摘要
The reduction of nitrate using internal circulation micro-electrolysis te chnology(ICE)was investigated.The effect of the reaction time,initial pH,Fe/C ratio,and aeration rate on the nitrate reduction was investigated using a single factor experiment.Based on the results of the single factor experiment,a response surface methodology(RSM)was applied to optimize the N2 generation selectivity.The effects and interactions of three independent variables were estimated using a Box-Behnken design.Using the RSM analysis,a quadratic polynomial model with optimal conditions at pH=8.8,Fe/C=1:1,and an aeration rate of 30 L·min-1 was developed by means of the regre ssion analysis of the experimental data.Using the RSM optimization,the optimal conditions yielded a N2 generation selectivity of 72.0%,which is in good agreement with experimental result(73.2%±0.5%)and falls within the 95%confidence interval(IC:66.8%-77.3%)of the model results.This indicates that the model obtained in this study effectively predicts the N2 generation selectivity for nitrate reduction by the ICE process,thus providing a theoretical basis for process design.
The reduction of nitrate using internal circulation micro-electrolysis te chnology（ICE） was investigated.The effect of the reaction time,initial pH,Fe/C ratio,and aeration rate on the nitrate reduction was investigated using a single factor experiment.Based on the results of the single factor experiment,a response surface methodology（RSM） was applied to optimize the N2 generation selectivity.The effects and interactions of three independent variables were estimated using a Box-Behnken design.Using the RSM analysis,a quadratic polynomial model with optimal conditions at pH=8.8,Fe/C=1:1,and an aeration rate of 30 L·min-1 was developed by means of the regre ssion analysis of the experimental data.Using the RSM optimization,the optimal conditions yielded a N2 generation selectivity of 72.0%,which is in good agreement with experimental result（73.2%±0.5%） and falls within the 95% confidence interval（IC:66.8%-77.3 %） of the model results.This indicates that the model obtained in this study effectively predicts the N2 generation selectivity for nitrate reduction by the ICE process,thus providing a theoretical basis for process design.
基金
Supported by the National Natural Science Foundation of China(21677018)
the Joint Fund of the Beijing Natural Science Foundation and Beijing Municipal Education Commission(KZ201810017024).
作者简介
Corresponding author.Yanhe Han,E-mail address:hanyanhe@bipt.edu.cn
