Artificial Neural Networks (ANNs) are used to link PM10 concentration from a deterministic air quality model and precursor scenario emissions to the PM10 concentration of a base case re-analyzed using PM10 surface observations. A case study over Northern Italy is presented. The goal is to show that ANNs are capable to model the nonlinear relationship between precursor emissions and PM10 reanalyzed concentrations, so they can be used for reducing the under-prediction of this pollutant by deterministic air quality models in scenario simulations.
- Contributions to Conferences
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Institute for Environment and Sustainability
University of Hertfordshire and Institute of Meteorology and Climate Research
9th International Conference on Air Quality - Science and Application