Quantitative image analysis as a robust tool to assess effluent quality from an aerobic granular sludge system treating industrial wastewater

Quantitative image analysis (QIA) is a simple and automated method for process monitoring, complementary to chemical analysis, that when coupled to mathematical modelling allows associating changes in the biomass to several operational parameters. The majority of the research regarding the use of QIA has been carried out using synthetic wastewater and applied to activated sludge systems, while there is still a lack of knowledge regarding the application of QIA in the monitoring of aerobic granular sludge (AGS) systems. In this work, chemical oxygen demand (COD), ammonium (N-NH₄⁺), nitrite (N-NO₂^-), nitrate (N-NO₃^-), salinity (Cl^-), and total suspended solids (TSS) levels present in the effluent of an AGS system treating fish canning wastewater were successfully associated to QIA data, from both suspended and granular biomass fractions by partial least squares models. The correlation between physical-chemical parameters and QIA data allowed obtaining good assessment results for COD (R² of 0.94), N-NH₄⁺ (R² of 0.98), N-NO₂^- (R² of 0.96), N-NO₃^- (R² of 0.95), Cl^- (R² of 0.98), and TSS (R² of 0.94). While the COD and N-NO₂^- assessment models were mostly correlated to the granular fraction QIA data, the suspended fraction was highly relevant for N-NH₄⁺ assessment. The N-NO₃^-, Cl^- and TSS assessment benefited from the use of both biomass fractions (suspended and granular) QIA data, indicating the importance of the balance between the suspended and granular fractions in AGS systems and its analysis. This study provides a complementary approach to assess effluent quality parameters which can improve wastewater treatment plants monitoring and control, with a more cost-effective and environmentally friendly procedure, while avoiding daily physical-chemical analysis.

Long-term stability of a non-adapted aerobic granular sludge process treating fish canning wastewater associated to EPS producers in the core microbiome

The tolerance of aerobic granular sludge (AGS) to variable wastewater composition is perceived as one of its greatest advantages compared to other aerobic processes. However, research studies select optimal operational conditions for evaluating AGS performance, such as the use of pre-adapted biomass and the control of wastewater composition. In this study, non-adapted granular sludge was used to treat fish canning wastewater presenting highly variable organic, nutrient and salt levels over a period of ca. 8 months. Despite salt levels up to 14 g NaCl L^-1, the organic loading rate (OLR) was found to be the main factor driving AGS performance. Throughout the first months of operation, the OLR was generally lower than 1.2 kg COD m^-3 day^-1, resulting in stable nitrification and low COD and phosphorous levels at the outlet. An increase in OLR up to 2.3 kg COD m^-3 day^-1 disturbed nitrification and COD and phosphate removal, but a decrease to average values between 1 and 1.6 kg COD m^-3 day^-1 led to resuming of those processes. Most of the bacteria present in the AGS core microbiome were associated to extracellular polymeric substances (EPS) production, such as Thauera and Paracoccus, which increased during the higher OLR period. Ammonium-oxidizing bacteria (AOB) and nitrite-oxidizing bacteria (NOB) species were detected in AGS biomass; while AOB were identified throughout the operation, NOB were no further identified after the period of increased OLR. Different polyphosphate-accumulating organisms (PAOs) were detected along the process: CandidatusAccumulibacter, Tetrasphaera and Gemmatimonas. A non-adapted granular sludge was able to treat the fish canning wastewater and to tolerate salinity fluctuations up to 14 g L^-1. Overall, a high microbial diversity associated to EPS producers allowed to preserve bacterial groups responsible for nutrients removal, contributing to the adaptation and long-term stability of the AGS system.