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Aerobiologia

, Volume 33, Issue 4, pp 517–528 | Cite as

Poaceae pollen in the atmosphere of Tetouan (NW Morocco): effect of meteorological parameters and forecast of daily pollen concentration

  • Asmae Janati
  • Hassan Bouziane
  • Maria del Mar Trigo
  • Mohamed Kadiri
  • Mohamed Kazzaz
Original Paper

Abstract

The Poaceae pollen season has been characterized in Tetouan during a 7-year period, and the effect of weather conditions on daily concentrations was examined. The forecast models were produced using a stepwise multiple regression analyses. Firstly, three models were constructed to predict daily Poaceae pollen concentrations during the main pollen season, as well as the pre-peak and post-peak periods with data from 2008 to 2012 and tested on data from 2013 and 2014. Secondly, the regression models using leave-one-out cross-validation were produced with data obtained during 2008–2014 taking into account meteorological parameters and mean pollen concentrations of the same day in other years. The duration of the season ranged from 70 days in 2009 to 158 days in 2012. The highest amount of Poaceae pollen was detected in spring and the first fortnight of July. The annual sum of airborne Poaceae pollen concentrations varied between 2100 and 6251. The peak of anthesis was recorded in May in six of the other years studied. The regression models accounted for 36.3–85.7% of variance in daily Poaceae pollen concentrations. The models fitted best when the mean pollen concentration of the same day in other years was added to meteorological variables, and explained 78.4–85.7% of variance of the daily pollen changes. When the year 2014 was used for validating the models, the lowest root-mean-square errors values were found between the observed and estimated data (around 13). The reasonable predictor variables were the mean pollen concentration of the same day in other years, mean temperature, precipitations, and maximum relative humidity.

Keywords

Aerobiology Grass pollen Concentration changes Meteorology Modeling Stepwise regression analysis 

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Copyright information

© Springer Science+Business Media B.V. 2017

Authors and Affiliations

  • Asmae Janati
    • 1
  • Hassan Bouziane
    • 1
  • Maria del Mar Trigo
    • 2
  • Mohamed Kadiri
    • 1
  • Mohamed Kazzaz
    • 1
  1. 1.Laboratory of Ecology, Biodiversity and Environment, Faculty of SciencesUniversity Abdelmalek EssaâdiTétouanMorocco
  2. 2.Department of Plant BiologyUniversity of MalagaMalagaSpain

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