AIMC Topic: Water Pollutants, Chemical

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Reimagining the Kendall plot: using N and O of nitrate and advanced machine learning to improve N pollutant source classification.

Isotopes in environmental and health studies
Nitrate () pollution is a serious water quality issue in many countries due to contamination of lakes, rivers, and aquifers by intensive agriculture practices and inadequate wastewater management. Nitrate pollution and associated cultural eutrophicat...

Biohybrid microrobots with a Spirulina skeleton and MOF skin for efficient organic pollutant adsorption.

Nanoscale
Wastewater treatment is a key component in maintaining environmental health and sustainable urban life, and the rapid development of micro/nanotechnology has opened up new avenues for more efficient treatment processes. This work developed a novel bi...

The spatiotemporal evolution of dissolved-phase NAPL plumes revealed by the integrated groundwater quality and machine learning models.

Water research
Rapid prediction of dissolved-phase contamination plume distributions is crucial for emergency remediation of aquifers contaminated with non-aqueous phase liquids (NAPLs). However, collecting and analyzing contaminated groundwater samples is expensiv...

Sentinel-2 imagery coupled with machine learning to modelling water turbidity in the Doce River Basin, Brazil.

Environmental monitoring and assessment
Remote sensing and machine learning are techniques that can be used to monitor water quality properties, surpassing the limitations of the conventional techniques. Turbidity is an important water quality property directly influenced by the Fundão dam...

Antioxidant activity of Mentha piperita phenolics on arsenic induced oxidative stress, biochemical alterations, and cyto-genotoxicity in fish, Channa punctatus.

Fish physiology and biochemistry
The study aims to investigate the synergistic antioxidant effects of the phenolics present in Mentha piperita (MP) against arsenic trioxide-induced oxidative stress, biochemical alteration, and cyto-genotoxicity in the fish, Channa punctatus. The phe...

Risk assessment of potentially toxic elements and mapping of groundwater pollution indices using soft computer models in an agricultural area, Northeast Algeria.

Journal of hazardous materials
Groundwater (GW) quality and contamination by potentially toxic elements (PTEs) are major concerns for environmental sustainability, particularly in arid regions. The aim of this study was to assess the human health risks associated with GW contamina...

Artificial intelligence based detection and control strategies for river water pollution: A comprehensive review.

Journal of contaminant hydrology
Water quality (WQ) is a metric for assessing the overall health and safety of water bodies like a river. Owing to the habitation of anthropogenic habitation around its basin, the rivers can become one of the most contaminated water sources globally. ...

Integrated machine learning based groundwater quality prediction through groundwater quality index for drinking purposes in a semi-arid river basin of south India.

Environmental geochemistry and health
The main objective of this study is to predict and monitor groundwater quality through the use of modern Machine Learning (ML) techniques. By employing ML techniques, the research effectively evaluates groundwater quality to forecast its future trend...

Explainable machine learning models enhance prediction of PFAS bioactivity using quantitative molecular surface analysis-derived representation.

Water research
The extensive use of per- and polyfluoroalkyl substances (PFAS) in industrial and consumer products poses health risks due to their toxicity. Computational toxicology approaches, particularly quantitative structure-activity relationship (QSAR) models...

AI-aided chronic mixture risk assessment along a small European river reveals multiple sites at risk and pharmaceuticals being the main risk drivers.

Environment international
The vast amount of registered chemicals leads to a high diversity of substances occurring in the environment and the creation of new substances outpaces chemical risk assessment as well as monitoring strategies. Hence, risk assessment strategies need...