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

Real-time bioprocess monitoring is crucial for efficient operation and effective control. Aiming to develop an online strategy facilitating optimization, fault detection decision-making during wastewater treatment in a photo-biological nutrient removal (photo-BNR) process, this study investigated the application of Raman spectroscopy quantification total organic content (TOC), volatile fatty acids (VFAs), carbon dioxide (CO2), ammonia (NH3), nitrate (NO3), phosphate (PO4), phosphorus (total P), polyhydroxyalkanoates (PHAs), carbohydrates, suspended solids (TSSs VSSs, respectively). Specifically, partial least squares (PLS) regression models were developed predict these parameters based on spectra, evaluated full cross-validation. Through optimization spectral pre-processing, shift regions latent variables, 8 out 11 that investigated—namely TOC, VFAs, CO2, NO3, P, PHAs, TSSs VSSs—could be predicted with good quality by respective Raman-based PLS calibration models, as shown high coefficient determination (R2 > 90.0%) residual prediction deviation (RPD 5.0), relatively low root mean square error This showed first time potential VSSs photo-BNR reactor.