Back-trajectories Show Export of Airborne Fungal Spores (Ganoderma sp.) From Forests to Agricultural and Urban Areas in England

We propose here the hypothesis that all of United Kingdom (UK) is likely to be affected by Ganoderma sp. spores, an important plant pathogen. We suggest that the main sources of this pathogen, which acts as a bioaerosol, are the widely scattered woodlands in the country, although remote sources must not be neglected. The hypothesis is based on related studies on bioaerosols and supported by new observations from a non-forest site and model calculations to support our hypothesis. Hourly concentrations of Ganoderma sp. spores were measured from 2006 to 2010 using a 7-day volumetric spore trap at the city of Worcester. The concentrations peak during the night and early in the morning. This suggests that the main spore sources are located a few hours away with respect to air masses transport and reach urban areas thanks to air masses transport. The back-trajectory analysis was applied to determine the location of Ganoderma sp. spore sources. The analysis of back-trajectories demonstrated that 78% of the air masses reached Worcester from a 180° arc direction from the East to West. Three episodes were selected for detailed investigation and they revealed that during the episodes air masses always passed main UK woodlands before the arrival in Worcester, independently of their origin, but the long distance transport under certain conditions might be possible. Our studies suggest that the sources of UK Ganoderma sp. spores are mainly to be found in UK. Hence our studies suggest that research and mitigation strategies in UK should give their main attention to national sources, without neglecting the contribution from long distance transport.

Atmospheric Concentrations of Alternaria, Cladosporium, Ganoderma and Didymella Spores Monitored in Cork (Ireland) and Worcester (England) During the Summer of 2010

This study represents the first international intercomparison of fungal spore observations since 1990, focusing on atmospheric concentrations of Alternaria, Cladosporium, Ganoderma and Didymella spores. The campaigns were performed at sites located in Cork (Ireland) and Worcester (England) during summer 2010. Observations were made using Hirst-type volumetric spore traps and corresponding optical identification at the genus level by microscope. The measurements at both sites (including meteorological parameters) were compared and contrasted. The relationships between the fungal spore concentrations with selected meteorological parameters were investigated using statistical methods and multivariate regression trees (MRT). The results showed high correlations between the two sites with respect to daily variations. Statistically significant higher spore concentrations for Alternaria, Cladosporium and Ganoderma were monitored at the Worcester site. This result was most likely due to the differences in precipitation and local fungal spore sources at the two sites. Alternaria and Cladosporium reached their maxima a month earlier in Cork than in Worcester, and Didymella with Ganoderma peaked simultaneously with similar diurnal trends found for all the investigated spore types. MRT analysis helped to determine threshold values of the meteorological parameters that exerted most influence on the presence of spores: they were found to vary at the two sites. Our results suggest that the aeromycological profile is quite uniform over the British Isles, but a description of bioaerosols with respect to overall load and daily concentration can be quite diverse although the geographical difference between sites is relatively small. These variations in the concentrations therefore need to be explored at the national level

Forecasting Methodologies for Ganoderma Spore Concentration Using Combined Statistical Approaches and Model Evaluations

High concentration levels of Ganoderma spp. spores were observed in Worcester, UK, during 2006–2010.These basidiospores are known to cause sensitization due to the allergen content and their small dimensions. This enables them to penetrate the lower part of the respiratory tract in humans. Establishment of a link between occurring symptoms of sensitization to Ganoderma spp. and other basidiospores is challenging due to lack of information regarding spore concentration in the air. Hence, aerobiological monitoring should be conducted, and if possible extended with the construction of forecast models. Daily mean concentration of allergenic Ganoderma spp. spores in the atmosphere of Worcester was measured using 7-day volumetric spore sampler through five consecutive years. The relationships between the presence of spores in the air and the weather parameters were examined. Forecast models were constructed for Ganoderma spp. spores using advanced statistical techniques, i.e. multivariate regression trees and artificial neural networks. Dew point temperature along with maximumtemperature was the most important factor influencing the presence of spores in the air of Worcester. Based on these two major factors and several others of lesser importance, thresholds for certain levels of fungal spore concentration, i.e. low (0–49 s m−3), moderate(50–99 s m−3), high (100–149 s m−3) and very high (150

Investigating and Predicting Atmospheric Concentrations of Allergenic Fungal Spores (Alternaria, Cladosporium, Didymella and Ganoderma)

Air quality is an increasing concern of the European Union, local authorities, scientists and most of all inhabitants that become more aware of the quality of the surrounding environment. Bioaerosols may be consisted of various elements, and the most important are pollen grains, fungal spores, bacteria, viruses. More than 100 genera of fungal spores have been identified as potential allergens that cause immunological response in susceptible individuals. Alternaria and Cladosporium have been recognised as the most important fungal species responsible for respiratory tract diseases, such as asthma, eczema, rhinitis and chronic sinusitis. While a lot of attention has been given to these fungal species, a limited number of studies can be found on Didymella and Ganoderma, although their allergenic properties were proved clinically. Monitoring of allergenic fungal spore concentration in the air is therefore very important, and in particular at densely populated areas like Worcester, UK. In this thesis a five year spore data set was presented, which was collected using a 7-day volumetric spore trap, analysed with the aid of light microscopy, statistical tests and geographic information system techniques. Although Kruskal-Wallis test detected statistically significant differences between annual concentrations of all examined fungal spore types, specific patterns in their distribution were also found. Alternaria spores were present in the air between mid-May/mid-June until September-October with peak occurring in August. Cladosporium sporulated between mid-May and October, with maximum concentration recorded in July. Didymella spores were seen from June/July up to September, while peaks were found in August. Ganoderma produced spores for 6 months (May-October), and maximum concentration could be found in September. With respect to diurnal fluctuations, Alternaria peaked between 22:00h and 23:00h, Cladosporium 13:00-15:00h, Didymella 04:00-05:00h and 22:00h-23:00h and Ganoderma from 03:00h to 06:00h. Spatial analysis showed that sources of all fungal species were located in England, and there was no evidence for a long distance transport from the continent. The maximum concentration of spores was found several hours delayed in comparison to the approximate time of the spore release from the crops. This was in agreement with diurnal profiles of the spore concentration recorded in Worcester, UK. Spores of Alternaria, Didymella and Ganoderma revealed a regional origin, in contrast to Cladosporium, which sources were situated locally. Hence, the weather conditions registered locally did not exhibit strong statistically significant correlations with fungal spore concentrations. This has had also an impact on the performance of the forecasting models. The best model was obtained for Cladosporium with 66% of the accuracy.