基于三维荧光指纹的污水处理系统有机物迁移转化特性表征

目前我国污水处理厂普遍存在运行管理粗放低效的问题，对工艺状态进行全面快速的在线监测，是提升污水处理效率和稳定性的重要策略。本项目提出以三维荧光光谱为工具，通过系统表征溶解性有机物的迁移转化特性，达到指示工艺状态的目的，从而为污水厂在线监测提供新的思路。项目通过对三维荧光图谱进行拓展解析，重点考察荧光指纹对有机物迁移转化过程中亲疏水性、酸碱性、分子量、可生化性、平均氧化态等性质变化的指示作用。首先通过间歇试验对有机物性质进行分级表征，揭示荧光指纹随有机物性质变化的基本规律，利用荧光理论论证其合理性；其次建立荧光指纹与工艺过程的联系，探讨荧光指纹的指示作用对于不同工艺过程的特殊性与普遍性；最后以典型污水厂为案例，长期跟踪监测工艺动态，探索荧光指纹与有机物性质之间的统计学相关关系，优选具有灵敏可靠响应的荧光指纹信息。本项目旨在为基于三维荧光光谱的污水厂在线监测技术开发与功能拓展提供理论支持。

Higher treatment efficiency and smarter operational management are urgently required in China’s wastewater treatment plants. Rapid, sensitive, and comprehensive online monitoring of the whole process state is of great importane in this regard. Three-dimensional excitation-emission matrix (EEM) fluorescence spectroscopy is suggested as a novel online monitoring tool for wastewater treatment systems, giving fingerprints of dissolved organic matter (DOM) which is closely related to the process state. The present project aims to establish the relationship between EEM fingerprints and DOM behaviors in wastewater treatment systems, so that EEM fingerprints could serve as an indicator of the process state. The DOM properties of particular interest, that could be closely involved in the migration and transformation of DOM during the process of wastewater treatment, include hydrophobicity, acidity, molecular weight, biodegradability, mean oxidation state, etc. The dependency of EEM fingerprints on DOM properties will be systematically investigated by characterizing DOM fractions of varied properties, with the mechanisms to be elucidated using fluorescence theories. EEM fingerprints will then be related to different wastewater treatment processes, to identify their specific or common roles in indicating DOM behaviors. Finally, a case study will be performed based on a practical wastewater treatment plant, to examine the indicative role of EEM fingerprints during long-term operation with dynamic fluctuations. Statistical relationship between EEM fingerprints and DOM properties will be explored, to identify the EEM parameters with good reliability and sensitivity that could be feasible for online monitoring. This project could promisingly provide theoretical and experimental foundations for the development of EEM-based online monitoring strategies and techniques for wastewater treatment systems.