title: Forecasting spore concentrations: a time series approach.
abstract: Fungal basidiospores and Cladosporium spores are the two most numerous spore types in the air of Dublin and its surroundings. They are known to have allergenic components, and the aim of the study described here is to develop a predictive model for these spores. A very simple model, which combines an estimated diurnal rhythm with a simple, one-parameter time series model, provided good short-term forecasts. The one-step prediction error variance was reduced by 88% for Cladosporium spores and by 98% for basidiospores.
authors.affiliation: Im Mahden 38, Ehningen, Federal Republic of Germany.
authors.forename: E
authors.initials: E
authors.lastname: Stephen
authors.forename: A E
authors.initials: AE
authors.lastname: Raftery
authors.forename: P
authors.initials: P
authors.lastname: Dowding
mesh_terms: D000391:Air Microbiology; D001487:Basidiomycota; D002940:Circadian Rhythm; D002963:Cladosporium; D008685:Meteorological Concepts; D015233:Models, Statistical; D011058:Pollen; D013172:Spores, Fungal