AIMC Topic: Water Pollutants, Chemical

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Chitosan-based adsorbents for remediation of toxic dyes from wastewater: A review on adsorption mechanism, reusability, machine learning based modeling and future perspectives.

International journal of biological macromolecules
The disposal of recalcitrant dyes in aquatic environments from various industrial sectors is a threat to both the plant and animal kingdom. The presence of dyes in various water bodies undermines the availability of uncontaminated drinking water and ...

Comparing neural network architectures for simulating pollutant loads and first flush events in urban watersheds: Balancing specialization and generalization.

Chemosphere
This study investigates the effectiveness of artificial neural networks (ANNs) models in predicting urban water quality, specifically focusing on first flush (FF) event classification and pollutant event mean load (EML) predictions for total suspende...

Heavy metals prediction system in groundwater using online sensor and machine learning for water management: the case of typical industrial park.

Environmental pollution (Barking, Essex : 1987)
With the expansion of human industrial activities, heavy metal contamination in groundwater environments has become increasingly severe. Environmental management agencies invest significant financial resources into groundwater monitoring, primarily d...

Rapid and sensitive detection of pharmaceutical pollutants in aquaculture by aluminum foil substrate based SERS method combined with deep learning algorithm.

Analytica chimica acta
BACKGROUND: Pharmaceutical residual such as antibiotics and disinfectants in aquaculture wastewater have significant potential risks for environment and human health. Surface enhanced Raman spectroscopy (SERS) has been widely used for the detection o...

Machine Learning-Assisted Molecular Structure Embedding for Accurate Prediction of Emerging Contaminant Removal by Ozonation Oxidation.

Environmental science & technology
Ozone has demonstrated high efficacy in depredating emerging contaminants (ECs) during drinking water treatment. However, traditional quantitative structure-activation relationship (QSAR) models often fall short in effectively normalizing and charact...

UAV-based water pollutants detection and classification framework using multi-modal and multi-sensor ensemble learning.

Environmental monitoring and assessment
The massive increment in water pollutants due to the release of plastic, industrial, and household waste has threatened the delicate balance of ecosystems and the well-being of human life. Therefore, detection and monitoring of such water pollutants ...

Satellite Remote Sensing-Implemented Nontargeted Screening of Emerging Contaminant Fingerprints in a River-to-Ocean Continuum through Interpretable Machine Learning: The Pivotal Intermediary Role of Dissolved Organic Matter.

Environmental science & technology
Emerging contaminants (ECs) can exert irreversible health impacts on humans, even at trace concentrations. Currently, nontargeted screening of ECs has been developed for their assessment, which requires sophisticated instrumentation. Although satelli...

Prediction of total phosphorus removal in hybrid constructed wetlands: a machine learning approach for rice mill wastewater treatment.

Water environment research : a research publication of the Water Environment Federation
Efficient prediction of pollutant concentrations in constructed wetlands is critical for optimizing treatment performance, yet existing methodologies often fail to account for the influence of meteorological conditions and flow rate variations in rea...

Application of artificial intelligence for nutrient estimation in surface water bodies of basins with intensive agriculture.

Integrated environmental assessment and management
Eutrophication is one of the most relevant concerns due to the risk to water supply and food security. Nitrogen and phosphorus chemical species concentrations determined the risk and magnitude of eutrophication. These analyses are even more relevant ...

Comparison and prediction of shallow groundwater nitrate in Shaying River basin based on urban distribution using multiple machine learning approaches.

Water environment research : a research publication of the Water Environment Federation
Groundwater, a pivotal water resource in numerous regions worldwide, confronts formidable challenges posed by severe nitrate pollution. Traditional research methodologies aimed at addressing groundwater nitrate contamination frequently struggle to ac...