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污泥干化芦苇床渗滤液中CODCr和TP浓度预测模型

崔玉波 孙红杰 张万筠 贺张伟

崔玉波, 孙红杰, 张万筠, 贺张伟. 污泥干化芦苇床渗滤液中CODCr和TP浓度预测模型[J]. 环境科学研究, 2016, 29(8): 1224-1229.
引用本文: 崔玉波, 孙红杰, 张万筠, 贺张伟. 污泥干化芦苇床渗滤液中CODCr和TP浓度预测模型[J]. 环境科学研究, 2016, 29(8): 1224-1229.
CUI Yubo, SUN Hongjie, ZHANG Wanjun, HE Zhangwei. Percolate CODCr and TP Prediction Models in Sludge Treatment Wetland[J]. Research of Environmental Sciences, 2016, 29(8): 1224-1229.
Citation: CUI Yubo, SUN Hongjie, ZHANG Wanjun, HE Zhangwei. Percolate CODCr and TP Prediction Models in Sludge Treatment Wetland[J]. Research of Environmental Sciences, 2016, 29(8): 1224-1229.

污泥干化芦苇床渗滤液中CODCr和TP浓度预测模型

基金项目: 国家自然科学基金项目(51278088);辽宁省科学事业公益研究基金项目(2014004006);中央高校基本科研业务费专项(DC201502070203)

Percolate CODCr and TP Prediction Models in Sludge Treatment Wetland

  • 摘要: 为便于水质管理,在大连开发区污水处理厂设立了1个传统污泥干化床和2个污泥干化芦苇床,根据系统出水ρ(CODCr)和ρ(TP)检测数据的平稳系列特点,采用ARIMA时间序列分析模型对出水ρ(CODCr)和ρ(TP)进行模拟和预测. 结果表明:ARIMA(1,0,0)模型可较好地模拟和预测出水ρ(CODCr)的变化,R2达0.577以上,预测相对误差在-10%~19%之间,实测值和预测值之比处于0.8~1.2之间;ARIMA(6,0,0)模型能较好地模拟和预测污泥处理湿地渗滤液出水ρ(TP)的变化,R2在0.487以上,预测相对误差在-4%~16%之间,实测值和预测值之比处于0.8~1.2之间. 研究显示,所构建的ARIMA模型可用于污泥处理湿地系统运行过程中渗滤液出水ρ(CODCr)和ρ(TP)的预测.

     

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出版历程
  • 收稿日期:  2015-12-12
  • 修回日期:  2016-03-19
  • 刊出日期:  2016-08-25

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