A Deep Learning Method for Improving Community Multiscale Air Quality Forecast: Bias Correction, Event Detection, and Temporal Pattern Alignment
Accurate air quality forecasting is essential for environmental management and health protection. However, conventional air quality models often exhibit systematic biases and underpredict pollution events due to uncertainties in emissions, meteorology, and atmospheric processes. Addressing these lim...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-06-01
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| Series: | Atmosphere |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2073-4433/16/6/739 |
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