AIMC Topic: Water Purification

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An artificial intelligence modeling framework based on microbial community structure prediction enhances the pollutant removal efficiency of the algae-bacteria granular sludge system.

Journal of environmental management
Algae-bacteria granular sludge (ABGS) technology is a new energy-saving and low-carbon water treatment technology based on the algae-bacteria symbiotic system. However, due to its complex internal microbial system, the regulation mechanism of ABGS is...

Magnetically Driven Living Microrobot Swarms for Aquatic Micro- and Nanoplastic Cleanup.

ACS nano
Micro- and nanoplastic pollution is pervasive worldwide, infiltrating drinking water and food chains, accumulating in the human body, and posing serious threats to public health and ecosystems. Despite these urgent challenges, effective strategies to...

Optimizing models for the prediction of one step ahead extreme flows to wastewater treatment plants using different synthetic sampling methods.

Journal of environmental management
High-flow events that significantly impact Water Resource Recovery Facility (WRRF) operations are rare, but accurately predicting these flows could improve treatment operations. Data-driven modeling approaches could be used; however, high flow events...

A methodology for coagulant virtual testing to improve dissolved organic matter removal in surface water treatment.

The Science of the total environment
Coagulation is one of the most crucial steps in a Drinking Water Treatment Plant (DWTP). The coagulant dose required for the removal of particles and natural organic matter (NOM) is typically determined through jar tests. However, this method is time...

Escaping Historical Lock-in─Redesigning Wastewater Treatment Plants and Their Microbiomes for the 21st Century.

Environmental science & technology
Wastewater treatment plants (WWTPs) have gradually, over the last hundred years, been designed and extended to deal with a sequence of problems, including a) odor, b) suspended solids, c) organics, d) ammonia, e) nitrate and phosphate, and f) recalci...

Insight mechanism of ANN model for denitrification in spouted bed bioreactor.

Scientific reports
Numerous technologies have been developed to remove nitrate from wastewater due to its significant health and environmental impacts. In the present study, an isolate of Pseudomonas syringae was utilized to investigate the denitrification rate using i...

AI-driven wastewater management through comparative analysis of feature selection techniques and predictive models.

Scientific reports
The integration of artificial intelligence (AI) in wastewater treatment management offers a promising approach to optimizing effluent quality predictions and enhancing operational efficiency. This study evaluates the performance of machine learning m...

Machine learning-based identification of wastewater treatment plant-specific microbial indicators using 16S rRNA gene sequencing.

Scientific reports
Effluent released from municipal wastewater treatment plants reflects the microbial communities responsible for degrading and removing contaminants within the plants. Monitoring this effluent offers essential insights into its environmental impacts, ...

Underestimated roles of phages in biological wastewater treatment systems: Recent advances and challenges.

Journal of hazardous materials
Bacteriophages (phages) are vital components in biological wastewater ecosystems, whose concentrations are far exceeding those bacteria. Despite their importance, they are often overlooked and regarded as the "dark matter" in biological treatment pro...

Multimodal Learning-Assisted Identification of Effluent Water Quality and Toxicity in Wastewater Treatment Plants.

Environmental science & technology
Effluent of wastewater treatment plants (WWTPs) poses significant ecological risks due to potential biological toxicity, demanding effective monitoring and assessment of water quality and toxicity. However, the complexity of the wastewater treatment ...