Print Email Facebook Twitter Use of near-infrared spectroscopy on predicting wastewater constituents to facilitate the operation of a membrane bioreactor Title Use of near-infrared spectroscopy on predicting wastewater constituents to facilitate the operation of a membrane bioreactor Author Kim, E. (TU Delft BN/Cees Dekker Lab; IHE Delft Institute for Water Education) Ćurko, Josip (University of Zagreb) Gajdoš Kljusurić, Jasenka (University of Zagreb) Matošić, Marin (University of Zagreb) Crnek, Vlado (University of Zagreb) López-Vázquez, Carlos M. (IHE Delft Institute for Water Education) Garcia, H. (IHE Delft Institute for Water Education) Brdjanovic, Damir (TU Delft BT/Environmental Biotechnology; IHE Delft Institute for Water Education) Valinger, Davor (University of Zagreb) Date 2021 Abstract The use of near-infrared (NIR) spectroscopy in wastewater treatment has continuously expanded. As an alternative to conventional analytical methods for monitoring constituents in wastewater treatment processes, the use of NIR spectroscopy is considered to be cost-effective and less time-consuming. NIR spectroscopy does not distort the measured sample in any way as no prior treatment is required, making it a waste-free technique. On the negative side, one has to be very well versed with chemometric techniques to interpret the results. In this study, filtered and centrifuged wastewater and sludge samples from a lab-scale membrane bioreactor (MBR) were analysed. Two analytical methods (conventional and NIR spectroscopy) were used to determine and compare major wastewater constituents. Particular attention was paid to soluble microbial products (SMPs) and extracellular polymeric substances (EPSs) known to promote membrane fouling. The parameters measured by NIR spectroscopy were analysed and processed with partial least squares regression (PLSR) and artificial neural networks (ANN) models to assess whether the evaluated wastewater constituents can be monitored by NIR spectroscopy. Very good results were obtained with PLSR models, except for the determination of SMP, making the model qualitative rather than quantitative for their monitoring. ANN showed better performance in terms of correlation of NIR spectra with all measured parameters, resulting in correlation coefficients higher than 0.97 for training, testing, and validation in most cases. Based on the results of this research, the combination of NIR spectra and chemometric modelling offers advantages over conventional analytical methods. Subject Extracellular polymeric substancesMembrane bioreactorNear-infrared spectroscopySoluble microbial productsWastewater analysesWastewater treatment To reference this document use: http://resolver.tudelft.nl/uuid:15697fb5-a041-4900-888b-805047db8fc3 DOI https://doi.org/10.1016/j.chemosphere.2021.129899 ISSN 0045-6535 Source Chemosphere, 272 Part of collection Institutional Repository Document type journal article Rights © 2021 E. Kim, Josip Ćurko, Jasenka Gajdoš Kljusurić, Marin Matošić, Vlado Crnek, Carlos M. López-Vázquez, H. Garcia, Damir Brdjanovic, Davor Valinger Files PDF 1_s2.0_S0045653521003684_main.pdf 913.63 KB Close viewer /islandora/object/uuid:15697fb5-a041-4900-888b-805047db8fc3/datastream/OBJ/view