Integrated temperature and DO effect on the lab scale A2O process: Performance, kinetics and microbial community

Li, Songya; Fei, Xuening; Chi, Yongzhi; Jiao, Xiumei; Wang, Le

doi:10.1016/j.ibiod.2018.07.006

Cited by 21 publications

(6 citation statements)

References 46 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The nitrification batch activity test indicated that the partial nitrification was achieved in the system with the inhibition of NOB activity. (Li et al, 2018) Full-scale 85.4 138 (Seuntjens et al, 2018) Full-scale 78 112.25 (Yao and Peng, 2017) AOR: ammonia oxidizing rate; NOR: nitrite oxidizing rate.…”

Section: Microbial Community Of Paosmentioning

confidence: 99%

Combined Enhanced Biological Phosphorus Removal (EBPR) and Nitrite Accumulation for Treating High-strength Wastewater

Yuan

Kang

et al. 2021

Preprint

View full text Add to dashboard Cite

The enhanced biological phosphorus removal (EBPR) has been widely applied in treating domestic wastewater, while the performance on high-strength P wastewater is less investigated and the feasibility of coupling with short-cut nitrogen removal process remains unknown. This study first achieved the simultaneous high-efficient P removal and stable nitrite accumulation in one sequencing batch reactor for treating the synthetic digested manure wastewater. The average effluent P could be down to 0.8 ± 1.0 mg P/L and the P removal efficiency was 99.5 ± 0.8%. Candidatus Accumulibacter was the dominant polyphosphate accumulating organism (PAO) with the relative abundance of 14.2-33.1% in the reactor. Examination of the micro-diversity of Candidatus Accumulibacter using 16s rRNA gene-based oligotyping analysis revealed one unique Accumulibacter oligotype that different from the conventional system, which accounted for 64.2-87.9% of the total Accumulibacter abundance. The presence of high-abundant glycogen accumulating organisms (GAO) (15.6-40.3%, Defluviicoccus and Candidatus Competibacter) did not deteriorate the EBPR performance. Moreover, nitrite accumulation happened in the system with the effluent nitrite up to 20.4 ± 6.4 mg N/L and the nitrite accumulation ratio was nearly 100% maintained for 140 days (420 cycles). Nitrosomonas was the dominant ammonia-oxidizing bacteria with relative abundance of 0.3-2.4% while nitrite-oxidizing bacteria were almost undetected (<0.1%). The introduction of extended anaerobic phase and high volatile fatty acid concentrations were proposed to be the potential selector forces to promote partial nitrification. This is the first study that combined EBPR with nitrite-accumulation for digested manure wastewater treatment, and it provided new sights in strategies to combine the EBPR and short-cut nitrogen removal via nitrite to achieve simultaneous nitrogen and phosphorus removal.

show abstract

Section: Microbial Community Of Paosmentioning

confidence: 99%

Combined Enhanced Biological Phosphorus Removal (EBPR) and Nitrite Accumulation for Treating High-strength Wastewater

Yuan

Kang

et al. 2021

Preprint

View full text Add to dashboard Cite

show abstract

“…2. Since biological treatment is greatly influenced by procedure Mathematical Problems in Engineering variables, like DO of aerobic tank [5], future studies can try to use some procedure variables as inputs for the improvement of model accuracy.…”

Section: Advantages Limitations and Recommendation For Futurementioning

confidence: 99%

“…Traditional biological treatment (A 2 O) dominates the technology mainstream of these terminals with regard to its competitive edge in a low construction cost and energy demands. Whereas, the notorious problem of A 2 O that the performance of the biological process is easily affected by the ambient environment has gradually stood out in recent years [5].…”

Section: Introductionmentioning

confidence: 99%

Employing Artificial Neural Networks to Predict the Performance of Domestic Sewage Treatment Terminals in the Rural Region

Lin

Luo

Zhang

et al. 2021

Mathematical Problems in Engineering

View full text Add to dashboard Cite

Domestic sewage in rural regions is mainly treated by small-scale treatment terminals in China. The large quantities and high dispersion of these terminals render the chemical measurement of effluent to be a time and energy intensive work and further hinder the efficient surveillance of terminals’ performance. After a thorough investigation of 136 operating terminals, this study successfully employs two artificial neural network (ANN) models to predict effluent total nitrogen (TN) and COD (R2 both higher than 0.8) by setting some easily detectable parameters, e.g., pH and conductivity, as inputs. To prevent ANN models getting stuck on local optima and enhance the model performance, genetic algorithm (GA) and particle swarm optimization (PSO) are introduced into ANN, respectively. By comparison, ANN-PSO excels in modelling both TN and COD. The root mean square error (RMSE) and R2 of ANN-PSO in modelling TN are 9.14 and 0.90, respectively, in the training stage, and 11.54 and 0.90, respectively, in the validation stage. The RMSE and R2 of ANN-PSO in modelling COD are 22.10 and 0.90, respectively, in the training stage, and 26.57 and 0.85, respectively, in the validation stage. This is the first study to provide performance prediction models that are available for different terminals. Two established ANN-PSO models show great practical significance in monitoring huge amounts of terminals despite the slight sacrifice of models’ accuracy caused by the great heterogeneity of different terminals.

show abstract

“…On the 35th and 70th days, sludge samples were collected from both reactors and stored at À80°C for performing further high-throughput sequencing. DNA was extracted using the Hipure Soil DNA Kit (Magen, China) and the V3-V4 region of the bacterial 16S rRNA genes was amplified by polymerase chain reaction (PCR) according to the mentioned procedure of Li et al (2018). Subsequently, the MiSeq sequencing platform (Illumina, USA) was used to sequence the purified PCR products.…”

Section: Microbial Community Analysismentioning

confidence: 99%

“…Subsequently, the MiSeq sequencing platform (Illumina, USA) was used to sequence the purified PCR products. Detailed bioinformatics analysis can be found elsewhere (Li et al 2018). Finally, Tax4Fun was used to identify the metagenomics characteristics of the sequenced data.…”

Section: Microbial Community Analysismentioning

confidence: 99%

Impact of light on anoxic/oxic reactors: performance, quorum sensing, and metagenomic characteristics

Fei

Wang

et al. 2021

Water Science and Technology

Self Cite

View full text Add to dashboard Cite

The effect of light has raised attention on wastewater treatment. However, little research has concentrated on the influences of light on activated sludge. In this study, the influences of light on the performance, quorum sensing (QS) and metagenomic characteristics of anoxic/oxic reactors were investigated. The reactor without light (AO1) showed higher total nitrogen (TN) removal (79.15 ± 1.69%) than the reactor with light (AO2) (74.54 ± 1.30%), and significant differences were observed. It was observed that light facilitated the production of protein-like and tryptophan-like substances by employing parallel factor analysis for extracellular polymeric substance (EPS), resulting in more EPS production in AO2, indicating light was beneficial to EPS production. The concentrations of N-acyl-homoserine lactones (AHLs) were various in the two reactors, so the AHLs-mediated QS behaviors in both reactors were also different. These results revealed that light significantly influenced nitrogen removal, EPS, and QS. Metagenomic analysis based on Tax4Fun demonstrated that light reduced the denitrification, stimulated the polysaccharide and protein biosynthesis pathways and down-regulated the AHLs synthesis pathway, resulting in lower TN removal, more EPS production, and lower AHLs concentrations. Based on the above, the likely mechanism was proposed for the influences of light on the reactor.

show abstract

Integrated temperature and DO effect on the lab scale A2O process: Performance, kinetics and microbial community

Cited by 21 publications

References 46 publications

Combined Enhanced Biological Phosphorus Removal (EBPR) and Nitrite Accumulation for Treating High-strength Wastewater

Combined Enhanced Biological Phosphorus Removal (EBPR) and Nitrite Accumulation for Treating High-strength Wastewater

Employing Artificial Neural Networks to Predict the Performance of Domestic Sewage Treatment Terminals in the Rural Region

Impact of light on anoxic/oxic reactors: performance, quorum sensing, and metagenomic characteristics

Contact Info

Product

Resources

About