Direct start-up of aerobic granular sludge system with dewatered sludge granular particles as inoculant

In-situ rapid cultivation of aerobic granular sludge in A/O bioreactor by using Ca(ClO)2 pretreating sludge

The efficient utilization of residual sludge and the rapid cultivation of aerobic granular sludge in continuous-flow engineering applications present significant challenges. In this study, aerobic granular cultivation was fostered in a continuous-flow system using Ca(ClO)2-sludge carbon (Ca-SC). Ca-SC retained the original sludge properties, contributing to granular growth in an A/O bioreactor. By day 40, the granule diameters increased to 0.8 mm with the SVI30 decreased by 2.7 times. Moreover, Ca-SC facilitated protein secretion, reaching 98.06 mg/g VSS and enhanced the hydrophobicity to 68.4 %. The continuous-flow aerobic granular sludge exhibited a nutrient removal rate above 90 %. Furthermore, Tessaracoccus and Nitrospira were enriched to promote granular formation and nitrogen removal. The residual sludge was carbonized and reused in the traditional wastewater treatment process to culture granular sludge in situ, aiming to achieve "self-production and self-consumption" of sludge and promote the innovative model of "treating waste with waste" in urban sewage environmental restoration.

The potential effects of N-Acyl homoserine lactones on aerobic sludge granulation during phenolic wastewater treatment

The formation of aerobic granular sludge (AGS) is relatively difficult during the treatment of refractory wastewater, which generally shows small granular sizes and poor stability. The formation of AGS is regulated by N-Acyl homoserine lactones (AHLs)-mediated quorum sensing (QS). However, the potential role of AHLs in AGS formation under the toxic stress of refractory pollutants and the heterogeneity in the distribution and function of AHLs across different aggregates are not well understood. This study investigated the potential effects of AHLs on the formation of AGS during phenolic wastewater treatment. The distribution and succession of AHLs across varying granular sizes and development stages of AGS were investigated. Results showed that AGS was successfully formed in 13 days with an average granular size of 335 ± 39 μm and phenol removal efficiency of >99%. The levels of AHLs initially increased and then decreased. C4-HSL and 3-oxo-C10-HSL were enriched in large granules, suggesting they may play a pivotal role in regulating the concentration and composition of extracellular polymeric substances (EPS). The content of EPS constantly increased to 149.4 mg/gVSS, and protein (PN) was enriched in small and large granules. Luteococcus was the dominant genus constituting up to 62% after the granulation process, and exhibited a strong association with C4-HSL. AHLs might also regulate the bacterial community responsible for EPS production, and pollutant removal, and facilitate the proliferation of slow-growing microorganisms, thereby enhancing the formation of AGS. The synthesis and dynamics of AHLs were mainly governed by AHLs-producing bacterial strains of Rhodobacter and Pseudomonas, and AHLs-quenching strains of Flavobacterium and Comamonas. C4-HSL and 3-oxo-C10-HSL might be the major contributors to promoting sludge granulation under phenol stress and play critical roles in large granules. These findings enhance our understanding of the roles that AHLs play in sludge granulation under toxic conditions.

Key function of Kouleothrix in stable formation of filamentous aerobic granular sludge at low superficial gas velocity with polymeric substrates

Forming and maintaining stable aerobic granular sludge (AGS) at a low superficial gas velocity (SGV) is challenging, particularly with polymeric substrates. This study cultivated filamentous aerobic granular sludge (FAGS) with filamentous Kouleothrix (Type 1851) at low SGV (0.15 cm/s) utilizing mixed acetate-soluble starch. Within approximately 260 days, notable increases in the relative abundance of Kouleothrix (from 4 % to 10 %) and Ca. Competibacter (from 1 % to 26 %) were observed through 16S rRNA gene analysis. Metagenomic analysis revealed increased expression of functional genes involved in volatile fatty acid (VFA) production (e.g., ackA and pta) and polyhydroxyalkanoate synthesis (e.g., phbB and phbC). Kouleothrix acted as a skeleton for bacterial attachment and was the key fermenting bacteria promoting granulation and maintaining granule stability. This study provides insight into the formation of FAGS with low-energy and non-VFA substrates.

Full-scale upgrade activated sludge to continuous-flow aerobic granular sludge: Implementing microaerobic-aerobic configuration with internal separators

Aerobic granular sludge (AGS) has been successfully used in sequencing batch reactors. However, their application to existing continuous-flow systems remains challenging. In this study, a novel microaerobic-aerobic configuration with internal separators was implemented in a full-scale municipal wastewater treatment facility with a nominal capacity of 2.5 × 104 m3 d-1. Sludge characteristics, pollutant removal and associated pathways, shifts in the microbial community, and underlying granulation mechanisms were investigated. Following a two-month operation period, the transition from flocculent-activated sludge to well-defined AGS with distinct boundaries and compact structures was successfully achieved. The average size of sludge increased from 31.9 to 138.5 μm, with granules larger than 200 μm constituting 28.9 % of the total sludge and SVI30 averaging 51.4 ± 8.2 mL g-1. The 95th percentile effluent COD, NH4+-N, and TN concentrations were 35.0, 1.2, and 13.3 mg L-1, respectively. The primary pathways for pollutant removal were identified as simultaneous nitrification, denitrification, and phosphorus removal within the microaerobic tanks. The enrichment of denitrifying phosphorus-accumulating organisms, including Hydrogenophaga, Accumulibacter, Azospira, Dechloromonas, and Pseudomonas, provides an essential microbial foundation. Furthermore, computational fluid dynamics modeling revealed that the incorporation of internal separators in aerobic tanks induced shifts in the flow pattern, transitioning from a single-circulation cell to multiple vortical cells. This alteration amplified the local velocity gradients, generating the required shear forces to drive granulation. Moreover, mass balance analysis revealed that the microaerobic and aerobic tanks operated under feast and famine conditions, respectively, creating a microbial selection pressure that favored granulation. This process eliminates the need for external clarifiers, resulting in a footprint reduction of 38.2 % and one-third energy savings for sludge reflux. This study offers valuable insights into the application of continuous-flow AGS to upgrade existing activated sludge systems with limited retrofitting requirements.

Research progress of novel bio-denitrification technology in deep wastewater treatment

Excessive nitrogen emissions are a major contributor to water pollution, posing a threat not only to the environment but also to human health. Therefore, achieving deep denitrification of wastewater is of significant importance. Traditional biological denitrification methods have some drawbacks, including long processing times, substantial land requirements, high energy consumption, and high investment and operational costs. In contrast, the novel bio-denitrification technology reduces the traditional processing time and lowers operational and maintenance costs while improving denitrification efficiency. This technology falls within the category of environmentally friendly, low-energy deep denitrification methods. This paper introduces several innovative bio-denitrification technologies and their combinations, conducts a comparative analysis of their denitrification efficiency across various wastewater types, and concludes by outlining the future prospects for the development of these novel bio-denitrification technologies.

Feasibility and optimization of a novel upflow denitrification reactor using denitrifying granular sludge for nitric acid pickling wastewater treatment

Stainless steel is highly valued for its superior resistance to corrosion. However, the pickling process involved in stainless steel production generates abundant NO₃^--N, causing health and environmental risks. To address this issue, this study proposed a novel solution utilizing an up-flow denitrification reactor and denitrifying granular sludge for treating NO₃^--N pickling wastewater under high NO₃^--N loading. It was found that, the denitrifying granular sludge exhibited stable denitrification performance with the highest denitrification rate of 2.79 gN/(gVSS·d) and average removal rates of NO₃^--N and TN of 99.94% and 99.31%, respectively, under optimal operating conditions of pH 6-9, temperature 35 °C, C/N ratio 3.5, hydraulic retention time (HRT) 11.1 h and ascending flow rate 2.75 m/h. This process reduced carbon source usage by 12.5-41.7% as compared to traditional denitrification methods. These findings demonstrate the efficacy of combining granular sludge and an up-flow denitrification reactor for treating nitric acid pickling wastewater.

A review of biowaste remediation and valorization for environmental sustainability: Artificial intelligence approach

Biowaste remediation and valorization for environmental sustainability focuses on prevention rather than cleanup of waste generation by applying the fundamental recovery concept through biowaste-to-bioenergy conversion systems - an appropriate approach in a circular bioeconomy. Biomass waste (biowaste) is discarded organic materials made of biomass (e.g., agriculture waste and algal residue). Biowaste is widely studied as one of the potential feedstocks in the biowaste valorization process due to its being abundantly available. In terms of practical implementations, feedstock variability from biowaste, conversion costs and supply chain stability prevent the widespread usage of bioenergy products. Biowaste remediation and valorization have used artificial intelligence (AI), a newly developed idea, to overcome these difficulties. This report analyzed 118 works that applied various AI algorithms to biowaste remediation and valorization-related research published between 2007 and 2022. Four common AI types are utilized in biowaste remediation and valorization: neural networks, Bayesian networks, decision tree, and multivariate regression. The neural network is the most frequent AI for prediction models, the Bayesian network is utilized for probabilistic graphical models, and the decision tree is trusted for providing tools to assist decision-making. Meanwhile, multivariate regression is employed to identify the relationship between experimental variables. AI is a remarkably effective tool in predicting data, which is reportedly better than the conventional approach owing to its characteristics of time-saving and high accuracy. The challenge and future work in biowaste remediation and valorization are briefly discussed to maximize the model's performance.