Literature DB >> 23087540

The effect of meteorological factors on airborne Betula pollen concentrations in Lublin (Poland).

Krystyna Piotrowska1, Agnieszka Kubik-Komar.   

Abstract

The present study investigated the pattern of the birch atmospheric pollen seasons in Lublin in the period 2001-2010. Pollen monitoring was conducted using a Lanzoni VPPS 2000 sampler. The atmospheric pollen seasons were determined with the 98% method. Regression analysis was used to determine correlations between meteorological conditions and the pattern of the birch pollen season. On average, the birch pollen season started on 12 April, ended on 13 May, and lasted 32 days. The peak value and the Seasonal Pollen Index showed the greatest variation in particular years. All the seasons were right-skewed. During the study years, a trend was found towards earlier occurrence of the seasonal peak. Regression equations were developed for the following parameters of the atmospheric pollen season: start, duration, peak value and average pollen concentration during the season. The obtained model fit was at a level of 64-81%. Statistical analysis shows that minimum temperature of February and March and total rainfall in June in the year preceding pollen release have the greatest effect on the birch atmospheric pollen season in Lublin. Low temperatures in February promote the occurrence of high pollen concentrations.

Entities:  

Year:  2012        PMID: 23087540      PMCID: PMC3470820          DOI: 10.1007/s10453-012-9249-z

Source DB:  PubMed          Journal:  Aerobiologia (Bologna)        ISSN: 0393-5965            Impact factor:   2.410


  6 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.  Airborne pollen calendar of Lublin, Poland.

Authors:  Elzbieta Weryszko-Chmielewska; Krystyna Piotrowska
Journal:  Ann Agric Environ Med       Date:  2004       Impact factor: 1.447

3.  Responses in the start of Betula (birch) pollen seasons to recent changes in spring temperatures across Europe.

Authors:  J Emberlin; M Detandt; R Gehrig; S Jaeger; N Nolard; A Rantio-Lehtimäki
Journal:  Int J Biometeorol       Date:  2002-07-26       Impact factor: 3.787

4.  Factors that determine the severity of Betula spp. pollen seasons in Poland (Poznań and Krakow) and the United Kingdom (Worcester and London).

Authors:  A Stach; J Emberlin; M Smith; B Adams-Groom; D Myszkowska
Journal:  Int J Biometeorol       Date:  2007-10-30       Impact factor: 3.787

5.  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

6.  Climate change and its impact on birch pollen quantities and the start of the pollen season an example from Switzerland for the period 1969-2006.

Authors:  Thomas Frei; Ewald Gassner
Journal:  Int J Biometeorol       Date:  2008-05-15       Impact factor: 3.787

  6 in total
  9 in total

1.  The effect of geographical and climatic properties on grass pollen and Phl p 5 allergen release.

Authors:  Şenol Alan; Aydan Acar Şahin; Tuğba Sarışahin; Serap Şahin; Ayşe Kaplan; Nur Münevver Pınar
Journal:  Int J Biometeorol       Date:  2018-04-06       Impact factor: 3.787

2.  Spatiotemporal models for predicting high pollen concentration level of Corylus, Alnus, and Betula.

Authors:  Jakub Nowosad
Journal:  Int J Biometeorol       Date:  2015-10-21       Impact factor: 3.787

3.  Extension of WRF-Chem for birch pollen modelling-a case study for Poland.

Authors:  Małgorzata Werner; Jakub Guzikowski; Maciej Kryza; Małgorzata Malkiewicz; Daria Bilińska; Carsten Ambelas Skjøth; Piotr Rapiejko; Kazimiera Chłopek; Katarzyna Dąbrowska-Zapart; Agnieszka Lipiec; Dariusz Jurkiewicz; Ewa Kalinowska; Barbara Majkowska-Wojciechowska; Dorota Myszkowska; Krystyna Piotrowska-Weryszko; Małgorzata Puc; Anna Rapiejko; Grzegorz Siergiejko; Elżbieta Weryszko-Chmielewska; Andrzej Wieczorkiewicz; Monika Ziemianin
Journal:  Int J Biometeorol       Date:  2020-11-11       Impact factor: 3.787

4.  Analysis of changes in Betula pollen season start including the cycle of pollen concentration in atmospheric air.

Authors:  Agnieszka Kubik-Komar; Krystyna Piotrowska-Weryszko; Izabela Kuna-Broniowska; Elżbieta Weryszko-Chmielewska; Bogusław Michał Kaszewski
Journal:  PLoS One       Date:  2021-08-23       Impact factor: 3.240

5.  Detection and Recognition of Pollen Grains in Multilabel Microscopic Images.

Authors:  Elżbieta Kubera; Agnieszka Kubik-Komar; Paweł Kurasiński; Krystyna Piotrowska-Weryszko; Magdalena Skrzypiec
Journal:  Sensors (Basel)       Date:  2022-03-31       Impact factor: 3.576

6.  Deep Learning Methods for Improving Pollen Monitoring.

Authors:  Elżbieta Kubera; Agnieszka Kubik-Komar; Krystyna Piotrowska-Weryszko; Magdalena Skrzypiec
Journal:  Sensors (Basel)       Date:  2021-05-19       Impact factor: 3.576

7.  Temporal and spatiotemporal autocorrelation of daily concentrations of Alnus, Betula, and Corylus pollen in Poland.

Authors:  J Nowosad; A Stach; I Kasprzyk; Ł Grewling; M Latałowa; M Puc; D Myszkowska; E Weryszko-Chmielewska; K Piotrowska-Weryszko; K Chłopek; B Majkowska-Wojciechowska; A Uruska
Journal:  Aerobiologia (Bologna)       Date:  2014-11-15       Impact factor: 2.410

8.  A model to predict the incidence of allergic rhinitis based on meteorological factors.

Authors:  Yuhui Ouyang; Jin Li; Deshan Zhang; Erzhong Fan; Ying Li; Luo Zhang
Journal:  Sci Rep       Date:  2017-08-30       Impact factor: 4.379

9.  Selection of morphological features of pollen grains for chosen tree taxa.

Authors:  Agnieszka Kubik-Komar; Elżbieta Kubera; Krystyna Piotrowska-Weryszko
Journal:  Biol Open       Date:  2018-04-30       Impact factor: 2.422

  9 in total

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