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Spatiotemporal estimation of daily surface NO2 concentrations over China from 2019 to 2024 based on TROPOMI data and MAPST-Net model
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DOI：10.1016/j.atmosenv.2026.122203.png)
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Abstract
En 中文
• Propose a point-plane estimation framework. • Construct a spatiotemporal model with temporal dependencies and spatial encoding. • Improve conventional attention mechanisms and convolutional layers. • Analyze the spatiotemporal patterns of surface NO2 concentrations across China.
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