AIMC Topic: Particulate Matter

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DF-OSELM: a dynamic feedback feature learning model for air quality online prediction.

Environmental monitoring and assessment
Accurate and timely air quality forecasting is crucial for mitigating pollution risks and protecting public health. However, existing offline and online models face limitations in adaptability, computational efficiency, and interpretability. To addre...

Long-term exposure to ambient air pollution and cardiometabolic multimorbidity in Chinese adults over 45 years.

Scientific reports
The rising prevalence of cardiometabolic multimorbidity (CMM), characterized by the coexistence of two or more cardiometabolic disorders, poses a significant public health challenge in aging populations. While ambient air pollution is a recognized en...

Ischemic heart disease mortality due to fine particulate matter in Seoul between 2016 and 2020.

BMC public health
BACKGROUND: Ischemic heart disease (IHD) continues to rank among the leading global causes of mortality, consistently linked to long-term exposure to fine particulate matter (PM). Despite a declining trend in the annual average PM concentration in Se...

Association between exposure to PM and black carbon and the risk of childhood leukemia in Tehran: A case-control study with critical exposure time windows.

Environmental research
Limited research has explored the relationship between air pollutants and childhood leukemia during critical exposure periods, and no such research has been conducted in Tehran to date. This study assessed the association between exposure to fine par...

Machine learning framework for forecasting air pollution: Evaluating seasonal and climatic influences in Istanbul, Turkey.

PloS one
Air pollution, driven by seasonal and meteorological variations, poses a significant threat to public health and urban sustainability. Despite numerous forecasting approaches, the influence of seasonal patterns on air pollutant levels remains underex...

Particle number emissions on mountainous roads: machine learning insights from on-road testing.

Environmental research
Mountainous roads pose unique challenges for controlling vehicular fine particulate number (PN) emissions, a critical pollutant impacting air quality and public health. This study integrates on-road testing with interpretable machine learning to anal...

Regional PM2.5 pollution forecasting using a hybrid model based on multi-scales feature fusion and deep learning algorithms.

PloS one
The issue of regional haze pollution has become increasingly prominent. However, early warning models for regional haze pollution are significantly lacking. To accurately predict regional PM2.5 pollution, hourly average concentration data of pollutan...

Advancing Air Pollution Exposure Models with Open-Vocabulary Object Detection and Semantic Segmentation of Street-View Images.

Environmental science & technology
Mobile monitoring campaigns combined with land use regression (LUR) models effectively capture fine-scale spatial variations in urban air pollution. However, traditional predictor variables often fail to capture the nuances of the built environment a...

A Novel Framework for Airshed Delineation and PM Estimation across India Using Machine Learning and Spatial Clustering.

Environmental science & technology
Air pollution continues to pose a major challenge in India, with PM being a key contributor to serious health risks. Its spatial distribution is influenced by climatic, topographic, and anthropogenic factors, which are often poorly represented in ana...