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Predicting onset and duration of airborne allergenic pollen season in the United States
Abstract Allergenic pollen is one of the main triggers of Allergic Airway Disease (AAD) affecting 5%–30% of the population in industrialized countries. A modeling framework has been developed using correlation and collinearity analyses, simulated annealing, and stepwise regression based on nationwide observations of airborne pollen counts and climatic factors to predict the onsets and durations of allergenic pollen seasons of representative trees, weeds and grass in the contiguous United States. Main factors considered are monthly, seasonal and annual mean temperatures and accumulative precipitations, latitude, elevation, Growing Degree Day (GDD), Frost Free Day (FFD), Start Date (SD) and Season Length (SL) in the previous year. The estimated mean SD and SL for birch (Betula), oak (Quercus), ragweed (Ambrosia), mugwort (Artemisia) and grass (Poaceae) pollen season in 1994–2010 are mostly within 0–6 days of the corresponding observations for the majority of the National Allergy Bureau (NAB) monitoring stations across the contiguous US. The simulated spatially resolved maps for onset and duration of allergenic pollen season in the contiguous US are consistent with the long term observations.
Highlights A framework was established to optimize modeling of allergenic pollen season. Models were developed using observed airborne pollen data across the contiguous US. Estimated onset and duration are within 0–6 days of observations at most stations. Models are applicable to multiple species and spatiotemporal scales in large area. Models provide season onset and duration for operational pollen forecast model.
Predicting onset and duration of airborne allergenic pollen season in the United States
Abstract Allergenic pollen is one of the main triggers of Allergic Airway Disease (AAD) affecting 5%–30% of the population in industrialized countries. A modeling framework has been developed using correlation and collinearity analyses, simulated annealing, and stepwise regression based on nationwide observations of airborne pollen counts and climatic factors to predict the onsets and durations of allergenic pollen seasons of representative trees, weeds and grass in the contiguous United States. Main factors considered are monthly, seasonal and annual mean temperatures and accumulative precipitations, latitude, elevation, Growing Degree Day (GDD), Frost Free Day (FFD), Start Date (SD) and Season Length (SL) in the previous year. The estimated mean SD and SL for birch (Betula), oak (Quercus), ragweed (Ambrosia), mugwort (Artemisia) and grass (Poaceae) pollen season in 1994–2010 are mostly within 0–6 days of the corresponding observations for the majority of the National Allergy Bureau (NAB) monitoring stations across the contiguous US. The simulated spatially resolved maps for onset and duration of allergenic pollen season in the contiguous US are consistent with the long term observations.
Highlights A framework was established to optimize modeling of allergenic pollen season. Models were developed using observed airborne pollen data across the contiguous US. Estimated onset and duration are within 0–6 days of observations at most stations. Models are applicable to multiple species and spatiotemporal scales in large area. Models provide season onset and duration for operational pollen forecast model.
Predicting onset and duration of airborne allergenic pollen season in the United States
Zhang, Yong (author) / Bielory, Leonard (author) / Cai, Ting (author) / Mi, Zhongyuan (author) / Georgopoulos, Panos (author)
Atmospheric Environment ; 103 ; 297-306
2014-12-04
10 pages
Article (Journal)
Electronic Resource
English
Pollen season , Allergy , Start date , Season length , Model , AAAAI , American Academy of Allergy, Asthma and Immunology , AAD , allergic airway disease , FFD , frost free day , GDD , growing degree day , NAB , National Allergy Bureau , NARCCAP , North American Regional Climate Change Assessment Program , NOAA , National Oceanic and Atmospheric Administration , SD , start date , SL , season length , WRF , Weather Research & Forecasting model
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