Centre for Marine and Renewable Energy (MaREI) - Journal Articles
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Item Population structure and genetic connectivity reveals distinctiveness of Irish harbour seals (Phoca vitulina) and implications for conservation management(John Wiley & Sons, Inc., 2022-12-28) Steinmetz, Kristina; Murphy, Sinéad; Ó Cadhla, Oliver; Carroll, Emma L.; Onoufriou, Aubrie B.; Russell, Debbie J. F.; Cronin, Michelle; Mirimin, Luca; Galway-Mayo Institute of Technology; Department of Housing, Local Government and Heritage; National Parks and Wildlife ServiceThe identification of discrete intraspecific units, such as genetically informed management units (MUs), is important to effectively develop and implement conservation strategies for protected species. Harbour seals (Phoca vitulina) occurring in Irish waters are currently viewed as a single nationwide panmictic population (and hence MU), although this assumption is not based on any knowledge of population structure because of the lack of available genetic data. Thus, the present study used mitochondrial control region sequences and between nine and 11 microsatellite loci from harbour seals from Ireland and Northern Ireland (up to n = 123) and adjacent UK/European waters (up to n = 289) to provide insights into the genetic population structure and diversity of harbour seals in the areas studied. Within the island of Ireland, genetic analyses revealed the presence of three genetically distinct local populations, characterized by high genetic diversity, hereby defined as: East Ireland (EI), North-west & Northern Ireland (NWNI), and South-west Ireland (SWI). Using previously published and newly generated data, a subsequent wider scale analysis revealed that the EI and SWI local populations were genetically distinct from neighbouring UK/European areas, whereas seals from the NWNI area could not be distinguished from a previously identified Northern UK metapopulation. Migration rate estimates showed that NWNI receives migrants from North-west Scotland, with NWNI acting as a genetic source for both SWI and EI. The present study provides the most comprehensive genetic assessment of harbour seals in European waters to date, with findings indicating that conservation strategies for harbour seals in Irish waters should be amended to accommodate at least three genetically distinct local populations/MUs. The use of approaches considering both ecological and genetic parameters is recommended for future assessments and delineation of units of ecological relevance for conservation management purposes.Item Acidogenic fermentation of Ulva in a fed-batch reactor system: tubular versus foliose biomass(Elsevier Ltd., 2025-01-08) Lawrence, James; Oliva, Armando; Murphy, Jerry D.; Lens, Piet N. L.; Science Foundatin IrelandThe present study proposes a biorefinery of the macroalgae Ulva, focusing on evaluating two different morphologies of the species (foliose and tubular) during acidogenic fermentation in fed-batch reactors. Stage 1 of the study evaluates lyophilised foliose and tubular Ulva, whilst Stage 2 analyses the impact of ulvan extraction on volatile fatty acids yield and changes in carbohydrate availability. Acetic, propionic, and butyric acids were produced from each substrate, with peak concentrations of total VFAs recorded at 2179.5 mg HAc/L (foliose Ulva) and 2029.3 mg HAc/L (tubular Ulva) when ulvan was present. After ulvan extraction, the acidogenic fermentation of the foliose morphotype was negatively affected, reaching at most 315.3 mg HAc/L. In contrast, the extraction showed no influence on the tubular morphotype, peaking at 2165.0 mg HAc/L. Additional variations were noted in the availability of carbohydrates in each substrate during the acidogenic fermentation process. The ulvan-extracted tubular morphotype exhibited the highest peak in carbohydrate concentration (9.8 g glucose/L), whilst the ulvan-extracted foliose morphotype yielded up to 8.5 g glucose/L. This study highlights the biorefinery potential of Ulva biomass, proposing a multiple cascading approach linking multiple energy and biomolecule applications to maximise the valorisation of the biomass.Item A low-carbon electricity transition for small island developing states: The case of Mauritius(Elsevier Ltd., 2024-12-20) Jaggeshar, Doorgeshwaree; Mao, Xianqiang; Guo, Zhi; Zusman, Eric; Tu, Kevin; Chen, Xing; Ma, Zhiyuan; Global Energy Interconnection GroupA clean energy transition can not only help rebuild the energy landscape of small island developing states (SIDS) but also boost their resilience and long-term development prospects. This study employs the Open-Source Energy Modeling System (OSeMOSYS) model to analyze low-carbon transition pathways for Mauritius, which are aligned with its nationally determined contribution (NDC) objectives to increase renewable energy to 60 % and phase out coal by 2030. The study applied key performance indicators to assess this pathway against energy self-sufficiency, economic, environmental and social criteria. The study showed that renewable energy sources, namely, solar, biomass, wind and waste-to-energy, can be game-changers for the island. The optimal transition pathway would achieve a renewable target of 76.8 % and reduce CO2 emissions by more than 67 % across the modeling period at an estimated cost of 1.94 billion USD by 2040. Finally, the study evaluated the implications of Mauritius' clean transition in terms of its effects on green jobs as well as whether there is sufficient infrastructure, administrative and financial capacity and energy pricing policies to support the optimal pathway. The study concludes that the experience modeling a low-carbon transition pathway for Mauritius could also offer useful lessons for other SIDS contemplating similar transitions.Item A tri-level distribution locational marginal price-based demand response framework(Elsevier B.V., 2025-01-01) Pandey, Vipin Chandra; Rawat, Tanuj; Ospina, Juan; Dvorkin, Yury; Konstantinou, Charalambos; Keane, James; Science Foundation Ireland; Popov, Jelena; Stanton, CatherineIn this paper, we propose a tri-level, nested, two-stage price-based demand response (PBDR) framework that considers distribution locational marginal price (DLMP) as DR enabler between load-serving entities (LSE), demand response providers (DRPs), and customers in the day-ahead distribution market. It enables LSE and customer interactions by using multiple DRPs, positioned in-between, and independently optimizes their objectives. The problem is formulated using linear power flow with approximated power losses and its application in DLMP as DR pricing. The tri-level problem is solved using a nested reformulation & decomposition (R&D) method and tested on the real Indian-108 bus distribution system under various dynamic pricings. Further, the temporal–spatial variations in DLMPs are assessed using fairness criteria. Numerical analyses demonstrate that DLMP applications can effectively improve economic efficiency, and transparency in DR programs valuation with a favorable fairness margin. The results show that DLMP as DR pricing signal induces (0-2) % variation in DLMP for DR participation up to 10 %. Further, it gives over 90 % fairness over temporal–spatial variation for all the customers.Item A framework for high resolution coupled global electricity & hydrogen models based on integrated assessment model scenarios(Elsevier B.V., 2024-12-02) Mathews, Duncan; Brinkerink, Maarten; Deane, Paul; Irish Research Council; Science Foundation IrelandTechnology-rich Integrated Assessment Models (IAMs) offer the possibility to endogenously resolve hydrogen demand as a function of competition between technologies to meet energy service demands while considering wider interactions with climate and the economy. Such models are typically configured with relatively low spatial and temporal resolution thereby limiting their utility in studying future global hydrogen trade scenarios. This work presents a framework for the soft-linking of IAM scenarios to a higher spatial and temporal resolution global model. This framework provides an “engine” with which to generate future-looking coupled hydrogen & electricity models with the co-optimization of production capacity, storage, and transmission infrastructure that allow the user to vary key technoeconomic input parameters. The modelling framework is applied to an IAM scenario and validated against the parent IAM. The utility of the model when examining electricity & hydrogen commodity trade in future scenarios is then demonstrated.