臺灣博碩士論文加值系統

因金門太湖原水中高溶解性有機碳(DOC)、低濁度(Turbidity)與低鹼度(Alkalinity)的特性，水中有機物質不易經由傳統處理程序去除。然而，根據消毒劑/消毒副產物規則(D/DBP Rule)，導入加強混凝程序後，其三鹵甲烷生成潛能仍高於水質標準。因此，本研究將利用不同條件的前臭氧結合混凝來去除太湖原水之天然有機物，以及降低其三鹵甲烷生成潛能(THMFP)，並針對天然有機物(NOMs)的特性，將原水分成親水性和疏水性進行實驗；探討前臭氧的劑量和pH值對於加強混凝過程中有機物去除效能的影響，並建立天然水中溶解性有機碳(DOC)的混凝去除預測模式。
研究結果顯示，前臭氧劑量和pH值均會影響混凝效果。當操作條件為pH 9且前臭氧劑量為0.45 mg O3/mg DOC時為最佳操作條件，其三鹵甲烷生成潛勢減少約60%。此外，DAX-8樹脂分離實驗結果顯示，疏水性與親水性有機物之三鹵甲烷比生成潛勢(Specific THMFP)分別為57.3與98.7 ugTHMFP/mgDOC。因此，親水性有機物為水中三鹵甲烷的主要前驅物質。然而，導入前臭氧程入有助於疏水性有機物混凝的去除，但是對於親水性有機物影響不明顯。
在建立混凝去除預測模式之研究中，利用競爭和非競爭吸附模式，考量天然有機物中親、疏水性的差異，並探討其競爭性；藉由原水SUVA值、溶解性有機碳與添加混凝劑量的發現，結合親疏水性非競爭性吸附模式有較合理的結果，並且能獲得一個準確度高的預測模式。

Due to the characteristics of high concentrations of dissolved organic carbon (DOC), low turbidity and low alkalinity in the Tai-Lake source water in Kinmen, the DOC is difficult to remove by conventional treatment processes. However, the introduction of the enhanced coagulation based on disinfectant/disinfection by-product Rule (D/DBP Rule) again would result in the formation of high trihalomethanes beyond the drinking water quality standard (80μg/L) in Taiwan. As a result, the purpose of this study was intended to evaluate the effect of pre-ozonation on the performance of coagulation and formation of trihalomethanes, to separate the hydrophobic and hydrophilic fractions of natural organic matters (NOMs), and to develop at DOC removal model in enhanced coagulation.
The results of this investigation reveal that the ozone doses and pH levels would influence the coagulation performance significantly. The pH levels and ozone doses were held at 9 and 0.45 mgO3/mgDOC, respectively. The removal efficiency of THMFP was about 60%. In addition, the results of the DAX-8 resin separation process indicate that the specific THMFP for hydrophobic and hydrophilic organics are 57.3 and 98.7 ugTHMFP/mgDOC, respectively. This suggests that hydrophilic organics are significant precursors of THMs. The introduction of pre-ozonation have a positive effect on hydrophobic organic removal, but an insignificant on hydrophilic organics.
In the comparison of competitive and non-competitive adsorption models for the hydrophilic and hydrophobic organics, the non-competitive adsorption models could successfully predict the hydrophilic and hydrophobic DOCs removal in the enhanced coagulation process.

誌謝 Ⅰ
中文摘要 Ⅲ
ABSTRACT Ⅴ
CONTENTS Ⅶ
LIST OF FIGURES Ⅹ
LIST OF TABLES ⅪⅤ
CHAPTER 1 INTRODUCTION 1-1
1.1 BACKGROUND 1-1
1.2 OBJECTIVES 1-2
1.3 MAJOR TASKS 1-3
CHAPTER 2 LITERATURE REVIEW 2-1
2.1 CHARACTERIZATION OF ORGANIC MATTERS IN NATURAL WATER 2-1
2.1.1 Surrogate parameters of NOMs 2-4
2.1.2 Separating organic matters by XAD resin 2-4
2.2 COAGULATION 2-6
2.2.1 Enhanced coagulation 2-6
2.2.2 Mechanism of coagulation 2-10
2.3 OZONATION 2-15
2.3.1 Mechanism of ozone 2-15
2.3.2 Effect of pre-ozonation on coagulation 2-17
2.4 PREDICTIVE MODEL OF DOC REMOVAL 2-21
2.4.1 The langmuir-based model 2-21
2.4.2 Modeling DOC removal by Kastl 2-23
CHAPTER 3 MATERIALS AND METHODS 3-1
3.1 RESEARCH FLOWCHART 3-1
3.2 METHODS 3-2
3.2.1 Experimental design 3-2
3.2.2 Unit process 3-7
3.2.3 Analytical method for traditional physical and chemical properties 3-14
3.2.4 Analytical method for THMs 3-23
3.2.5 FTIR analysis 3-26
3.3 MATERIALS 3-27
3.3.1 Apparatus 3-27
3.3.2 Chemicals 3-29
CHAPTER 4 RESULTS AND DISCUSSIONS 4-1
4.1 PRELIMINARY EXPERIMENT 4-1
4.1.1 Basic water quality 4-1
4.1.2 Isolated NOM components 4-1
4.1.3 Effects of ozone treatment on raw water 4-3
4.1.4 Background information analyses 4-8
4.2 PERFORMANCE EVALUATION OF PRE-OZONATION/COAGULATION PROCESSES 4-11
4.2.1 Turbidity removal 4-11
4.2.2 Nature organic matters (NOMs) removal 4-16
4.2.3 Determination of the optimum pre-ozonation/coagulation dosage 4-27
4.3 COMPARISON OF DBPS AND CHARACTER OF NOM 4-30
4.3.1 Effects of hydrophilic/hydrophobic on removal efficiency 4-31
4.3.2 Comparison of THM formation with and without pre-ozonation on coagulation 4-40
4.4 MODEL DEVELOPMENT 4-51
4.4.1 Kastl’s model for predicting DOC removal 4-52
4.4.2 Model development for bi-components 4-62
4.4.3 Development of the model with ozone for predicting DOC removal 4-80
CHAPTER 5 CONCLUSIONS AND RECOMMENDATIONS 5-1
5.1 CONCLUSIONS 5-1
5.2 RECOMMENDATIONS 5-3
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