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厌氧/特异性移动床生物膜反应器处理低碳氮比工业废水脱氮效果优化分析 被引量:2

Optimization analysis of denitrification effect of industrial wastewater with low carbon nitrogen ratio treated by A/SMBBR
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摘要 采用SDC-03型填料作为生物载体,对厌氧/特异性移动床生物膜反应器(A/SMBBR)工艺处理低碳氮比工业废水的挂膜启动及稳定运行过程进行优化分析。通过单因素试验和基于Box-Behnken设计的响应曲面法考察了碳源投加量(以乙醇为碳源)、水力停留时间(HRT)及填料填充率对系统TN去除率的影响及其交互作用。结果表明:(1)3个参数对TN去除率影响顺序为填料填充率>碳源投加量>HRT,其中填料填充率和HRT之间的交互作用最显著。(2)模型预测的最佳条件为碳源投加量90mg/L、HRT=3.0d、填料填充率55%,TN去除率预测值为90.78%。在该条件下TN去除率实际值达91.02%,与模型预测值基本一致,表明响应曲面模型与实际情况拟合良好。 The SDC-03 packing was used as the biological carrier,and the membrane start-up and stable operation of the anaerobic/specific moving bed biofilm reactor(A/SMBBR)process for the treatment of industrial wastewater with low carbon-nitrogen ratio was optimized and analyzed.The effects of carbon input(ethanol as carbon source),hydraulic retention time(HRT)and filler filling rate on TN removal and their interactions were investigated by single factor test and response surface method based on box-behnken.The results showed that:(1)the order of the three parameters on TN removal rate was filling rate>carbon source dosage>HRT,and the interaction between filling rate and HRT was the most significant.(2)The best conditions predicted by the model were the carbon source dosage of 90 mg/L,HRT of 3.0 d,filler filling rate of 55%,and the predicted TN removal rate of 90.78%.Under these conditions,the actual value of the TN removal rate reached 91.02%,which was basically consistent with the model,indicating that the response surface model fitted the actual situation well.
作者 郝梦影 杨宇杰 敬双怡 杨文焕 于玲红 李卫平 HAO Mengying;YANG Yujie;JING Shuangyi;YANG Wenhuan;YU Linghong;LI Weiping(School of Energy and Environment,Inner Mongolia University of Science and Technology,Baotou Inner Mongolia 014010)
出处 《环境污染与防治》 CAS CSCD 北大核心 2020年第4期437-441,448,共6页 Environmental Pollution & Control
基金 内蒙古自治区高等学校科学技术研究项目(No.NJZY16164) 内蒙古科技创新引导项目(No.KCBJ2018033) 包头科技计划重点领域技术攻关项目(No.2017Z1009-1)。
关键词 厌氧/特异性移动床生物膜反应器 低碳氮比 脱氮效果 响应曲面法 优化 A/SMBBR low carbon nitrogen ratio denitrification effect response surface method optimization
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