Literature DB >> 22434484

A numerical model of birch pollen emission and dispersion in the atmosphere. Model evaluation and sensitivity analysis.

Pilvi Siljamo1, Mikhail Sofiev, Elena Filatova, Łukasz Grewling, Siegfried Jäger, Ekaterina Khoreva, Tapio Linkosalo, Sara Ortega Jimenez, Hanna Ranta, Auli Rantio-Lehtimäki, Anton Svetlov, Laura Veriankaite, Ekaterina Yakovleva, Jaakko Kukkonen.   

Abstract

An evaluation of performance of the System for Integrated modeLling of Atmospheric coMposition (SILAM) in application to birch pollen dispersion is presented. The system is described in a companion paper whereas the current study evaluates the model sensitivity to details of the pollen emission module parameterisation and to the meteorological input data. The most important parameters are highlighted. The reference year considered for the analysis is 2006. It is shown that the model is capable of predicting about two-thirds of allergenic alerts, with the odds ratio exceeding 12 for the best setup. Several other statistics corroborate with these estimations. Low-pollen concentration days are also predicted correctly in more than two-thirds of cases. The model experiences certain difficulties only with intermediate pollen concentrations. It is demonstrated that the most important input parameter is the near-surface temperature, the bias of which can easily jeopardise the results. The model sensitivity to random fluctuations of temperature is much lower. Other parameters important at various stages of pollen development, release, and dispersion are precipitation and ambient humidity, as well as wind direction.

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Year:  2012        PMID: 22434484      PMCID: PMC3527737          DOI: 10.1007/s00484-012-0539-5

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


  8 in total

1.  Significance of sampling height of airborne particles for aerobiological information.

Authors:  A Rantio-Lehtimäki; A Koivikko; R Kupias; Y Mäkinen; A Pohjola
Journal:  Allergy       Date:  1991-01       Impact factor: 13.146

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Journal:  Ann Allergy       Date:  1992-07

3.  Towards numerical forecasting of long-range air transport of birch pollen: theoretical considerations and a feasibility study.

Authors:  M Sofiev; P Siljamo; H Ranta; A Rantio-Lehtimäki
Journal:  Int J Biometeorol       Date:  2006-04-05       Impact factor: 3.787

Review 4.  Allergenic pollen and pollen allergy in Europe.

Authors:  G D'Amato; L Cecchi; S Bonini; C Nunes; I Annesi-Maesano; H Behrendt; G Liccardi; T Popov; P van Cauwenberge
Journal:  Allergy       Date:  2007-05-22       Impact factor: 13.146

5.  Numerical simulation of birch pollen dispersion with an operational weather forecast system.

Authors:  Heike Vogel; Andreas Pauling; Bernhard Vogel
Journal:  Int J Biometeorol       Date:  2008-07-24       Impact factor: 3.787

Review 6.  Sampling airborne allergens.

Authors:  W R Solomon
Journal:  Ann Allergy       Date:  1984-03

7.  The seasonal symptoms of hyposensitized and untreated hay fever patients in relation to birch pollen counts: correlations with nasal sensitivity, prick tests and RAST.

Authors:  M Viander; A Koivikko
Journal:  Clin Allergy       Date:  1978-07

8.  The long-range transport of birch (Betula) pollen from Poland and Germany causes significant pre-season concentrations in Denmark.

Authors:  C A Skjøth; J Sommer; A Stach; M Smith; J Brandt
Journal:  Clin Exp Allergy       Date:  2007-08       Impact factor: 5.018

  8 in total
  12 in total

1.  Aerobiology in the International Journal of Biometeorology, 1957-2017.

Authors:  Paul J Beggs; Branko Šikoparija; Matt Smith
Journal:  Int J Biometeorol       Date:  2017-06-12       Impact factor: 3.787

2.  Predicting Onset and Duration of Airborne Allergenic Pollen Season in the United States.

Authors:  Yong Zhang; Leonard Bielory; Ting Cai; Zhongyuan Mi; Panos Georgopoulos
Journal:  Atmos Environ (1994)       Date:  2015-02       Impact factor: 4.798

3.  Development of personal pollen information-the next generation of pollen information and a step forward for hay fever sufferers.

Authors:  Maximilian Kmenta; Katharina Bastl; Siegfried Jäger; Uwe Berger
Journal:  Int J Biometeorol       Date:  2013-12-20       Impact factor: 3.787

4.  Pollen information consumption as an indicator of pollen allergy burden.

Authors:  Maximilian Kmenta; Reinhard Zetter; Uwe Berger; Katharina Bastl
Journal:  Wien Klin Wochenschr       Date:  2015-09-15       Impact factor: 1.704

5.  Climate change effect on Betula (birch) and Quercus (oak) pollen seasons in the United States.

Authors:  Yong Zhang; Leonard Bielory; Panos G Georgopoulos
Journal:  Int J Biometeorol       Date:  2013-06-21       Impact factor: 3.787

6.  Development of a semi-mechanistic allergenic pollen emission model.

Authors:  Ting Cai; Yong Zhang; Xiang Ren; Leonard Bielory; Zhongyuan Mi; Christopher G Nolte; Yang Gao; L Ruby Leung; Panos G Georgopoulos
Journal:  Sci Total Environ       Date:  2018-10-18       Impact factor: 7.963

7.  A numerical model of birch pollen emission and dispersion in the atmosphere. Description of the emission module.

Authors:  M Sofiev; P Siljamo; H Ranta; T Linkosalo; S Jaeger; A Rasmussen; A Rantio-Lehtimaki; E Severova; J Kukkonen
Journal:  Int J Biometeorol       Date:  2012-03-13       Impact factor: 3.787

8.  On impact of transport conditions on variability of the seasonal pollen index.

Authors:  M Sofiev
Journal:  Aerobiologia (Bologna)       Date:  2016-10-24       Impact factor: 2.410

9.  USA National Phenology Network's volunteer-contributed observations yield predictive models of phenological transitions.

Authors:  Theresa M Crimmins; Michael A Crimmins; Katharine L Gerst; Alyssa H Rosemartin; Jake F Weltzin
Journal:  PLoS One       Date:  2017-08-22       Impact factor: 3.752

Review 10.  Defining Pollen Seasons: Background and Recommendations.

Authors:  Katharina Bastl; Maximilian Kmenta; Uwe E Berger
Journal:  Curr Allergy Asthma Rep       Date:  2018-10-29       Impact factor: 4.806

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