TY - JOUR
T1 - Raman spectrometry as a tool for an online control of a phototrophic biological nutrient removal process
AU - Franca, Rita D. G.
AU - Carvalho, Virgínia C. F.
AU - Fradinho, Joana C.
AU - Reis, Maria A. M.
AU - Lourenço, Nídia D.
N1 - UIDP/04378/2020
UIDB/04378/2020
PD/BD/114574/2016
PY - 2021/7/18
Y1 - 2021/7/18
N2 - 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.
AB - 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.
KW - Biological wastewater treatment
KW - Intracellular polymers
KW - Microalgal–bacterial consortium
KW - Nutrient removal
KW - Partial least squares (PLS)
KW - Photo-biological nutrient removal reactor
KW - Raman spectroscopy
KW - Real-time monitoring
KW - Total organic carbon (TOC)
KW - Total suspended solids (TSSs)
UR - http://www.scopus.com/inward/record.url?scp=85111309230&partnerID=8YFLogxK
U2 - 10.3390/app11146600
DO - 10.3390/app11146600
M3 - Article
AN - SCOPUS:85111309230
SN - 2076-3417
VL - 11
JO - Applied Sciences
JF - Applied Sciences
IS - 14
M1 - 6600
ER -