基于有机物荧光指纹响应的膜污染预警机制及效能研究

Membrane fouling is a serious challenge to microfiltration and ultrafiltration processes for wastewater treatment and reclamation. Early warning of membrane fouling potential of mixed liquor organic matter is critical to the efficient control of fouling. Fluorescence spectroscopy is suggested as a promising tool for the rapid and sensitive early warning of fouling potential, with the real-time monitored fluorescence fingerprints quite informative for predicting the fouling rate, fouling evolution tendency, and foulant layer properties. The present project aims to establish the relationships between fluorescence fingerprints and fouling potential, and explore the underlying mechanisms to support the fluorescence-based early warning of membrane fouling. Statistical analyses will be systematically conducted to assess the qualitative or semi-quantitative relationships between detailed fluorescence properties and fouling potential indices. To elucidate the fouling-responsive feature of fluorescence fingerprints, the effect of organic matter properties on the the fluorescence excitation-emission process will be analyzed from the perspectives of fluorophore energy and molecular structure. On the basis of the relationships and mechanisms, a strategy for fluorescence-based early warning of membrane fouling will then be proposed. Finally, the effectiveness of the early warning and the early warning-aided fouling control will be examined in lab-scale systems. This project could promisingly provide theoretical and experimental foundations for the development of fluorescence-based technologies for early warning and efficient control of membrane fouling.

膜污染是污水处理微/超滤工艺面临的巨大挑战。混合液有机物膜污染潜势的及时预警，对膜污染的有效预防意义重大。荧光光谱法由于能快速灵敏地提供极其丰富的有机物指纹信息，在膜污染潜势的实时监测与快速预警方面潜力巨大。本项目提出利用混合液有机物荧光指纹信息，预判膜污染的速率、分阶段发展倾向和污染层属性，为膜污染的预警和防控提供新的思路。本项目首先通过细化膜污染潜势指标、拓展挖掘荧光指纹信息、运用多层次的统计学分析方法，系统建立荧光特性与膜污染潜势之间的规律性联系，识别灵敏可靠的定性或半定量荧光指标；进而以荧光指标-有机物性质-膜污染潜势的逐级联系为线索，通过对荧光能量过程和分子结构的深入解析，揭示荧光指纹对膜污染潜势的内在响应机制；以此为科学依据，提出基于荧光指标的预警策略并在小试体系中加以验证，并进一步评测预警指导下的膜污染防控效果。本项目旨在为基于荧光指纹响应的膜污染预警技术开发提供理论支持。

膜污染是污水处理膜过滤工艺面临的巨大挑战。本项目的目标是利用有机物的荧光指纹信息，预判膜污染的发展趋势和分阶段特征，从而为膜污染的预警和防控提供新的思路。首先发掘了荧光光谱指标与膜污染细化属性之间的统计学规律，发现污泥混合液中有机物的总体荧光强度与光谱能量特征与膜通量衰减趋势有关，出水荧光性质能进一步反映多糖、蛋白和腐殖质在初期膜孔吸附/堵塞和后续凝胶/滤饼层中的贡献。进而解析了荧光-有机物性质-膜污染潜势之间的内在关联机制，发现荧光密度、波长区域参数和荧光能量参数与疏水程度显著相关，荧光的激发和发射效率与分子量显著相关，O=C-(R N O)作为不饱和键、荧光团取代基和硬度离子络合基团，能够同时影响荧光性质和膜污染潜势。最后提出基于荧光指纹的膜污染预警技术策略，在连续运行的小试膜生物反应器中进行初步验证，根据在线荧光信号对膜吹扫曝气强度进行高低反馈式控制，发现可在较低曝气量的能耗代价下有效控制膜污染。本项目的研究结果可为基于荧光指纹响应的膜污染预警技术开发提供一定的理论依据。

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