Please use this identifier to cite or link to this item:
|Title:||Use of artificial neural networks for PM10 re-analysis over northern Italy|
|Authors:||CARNEVALE C.; FINZI G.; PISONI ENRICO; PEDERZOLI Anna; TURRINI Enrico; VOLTA Luisa|
|Citation:||9th International Conference on Air Quality - Science and Application|
|Publisher:||University of Hertfordshire and Institute of Meteorology and Climate Research|
|Type:||Articles in periodicals and books|
|Abstract:||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.|
|JRC Directorate:||Sustainable Resources|
Files in This Item:
There are no files associated with this item.
Items in repository are protected by copyright, with all rights reserved, unless otherwise indicated.