropagationÞ ð10Þ2ROO� ! ROORþO2 terminationð Þ ð11Þ

These reactions generate organic radicals and otherfree radicals, which in turn initiate the chain reactions ofdye degradation with the help of dissolved oxygen. Severaloperating parameters influence the aforementionedformation of free radicals, and thereby the degradationrate of pollutants, among which temperature plays themost important role in the case of sufficient oxygensupply [7,50,51].

Interactive effect of temperature and timeFigure 5 presents 3D plots indicating the effect oftemperature and time on percentage TOC removalunder the predefined conditions given by Design Expert.As indicated in Figure 5, the maximum 80.3% TOCremoval occurs at 60 min of experimental time and at300°C ± 2°C in WAO conditions. The degradation rateslightly increases with the increase in the experimentaltime at moderate temperature; however, when thetemperature increases, the effect of time is almost insig-nificant, and temperature becomes the main factorowing to the interaction between the oxidant andtemperature. Thus, the degradation rate is almost

Figure 7 Major degradation pathway proposed for WAO of Acid Red 274.


primarily controlled by the temperature, the details ofwhich are described above. Therefore, it appears thattime might be less important for the degradation rate ofdye. The same effect was observed in the study reportedpreviously [9].

Interactive effect of oxygen pressure and timeAs seen in Figure 6, the response surface and 3D plotswere enhanced as a function of oxidant pressure and

Figure 8 GC-MS analysis of the organic intermediates of AR274 after 5-min WAO treatment. Reaction conditions: T= 200°C;[AR 274]o = 1,000 mg/L.

experimental time. In addition, the TOC removal percent-age rate increased with increased oxygen pressure and timeat constant temperature. With the increasing experimentaltime, the interaction probability of formed radicals withdye, according to Equations 5 to 11, increased. The dyedegradation by WAO was regarded as a free radicalmechanism. With increasing time, the free radicals such asR� and ROO� would be increased, which promotes thedegradation rate [7]. However, regardless of the experimen-tal time, this interaction would be limited to the amount ofoxygen. As free radical occurs easily at oxygen-rich condi-tions, depending on the time decrease, the amount ofoxygen in the radicals will reduce and the degradation ratewill gradually slow down.

Figure 9 Molecular structure of reactive Acid Red 274 dye.

Figure 10 Scheme of the wet air oxidation system.


Identification of degradation productsThe degradation products obtained in the present studywere similar to that obtained from the previous studywherein the degradation of AR 274 was realized usingH2O2 in subcritical water [9]. This result is normal ascommon reagents were occurring in both studies. In thisprocess, the attack of the azo bond would be the initialstep of dye degradation, which pioneers the fast removalof color [7]. Figure 7 depicts the GC-MS analysis ofshort-time oxidized solutions in WAO condition revealingthe formation of benzamide (A1), benzoic acid (A2),hydroquinone (A3), benzoquinone (A4), 1-naphthol (B1),naphthalene-1,6-diol (B2), naphthalene-1,2,4,6-tetraol (B3),phthalic anhydride (B4), 2,6-dihydroxynaphthalene-1,4-dione (B5), phthalic acid (B6), o-cyclohexylphenol (C1), andcatechol (C2). In the process, C-N and C-O bonds werecleavaged owing to temperature effects and attacks ofhydroxyl radicals. The main intermediates identified duringWAO treatment of AR 274 by GC-MS was shown on GCchromatogram in Figure 8. For a longer duration of oxida-tion, all aromatic compounds would be further transformedinto small molecules.

ExperimentalMaterialsThe azo dye C.I. Acid Red 274, commercial name SupranolRed 3BW (CAS no: 61931-18-8), was obtained from DystarColours Distribution GmbH (Germany) and was usedwithout further purification. The solution of AR 274 wasprepared in 1,000 mg/L initial concentration with distilled

water for all treatments. The molecular structure of AR274 (C35H28N3O9Na2S2, Mw=744 g/mol) was shown inFigure 9. Oxygen was used as the oxidant in the WAOprocess, which was supplied by Linde Gas (Linde GroupTurkey, Adana, Turkey) with 99.9% purity.

Wet air oxidation processThe experimental process is described in detail in Kayanet al. [44]. A brief overview of the process is as follows:Wet air oxidation process was carried out at temperatureranging from 100°C to 250°C with oxygen pressure of 3.0to 5.0 MPa in a 150-mL stainless steel reactor with mag-netic stirrer and heater as shown in Figure 10. The glassvessel was placed in the reactor and filled with 1,000 mg/Lof AR 274 solution, and subsequently the reactor wasplaced on a magnetic stirrer and heater. Oxygen wasdirectly supplied through a tube into the liquid phase.Ordinarily, the reactor was filled with 150 mL of reactionsolution. The reaction solution was heated to the targetedtemperature, and all the valves of the reactor were tightlyclosed during preheating. Upon reaching the targetedtemperature, the amount of pure oxygen gas fed in thereactor in the liquid phase and its partial pressure weremaintained with a gas relief valve. Samples were taken outperiodically and analyzed for AR 274 degradation using aUV–vis spectrophotometer. The reaction temperature wasmeasured using a thermocouple and controlled using aregulator. After the sample collection treatment, thereactor was cooled to room temperature using a waterbath and sampled for total organic carbon (TOC) analysis


of the final effluent in 90-min reaction time. The quantityof dissolved oxygen in water was calculated using an oxy-gen solubility model for the required degradation of AR274 in distilled water [52].

ConclusionsThe degradation of the azo dye was obtained by wetair oxidation system. Wet air oxidation seems a veryattractive technique for the treatment of waste streamsthat are toxic and dilute. When molecular oxygen wasused as an oxidant in WAO system, effective degrad-ation or mineralization efficiency was obtained at hightemperature. This clearly indicated that temperaturehad an effect on dye degradation. An increase in thepressure of oxygen partially speeded up the dye deg-radation and increased the dye degradation rate untilthe oxygen was exhausted in the reaction medium.This result indicated that temperature was the mainfactor, and the interactions of other parameters werediscussed in detail. The degradation process was opti-mized using RSM based on CCD. The optimum valuesof oxygen pressure, temperature, and reaction timewere 3.3 MPa, 255°C, and 111 min, respectively, where67.02% TOC removal could be obtained from theproposed model. The ANOVA showed high coefficient ofthe determination values (R2 = 0.9981 and Adj-R2= 0.9965).In this way, the degradation mechanism of WAO of AcidRed 274 dye was discussed, and the probable degradationpathway was deduced.

AbbreviationsANOVA: analysis of variance; AR 274: Acid Red 274; AOPs: advancedoxidation processes; CCD: central composite design; CWAO: catalytic wet airoxidation; GC-MS: gas chromatography–mass spectrometry; RSM: responsesurface methodology; WAO: wet air oxidation; TOC: total organic carbon.

Competing interestsThe authors declare that they have no competing interests.

Authors' contributionsBK conceived of the study, coordinated in the research, and participated inthe experimental design and optimization. MD participated in thedegradation experiments, the preparation of graphs and tables, and in thestatistical analysis of the data. All authors read and approved the finalmanuscript.

AcknowledgmentsWe wish to thank Dr. Belgin Gözmen for GC-MS analysis and other supports.We also would like to thank Prof. Dr. A. Murat Gizir for the ever positivesupport and for the continuous encouragement.

Author details1Department of Chemistry, Arts and Sciences Faculty, Mersin University,Mersin 33342, Turkey. 2Department of Chemistry, Arts and Sciences Faculty,Aksaray University, Aksaray 68100, Turkey.

Received: 28 May 2012 Accepted: 31 August 2012Published: 2 October 2012

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doi:10.1186/2228-5547-3-24Cite this article as: Demirel and Kayan: Application of response surfacemethodology and central composite design for the optimization oftextile dye degradation by wet air oxidation. International Journal ofIndustrial Chemistry 2012 3:24.

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