Articles | Volume 16, issue 20
https://doi.org/10.5194/gmd-16-6029-2023
https://doi.org/10.5194/gmd-16-6029-2023
Methods for assessment of models
 | 
27 Oct 2023
Methods for assessment of models |  | 27 Oct 2023

A standardized methodology for the validation of air quality forecast applications (F-MQO): lessons learnt from its application across Europe

Lina Vitali, Kees Cuvelier, Antonio Piersanti, Alexandra Monteiro, Mario Adani, Roberta Amorati, Agnieszka Bartocha, Alessandro D'Ausilio, Paweł Durka, Carla Gama, Giulia Giovannini, Stijn Janssen, Tomasz Przybyła, Michele Stortini, Stijn Vranckx, and Philippe Thunis

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Cited articles

Adani, M., Piersanti, A., Ciancarella, L., D'Isidoro, M., Villani, M. G., and Vitali, L.: Preliminary Tests on the Sensitivity of the FORAIR_IT Air Quality Forecasting System to Different Meteorological Drivers, Atmosphere, 11, 574, https://doi.org/10.3390/atmos11060574, 2020. 
Adani, M., D'Isidoro, M., Mircea, M., Guarnieri, G., Vitali, L., D'Elia, I., Ciancarella, L., Gualtieri, M., Briganti, G., Cappelletti, A., Piersanti, A., Stracquadanio, M., Righini, G., Russo, F., Cremona, G., Villani, M. G., and Zanini, G.: Evaluation of air quality forecasting system FORAIR-IT over Europe and Italy at high resolution for year 2017, Atmos. Pollut. Res., 13, 101456, https://doi.org/10.1016/j.apr.2022.101456, 2022. 
Agarwal, S., Sharma, S., R., S., Rahman, M. H., Vranckx, S., Maiheu, B., Blyth, L., Janssen, S., Gargava, P., Shukla, V. K., and Batra, S.: Air quality forecasting using artificial neural networks with real time dynamic error correction in highly polluted regions, Sci. Total Environ., 735, 139454, https://doi.org/10.1016/j.scitotenv.2020.139454, 2020. 
Alfaro, S. C. and Gomes, L.: Modeling mineral aerosol production by wind erosion: Emission intensities and aerosol size distributions in source areas, J. Geophys. Res.-Atmos., 106, 18075–18084, https://doi.org/10.1029/2000JD900339, 2001. 
Bai, L., Wang, J., Ma, X., and Lu, H.: Air Pollution Forecasts: An Overview, Int. J. Environ. Res. Publ. He., 15, 780, https://doi.org/10.3390/ijerph15040780, 2018. 
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Short summary
Air quality forecasting models play a key role in fostering short-term measures aimed at reducing human exposure to air pollution. Together with this role comes the need for a thorough assessment of the model performances to build confidence in models’ capabilities, in particular when model applications support policymaking. In this paper, we propose an evaluation methodology and test it on several domains across Europe, highlighting its strengths and room for improvement.
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