摘要:
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3h,活性炭纤维投加量为2.5g/200mL (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。
Abstract:
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/200mL (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
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