AIMC Topic: Water Pollutants, Chemical
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Dissolved organic carbon estimation in lakes: Improving machine learning with data augmentation on fusion of multi-sensor remote sensing observations.
Water research
Feb 21, 2025
This paper presents a novel approach for estimating Dissolved Organic Carbon (DOC) concentrations in lakes considering both carbon sources and sink operators. Despite the critical role of DOC, the combined application of machine learning, as a robust...
Driving factors of TOC concentrations in four different types of estuaries (canal, urban, agricultural, and natural estuaries) identified by machine learning technique.
Marine pollution bulletin
Feb 21, 2025
Mangroves are among the most significant organic carbon sinks on Earth. However, the drivers of mangrove carbon remain poorly understood due to the lack of data on organic carbon across different types of estuaries. In this study, boosted regression ...
Classification and predictive leaching risk assessment of construction and demolition waste using multivariate statistical and machine learning analyses.
Waste management (New York, N.Y.)
Feb 19, 2025
Managing construction and demolition waste (CDW) poses serious concerns regarding landfilling and recycling because of the potential release of hazardous elements after leaching. Ceramic materials such as bricks, tiles, and porcelain account for more...
Using artificial intelligence tools for data quality evaluation in the context of microplastic human health risk assessments.
Environment international
Feb 17, 2025
Concerns about the negative impacts of microplastics on human health are increasing in society, while exposure and risk assessments require high-quality, reliable data. Although quality assurance and -control (QA/QC) frameworks exist to evaluate the ...
Emerging applications of fluorescence excitation-emission matrix with machine learning for water quality monitoring: A systematic review.
Water research
Feb 13, 2025
Fluorescence excitation-emission matrix (FEEM) spectroscopy is increasingly utilized in water quality monitoring due to its rapid, sensitive, and non-destructive measurement capabilities. The integration of machine learning (ML) techniques with FEEM ...
Data-Driven Insights into Resin Screening for Targeted Per- and Polyfluoroalkyl Substances Removal Using Machine Learning.
Environmental science & technology
Feb 11, 2025
In this study, we address the challenge of screening resins and optimizing operation conditions for the removal of 43 perfluoroalkyl and polyfluoroalkyl substances (PFASs), spanning both long- and short-chain fluorocarbon variants, across diverse wat...
Exploring the response of bacterial community functions to microplastic features in lake ecosystems through interpretable machine learning.
Environmental research
Feb 10, 2025
Microplastics (MPs) are ubiquitous and have various characteristics. However, their impacts on bacterial community functions in lakes remain elusive. In this study, we identified 33 different MPs features including their abundance, shape, color, size...
Classification and regression machine learning models for predicting mixed toxicity of carbamazepine and its transformation products.
Environmental research
Feb 8, 2025
Carbamazepine (CBZ) and its transformation products (TPs) often occur in aquatic environments in the form of mixtures, posing potential risks to ecosystems. However, establishing standardized protocols for synthesizing, isolating, and acquiring these...
Integration of machine learning and meta-analysis reveals the behaviors and mechanisms of antibiotic adsorption on microplastics.
Journal of hazardous materials
Feb 7, 2025
Microplastics (MPs) can adsorb antibiotics (ATs) to cause combined pollution in the environment. Research on this topic has been limited to specific types of MPs and ATs, resulting in inconsistent findings, particularly for the influencing factors an...
Machine learning-assisted prediction of engineered carbon systems' capacity to treat textile dyeing wastewater via adsorption technology.
Environmental monitoring and assessment
Feb 1, 2025
Dyes are widely used in industries like printing, cosmetics, paper, leather processing, textiles, and manufacturing to add color to products. However, improper disposal of dyes into wastewater has raised major concerns due to their harmful effects on...
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