Author(s)

A.J. Greig, G. Cawley, S. Darling, K. Eben, A.J. Fiala, A. Karppinen, J. Keder, M. Kolehmainen, K. Kukkonen, B. Libero, J. Macoun, M. Nironjan, A. Nucifora, A. Nunnari, M. Palus, E. Pelikan, J. Ruuskanen & U. Schlink

Abstract

Air pollution episodes: modelling tools for improved smog management (APPETISE) A.J. Greig\ G, Cawle/, S, Dorling\ K, Eben\ A.J. Fiala\ A. Karppinen\ J. Keder^, M. KolehmainerA K. Kukkonen\ B, Libero^, J, Macourr\ M. Niranjan^, A. Nucifora^, A, Nunnari^, M. Palus~\ E. Pelikarr\ J. RuuskanetA U. Schlink^ ^ Anglia Polytechnic University, UK, * University of East Anglia, UK * Academy of Sciences of the Czech Republic, * Finnish Meteorological Institute, Finland, * Czech Hydrometeorological Institute, Czech Republic, ^ University ofKuopio, Finland, ^ University of Catania, Italy University of Sheffield, UK, * Centre of Environmental Research Leipzig-Halle Ltd, Germany Abstract Most ambient air quality models are deterministic models or rely upon simple regression based statistics. Their success, however, is limited either by their failure to capture the non-linear behaviour of air pollutants, or our incomplete understanding of the physical and chemical processes involved. The

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