Literature DB >> 16841868

Prediction of airborne Alnus pollen concentration by using ARIMA models.

Francisco Javier Rodríguez-Rajo1, Rosa Maria Valencia-Barrera, Ana María Vega-Maray, Francisco Javier Suárez, Delia Fernández-González, Victoria Jato.   

Abstract

To take preventative measures to protect allergic people from the severity of the pollen season, one of aerobiology's objectives is to develop statistical models enabling the short- and long-term prediction of atmospheric pollen concentrations. During recent years some attempts have been made to apply Time Series analysis, frequently used in biomedical studies and atmospheric contamination to pollen series. The aim of this study is to understand the behaviour of atmospheric alder pollen concentrations in northwest Spain in order to develop predictive models of pollen concentrations by using Time Series analysis. The prediction line proposed for Oviedo and Ponferrada are similar (Arima 2,0,1) while in Vigo a more accurate model founded by Arima (3,0,1) and in Leon (1,0,1) was used. The results suggest that Ponferrada and Oviedo are the cities in northwest Spain where Alnus pollen allergic individuals should to take preventive measures to protect themselves from the severity of the pollen season. Alnus pollen values higher than 30 grains/m3, a quantity considered sufficient to trigger severe allergy symptoms of other trees of the Betulaceae family, could be reached during 25 days in some years. The predicted lines conformed with the observed values overall in the case of Leon and Ponferrada. Time Series regression models are especially suitable in allergology for evaluating short-term effects of time-varying pollen appearance in the atmosphere.

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Year:  2006        PMID: 16841868

Source DB:  PubMed          Journal:  Ann Agric Environ Med        ISSN: 1232-1966            Impact factor:   1.447


  13 in total

1.  Biometeorological and autoregressive indices for predicting olive pollen intensity.

Authors:  J Oteros; H García-Mozo; C Hervás; C Galán
Journal:  Int J Biometeorol       Date:  2012-06-02       Impact factor: 3.787

2.  Forecasting ragweed pollen characteristics with nonparametric regression methods over the most polluted areas in Europe.

Authors:  László Makra; István Matyasovszky; Michel Thibaudon; Maira Bonini
Journal:  Int J Biometeorol       Date:  2010-07-13       Impact factor: 3.787

Review 3.  Diurnal variations of airborne pollen concentration and the effect of ambient temperature in three sites of Mexico City.

Authors:  B Ríos; R Torres-Jardón; E Ramírez-Arriaga; A Martínez-Bernal; I Rosas
Journal:  Int J Biometeorol       Date:  2015-10-02       Impact factor: 3.787

4.  Forecasting the start of Quercus pollen season using several methods - the evaluation of their efficiency.

Authors:  Idalia Kasprzyk
Journal:  Int J Biometeorol       Date:  2009-04-16       Impact factor: 3.787

5.  Models to predict the start of the airborne pollen season.

Authors:  Consolata Siniscalco; Rosanna Caramiello; Mirco Migliavacca; Lorenzo Busetto; Luca Mercalli; Roberto Colombo; Andrew D Richardson
Journal:  Int J Biometeorol       Date:  2014-09-19       Impact factor: 3.787

6.  Modeling pollen time series using seasonal-trend decomposition procedure based on LOESS smoothing.

Authors:  Jesús Rojo; Rosario Rivero; Jorge Romero-Morte; Federico Fernández-González; Rosa Pérez-Badia
Journal:  Int J Biometeorol       Date:  2016-08-04       Impact factor: 3.787

7.  Predicting tree pollen season start dates using thermal conditions.

Authors:  Dorota Myszkowska
Journal:  Aerobiologia (Bologna)       Date:  2014-02-20       Impact factor: 2.410

8.  The patterns of Corylus and Alnus pollen seasons and pollination periods in two Polish cities located in different climatic regions.

Authors:  Małgorzata Puc; Idalia Kasprzyk
Journal:  Aerobiologia (Bologna)       Date:  2013-03-14       Impact factor: 2.410

9.  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

10.  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

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