AIMC Topic: Soil Pollutants
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Modeling PFAS Sorption in Soils Using Machine Learning.
Environmental science & technology
Apr 11, 2025
In this study, we introduce PFASorptionML, a novel machine learning (ML) tool developed to predict solid-liquid distribution coefficients () for per- and polyfluoroalkyl substances (PFAS) in soils. Leveraging a data set of 1,274 entries for PFAS in ...
Applications of machine learning in potentially toxic elemental contamination in soils: A review.
Ecotoxicology and environmental safety
Apr 6, 2025
Soil contamination by potentially toxic elements (PTEs) poses substantial risks to the environment and human health. Traditional investigational methods are often inadequate for large-scale assessments because they are time-consuming, costly, and hav...
Assessing potential toxic metal threats in tea growing soils of India with soil health indices and machine learning technologies.
Environmental monitoring and assessment
Mar 25, 2025
This study explores the impact of potentially toxic metals (PTMs) contamination in Indian tea-growing soils on ecosystems, soil quality, and human health using machine learning and statistical analysis. A total of 148 surface soil samples were collec...
Machine learning for predictive mapping of exceedance probabilities for potentially toxic elements in Czech farmland.
Journal of environmental management
Mar 24, 2025
For efficient decision-making and optimal land management trajectories, information on soil properties in relation to safety guidelines should be processed from point inventories to surface predictive maps. For large-scale predictive mapping, very fe...
Addressing data handling shortcomings in machine learning studies on biochar for heavy metal remediation.
Journal of hazardous materials
Mar 10, 2025
Recent advancements in machine learning (ML) technologies have significantly enhanced their applications in environmental sciences, particularly in the domains of soil and water remediation. This paper reviews recent studies that employ ML to optimiz...
Unlocking the potential of Eudrilus eugeniae in mitigating the pollution risk of pesticides and heavy metals: Fostering machine learning tactics to optimize environmental health.
The Science of the total environment
Mar 8, 2025
Agro-industrial waste management remains a critical challenge in sustainable development, particularly due to contamination with heterogeneous micropollutants such as heavy metals (HMs), pesticides, and polyphenols. This study explores an innovative ...
Construction of multi-metal interspecies correlation estimation models based on typical soil scenarios.
Environmental research
Feb 28, 2025
The ecological risk assessment of metals in soils is essential for soil pollution management. However, regional soil heterogeneity and species diversity need to be considered when making these assessments. Therefore, an interspecies correlation estim...
Uncovering soil heavy metal pollution hotspots and influencing mechanisms through machine learning and spatial analysis.
Environmental pollution (Barking, Essex : 1987)
Feb 21, 2025
Soil heavy metal (HM) pollution is a significant and widespread environmental issue in China, highlighting the need to quantify influencing factors and identify priority concern areas for effective prevention and management. Based on published litera...
A novel graph convolutional neural network model for predicting soil Cd and As pollution: Identification of influencing factors and interpretability.
Ecotoxicology and environmental safety
Feb 19, 2025
Soil pollution caused by toxic metals poses serious threats to the ecological environment and human well-being. Accurately predicting toxic metal concentrations is critical for safeguarding soil environmental security. However, the distribution of so...
Development of a method for detecting and classifying hydrocarbon-contaminated soils via laser-induced breakdown spectroscopy and machine learning algorithms.
Environmental science and pollution research international
Feb 5, 2025
In recent years, there has been a significant increase in oil exploration and exploitation activities, resulting in spills that pose a severe threat to the environment and public health. The present work aims to develop a method to detect and classif...
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