Determination of Alternaria spp. Habitats Using 7-Day Volumetric Spore Trap, Hybrid Single Particle Lagrangian Integrated Trajectory Model and Geographic Information System

There are many species among the Alternaria genus, which hosts on economically important crops causing significant yield losses. Less attention has been paid to fungi hosting on plants constituting substantial components of pastures and meadows. Alternaria spp. spores are also recognised as important allergens. A 7-day volumetric spore trap was used to monitor the concentration of airborne fungal spores. Air samples were collected in Worcester, England (2006–2010). Days with a high spore count were then selected. The longest episode that occurred within a five year study was chosen for modelling. Two source maps presenting distribution of crops under rotation and pastures in the UK were produced. Back trajectories were calculated using the HYSPLIT model. In ArcGIS clusters of trajectories were studied in connection with source maps by including the height above ground level and the speed of the air masses. During the episode no evidence for a long distance transport from the continent of Alternaria spp. spores was detected. The overall direction of the air masses fell within the range from South-West to North. The back trajectories indicated that the most important sources of Alternaria spp. spores were located in the West Midlands of England.

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.