Recent developments in (photo)electrocatalytic materials for wastewater treatment and resource recovery

Applied Catalysis O Open, Journal Year: 2025, Volume and Issue: unknown, P. 207033 - 207033

Published: Feb. 1, 2025

Language: Английский

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Modelling and optimization of membrane process for removal of biologics (pathogens) from water and wastewater: Current perspectives and challenges

Heliyon, Journal Year: 2024, Volume and Issue: 10(9), P. e29864 - e29864

Published: April 21, 2024

As one of the 17 sustainable development goals, United Nations (UN) has prioritized "clean water and sanitation" (Goal 6) to reduce discharge emerging pollutants disease-causing agents into environment. Contamination by pathogenic microorganisms their existence in treated is a global public health concern. Under natural conditions, frequently prone contamination invasive microorganisms, such as bacteria, viruses, protozoa. This circumstance therefore highlighted critical need for research techniques prevent, treat, get rid pathogens wastewater. Membrane systems have emerged effective ways removing contaminants from wastewater However, few studies examined synergistic or conflicting effects operating conditions on newly developing found Therefore, efficient, dependable, expeditious examination intricate matrix remains significant obstacle. far it can be ascertained, much attention not recently been given optimizing membrane processes develop optimal operation design related pathogen removal this state-of-the-art review aims discuss current trends techniques. In addition, conventional treating pathogenic-containing shortcomings were briefly discussed. Furthermore, derived mathematical models suitable modelling, simulation, control technologies are highlighted. conclusion, challenges facing extensively discussed, future outlooks/perspectives modelling recommended.

Language: Английский

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Research trends on phosphorus removal from wastewater: A review and bibliometric analysis from 2000 to 2022

Journal of Water Process Engineering, Journal Year: 2023, Volume and Issue: 55, P. 104201 - 104201

Published: Sept. 2, 2023

Language: Английский

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Artificial intelligence integration in conventional wastewater treatment techniques: techno-economic evaluation, recent progress and its future direction

International Journal of Environmental Science and Technology, Journal Year: 2024, Volume and Issue: unknown

Published: May 26, 2024

Language: Английский

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Prediction of wastewater quality parameters using adaptive and machine learning models: A South African case study

Journal of Water Process Engineering, Journal Year: 2024, Volume and Issue: 67, P. 106185 - 106185

Published: Sept. 20, 2024

Language: Английский

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Transition from sulfur autotrophic to mixotrophic denitrification: performance with different carbon sources, microbial community and artificial neural network modeling

Chemosphere, Journal Year: 2024, Volume and Issue: unknown, P. 143432 - 143432

Published: Sept. 1, 2024

Language: Английский

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From biomass waste to bioaerogels - An alternative sustainable approach for wastewater remediation

International Journal of Biological Macromolecules, Journal Year: 2024, Volume and Issue: 282, P. 136994 - 136994

Published: Nov. 2, 2024

Language: Английский

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Managing industrial water treatment processes knowledge with knowledge graphs

Intelligent Decision Technologies, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 27, 2025

The paper reviews, represents and captures knowledge about industrial water treatment processes predicative models, in order to facilitate management of relevant knowledge. proposed approach is based on a Knowledge Graph (KG), which integrates process predictive adding context their application usage; improves problem data understanding by facilitating communication between analysts engineers, providing clear, human-readable explanations; facilitates answering process-related questions provides answers that include elements, key performance indicators (KPIs).Further, the includes examples how KG can be used practice. Directions recommendations are provided, as well research guidelines augment generative AI approaches, paving way for development retrieval-augmented models systems.

Language: Английский

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Innovative approaches to greywater micropollutant removal: AI-driven solutions and future outlook

RSC Advances, Journal Year: 2025, Volume and Issue: 15(16), P. 12125 - 12151

Published: Jan. 1, 2025

Greywater constitutes a significant portion of urban wastewater and is laden with numerous emerging contaminants that have the potential to adversely impact public health ecosystem.

Language: Английский

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Artificial neural networks for performance prediction of full-scale wastewater treatment plants: a systematic review

Water Science & Technology, Journal Year: 2023, Volume and Issue: 88(6), P. 1447 - 1470

Published: Aug. 29, 2023

Wastewater treatment plants (WWTPs) are complex systems that must maintain high levels of performance to achieve adequate effluent quality protect the environment and public health. Artificial intelligence machine learning methods have gained attention in recent years for modeling problems, such as wastewater treatment. Although artificial neural networks (ANNs) been identified most common these methods, no study has investigated development configuration models. We conducted a systematic literature review on use ANNs predict removal efficiencies full-scale WWTPs. Three databases were searched, 44 records 667 selected based eligibility criteria. The data extracted from papers showed majority studies used feedforward network model with backpropagation training algorithm plants, particularly terms organic matter indicators. findings this research may help search an optimum design process future similar prediction problems.

Language: Английский

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