【作者】 孙世昌；

【导师】 孙德智；

【作者基本信息】 北京林业大学 ， 生态环境工程， 2014， 博士

【摘要】 随着城市水使用量及污水处理率的不断提高,城市污水处理厂N20的排放量将会不断增大。我国城市污水处理厂N20的研究不仅基础数据缺乏,且没有任何减排方法。本文给出了我国城市污水处理典型工艺N20的排放特征,研究了影响典型工艺N20排放的主要因素,构建出了N20排放量的计算模型,预测了未来10年我国城市污水处理厂N20的排放总量,并分别从国家和城市污水处理厂层面提出了城市污水处理N20的减排策略。本文首先采用了静态平衡箱法、气袋法和静态顶空法对典型工艺城市污水处理厂N20的释放强度及水中溶解态N20浓度进行了监测。研究结果表明,受硝化过程DO浓度过低以及反硝化过程DO存在的影响,好氧和缺氧处理单元(阶段)都会产生N20,它们都是控制各工艺N20产生的关键点位；四种典型工艺好氧处理单元(阶段)N20的吨水释放量分别占A2/O工艺的99.14%、A/O工艺的98.6%、氧化沟工艺的86.7%和SBR工艺的99.9%,是各工艺控制N20排放的关键点位。本文分别设计了A/O、氧化沟和SBR工艺N20排放的中试试验,通过调节各工艺主要运行参数,研究DO浓度和反硝化过程对进水碳源的利用率的改变对于典型工艺N20产生与排放的影响。研究结果表明,A/O工艺采用合适的好氧池曝气速率、氧化沟工艺采用先反硝化后硝化的运行模式并提高曝气转刷的转动速率、SBR工艺采用先进水搅拌后曝气的运行模式并提高曝气速率,能够有效地控制各工艺硝化过程和反硝化过程的DO浓度并提高反硝化过程对进水碳源的利用率,有利于减少典型工艺N20的产生与排放。本文利用基于遗传算法优化的BP人工神经网络建立了N20排放量的预测模型,实现了对2014年至2023年城市污水处理厂N20排放总量的预测。研究结果表明,所建立的GA-BP模型对于污水处理厂N20排放量的预测值与实测值之间的相关系数分别为0.91、0.95、0.98和0.99,可以实现对我国污水处理厂N20排放量的准确预测。预测结果显示,我国污水处理厂N20的排放总量将会从2014年的(1.32～4.67)×104吨增加到2023年的(2.17～7.64)×104吨。本文根据我国城市污水处理典型工艺N20排放特征及影响因素的研究结果,分别从国家和城市污水处理厂层面提出了城市污水处理典型工艺N20减排技术策略。国家控制城市污水处理厂N20排放的技术策略包括选取氧化沟工艺作为削减污水处理厂N2O排放的最优工艺以及推荐同步硝化反硝化、短程硝化反硝化、厌氧氨氧化等新工艺处理城市污水等；城市污水处理厂N20减排的技术策略包括合理地提高硝化过程的DO浓度、提高缺氧反硝化工段对进水碳源的利用率等。更多还原

【Abstract】 As the increase of urban water usage and wastewater treatment efficiency, the emission of N2O from wastewater treatment plants (WWTPs) will get an increase gradually. By now, there is a great defect not only in the basic data but also in N2O reduction method on N2O emission from WWTPs in China. This research has given out the emission characteristics of N2O from urban WWTPs using typical treatment processes, studied the influencing factors on N2O emission from each process, constructed the predicting models of N2O emission from typical processes, forecasted the emission of N2O from all the urban WWTPs in the future10years in China, and proposed the reduction strategies of N2O emission from urban WWTPs, which is suitable for our national conditions. These works can offer a certain data reference for constituting the reduction policy and environmental management for N2O emission from WWTPs in China, and supply some technical support for the diplomatic negotiations and the implementation of international conventions.N2O emission from the non-aerated and aerated units and the dissolved N2O concentration in the typical treatment processes were monitored using the static chamber technique, the gas bag technique and the static headspace technique respectively. Results showed that, for the effect of insufficient O2supply during nitrification and O2-inhibition during denitrification, N2O could be produced in both the oxic and the anoxic treatment units (periods), where could be determined as the main control points for N2O production. Because the N2O dissolved in the oxic treatment units (periods) would be stripped out to the atmosphere through aeration in the four typical wastewater treatment processes, the emission of N2O from the A2/0-oxic tank, the A/O-oxic tank, the oxidation ditch tank and the SBR-feeding and aeration period accounted for99.14%of A2/O process,98.6%of A/O process,86.7%of the OD process and99.9%of the SBR process, which showed as the main control points for N2O emission. Pilot experiments were designed to study the influence of DO and the utilization efficiency of carbon source in influent during denitrification on N2O emission from A/O, OD and SBR processes through adjusting some critical operating parameters. Results showed that, a proper adjustment of the aeration rate in A/O process, a pre-denitrificaiton operating mode with a higher aeration rate in the OD and SBR processes could lead to a effective control of DO concentration during nitrification and denitrificaiton and enhacing the utilization of influent carbon during denitrification, which were favorable to reduce the production and emission of N2O from different processes.A back propogation (BP) artificial neural network basing on the optimization by genetic algorithm was established for the prediction of N2O emission from WWTPs and the emission of N2O from urban WWTPs in China in the future10years (from2014to2023) was predicted. The results showed that, the correlation coefficient (r) between the predicted values got by the GA-BP models and the monitored values of N2O emission from WWTPs were0.91,0.95,0.98and0.99, which indicated that the models constructed in our work could realize an accurate prediction of N2O emission from urban WWTPs in China. The forecasting results showed that, the total emission of N2O would increased from (1.32～4.67)×104ton in2014to that of (2.17～7.64)×104ton in2023as the continuous increase of China’s urban sewage treatment.According to the research results of N2O emission characteristics and influencing factors in typical urban wastewater treatment processes, technical strategies suitable for our national conditions were proposed to reduce N2O emission from both national and urban WWTPs’aspects. The national technical strategy controlling N2O emission included selecting the OD process as the optimal treatment process and recommending some newer technologies for wastewater treatment, et al. The WWTPs’included raising the DO concentration during nitrification properly and enhancing the utilization efficiency of carbon source in influent during denitrification, et al.更多还原