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Development and deployment of a novel in situ multiparameter optical sensor for marine and freshwater environments

Power, Sean (2024) Development and deployment of a novel in situ multiparameter optical sensor for marine and freshwater environments. PhD thesis, Dublin City University.

Global warming and pollution due to human activities has had a major impact on the world’s waterbodies which are vital for sustaining life on this planet. With this rapid escalation of threat to the oceans, seas, lakes, and rivers there has been an increased focus and urgency to monitor these changes to better understand the consequences of our anthropogenic impact. This culminates in a greater need for monitoring technologies to gather real-time data with high temporal and spatial resolutions to provide a holistic understanding of the changes to the waterbodies and inform regulations to protect our waters from further damage. The bridge the technological and research gaps required to sufficiently monitor the aquatic environments the work presented in this thesis aimed to demonstrate the design and development of beyond state of the art in situ optical detection by applying advanced optical and electronic components. A unique and novel design was produced by applying two mini spectrometers, a multispectral LED array light source, a photodiode, and custom electronics for interfacing with the optical system and housing the system in a robust enclosure using advanced manufacturing methods. The finalised system and enclosure design was replicated by manufacturing multiple identical systems as low-cost going beyond what is currently being achieved in the research field. The systems were demonstrated to have superior multispectral and multiparameter optical measurement capabilities when compared to current commercial systems with higher resolution detection of chlorophyll and turbidity as well as the ability to measure other tested analytes of petroleum and dissolved organic matter. The built systems showed robustness through repeated deployments and provided insightful data on the locations of deployment measuring multiple different environmental events while in situ.
Item Type:Thesis (PhD)
Date of Award:March 2024
Supervisor(s):Regan, Fiona and Kent, Nigel
Subjects:Computer Science > Artificial intelligence
Computer Science > Machine learning
Engineering > Environmental engineering
Engineering > Signal processing
Physical Sciences > Chemical detectors
Physical Sciences > Environmental chemistry
Physical Sciences > Photonics
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:Enterprise Ireland
ID Code:29381
Deposited On:25 Mar 2024 15:10 by Fiona Regan . Last Modified 25 Mar 2024 15:10

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