Abstract Machine learning (ML) is an artificial intelligence technology that has been used in
atmospheric pollution research due to their powerful fitting ability. In this review, 105 articles …

Objective to summarize the main updated evidence about the health effects of air pollution
and to focus on Italian epidemiological experiences on the respiratory effects. Results the …

Background Despite mounting evidence linking outdoor air pollution with otitis media (OM),
the role of air pollutant (s) exposure during which critical window (s) on childhood OM …

The epidemiological association between exposure to particulate matter (PM10) and various
respiratory and cardiovascular problems is well known, but the mechanisms driving these …

Background air pollution is a complex mixture; novel multipollutant approaches could help
understanding the health effects of multiple concomitant exposures to air pollutants. Aim to …

Long-term exposure to air pollution has adverse respiratory health effects. We investigated
the cross-sectional relationship between residential exposure to air pollutants and the risk of …

In this study, we employed Principal Component Analysis (PCA) and Multi-Linear
Regression (MLR) to identify the most significant sources contributing to the toxicity of PM 10 …

California's diverse geography and meteorological conditions necessitate models capturing
fine-grained patterns of air pollution distribution. This study presents the development of …

The need to address the impact of air pollution on health is reinforced by recent scientific
evidence and the 2021 WHO Air Quality Guidelines (AQG). Air pollution is an avoidable risk …

Background Ambient fine particulate matter (PM 2.5) pollution poses a great threat on global
health. Previous studies have reported that PM 2.5 regulates circulating fibrinogen and IL-6 …