An improved ASM-GDA approach to evaluate the production kinetics of loosely bound and tightly bound extracellular polymeric substances in biological phosphorus removal process

Extracellular Polymeric Substances Drive Symbiotic Interactions in Bacterial‒Microalgal Consortia

The importance of several factors that drive the symbiotic interactions between bacteria and microalgae in consortia has been well realised. However, the implication of extracellular polymeric substances (EPS) released by the partners remains unclear. Therefore, the present study focused on the influence of EPS in developing consortia of a bacterium, Variovorax paradoxus IS1, with a microalga, Tetradesmus obliquus IS2 or Coelastrella sp. IS3, all isolated from poultry slaughterhouse wastewater. The bacterium increased the specific growth rates of microalgal species significantly in the consortia by enhancing the uptake of nitrate (88‒99%) and phosphate (92‒95%) besides accumulating higher amounts of carbohydrates and proteins. The EPS obtained from exudates, collected from the bacterial or microalgal cultures, contained numerous phytohormones, vitamins, polysaccharides and amino acids that are likely involved in interspecies interactions. The addition of EPS obtained from V. paradoxus IS1 to the culture medium doubled the growth of both the microalgal strains. The EPS collected from T. obliquus IS2 significantly increased the growth of V. paradoxus IS1, but there was no apparent change in bacterial growth when it was cultured in the presence of EPS from Coelastrella sp. IS3. These observations indicate that the interaction between V. paradoxus IS1 and T. obliquus IS2 was mutualism, while commensalism was the interaction between the bacterial strain and Coelastrella sp. IS3. Our present findings thus, for the first time, unveil the EPS-induced symbiotic interactions among the partners involved in bacterial‒microalgal consortia.

Insight into the generation and consumption mechanism of tightly bound and loosely bound extracellular polymeric substances by mathematical modeling

The quantity of tightly bound extracellular polymeric substances (TB-EPS) and loosely bound extracellular polymeric substances (LB-EPS) are recognized to be crucial for activated sludge flocculability and settleability. However, the generation and consumption mechanisms of TB-EPS and LB-EPS are vague, and there is no effective model to quantitatively predict LB-EPS and TB-EPS. In this work, a decrease in LB-EPS and TB-EPS was verified to increase the absolute value of the zeta potential and decrease the sludge settling volume, which affects the flocculation and settling performance of sludge. Hence, we comparatively developed, calibrated and validated two different mathematical model structure (named expanded unified model-TL1 and expanded unified model-TL2), aiming to systematically reveal the generation and consumption mechanism of TB-EPS and LB-EPS and quantitatively predict changes of TB-EPS and LB-EPS. On the basis of microbial physiology and the existing literature, two different mechanisms of the generation and consumption of TB-EPS and LB-EPS are described. According to the validation performed, expanded unified model-TL2 fit better with experimental TB-EPS and LB-EPS, which described with the hypotheses: (i) TB-EPS and LB-EPS are simultaneously generated while activate biomass growth on external substrate, (ii) LB-EPS can also be hydrolyzed by TB-EPS, and (iii) Biomass-associated products (BAP) are hydrolyzed by LB-EPS, and it was further proven to be more realistic from the perspective of microbial physiology. This study systematically revealed the generation and consumption mechanism of TB-EPS and LB-EPS by mathematical modeling, and provides a basis for regulating the concentrations of them to improve sludge settling capacity and system stability.

Effects of side-stream operation on the mainstream biological phosphorus metabolic pathway for phosphorus recovery: Simulation by an extended ASM2d model

An extended activated sludge model (E-ASM2d) was established by including the metabolic processes of double-layer extracellular polymeric substances (EPS) and glycogen-accumulating organisms (GAOs) into the existing ASM2d model for describing and predicting the metabolic processes of the side-stream phosphorus (P) recovery reactor. A sensitivity analysis of model parameters on S_PO4(soluble phosphate), X_LEPS (loosely-bound EPS), X_TEPS (tightly-bound EPS), COD, and S_NH4 (soluble ammonia nitrogen) outputs was conducted for identifying influential parameters. The predicted effluent values of COD, ammonia nitrogen (NH₄), and P corresponded well with actual measured values and all the model performance coefficient values for COD, NH_4, and P were higher than 0.65, implying the E-ASM2d model could accurately simulate the metabolic processes of the side-stream P recovery process under different COD:P ratio conditions. The variations in the mainstream biological P metabolic pathway under different COD:P conditions were investigated by the E-ASM2d model. At COD:P ratios of 30, 20, and 10, the values of f_PP,TEPS (fraction of X_TEPS in polyphosphate metabolic process) increased from 0.092, 0.094, and 0.096 in the initial phase to 0.107, 0.124, and 0.187 in the side-stream phase, respectively, demonstrating that the fraction of P removal by tightly-bound EPS was improved by the side-stream operation.

Simulating a combined lysis-cryptic and biological nitrogen removal system treating domestic wastewater at low C/N ratios using artificial neural network

In this study, a combined alkaline (ALK) and ultrasonication (ULS) sludge lysis-cryptic pretreatment and anoxic/oxic (AO) system (AO + ALK/ULS) was developed to enhance biological nitrogen removal (BNR) in domestic wastewater with a low carbon/nitrogen (C/N) ratio. A real-time control strategy for the AO + ALK/ULS system was designed to optimize the sludge lysate return ratio (R_SLR) under variable sludge concentrations and variations in the influent C/N (⩽ 5). A multi-layered backpropagation artificial neural network (BPANN) model with network topology of 1 input layer, 3 hidden layers, and 1 output layer, using the Levenberg-Marquardt algorithm, was developed and validated. Experimental and predicted data showed significant concurrence, verified with a high regression coefficient (R² = 0.9513) and accuracy of the BPANN. The BPANN model effectively captured the complex nonlinear relationships between the related input variables and effluent output in the combined lysis-cryptic + BNR system. The model could be used to support the real-time dynamic response and process optimization control to treat low C/N domestic wastewater.