Dynamic calibration of a new secondary settler model using Cand. Microthrix as a 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.

Seasonal microbial community dynamics complicates the evaluation of filamentous bulking mitigation strategies in full-scale WRRFs.

The activated sludge wastewater treatment process has been thoroughly researched in more than 100 years, yet there are still operational challenges that have not been fully resolved. Such a challenge is the control of filamentous bulking caused by the overgrowth of certain filamentous bacteria. In this study, we tested different mitigation strategies to reduce filamentous bulking, caused by two common filamentous genera found in full-scale water resource recovery facilities (WRRF), Candidatus Microthrix and Candidatus Amarolinea. PAX dosing, ozone addition, hydrocyclone implementation, and the addition of nano-coagulants were tested as mitigation strategies in four parallel treatment lines in a full-scale WRRF over three consecutive years. Unexpectedly, the activated sludge settleability was not affected by any of the mitigation strategies. Some of the strategies appeared to have a strong mitigating effect on the two filamentous species. However, detailed analyses of the microbial communities revealed strong recurrent seasonal variations in all four lines, including the control line which masked the real effect. After removing the effect of the seasonal variation by using a time-series decomposition approach, it was clear that the filamentous bacteria were mostly unaffected by the mitigation strategies. Only PAX dosing had some effect on Ca. Microthrix, but only on one species, Ca. Microthrix subdominans, and not on the most common Ca. Microthrix parvicella. Overall, our study shows the importance of long-term monitoring of microbial communities at species level to understand the normal seasonal pattern to effectively plan and execute full-scale experiments. Moreover, the results highlight the importance of using parallel reference treatment lines when evaluating the effect of mitigation strategies in full-scale treatment plants.

Optimal influent N-to-P ratio for stable microalgal cultivation in water treatment and nutrient recovery.

Species specific nitrogen-to-phosphorus molar ratio (NPR) has been suggested for green microalgae. Algae can store nitrogen and phosphorus, suggesting that the optimum feed concentration dynamically changes as function of the nutrient storage. We assessed the effect of varying influent NPR on microalgal cultivation in terms of microbial community stability, effluent quality and biokinetics. Mixed green microalgae (Chlorella sorokiniana and Scenedesmus sp.) and a monoculture of Chlorella sp. were cultivated in continuous laboratory-scale reactors treating used water. An innovative image analysis tool, developed in this study, was used to track microbial community changes. Diatoms proliferated as influent NPR decreased, and were outcompeted once cultivation conditions were restored to the optimal NPR range. Low NPR operation resulted in decrease in phosphorus removal, biomass concentration and effluent nitrogen concentration. ASM-A kinetic model simulation results agreed well with operational data in the absence of diatoms. The failure to predict operational data in the presence of diatoms suggest differences in microbial activity that can significantly influence nutrient recovery in photobioreactors (PBR). No contamination occurred during Chlorella sp. monoculture cultivation with varying NPRs. Low NPR operation resulted in decrease in biomass concentration, effluent nitrogen concentration and nitrogen quota. The ASM-A model was calibrated for the monoculture and the simulations could predict the experimental data in continuous operation using a single parameter subset, suggesting stable biokinetics under the different NPR conditions. Results show that controlling the influent NPR is effective to maintain the algal community composition in PBR, thereby ensuring effective nutrients uptake.

Towards a consensus-based biokinetic model for green microalgae - The ASM-A.

Cultivation of microalgae in open ponds and closed photobioreactors (PBRs) using wastewater resources offers an opportunity for biochemical nutrient recovery. Effective reactor system design and process control of PBRs requires process models. Several models with different complexities have been developed to predict microalgal growth. However, none of these models can effectively describe all the relevant processes when microalgal growth is coupled with nutrient removal and recovery from wastewaters. Here, we present a mathematical model developed to simulate green microalgal growth (ASM-A) using the systematic approach of the activated sludge modelling (ASM) framework. The process model - identified based on a literature review and using new experimental data - accounts for factors influencing photoautotrophic and heterotrophic microalgal growth, nutrient uptake and storage (i.e. Droop model) and decay of microalgae. Model parameters were estimated using laboratory-scale batch and sequenced batch experiments using the novel Latin Hypercube Sampling based Simplex (LHSS) method. The model was evaluated using independent data obtained in a 24-L PBR operated in sequenced batch mode. Identifiability of the model was assessed. The model can effectively describe microalgal biomass growth, ammonia and phosphate concentrations as well as the phosphorus storage using a set of average parameter values estimated with the experimental data. A statistical analysis of simulation and measured data suggests that culture history and substrate availability can introduce significant variability on parameter values for predicting the reaction rates for bulk nitrate and the intracellularly stored nitrogen state-variables, thereby requiring scenario specific model calibration. ASM-A was identified using standard cultivation medium and it can provide a platform for extensions accounting for factors influencing algal growth and nutrient storage using wastewater resources.

Short-sludge age EBPR process - Microbial and biochemical process characterisation during reactor start-up and operation.

The new paradigm for used water treatment suggests the use of short solid retention times (SRT) to minimize organic substrate mineralization and to maximize resource recovery. However, little is known about the microbes and the underlying biogeochemical mechanisms driving these short-SRT systems. In this paper, we report the start-up and operation of a short-SRT enhanced biological phosphorus removal (EBPR) system operated as a sequencing batch reactor (SBR) fed with preclarified municipal wastewater, which is supplemented with propionate. The microbial community was analysed via 16S rRNA amplicon sequencing. During start-up (SRT = 8 d), the EBPR was removing up to 99% of the influent phosphate and completely oxidized the incoming ammonia. Furthermore, the sludge showed excellent settling properties. However, once the SRT was shifted to 3.5 days nitrification was inhibited and bacteria of the Thiothrix taxon proliferated in the reactor, thereby leading to filamentous bulking (sludge volume index up to SVI = 1100 mL/g). Phosphorus removal deteriorated during this period, likely due to the out-competition of polyphosphate accumulating organisms (PAO) by sulphate reducing bacteria (SRB). Subsequently, SRB activity was suppressed by reducing the anaerobic SRT from 1.2 day to 0.68 day, with a consequent rapid SVI decrease to ∼200 ml/g. The short-SRT EBPR effectively removed phosphate and nitrification was mitigated at SRT = 3 days and oxygen levels ranging from 2 to 3 mg/L.

Microthrix parvicella abundance associates with activated sludge settling velocity and rheology - Quantifying and modelling filamentous bulking.

The objective of this work is to identify relevant settling velocity and rheology model parameters and to assess the underlying filamentous microbial community characteristics that can influence the solids mixing and transport in secondary settling tanks. Parameter values for hindered, transient and compression settling velocity functions were estimated by carrying out biweekly batch settling tests using a novel column setup through a four-month long measurement campaign. To estimate viscosity model parameters, rheological experiments were carried out on the same sludge sample using a rotational viscometer. Quantitative fluorescence in-situ hybridisation (qFISH) analysis, targeting Microthrix parvicella and phylum Chloroflexi, was used. This study finds that M. parvicella - predominantly residing inside the microbial flocs in our samples - can significantly influence secondary settling through altering the hindered settling velocity and yield stress parameter. Strikingly, this is not the case for Chloroflexi, occurring in more than double the abundance of M. parvicella, and forming filaments primarily protruding from the flocs. The transient and compression settling parameters show a comparably high variability, and no significant association with filamentous abundance. A two-dimensional, axi-symmetrical computational fluid dynamics (CFD) model was used to assess calibration scenarios to model filamentous bulking. Our results suggest that model predictions can significantly benefit from explicitly accounting for filamentous bulking by calibrating the hindered settling velocity function. Furthermore, accounting for the transient and compression settling velocity in the computational domain is crucial to improve model accuracy when modelling filamentous bulking. However, the case-specific calibration of transient and compression settling parameters as well as yield stress is not necessary, and an average parameter set - obtained under bulking and good settling conditions - can be used.

A new settling velocity model to describe secondary sedimentation.

Secondary settling tanks (SSTs) are the most hydraulically sensitive unit operations in biological wastewater treatment plants. The maximum permissible inflow to the plant depends on the efficiency of SSTs in separating and thickening the activated sludge. The flow conditions and solids distribution in SSTs can be predicted using computational fluid dynamics (CFD) tools. Despite extensive studies on the compression settling behaviour of activated sludge and the development of advanced settling velocity models for use in SST simulations, these models are not often used, due to the challenges associated with their calibration. In this study, we developed a new settling velocity model, including hindered, transient and compression settling, and showed that it can be calibrated to data from a simple, novel settling column experimental set-up using the Bayesian optimization method DREAM(ZS). In addition, correlations between the Herschel-Bulkley rheological model parameters and sludge concentration were identified with data from batch rheological experiments. A 2-D axisymmetric CFD model of a circular SST containing the new settling velocity and rheological model was validated with full-scale measurements. Finally, it was shown that the representation of compression settling in the CFD model can significantly influence the prediction of sludge distribution in the SSTs under dry- and wet-weather flow conditions.