Prediction of airborne Alnus pollen concentration by using ARIMA models.
To take preventative measures to protect allergic people from the severity of the pollen season, one of aerobiology's objectives is to develop statistical models enabling the short- and long-term prediction of atmospheric pollen concentrations. During recent years some attempts have been made to apply Time Series analysis, frequently used in biomedical studies and atmospheric contamination to pollen series. The aim of this study is to understand the behaviour of atmospheric alder pollen concentrations in northwest Spain in order to develop predictive models of pollen concentrations by using Time Series analysis. The prediction line proposed for Oviedo and Ponferrada are similar (Arima 2,0,1) while in Vigo a more accurate model founded by Arima (3,0,1) and in Leon (1,0,1) was used. The results suggest that Ponferrada and Oviedo are the cities in northwest Spain where Alnus pollen allergic individuals should to take preventive measures to protect themselves from the severity of the pollen season. Alnus pollen values higher than 30 grains/m3, a quantity considered sufficient to trigger severe allergy symptoms of other trees of the Betulaceae family, could be reached during 25 days in some years. The predicted lines conformed with the observed values overall in the case of Leon and Ponferrada. Time Series regression models are especially suitable in allergology for evaluating short-term effects of time-varying pollen appearance in the atmosphere.
Rodríguez-Rajo
Francisco Javier
FJ
Department of Plant Biology and Soil Sciences, Sciences Faculty of Ourense, University of Vigo, Ourense, 32004, Spain. javirajo@uvigo.es
Valencia-Barrera
Rosa Maria
RM
Vega-Maray
Ana María
AM
Suárez
Francisco Javier
FJ
Fernández-González
Delia
D
Jato
Victoria
V
D000397:Air Pollution / Q000032:analysis*; D000485:Allergens / Q000032:analysis*; D029661:Alnus; D004784:Environmental Monitoring; D005544:Forecasting; D006801:Humans; D015233:Models, Statistical; D011058:Pollen; D011237:Predictive Value of Tests; D011634:Public Health; D006255:Rhinitis, Allergic, Seasonal / Q000209:etiology* / Q000517:prevention & control; D012307:Risk Factors; D012621:Seasons; D013030:Spain; D013997:Time Factors
D000485:Allergens