Excitation-emission matrix (EEM) fluorescence spectroscopy for characterization of organic matter in membrane bioreactors: Principles, methods and applications

The membrane bioreactor(MBR)technology is a rising star for wastewater treatment.The pollutant elimination and membrane fouling performances of MBRs are essentially related to the dissolved organic matter(DOM)in the system.Three-dimensional excitation-emission matrix(3D-EEM)fluorescence spectroscopy,a powerful tool for the rapid and sensitive characterization of DOM,has been extensively applied in MBR studies;however,only a limited portion of the EEM fingerprinting information was utilized.This paper revisits the principles and methods of fluorescence EEM,and reviews the recent progress in applying EEM to characterize DOM in MBR studies.We systematically introduced the information extracted from EEM by considering the fluorescence peak location/intensity,wavelength regional distribution,and spectral deconvolution(giving fluorescent component loadings/scores),and discussed how to use the information to interpret the chemical compositions,physiochemical properties,biological activities,membrane retention/fouling behaviors,and migration/transformation fates of DOM in MBR systems.In addition to conventional EEM indicators,novel fluorescent parameters are summarized for potential use,including quantum yield,Stokes shift,excited energy state,and fluorescence lifetime.The current limitations of EEM-based DOM characterization are also discussed,with possible measures proposed to improve applications in MBR monitoring.

Excitation-emission matrices （EEMs） of colorectal tumors- tool for spectroscopic diagnostics of gastrointestinal neoplasia

The autofluorescence spectroscopy of biologi- cal tissues is a powerful tool for non-invasive detection of tissue pathologies and evaluation of any biochemical and morphological changes arising during the lesions＇ growth. To obtain a full picture of the whole set of endogenous fluorophores appearing in the gastrointestinal （GI） tumors investigated, the technique of excitation-emission matrix （EEM） development was applied in a broad spectral region, covering the ultraviolet and visible spectral ranges. We could thus address a set of diagnostically-important chromophores and their alterations during tumor develop- ment, namely, collagen, elastin, nicotinamide adenine dinucleotide （NADH）, flavins, porphyrins, while hemo- globin＇s absorption influence on the spectra obtained could be evaluated as well. Comparisons are presented between EEM data of normal mucosae, benign polyps and malignant carcinoma, and the origins are determined of the fluorescence signals forming these matrices.

Multivariate analysis of fluorescence and source identification of dissolved organic matter in Jiaozhou Bay, China

Hierarchical clustering analysis and principal component analysis （PCA） methods were used to assess the similarities and dissimilarities of the entire Excitation-emission matrix spectroscopy （EEMs） data sets of samples collected from Jiaozhou Bay, China. The results demonstrate that multivariate analysis facilitates the complex data treatment and spectral sorting processes, and also enhances the probability to reveal otherwise hidden information concerning the chemical characteristics of the dissolved organic matter （DOM）. The distribution of different water samples as revealed by multivariate results has been used to track the movement of DOM material in the study area, and the interpretation is supported by the results obtained from the numerical simulation model of substance tracing technique, which show that the substance discharged by Haibo River can be distributed in Jiaozhou Bay.

Spatial heterogeneity and compositional profiles of dissolved organic matter in farmland soils across China' Mainland

Dissolved organic matter(DOM) plays an essential role in many geochemical processes,however its complexity, chemical diversity, and molecular composition are poorly understood. Soil samples were collected from 500 vegetable fields in administrative regions of China' Mainland, of which 122 were selected for further investigation. DOM properties were characterized by three-dimensional excitation-emission matrix(3D-EEM) fuorescence spectroscopy and Fourier transform ion cyclotron resonance mass spectrometry(FTICRMS)(field intensity is 15 Tesla). Our results indicated that the main constituents were UVA humic-like substances, humic-like substances, fulvic acid-like substances, and tyrosine-like substances. A total of 10,989 molecular formulae with a mass range of 100.04 to 799.59 Da were detected, covering the mass spectrometric information of the soil samples from 27 different regions. CHO and CHON molecules were dominant in DOM, whereas lignin, tannins,and aromatic substances served as the main components. The results of cluster analysis revealed that the soil properties in Jiangxi Province were considerably different from those in other regions. The key backgrounds of the DOM molecular characteristics in the vegetablefield soil samples across China' Mainland were provided at the molecular level, with large abundance and great variability.

A chemometric analysis on the fluorescent dissolved organic matter in a full-scale sequencing batch reactor for municipal wastewater treatment

Rapid monitoring of water quality is crucial to the operation of municipal wastewater treatment plants （WWTPs）. Fluorescence excitation-emission matrix （EEM） in combination with parallel lhctor analysis （PARAFAC） has been used as a powerful tool for the characterization of dissolved organic matter （DOM） in WWTPs. However, a recent work has revealed the drawback of PARAFAC analysis, i.e., overestimating the component number. A novel method, parallel lhctor framework-clustering analysis （PFFCA）,＂has been cleveloped in our earlier work to resolve this drawback of PARAFAC. In the present work, both PARAFAC and PFFCA were used to analyze the EEMs of water samples from a full-scale WWTP from a practical application point of view. The component number and goodness-of- fit from these two methods were compared and the relationship between the relative score change of component and the actual concentration was investigated to evaluate the estimation error introduced by 9 both methods. PFFCA score and actual concentration exhibited a higher correlation coefficient （R- = 0.870） compared with PARAFAC （R2〈 0.771）, indicating that PFFCA provided a more accurate relative change estimation than PARAFAC. The results suggest that use of PARAFAC may cause confusion in selecting the component number, while EEM-PFFCA is a more reliable alternative approach for monitoring water quality in WWTPs.