AIMC Topic: Environmental Monitoring

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Predicting the amount of toxic metals and metalloids in silt loading using neural networks.

Environmental monitoring and assessment Apr 1, 2025
Material deposited on road surfaces, called road dust, are known to contain different toxic elements. According to particle size, there are different fractions. Particles with an aerodynamic size less than or equal to 75 µm are called silt loading. A...
Dust Environmental Monitoring Metalloids Neural Networks, Computer Metals, Heavy Metals
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Identification of key feature variables and prediction of harmful algal blooms in a water diversion lake based on interpretable machine learning.

Environmental research Mar 28, 2025
Harmful algal blooms (HABs) as an increasing environmental problem in lakes, and water diversion has become a common and effective strategy for mitigating HABs. Early and accurate identification of the occurrence of HABs in lakes is essential for sci...
China Environmental Monitoring Harmful Algal Bloom Machine Learning Lakes
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Assessing climate change and human impacts on runoff and hydrological droughts in the Yellow River Basin using a machine learning-enhanced hydrological modeling approach.

Journal of environmental management Mar 26, 2025
Analyzing the impacts of climate change (CC) and human activities (HA) on hydrological events is important for water resource management. This study quantifies the impacts of CC and HA on runoff and hydrological drought characteristics (HDC) in the Y...
Models, Theoretical Droughts Humans Rivers Environmental Monitoring Machine Learning China Climate Change Hydrology
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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...
Soil Pollutants Metals, Heavy Environmental Monitoring Tea Machine Learning Soil Metals Risk Assessment Humans India
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Optimization of Decision Support Technology for Offshore Oil Condition Monitoring with Carbon Neutrality as the Goal in the Enterprise Development Process.

PloS one Mar 25, 2025
This study aims to explore the integration of the Faster R-CNN (Region-based Convolutional Neural Network) algorithm from deep learning into the MobileNet v2 architecture, within the context of enterprises aiming for carbon neutrality in their develo...
Environmental Monitoring Decision Support Techniques Carbon Neural Networks, Computer Conservation of Natural Resources Petroleum Deep Learning Algorithms
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Reimagining the Kendall plot: using N and O of nitrate and advanced machine learning to improve N pollutant source classification.

Isotopes in environmental and health studies Mar 24, 2025
Nitrate () pollution is a serious water quality issue in many countries due to contamination of lakes, rivers, and aquifers by intensive agriculture practices and inadequate wastewater management. Nitrate pollution and associated cultural eutrophicat...
Nitrates Machine Learning Oxygen Isotopes Nitrogen Isotopes Environmental Monitoring Water Pollutants, Chemical
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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...
Machine Learning Farms Agriculture Probability Czech Republic Soil Environmental Monitoring Soil Pollutants
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Advancing non-target analysis of emerging environmental contaminants with machine learning: Current status and future implications.

Environment international Mar 22, 2025
Emerging environmental contaminants (EECs) such as pharmaceuticals, pesticides, and industrial chemicals pose significant challenges for detection and identification due to their structural diversity and lack of analytical standards. Traditional targ...
Pesticides Machine Learning Mass Spectrometry Environmental Pollutants Risk Assessment Environmental Monitoring
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Sentinel-2 imagery coupled with machine learning to modelling water turbidity in the Doce River Basin, Brazil.

Environmental monitoring and assessment Mar 22, 2025
Remote sensing and machine learning are techniques that can be used to monitor water quality properties, surpassing the limitations of the conventional techniques. Turbidity is an important water quality property directly influenced by the Fundão dam...
Water Quality Rivers Machine Learning Brazil Water Pollutants, Chemical Remote Sensing Technology Environmental Monitoring
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Forecasting the concentration of the components of the particulate matter in Poland using neural networks.

Environmental science and pollution research international Mar 21, 2025
Air pollution is a significant global challenge with profound impacts on human health and the environment. Elevated concentrations of various air pollutants contribute to numerous premature deaths each year. In Europe, and particularly in Poland, air...
Humans Neural Networks, Computer Cities Environmental Monitoring Air Pollutants Forecasting Poland Air Pollution Particulate Matter
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