ArticleInternational journal of biometeorology2016
Regional forecast model for the Olea pollen season in Extremadura (SW Spain).
Article in International journal of biometeorology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Climate change, airborne allergens, and three translational mitigation approaches.EBioMedicine · 2023Review
- Predicting the Olea pollen concentration with a machine learning algorithm ensemble.International journal of biometeorology · 2021Article
- Urban atmospheric levels of allergenic pollen: comparison of two locations in Salamanca, Central-Western Spain.Environmental monitoring and assessment · 2020Article
- Aerobiology in the International Journal of Biometeorology, 1957-2017.International journal of biometeorology · 2017Article
- The rise of phenology with climate change: an evaluation of IJB publications.International journal of biometeorology · 2017Article
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Authors and funding
6 authors.
Funding
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Abstract
The olive tree (Olea europaea) is a predominantly Mediterranean anemophilous species. The pollen allergens from this tree are an important cause of allergic problems. Olea pollen may be relevant in relation to climate change, due to the fact that its flowering phenology is related to meteorological parameters. This study aims to investigate airborne Olea pollen data from a city on the SW Iberian Peninsula, to analyse the trends in these data and their relationships with meteorological parameters using time series analysis. Aerobiological sampling was conducted from 1994 to 2013 in Badajoz (SW Spain) using a 7-day Hirst-type volumetric sampler. The main Olea pollen season lasted an average of 34 days, from May 4th to June 7th. The model proposed to forecast airborne pollen concentrations, described by one equation. This expression is composed of two terms: the first term represents the resilience of the pollen concentration trend in the air according to the average concentration of the previous 10 days; the second term was obtained from considering the actual pollen concentration value, which is calculated based on the most representative meteorological variables multiplied by a fitting coefficient. Due to the allergenic characteristics of this pollen type, it should be necessary to forecast its short-term prevalence using a long record of data in a city with a Mediterranean climate. The model obtained provides a suitable level of confidence to forecast Olea airborne pollen concentration.
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