Dew Point Temperature Affects Ascospore Release of Allergenic Genus Leptosphaeria

The genus Leptosphaeria contains numerous fungi that cause the symptoms of asthma and also parasitize wild and crop plants. In search of a robust and universal forecast model, the ascospore concentration in air was measured and weather data recorded from 1 March to 31 October between 2006 and 2012. The experiment was conducted in three European countries of the temperate climate, i.e., Ukraine, Poland, and the UK. Out of over 150 forecast models produced using artificial neural networks (ANNs) and multivariate regression trees (MRTs), we selected the best model for each site, as well as for joint two-site combinations. The performance of all computed models was tested against records from 1 year which had not been used for model construction. The statistical analysis of the fungal spore data was supported by a comprehensive study of both climate and land cover within a 30-km radius from the air sampler location. High-performance forecasting models were obtained for individual sites, showing that the local micro-climate plays a decisive role in biology of the fungi. Based on the previous epidemiological studies, we hypothesized that dew point temperature (DPT) would be a critical factor in the models. The impact of DPT was confirmed only by one of the final best neural models, but the MRT analyses, similarly to the Spearman's rank test, indicated the importance of DPT in all but one of the studied cases and in half of them ranked it as a fundamental factor. This work applies artificial neural modeling to predict the Leptosphaeria airborne spore concentration in urban areas for the first time

Occurrence of Didymella ascospores in western and southern Poland in 2004–2006

The concentration of airborne Didymella spores has been investigated at two monitoring sites situated along the west–south transect in Poland (Szczecin, Kraków), i.e. from a height of 100 to 219 m, respectively, above sea level. The aerobiological monitoring of fungal spores was performed by means of two Lanzoni volumetric spore traps. The high Didymella spore numbers were observed at both cities in June, July and August. Statistically significant correlations have been found mainly between the Didymella spore concentrations in the air and the minimum air temperature and relative air humidity. The spore count of Didymella is determined by the diversity of local flora and weather conditions, especially by the relative air humidity. The identification of factors that influence and shape spore concentrations may significantly improve the current methods of allergy prevention

Alternaria Spores in the Air Across Europe: Abundance, Seasonality and Relationships with Climate, Meteorology and Local Environment

We explored the temporal and spatial variations in airborne Alternaria spore quantitative and phenological features in Europe using 23 sites with annual time series between 3 and 15 years. The study covers seven countries and four of the main biogeographical regions in Europe. The observations were obtained with Hirst-type spore traps providing time series with daily records. Site locations extend from Spain in the south to Denmark in the north and from England in the West to Poland in the East. The study is therefore the largest assessment ever carried out for Europe concerning Alternaria. Aerobiological data were investigated for temporal and spatial patterns in their start and peak season dates and their spore indices. Moreover, the effects of climate were checked using meteorological data for the same period, using a crop growth model. We found that local climate, vegetation patterns and management of landscape are governing parameters for the overall spore concentration, while the annual variations caused by weather are of secondary importance but should not be neglected. The start of the Alternaria spore season varies by several months in Europe, but the peak of the season is more synchronised in central northern Europe in the middle of the summer, while many southern sites have peak dates either earlier or later than northern Europe. The use of a crop growth model to explain the start and peak of season suggests that such methods could be useful to describe Alternaria seasonality in areas with no available observations

The effects of meteorological factors on the occurrence of Ganoderma sp. spores in the air

Ganoderma sp. is an airborne fungal spore type known to trigger respiratory allergy symptoms in sensitive patients. Aiming to reduce the risk for allergic individuals, we analysed fungal spore circulation in Szczecin, Poland, and its dependence on meteorological conditions. Statistical models for the airborne spore concentrations of Ganoderma sp.—one of the most abundant fungal taxa in the area—were developed. Aerobiological sampling was conducted over 2004–2008 using a volumetric Lanzoni trap. Simultaneously, the following meteorological parameters were recorded: daily level of precipitation, maximum and average wind speed, relative humidity and maximum, minimum, average and dew point temperatures. These data were used as the explaining variables. Due to the non-linearity and non-normality of the data set, the applied modelling techniques were artificial neural networks (ANN) and mutlivariate regression trees (MRT). The obtained classification and MRT models predicted threshold conditions above which Ganoderma sp. appeared in the air. It turned out that dew point temperature was the main factor influencing the presence or absence of Ganoderma sp. spores. Further analysis of spore seasons revealed that the airborne fungal spore concentration depended only slightly on meteorological factors

Effects of Wind Speed and Direction on Monthly Fluctuations of Cladosporium Conidia Concentration in the Air

This study determined the relationship between airborne concentration of Cladosporium spp. spores and wind speed and direction using real data (local wind measured by weather station) and modelled data (air mass flow computed with the aid of HYbrid Single Particle Lagrangian Trajectory model). Air samples containing fungal conidia were taken at an urban site (Worcester, UK) for a period of five consecutive years using a spore trap of the Hirst design. A threshold of ≥6000 s m−3 (double the clinical value) was applied in order to select high spore concentration days, when airborne transport of conidia at a regional scale was more likely to occur. Collected data were then examined using geospatial and statistical tools, including circular statistics. Obtained results showed that the greatest numbers of spore concentrations were detected in July and August, when C. herbarum, C. cladosporioides and C. macrocarpum sporulate. The circular correlation test was found to be more sensitive than Spearman’s rank test. The dominance of either local wind or the air mass on Cladosporium spore distributions varied between examined months. Source areas of this pathogen had an origin within the UK territory. Very high daily mean concentrations of Cladosporium spores were observed when daily mean local wind speed was vs ≤ 2.5 m s−1 indicating warm days with a light breeze

Airborne Alternaria and Cladosporium Fungal Spores in Europe: Forecasting Possibilities and Relationships with Meteorological Parameters

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 in space 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 values. 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

Airborne Alternaria and Cladosporium Fungal Spores in Europe: Forecasting Possibilities and Relationships with Meteorological Parameters

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 in space 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 values. 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

Spatial and Temporal Variations in the Annual Pollen Index Recorded by Sites Belonging to the Portuguese Aerobiology Network

This study presents the findings of a 10-year survey carried out by the Portuguese Aerobiology Network (RPA) at seven pollen-monitoring stations: five mainland stations (Oporto, Coimbra, Lisbon, Évora and Portimão) and two insular stations [Funchal (Madeira archipelago) and Ponta Delgada (Azores archipelago)]. The main aim of the study was to examine spatial and temporal variations in the Annual Pollen Index (API) with particular focus on the most frequently recorded pollen types. Pollen monitoring (2003–2012) was carried out using Hirst-type volumetric spore traps, following the minimum recommendations proposed by the European Aerobiology Society Working Group on Quality Control. Daily pollen data were examined for similarities using the Kruskal–Wallis nonparametric test and multivariate regression trees. Simple linear regression analysis was used to describe trends in API. The airborne pollen spectrum at RPA stations is dominated by important allergenic pollen types such as Poaceae, Olea and Urticaceae. Statistically significant differences were witnessed in the API recorded at the seven stations. Mean API is higher in the southern mainland cities, e.g. Évora, Lisbon and Portimão, and lower in insular and littoral cities. There were also a number of significant trends in API during the 10-year study. This report identifies spatial and temporal variations in the amount of airborne pollen recorded annually in the Portuguese territory. There were also a number of significant changes in API, but no general increases in the amount of airborne pollen