TY - JOUR
T1 - Airborne Alternaria and Cladosporium fungal spores in Europe: Forecasting possibilities and relationships with meteorological parameters
AU - Grinn-Gofroń, Agnieszka
AU - Nowosad, Jakub
AU - Bosiacka, Beata
AU - Camacho, Irene
AU - Pashley, Catherine
AU - Belmonte, Jordina
AU - De Linares, Concepción
AU - Ianovici, Nicoleta
AU - Manzano, Jose María Maya
AU - Sadyś, Magdalena
AU - Skjøth, Carsten
AU - Rodinkova, Victoria
AU - Tormo-Molina, Rafael
AU - Vokou, Despoina
AU - Fernández-Rodríguez, Santiago
AU - Damialis, Athanasios
N1 - Copyright © 2018 Elsevier B.V. All rights reserved.
PY - 2019/2/25
Y1 - 2019/2/25
N2 - © 2018 Elsevier B.V. Airborne fungal spores are prevalent components of bioaerosols with a large impact on ecology, economy and health. Their major socioeconomic effects could be reduced by accurate and timely prediction of airborne spore concentrations. The main aim of this study was to create and evaluate models of Alternaria and Cladosporium spore concentrations based on data on a continental scale. Additional goals included assessment of the level of generalization of the models spatially and description of the main meteorological factors influencing fungal spore concentrations. Aerobiological monitoring was carried out at 18 sites in six countries across Europe over 3 to 21 years depending on site. Quantile random forest modelling was used to predict spore concentrations. Generalization of the Alternaria and Cladosporium models was tested using (i) one model for all the sites, (ii) models for groups of sites, and (iii) models for individual sites. The study revealed the possibility of reliable prediction of fungal spore levels using gridded meteorological data. The classification models also showed the capacity for providing larger scale predictions of fungal spore concentrations. Regression models were distinctly less accurate than classification models due to several factors, including measurement errors and distinct day-to-day changes of concentrations. Temperature and vapour pressure proved to be the most important variables in the regression and classification models of Alternaria and Cladosporium spore concentrations. Accurate and operational daily-scale predictive models of bioaerosol abundances contribute to the assessment and evaluation of relevant exposure and consequently more timely and efficient management of phytopathogenic and of human allergic diseases.
AB - © 2018 Elsevier B.V. Airborne fungal spores are prevalent components of bioaerosols with a large impact on ecology, economy and health. Their major socioeconomic effects could be reduced by accurate and timely prediction of airborne spore concentrations. The main aim of this study was to create and evaluate models of Alternaria and Cladosporium spore concentrations based on data on a continental scale. Additional goals included assessment of the level of generalization of the models spatially and description of the main meteorological factors influencing fungal spore concentrations. Aerobiological monitoring was carried out at 18 sites in six countries across Europe over 3 to 21 years depending on site. Quantile random forest modelling was used to predict spore concentrations. Generalization of the Alternaria and Cladosporium models was tested using (i) one model for all the sites, (ii) models for groups of sites, and (iii) models for individual sites. The study revealed the possibility of reliable prediction of fungal spore levels using gridded meteorological data. The classification models also showed the capacity for providing larger scale predictions of fungal spore concentrations. Regression models were distinctly less accurate than classification models due to several factors, including measurement errors and distinct day-to-day changes of concentrations. Temperature and vapour pressure proved to be the most important variables in the regression and classification models of Alternaria and Cladosporium spore concentrations. Accurate and operational daily-scale predictive models of bioaerosol abundances contribute to the assessment and evaluation of relevant exposure and consequently more timely and efficient management of phytopathogenic and of human allergic diseases.
KW - Advanced statistical models
KW - Aerobiology
KW - Bioaerosols
KW - Biometeorology
KW - Continental scale
KW - Molds
UR - http://www.mendeley.com/research/airborne-alternaria-cladosporium-fungal-spores-europe-forecasting-possibilities-relationships-meteor
U2 - 10.1016/j.scitotenv.2018.10.419
DO - 10.1016/j.scitotenv.2018.10.419
M3 - Article
C2 - 30759619
SN - 0048-9697
VL - 653
SP - 938
EP - 946
JO - Science of the Total Environment
JF - Science of the Total Environment
ER -