###### Abstract  
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. 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) Article  
Rana  
removal (BNR) is the most common process implemented for simultaneous P and N removal, typically through sequential zones in activated sludge systems: anaerobic for carbon uptake and P release; anoxic for heterotrophic denitrification and P uptake; and aerobic for nitrification and P uptake. Such BNR systems require intensive O\({}_{2}\) supply, often accounting for approximately 60% of WWTPs energy costs [4; 5]. The use of phototrophic anoxygenic bacteria or microalgae systems for wastewater treatment is a good alternative to decrease aeration energy costs in WWTPs [6; 3; 7; 8]. Furthermore, microalgal-bacterial consortia can achieve higher nutrient removal efficiencies than bacterial or microalgal systems alone and with reduced oxygenation costs. In fact, microalgae not only perform nutrient removal but also consume carbon dioxide (CO\({}_{2}\)) produced by bacteria, while producing, through photosynthesis, the O\({}_{2}\) required for system oxygenation and heterotrophic bacterial growth [3]. In addition, higher nutrient recovery can be achieved when compared with anaerobic technologies in WWTPs [9; 10], and the good settling properties of the microalgal-bacterial flocs reduce the biomass harvesting costs associated with microalgal systems [11; 12]. Recently, a photo-enhanced biological phosphorus removal (photo-EBPR) system composed of a consortium of microalgae and bacteria demonstrated a good capacity for P removal at a low chemical oxygen demand (COD) to P ratio (COD/P) and without external aeration requirements [13]. The photo-EBPR system was operated with dark-light cycles, simulating conventional anaerobic-aerobic EBPR cycles, resulting in a culture enriched with polyphosphate accumulating organisms (PAOs) and microalgae [13]. In the current work, a photo-BNR system combining P and N removal was operated and monitored [14]. In photo-BNR systems, volatile fatty acids (VFAs), or other organic carbon sources, are consumed during the dark period. During the light period, microalgae consume CO\({}_{2}\) and produce O\({}_{2}\) to be used by PAOs and nitrifiers. Furthermore, PAOs will store excess P as polyphosphate, while nitrifiers oxidize ammonia to nitrate.