AIMC Topic: Water Pollutants, Chemical

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Basic research for identification and classification of organophosphorus pesticides in water based on ultraviolet-visible spectroscopy information.

Environmental science and pollution research international
In this study, the goal was to develop a method for detecting and classifying organophosphorus pesticides (OPPs) in bodies of water. Sixty-five samples with different concentrations were prepared for each of the organophosphorus pesticides, namely ch...

Validity of zinc oxide nanoparticles biosynthesized in food wastes extract in treating real samples of printing ink wastewater; prediction models using feed-forward neural network (FFNN).

Chemosphere
In the present study, biosynthesized ZnO nanoparticles in food wastewater extract (FWEZnO NPs) was used in the photocatalytic degradation of real samples of printing ink wastewater. FWEZnO NPs were prepared using green synthesis methods using a compo...

Application of machine learning models to improve the prediction of pesticide photodegradation in water by ZnO-based photocatalysts.

Chemosphere
Pesticide pollution has been posing a significant risk to human and ecosystems, and photocatalysis is widely applied for the degradation of pesticides. Machine learning (ML) emerges as a powerful method for modeling complex water treatment processes....

Application of machine learning in the study of development, behavior, nerve, and genotoxicity of zebrafish.

Environmental pollution (Barking, Essex : 1987)
Machine learning (ML) as a novel model-based approach has been used in studying aquatic toxicology in the environmental field. Zebrafish, as an ideal model organism in aquatic toxicology research, has been widely used to study the toxic effects of va...

Application of artificial intelligence in modeling of nitrate removal process using zero-valent iron nanoparticles-loaded carboxymethyl cellulose.

Environmental geochemistry and health
This study explores nitrate reduction in aqueous solutions using carboxymethyl cellulose loaded with zero-valent iron nanoparticles (Fe-CMC). The structures of this nano-composite were characterized using various techniques. Based on the characteriza...

Assessment of groundwater quality in arid regions utilizing principal component analysis, GIS, and machine learning techniques.

Marine pollution bulletin
Assessing water quality in arid regions is vital due to scarce resources, impacting health and sustainable management.This study examines groundwater quality in Assuit Governorate, Egypt, using Principal Component Analysis, GIS, and Machine Learning ...

Prediction of micropollutant degradation kinetic constant by ultrasonic using machine learning.

Chemosphere
A prediction model based on XGBoost is proposed for ultrasonic degradation of micropollutants' kinetic constants. After parameter optimization through iteration, the model achieves Evaluation metrics with R and SMAPE reaching 0.99 and 2.06%, respecti...

Causal prior-embedded physics-informed neural networks and a case study on metformin transport in porous media.

Water research
This study introduces a novel approach to transport modelling by integrating experimentally derived causal priors into neural networks. We illustrate this paradigm using a case study of metformin, a ubiquitous pharmaceutical emerging pollutant, and i...

Appraising water resources for irrigation and spatial analysis based on fuzzy logic model in the tribal-prone areas of Bangladesh.

Environmental monitoring and assessment
The lack of quality water resources for irrigation is one of the main threats for sustainable farming. This pioneering study focused on finding the best area for farming by looking at irrigation water quality and analyzing its location using a fuzzy ...

Applicability of machine learning techniques to analyze Microplastic transportation in open channels with different hydro-environmental factors.

Environmental pollution (Barking, Essex : 1987)
This research utilized machine learning to analyze experiments conducted in an open channel laboratory setting to predict microplastic transport with varying discharge, velocity, water depth, vegetation pattern, and microplastic density. Four machine...