基于r-K策略菌群选择的硝化动力学模拟及其优化调控

项目名称： 基于r-K策略菌群选择的硝化动力学模拟及其优化调控

项目编号： No.51478410

项目类型： 面上项目

立项/批准年度： 2015

项目学科： 其他

项目作者： 吴军

作者单位： 扬州大学

项目金额： 80万元

中文摘要： 活性污泥系统优化常以提高短期出水水质和降低运行费用为目标，一般不涉及菌群结构,而合理的菌群结构对污水生物处理的长期稳定运行至关重要。分子生物学手段可对活性污泥中的菌群进行鉴定，但是其鉴定结果一般比较多样、具体，不能作为定量化手段。本项目拟通过生态学中的r-K选择理论，来系统地界定活性污泥菌群结构。r、K策略菌具有不同的底物降解特性：在底物浓度较高时，r-策略细菌具有竞争优势，可快速降解底物;底物浓度较低时，K-策略细菌具有优势，能进一步降低污染物浓度。因此通过优化r-K策略菌的结构，可应对冲击负荷和降低出水污染物浓度。而目前又缺乏对活性污泥r-K策略菌竞争机制的研究。本项目拟通过对硝化过程中r-K策略硝化菌（AOB和NOB）选择机制的研究，并建立动力学模型，对硝化系统进行调控，做到在满足硝化效果的同时，又能对硝化菌群结构进行优化。研究成果也可扩展到活性污泥系统中其它菌群结构优化。

中文关键词： 硝化；r-K选择；活性污泥模型；模型预测控制；菌群结构

英文摘要： The optimization of activated sludge process is mainly for improving short term effluent quality and reducing operation cost, without considering the bacterial population structure, which is important for the long term stable operation of activated sludge process. The molecular techniques for biological assays can be used to identify the bacterial species within activated sludge. However the results from these techniques are usually case-specific and cannot be used for qualitative evaluation. In this project, the r-K selection theory from ecology will be used to quantify the activated sludge bacterial population structure systematically. The r and K strategist bacterial have different substrate consumption kinetics. The r- strategist bacterial is strong competitor at high substrate concentration and can be used for rapid substrate reduction. The K- strategist bacterial is favoured at low substrate concentration and can be used for refining the effluent quality. Therefore by optimizing the r-K strategist bacterial population structure, the shocking load management and effluent refinement can be achieved. Currently, it is not clear on the mechanism of r-K strategist bacterial population selection. In this project, the r-K strategist nitrifier (AOB and NOB) selection mechanism during nitrification process will be studied to develop a kinetic model that can be used for the optimization of nitrification process the nitrifier population structures. The results will not be limited to nitrification process and can be used in other activated sludge processes that involve bacterial selections.

英文关键词： Nitrification;r-K selection;activated sludge model;model predictive control;bacterial population structure