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

International Journal of Biometeorology
László MakraMaira Bonini

Abstract

Nonparametric time-varying regression methods were developed to forecast daily ragweed pollen concentration, and the probability of the exceedance of a given concentration threshold 1 day ahead. Five-day and 10-day predictions of the start and end of the pollen season were also addressed with a nonparametric regression technique combining regression analysis with the method of temperature sum. Our methods were applied to three of the most polluted regions in Europe, namely Lyon (Rhône Valley, France), Legnano (Po River Plain, Italy) and Szeged (Great Plain, Hungary). For a 1-day prediction of both the daily pollen concentration and daily threshold exceedance, the order of these cities from the smallest to largest prediction errors was Legnano, Lyon, Szeged and Legnano, Szeged, Lyon, respectively. The most important predictor for each location was the pollen concentration of previous days. The second main predictor was precipitation for Lyon, and temperature for Legnano and Szeged. Wind speed should be considered for daily concentration at Legnano, and for daily pollen threshold exceedances at Lyon and Szeged. Prediction capabilities compared to the annual cycles for the start and end of the pollen season decreased from west to ...Continue Reading

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Citations

Oct 22, 2013·Environment International·M SmithB Šikoparija
Sep 23, 2014·International Journal of Biometeorology·Consolata SiniscalcoAndrew D Richardson
Sep 23, 2014·Annals of Allergy, Asthma & Immunology : Official Publication of the American College of Allergy, Asthma, & Immunology·Lauren Eileen Howard, Estelle Levetin
Aug 25, 2020·Journal of Quantitative Spectroscopy & Radiative Transfer·Danaël CholletonAlain Miffre
Jul 10, 2021·The Science of the Total Environment·Andrés M Vélez-PereiraJordina Belmonte

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