摘要
为优化污水处理厂化学除磷效果,以液态聚合氯化铝为混凝剂研究了投药比(β)、pH值、反应温度和搅拌强度4个因素的除磷效果。在单因素试验基础上,以磷去除率为响应值,采用Box-Behnken响应面法考察了β值、pH值、反应温度之间的交互作用,利用Design Export 8.0.6软件建立二次多项式响应面模型。模型拟合结果显示温度这一因素对磷去除率的影响显著,几种因素的影响排序为温度>β值>pH值。模型优化最佳工艺条件为β:4.86,pH:6.4,反应温度:29.5℃。在此条件下,预测最大磷去除率为97.5%,验证试验磷去除率为96%,与预测值偏差较小,说明该模型可信度高。试验结果可以为污水厂除磷工艺优化提供科学支持。
In order to optimize the chemical phosphorus removal in sewage treatment plant,poly aluminium chloride was used as the coagulant to study the phosphorus removal effect of four factors,namely,dosing ratio(β),pH value,temperature,and agitation speed.The Box-Behnken response surface method(RSM)was adopted to examine the phosphorus removal efficiency based on the results of one-factor tests.The individual effects and interactive interactions of the three factors includingβvalue,pH value,and temperature were investigated.The quadratic polynomial response surface model was obtained by Design Export 8.0.6 software.The results showed that influence of temperature on phosphorus removal efficiency was the best among the three factors,and the influence factors followed a descending order as temperature>βvalue>pH value.The optimal reaction conditions were obtained asβ:4.86,pH:6.4,temperature:29.5℃,and the estimated maximum phosphorus removal efficiency was 97.5%.Under these conditions,the phosphorus removal efficiency was 96%in the Verification test,which had a small deviation of prediction value.The results can be used to optimize the phosphorus removal process in sewage plants.
作者
苗志加
孟祥源
石林松
云玉攀
梁嘉芹
孙莉丽
刘晶晶
赵志瑞
MIAO Zhi-jia;MENG Xiang-yuan;SHI Lin-song;YUN Yu-pan;LIANG Jia-qin;SUN Li-li;LIU Jing-jing;ZHAO Zhi-rui(Hebei GEO University,Shijiazhuang 050031,China;Shijiazhuang Wastewater Treatment Co.,Ltd.Qiaoxi Wastewater Treatment Plant,Shijiazhuang 050031,China)
出处
《河北地质大学学报》
2022年第6期69-76,共8页
Journal of Hebei Geo University
基金
河北省自然科学基金面上基金(C2021403002)
河北省创新能力提升计划项目(21553601D)
河北省高校基本科研业务费资助(QN202109)
河北省水资源可持续利用与产业结构优化协同创新中心开放基金(XTZX202115)。
关键词
化学除磷
混凝剂
响应面
影响因素
chemical phosphorus removal
coagulants
response surfaces
influencing factors
