AIMC Topic: Particulate Matter
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Fusing satellite imagery and ground-based observations for PM air pollution modeling in Iran using a deep learning approach.
Scientific reports
Jul 1, 2025
With the rapid advancement of urbanization and industrialization in cities, air pollution has become one of the significant environmental challenges and issues in many countries. The concentration of particulate matter with an aerodynamic diameter of...
Air Pollution and Autism Spectrum Disorder: Unveiling Multipollutant Risks and Sociodemographic Influences in California.
Environmental health perspectives
Jun 12, 2025
BACKGROUND: Autism spectrum disorder (ASD) is a neurodevelopmental condition with increasing prevalence worldwide. Air pollution may be a major contributor to the rise in ASD cases. This study investigated how the risk of ASD associated with prenatal...
Enhancing particulate matter prediction in Delhi: insights from statistical and machine learning models.
Environmental monitoring and assessment
Jun 3, 2025
This study advances our approach to modeling particulate matter levels-specifically, PM and PM-in Delhi's dynamic urban environment through an extensive evaluation of traditional time series models (ARIMAX, SARIMAX) and machine learning models (RF, S...
Epidemiological association and machine learning-based prediction of lung cancer risk linked to long-term lagged satellite-derived PM in China.
Frontiers in public health
May 30, 2025
OBJECTIVES: This study investigated association between long-term PM exposure and lung cancer incidence, focusing on Jiangsu Province, China. We aimed to explore the effects of historical PM with time lags and build a prediction model using machine l...
Low-Cost Particulate Matter Mass Sensors: Review of the Status, Challenges, and Opportunities for Single-Instrument and Network Calibration.
ACS sensors
May 7, 2025
As an emerging atmospheric monitoring technology, low-cost sensors for particulate matter of diameters below 2.5 μm (PMLCSs) supplement traditional air quality monitoring instruments. Because their stability and accuracy are typically low, they requi...
Machine learning-based quantification and separation of emissions and meteorological effects on PM in Greater Bangkok.
Scientific reports
Apr 28, 2025
This study presents the first-ever application of machine learning (ML)-based meteorological normalization and Shapley additive explanations (SHAP) analysis to quantify, separate, and understand the effect of meteorology on PM over Greater Bangkok (G...
Low-cost video-based air quality estimation system using structured deep learning with selective state space modeling.
Environment international
Apr 26, 2025
Air quality is crucial for both public health and environmental sustainability. An efficient and cost-effective model is essential for accurate air quality predictions and proactive pollution control. However, existing research primarily focuses on s...
Effect of pregnancy and infancy exposure to outdoor particulate matter (PM, PM, PM) and SO on childhood pneumonia in preschool children in Taiyuan City, China.
Environmental pollution (Barking, Essex : 1987)
Apr 24, 2025
There is currently a paucity of research on the effects of early life exposure to particulate matter (PM) of various size fractions on pneumonia in preschool-aged children. We explored the connections between antenatal and postnatal exposure to atmos...
Temporally boosting neural network for improving dynamic prediction of PM concentration with changing and unbalanced distribution.
Journal of environmental management
Apr 22, 2025
Increasing medical research evidence suggests that even low PM concentrations may trigger significant health issues. Hence, an accurate prediction of PM holds immense significance in securing public health safety. However, current data-drive predicti...
A method for delineating traffic low emission control zone based on deep learning and multi-objective optimization.
Environmental monitoring and assessment
Apr 8, 2025
Current methods for defining traffic low emission control zones (TLEZ) often face limitations that hinder their widespread implementation and effectiveness. This study addresses these challenges by employing a comprehensive approach to analyze PM con...
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