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Water Pollutants, Chemical

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Artificial intelligence modeling and experimental studies of oily pollutants uptake from water using ZIF-8/carbon fiber nanostructure.

Journal of environmental management
In this study, the experimental and modeling of oily pollutants (crude oil, asphaltene, and maltene) uptake by ZIF-8/carbon fiber nanostructure was investigated. The influence of pollutant type, concentration, ionic strength, and sorption time on upt...

Quality evaluation parameter and classification model for effluents of wastewater treatment plant based on machine learning.

Water research
With the growing consensus of emerging pollutants and biological toxicity risks in wastewater treatment plant (WWTP) effluents, traditional water quality management based on general chemical parameters no longer meets the new challenges. Here, a firs...

From microplastics to pixels: testing the robustness of two machine learning approaches for automated, Nile red-based marine microplastic identification.

Environmental science and pollution research international
Despite the urgent need for accurate and robust observations of microplastics in the marine environment to assess current and future environmental risks, existing procedures remain labour-intensive, especially for smaller-sized microplastics. In addi...

Derivation of marine water quality criteria for copper based on artificial neural network model.

Environmental pollution (Barking, Essex : 1987)
The water chemical effects of copper have been a focus in the study of water quality criteria (WQC). Currently, multiple regression models are commonly used to quantitatively describe the impact of environmental factors on Cu toxicity in WQC studies....

A machine learning based framework to tailor properties of nanofiltration and reverse osmosis membranes for targeted removal of organic micropollutants.

Water research
Nanofiltration (NF) and reverse osmosis (RO) membranes play an increasingly important role in the removal of organic micropollutants (OMPs), which puts higher demands on the customization of membranes suitable for OMPs removal based on the rejection ...

Machine learning prediction and exploration of phosphorus migration and transformation during hydrothermal treatment of biomass waste.

The Science of the total environment
Hydrothermal treatment (HTT) held promise for phosphorus (P) recovery from high-moisture biomass. However, traditional experimental studies of P hydrothermal conversion were time-consuming and labor-intensive. Thus, based on biomass characteristics a...

Perfluorooctanoic Acids (PFOA) removal using electrochemical oxidation: A machine learning approach.

Journal of environmental management
The urgent need to eliminate Perfluorooctanoic Acid (PFOA) has positioned electrooxidation (EO) as a key solution for pollutant degradation. This study evaluates several machine learning (ML) models, including K-Nearest Neighbors (KNN), Decision Tree...

A novel interpretable machine learning and metaheuristic-based protocol to predict and optimize ciprofloxacin antibiotic adsorption with nano-adsorbent.

Journal of environmental management
The existence of antibiotics in water sources poses substantial hazards to both the environment and public health. To effectively monitor and combat this problem, accurate predictive models are essential. This research focused on employing machine le...

Understanding the mechanism of microplastic-associated antibiotic resistance genes in aquatic ecosystems: Insights from metagenomic analyses and machine learning.

Water research
The pervasive presence of microplastics (MPs) in aquatic systems facilitates the transmission of antibiotic resistance genes (ARGs), thereby posing risks to ecosystems and human well-being. However, owing to variations in environmental backgrounds an...

Task decomposition strategy based on machine learning for boosting performance and identifying mechanisms in heterogeneous activation of peracetic acid process.

Water research
Heterogeneous activation of peracetic acid (PAA) process is a promising method for removing organic pollutants from water. Nevertheless, this process is constrained by several complex factors, such as the selection of catalysts, optimization of react...