采用三维荧光光谱(3D-EEMs)结合主成分分析(PCA)方法, 将城市生活污水的三维荧光光谱分为芳香性蛋白类、 微生物代谢产物、 腐殖酸类和富里酸类物质四个光谱区域, 判断各区域的主成分贡献率, 求取各区域的第一主成分区域值, 建立其与水体化学需氧量(COD)和总氮(TN)关系, 研究了城市生活污水处理效果快速分析评价方法。 研究结果表明, 城市生活污水荧光物质主要由方香性蛋白类物质、 微生物代谢产物、 腐殖酸类和富里酸类物质构成, 各物质的荧光区域分布不同, 在污水处理过程中芳香性蛋白类物质和微生物代谢产物区域光谱变化明显, 腐殖酸类和富里酸类物质区域光谱变化较小； 光谱各区域第一主成分区域值与水体COD及TN之间具有良好相关性, 其中芳香性蛋白类物质光谱第一主成分区域值与COD相关系数达到97.63%, 芳香性蛋白类物质和微生物代谢产物第一主成分区域值之和与腐殖酸类和富里酸类物质第一主成分区域值之和的比值(Yp／Yf)与TN相关系数达到94.02%。 通过将水体三维荧光光谱结合主成分分析方法, 实现了对污水处理各流程的荧光光谱的信息降维提取, 避免了各物质荧光峰的重叠和光谱信息冗余； 通过水体中各物质的光谱特性将光谱分割为不同的物质区域, 求取各区域内光谱第一主成分区域值, 提高了物质识别的准确率, 有效地解决了各物质光谱信息识别问题； 通过利用芳香性蛋白类物质光谱第一主成分区域值和Yp／Yf与常规水质指标COD和TN作相关性分析, 为污水处理监测提供了一种实时有效的监测生活污水水质状况方法, 解决了污水处理流程难以实时准确监测的问题。 因此, 利用三维荧光光谱结合主成分分析方法可对城市生活污水处理过程进行快速判别, 为污水处理过程中水质监测、 工艺优化及处理效果评估提供了一种全新的快速在线监测分析方法。

Three-dimensional fluorescence spectrum (3D-EEMs) and principal component analysis (PCA) were used. The three-dimensional fluorescence spectrum of urban sewage was divided into four spectral regions: aromatic proteins, microbial metabolites, humic acids and fulvic acids. Determine the regional principal component contribution rate of the lambda λ. Calculate the value of the first principal component area of each area, to establish it with water chemical oxygen demand (COD) and total nitrogen (TN), studies the urban sewage treatment effect rapid analysis and evaluation method.The results show that the urban sewage fluorescent material is mainly composed of aromaticity protein material, microbial metabolites, humic acid and fulvic acid material, regional fluorescent distribution is different, the material in the process of sewage treatment aromaticity protein material area spectral changes obviously, and the microorganism metabolites humic acid and fulvic acid material area spectral changes smaller, Spectral regions the value of the first principal component area and water body has a good correlation between COD and TN, aromaticity of protein material spectrum coefficient of the value of the first principal component areas related to the COD reached 97.63%, aromaticity protein material and the sum of the value of the first principal component area microbial metabolites and humic acid and fulvic acid material ratio of the sum of the value of the first principal component area (Yp/Yf) and TN correlation coefficient reached 94.02%.By combining the three-dimensional fluorescence spectrum of water with the principal component analysis method, the dimensionless extraction of fluorescence spectrum information of each process of sewage treatment is realized, the overlapping of fluorescence peaks and redundancy of spectral information of each substance are avoided. Through the spectral characteristics of each substance in the water, the spectrum is divided into different material regions, the first principal component region value of each region is obtained, which improves the accuracy of substance identification and effectively solves the problem of spectral information identification of each substance. By using the correlation analysis of the first principal component area value of aromatic protein spectrum and Yp/Yf and the conventional water quality indexes COD and TN, it provides a real-time and effective method for monitoring the quality of domestic sewage and solves the problem that the sewage treatment process is difficult to accurately monitor in real-time. Therefore, the three-dimensional fluorescence spectrum combined with principal component analysis method can be used for fast discrimination of urban domestic sewage treatment process, providing a new fast on-line monitoring and analysis method for water quality monitoring, process optimization and treatment effect evaluation in the sewage treatment process.