我們發現國內之飲用水水質變化之原因，最主要是因為原水經水處理場處理程序效能導致給配水系統異營性微生物生長，此現象稱為後生長（Aftergrowth）或再生長(Regrowth)。
本研究針對高級及傳統淨水處理場之原水、各種淨水處理程序與管網之水質項目進行採樣及分析來探討：(1)傳統水處理和高級水處理程序水中微量有機物之去除效率；(2) 淨水處理程序中生物可利用有機碳(Assimilable Organic Carbon，簡稱AOC)之濃度變化；(3)以類神經網路系統中之AutoNet(6.03)方法建立AOC之預測模式。
研究採樣時間從2009年12月至2010年11月，每月採樣一次，其原水取得為水庫貯留水，就高級淨水處理場及傳統淨水處理場中去除水中微量有機物進行分析(含TOC、DOC、UV254和 AOC)，實驗結果表明高級淨水處理場中採用較先進水處理流程之預臭氧接觸槽、脈動式膠凝沉澱池及生物活性碳濾床之AOC去除率分別為19%、36%及22%。證明其新設預臭氧接觸槽、脈動式膠凝沉澱池和生物活性碳濾床可有效去除AOC；總有機碳TOC和溶解性有機碳DOC於預臭氧接觸槽之生成率為5%及7%。傳統淨水處理場中則以平底式混凝沉澱池之AOC去除率39%最為有效，快濾池只能去除3%的AOC，前加氯之總有機碳TOC和溶解性有機碳DOC生成率為3%及2%。以採樣分析之13項水質數值進行類神經網路模式模擬預測，預測值差異百分比介於13.6~27.4%，依模擬預測結果建議高級水處理場需將TDS及NH3-N數值納入定期監測；傳統水處理場則應將DOC、UV254及水溫數值納入定期監測。
研究中發現，高級淨水處理場之預臭氧處理單元的臭氧濃度介於1.0~1.24 mg/L，受優養化湖水之藻類及其他物質消耗影響，對於可利用之有機碳原為AOC-P17可用轉變成AOC-NOX可利用之氧化作用不足。結晶軟化槽處理單元之AOC-P17生成量達73.9%，其可能生成機制以腐植質中之腐植酸溶於鹼性環境中，與加入之鹼劑扮演一重要的陽離子與微量金屬離子之吸附劑，進行離子交換作用，釋出AOC-P17可利用機質有關。澄清湖水庫於底泥挖除工程後接續之排砂道工程可減少原水中14.1%之TOC；本研究期間，仁義潭水庫之原水TOC平均值為1.25mg/L，稍高於澄清湖水庫之0.8 mg/L，如能以底泥挖除工程配合引流端之沉澱池固定排砂工程施作，應可降低原水取水口之AOC。於GW淨水場前加氯處理單元後，AOC-NOX可利用機質生成率為183%，且以AOC-P17可利用機質為主要去除對象，無法對於低分子量AOC-NOX可利用機質進行有效去除，建議配合各淨水場之原水特性，增設高級淨水處理單元之薄膜處理單元及配水管網之管線維修防止外滲，對於降低飲用水之AOC應是較容易完成之近程目標。

We found numerous factors deteriorate the quality of drinking water in water treatment plant (WTP). These problems are caused by the performance of WTP processes and heterotrophic microbial growth in water distribution network.
In this study, analysis on water quality items of raw water sampled from various water treatment processes in advanced and traditional WTP and pipeline networks. We conducted to explore: (a) the efficiency of traditional and advanced water treatment processes in removing trace organics; (b) fluctuations in the concentration of assimilable organic carbon (AOC) during the water treatment process; (c) the applicability of the AutoNet (6.03) method for constructing an AOC forecast model in an artificial neural network (ANN).
The sampling period was December, 2009 to November, 2010 and raw water was sampled once a month. Raw water was obtained from two reservoirs. An analysis of the trace organics, such as total organic carbon (TOC), dissolved organic carbon (DOC), UV254, and AOC. The results of removal of the advanced and traditional WTP showed that the pre-ozone contactor, pulsator, and biological activated carbon (BAC) filter used in advanced WTP had AOC removal rates of 19%, 36%, and 22%, respectively. This proved that pre-ozone contactor, pulsator, and BAC filters can effectively remove AOC. The growth rates of TOC and DOC in the pre-ozone contactor were 5% and 7%, respectively. In a traditional WTP, the flat bottom coagulation-sedimentation basin was the most effective in AOC removal (39%). The rapid sand filter only removes 3% of the AOC. The TOC and DOC pre-chlorination growth rates were 3% and 2%, respectively. The variations in the forecasted ANN values were based on the 13 water quality values rom the sample analyses, which varied from 13.6% ~ 27.4%. Based on the simulated forecasts, it is recommended that advanced WTP should regularly monitor the total dissolved solids (TDS) and NH3-N values. Traditional WTP should regularly monitor the DOC, UV254, and water temperature values.
In the pre-ozone treatment units of the advanced WTPs, the ozone concentrations varied from 1.0 mg/L to 1.24 mg/L and were affected by the eutrophication of algae in the lake water and the consumption of other materials. This led to the insufficient oxidation of AOC, which converted AOC-P17 to AOC-NOX. The quantity of AOC-P17 generated in the pellet softening treatment unit reached 73.9%. This may be related to the release of the AOC-P17 through the mechanism of humic acid dissolved in alkaline environments. When combined with alkali agents, humic acid becomes a cation and trace metal ion adsorbent that produces an ion-exchange reaction. The sediment releasing project combined with the Chengcing Lake Reservoir sediment excavation projects can remove 14.1% of the TOC in the raw water. During the current study, the mean TOC value of the Jen-Yi-Tan Reservoir was 1.25mg/L, which was slightly higher than the 0.8 mg/L at the Chengcing Lake Reservoir. If sediment excavation projects coordinate the regular release of sediment on the sedimentation basin of intake, the AOC of the raw water at the intake can be reduced. After the pre-chlorination of the GWWTP, the AOC-NOX growth rate was 183% and the primarily removed organic matter was AOC-P17. The AOC-NOX with low molecular weight could not be effectively removed. It is recommended that based on the raw water characteristics of each WTP, installing additional membrane-based treatment units and maintaining water distribution networks to prevent leaks in advanced WTPs be the feasible short-term goal to reduce the AOC in drinking water.

摘 要 i
Abstract iii
目 錄 v
圖目錄 x
表目錄 xii
第一章 前言 1
1-1研究緣起 1
1-2 研究目的與內容 2
第二章 文獻回顧 4
2-1 水源現況 4
2-1-1卡爾森優養指數(CTSI) 4
2-1-2自然水體BOM之影響 6
2-2水質水源保護區 7
2-2-1蘭潭仁義潭飲用水水質水源保護區 7
2-2-2澄清湖飲用水水質水源保護區 9
2-3淨水廠現況 10
2-3-1 GW淨水場 10
2-3-2 CW淨水場 12
2-4淨水處理程序 16
2-4-1傳統淨水處理程序 16
2-4-1-1分水井 17
2-4-1-2量水堰 17
2-4-1-3膠凝沉澱池 18
2-4-1-4快濾池 18
2-4-2高級淨水處理程序 19
2-4-2-1臭氧接觸池 19
2-4-2-3粒狀活性碳濾池 24
2-5有機物的來源與種類 27
2-6配水管網微生物 29
2-6-1管網微生物生長 29
2-6-2配水管網微生物生長之影響因子 30
2-6-3控制配水管網微生物生長 31
2-7生物可利用有機碳之測定 32
2-7-1生物可利用有機碳之菌種概述 34
2-7-2傳統淨水程序對AOC去除之影響 37
2-7-3臭氧處理對AOC去除之影響 38
2-7-4 AOC對飲用水水質之影響 39
2-8淨水處理程序之消毒副產物 40
2-8-1加氯消毒副產物 41
2-8-1-1三鹵甲烷 41
2-8-1-1-1來源及分類 41
2-8-1-1-2生成因素 42
2-8-1-1-3法規管制 45
2-8-1-2鹵化乙酸 46
2-8-1-2-1來源及分類 46
2-8-1-2-2生成因素 48
2-8-1-2-3法規管制 50
2-8-2加臭氧消毒副產物 51
2-9 GMDH理論 52
2-9-1網路架構 53
2-9-2演算方法 53
第三章 研究方法 55
3-1研究流程之規劃 55
3-2採樣 56
3-2-1時程與採樣點規劃 56
3-2-2現場採樣程序 56
3-3分析項目及方法 57
3-3-1水溫 58
3-3-2氫離子濃度指數 59
3-3-3導電度 59
3-3-4總溶解固體 59
3-3-5總有機碳 60
3-3-6溶解性有機碳 60
3-3-7生物可利用有機碳 60
3-3-7-1培養基配製 61
3-3-7-2菌種保存與活化 63
3-3-7-3菌種純種鑑定與特性分析 64
3-3-7-4 AOC器皿之清潔方式 66
3-3-7-5生長曲線及產率之求取 67
3-3-7-6水樣分析方式 67
3-3-8氨氮 70
3-3-9硝酸鹽氮 70
3-3-10 UV254 70
3-3-11 SUVA 71
3-4菌種鑑定 71
3-5建立預測模式 72
3-5-1 Autonet6.03軟體簡介 72
3-5-2 基本參數設定 73
第四章結果與討論 75
4-1原水中有機物性質分析 75
4-1-1水質分類 75
4-1-2 原水中有機物性質比較 79
4-2 淨水處理程序 85
4-2-1 前氧化處理單元 85
4-2-2 混凝沉澱處理單元 88
4-2-3 結晶軟化處理單元 90
4-2-4 過濾處理單元 92
4-2-5 後臭氧&生物活性碳處理單元 94
4-2-6 清水消毒處理單元 96
4-2-7 淨水場各處理單元AOC 去除效率評估 98
4-3配水管網AOC 之變化 100
4-4淨水場AOC 預測模式 102
4-4-1 淨水處理程序之預測方程式 102
4-4-1-1 GW淨水場 102
4-4-1-2 CW淨水場 104
4-4-2 配水管網之預測方程式 105
4-4-2-1 GW淨水場 105
4-4-2-2 CW淨水場 106
4-4-3 整體水質預測方程式 107
4-4-3-1GW淨水場 107
4-4-3-2 CW淨水場 108
4-4-4預測模式驗證 109
4-4-5預測模式結果受水質參數影響評估 109
4-4-6 AOC預測模式外部驗證 111
第五章 結論與建議 112
5-1 結論 112
5-2 建議 114
參考文獻 116
學位考試口試委員意見修正書 129

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