Surrogate models to compute optimal air quality planning policies at a regional scale

• Published in: Environmental modelling & software : with environment data news Vol. 34; pp. 44 - 50
• Main Authors: Carnevale, Claudio, Finzi, Giovanna, Guariso, Giorgio, Pisoni, Enrico, Volta, Marialuisa
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.06.2012
• Subjects: Air quality modeling; Air quality planning; Model reduction; Multi-objective optimization; Neural networks; Air quality planning; Multi-objective optimization; Air quality modeling; Model reduction; Neural networks

Secondary pollutants (such as PM10) derives from complex non-linear reactions involving precursor emissions, namely VOC, NOx, NH3, primary PM and SO2. Due to difficulty to cope with this complexity, Decision Support Systems (DSSs) are essential tools to help Environmental Authorities to plan air qua...