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Orientador(es)
Resumo(s)
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 quantifi-cation 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.
Descrição
UIDP/04378/2020 UIDB/04378/2020 PD/BD/114574/2016
Palavras-chave
Biological wastewater treatment Intracellular polymers Microalgal–bacterial consortium Nutrient removal Partial least squares (PLS) Photo-biological nutrient removal reactor Raman spectroscopy Real-time monitoring Total organic carbon (TOC) Total suspended solids (TSSs) General Materials Science Instrumentation General Engineering Process Chemistry and Technology Computer Science Applications Fluid Flow and Transfer Processes
