Prediction and Analysis of Total Nitrogen in a Sewage Treatment Plant Effluent  

作　　者：Kemeng Xue Kemeng Xue(Beijing No.4 High School, Xicheng District, Beijing, China)

机构地区：[1]Beijing No.4 High School, Xicheng District, Beijing, China

出　　处：《Open Journal of Modelling and Simulation》2024年第4期114-129,共16页建模与仿真（英文）

摘　　要：Total nitrogen was an important indicator for characterizing eutrophication of polluted water. Although the use of water quality online monitoring instrument can monitor water quality changes in real time, the degree of intelligence was low, so it was urgent to predict the water quality and take precautions in advance. A predictive model for total nitrogen levels in a sewage treatment plant utilizing the Anaerobic-Anoxic-Oxic (AAO) process was investigated in this paper. This model demonstrated significant practical application value. Based on the ARIMA (Autoregressive Integrated Moving Average) model and taking into account the impact of Biochemical Oxygen Demand (BOD), a prediction model for effluent total nitrogen was developed. However, the initial results exhibited significant deviations. To address this issue, seasonal factors were further considered. Then, the dataset was divided into winter and Non-winter sub-samples, leading to a reconstruction of the prediction model. Additionally, in developing the Non-winter prediction model, life cycle considerations were incorporated, and consequently, a SARIMA (Seasonal Autoregressive Integrated Moving Average) model was established. The predicting deviation associated with both the winter and Non-winter forecasting models showed a significant reduction.Total nitrogen was an important indicator for characterizing eutrophication of polluted water. Although the use of water quality online monitoring instrument can monitor water quality changes in real time, the degree of intelligence was low, so it was urgent to predict the water quality and take precautions in advance. A predictive model for total nitrogen levels in a sewage treatment plant utilizing the Anaerobic-Anoxic-Oxic (AAO) process was investigated in this paper. This model demonstrated significant practical application value. Based on the ARIMA (Autoregressive Integrated Moving Average) model and taking into account the impact of Biochemical Oxygen Demand (BOD), a prediction model for effluent total nitrogen was developed. However, the initial results exhibited significant deviations. To address this issue, seasonal factors were further considered. Then, the dataset was divided into winter and Non-winter sub-samples, leading to a reconstruction of the prediction model. Additionally, in developing the Non-winter prediction model, life cycle considerations were incorporated, and consequently, a SARIMA (Seasonal Autoregressive Integrated Moving Average) model was established. The predicting deviation associated with both the winter and Non-winter forecasting models showed a significant reduction.

关 键 词：Total Nitrogen Sewage Treatment Plant PREDICTION ARIMA Model 

分 类 号：X70[环境科学与工程—环境工程]