A novel ensemble learning algorithm integrating WRF-CMAQ and downscaling models for hourly estimation of regional air pollution along with vegetation exposure risk detection

A novel ensemble learning algorithm integrating WRF-CMAQ and downscaling models for hourly estimation of regional air pollution along with vegetation exposure risk detection

Timely assessment of the spatiotemporal evolution, meteorological drivers, and vegetation exposure risks of regional air pollution is critical for addressing challenges posed by rapid urbanization. To achieve this, an integrated machine learning algorithm was developed by coupling the Weather Resear...

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Bibliographic Details
Main Authors: Peng Zhou, Jieming Chou, Shan Ye, Leiku Yang, Mengting Sun, Pengao Li, Huanpeng Wang, Jie Luo, Zhaoxiang Cao, Qian Yao, Hao Zhang, Hongze Pei
Format: Article
Language:English
Published: Taylor & Francis Group 2025-08-01
Series:International Journal of Digital Earth
Subjects:
Geostationary satellite observations
spatiotemporal distribution characteristics
compound pollution episodes
meteorological drivers
vegetation exposure intensity
Online Access:https://www.tandfonline.com/doi/10.1080/17538947.2025.2509825
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https://www.tandfonline.com/doi/10.1080/17538947.2025.2509825

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