Chemical Engineering Journal, Journal Year: 2023, Volume and Issue: 475, P. 145995 - 145995
Published: Sept. 15, 2023
Language: Английский
Chemical Engineering Journal, Journal Year: 2023, Volume and Issue: 475, P. 145995 - 145995
Published: Sept. 15, 2023
Language: Английский
Environmental Science & Technology, Journal Year: 2023, Volume and Issue: 57(37), P. 13887 - 13900
Published: Sept. 5, 2023
In this study, sequencing batch operation was successfully combined with a pilot-scale anaerobic biofilm-modified anaerobic/aerobic membrane bioreactor to achieve ammonium oxidation (anammox) without inoculation of anammox aggregates for municipal wastewater treatment. Both total nitrogen and phosphorus removal efficiencies the reactor reached up 80% in 250-day operation, effluent concentrations 4.95 mg-N/L 0.48 mg-P/L. situ enrichment bacteria maximum relative abundance 7.86% observed biofilm, contributing 18.81% removal, denitrification being primary pathway (38.41%). Denitrifying (DPR) (40.54%) aerobic uptake (48.40%) played comparable roles removal. Metagenomic results showed that biofilm contained significantly lower abundances NO-reducing functional genes than bulk sludge (p < 0.01), favoring catabolism former. Interactions between flanking community were dominated by cooperation behaviors (e.g., nitrite supply, amino acids/vitamins exchange) network. Moreover, hydrolytic/fermentative endogenous heterotrophic (Dechloromonas, Candidatus competibacter) substantially enriched under which could alleviate inhibition complex organics. Overall, study provides feasible promising strategy enriching achieving partial mainstream as well DPR.
Language: Английский
Citations
19Journal of Cleaner Production, Journal Year: 2024, Volume and Issue: 442, P. 141087 - 141087
Published: Feb. 1, 2024
Language: Английский
Citations
8IEEE Transactions on Industrial Informatics, Journal Year: 2024, Volume and Issue: 20(5), P. 7292 - 7302
Published: Feb. 8, 2024
Data-driven methods for predicting quality variables in wastewater treatment processes (WWTPs) have mostly ignored the slow time-varying nature of WWTP, and they are data-consuming that need a large amount independent homogeneously distributed data, which makes it difficult to collect. To address this issue with few-shot inconsistent distribution, transfer learning method called transferable deep feature network (TDSFN) time-series prediction is proposed by leveraging knowledge relevant datasets. TDSFN extracts nonlinear features WWTP inertia from time series through constructs domain invariant based on them. Target attention designed enhance predictor adaptability target assigning weights source their similarity features. Furthermore, variational Bayesian inference framework introduced learn parameters TDSFN. The effectiveness verified experiments WWTP.
Language: Английский
Citations
8Water Research, Journal Year: 2024, Volume and Issue: 255, P. 121535 - 121535
Published: March 28, 2024
Language: Английский
Citations
6Chemical Engineering Journal, Journal Year: 2024, Volume and Issue: 489, P. 151242 - 151242
Published: April 16, 2024
Language: Английский
Citations
6Bioresource Technology, Journal Year: 2022, Volume and Issue: 369, P. 128484 - 128484
Published: Dec. 10, 2022
Language: Английский
Citations
24Journal of Water Process Engineering, Journal Year: 2023, Volume and Issue: 55, P. 104090 - 104090
Published: Aug. 4, 2023
Language: Английский
Citations
13Bioresource Technology, Journal Year: 2022, Volume and Issue: 363, P. 127928 - 127928
Published: Sept. 9, 2022
Language: Английский
Citations
20Bioresource Technology, Journal Year: 2022, Volume and Issue: 362, P. 127855 - 127855
Published: Aug. 28, 2022
Language: Английский
Citations
19Water, Journal Year: 2025, Volume and Issue: 17(2), P. 162 - 162
Published: Jan. 9, 2025
Traditional wastewater treatment processes still encounter challenges such as the limited efficiency and excessive greenhouse gas emissions, which restrict their application in environmentally sustainable practices. This study developed an A/O biofilm system assessed impact of inoculating with heterotrophic nitrification–aerobic denitrification (HN–AD) strain Alcaligenes faecalis WT14 on pollutant removal emissions. A continuous monitoring experiment was conducted over 140 days, comparing inoculated (the TWT14 system) non-inoculated CK system). The results demonstrated that outperformed removal, higher NH₄⁺-N, TN, COD efficiencies 11.22%, 21.96%, 12.51%, respectively, quality discharge water from maintaining compliance national standards. improvement underscores positive inoculation enhancing performance system. Regarding exhibited a significantly N₂O emission flux aeration tank compared system, while CO₂ CH₄ emissions were predominantly concentrated anaerobic tank. Global warming potential (GWP) analysis showed no significant difference total average GWP between two systems. However, lower per unit TN removed, highlighting its superior ecological benefits. Environmental factor revealed temperature, pH, humidity, salinity had impacts both Additionally, microbial community indicated enhanced diversity richness within norank_f_JD30-KF-CM45 playing key roles nitrogen removal. provides valuable insights for optimizing design offers scientific guidance upgrading technologies.
Language: Английский
Citations
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