EMS Annual Meeting Abstracts
Vol. 23, EMS2026-245, 2026, updated on 22 Jun 2026
https://doi.org/10.5194/ems2026-245
EMS Annual Meeting 2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
QUALARIA Project: Air Quality Prediction Artificial Intelligence System in Street-Level Scale
Victória Peli1,2, Mario Calderón2, Andrea Orfanoz3, Gabriel Perez1, Thomas Martin1, Amanda Lucena1, Edson Barbosa1, Felix Laimer4, Thomas Gstir4, Maria de Fátima Andrade2, Edmilson Freitas2, Cathy Li3, and Guy Brasseur3,5
Victória Peli et al.
  • 1MeteoIA Data Science, São Paulo, Brazil (victoria@meteoia.com)
  • 2Institute of Astronomy, Geophysics and Atmospheric Sciences of University of São Paulo, São Paulo, Brazil (victoria.peli@iag.usp.br)
  • 3Max Planck Institute for Meteorology, Hamburg, Germany (andrea.orfanoz@mpimet.mpg.de)
  • 4Bernard Technologies GmbH, Munich, Germany (thomas.gstir@bernard-gruppe.com)
  • 5National Center for Atmospheric Research, Boulder, USA

How to cite: Peli, V., Calderón, M., Orfanoz, A., Perez, G., Martin, T., Lucena, A., Barbosa, E., Laimer, F., Gstir, T., Andrade, M. D. F., Freitas, E., Li, C., and Brasseur, G.: QUALARIA Project: Air Quality Prediction Artificial Intelligence System in Street-Level Scale, EMS Annual Meeting 2026, Utrecht, Netherlands, 6–11 Sep 2026, EMS2026-245, https://doi.org/10.5194/ems2026-245, 2026.

This abstract has been withdrawn on 01 Sep 2026.