Estimating PM<sub>2.5</sub> Exposures and Cardiovascular Disease Risks in the Yangtze River Delta Region Using a Spatiotemporal Convolutional Approach to Fill Gaps in Satellite Data

Estimating PM<sub>2.5</sub> Exposures and Cardiovascular Disease Risks in the Yangtze River Delta Region Using a Spatiotemporal Convolutional Approach to Fill Gaps in Satellite Data

Accurate estimation of ambient PM<sub>2.5</sub> concentrations is crucial for assessing air quality and health risks, particularly in regions with limited ground-based monitoring. Satellite-retrieved data products, such as top-of-atmosphere reflectance (TOAR) and aerosol optical depth (A...

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Bibliographic Details
Main Authors: Muhammad Jawad Hussain, Myeongsu Seong, Behjat Shahid, Heming Bai
Format: Article
Language:English
Published: MDPI AG 2025-05-01
Series:Toxics
Subjects:
PM<sub>2.5</sub>
aerosol optical depth
top of atmospheric reflectance
cardiovascular diseases
machine-learning
Online Access:https://www.mdpi.com/2305-6304/13/5/392
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