Search

Forecasting PM10 concentrations accurately will all for improved early warning procedures, useful for safety reasons and opens for example the possibility to restrict circulation or to decide free public transportation. So the need of a statistical pollution forecasting tool from particulate matter is an important issue for the public authorities. Hourly concentrations of PM10 have been measured in three cities of Haute-Normandie (France): Rouen, Le Havre and Dieppe. The Haute-Normandie region is located at northwest of Paris, near the south side of Manche sea and is heavily industrialized. We consider six monitoring stations reflecting the diversity of situations. We have focused our attention on recent data from 2007 to 2011. We forecast the daily mean PM10 concentration by modeling it as a mixture of linear regression models involving meteorological predictors and the average concentration measured on the previous day. The values of observed meteorological variables are used for fitting the models while the corresponding predictions are considered for the test data, leading to realistic evaluations of forecasting performances, which are calculated through a leave-one-out scheme on the four years. We discuss in this paper several methodological issues including estimation schemes, introduction of the deterministic predictions of meteorological models and how to handle the forecasting at various horizons from some hours to one day ahead. [ABSTRACT FROM AUTHOR]