Dynamic calibration of a new secondary settler model using <i>Cand. Microthrix</i> as predictor of settling velocity

Climate change is projected to increase the frequency of hydraulic shocks on urban water systems, affecting water resource recovery facilities (WRRFs). In these facilities, the settleability of activated sludge is a critical hydraulic bottleneck. However, to date, the dynamic prediction of hindered settling velocity (v0/rH) has remained unresolved. To address this significant knowledge gap, this study presents an assessment of microbial community predictors of hindered settling velocity. Through a regression analysis of independent laboratory and full-scale experimental data, we identified a close association between the relative abundance of Candidatus Microthrix filamentous bacteria and hindered settling velocity parameter values. While no direct association was observed between filamentous abundance and compression settling parameters, we propose linking the dynamic calibration of the compressive solid stress function to v0/rH. Notably, our results demonstrate, for the first time, the efficacy of dynamic calibration of SST models using the relative abundance of filamentous microbial predictors in a simulation model of the Kloten-Opfikon full-scale WRRF. Furthermore, besides Cand. Microthrix, Thiothrix is found to be a putative predictor for biomolecular SST calibration. These findings shed light on the potential of microbial communities to predict hindered settling velocity in WRRFs and offer valuable insights for improving wastewater treatment processes in the face of climate change challenges

Microalgae and cyanobacteria modeling in water resource recovery facilities: A critical review

Microalgal and cyanobacterial resource recovery systems could significantly advance nutrient recovery from wastewater by achieving effluent nitrogen (N) and phosphorus (P) levels below the current limit of technology. The successful implementation of phytoplankton, however, requires the formulation of process models that balance fidelity and simplicity to accurately simulate dynamic performance in response to environmental conditions. This work synthesizes the range of model structures that have been leveraged for algae and cyanobacteria modeling and core model features that are required to enable reliable process modeling in the context of water resource recovery facilities. Results from an extensive literature review of over 300 published phytoplankton models are presented, with particular attention to similarities with and differences from existing strategies to model chemotrophic wastewater treatment processes (e.g., via the Activated Sludge Models, ASMs). Building on published process models, the core requirements of a model structure for algal and cyanobacterial processes are presented, including detailed recommendations for the prediction of growth (under phototrophic, heterotrophic, and mixotrophic conditions), nutrient uptake, carbon uptake and storage, and respiration. Keywords: Growth, Nutrient uptake, Lipid storage, Starch storage, Wastewater treatment plant (WWTP