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Two‐dimensional fluorescence as a fingerprinting tool for monitoring wastewater treatment systems
Authors:Claudia F Galinha  Gilda Carvalho  Carla A M Portugal  Giuseppe Guglielmi  Maria A M Reis  João G Crespo
Affiliation:1. REQUIMTE/CQFB, Chemistry Department, Faculdade de Ciências e Tecnologia—Universidade Nova de Lisboa, 2829‐516 Caparica, Portugal;2. Instituto de Biologia Experimental e Tecnológica (IBET), Av. República, Quinta do Marquês (EAN), 2784‐505 Oeiras, Portugal;3. Department of Civil and Environmental Engineering, University of Trento, Via Mesiano, 77‐38123 Trento, Italy;4. (current address): E.T.C. Engineering srl, Via Praga, 7‐38121 Trento, Italy
Abstract:BACKGROUND: The use of two‐dimensional (2D) fluorescence for monitoring complex biological systems requires careful assessment of the effect of chemical species present, which may be fluorescent and/or may interfere with the fluorescence response of target fluorophores. Given the complexity of fluorescence data (excitation emission matrices—EEMs), the challenge is how to recover the information embedded into those EEMs that can be related quantitatively with the observed performance of the biological processes under study. RESULTS: This work shows clearly that interference effects (such as quenching and inner filter effects) occur due to the presence of multiple species in complex biological media, such as natural water matrices, wastewaters and activated sludge. A statistical multivariate analysis is proposed to recover quantitative information from 2D fluorescence data, correlating EEMs with the observed performance. A selected case study is discussed, where 2D fluorescence spectra obtained from the effluent of a membrane bioreactor were compressed using PARAFAC and successfully correlated with the effluent chemical oxygen demand, using projection to latent structures modelling. CONCLUSION: This study demonstrates the potential of using 2D fluorescence spectroscopy as a status fingerprint. Additionally, it is shown how statistical multivariate data analysis can be used to correlate EEMs with selected performance parameters for monitoring of biological systems. Copyright © 2011 Society of Chemical Industry
Keywords:2D fluorescence spectroscopy  monitoring of biological processes  wastewater treatment  quenching and inner filter effects  multivariate statistical modelling
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