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Article

Raman Spectrometry as a Tool for an Online Control of a Phototrophic Biological Nutrient Removal Process

1
Associate Laboratory i4HB–Institute for Health and Bioeconomy, NOVA School of Science and Technology, NOVA University Lisbon, 2829-516 Caparica, Portugal
2
UCIBIO—Applied Molecular Biosciences Unit, Department of Chemistry, NOVA School of Science and Technology, NOVA University Lisbon, 2829-516 Caparica, Portugal
*
Author to whom correspondence should be addressed.
Academic Editor: Ramaraj Boopathy
Appl. Sci. 2021, 11(14), 6600; https://doi.org/10.3390/app11146600
Received: 4 June 2021 / Revised: 14 July 2021 / Accepted: 16 July 2021 / Published: 18 July 2021
(This article belongs to the Special Issue Novel Technologies for Pollutants Removal from Water and Wastewater)
Real-time bioprocess monitoring is crucial for efficient operation and effective bioprocess control. Aiming to develop an online monitoring strategy for facilitating optimization, fault detection and decision-making during wastewater treatment in a photo-biological nutrient removal (photo-BNR) process, this study investigated the application of Raman spectroscopy for the quantification of total organic content (TOC), volatile fatty acids (VFAs), carbon dioxide (CO2), ammonia (NH3), nitrate (NO3), phosphate (PO4), total phosphorus (total P), polyhydroxyalkanoates (PHAs), total carbohydrates, total and volatile suspended solids (TSSs and VSSs, respectively). Specifically, partial least squares (PLS) regression models were developed to predict these parameters based on Raman spectra, and evaluated based on a full cross-validation. Through the optimization of spectral pre-processing, Raman shift regions and latent variables, 8 out of the 11 parameters that were investigated—namely TOC, VFAs, CO2, NO3, total P, PHAs, TSSs and VSSs—could be predicted with good quality by the respective Raman-based PLS calibration models, as shown by the high coefficient of determination (R2 > 90.0%) and residual prediction deviation (RPD > 5.0), and relatively low root mean square error of cross-validation. This study showed for the first time the high potential of Raman spectroscopy for the online monitoring of TOC, VFAs, CO2, NO3, total P, PHAs, TSSs and VSSs in a photo-BNR reactor. View Full-Text
Keywords: microalgal–bacterial consortium; biological wastewater treatment; intracellular polymers; nutrient removal; partial least squares (PLS); photo-biological nutrient removal reactor; Raman spectroscopy; real-time monitoring; total organic carbon (TOC); total suspended solids (TSSs) microalgal–bacterial consortium; biological wastewater treatment; intracellular polymers; nutrient removal; partial least squares (PLS); photo-biological nutrient removal reactor; Raman spectroscopy; real-time monitoring; total organic carbon (TOC); total suspended solids (TSSs)
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MDPI and ACS Style

Franca, R.D.G.; Carvalho, V.C.F.; Fradinho, J.C.; Reis, M.A.M.; Lourenço, N.D. Raman Spectrometry as a Tool for an Online Control of a Phototrophic Biological Nutrient Removal Process. Appl. Sci. 2021, 11, 6600. https://doi.org/10.3390/app11146600

AMA Style

Franca RDG, Carvalho VCF, Fradinho JC, Reis MAM, Lourenço ND. Raman Spectrometry as a Tool for an Online Control of a Phototrophic Biological Nutrient Removal Process. Applied Sciences. 2021; 11(14):6600. https://doi.org/10.3390/app11146600

Chicago/Turabian Style

Franca, Rita D.G., Virgínia C.F. Carvalho, Joana C. Fradinho, Maria A.M. Reis, and Nídia D. Lourenço 2021. "Raman Spectrometry as a Tool for an Online Control of a Phototrophic Biological Nutrient Removal Process" Applied Sciences 11, no. 14: 6600. https://doi.org/10.3390/app11146600

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