AIMC Topic: Sewage
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Responses of Microbial Community to Heterogeneous Dissolved Organic Nitrogen Constituents in the Hyporheic Zones of Treated Sewage-Dominated Rivers.
Microbial ecology
Jul 2, 2025
The hyporheic zone (HZ) of treated sewage-dominated rivers serves as a critical biogeochemical hotspot for dissolved organic nitrogen (DON) transformation, yet the mechanisms linking DON chemodiversity to microbial community dynamics remain poorly re...
Machine learning-based optimization of biogas and methane yields in UASB reactors for treating domestic wastewater.
Biodegradation
Jun 26, 2025
This study aimed to optimize biogas and methane production from Up-flow anaerobic sludge blanket reactors for treating domestic wastewater using advanced machine learning models-namely, eXtreme Gradient Boosting (XGBoost) and its hybridized form, XGB...
Machine learning approaches for predicting antibiotic resistance genes abundance changes during biological nitrogen removal process.
Journal of environmental management
Jun 20, 2025
Wastewater treatment plants (WWTPs) serve as reservoirs for multiple antimicrobial agents (AAs), thereby promoting the risk of antibiotic resistance genes (ARGs) transmission in sewage and sludge during biological nitrogen removal (BNR) processes. An...
Optimization of nitrogen removal through an intelligent automated operational strategy based on real-time process simulation in an A2O membrane bioreactor.
Journal of environmental management
Jun 17, 2025
In this study, an intelligent automated operational strategy (IAOS) was developed and evaluated to enhance nitrogen removal efficiency in an anaerobic-anoxic-oxic (A2O) membrane bioreactor (MBR). To effectively respond to fluctuations in inflow load,...
Surveillance of SARS-CoV-2 RNA in wastewater treatment plants in Türkiye, Istanbul: a long-term study and statistical analysis.
Environmental monitoring and assessment
May 12, 2025
Wastewater-based epidemiology (WBE) is a powerful method that allows community surveillance to identify diseases/pandemic dynamics in a city, especially in metropolitan areas with high overpopulation. This study investigated the detection and quantif...
Multi-agent large language model frameworks: Unlocking new possibilities for optimizing wastewater treatment operation.
Environmental research
Mar 14, 2025
Wastewater treatment plants (WWTPs) are highly complex systems where biological, chemical, and physical processes interact dynamically, creating significant operational challenges. Traditional modeling approaches, such as Activated Sludge Models (ASM...
Water level estimation in sewage pipes using texture-based methods and machine learning algorithms.
Water science and technology : a journal of the International Association on Water Pollution Research
Mar 10, 2025
Water companies use closed-circuit television (CCTV) to inspect the condition of sewage pipes. The reports generated by surveyors help companies to plan for the maintenance and rehabilitation of sewage pipes. A surveyor needs to record the water leve...
Effect of training sample size, image resolution and epochs on filamentous and floc-forming bacteria classification using machine learning.
Journal of environmental management
Mar 9, 2025
Computer vision techniques can expedite the detection of bacterial growth in wastewater treatment plants and alleviate some of the shortcomings associated with traditional detection methods. In recent years, researchers capitalized on this potential ...
Bayesian Optimization-Enhanced Reinforcement learning for Self-adaptive and multi-objective control of wastewater treatment.
Bioresource technology
Feb 9, 2025
Controllers of wastewater treatment plants (WWTPs) often struggle to maintain optimal performance due to dynamic influent characteristics and the need to balance multiple operational objectives. In this study, Reinforcement Learning (RL) algorithms a...
Semi-supervised learning-based identification of the attachment between sludge and microparticles in wastewater treatment.
Journal of environmental management
Jan 31, 2025
Monitoring the microparticle transfer process in wastewater treatment systems is crucial for improving treatment performance. Supervised deep learning methods show high performance to automatically detect particles, but they rely on vast amounts of l...
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