响应面法优化复合微生物吸附剂对低浓度Cr3+的吸附

Optimizing the Removal of Cr(Ⅲ) from Low Concentration Solution Using Composite Microbial Biosorbents by Response Surface Methodological Approach

  • 摘要: 根据已有4种微生物吸附剂的吸附基团存在的差异特征,将其复配成复合吸附剂,借助统计学方法研究其对低ρ(Cr3+)废水的吸附性能.在单因素试验基础上,利用P-B(Plackett-Burman)法筛选出吸附过程4个主要影响因素分别为pH,初始ρ(Cr3+)及微生物吸附剂XB和TQ的投加量,应用最陡爬坡试验接近主要因素最优水平,采用Box-Behnken试验设计和响应面分析得到对低浓度Cr3+吸附过程的二阶模型.结果表明,最优吸附条件为pH 4.0,初始ρ(Cr3+)为4.86  mg/L,XB和TQ的投加量分别为0.20和0.13 g/L,实际吸附率达到87.54%,与理论预测值(87.68%)接近,且高出单一吸附剂吸附率7.79%~17.35%.FT-IR扫描显示,复合微生物吸附剂性能提高与表面基团增多有关.通过响应面分析法优化复合微生物吸附,吸附性能明显提高.

     

    Abstract: A composite biosorbent was prepared by mixing four microbial biosorbents from absorption groups with diverse characteristics.The Cr(Ⅲ) adsorptive property of the composite biosorbent was tested in low Cr(Ⅲ) mass concentration solution by statistical method.The Plackett-Burman (P-B) design and Response Surface Methodology (RSM) were applied to optimize the adsorption process based on single factor experiments.The P-B results showed that the pH,initial Cr(Ⅲ) mass concentration,dosage of biosorbent XB and TQ were the four main factors that significantly affected the adsorption process.The path of steepest ascent was undertaken to approach the optimal region of the four significant factors.A second order model of the adsorption of low Cr(Ⅲ) mass concentration was obtained by Box-Behnken design and response surface analysis.Results indicated that the optimal adsorption condition of pH,initial Cr(Ⅲ) mass concentration,microbial biosorbents XB and TQ concentration were 4.0,4.86  mg/L,0.20 and 0.13 g/L,respectively.The results of verification testing showed that the optimized adsorption rate was 87.54%,very close to the predicted value of 87.68%,and the absorptive was rate higher than that of a single biosorbent by 7.79%-17.35%.FT-IR spectra photography revealed that the improved adsorption capability was related to the increase of functional groups in composite biosorbents.The sorption characteristics of the composite biosorbent will obviously be enhanced if Response Surface Methodology (RSM) were applied to optimize the adsorption process.

     

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