多段進流去氮除磷系統穩動態處理及
控制特性之研究

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周裕然(yu-jan chou) 查詢紙本館藏

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論文名稱

多段進流去氮除磷系統穩動態處理及控制特性之研究
(The characteristics of nutrient removal in multiple stages in enhanced biological nutrient removal process )

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摘要(中)

摘要
本研究所探討之TNCU-III 程序由厭氧及多段好氧-缺氧槽串聯而成，在無回流好氧硝化液的情況下，藉由階梯進流結合傳統活性污泥程序的方式，可提升總氮去除效率而不造成總磷去除效果的降低。本研究以穩、動態進流的方式進行微生物馴養，探討TNCU-III 程序於不同進流狀態時之營養鹽去除特性，並輔以分子生物技術之微生物鑑定、不同外部碳源添加及柔性計算原理，結合線上水質監
測技術，建立動態多段進流提昇總氮去除率之技術與操作準則。穩態實驗結果顯示TNCU-III 程序無須迴流硝化液，並可節省鹼劑使用量，因此大幅降低操作費用，三段式、兩段式及不分流操作皆可滿足出流水總氮小於
15mg/L、總磷2mg/L 之放流水標準。若欲達總氮濃度小於10mg/L、總磷濃度小於0.5mg/L 之出流水質，則所需總水力停留時間約為10 小時，其中厭氧段、好氧段與缺氧段之水力停留時間比約為1.5:5.5:3.0。TNCU-III 程序活性污泥菌相分析方面，不分流操作之活性污泥菌相包括
Proteobacteria、CFB group、Chloroflexi 及Firmicutes 屬；而三段分流操作之活性污泥菌相包含Proteobacteria、CFB group、Chloroflexi 、Nitrospirae group 及
Planctomycetales 屬。兩污泥樣本中皆存在硝化菌、脫硝菌、除磷菌、絲狀菌與化學需氧量降解菌，其中三段分流操作化學需氧量降解菌菌種多樣性高於單段操作，同時兼具除磷與脫硝能力的Acidovorax defluvii 菌種比例亦較高，約為15.2%。此外兩試程操作皆馴養出Eikelboom Type 1851 的絲狀菌，約佔不分流與三段分流操作總菌落數10%與12%。添加外部碳源提升總氮去除之批次實驗結果顯示，醋酸鈉之添加將導致磷的再釋出效應，且較大的C/N 比會造成較高的比釋磷量及PHAs 累積。添加甲醇時，微生物在前15 分鐘可進行脫硝反應，但其後反應槽混合液溶解性化學需氧量增加、變動，同時過濾液濁度增加，實驗終了時無亞硝酸氮的累積。若以醣類作為脫硝碳源，最終總硝酸氮去除率高於醋酸鈉、甲醇之添加約10~25%。因批次實驗（醋酸鈉除外）皆檢測不到反應液正磷酸鹽濃度，但活性污泥中PHAs 卻增加，故推論TNCU-III 程序中存在肝醣蓄積菌，增加脫硝所需之碳源劑量。
動態實驗結果顯示因進流量變動發生污泥沖刷、營養鹽未能充分分解利用的現象以前四槽最為明顯，且十二個實驗試程厭氧段C/P 比約在20~70 之間變化，因C/P 變化過大，影響磷蓄積菌除磷之穩定性，故除磷效果較穩態為不理想。水質數據顯示以回流比=0.5、Q1:Q2:Q3=(0.7:0.2:0.1)試程之總氮、總磷去除效果最佳，出流水總氮、總磷濃度可低於7.6 與0.3mg/L。此外即時監測數據顯示厭氧段pH 值可作為基質酸化水解指標，而厭氧段ORP 及好氧第一段殘餘溶氧濃度變化可呈現污水生物處理之負荷變動趨勢，亦可作為動態控制的指標參數，此指
標參數於TNCU-III 程序動態操作時發生1~2 小時的時間延遲現象，且出流水殘餘營養鹽濃度或是懸浮固體物濃度變化與進流水流量變動無明顯之一致性。此外本研究結合遺傳演算法與描述營養鹽降解之串聯式類神經網路以建立
水質模擬模式，並進行動態操作之最佳化演算與模式敏感度分析，獲致TNCU-III程序動態操作不同時段之最佳分流比及污泥回流比，因水質實驗數據與模擬值間的高度相關性與低均方根誤差，且最佳試程操作之出流水水質總氮濃度較固定進流分流比、污泥回流比操作為佳，因此人工智慧技術可做為EBNR 程序水質模擬及最佳化控制之輔助工具。

摘要(英)

ABSTRACT
Improvement of nutrient removal efficiency without recycling nitrified liquor was
accomplished in this research. A step feed strategy was successfully incorporated into
the TNCU-III process for enhancing the nitrogen removal without phosphorus
elimination decline. The thesis investigated the nutrient removal characteristics,
microbial population, and denitrification behavior of microorganisms by cultivating
activated sludge under stable wastewater influent condition, molecular biotechnology,
and external carbon source addition, respectively. Moreover, microbial kinetic
parameters obtained from continuous pilot-plant operation were used to optimize each
reactive volume of TNCU-III process. Under dynamic loading, real-time effluent
water quality data acquired from monitoring instruments and soft-computing
technology in terms of artificial neural networks (ANNs) and genetic algorithm (GA)
were combined to minimize effluent nutrients concentration.
In the steady-state experiments, non-, two or three step-feeding strategy resulted in
excellent treated water quality, and effluent total nitrogen (T-N) and phosphorus (T-P)
concentration were less than 15 mg/L and 2 mg/L, respectively. Results also showed
the potential of saving energy or alkaline consumption in TNCU-III process. When
three step-feeding strategy and enough hydraulic retention time (10hrs) were
implemented, the better effluent water quality was obtained (T-N<10mg/L,
T-P<0.5mg/L); meanwhile the ratio of anaerobic-oxic-anoxic retention time was
1.5:5.5:3.0.
In the microbial population identification, bacteria of Proteobacteria group, CFB
group, Chloroflexi group, and Firmicutes group were present in non step-feeding
operation. Additionally, bacteria of Proteobacteria group, CFB group, Chloroflexi
group, Nitrospirae group, and Planctomycetales existed in three step-feeding sludge
sample. Both two activated sludge samples involved specific species for nutrient
removal, carbon utilization, and filamentous bacteria. The diversity of microbial
population response for carbon uptake in three step-feeding was higher than that in
non step-feeding mode. Filamentous bacteria (Eikelboom Type 1851) existed in both
two sludge samples, and the proportion were about 10 and 12%.
According to external carbon source addition experiments, sodium acetate addition
resulted in phosphate re-release problem. If methanol was used to be the electron
donor, microorganisms needed more adaptive time to utilize methanol; meanwhile
resulted in carbon breakthrough. When glucose was fed, the final nitrate (NO3-N)
removal efficiency was higher than former carbon sources about 10~25%. Moreover,
the final PHAs contained within the biomass were more than original level and no
PO4-P re-release was observed when methanol and glucose addition, glycogen
accumulating organisms (GAOs) might exist in TNCU-III process and increased
carbon dosage for NO3-N removal.
Furthermore, wash-out effect of mixed liquor suspended solid and nutrients were
occurred in the first four reactive zones under dynamic loading. Because of the
obvious variation of C/P ratio (C/P=20~70) in anaerobic zone, the activity of
polyphosphate accumulating organisms (PAOs) decreased. When TNCU-III process
was operated at sludge recycle ratio=0.5 and Q1:Q2:Q3=(0.7:0.2:0.1), effluent T-N and
T-P concentration were less than 7.6mg/L and 0.3mg/L, respectively. Additionally,
real-time monitoring data demonstrated pH and reduction potential in anaerobic zones
and residual dissolved oxygen (DO) concentration in the first aerobic zone well
described the variation of organic loading. All the aforementioned parameters could
be considered as the indicators in TNCU-III control strategy-making procedure.
Moreover, artificial intelligence (AI) technique by means of serial ANNs describing
metabolic behavior of microorganisms and GA were successfully integrated into the
modeling system. The modeling system simulate the dynamic characteristics of
nutrients removal and minimized effluent NO3-N concentration. Due to low root mean
squared of error and high correlation coefficient between simulated and experimental
data, AI technology offered an alternative approach to simulate and optimized nutrient
removal of an EBNR system.

關鍵字(中)

★ TNCU-III 程序
★ 動態多段進流
★ 柔性計算原理

關鍵字(英)

★ soft-computing technology
★ dynamic loading
★ TNCU-III process

論文目次

V
目錄
中文摘要……………………………………………………………… I
英文摘要……………………………………………………………… III
目錄…………………………………………………………………. V
圖目錄…………………………………………………………………. VIII
表目錄…………………………………………………………………. XI
第一章緒論………………………………………………………………… 1
1.1 研究緣起……………………………………………………………. 1
1.2 研究目的與內容……………………………………………………. 3
1.3 研究架構……………………………………………………………. 4
第二章文獻回顧…………………………………………………………... 5
2.1 生物營養鹽氮磷代謝機制…………………………………………. 5
2.1.1 生物去氮………………………………………………. 6
2.1.1.1 生物去氮機制及影響因子……………………….. 6
2.1.1.2 生物去氮程序…………………………………….. 11
2.1.2 生物除磷………………………………………………. 13
2.1.2.1 生物除磷原理及影響因子……………………….. 13
2.1.2.2 生物除磷程序…………………………………….. 16
2.1.3 氮磷併同去除程序之發展……………………………. 17
2.2 外部碳源添加對生物營養鹽去除程序之影響……………………. 21
2.3 分子生物技術於活性污泥微生物鑑定之原理……………………. 27
2.3.1 污泥DNA 萃取及PCR 反應…………………………. 27
2.3.2 基因選殖………………………………………………. 28
2.3.3 族群指紋譜建立………………………………………. 29
2.3.4 定序及資料庫比對……………………………………. 30
2.4 強化生物營養鹽去除(EBNR)程序之動態控制策略擬定………... 32
2.4.1 動態控制之目標與監測項目…………………………. 32
2.4.2 控制參數選定之依據與擾動因子……………………. 36
2.4.3 前餽式與後餽式控制原理及其應用…………………. 41
2.5 柔性計算原理應用於活性污泥程序之最佳化操作………………. 45
2.5.1 模糊理論應用於活性污泥法操作策略擬定…………. 46
2.5.2 類神經網路原理及其相關應用………………………. 48
2.5.3 遺傳演算法及其最佳化求解…………………………. 54
VI
第三章實驗材料與方法…………………………………………………. 58
3.1 反應槽配置及馴養基質組成………………………………………. 58
3.1.1 連續式穩、動態進流之模廠反應槽配置……………. 58
3.1.2 連續式穩、動態進流之馴養基質組成………………. 62
3.1.3 連續式動態進流之監測儀器配置……………………. 64
3.1.4 批次反應槽配置………………………………………. 68
3.2 實驗設計……………………………………………………………. 69
3.3 實驗方法與分析設備………………………………………………. 70
3.3.1 水質檢驗方法與分析設備……………………………. 70
3.3.2 分子生物實驗方法與分析設備………………………. 70
3.4 柔性計算原理及其相關參數設定…………………………………. 72
3.4.1 類神經網路參數設定…………………………………. 72
3.4.2 遺傳演算法參數設定…………………………………. 73
第四章TNCU-III 程序於穩態進流之實驗結果…………………….. 74
4.1 TNCU-III 程序於不同分流比操作之實驗結果……………………. 74
4.1.1 實驗設計………………………………………………. 74
4.1.2 TNCU-III 程序之COD 去除特性…………………….. 74
4.1.3 TNCU-III 程序之釋磷、攝磷特性……………………. 75
4.1.4 TNCU-III 程序之硝化、脫硝特性……………………. 79
4.2 TNCU-III 程序之活性污泥菌相分析………………………………. 82
4.2.1 實驗設計………………………………………………. 82
4.2.2 單段進流操作之污泥菌相……………………………. 83
4.2.3 三段分流操作之污泥菌相……………………………. 89
4.2.4 TNCU-III 程序活性污泥菌相之比較………………… 95
4.3 TNCU-III 程序添加外部碳源提升總氮去除之實驗結果…………. 100
4.3.1 實驗設計………………………………………………. 100
4.3.2 添加醋酸鈉之實驗結果………………………………. 102
4.3.3 添加甲醇之實驗結果…………………………………. 104
4.3.4 添加葡萄醣之實驗結果………………………………. 105
4.3.5 添加蔗醣之實驗結果…………………………………. 105
4.3.6 空白實驗………………………………………………. 106
4.3.7 添加不同外部碳源之比較……………………………. 106
4.4 TNCU-III 程序之反應槽體積推估…………………………………. 110
4.5 TNCU-III 程序於穩態進流操作之結論……………………………. 116
VII
第五章TNCU-III 程序於動態進流之實驗結果…………………….. 121
5.1 TNCU-III 程序於動態不同分流比、回流比之實驗結果………….. 121
5.1.1 實驗設計………………………………………………. 121
5.1.2 單段進流操作之營養鹽去除特性……………………. 122
5.1.3 兩段分流操作之營養鹽去除特性……………………. 124
5.1.4 三段分流操作之營養鹽去除特性……………………. 130
5.1.5 不同實驗試程之營養鹽去除特性比較………………. 136
5.2 TNCU-III 程序於動態操作之即時監測數據分析…………………. 140
5.2.1 實驗設計………………………………………………. 140
5.2.2 單段進流操作之即時監測數據分析…………………. 140
5.2.3 兩段分流操作之即時監測數據分析…………………. 142
5.2.4 三段分流操作之即時監測數據分析…………………. 144
5.2.5 TNCU-III 程序動態控制之指標參數………………… 145
5.3 TNCU-III 程序於動態進流操作之結論……………………………. 148
第六章應用柔性計算原理於TNCU-III 程序之最佳化操作…… 150
6.1 類神經網路於TNCU-III 程序動態操作之水質模擬………………. 150
6.1.1 類神經網路訓練、測試數據來源及前處理…………. 150
6.1.2 類神經網路架構之選定及預測試結果………………. 151
6.1.3 類神經網路之合理性評估與敏感度分析結果………. 154
6.1.4 類神經網路於兩段分流動態操作之水質模擬………. 156
6.2 類神經網路結合遺傳演算法於TNCU-III 程序動態操作最佳化... 162
6.2.1 最佳化模式之建立……………………………………. 162
6.2.2 動態進流最佳試程操作結果…………………………. 169
6.3 TNCU-III 程序動態進流最佳化操作之結論………………………. 176
第七章結論與建議……………………………………………………….. 178
7.1 結論…………………………………………………………………. 178
7.2 建議…………………………………………………………………. 184
參考文獻………………………………………………………………………... 185
附錄………………………………………………………………………............. 195
附錄A 水質監測儀器規格與校正曲線………….............…………... 195
附錄B PHAs 分析方法………………………………………............... 200
附錄C 分子生物實驗方法………………………………..................... 201
附錄D 遺傳演算最佳化模式預測試結果…………………………… 207

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指導教授

歐陽嶠暉(Chaio-Fuei Ouyang)

審核日期

2002-10-9

推文