• Principles and methods for fluorescence EEM are systematically outlined.• Fluorophore peak/region/component and energy information can be extracted from EEM.• EEM can fingerprint the physical/chemical/biological properties of DOM in MBRs.• EEM is useful for tracking pollutant transformation and membrane retention/fouling.• Improvements are still needed to overcome limitations for further studies. 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. 相似文献
Identification of different pollution sources in groundwater is challenging, especially in areas with diverse land uses and receiving multiple inputs. In this study, principal component analysis (PCA) was combined with geographic information system (GIS) to explore the spatial and temporal variation of groundwater quality and to identify the sources of pollution and main factors governing the quality of groundwater in a multiple land-use area in southwestern China. Groundwater samples collected from 26 wells in 2012 and 38 wells in 2018 were analyzed for 13 water quality parameters. The PCA results showed that the hydro-geochemical process was the predominant factor determining groundwater quality, followed by agricultural activities, domestic sewage discharges, and industrial sewage discharges. Agriculture expansion from 2012 to 2018 resulted in increased apportionment of agricultural pollution. In contrast, economic restructure and infrastructure improvement reduced the contributions of domestic sewage and industrial pollution. Anthropogenic activities were found the major causes of elevated nitrogen concentrations (NO3?, NO2?, NH4+) in groundwater, highlighting the necessity of controlling N sources through effective fertilizer managements in agricultural areas and reducing sewage discharges in urban areas. The applications of GIS and PCA successfully identified the sources of pollutants and major factors driving the variations of groundwater quality in tested years.
Environmental Science and Pollution Research - A submerged anaerobic membrane bioreactor (SAnMBR) was used to treat low-concentration domestic sewage. The effects of hydraulic retention time (HRT)... 相似文献