強化ANAMMOX 去除碳氮磷程序及ANFIS預測之研究

A Study on Enhance ANAMMOX Nutrient Removal Process and ANFIS Prediction

張延欣(Yen-hsin Chang)

指導教授 ： 白子易 ； 王順成

朝陽科技大學/理工學院/環境工程與管理系/碩士(2012年)

摘要

摘要

本研究主要了解ANAMMOX 反應於EABD-AO之效益和ANFIS之預測目的於增進污水處理廠處理之效益。主要分為兩大部分：1. ANFIS: (1) 應用相關系數方法篩選系統參數探討應用適應性模糊推論系統 ( adaptive network based fuzzy inference system, ANFIS)並建立模擬模型。(2) 探討ANFIS對工業區廢水廠出流水水質之預測效能。2. ANAMMOX: (1) 建立新穎之去除碳、氮、磷併同ANAMMOX 程序。(2)利用EABD-AO 活性污泥系統進而了解其活性污泥微生物功能族群之反應常數。研究結果顯示， ANFIS 對於工業區廢水廠出流水水質之預測結果： ANFIS之 SSeff、CODeff、pHeff預測結果最佳之平均百分誤差值 ( mean absolute percentage error, MAPE) 分別為13.88%、9.47%、2.11%；相關係數 ( correlation coefficient, R )分別為0.41、0.36、0.80；經研究結果所示ANFIS之MAPE與 R 值皆屬於高度相關性，顯示模擬值與實際值將近一致。而模廠活性污泥微生物功能族群之反應常數驗證EABD-AO模廠於添加無機碳後ANAMMOX反應有助於模廠之去除率，於批次筒試驗及ANAMMOX計量計算中更加證實其存在性，有助於了解其反應所消耗的能量常數。

關鍵字

適應性模糊類神經推論系統 ； ANAMMOX ； 預測模式 ； EABD-AO

並列摘要

Abstract

This study aims to investigate the effectiveness of applying ANAMMOX in EABD-AO and the ANFIS prediction purposes for enhancing the effectiveness of sewage treatment plants. The paper is divided into two parts: 1) ANFIS: (1) to apply the correlation coefficient method to screen system parameters for discussion of applying ANFIS (adaptive network based fuzzy inference system) and establish the simulation model; (2) to discuss the ANFIS’ efficiency in predicting the quality of industrial wastewater plant effluents; 2) ANAMMOX: (1) to establish the innovative removal procedures of carbon, nitrogen and phosphorus and the ANAMMOX program; (2) to use the EABD-AO active sludge system to understand the response constant of the active sludge microbial functional groups. The results showed that, the prediction results of ANFIS regarding the industrial wastewater plant effluents are: the optimal MAPE (mean absolute percentage error) of SSeff, CODeff, pHeff as predicted by ANFIS are 13.88%, 9.47%, 2.11%, respectively; CR (correlation coefficient) are 0.41, 0.36, 0.80 respectively. The results suggested that, the MAPE and R value of ANFIS are highly correlated, indicating that the simulated values and the actual values are almost consistent. The response constant of the simulated active sludge microbial functional groups has confirmed that the ANAMMOX reaction after the addition of inorganic carbon in the EABD-AO simulated plant can help the removal rate of the plant. The batch barrel test and ANAMMOX calculation also confirm its existence, thus help to understand the constant of the energy consumed in reaction.

並列關鍵字

ANAMMOX ； EABD-AO ； prediction model ； adaptive network-based fuzzy inference system

參考文獻

5. 陶雨龍，「改良式模糊類神經網路與其應用」，私立中原大學工業工程系碩士論文，桃園(2004)。

1. APHA, AWWA, WEF. Standard Methods for the Examination of Water and Wastewater. 19th ed(1995).

3. Dong Z. and Sun T. A potential new process for improving nitrogen removal in constructed wetlands-Promoting coexistence of partial-nitrification and ANAMMOX. Ecological Engineering, 31(2), 69-78(2007).

4. Egli K., Franger U., Alvarez P.J.J., Siegrist H., Vandermeer J.R. and Zehnder A.J.B. Enrichment and characterization of ANANAMMOX bacterium from a rotating biological contactor treating ammonium-rich leachate. Arch Microbiol, 175, 198-207(2001).

5. Engström P., Dalsgaard T., Hulth S. and Aller R.C. Anaerobic ammonium oxidation by nitrite (ANAMMOX): Implications for N2 production in coastal marine sediments.Geochimica et Cosmochimica Acta, 69(8), 2057-2065(2005).