The influencing mechanisms and optimization strategies of organics on anammox process: A critical review

Chemical Engineering Journal, Год журнала: 2024, Номер 493, С. 152743 - 152743

Опубликована: Июнь 1, 2024

Язык: Английский

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Machine learning framework for wastewater circular economy — Towards smarter nutrient recoveries

Desalination, Год журнала: 2024, Номер 592, С. 118092 - 118092

Опубликована: Сен. 7, 2024

Язык: Английский

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A probabilistic deep learning approach to enhance the prediction of wastewater treatment plant effluent quality under shocking load events

Water Research X, Год журнала: 2024, Номер 26, С. 100291 - 100291

Опубликована: Дек. 3, 2024

Sudden shocking load events featuring significant increases in inflow quantities or concentrations of wastewater treatment plants (WWTPs), are a major threat to the attainment treated effluents discharge quality standards. To aid real-time decision-making for stable WWTP operations, this study developed probabilistic deep learning model that comprises encoder-decoder long short-term memory (LSTM) networks with added capacity producing probability predictions, enhance robustness effluent prediction under such events. The LSTM (P-ED-LSTM) was tested an actual WWTP, where bihourly total nitrogen performed and compared classical models, including LSTM, gated recurrent unit (GRU) Transformer. It found events, P-ED-LSTM could achieve 49.7% improvement accuracy predictions concentration GRU, A higher quantile data from output, indicated value more approximate real quality. also exhibited predictive power next multiple time steps scenarios. captured approximately 90% over-limit discharges up 6 hours ahead, significantly outperforming other models. Therefore, model, its robust adaptability fluctuations, has potential broader applications across WWTPs different processes, as well providing strategies system regulation emergency conditions.

Язык: Английский

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Rapid reactivation of long-term frozen preservation anammox granular sludge by biochar: Performance, mechanism and artificial neural network optimization

Journal of Water Process Engineering, Год журнала: 2024, Номер 63, С. 105516 - 105516

Опубликована: Май 19, 2024

Язык: Английский

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Machine Learning Methods for the Prediction of Wastewater Treatment Efficiency and Anomaly Classification with Lack of Historical Data

Applied Sciences, Год журнала: 2024, Номер 14(22), С. 10689 - 10689

Опубликована: Ноя. 19, 2024

This study examines an algorithm for collecting and analyzing data from wastewater treatment facilities, aimed at addressing regression tasks predicting the quality of treated classification preventing emergency situations, specifically filamentous bulking activated sludge. The feasibility using obtained under laboratory conditions simulating technological process as a training dataset is explored. A small collected actual plants considered test dataset. For both tasks, best results were achieved gradient-boosting models CatBoost family, yielding metrics SMAPE = 9.1 ROC-AUC 1.0. set most important predictors modeling was selected each target features.

Язык: Английский

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Maintenance 4.0 for HVAC Systems: Addressing Implementation Challenges and Research Gaps

Smart Cities, Год журнала: 2025, Номер 8(2), С. 66 - 66

Опубликована: Апрель 10, 2025

This article explores the integration of Maintenance 4.0 into HVAC (heating, ventilation, and air conditioning) systems, highlighting its essential role within framework Industry 4.0. utilizes advanced technologies such as artificial intelligence IoT sensing technologies. It also incorporates sophisticated data management techniques to transform maintenance strategies indoor ventilation systems. These innovations work together enhance energy efficiency, quality, overall system performance. The paper provides an overview various frameworks, discussing sensors in real-time monitoring environmental conditions, equipment health, consumption. highlights how AI-driven analytics, supported by data, enable predictive fault detection. Additionally, identifies key research gaps challenges that hinder widespread implementation 4.0, including issues related model interpretability, integration, scalability. proposes solutions address these challenges, techniques, explainable AI models, robust strategies, user-centered design approaches. By addressing gaps, this aims accelerate adoption contributing more sustainable, efficient, intelligent built environments.

Язык: Английский

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Leveraging big data to elucidate the impact of heavy metal nanoparticles on anammox processes in wastewater treatment

Journal of Environmental Management, Год журнала: 2025, Номер 382, С. 125243 - 125243

Опубликована: Апрель 16, 2025

Язык: Английский

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Evaluating the Mechanisms and Efficiency of Johkasou Systems for Decentralized Domestic Effluent Treatment: A Review

Water, Год журнала: 2024, Номер 16(16), С. 2266 - 2266

Опубликована: Авг. 12, 2024

Johkasou systems have emerged as quintessential examples of decentralized wastewater treatment technologies due to their compact design, easy operation, and robust resistance mechanical impact attributes that are particularly effective in mitigating treating rural domestic wastewater. Although the efficiency process removing nitrogen phosphorus has been well-documented, a comprehensive synthesis underlying mechanisms influencing factors is still elusive. This review seeks elucidate these aspects by detailing biogeochemical pathways involved removal, characterizing key microbial consortia, addressing potential accumulation nitrous oxide (N2O). Furthermore, critically examines various media used on nutrient removal efficacy, with particular emphasis nitrogen. It also proposes range practical adjustments design parameters, including dissolved oxygen (DO), pH, temperature, hydraulic retention time (HRT), enhance performance. Finally, implementation integration ancillary processes actual sewage scenarios synthesized, providing theoretical foundation for advancing methodologies areas.

Язык: Английский

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Ammonia oxidation with bicarbonate as an electron acceptor: An energy-saving process to accumulate nitrite for potential anammox in wastewater

Journal of Water Process Engineering, Год журнала: 2024, Номер 68, С. 106421 - 106421

Опубликована: Ноя. 1, 2024

Язык: Английский

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