During peak hours, both pedestrians and drivers face extended exposure to road air
pollution, raising the risk of respiratory diseases. Variations in traffic volume, building …

Background Exposure to ambient air pollution is associated with morbidity and mortality,
making it an important public health concern. Emissions from motorized traffic are a common …

Background Concentrations of outdoor ultrafine particles (UFP;< 0.1 µm) and black carbon
(BC) can vary greatly within cities and long-term exposures to these pollutants have been …

In the quest to reconcile public perception of air pollution with scientific measurements, our
study introduced a pioneering method involving a gradient boost-regression tree model …

Identifying sources of air pollution exposure is crucial for addressing their health impacts
and associated inequities. Researchers have developed modeling approaches to resolve …

BACKGROUND There remain important limitations and challenges when estimating long-
term air pollution exposure for use in epidemiological studies. In 2019, the Health Effects …

Mobile monitoring provides robust measurements of air pollution. However, resource
constraints often limit the number of measurements so that assessments cannot be obtained …

Background Machine learning methods are proposed to improve the predictions of ambient
air pollution, yet few studies have compared ultrafine particles (UFP) models across a broad …

Abstract Machine learning, especially deep learning, can outperform traditional atmospheric
models in air quality assessment, offering enhanced efficiency and accuracy without relying …

This study investigated the utilization of images collected from low-quality dash cameras on
passenger vehicles for the estimation of traffic-related air pollution (TRAP). We conducted …