Articles | Volume 24, issue 3
https://doi.org/10.5194/acp-24-1673-2024
https://doi.org/10.5194/acp-24-1673-2024
Technical note
 | 
06 Feb 2024
Technical note |  | 06 Feb 2024

Technical note: Accurate, reliable, and high-resolution air quality predictions by improving the Copernicus Atmosphere Monitoring Service using a novel statistical post-processing method

Angelo Riccio and Elena Chianese

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Subject: Aerosols | Research Activity: Atmospheric Modelling and Data Analysis | Altitude Range: Troposphere | Science Focus: Chemistry (chemical composition and reactions)
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Cited articles

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Bakka, H., Rue, H., Fuglstad, G.-A., Riebler, A., Bolin, D., Illian, J., Krainski, E., Simpson, D., and Lindgren, F.: Spatial modeling with R-INLA: A review, WIRes: Computational Statistics, 10, e1443, https://doi.org/10.1002/wics.1443, 2018. a, b
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Starting from the Copernicus Atmosphere Monitoring Service (CAMS), we provided a novel ensemble statistical post-processing approach to improve their air quality predictions. Our approach is able to provide reliable short-term forecasts of pollutant concentrations, which is a key challenge in supporting national authorities in their tasks related to EU Air Quality Directives, such as planning and reporting the state of air quality to the citizens.
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