Literature DB >> 11411409

Forecasting the start of the pollen season of Poaceae: evaluation of some methods based on meteorological factors.

M Laaidi1.   

Abstract

The pollen of anemogamous plants is responsible for half the allergic diseases, that is to say a prevalence of 10% in the French population. Poaceae produce the first allergenic pollen almost everywhere. The work described in this article aimed to validate forecast methods for the use of physicians and allergic people who need accurate and early information on the first appearance of pollen in the air. The methods were based on meteorological parameters, mainly temperature. Four volumetric Hirst traps were used from 1995 to 1998, situated in two departments of Burgundy. Two of the methods tested proved to be of particular interest: the sum of the temperatures and the sum of Q10 values, an agrometeorological coefficient integrating temperature. A multiple regression, using maximum temperature and rainfall, was also performed but it gave slightly less accurate results. A chi 2-test was then used to compare the accuracy of the three methods. It was found that the date of onset of the pollen season could be predicted early enough to be useful in medical practice. Results were verified in 1999, and the research must be continued to obtain better statistical validity.

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Year:  2001        PMID: 11411409     DOI: 10.1007/s004840000079

Source DB:  PubMed          Journal:  Int J Biometeorol        ISSN: 0020-7128            Impact factor:   3.787


  11 in total

1.  Effect of air temperature on forecasting the start of the Betula pollen season at two contrasting sites in the south of Europe (1995-2001).

Authors:  F J Rodríguez-Rajo; G Frenguelli; M V Jato
Journal:  Int J Biometeorol       Date:  2003-03-07       Impact factor: 3.787

2.  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

3.  The use of discriminant analysis and neural networks to forecast the severity of the Poaceae pollen season in a region with a typical Mediterranean climate.

Authors:  Juan Antonio Sánchez Mesa; Carmen Galán; César Hervás
Journal:  Int J Biometeorol       Date:  2005-03-24       Impact factor: 3.787

4.  Alternative statistical methods for interpreting airborne Alder (Alnus glutimosa (L.) Gaertner) pollen concentrations.

Authors:  Zulima González Parrado; Rosa M Valencia Barrera; Carmen R Fuertes Rodríguez; Ana M Vega Maray; Rafael Pérez Romero; Roberto Fraile; Delia Fernández González
Journal:  Int J Biometeorol       Date:  2008-10-14       Impact factor: 3.787

5.  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

6.  Assessment of Quercus flowering trends in NW Spain.

Authors:  V Jato; F J Rodríguez-Rajo; M Fernandez-González; M J Aira
Journal:  Int J Biometeorol       Date:  2014-08-10       Impact factor: 3.787

7.  Airborne pollen of allergenic herb species in Toledo (Spain).

Authors:  Consolación Vaquero; Alfonso Rodríguez-Torres; Jesús Rojo; Rosa Pérez-Badia
Journal:  Environ Monit Assess       Date:  2012-02-14       Impact factor: 2.513

8.  A glossary for biometeorology.

Authors:  Simon N Gosling; Erin K Bryce; P Grady Dixon; Katharina M A Gabriel; Elaine Y Gosling; Jonathan M Hanes; David M Hondula; Liang Liang; Priscilla Ayleen Bustos Mac Lean; Stefan Muthers; Sheila Tavares Nascimento; Martina Petralli; Jennifer K Vanos; Eva R Wanka
Journal:  Int J Biometeorol       Date:  2014-02-19       Impact factor: 3.787

Review 9.  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

10.  Increased duration of pollen and mold exposure are linked to climate change.

Authors:  Bibek Paudel; Theodore Chu; Meng Chen; Vanitha Sampath; Mary Prunicki; Kari C Nadeau
Journal:  Sci Rep       Date:  2021-06-17       Impact factor: 4.379

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