基于响应面法的活性炭纤维去除叶绿素a优化研究

Optimization of Activated Carbon Fiber to Remove Chlorophyll a by Using Response Surface Methodology

为优化活性炭纤维去除叶绿素a系统操作参数,在单因素试验研究的基础上,应用Box-Behnken试验设计,采用3因素3水平的响应面分析法,建立了初始pH、反应时间、活性炭纤维投加量对反应后叶绿素a浓度影响的回归模型。结果表明,模型显著,拟合度良好,精确度高,数据合理,试验误差小。通过对回归模型的求解及综合考虑,得到优化的工艺条件为初始pH=6.0,反应时间为3 h,活性炭纤维投加量为2.5 g/200 mL(活性炭纤维重量/水样体积)。在此条件下,验证结果表明,活性炭纤维平均除藻率达到94.55%,反应后叶绿素a浓度的相对误差在7%以内,说明该模型能较好地优化活性炭纤维对叶绿素a的去除操作条件和预测反应后叶绿素a浓度。

In order to optimize the activated carbon fiber to remove Chlorophyll a(Chl-a),a Box-Behnken design and a response surface methodology with three factors and three levels were used in this study to establish regression models for predicting initial pH,time and activated carbon fiber dosage effects on Chlorophyll a concentration after reaction.The results showed that the regression model were significant(P<0.05),fitted well with experimental data and had a high degree of accuracy.And the data were reasonable with low errors.By solving the regression models and considering other factors,the optimized operation conditions of algal removal were pH=6.0,3 h and 2.5 g/200 mL(activated carbon fiber/the volume of water sample)of activated carbon fiber dosage.Through validation,the average algae removal rate of activated carbon fibers reached 94.55%,relative errors of Chlorophyll a concentrations were less than 7%,indicating that the models were reliable and accurate.