Mapping of Alternaria and Pleospora concentrations in Central Italy using meteorological forecast and neural network estimator

Airborne particles (pollens and fungal spores) are recognized as important causes of allergies and many other pathologies whose main symptoms are usually associated with respiratory problems. In addition these particles seem to be responsible for clinical symptoms of oculorhinitis and bronchial asthma. Many authors showed how pollen and spore concentrations are critically linked to meteorological conditions, while other studies investigated the possibility to estimate these concentrations through meteorological parameters. So, many different approaches have been proposed, and one of the most sophisticated is based on the use of a complex Artificial Neural Network (ANN) architecture. Once the neural device is calibrated using simultaneous time series of observed meteorological parameters and airborne biological particles, it is straightforward to use the Neural Network to predict spore concentrations using operational Limited Area Meteorological Model. In a previous work it has been shown that the MM5 meteorological Model developed by National Center for Atmospheric Research and Pennsylvania State University can be coupled with the above cited neural predictor to provide a good prediction of Alternaria and Pleospora spore in the location of L’Aquila (Central Italy). Following the same approach, this work aims to provide the mapping of spore concentration over a wide area covered by high resolution meteorological prediction in Central Italy. The complex patterns of fungal spore concentrations in selected areas will be described and the high temporal variability of such fields will be discussed as well. The possibility to infer useful informations from the predicted pattern of spore concentrations is discussed, as an example it appear that for people suffering from allergy to fungal spores is more comfortable to spend summertime close to the east coast of Italian Peninsula respect to the west coast. A further step of this work may easily lead to an operational use of the model for supporting the clinical management of allergies and for establishing a preventive strategy in agriculture to avoid unsafe and useless pollution of atmosphere, crops and fields.