Civil and Environmental Engineering - Journal articles
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Item Modelling urban carbon emissions for multiple sectors in high spatial resolution for achieving sustainable & net-zero cities(Elsevier Ltd, 2025) Purcell, Lily; O'Regan, Anna C.; McGookin, Conor; Nyhan, Marguerite M.Many largescale initiatives and networks have been established to support city efforts and leadership in decarbonisation. An essential first step in these initiatives is developing a Baseline Emissions Inventory (BEI) to understand drivers of current emissions and provide a benchmark that progress can be measured against. There has been increasing interest in emission inventory methods. However, previous research has focused on single sectors, has neglected emissions other than CO2, or has not followed a spatial approach. The latter is particularly important to support policy planning and decision-making. This study investigates the development of a novel BEI for a medium-sized city in Ireland to address the methodological knowledge gap in existing literature for a detailed methodology using mainly open-source and spatially resolved data for developing a multi-sectoral BEI in high spatial resolution. Greenhouse Gas (GHG) emissions including CO2, CH4, and N2O, represented as kilotonnes CO2-equivalent (ktCO2-eq), were modelled for the Residential; Transport; Commercial & Industrial; Public; Agriculture, Land Use & Fishing (ALUF); and Waste sectors. Total annual emissions were 987 ktCO2-eq, with emissions per capita of 4.7 tCO2-eq. The Residential sector accounted for 34 % of emissions followed by the Transport (29 %), Commercial & Industrial (22 %), Public (7 %), ALUF (6 %), and Waste (2 %) sectors. The fine-resolution spatial outputs facilitate the investigation of socioeconomic factors alongside GHG emissions helping to elucidate local drivers and produce equitable mitigation strategies. The findings will contribute to effective policy development and the methodologies, developed in accordance with the Global Covenant of Mayors, can be replicated by cities globally.Item Automatic inspection and assessment of a cross-passage twin tunnel using UAV(Elsevier B.V., 2025) Zhang, Ran; Wang, Chao; Li, Zili; China Scholarship Council; Science Foundation IrelandThe inspection of large-scale tunnel networks is essential to identify any long-term deterioration mechanisms. Traditional manual inspection is not automatic and adaptive in geometrically complex tunnel configurations. This paper presents an automatic unmanned aerial vehicle (UAV)-based tunnel assessment application in a critical cross-passage twin tunnel section of Dublin Port Tunnel. It adopts a reactive method for UAV navigation and photogrammetry, and a point cloud for data processing. This study specifically verifies the patterns of cross-section deformation and defect distribution in twin tunnels and discovers that the deterioration pattern agrees with previous monitoring results. It shows that observed tunnel deformation could be attributed to the effect of twin tunnel interaction and vehicle cross passage, whilst the distribution of lining cracks could be associated with the differential structural stiffness and the differential longitudinal bending along the tunnel section. © 2025 The Author(s)Item End-of-life wind turbine blades and paths to a circular economy(Elsevier, 2025) Deeney, Peter; Leahy, Paul G.; Campbell, Kevin; Ducourtieux, Claire; Mullally, Gerard; Dunphy, Niall P.; Science Foundation Ireland; Irish Research Council; Sustainable Energy Authority of IrelandA structured literature review is used to identify barriers to the recommended methods of processing end-of-life wind turbine blades. The Waste Management Hierarchy recommends firstly avoidance, then repurposing, recycling, energy recovery and lastly, disposal. The review finds that most recent research articles are concerned with recycling, despite its position in third place in the Hierarchy. The review also identifies the following barriers to the first, second and third most recommended processes: misalignment of financial rewards for blade manufacturers making more durable blades; lack of information about blades which could help repurposing and recycling; and lack of financial incentives for any of the top three methods. Based on these findings the following solutions are proposed: alternative payment structures for blade ownership incentivising blade quality and longevity; an information exchange to facilitate the second hand market, repurposing and recycling; and the widespread use of compliance bonds to provide a financial incentive for repurposing and recycling.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 Prediction of load-bearing capacity of FRP-steel composite tubed concrete columns: Using explainable machine learning model with limited data(Elsevier Ltd., 2024-12-03) Liu, Xiaoyang; Sun, Guozheng; Ju, Ruiqing; Li, Jing; Li, Zili; Jiang, Yali; Zhao, Kai; Zhang, Ye; Jing, Yucai; Yang, Guotao; Natural Science Foundation of Shandong ProvinceThe complex interaction mechanism between the FRP jacket, steel tube, and confined concrete in the FRP-steel composite tubed concrete (F-STC) column makes the prediction of its mechanical behaviour a challenging task. This paper specifically investigates the application of machine learning models to predict the load-bearing capacity of F-STC columns. Since relatively few experimental works are performed on F-STC columns, the database established based on the test results from previous research contains only 69 data samples. In order to circumvent the training difficulties caused by the relatively small database, the application of the Gaussian process regression (GPR) model is trialled in this study. To make the predictions of the GPR model explainable, the Shapley additive explanations (SHAP) approach is incorporated with the GPR model in this study. Besides, four contrasting prediction models based on artificial neural network (ANN), support vector regression (SVR), decision tree (DT), and random forest (RF), are also proposed. The k-fold validation and test results indicate that the GPR model provides strong potential in predicting the load-bearing capacity of F-STC columns with high prediction accuracy and generalisation capability. Besides, 95 % and 99 % confidence intervals obtained by the GPR model are provided to show the uncertainty of the prediction results. Furthermore, the effect of the database size on the prediction performance of GPR, ANN, and SVR models is further examined by gradually reducing the number of data samples, and the comparisons illustrate the superiority of the GPR model.