建立及模擬地下水中含氯碳氫化合物之生物性傳輸模式

Abstract

含氯有機溶劑為重要的工業用溶劑，因為它已被證實為致癌或可能致癌的 物質，所以工廠若處置或排放不當，地下水將受含氯碳氫化合物的污染， 並可能經由地下水的流動而回到人類的生活圈，使人體或生物的健康受到 威脅。含氯碳氫化合物在自然環境下轉換甚慢，必須靠生物性的反應才得 以去除，因此，必須建立含氯碳氫化合物之生物性傳輸模式，以模擬、預 測、或分析它在地下水中的流動分佈情形。在甲烷化的生物環境條件下， 添加提供微生物碳源及能源的初級基質後，因二級利用的機制，微生物會 使含氯量較高的碳氫化合物，進行還原性脫氯反應，變成一系列含氯量較 低的衍生物，而這些衍生物可能亦具毒害，模式建立時必須一併考慮。因 此，本研究分別將Michaelis -Menten和Monod生物動力反應式，代入含生 物反應項的吸附型地下水傳輸方程式，建立BIOMM和BIOMO傳輸數學模式， BIOMM模式中的主要變數為初級基質及四種還原性連鎖脫氯反應的含氯碳 氫化合物，BIOMO模式中則多考慮了微生物濃度的變化。建立的兩個數學 模式，皆由一組非線性的偏微分方程式所構成，且模式中的變數為耦合， 其解析解無法求得。因此，本研究利用Crank- Nicolson或upwind有限差 分法建立數值模式，再配合預估-修正法及 Thomas法進行疊代求解。經參 數微調後的模擬結果，與蒐集文獻中的實驗數據做比較，在濃度分佈的趨 勢上有不錯的一致性，並由敏感度分析的結果得知，基質消耗最大速率 Rmax、最大比生長速率μm、衰退常數 b、生長轉換率Y、及流速V為重要 的模擬參數。本研究的研究成果，可當未來污染物排放管制或地下水復育 、整治策略的參考工具。 Chlorinated organic solvents are important industrial solvents. They are known or suspected carcinogens. The ground- water was contaminated by chlorinated hydrocarbons due to wastewater from factories. Chlorinated organic contaminants may adverse health of human or creatures. They are transformed slowly in natural environments and must be removed by biological reactions. Therefore, this proposed research develop a biological transport model. Under methanogenic conditions and the process of secondary utilization, the microorganisms supported primary substrate as carbon and energy sources will biotransform chlorinated hydro- carbons into several intermediate compounds through reductive dechlorination. This research introduces Michaelis-Menten and Monod equations into biological reaction term respectively to develop BIOMM and BIOMO model. The variables of BIOMM model are primary and secondary substrate. BIOMO model considers microorganism concentration additionally. The governing equations of the present both models are consist of nonlinear partial differential equations and the variables of models are coupled, so their analytical solutions can't be solved. The Crank-Nicolson or upwind scheme of finite difference approximations are employed to develop numerical models which can be solved by predictor-corrector method and Thomas algorithm iteratively. Simulation results with parameter calibration compare with experimental data of literatures that get good consistency on tendency of concentration distribution. The results of sensitivity analysis conclude that maximum rate of substrate depletion, maximum specific growth rate, decay constant, growth yield, and flow velocity are important simulation parameters. The developed models may provide a useful tool in selecting the in-situ bioremediation strategies for the groundwater contaminants.