title: Pollen allergy in the Bilbao area (European Atlantic seaboard climate): pollination forecasting methods.
abstract: Forecasting pollination can help the allergist to establish the appropriate treatment and advice for patients. Based on previous studies, we have related the climate variables with the grass pollen counts in the search for pollination predictors. By relating the meteorological data of the temperature recorded every 6 h and of the rainfall in hourly periods, together with the daily pollen counts obtained by the Hirst volumetric system, over a period of 3 years, we have tried to predict the start, duration and severity of the grass pollination, as well as the days of peak pollination. We have established a relationship by means of a polynomic regression originating from the mean cumulated temperature higher than 9 degrees C [R2 = 0.927 (P = 0.0001)], with the pollination season starting from 300 degrees C and the maximum peak at 356 degrees C, in the 3 years of the study. During the days of pollination, peaks higher than 50 grains/m3 coincide with average daily temperatures of 18.7 +/- 3 and lower than 50 grains/m3 with temperatures of 16.8 +/- 3 (significant to 95%). The duration of the pollination is influenced by the cumulated average temperatures (from 800 to 900 degrees C) and especially by precipitation at the start of and during pollination. In order to forecast grass pollination, the cumulated average temperatures are useful, starting from a basal (9 degrees C), pollination begins when this sum is greater than 300 degrees C, whereas when 800 degrees C is reached and depending on the rainfall during the season, pollination will end.(ABSTRACT TRUNCATED AT 250 WORDS)
authors.affiliation: Allergy Unit, Hospital de Basurto, Bilbao, Spain.
authors.forename: I
authors.initials: I
authors.lastname: Antépara
authors.forename: J C
authors.initials: JC
authors.lastname: Fernández
authors.forename: P
authors.initials: P
authors.lastname: Gamboa
authors.forename: I
authors.initials: I
authors.lastname: Jauregui
authors.forename: F
authors.initials: F
authors.lastname: Miguel
mesh_terms: D002980:Climate; D005060:Europe; D005544:Forecasting; D006801:Humans; D006967:Hypersensitivity / Q000517:prevention & control*; D006109:Poaceae; D011058:Pollen / Q000276:immunology*