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利用菌株Gb对合成废水中甲苯胺红生物降解进行统计建模与优化

Statistical modeling and optimization of Toluidine Red biodegradation in a synthetic wastewater using strain Gb.

作者信息

Amini Baharnaz, Otadi Maryam, Partovinia Ali

机构信息

1Department of Chemical Engineering, Faculty of Engineering, Central Tehran Branch, Islamic Azad University, Tehran, Iran.

2Faculty of New Technologies Engineering, Zirab Campus, Shahid Beheshti University, Tehran, Iran.

出版信息

J Environ Health Sci Eng. 2019 Apr 8;17(1):319-330. doi: 10.1007/s40201-019-00350-5. eCollection 2019 Jun.

DOI:10.1007/s40201-019-00350-5
PMID:31297214
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6582210/
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 strain Gb bacterium. In order to model, optimize, and investigate the individual factors affecting the biodegradation capacity of this dye by 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 D 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.

摘要

背景

合成染料废水是一类环境污染物,广泛应用于纺织、印染等行业。由于这些污染物的化学稳定性,含合成染料废水的传统处理方法被认为成本高且耗时。因此,近年来,利用有能力的微生物进行生物降解被视为去除这些污染物的有效方法。因此,本研究旨在考察嗜盐菌株Gb细菌对油溶性偶氮染料甲苯胺红(C.I. 编号12120)的脱色情况,该染料作为合成染料废水中唯一的碳源和能源。为了模拟、优化和研究影响该菌株对这种染料生物降解能力的各个因素,首次应用了响应面法(RSM)和中心复合设计(CCD)。

方法

在本研究中,使用Design Expert软件版本10进行统计建模和优化,并采用RSM方法进行30次试验来考察降解能力。为此,研究了4个变量在第2天、第4天和第10天不同时间的影响,这些变量包括染料浓度(10 - 30 ppm)、盐浓度(2 - 10%)、pH值(5.5 - 9.5)和温度(20 - 40)。然后,基于统计建模,针对所选的四个变量给出了染料去除量的二阶函数。

结果

根据所得结果和方差分析,发现所有主要变量对生物降解能力均有显著影响。根据结果,不同天数间的最高生物降解量为81%,在第4天观察到,而此时最大生物降解的最佳条件已确定为pH值6.5、温度35℃,盐浓度和染料浓度分别相当于4%和25 ppm。所选实验中实验结果与预测结果之间的相对误差为11%,这证实了所获得的用于计算脱色能力的相关性的可靠性。

结论

根据结果,所提出的模型可以很好地预测不同条件对甲苯胺红生物降解的影响,本研究中的优化结果与先前用OFAT方法对IP8和D菌株进行的研究一致。此外,所提出的模型可能有助于更好地理解主要效应以及变量之间的相互作用对染料去除的影响。总体而言,结果表明用于染料去除的嗜盐细菌在高盐环境中可能更有效。