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Reverse electrodialysis (RED) is one of the emerging, membrane-based technologies for harvesting salinity gradient energy. In RED process, fouling is an undesirable operation constraint since it leads to a decrease of the obtainable net power density due to increasing stack electric resistance and pressure drop. Therefore, early fouling detection is one of the main challenges for successful RED technology implementation. In the present study, two-dimensional (2D) fluorescence spectroscopy was used, for the first time, as a tool for fouling monitoring in RED. Fluorescence excitation-emission matrices (EEMs) of ion-exchange membrane surfaces and of natural aqueous streams were acquired during one month of a RED stack operation. Fouling evolvement on the ion-exchange membrane surfaces was successfully followed by 2D fluorescence spectroscopy and quantified using principal components analysis (PCA). Additionally, the efficiency of cleaning strategy was assessed by measuring the membrane fluorescence emission intensity before and after cleaning. The anion-exchange membrane (AEM) surface in contact with river water showed to be significantly affected due to fouling by humic compounds, which were found to cross through the membrane from the lower salinity (river water) to higher salinity (sea water) stream. The results obtained show that the combined approach of using 2D fluorescence spectroscopy and PCA has a high potential for studying fouling development and membrane cleaning efficiency in ion exchange membrane processes., (Copyright © 2015 Elsevier Ltd. All rights reserved.)

This work presents the development of multivariate statistically-based models for monitoring several key performance parameters of membrane bioreactors (MBR) for wastewater treatment. This non-mechanistic approach enabled the deconvolution of 2D fluorescence spectroscopy data, a powerful technique that has previously been shown to capture important information regarding MBR performance. Projection to latent structure (PLS) modelling was used to integrate 2D fluorescence data, after compression through parallel factor analysis (PARAFAC), with operation and analytical data to describe an MBR fouling indicator (transmembrane pressure, TMP), five descriptors of the effluent quality (total COD, soluble COD, concentration of nitrite and nitrate, total nitrogen and total phosphorus in the permeate) and the biomass concentration in the bioreactor (MLSS). A multilinear correlation was successfully established for TMP, CODtp and CODsp, whereas the optimised models for the remaining outputs included quadratic and interaction terms of the compressed 2D fluorescence matrices. Additionally, the coefficients of the optimised models revealed important contributions of some of the input parameters to the modelled outputs. This work demonstrates the applicability of 2D fluorescence and statistically-based models to simultaneously monitor multiple key MBR performance parameters with minimal analytical effort. This is a promising approach to facilitate the implementation of MBR technology for wastewater treatment., (Copyright © 2012 Elsevier Ltd. All rights reserved.)