# Optimization of Acid Black 172 decolorization by electrocoagulation using response surface methodology

- Mahsa Taheri
^{1}, - Mohammad Reza Alavi Moghaddam
^{2}Email author and - Mokhtar Arami
^{3}

**9**:23

https://doi.org/10.1186/1735-2746-9-23

© Taheri et al; licensee BioMed Central Ltd. 2012

**Received: **5 December 2012

**Accepted: **5 December 2012

**Published: **11 December 2012

## Abstract

This paper utilizes a statistical approach, the response surface optimization methodology, to determine the optimum conditions for the Acid Black 172 dye removal efficiency from aqueous solution by electrocoagulation. The experimental parameters investigated were initial pH: 4–10; initial dye concentration: 0–600 mg/L; applied current: 0.5-3.5 A and reaction time: 3–15 min. These parameters were changed at five levels according to the central composite design to evaluate their effects on decolorization through analysis of variance. High R^{2} value of 94.48% shows a high correlation between the experimental and predicted values and expresses that the second-order regression model is acceptable for Acid Black 172 dye removal efficiency. It was also found that some interactions and squares influenced the electrocoagulation performance as well as the selected parameters. Optimum dye removal efficiency of 90.4% was observed experimentally at initial pH of 7, initial dye concentration of 300 mg/L, applied current of 2 A and reaction time of 9.16 min, which is close to model predicted (90%) result.

## Keywords

## Introduction

Effluents from industries, such as textile, leather, plastics, paper, food and cosmetics contain many coloring substances, which can be toxic, carcinogenic and mutagenic [1–3]. In addition, some synthetic dyes cause allergy and skin irritation [4]. The dye-containing wastewater, are not only aesthetic pollutants, but also may prevent light penetration in water, and thereby damage water sources and ecosystem [5–7].

Electrocoagulation (EC) treatment process has been widely used due to its simplicity and efficiency [8–10]. In this process, generation of coagulants (iron or aluminum ions) by electrodissolution of the sacrificial anode(s) leads to formation of particles that entrap the pollutants [11–13]. The main reactions for dye removal using aluminum electrodes are as follows:

Response surface methodology (RSM) is a collection of mathematical and statistical techniques for modeling and analysis of problems in which a response of interest is influenced by set of independent variables [14, 15]. Main advantages of optimization by RSM to conventional method are reduction of experimental trials in providing sufficient information for statistically valid results and evaluation of the relative significance of parameters and their interactions [16, 17].

In recent years, the area of optimization dye removal efficiency by electrocoagulation has received enormous attentions [6, 18–20]. However, according to our knowledge, application of RSM design in decolorization by EC rarely presented in scientific papers [21–24]. On the other hand, up to now there is no research available on treatment of diazo and metal-complex Acid Black 172 dye in aqueous media except by biological procedures.

The aim of the present study was to optimize Acid Black 172 dye removal from aqueous solution by electrocoagulation process using RSM. For this purpose, central composite design (CCD) was used to develop a mathematical correlation between Acid Black 172 dye removal efficiency and four selected independent parameters including initial pH, initial dye concentration, applied current and reaction time.

## Materials and methods

^{2}were used; the thicknesses of aluminum plates were 3 mm and the distances between electrodes was kept constant at 3 cm. Electrodes were connected to a DC power supply (Micro, PW4053R, 0-5A, 0–40 V) in a monopolar mode. For preparing a mixed solution in EC cell, a magnetic stirrer (Velp, Scientifica, Italy) was used.

For preparation of stock solutions of the synthetic wastewater, Acid Black 172 dye as dissolved in deionized water and then diluted to obtain the desired concentrations. Sodium chloride (NaCl) was used to increase the conductivity of the solutions containing Acid Black 172 as the supporting electrolyte. The solution initial pH was adjusted before experiments by NaOH and H_{2}SO_{4} and controlled using pH meter (340i, WTW, Germany). All the experiments were performed at room temperature. A total of 30 samples were taken from the cell at the end of experiments and centrifuged by a centrifuge device (Hettich, EBA 21, USA) at 5000 rpm for 5 min and then analyzed. Dye concentration was measured at a wavelength corresponding to the maximum absorbance (λ_{max}) by UV-visible spectrophotometer (HACH, DR4000, USA).

_{i}according to Equation 4:

_{0}is value of the X

_{i}(selected parameters) at the center point and ΔX presents the step change. Acid Black 172 removal efficiency was taken as the response of the experiments according Equation 5:

_{i}is the percentage of dye removal efficiency

**Experimental range and levels of independent parameters**

Parameters | Levels | |||||
---|---|---|---|---|---|---|

- α | −1 | 0 | 1 | α | ||

Initial pH | X | 4 | 5.5 | 7 | 8.5 | 10 |

Initial concentration (mg/L) | X | 0 | 150 | 300 | 450 | 600 |

Applied current (A) | X | 0.5 | 1.25 | 2 | 2.75 | 3.5 |

Reaction time (min) | X | 3 | 6 | 9 | 12 | 15 |

b_{0=} the constant coefficient

b_{i} = the regression coefficients for linear effects

b_{ii} = the quadratic coefficients

b_{ij} = the interaction coefficients

and x_{i}, x_{j} are the coded values of the parameters.

The statistical software “Minitab”, version 15.1.1.0 was used for the regression and graphical analyses of the experimental data obtained. The accuracy of the fitted model was justified through analysis of variance (ANOVA) and the coefficient of R^{2}.

## Results

### Development of regression model equation and validation of the model

**RSM design and experimental and predicted values**

Run | Initial pH (x | Initial dye concentration (x | Applied current (x | Reaction time (x | Dye removal (%) | |
---|---|---|---|---|---|---|

Experimental | Predicted | |||||

1 | −2 | 0 | 0 | 0 | 96.64 | 94.74 |

2 | 0 | 0 | −2 | 0 | 58.89 | 65.47 |

3 | −1 | −1 | −1 | −1 | 93.01 | 89.57 |

4 | 0 | 0 | 0 | 0 | 89.33 | 89.56 |

5 | 0 | 0 | 0 | 0 | 89.91 | 89.56 |

6 | 0 | 0 | 2 | 0 | 91.33 | 89.33 |

7 | 0 | 2 | 0 | 0 | 70.19 | 69.28 |

8 | 1 | 1 | −1 | −1 | 43.7 | 43.11 |

9 | 1 | −1 | 1 | −1 | 87.16 | 87.05 |

10 | −1 | −1 | −1 | 1 | 96.42 | 97.3 |

11 | 0 | 0 | 0 | −2 | 50.43 | 58.09 |

12 | 0 | 0 | 0 | 0 | 89.99 | 89.56 |

13 | −1 | −1 | 1 | −1 | 95.31 | 94.67 |

14 | 1 | −1 | −1 | 1 | 89.78 | 89.22 |

15 | −1 | −1 | 1 | 1 | 97.26 | 96.86 |

16 | 1 | 1 | −1 | 1 | 76.46 | 73.5 |

17 | −1 | 1 | −1 | 1 | 81.6 | 80.73 |

18 | 0 | 0 | 0 | 0 | 90.44 | 89.56 |

19 | 0 | 0 | 0 | 0 | 89.85 | 89.56 |

20 | 1 | −1 | −1 | −1 | 89.36 | 80.4 |

21 | 0 | 0 | 0 | 2 | 93.74 | 90.67 |

22 | 1 | 1 | 1 | −1 | 71.89 | 67.41 |

23 | 2 | 0 | 0 | 0 | 73.4 | 79.89 |

24 | 1 | 1 | 1 | 1 | 89.79 | 92.25 |

25 | 0 | 0 | 0 | 0 | 88.65 | 89.56 |

26 | −1 | 1 | 1 | 1 | 92.57 | 97.93 |

27 | 1 | −1 | 1 | 1 | 92.67 | 90.32 |

28 | 0 | 0 | 0 | 0 | 88.78 | 89.56 |

29 | −1 | 1 | 1 | −1 | 74.61 | 74.18 |

30 | −1 | 1 | −1 | −1 | 52.67 | 51.42 |

31 | 0 | −2 | 0 | 0 | 100 | 105.5 |

_{1}

^{2}, x

_{2}

^{2}, x

_{1}x

_{2}, x

_{1}x

_{3}, x

_{1}x

_{4}and x

_{3}x

_{4}(P ≥ 0.05) were significant to the response. The analysis of variance (ANOVA) for the Acid Black 172 dye removal efficiency is given in Table 3, According to this table, the P value of 0 (P ≤ 0.05) justifies the reliability of the fitted polynomial model through ANOVA with 95% confidence level. Furthermore, parity plot for the experimental and predicted value of Acid Black 172 removal efficiency (%) is demonstrated in Figure 3. High R

^{2}value of 94.48% validates the statistical significance of the model for the selected dye removal.

**Analysis of variance** (**ANOVA**) **for Acid Black 172 removal efficiency** (%)

Source | DF | Seq SS | Adj SS | Adj MS | F | P |
---|---|---|---|---|---|---|

Regression | 14 | 6169.47 | 6169.47 | 440.68 | 19.55 | 0 |

Linear | 4 | 4743.97 | 4743.97 | 1185.99 | 52.61 | 0 |

Square | 4 | 613.84 | 613.84 | 153.46 | 6.81 | 0.002 |

Interaction | 6 | 811.65 | 811.65 | 135.28 | 6 | 0.002 |

Residual Error | 16 | 360.7 | 360.7 | 22.54 | ||

Lack-of-Fit | 10 | 358.04 | 358.04 | 35.8 | 80.91 | 0 |

Pure Error | 6 | 2.66 | 2.66 | 0.44 | ||

Total | 30 | 6530.17 |

### Effects of operating parameters

### Process optimization

**Optimum values for Acid Black 172 removal from aqueous solution**

No | Initial pH | Initial dye concentration (mg/L) | Applied current (A) | Reaction time (min) | Dye removal efficiency (%) | |
---|---|---|---|---|---|---|

Predicted | Experimental | |||||

1 | 7 | 300 | 2 | 9.16 | 90 | 90.4 |

2 | 4 | 150 | 1.76 | 4.37 | 90 | 91.96 |

3 | 4 | 300 | 2.78 | 6.72 | 90 | 94.26 |

4 | 4 | 450 | 3.3 | 8.41 | 90 | 95.2 |

5 | 4 | 600 | 3.5 | 9.1 | 90 | 94.57 |

### Dye removal kinetic

_{t}, C

_{o}, and k are dye concentrations at any time t, initial dye concentration, and kinetic constant, respectively. Plots of (1/C

_{t}-1/C

_{0}) with time are shown in Figure 7(b) for various initial dye concentrations (from 50 to 600 mg/L), at initial pH of 7 and applied current of 2 A. As demonstrated in this figure, reaction rate follows second order kinetic and its values increases from 0.001/min to 0.041/min when initial dye concentration decreased from 600 to 50 mg/L in the solutions, respectively.

## Discussion

According to the obtained results, the most and the least important independent parameters were initial dye concentration and initial pH, respectively. Similar to our results, Aleboyeh *et al*. [22], Alinsafi *et al*. [21] and Arslan-Alaton *et al*. [23] study groups reported that initial pH was the least important parameter in comparison with the other variables. In addition, Durango-Usuga *et al*. [25] and Srivastava *et al*. [26] expressed that initial dye concentration is one of the most important factors in decolorization optimization respectively by Factorial and Taguchi designs, which is similar to our results.

*et al*. [21] and Yildiz [27] achieved over 90% dyes removal efficiency at much higher reaction time and lower current density, respectively in comparison with the present study.

**Comparison of dye removal efficiency in treatment by electrocoagulation under optimal conditions through design of experiment methods**

Dye | Design | Independent parameters | Dye removal efficiency(%) | Reference | |||
---|---|---|---|---|---|---|---|

Current density (A/m | Reaction time (min) | Initial pH | Initial dye concentration (mg/L) | ||||

Acid Black 172 | RSM | 166.67 | 9.16 | 7 | 300 | 90.4 | Present study |

Acid Red 14 | RSM | 100 | 4 | 7 | 50 | 91.3 | Aleboyeh |

Reactive textile dyes | RSM | 120 | 105 | 10 | 50 | 92 | Alinsafi |

Bomaplex Red CR-L | Taguchi | 5 | 30 | 3 | 100 | 99.1 | Yildiz [27] |

Crystal Violet | Factorial | 28 | 5 | Natural | 200 | 85 | Durango-Usuga |

Many Researchers have examined the impact of different parameters including initial pH, initial dye concentration, current density and reaction time on the dye removal efficiency in complex electrocoagulation process. Some study groups showed that the increase in current density and reaction time and the decrease in initial dye concentration improved the decolorization efficiency [6, 19, 22, 28], which is similar to our results. However, optimum initial pH reported for different types of anionic dyes removal in electrocoagulation process was different. For example, optimum initial pH was reported 7, 5–9 and 4–6.5 by Aleboyeh *et al*. [22], Aoudj *et al*. [6] and Basiri Parsa *et al*. [20] study groups, respectively. Lower optimum initial pHs were also obtained by other researchers [26, 27, 29].

According to our knowledge, up to now there is no research available on treatment of Acid Black 172 in aqueous media by electrocoagulation procedure. Therefore, the observed data from our results have been compared with the other treatment methods of Acid Black 172. For instance, Du research group obtained 86% Acid Black 172 removal by Pseudomonas sp. DY1 at their optimum conditions through response surface methodology [30], which is close to our results.

## Conclusions

According to the results of this investigation, RSM is a powerful statistical optimization tool for Acid Black 172 removal using electrocoagulation process. The RSM results revealed that four selected parameters as well as some of their squares and interactions influenced the electrocoagulation performance. High R^{2} value of 94.48% through ANOVA, verified that the accuracy of the Minitab proposed polynomial model is acceptable. The optimum Acid Black 172 removal efficiency were found at initial pH of 7, initial dye concentration of 300 mg/l, applied current of 2 A and reaction time of 9.16 min. An experiment was performed in optimum conditions which confirmed that the model and experimental results are in close agreement (90.4% compared to 90% for the model).

## Declarations

### Acknowledgements

The authors are grateful to the Amirkabir University of Technology (AUT) research fund for the financial support. In addition, the authors wish to express thanks to Mr. Masoud Asadi Habib and Mr. Mohsen Behbahani (former MSc students of Amirkabir University of Technology), and Ms. Lida Ezzedinloo for their assistance during experiments.

## Authors’ Affiliations

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