Literature DB >> 7750005

Pollen allergy in the Bilbao area (European Atlantic seaboard climate): pollination forecasting methods.

I Antépara1, J C Fernández, P Gamboa, I Jauregui, F Miguel.   

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)

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Year:  1995        PMID: 7750005     DOI: 10.1111/j.1365-2222.1995.tb01018.x

Source DB:  PubMed          Journal:  Clin Exp Allergy        ISSN: 0954-7894            Impact factor:   5.018


  6 in total

1.  Two statistical approaches to forecasting the start and duration of the pollen season of Ambrosia in the area of Lyon (France).

Authors:  Mohamed Laaidi; Michel Thibaudon; Jean-Pierre Besancenot
Journal:  Int J Biometeorol       Date:  2003-05-29       Impact factor: 3.787

2.  Atmospheric Poaceae pollen frequencies and associations with meteorological parameters in Brisbane, Australia: a 5-year record, 1994-1999.

Authors:  Brett James Green; Mary Dettmann; Eija Yli-Panula; Shannon Rutherford; Rod Simpson
Journal:  Int J Biometeorol       Date:  2004-03-02       Impact factor: 3.787

3.  Spatial and temporal modeling of daily pollen concentrations.

Authors:  Curt T Dellavalle; Elizabeth W Triche; Michelle L Bell
Journal:  Int J Biometeorol       Date:  2011-02-18       Impact factor: 3.787

4.  Climate change: consequences on the pollination of grasses in Perugia (Central Italy). A 33-year-long study.

Authors:  Ghitarrini Sofia; Tedeschini Emma; Timorato Veronica; Frenguelli Giuseppe
Journal:  Int J Biometeorol       Date:  2016-06-21       Impact factor: 3.787

Review 5.  Effect of meteorological parameters on Poaceae pollen in the atmosphere of Tetouan (NW Morocco).

Authors:  Nadia Aboulaich; Lamiaa Achmakh; Hassan Bouziane; M Mar Trigo; Marta Recio; Mohamed Kadiri; Baltasar Cabezudo; Hassane Riadi; Mohamed Kazzaz
Journal:  Int J Biometeorol       Date:  2012-06-29       Impact factor: 3.787

6.  A new 'bio-comfort' perspective for Melbourne based on heat stress, air pollution and pollen.

Authors:  Stephanie J Jacobs; Alexandre B Pezza; Vaughan Barras; John Bye
Journal:  Int J Biometeorol       Date:  2013-02-13       Impact factor: 3.787

  6 in total

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