AIMC Topic: Water Pollutants, Chemical
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Ecological risks of PFAS in China's surface water: A machine learning approach.
Environment international
Jan 16, 2025
The persistence of per- and polyfluoroalkyl substances (PFAS) in surface water can pose risks to ecosystems, while due to data limitations, the occurrence, risks, and future trends of PFAS at large scales remain unknown. This study investigated the e...
Application of supervised learning models for enhanced lead (II) removal from wastewater via modified cellulose nanocrystals (CNCs).
Journal of environmental science and health. Part A, Toxic/hazardous substances & environmental engineering
Jan 16, 2025
Heavy metal ions are acknowledged to impact the environment and human health adversely. CNCs are effective materials for removing heavy metal ions in industrial applications and process innovations since they can be used in static and dynamic adsorpt...
Interpretable machine learning reveals transport of aged microplastics in porous media: Multiple factors co-effect.
Water research
Jan 12, 2025
Microplastics (MPs) easily migrate into deeper soil layers, posing potential risks to subterranean habitats and groundwater. However, the mechanisms governing the vertical migration of MPs in soil, particularly aged MPs, remain unclear. In this study...
Integrating machine learning, suspect and nontarget screening reveal the interpretable fates of micropollutants and their transformation products in sludge.
Journal of hazardous materials
Jan 11, 2025
Activated sludge enriches vast amounts of micropollutants (MPs) when wastewater is treated, posing potential environmental risks. While standard methods typically focus on target analysis of known compounds, the identity, structure, and concentration...
Assessment of groundwater chemistry to predict arsenic contamination from a canal commanded area: applications of different machine learning models.
Environmental geochemistry and health
Jan 9, 2025
Groundwater arsenic (As), contamination is a significant issue worldwide including China and Pakistan, particularly in canal command areas. In this study, 131 groundwater samples were collected, and three machine learning models [Random Forest (RF), ...
CLSSATP: Contrastive learning and self-supervised learning model for aquatic toxicity prediction.
Aquatic toxicology (Amsterdam, Netherlands)
Jan 7, 2025
As compound concentrations in aquatic environments increase, the habitat degradation of aquatic organisms underscores the growing importance of studying the impact of chemicals on diverse aquatic populations. Understanding the potential impacts of di...
Polymer Biodegradation in Aquatic Environments: A Machine Learning Model Informed by Meta-Analysis of Structure-Biodegradation Relationships.
Environmental science & technology
Jan 7, 2025
Polymers are widely produced and contribute significantly to environmental pollution due to their low recycling rates and persistence in natural environments. Biodegradable polymers, while promising for reducing environmental impact, account for less...
Optimal selection of machine learning algorithms for ciprofloxacin prediction based on conventional water quality indicators.
Ecotoxicology and environmental safety
Jan 6, 2025
The long-term presence of antibiotics in the aquatic environment will affect ecology and human health. Techniques for determining antibiotics are often time-consuming, labor-intensive and costly, and it is desirable to seek new methods to achieve rap...
Trace detection of antibiotics in wastewater using tunable core-shell nanoparticles SERS substrate combined with machine learning algorithms.
Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Jan 5, 2025
Surface-enhanced Raman scattering (SERS) show great potential for rapid and highly sensitive detection of trace amounts of contamination from the environment in the surface aquatic ecosystem. The widespread use of antibiotics has resulted in serious ...
Advancements and challenges in microplastic detection and risk assessment: Integrating AI and standardized methods.
Marine pollution bulletin
Jan 4, 2025
Microplastics (MPs) pose significant threats to ecosystems and human health due to their persistence and widespread distribution. This paper provides a comprehensive review of sampling methods for MPs in aquatic environments, soils, and biological sa...
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