On-Line Monitoring and Analysis Method of Three-Dimensional Fluorescence Spectrum in Urban Domestic Sewage Treatment Process
YANG Jin-qiang1, 2, 4, ZHAO Nan-jing1, 4*, YIN Gao-fang1, 4 , YU Zhi-min2, GAN Ting-ting1, 4, WANG Xiang1, 3, 4, CHEN Min1, 3, 4, FENG Chun1, 3, 4
1. Key Laboratory of Environmental Optics and Technology, Anhui Institute of Optic and Fine Mechanics, Chinese Academy of Sciences, Hefei 230031, China
2. Department of Biological and Environmental Engineering, Hefei University, Hefei 230601, China
3. University of Science and Technology of China, Hefei 230026, China
4. Key Laboratory of Optical Monitoring Technology for Environment, Hefei 230031, China
Abstract：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.
[1] SHI Jun, WANG Zhi-gang, XIAO Yong-hui, et al(施 俊, 王志刚, 肖永辉, 等). Journal of Atmospheric and Environmental Optics(大气与环境光学学报), 2012, 7(1): 31.
[2] LI Lu-lu, JIANG Tao, LU Song, et al(李璐璐, 江 韬, 卢 松, 等). Environmental Sciences(环境科学), 2014, 35(9): 3408.
[3] OUYANG Er-ming, ZHANG Xi-hui, WANG Wei, et al(欧阳二明, 张锡辉, 王 伟，等）. Water Resources Protection(水资源保护), 2007, (3): 56.
[4] Jacquin C, Lesage G, Traber J, et al. Water Res., 2017, 118: 82.
[5] Saadi I, Borisover M, Armon R, et al. Chemosphere, 2006, 63(3): 530.
[6] Zhou Jie, Wang Junjian, Antoine Baudon, et al. Journal of Environmental Quality, 2013, 42(3)：925.
[7] Yang J, Zhang D, Frangi A F, et al. IEEE Trans PAMI, 2004 , 26(1): 131.
[8] ZHAO Nan-jing, LIU Wen-qing, CUI Zhi-cheng, et al(赵南京, 刘文清, 崔志成, 等). Acta Optica Sinica(光学学报), 2005, 25(5): 687.
[9] Green S A, Blough N V. Limnology and Oceanography, 1994, 39(8): 1903.
[10] YAO Lu-lu, TU Xiang, YU Hui-bin，et al(姚璐璐，涂 响，于会彬，等). Chinese Journal of Environmental Engineering(环境工程学报)，2013，7(2): 411.
[11] CHEN Mao-fu, WU Jing, LÜ Yan-li, et al(陈茂福, 吴 静, 律严励, 等). Acta Optica Sinica(光学学报), 2008, 28(3): 578.
[12] Ohno T, Bro R. Soil Science Society of America Journal, 2006, 70: 2028.
[13] Cory R M, Mcknight D M. Environmental Science & Technology, 2005, 39: 8142.
[14] Stedmon C A, Markager S. Estuarine Coastal and Shelf Science, 2003, 57(5): 973.
