Centre for Marine and Renewable Energy (MaREI) - Doctoral Theses
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Item Applications of big data and machine learning in global energy system modelling(University College Cork, 2022) Joshi, Siddharth; O'Gallachoir, Brian; Holloway, Paul; Glynn, James; Science Foundation IrelandGlobal efforts to limit atmospheric warming well below 2 degree celcius above pre-industrial levels form the backbone of our response to mitigate the detrimental effects of climate change. The energy sector contributes circa 75% of global GHG emissions, amongst which the Electricity and Heat sectors each contribute ~40%, and the Transport sector contributes ~20% to the total global energy-related GHG emissions. The recent IPCC AR6 report finds that in nearly all possible emission scenarios considered, the world is heading towards a 1.5 degree celcius global temperature rise by the early 2030s. Pursuant to this, Energy Systems Models (ESMs) and Integrated Assessment Models (IAMs) are essential tools that provide energy system pathways to limit global warming below the temperature threshold. Thus, improving the accuracies of ESMs and IAMs will lead to measurable improvement in energy policy formulation and evaluation,thereby increasing the likelihood of meeting the commitments under the Paris Climate Agreement. This thesis develops and applies novel frameworks and methods that use a big data and machine learning driven strategy to improve the technology potential assessment of global decentralised solar PV technology and projection of transport energy service demand. The frameworks and methods developed in this thesis are presented in a format of methodological design principles followed by a case study using them. Specifically, on the supply side, the thesis investigates the global high-resolution spatiotemporal technical potential of rooftop solar PV for 2015 and further growth in the technical potentials from 2020-2050. For this assessment case study, the developed framework utilises a suite of GIS derived geospatial metrics in conjunction with a custom machine learning framework to calculate the global rooftop area at a high spatial resolution. Further using an IAM, the role of decentralised solar PV in global future energy transitions is explored. On the demand side, the thesis introduces a new machine learning model called ‘TrebuNet’ that is capable of high accuracy in estimating future energy service demand in the transport sector. The thesis thus provides the first development of machine learning and GIS based methods to improve the accuracy of global ESMs and IAMs. Particular attention is also paid towards the reproduction and transparency of the methods and the frameworks developed in this thesis for cross- disciplinary research. The thesis contributes to the important task of climate change mitigation by providing a bridge between mature IAM and ESM modelling and emerging machine learning-big data-driven tools. In doing so, this thesis demonstrates how the emerging methods in conjunction with large geospatial open source data, can aid in improving the technology representation of variable renewable energy technology in energy systems. The thesis also lays the foundation for providing solutions to energy system related tasks that are currently limited by high computational costs and data. The datasets and analysis generated by this thesis are presently assisting in unlocking the global role of decentralised renewable energy technologies in future energy systems and are also encouraging shifts in national decarbonisation pathways.Item Sediment transport modelling and geomorphological assessments related to offshore renewable energy developments in the Irish Sea(University College Cork, 2022) Creane, Shauna; Murphy, Jimmy; O'Shea, Michael; Coughlan, Mark; Irish Research Council for Science, Engineering and TechnologyA combination of in-situ geophysical, geological and oceanographic datasets, and advanced numerical modelling tools are used to: improve the understanding of hydrodynamics and morphodynamics in the Irish Sea, develop new methods and approaches to investigate hydrodynamics and seabed morphodynamics in an offshore setting, collect and produce novel datasets that will contribute to this scientific field, and facilitate the sustainable growth of anthropogenic activities in the Irish Sea. These new methods and approaches include, using process-based indicators to understand sediment wave development and distribution, utilising ADCP-based suspended solids concentration as a numerical model calibration tool, and the application of a ‘sediment budget’ to an offshore sand bank to understand external influences on the stability of its morphodynamic system. Results provide hydrodynamic proof underpinning the presence of the bed load parting (BLP) in central Irish Sea and associated divergent sediment transport pathways driving sediment dispersal across this tidally-dominated continental shelf sea. Analysis of tidal propagation through the Irish Sea Basin concludes that the origin of the BLP is mainly attributed to the intersection of the north and south tidal fronts at an inclined angle due to Coriolis Forcing and coastline interactions. Minor factors impacting the shape and location of the BLP are the change in tidal character at (a) abrupt bathymetry changes, (b) headlands and intricate coastline topography, and (c) large-scale constrictions. These outcomes set the basis of understanding for the thesis. Building upon this knowledge, analysis of targeted, high resolution, time-lapse bathymetry datasets in the south-western Irish Sea reveals sediment waves in a range of sizes (height = 0.1 to 25.7 m, and wavelength = 17 to 983 m), occurring in water depths of 8.2 to 83 mLAT, and migrating at a rate of 1.1 to 79 m/yr. Combined with numerical modelling outputs, a strong divergence of sediment transport pathways from the previously understood predominantly southward flow in the south Irish Sea is revealed. Furthermore, a new source and sink mechanism are defined for offshore independent sediment wave assemblages, whereby each sediment wave field is supported by circulatory residual current cells originating from offshore sand banks. Reliable sediment transport modelling is required to investigate these physical processes further, therefore, the need for cost-effective sediment validation datasets for 2D sediment transport models is addressed, utilising ADCP-based datasets. A robust spatial timeseries of ADCP-based suspended solids concentration was successfully calculated in an offshore, tidally-dominated setting. Three new validation techniques are deemed advantageous in developing an accurate 2D suspended sediment transport, including i) validation of 2D modelled suspended sediment concentration using water sample-based suspended solids concentration, ii) validation of the flood-ebb characteristics of 2D modelled suspended load transport and suspended sediment concentration using ADCP-based datasets and iii) validation of the 2D modelled peak suspended sediment concentration over a spring-neap cycle using the ADCP-based suspended solids concentration. The robust coupled hydrodynamic and sediment transport model produced from this research is used as a tool of investigation in subsequent chapters. The complex hydrodynamic processes controlling upper slope mobility and long-term base stability of Arklow Bank are determined. Results reveal a flood and ebb tidal current dominance on the west and east side of the bank respectively, ultimately generating a large anticlockwise residual current eddy encompassing the entire bank. The positioning of multiple off-bank anticlockwise residual current eddies on the edge of this cell is shown to both facilitate and inhibit east-west fluctuations of the upper slopes of the bank and control long-term bank base stability. Within Arklow Bank’s morphological cell, eight morphodynamically and hydrodynamically unique bank sections or ‘sub-cells’ are identified, whereby a complex morphodynamic-hydrodynamic feedback loop is present. The local east-west fluctuation of the upper slopes of the bank is driven by migratory on-bank stationary and transient clockwise residual eddies and the development of ‘narrow’ residual current cross-flow zones. Together these processes drive upper slope mobility but maintain long term bank base stability. A sediment budget was successfully estimated for an offshore linear sand bank, Arklow Bank, whereby seven source and nine sink pathways are identified. The restriction of sediment sources off the southern extent of Arklow Bank impact erosion and accretion patterns in the mid and northern sections of the bank after just one lunar month simulation. Where tidal current is the primary driver of sand bank morphodynamics, wind- and wave-induced flow is shown to alter sediment distribution patterns. This advanced body of work forms a robust scientific evidence-base to facilitate the sustainable growth of offshore renewable developments.Item Development and implementation of a framework to aid the transition to proactive maintenance approaches on air handling units in the industrial setting(University College Cork, 2023) Ahern, Michael; Bruton, Ken; O'Sullivan, Dominic; Science Foundation IrelandThis research explores the transition to proactive maintenance of HVAC equipment, specifically AHUs in industrial facilities, to make progress towards climate goals. HVAC systems account for 14% of global energy consumption, with the potential to increase efficiency by 20% by addressing energy-wasting faults according to Roth et al. However, these faults are difficult to detect due to their compensating control logic. This research highlights the potential of digitalisation techniques, particularly AI, to identify and rectify these faults, which would contribute to an approximate 2.8% global efficiency improvement. Notably, the study focuses on the nuances of industrial facilities, which have received limited attention compared to other building types. The research identifies several gaps in existing literature, including the knowledge gap between proactive data analysis and reactive engineering mind-sets, the data gap between high-quality experimental datasets and poor-quality industrial datasets, the operational gap between known baselines in experimental studies and unknown baselines in industrial settings, and the practice-theory gap between data-driven approaches in the literature and rule-based approaches in commercial tools. To address the knowledge gap, this thesis presents the IDAIC framework, a domain knowledge integration-type adaptation of the CRISP-DM process model. The implementation of the framework in an industrial facility to curate a dataset and develop a data assessment decision tree has contributed towards closing the data gap. Additionally, the study proposes extensions to the APAR ruleset and a practical data-driven fault detection method to address the operational gap. The deployment of the IDAIC framework as a tool leverages the UML modelling language to address practical considerations and demonstrate the approach's flexibility. Therefore, the main research outputs include the IDAIC framework, an industrial AHU dataset, a data assessment decision tree, an extension to the APAR ruleset, and a proactive maintenance decision support tool. Notably, this research unveils a fault in which the outside air damper is stuck in the fully open position, leading to estimated annual savings of €60,000. These findings validate the effectiveness of a human-centric, domain expertise-integrated approach that is resilient to industrial challenges, contributing to sustainable energy efficiency improvements and the achievement of climate targets using the best available solutions.Item How seabirds respond to a changing oceanic environment: a biologging approach(University College Cork, 2023) Darby, Jamie; Jessopp, Mark John; Quinn, John; Irish Research Council; Petroleum Infrastructure ProgramMarine habitats are undergoing rapid change due to human influences. The intensity and diversity of human impacts on oceanic habitats are increasing with rising demand for energy and resources. For example, fisheries operate in over 90% of the ocean, harvesting marine life and directly affecting ecosystem functions and resilience. Climate change is also changing the physical and chemical properties of the ocean and altering storm frequency and intensity at a global scale. Seabirds are a group of marine predators that are sensitive to such changes, with impacts contributing to global population declines. We broadly understand how stressors affect different species through effects on life histories and physiological traits, and where seabirds are most impacted based on spatiotemporal overlap of seabirds with human activities. However, finer scale behavioural data are required to understand the functional response of seabirds to different stressors. Biologging devices are continuously improving and miniaturising, being applied to collect fine-scale behavioural information for smaller species and for more protracted durations. In this thesis, biotelemetry is used to investigate the at-sea behaviour of three North Atlantic seabird species in order to understand the drivers of distribution. A better understanding of such drivers sheds light on the challenges facing seabird species when far from land, susceptibility to stressors, and provides insights into more effective monitoring and conservation efforts. Chapter 1 provides a broad introduction to seabird ecology, the application of biologging, and identifies model species for investigating seabird responses to a range of environmental stressors. Chapter 2 investigates the diving behaviour of Manx shearwaters (Puffinus puffinus) and how this correlates with water clarity, which is predicted to deteriorate with increasing urbanisation, eutrophication, and climate impacts. Chapter 3 highlights the relative importance of commercial fisheries compared to other environmental variables in driving the foraging distribution and behaviour of northern fulmars (Fulmarus glacialis) during the breeding season. Chapter 4 expands on this by identifying fulmar-vessel encounters in the non-breeding season, showing how nocturnal vessel attendance is increasing over time, and the apparent relationship with migration effort and time-activity budgets. Chapter 5 identifies unusual levels of variability in the moult period of Atlantic puffins (Fratercula arctica), when they are flightless and more susceptible to climate impacts that may prevent them from foraging. Variability in moult strategy is tied to susceptibility of populations to risks posed by severe winter storms. Chapter 6 provides a synthesis of findings from previous chapters, highlighting how the methods and principles developed may be built upon to further improve our knowledge of seabird ecology and design appropriate conservation measures. Building on insights from previous chapters, I discuss how seabirds are likely to functionally respond to several stressors in the marine environment, including fisheries practices, climate change, and shifting prey availability. Several recommendations are made for further research, including exploring mitigative measures that can be employed to tackle the negative effects of changes to their environment.Item The impact of UV radiation on the health and pathogen development of the Pacific oyster (Crassostrea gigas)(University College Cork, 2022-10-07) Kett, Gary; Culloty, Sarah C.; Lynch, Sharon A.; Jansen, Marcel A. K.; Horizon 2020 Framework Programme; European Regional Development FundPacific oysters Crassostrea gigas are cultured worldwide and play an important role in global food supply and the sustainable blue economy. Oyster culture sites in Europe, USA, Australasia, and Asia have been experiencing episodic summer mass mortality events. These mortality events can be severely damaging with significant impacts on stock reliability and profitability. Summer mass mortality events are believed to have a multifactorial aetiology driven by high water temperatures and the presence of pathogens, particularly Ostreid herpesvirus-1 and variants (OsHV-1 Var) and bacteria of the genus Vibrio such as V. aestuarianus. UV radiation (UVR) is an intertidal stressor which functions as an ecosystem regulator. UVR has disinfectant properties with the energetic potential to damage nucleic acids of microbes inhabiting surface waters. UVR can also have both positive and negative impacts on animal immune functioning by the activation or inactivation of certain biochemical pathways. Climate model predictions show UV levels changing globally due to changes in cloud cover, aerosols, ozone, and precipitation patterns. This study aimed to investigate the impact of UV radiation (UVR) on oyster health and pathogen performance. Firstly, a desk-based literature review study found that UVR predominantly hinders pathogens, although with varying efficacy, has mixed effects on aquatic invertebrates and has mixed effects on host-pathogen relationships. A clear knowledge gap was identified in that no study could be found which investigated the impact of UVR on bivalve health and survival. Vibrio bacteria are reported to be highly sensitive to UVR while herpesviruses either have high tolerance or can even be activated by solar UVR. UVR can be additive, synergistic, antagonistic, or neutral in outcomes of host-pathogen dynamics. Secondly, novel diagnostic methods for the detection and localisation of Vibrio bacteria within oyster tissues were designed, a generic conventional polymerase chain reaction PCR and a DIG-labelled in situ hybridisation (ISH) assay. These tools were designed to complement existing PCR and qPCR tools and allow for improved understanding of pathogen behaviour inside a C. gigas host exposed to UVR. Primers (VibF3/VibR3) were designed to amplify a 286 bp product from the 16S ribosomal RNA gene common to all Vibrio spp. and to form the ISH probe. ISH was carried out on C. gigas seed sourced from a V. aestuarianus endemic bay (n = 17) and on C. gigas juveniles sourced from a V. aestuarianus naive site (n = 12). Positive ISH signals were observed in PCR and qPCR positive C. gigas while no ISH signal was observed in uninfected samples from the naïve site. Direct Sangar sequencing of PCR products (n = 30), Blastn analysis and Clustal Omega alignments were used to confirm Vibrio sp. detection and assess similarity. Next, to examine the effect of supplemental UV-B on C. gigas seed, a set of laboratory-based experiments were constructed. Various size classes of C. gigas seed were exposed to two conditions: i) a short duration, high intensity UV-B exposure while immersed underwater or ii) a longer duration, low intensity UV-B exposure while emersed out of water. These experimental conditions were chosen to mimic tidal immersion and emersion. The intensity of exposure was lowered in the second trial in order to carry out the treatment over the length of a typical solar peak (midday) during low tide, with the total dose typical of what would be experienced in the south coast of Ireland on a clear summer day. The impact of UV exposure on oyster health was measured by monitoring survival daily, gill tissue DNA samples were used to monitor pathogen prevalence and intensity, and histological tissue cross-sections were examined for pathological damage. Results showed that UV-B exposure negatively impacted oyster survival, most notable in the smallest seed, reducing survival by up to 35%. UV-B also impeded the development of V. aestuarianus, although most effects were transitory and returned to pre-exposure infection levels within 1 - 3 days. Moribund oysters exposed to UV-B had significantly weaker V. aestuarianus infection intensities than moribund oysters in the control group. OsHV-1 Var was not detected in any sample throughout the experiment. These findings indicate that oyster mortality was caused by UV-B exposure rather than by pathogen infection. These data are the first reported impacts of UV-B on C. gigas health and the host-pathogen dynamic with V. aestuarianus. Results from this study suggest that UVR is likely to be a causative factor in C. gigas summer mass mortality episodes. Lastly, to bridge the prior findings to the natural environment, a field trial was designed on a commercial oyster culture cite to investigate the impact of shore grow-out height and the resulting emersion conditions including solar UVR on C. gigas and pathogen performance. Emersion has been shown to have mixed effects on C. gigas performance, though little is known about the impact of UVR in this host-pathogen-environment model. The field experiment in this study was carried out over 5 months, in July C. gigas seed (n = 570) were relayed in 6 replicate mesh bags split across two shore heights equating to a +4-hour emersion time in High Shore (HS) groups compared to the Low Shore (LS) cohort. Mortality (%) was counted in the field and samples (n = 30/shore height) were returned to the lab for pathogen screening for OsHV-1 Var and V. aestuarianus using PCR and qPCR. Increased oyster mortality was associated with emersion, particularly in periods of high UV exposure (>2.4 kJ/m2) and high air temperatures (>21 oC). Pathogen partitioning was observed, OsHV-1 Var was detected more in high shore cohorts while a higher prevalence of V. aestuarianus was detected in low shore C. gigas. Results indicate that environmental conditions impacted spat survival more so than pathogen infection. These findings further demonstrate that oyster mortality and infection levels are influenced by shore height and emersion time. Results from this study can be applied in husbandry practices to reduce losses during summer mass mortality events. Research outcomes are discussed in terms of the wider framework of theoretical knowledge and global development goals, future research questions are posed and recommendations for experimental design are offered. In terms of commercial application, specific husbandry practices are suggested based on the findings of this study, however additional research should be carried out to support or improve upon these recommendations.