Atmospheric Chemistry and Physics
Atmospheric Chemistry and Physics
ACP
Articles | Volume 24, issue 3
Articles | Volume 24, issue 3
https://doi.org/10.5194/acp-24-1673-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-24-1673-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 24, issue 3
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

Viewed

Total article views: 5,333 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
4,008 1,110 215 5,333 206 239 247
  • HTML: 4,008
  • PDF: 1,110
  • XML: 215
  • Total: 5,333
  • Supplement: 206
  • BibTeX: 239
  • EndNote: 247
Views and downloads (calculated since 18 Aug 2023)
Cumulative views and downloads (calculated since 18 Aug 2023)

Viewed (geographical distribution)

Total article views: 5,333 (including HTML, PDF, and XML) Thereof 5,283 with geography defined and 50 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 09 Jun 2026
Download
Short summary
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.
Read more
Share
Altmetrics
Final-revised paper
Preprint