AIMC Topic: Waste Disposal, Fluid

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Machine learning for monitoring per- and polyfluoroalkyl substance (PFAS) in California's wastewater treatment plants: An assessment of occurrence and fate.

Journal of hazardous materials Apr 1, 2025
Wastewater treatment plants (WWTPs) are significant sources of per- and polyfluoroalkyl substances (PFAS) pollution, but comprehensive monitoring and management are impractical and cost-prohibitive. To strengthen monitoring programs, we developed mac...
California Machine Learning Water Pollutants, Chemical Wastewater Fluorocarbons Waste Disposal, Fluid Environmental Monitoring
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Effective evaluation of greenhouse gases (GHGs) emissions from anoxic/oxic (A/O) process of regenerated papermaking wastewater treatment through hybrid deep learning techniques: Leveraging the critical role of water quality indicators.

Journal of environmental management Apr 1, 2025
Accurate accounting of greenhouse gases (GHGs) emissions from industrial wastewater treatment processes/plants with high organic concentration and fluctuating inflows is crucial for the calculation and management of carbon emissions. The impacts of w...
Wastewater Deep Learning Neural Networks, Computer Greenhouse Gases Waste Disposal, Fluid Water Quality
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Treatment options of nitrogen heterocyclic compounds in industrial wastewater: From fundamental technologies to energy valorization applications and future process design strategies.

Water research Mar 29, 2025
Nitrogen heterocyclic compounds (NHCs) widely exist in industrial wastewater and presented significant environmental and health risks due to their toxicity and persistence. This review addressed the challenges in treating NHCs in industrial wastewate...
Wastewater Water Pollutants, Chemical Water Purification Waste Disposal, Fluid Industrial Waste Heterocyclic Compounds
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Enhancing process monitoring and control in novel carbon capture and utilization biotechnology through artificial intelligence modeling: An advanced approach toward sustainable and carbon-neutral wastewater treatment.

Chemosphere Mar 17, 2025
Integrating carbon capture and utilization (CCU) technologies into wastewater treatment plants (WWTPs) is essential for mitigating greenhouse gas (GHG) emissions and enhancing environmental sustainability, but further advancements in process monitori...
Carbon Sequestration Greenhouse Gases Wastewater Photobioreactors Waste Disposal, Fluid Carbon Dioxide Biotechnology Neural Networks, Computer Artificial Intelligence Carbon
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Machine learning algorithms for predicting membrane bioreactors performance: A review.

Journal of environmental management Mar 17, 2025
Membrane bioreactors (MBR) are recognized as a sustainable technology for treating polluted effluents. Machine learning (ML) algorithms have emerged as a modeling option to predict pollutant removal and operational variables such as membrane fouling,...
Machine Learning Wastewater Algorithms Waste Disposal, Fluid Bioreactors Neural Networks, Computer Membranes, Artificial
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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...
Wastewater Water Purification Sewage Large Language Models Waste Disposal, Fluid Models, Theoretical
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Development of artificial neural network model for anaerobic digestion-elutriated phase treatment.

Journal of environmental management Mar 5, 2025
Nonlinear autoregressive exogenous (NARX) neural network models were used to forecast the time-series profiles of anaerobic digestion-elutriated phase treatment (ADEPT). Experimental data from the operation of the pilot plant and lab-scale reactor we...
Biofuels Waste Disposal, Fluid Anaerobiosis Methane Bioreactors Neural Networks, Computer
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A machine learning approach to feature selection and uncertainty analysis for biogas production in wastewater treatment plants.

Waste management (New York, N.Y.) Feb 21, 2025
The growing demand for efficient waste management solutions and renewable energy sources has driven research into predicting biogas production at wastewater treatment plants. This study outlines a methodology starting with data collection from a full...
Uncertainty Waste Disposal, Fluid Machine Learning Biofuels Wastewater
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Carbon source dosage intelligent determination using a multi-feature sensitive back propagation neural network model.

Journal of environmental management Feb 15, 2025
The carbon reduction concept drives the development of low-carbon and sustainable wastewater treatment plant (WWTP) operation technologies. In the denitrification stage of WWTPs in China, there are widespread problems of uneconomical dosage consumpti...
Nitrogen Waste Disposal, Fluid Carbon Wastewater Neural Networks, Computer China Machine Learning
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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...
Machine Learning Bayes Theorem Wastewater Water Purification Sewage Algorithms Waste Disposal, Fluid
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