A Deep Learning Method for Improving Community Multiscale Air Quality Forecast: Bias Correction, Event Detection, and Temporal Pattern Alignment

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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Bibliographic Details
Main Authors: Ioannis Stergiou, Nektaria Traka, Dimitrios Melas, Efthimios Tagaris, Rafaella-Eleni P. Sotiropoulou
Format: Article
Language:English
Published: MDPI AG 2025-06-01
Series:Atmosphere
Subjects:
deep learning
convolutional neural networks—CNNs
Long Short-Term Memory—LSTM
Community Multiscale Air Quality—CMAQ
bias correction
Online Access:https://www.mdpi.com/2073-4433/16/6/739
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