Journal
ENVIRONMENTAL POLLUTION
Volume 159, Issue 2, Pages 602-608Publisher
ELSEVIER SCI LTD
DOI: 10.1016/j.envpol.2010.10.002
Keywords
Fungal spores; Air pollutants; Meteorological parameters; Artificial neural networks
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Funding
- Ministry of Science and Higher Education [N N305 367738]
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Fungal spores are an important component of bioaerosol and also considered to act as indicator of the level of atmospheric bio-pollution. Therefore, better understanding of these phenomena demands a detailed survey of airborne particles. The objective of this study was to examine the dependence of two the most important allergenic taxa of airborne fungi Alternaria and Cladosporium on meteorological parameters and air pollutant concentrations during three consecutive years (2006-2008). This study is also an attempt to create artificial neural network (ANN) forecasting models useful in the prediction of aeroallergen abundance. There were statistically significant relationships between spore concentration and environmental parameters as well as pollutants, confirmed by the Spearman's correlation rank analysis and high performance of the ANN models obtained. The concentrations of Cladosporium and Alternaria spores can be predicted with quite good accuracy from meteorological conditions and air pollution recorded three days earlier. (C) 2010 Elsevier Ltd. All rights reserved.
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