Baharnaz Amini1, Maryam Otadi1, Ali Partovinia2. 1. 1Department of Chemical Engineering, Faculty of Engineering, Central Tehran Branch, Islamic Azad University, Tehran, Iran. 2. 2Faculty of New Technologies Engineering, Zirab Campus, Shahid Beheshti University, Tehran, Iran.
Abstract
BACKGROUND: Synthetic dye wastewater is a group of environmental pollutants that are widely used in some industries like textile, printing, dyeing and etc. Traditional treatment methods for wastewaters containing synthetic dyes are considered as expensive and time consuming approaches due to the chemical stability of these pollutants. Therefore, in recent years, biodegradation by means of capable microorganisms has been considered as an effective way to remove these pollutants. Hence, the present study has aimed at examining the decolorization of Toluidine Red (C.I. no.12120), which is an oil soluble azo dye, as the sole sources of carbon and energy from a synthetic dye wastewater by the halophilic Halomonas strain Gb bacterium. In order to model, optimize, and investigate the individual factors affecting the biodegradation capacity of this dye by Halomonas strain Gb, for the first time response surface methodology (RSM) and central composite design (CCD) were applied. METHODS: In this research, statistical modeling and optimization were performed by Design Expert software version 10 and the degradation capacity was considered by carrying out 30 tests using RSM method. For this purpose, the effect of 4 variables included dye concentration (10-30 ppm), salt concentration (2-10%), pH (5.5-9.5), and temperature (20-40) at different times of 2nd, 4th, and 10th days have been studied. Then, a second-order function was presented for the amount of dye removal in terms of the four selected variables, based on statistical modeling. RESULTS: According to the obtained results and analysis of variance, all main variables were found to be significantly effective on the biodegradation capacity. With regard to the results, the highest amount of biodegradation between different days was 81% and observed at the 4th day, while the optimum conditions for the maximum biodegradation of this time has been determined at pH of 6.5, temperature of 35 °C, and salt and dye concentrations were equivalent to 4% and 25 ppm, respectively. There is 11% relative error between the experimental and predicted results in the selected experiments, which confirms the reliability of the obtained correlation for calculating the decolorization capacity. CONCLUSION: In accordance with the results, the proposed model can provide a good prediction of the effect of different conditions on the biodegradation of Toluidine Red, and the optimization results in this study have been consistent with the previous studies conducted with the IP8 and D2 strains by the OFAT method. Moreover, the proposed model may help in better understanding the impact of main effects and interaction between variables on the dye removal. Overall, the results indicated that the halophilic bacterium used in dye removal can be more effective in high-salinity environments.
BACKGROUND: Synthetic dye wastewater is a group of environmental pollutants that are widely used in some industries like textile, printing, dyeing and etc. Traditional treatment methods for wastewaters containing synthetic dyes are considered as expensive and time consuming approaches due to the chemical stability of these pollutants. Therefore, in recent years, biodegradation by means of capable microorganisms has been considered as an effective way to remove these pollutants. Hence, the present study has aimed at examining the decolorization of Toluidine Red (C.I. no.12120), which is an oil soluble azo dye, as the sole sources of carbon and energy from a synthetic dye wastewater by the halophilic Halomonas strain Gb bacterium. In order to model, optimize, and investigate the individual factors affecting the biodegradation capacity of this dye by Halomonas strain Gb, for the first time response surface methodology (RSM) and central composite design (CCD) were applied. METHODS: In this research, statistical modeling and optimization were performed by Design Expert software version 10 and the degradation capacity was considered by carrying out 30 tests using RSM method. For this purpose, the effect of 4 variables included dye concentration (10-30 ppm), salt concentration (2-10%), pH (5.5-9.5), and temperature (20-40) at different times of 2nd, 4th, and 10th days have been studied. Then, a second-order function was presented for the amount of dye removal in terms of the four selected variables, based on statistical modeling. RESULTS: According to the obtained results and analysis of variance, all main variables were found to be significantly effective on the biodegradation capacity. With regard to the results, the highest amount of biodegradation between different days was 81% and observed at the 4th day, while the optimum conditions for the maximum biodegradation of this time has been determined at pH of 6.5, temperature of 35 °C, and salt and dye concentrations were equivalent to 4% and 25 ppm, respectively. There is 11% relative error between the experimental and predicted results in the selected experiments, which confirms the reliability of the obtained correlation for calculating the decolorization capacity. CONCLUSION: In accordance with the results, the proposed model can provide a good prediction of the effect of different conditions on the biodegradation of Toluidine Red, and the optimization results in this study have been consistent with the previous studies conducted with the IP8 and D2 strains by the OFAT method. Moreover, the proposed model may help in better understanding the impact of main effects and interaction between variables on the dye removal. Overall, the results indicated that the halophilic bacterium used in dye removal can be more effective in high-salinity environments.
Entities:
Keywords:
Biodegradation; Dye wastewater; Halophilic bacteria; Statistical modeling and optimization; Toluidine red
Authors: Yogesh M Kolekar; Shrikant P Pawar; Kachru R Gawai; Pradeep D Lokhande; Yogesh S Shouche; Kisan M Kodam Journal: Bioresour Technol Date: 2008-06-17 Impact factor: 9.642