蔣本基臺灣大學：環境工程學研究所梁仲暉Liang, Chung-HueiChung-HueiLiang2007-11-292018-06-282007-11-292018-06-282006http://ntur.lib.ntu.edu.tw//handle/246246/62649本論文之重點在於發展非穩定態數學模式，以數值方法定量發生於生物活性碳的吸附以及生物降解兩種機制，所去除有機物之質量與時間變化。在實驗設計上，以連續式管柱試驗來評量生物活性碳管柱中吸附與生物降解之處理效能，並提供模式所需之輸入參數，以做為模式驗證與模擬之用。在模式應用上，本論文嘗試改變部分管柱之操作參數，例如填充介質之粒徑、管柱表面流速等，以模擬吸附與生物降解機制對於溶解性有機物處理效能之影響。 實驗結果顯示，在管柱發生貫穿之前，對於高吸附性但低生物降解性的目標污染物對羥基苯甲酸p-hydroxybenzoic acid，去除的機制以吸附為主；而生物降解主要去除其臭氧副產物。另一方面，增加空床接觸時間可使吸附平衡更加完全，進而提升吸附的處理效果；同時，提高空床接觸時間亦會提高吸附對生物降解之比例，此一現象進一步驗證在高空床接觸時間下，吸附乃為主要的去除機制。利用生物活性定量的方法，除可確認生物降解為去除臭氧中間副產物之主要機制之外，還可進一步做為吸附與生物降解定量之用。 本模式在適當的質傳係數修正之後，其預測之結果可與實驗結果有良好的一致性；而此一質傳係數與Stanton number之間具有特定之正比例關係。在敏感度分析結果發現，Freundlich等溫吸附線之係數、Monod方程式中的最大反應速率、以及擴散係數等，為模式中影響最為顯著的參數，此一訊息可進一步提供在實際操作上，改善處理效能之依據。降低填充介質顆粒之尺寸，對於吸附有顯著的改善，進而可提升整體的處理效能；在此同時降低Damköhler number可使更多基質穿過生物膜到達活性碳的表面，進而提高了吸附的比例。This research was focused on developing a non-steady-state numerical model to differentiate the adsorption and biodegradation quantities of a biological activated carbon (BAC) column. The mechanisms considered in this model included adsorption, biodegradation, convection and diffusion. The performance of adsorption and biodegradation on the BAC column was studied using continuous columns tests. Simulations were performed to evaluate the effects of some parameters such as packing media size and superficial velocity on adsorption and biodegradation performances for the removal of dissolved organic matter from water. The experimental results show that before breakthrough, adsorption should be the prevailing mechanism for removal the p-hydroxybenzoic acid, and biodegradation should be responsible for reducing the ozonation intermediates. EBCT could influence the performance of both adsorption and biodegradation in extent. Increasing EBCTs could make the equilibrium more complete for adsorption, thereby improving the performance. The ratio of adsorption to biodegradation on the BAC column increased as EBCT increased, and this implied that adsorption was dominant in an equilibrium condition. Also, the bioactivity approach of BAC can not only reveal the importance of biodegradation mechanisms for the intermediates of ozonation, but also quantify the extent of the adsorption or biodegradation reaction occurring on BAC. This model achieves a good approximation of the experimental data by adjusting the liquid-film mass transfer coefficients. Liquid-film mass transfer coefficient has a certain correlation to the Stanton number. The Freundlich isotherm exponential term and the maximum specific substrate utilization rate from Monod kinetics and the diffusion coefficient are the most sensitive variables, which provides important information to control the performance of the BAC. Decreasing particle size can improve the overall removal efficiency, especially for adsorption rather than biodegradation. Meanwhile, a lower Damköhler number permits more substrate passes the biofilm to the adsorbent and makes the adsorption ratio increase.Chapter I Introduction 1 Chapter II Literature Review 3 2-1 Effects of Operational Conditions on BAC 4 2-1-1 Effects of hydrodynamic conditions 4 2-1-2 Types of filler media 5 2-1-3 Effects of growth condition on mass transfer 6 2-2 Effects of Ozonation on BAC 7 2-2-1 The generation of ozonation by-products 7 2-2-2 Effects on adsorption 8 2-2-3 Effects on biodegradation 8 2-3 The biofilm on BAC Granules 10 2-3-1 Density and structure 10 2-3-2 Factors that affect the biofilm 12 2-3-3 Activity 12 2-3-4 Microbial species 13 2-4 Detachment of the Biofilm 15 2-4-1 Mechanisms 15 2-4-2 Sloughing of the biofilm 16 2-4-3 Effects of the biofilm morphology 17 2-5 Approaches of Modeling BAC 18 2-5-1 Empirical formulas 19 2-5-2 Biofilter model for gas-phase contaminants 22 2-5-3 Steady-state biofilm model with adsorption 23 2-5-4 Plug-flow dynamic biofilm model 24 2-5-5 “CHABROL” model 25 2-5-6 Dynamic BAC model in a complete mixing tank 26 Chapter III Materials and Method 28 3-1 Overview of Approaches 28 3-2 The Performance of BAC Column Treating Highly and Low Biodegradable Target Compounds 33 3-2-1 Apparatus 33 3-2-2 Media 33 3-2-3 Water samples 33 3-2-4 Analytical methods 34 3-3 Effect of Ozonation on Adsorption and Biodegradation 35 3-3-1 Apparaus 35 3-3-2 Media 35 3-3-3 Water samples 35 3-3-4 Analytical methods 36 3-4 Effect of Hydrodynamic Conditions on Adsorption and Biodegradation of the BAC Column 37 3-4-1 Apparatus 37 3-4-2 Media 37 3-4-3 Water Samples 37 3-4-4 Adsorption determination 37 3-4-5 Analytical methods 38 3-5 Modeling the Adsorption and Biodegradation Capacities on BAC 39 3-5-1 System definition and basic assumptions 39 3-5-2 Model development 42 3-5-3 Data analysis 47 Chapter IV Results and Discussion 50 4-1 Performance of Adsorption and Biodegradation 50 4-1-1 Influences of the biodegradability 50 4-1-2 Influences of ozonation pretreatment 53 4-1-3 Influences of EBCT 57 4-1-4 Assessment of adsorption and biodegradation for the control of DBPs 61 4-1-5 Summary 64 4-2 Evaluation of the Microbes Growth and Bioactivity 65 4-2-1 Influences of the biodegradability 65 4-2-2 Influences of ozonation pretreatment 68 4-2-3 Influences of EBCT 70 4-2-4 Summary 72 4-3 Estimation of of Adsorption and Biodegradation by Experiments 74 4-3-1 Estimated by the density of bacteria 74 4-3-2 Estimated by the activities of bacteria 79 4-3-3 Estimated by adsorption capacities 82 4-3-4 Summary 90 4-4 Model Calibration, Sensitivity Analysis, and Validation 91 4-4-1 Calibration 91 4-4-2 Sensitivity analysis 93 4-4-3 Validation 97 4-4-4 Summary 105 4-5 Model Simulations and Applications 106 4-5-1 Influences of the biofilm thickness 106 4-5-2 Effects of specific biodegradation rate 108 4-5-3 Effects of diffusivity 110 4-5-4 Effects of adsorption/biodegradation ratio 112 4-5-5 Effects of EBCT 115 4-5-6 Optimization for the ozonation conversion ratio 118 4-5-7 Effects of the particle size 121 4-5-8 Summary 124 Chapter V Conclusions and Future Works 126 5-1 Conclusions 126 5-2 Recommendation 127 References 128 Appendix 138 Table 2-1. The effects of EBCT on biodegradation and adsorption 5 Table 2-2. Literatures for biofilm density and structure 11 Table 2-3. Microorganisms detected in GAC columns w/o ozonation 15 Table 2-4. Some of the representative BAC models 21 Table 3-1. Specifications of apparatus or instruments 30 Table 3-2. Experimental design 32 Table 3-3. Operation conditions and parameters used for model simulation. 49 Table 4-1-1. Percentage of the p-hydroxybenzoic acid in the column effluent DOC of the ozonation experiment. (Column I) 55 Table 4-2-1. Difference of the bacteria density on unit volume media between the top and middle of the columns 68 Table 4-3-1. Difference of the accumulative acetate removal between adsorption and biodegradation mechanisms 75 Table 4-3-2. Difference of the accumulative p-hydroxybenzoic acid removed by unit volume media between adsorption and biodegradation mechanisms 76 Table 4-3-3. Calculation of the amount of acetate reduced by biodegradation or adsorption in BAC 77 Table 4-3-4. Calculation of the amount of p-hydroxybenzoic acid reduced by biodegradation or adsorption in BAC 78 Table 4-3-5. Estimation of the amount of p-hydroxybenzoic acid reduced by biodegradation or adsorption in BAC (unozonated experiment) 79 Table 4-3-6. Estimation of the amount of DOC reduced by biodegradation or adsorption in BAC in the ozonation experiment 81 Table 4-3-7. Estimation of the amount of p-hydroxybenzoic acid reduced by biodegradation or adsorption in BAC in the ozonation experiment 81 Table 4-3-8. Mass balance of organic carbon adsorbed on GAC 83 Table 4-4-1. The average fit value for kbf value in the glass bead case. 92 Table 4-4-2. The sensitivity analysis of the model input parameters. 94 Figure 3-1. Schematic flow chart of the thesis. 28 Figure 3-2. Conceptual basis of biological activated carbon coordinate system. 39 Figure 3-3. The conceptual diagram of the developed model. 41 Figure 4-1-1. The breakthrough curve of (a) GAC, (b) glass bead, and (c) BAC columns using acetate as substrate. 51 Figure 4-1-2. The breakthrough curves of (a) GAC, (b) glass bead, and (c) BAC columns in the unozonated experiment.( p-hydroxybenzoic acid = 4.5 mg/L) 52 Figure 4-1-3. The DOC breakthrough curves of (a) GAC, (b) glass bead, and (c) BAC columns in the ozonation experiment. (DOC0 = 2.5 mg/L) 54 Figure 4-1-4. Cumulative p-hydroxybenzoic acid removal by adsorption and biodegradation in the unozonated experiment. 55 Figure 4-1-5. Cumulative (a) DOC, (b) p-hydroxybenzoic acid removal by adsorption and biodegradation in the ozonation experiment. 56 Figure 4-1-6. Breakthrough curves of four OBPs of the GAC column. (a) formaldehyde, (b) glyoxal, (c) glyoxalic acid and (d) ketomalonic acid. 58 Figure 4-1-7. Average effluent concentration (solid symbols) and removal efficiency (empty symbols) of the glass bead column. 59 Figure 4-1-8. Average effluent concentration (solid symbols) and removal efficiency (empty symbols) of the BAC column. 60 Figure 4-1-9. Influence of dissolved matrix for the adsorption of DCAA. 62 Figure 4-1-10. Influence of dissolved matrix for the adsorption of TCAA. 62 Figure 4-1-11. Influence of dissolved matrix for the biodegradation of DCAA. 63 Figure 4-1-12. Influence of dissolved matrix for the biodegradation of TCAA. 63 Figure 4-2-1. The bacteria density of (a) GAC, (b) glass bead, and (c) BAC columns using acetate as substrate. 66 Figure 4-2-2. The bacteria density of (a) GAC, (b) glass bead, and (c) BAC columns using p-hydroxybenzoic acid as substrate. 67 Figure 4-2-3. The bacterial densities and the BRP of (a) GAC, (b) glass bead, and (c) BAC columns in the unozonated experiment. 69 Figure 4-2-4. The bacterial densities and the BRP of (a) GAC, (b) glass bead, and (c) BAC columns in the ozonation experiment. 70 Figure 4-2-5. The (a) bacterial densities and (b) specific BRP profiles of the glass bead column under various EBCTs (day=37). 71 Figure 4-3-1. Systematic approach to differentiate adsorption and biodegradation capacities of BAC. 80 Figure 4-3-2. The result of adsorption isotherm test. 82 Figure 4-3-3. Organic carbon adsorbed on the GAC granules under various EBCTs. (a) 2.5, (b) 10, and (c) 25 min. 84 Figure 4-3-4. Organic carbon adsorbed on the BAC granules under various EBCTs. (a) 2.5, (b) 10, and (c) 25 min. 86 Figure 4-3-5. Organic carbon removal through adsorption and biodegradation in the BAC column under various EBCTs. (a) 2.5, (b) 10, and (c) 25 min. 88 Figure 4-3-6. Comparison of cumulative biodegradation capacities estimated by regression and by adsorption capacity method. EBCT= (a) 2.5, (b) 10, and (c) 25 min. 89 Figure 4-4-1. Correlation between the liquid-film mass transfer coefficient (kbf) and the Stanton number (NSt). 93 Figure 4-4-2. Sensitivity analysis for the input parameter NF. 95 Figure 4-4-3. Sensitivity analysis for the input parameter kf. 95 Figure 4-4-4. Sensitivity analysis for the input parameter Df. 96 Figure 4-4-5. Sensitivity analysis for the input parameter Y. 96 Figure 4-4-6. Sensitivity analysis for the input parameter Xf. 96 Figure 4-4-7. Organic carbon adsorbed on the BAC granules under EBCT = 10 min. 98 Figure 4-4-8. Simulation effluent curves and the experimental data of the substrate concentration of the BAC column. 99 Figure 4-4-9. Cumulative removal of DOC by adsorption and biodegradation, (a) EBCT=2.5, (b) EBCT=10 min. 100 Figure 4-4-10. Simulation effluent curves and the experimental data of the BAC column. 102 Figure 4-4-11. Cumulative removal of DOC by adsorption and biodegradation, (a) substrate A, (b) substrate B. 103 Figure 4-4-12. Simulation for the removal of alachlor. 104 Figure 4-5-1. The bacterial densities and specific BRP profiles of the BAC column. (EBCT=10 min, sampled on the top of the column). 107 Figure 4-5-2. Biodegradation and adsorption rates as functions of the biofilm thickness. 108 Figure 4-5-3. Simulation removal efficiencies of adsorption and biodegradation under various maximum specific substrate utilization rates in the biofilm (kf). 109 Figure 4-5-4. Simulation effluents and the ratio of biodegradation to total removal efficiency under various maximum specific substrate utilization rates in the biofilm (kf). 110 Figure 4-5-5. Simulation removal efficiencies of adsorption and biodegradation under various diffusivities in the biofilm (Df). 111 Figure 4-5-6. Simulation effluents and the ratio of biodegradation to total removal efficiency under various diffusivities in the biofilm (Df). 112 Figure 4-5-7. Simulation removal efficiencies of various combinations of substrate A and B, (a) substrate A, (b) substrate B. 113 Figure 4-5-8. Simulated effluents and the ratio of biodegradation to total removal efficiency of various combinations of substrate A and B. 114 Figure 4-5-9. Simulation removal efficiencies of various EBCTs, (a) substrate A, (b) substrate B. 116 Figure 4-5-10. Simulated effluents and the ratio of biodegradation to total removal efficiency of various EBCTs. 117 Figure 4-5-11. Simulated adsorption and biodegradation ratios under various ozonation converted ratios (target compound A: highly adsorptable and low biodegradable). 119 Figure 4-5-12. Simulated removal efficiency and bed life extended ratio under various ozonation converted ratios (target compound A: highly adsorptable and low biodegradable). 119 Figure 4-5-13. Simulated adsorption and biodegradation ratios under various ozonation converted ratios (target compound A: low adsorptable and low biodegradable). 120 Figure 4-5-14. Simulated removal efficiency and bed life extended ratio under various ozonation converted ratios (target compound A: low adsorptable and low biodegradable). 121 Figure 4-5-15. Simulations of various particle diameters for the removal of p-hydroxybenzoic acid. (a) and (b) v = 5 cm/min; (c) and (d) v = 20 cm/min. 122 Figure 4-5-16. Simulations of various particle diameters for the removal of ozonation intermediates. (a) and (b) v = 5 cm/min; (c) and (d) v = 20 cm/min. 123810392 bytesapplication/pdfen-US吸附生物降解生物活性碳粒狀活性碳數值模式AdsorptionBiodegradationBiological activated carbon (BAC)Granular activated carbon (GAC)Numerical modelthesishttp://ntur.lib.ntu.edu.tw/bitstream/246246/62649/1/ntu-95-D86541002-1.pdf