Clancy, Jerry (2024) Monitoring and modelling of biological aerosols. PhD thesis, Dublin City University.
Abstract
The work completed had the primary aim of providing fungal spore monitoring capabilities to the
previously established Irish Pollen Network. This in turn lead to the creation of the first Irish Bioaerosol
Network for the simultaneous measurement of both pollen and fungal spores. The network was
established by traditional and real-time monitoring methods into the previously disparate traditional
sampling network (Dublin and Carlow). Full integration of sites in Cork and Sligo, and the collected
fungal spore data from all sites are being utilized to create an Irish fungal spore network.
This work primarily focused on the fungal spores in the ambient air, which have human health and
agricultural implications, with information on this being of great help to allergy sufferers as well as the
farming community, which is particularly susceptible to changes in fungal spore concentrations, as they
can damage crops.
The work involved a set of traditional device campaigns, from the analysis of old data collected decades
ago, to the collection of our own data at various sites nationwide. After this, several novel spectroscopic
techniques such as the WIBS-NEO and IBAC were implemented in a test centre in Dublin as part of a
real-time monitoring campaign for detection of ambient fungal spores, to determine the suitability of
these instruments for deployment in a wider multi-site sampling network. Finally, data generated via
both traditional and novel methods along with collected meteorological and pollution data was
combined, and the process of developing and refining a set of forecasting algorithms was carried out,
with a view to have full forecasting and predictive models in operation in the near future.
Metadata
Item Type: | Thesis (PhD) |
---|---|
Date of Award: | March 2024 |
Refereed: | No |
Supervisor(s): | O'Connor, David |
Subjects: | Biological Sciences > Botany Humanities > Biological Sciences > Botany Computer Science > Machine learning Physical Sciences > Analytical chemistry |
DCU Faculties and Centres: | DCU Faculties and Schools > Faculty of Science and Health > School of Chemical Sciences |
Use License: | This item is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 License. View License |
Funders: | Irish Reserach Council, Irish EPA |
ID Code: | 29434 |
Deposited On: | 26 Mar 2024 09:29 by David O'connor . Last Modified 26 Mar 2024 09:29 |
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