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Converting surplus electricity into hydrogen is considered a promising way for accommodating large-scale wind or solar power. However, it is expensive to establish a new-built hydrogen network or storage facilities at the current stage. Hydrogen-enriched compressed natural gas (HCNG), a mixture of natural gas and hydrogen, can be an alternative approach to consuming surplus renewable energy in the short-medium term. This paper investigates the feasibility of establishing an electricity-gas-hydrogen coupled energy system by modeling the HCNG network, power grid, and hydrogen electrolyzer in Ireland with consideration of pipeline characteristics. The economic analysis based on the planning results of the coupled system is presented in detail. When the hydrogen injection ratio reaches 20% at the HCNG stations, the system operating cost and carbon emission can be reduced by 24.2% and 6.4%, and 100% wind can be consumed. • A detailed modeling method for HCNG pipeline pressure drop and line pack is proposed. • An EGH-IES planning model encompassing entire HCNG supply chain is established. • A case study is conducted based on the real energy system in Ireland. [ABSTRACT FROM AUTHOR]

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Intertrochanteric hip fractures are significant and costly injuries and there remains controversy within the orthopaedic literature over the best method of fixation. The Irish Hip Fracture Database (IHFD) was established in 2012 to drive improvements in clinical outcomes and the quality of hip fracture care. This paper will review the outcomes of dynamic hip screw (DHS) versus intra-medullary nailing (IMN) in the treatment of intertrochanteric hip fractures in Ireland. Eligible cases for this study include patients >60 years of age with trochanteric hip fractures treated by DHS or IMN between January 2016 and December 2020. Outcomes recorded and compared include length of stay, inpatient mortality, mobilisation on post-operative day 1 (POD 1), and discharge destination. 5668 hip fractures treated with DHS or IMN were identified. There was no significant difference between inpatient mortality, re-operation rate or length of stay between the two groups. Females and patients with a high ASA grade (IV and V) were more likely to receive IMN. Patients receiving DHS were more likely to be mobilised day 1 post-operatively and be discharged directly home. It was noted that the use of IMN increased from 42% of cases in 2016 to 70% in 2020. IMN use for intertrochanteric fractures continues to increase. However, patients treated with DHS were more likely to mobilise early post-operatively and to go directly home. Notwithstanding the limitations of national registry data research, the dramatic rise in the use of IMN for these fractures appears unsupported by the evidence. • Controversy remains over the best method of fixation for trochanteric fractures. • Intramedullary nail fixation is increasingly popular. • Nails are not superior to DHS in this study. [ABSTRACT FROM AUTHOR]

[Display omitted] • This paper demonstrates the Kartini Reactor's educational utility. • A case study was conducted by investigating reactor criticality. • The study achieved reactor criticality by inserting 5 fuel elements, totaling 2524.57 g. • The critical mass determination was refined by plotting the inverse of counts against the total mass of U-235. • This approach utilized both polynomial and linear trend lines to analyze the data. Research reactors serve critical roles across multiple domains—from physics to medicine—while distinctly not being used for electrical power generation. The Kartini Research Reactor located in Indonesia exemplifies the integration of research reactors in education and scientific research, particularly highlighting its educational applications through the Internet Reactor Laboratory (IRL). Established in 1978 and operational since 1979, the Training Research and Isotope Production by General Atomic (TRIGA) Mark II reactor is instrumental in advancing nuclear science with facilities like the Lazy Suzan/Rotate Rack and Beam Port. The IRL significantly enhances its educational process, enabling remote access to reactor physics experiments, thus facilitating global university participation in nuclear engineering education. This capability allows for the real-time visualization of reactor operations and detailed presentation of operational data and experiment results, enriching the learning experience. This paper demonstrates the Kartini Reactor's educational utility through a case study investigating reactor criticality and determining the critical fuel mass under safe operational parameters. Employing telecommunication hardware and software, the study achieved reactor criticality by inserting 5 fuel elements, totaling 2524.57 g. The critical mass determination was further refined by plotting the inverse of counts against the total mass of U-235. This approach utilized both polynomial and linear trend lines to analyze the data. While the polynomial analysis provided upper and lower thresholds for critical mass, the linear regression offered a precise critical mass value of 2428.62 g, showcasing a deviation of only 4% from the experimental findings. [ABSTRACT FROM AUTHOR]

In the effort to achieve carbon neutrality through a decentralized electricity market, accurate short-term load forecasting at low aggregation levels has become increasingly crucial for various market participants' strategies. Accurate probabilistic forecasts at low aggregation levels can improve peer-to-peer energy sharing, demand response, and the operation of reliable distribution networks. However, these applications require not only probabilistic demand forecasts, which involve quantification of the forecast uncertainty, but also determining which consumers to include in the aggregation to meet electricity supply at the forecast lead time. While research papers have been proposed on the supply side, no similar research has been conducted on the demand side. This paper presents a method for creating a portfolio that optimally aggregates demand for a given energy demand, minimizing forecast inaccuracy of overall low-level aggregation. Using probabilistic load forecasts produced by either ARMA-GARCH models or kernel density estimation (KDE), we propose three approaches to creating a portfolio of residential households' demand: Forecast Validated, Seasonal Residual, and Seasonal Similarity. An evaluation of probabilistic load forecasts demonstrates that all three approaches enhance the accuracy of forecasts produced by random portfolios, with the Seasonal Residual approach for Korea and Ireland outperforming the others in terms of accuracy and computational efficiency. • We proposed new low-voltage aggregation techniques based on portfolio theory to improve probabilistic demand forecasting. • The increased volatility at the low voltage level requires probabilistic forecasting to measure uncertainties. • The proposed methods were found to outperform random aggregation with the real-world data from Korea and Ireland. • A simple forecasting approach minimizing the standard deviation of deseasonalized demands was accurate and efficient. • The new method can contribute to achieving carbon neutrality, enable P2P energy sharing, and benefit prosumers. [ABSTRACT FROM AUTHOR]

Once considered a scientific, technocratic activity, marine governance has shifted from a top down, state directed process toward participatory and deliberative approaches. In parallel, there has been increasing acknowledgment of the need to consider the human dimensions of marine and coastal issues, and the role of citizens in delivering the sustainable management and protection of the marine environment. By doing so, a more complete understanding of the complex relationship between society and the sea may be achieved. Research has shown that marine practitioners recognise that higher levels of civic involvement and citizenship in the management of the marine environment would be beneficial. Despite this, questions are raised as to whether existing governing institutions, legal structures, and planning instruments enable this to readily happen in practice. This paper explores the extent to which existing marine governance instruments are positioned to engender a society of marine citizens to meaningfully engage with marine stewardship behaviours in the UK and Ireland. A multi-phased research approach critically analyses existing relevant legislation, legal and policy frameworks, focusing on themes associated with the human dimensions of marine governance, including marine stewardship. This evaluation highlights a limited inclusion of terms relating to marine stewardship nationally, but recognises the foundations are there a more strategic and cognisant recognition of human-ocean relationships within marine governance across a range of scales and contexts. • Marine governance has shifted from a top-down to a more participatory process. • Practitioners recognise a need for higher civic involvement and citizenship. • Research critically analyses existing instruments for human dimensions. • Recommendations call for explicit inclusion of people in marine governance. [ABSTRACT FROM AUTHOR]

The national child welfare agency in Ireland identified the integration of trauma-informed practices as a service need, in the current significantly challenging practice climate. A promising program that meets the need of child welfare professionals to support need has been developed and is reported on in this paper. This study aimed to evaluate the effects of a newly developed post-graduate level trauma-informed care program for professionals in the national child welfare agency in Ireland. Study participants were 41 child welfare professionals that included front-line practitioners, supervisors, and senior managers. A pretest–posttest study design was used, data was collected over three-time points to measure the effects of the program on pre-defined outcomes of Trauma-informed Knowledge, Professional Self-efficacy, Professional Quality of Life, and Intention to Leave. Statistically significant positives effects were found in trauma-informed knowledge, professional confidence, burn-out and compassion fatigue/secondary traumatic stress, with effect sizes ranging from medium-large to large ( η 2 =. 133 t o η 2 =. 721) across the intervention time period. The positive impacts arising from the program were sustained for 3 months post-intervention. The results of this initial evaluation are promising in supporting child welfare professionals' capacity to integrate trauma-informed practices and addressing the need for trauma informed practitioners. The need for further research is highlighted. [ABSTRACT FROM AUTHOR]

Assessing the internal dynamics of organizations has been shown to provide information that can help planners and policymakers improve service delivery. A good organizational climate, which in this study incorporates mission clarity, team cohesion, staff autonomy, communication, levels of stress, and openness to change has been shown to be of particular importance. Still, there is a dearth of evidence in this area, and while relationships between organizational factors have been identified, little is known about the mechanisms that might underpin these relationships, and there is little understanding of how to address deficits once they are identified. The objective of this study was to identify relationships between program factors that influence organizational climate and to explore which mechanisms might underpin these relationships. This paper reports on a cross-sectional, concurrent, mixed-methods study design, across twelve discrete community-based prescribing service providers (organizations) in Ireland. Data was obtained using a staff survey [ n = 132] which utilized measurements of organizational readiness to change and one-to-one interviews [ n = 12]. Quantitative data was analyzed using multivariate linear regression modeling which assessed relationships between variables, while interviews were analyzed using an abductive approach, both types of data were synthesized at the interpretation stage. A range of interdependent factors were considered to affect the climate of organizations. Surveys identified that specific types of resources, such as physical infrastructure, training, and staffing resources were important for supporting a good organizational climate, while programs with greater needs had a poorer climate. Opportunities for professional growth, the skill sets of staff, and having access to e-communication were also significant. Interviewees reported that rigid organizational hierarchies and bureaucracy, philosophical views of addiction, stress, and staff turnover were influenced by the provision of fewer resources. Interdependent factors such as leadership, supervision, staff relationships, and collective training, also thought to be influenced by resources, were considered to positively influence programs. Resources were not the only challenge identified, and practices within programs and how existing resources are used were also thought to contribute both positively and negatively to the internal dynamics of services. Key findings in this study identified that the organization of effective services is influenced by a range of specific factors, some of which can be addressed without additional resources. Overall, staff views of organizations can provide us with valuable information to support service improvement. Using a mixed methods approach can not only identify where relationships between organizational variables exist but can also help us to understand the mechanisms that underpin these relationships and, importantly, how to address deficits once they are identified. In order to improve how substance misuse services work, the need for a long-term systemic approach to program development, which incorporates some of the findings from this study, is required. • Resources: ie. staffing, training, and office resources will likely influence a treatment program's organizational climate. • Programs with higher identified needs were less likely to have a favorable organizational climate. • Having greater growth opportunities was positively associated with; mission clarity, autonomy, and communication. • There is a likely interdependence between organizational domains with no indication of a hierarchy of importance. • How resources are used, not just their availability, was thought to influence to the organizational climate. [ABSTRACT FROM AUTHOR]

• We used disparate data in a decision tree to refine the mapping of Irish peat soils. • Peat Associated Landcover Class concept was applied to locate converted peatlands. • Shallow peat soils ≥ 10 cm were included in the new Irish Peat Soils Map (IPSM). • The IPSM shows a larger peat area than previous peat maps and accuracies ≥ 74 %. • The Adaptative Mapping Framework implemented can be applied in other regions. Accurate mapping for effective management of peat soils is necessary to help reduce GHG emissions and improve environmental quality. However, mapping remains a major challenge as definitions of peat soils vary substantially between jurisdictions and organizations, while field data are sparse and difficult to produce, and remote sensing of limited use for converted peatlands. Using an Adaptive Mapping Framework, this paper compiles disparate data sources to update the Derived Irish Peat Map to better facilitate its application for environmental issues. This includes incorporation of areas considered to be underlain by shallow peat soils (≥ 10 cm and ≥ 8.6 % Organic Matter content), and augmentation of the overall test dataset with an additional ∼ 20,000 points. The workflow for map generation employed 20 Decision Tree Output Maps (DTOMs), aggregated into 33 Map Combinations (MCs). These facilitated the addition of new areas and removal of areas where the presence of peat could not be confidently identified. The MC selected for the update had the highest accuracy metrics (≥ 74 %), consisting of DTOMs with a user accuracy ≥ 66 % and assessed over a minimum number of test points ≥ 50. The resulting map reveals peat to underlie 1.66 M ha of Ireland (∼ 23.3 % of the country), identified with values of 83 % for overall accuracy and F1 score for peat areas. This extent is 13.2 % larger than that delineated in previous versions and at least 23.2 % larger than areas presented in other previous maps. The methodology also allows transparency from which data sources can be distinguished to define different key peat thickness ranges (≥ 10 cm, ≥ 30–40 cm), better facilitating assessment of environmental impacts arising from land use change. This approach has potential relevance for peat mapping globally, notably in areas containing disparate datasets (e.g., land cover, soil map, etc.), or employing different production methods. The accuracy metrics generated also suggest that the approach can be used as a basis for implementing or updating national and international regulations concerning carbon-rich soils in comparable settings to those encountered in Ireland. [ABSTRACT FROM AUTHOR]

This work addresses the problem of automatic tunnel surface defect inspection using unmanned aerial vehicles (UAVs). The research aims at proposing a robust and efficient monitoring method for image data acquisition and processing in complex and dark tunnel environments. A method, called Proximity Move-Pause-Photo for Surface Defect Inspection (PMPP-SDI), is proposed by combining reactive flying control strategies with a grid scanning pattern to capture high-quality image data from multiple views and angles. The image data is then used to generate a 3D point cloud model of the tunnel surface for structural condition assessment. The method is tested in a field experiment in a railway tunnel in Ireland, and the results show that it can achieve stable navigation, high-resolution reconstruction, and accurate defect detection. The paper discusses the advantages and limitations of the method, and suggests improving the control/navigation intelligence, data quality, and defect analysis as the future research directions. • Reactive strategy for adaptative UAV navigation in tunnels. • UAV 3D close-range surface data acquisition. • Method validation and tunnel defect analysis. [ABSTRACT FROM AUTHOR]

• Model which simulates dairy farm electricity use in 15-min intervals. • Validated on 3 dairy farms of varying size. • Suitable for studying renewable energy integration and demand side management. • Reliable tool for decision support for dairy operations. The objective of this paper was to define, validate and demonstrate a model capable of accurately simulating dairy farm electricity consumption across varying herd and parlour sizes, to facilitate research investigating renewable energy systems (RES) and demand side management (DSM). The Farm Electricity System Simulator (FESS) was developed using grey-box modelling techniques utilizing empirical data for parameter tuning. Empirical data were gathered from nine spring calving, pasture based dairy farms located in the Republic of Ireland. A k-means clustering analysis was conducted, separating the farms into three, near homogenous groups, from which representative farms were selected. FESS was trained using 12 months of data from three representative farms using the repeat hold out method for data partitioning with 75 % of data used for training and 25 % used for validation. An optimisation algorithm was used to minimize the error during model training. Through cross-validation, FESS achieved a root mean squared error (RMSE) of 7.65 kWh, mean absolute percentage error (MAPE) of 7.10 %, mean percentage error (MPE) of −0.86 % and a relative prediction error (RPE) of 7.56 % for total daily electricity consumption. Across the three farms, the simulated outputs of FESS achieved an average R2 value of 0.72, demonstrating good agreement with observed data. FESS's utility was demonstrated by analysing the effects of different electricity pricing structures and on-site solar photovoltaic electricity generation on total farm energy costs. We concluded that FESS simulated on-farm electricity consumption with sufficient accuracy for the intended application. FESS accurately simulated dairy farm electricity consumption across three dairy farms of different herd and parlour sizes while evaluating the effects of demand side management and renewable generation on farm electricity consumption and costs. [ABSTRACT FROM AUTHOR]

Heavy-Duty Vehicles (HDVs) pose a significant challenge in meeting emissions reduction targets. However, studies on estimating emissions from Irish HDV fleet are rare. This paper estimates fuel consumption and CO 2 emissions from tractor-trailers that occupy nearly half of Ireland's HDV fleet using the European Commission recommended VECTO tool. To improve the estimation accuracy, driving cycles specific to Irish road conditions were developed utilising real naturalistic driving data from trucks. The Irish driving cycles significantly differ from the VECTO inbuilt driving cycles in percentage time spent in different gears, fuel consumption, and CO 2 emissions. CO 2 emissions estimated with Irish driving cycles range from 733 to 1961 g/km, while with VECTO driving cycles, the values ranged from 728 to 1865 g/km. Further, the study evaluated the sensitivity towards payload, road gradient, and idling percentages. The study insights would provide an essential evidence base for policymakers in Ireland. [Display omitted] • Developed Irish urban, regional, and freeway driving cycles. • Employed the VECTO tool to assess CO 2 emissions from Irish heavy-duty vehicle fleet. • Focused on tractor-trailers with a major share in the Irish fleet. • Evaluated the effect of idling, gradient, and payload on CO 2 emissions. • Fuel consumption is underestimated by up to 7.1% when the road gradient is ignored. [ABSTRACT FROM AUTHOR]

This paper investigates drivers or hindrances to households' adoption of behavioural changes concerning energy efficiency at home. A Choice Experiment survey has been conducted to elicit households' preferences regarding adoption of innovative heating/cooling systems in Ireland and Italy. The choice data is analysed through a Latent Class model, and posterior analysis is used for class profiling, aimed to detect the emergence of factors identified in the literature. In both country samples respondents could be grouped in three classes according to their preferences and willingness to pay for adoption of innovative heat pump systems. Early adopters, younger and with higher education, exhibit strong pro-innovation attitudes. Conversely, Laggards, typically older and less educated, display hesitancy, and may require substantial subsidies for adoption. Late adopters value trialability and rely less on social networks. Information processing varies according to individual capabilities and social contexts. Hence, we recommend targeted information to enhance awareness of benefits and on feasibility of installation in different types of dwelling. Technical information and support, possibly complemented by demonstration activities, is suggested to foster innovation, especially among less advantaged households. • Assessment of drivers and barriers to adoption of energy efficient heating systems. • A survey with Choice Experiments in Ireland and Italy. • Willingness to pay for innovative systems is assessed through a Latent Class model. • Three classes identified with specific preferences and willingness to pay. • Profiling confirms the importance of attitudinal factors and trialability. [ABSTRACT FROM AUTHOR]

The IPCC emphasises the need to centre climate change adaptation in climate actions due to a lack of progress on meaningful climate change mitigation. This requires the expansion of adaptive capacity across many sectors, including education. Research asserts the key role formal education plays in increasing the learning and cognitive aspects of adaptive capacity and associated capabilities, but further work is required to understand the impacts of attempts to enact such changes, specifically in relation to climate change adaptation planning. Drawing on impact data collected from an experimental place-based digital educational resource – Climate Smart – that includes a serious online role play game, designed with and for second level students aged 15–17 in Ireland, this paper outlines the challenges of, and opportunities for, engaging young people in learning about climate change adaptation planning. We conclude that while such educational innovations are impactful in the short-term and essential for developing foundational knowledge and skills, as well as shaping individual and social norms, they will be insufficient alone to optimise capabilities for long term adaptive capacity for climate change adaptation. Wider complementary structural changes across multiple systems which support people to enact their learning and functionalise their capabilities are required. Finally, a prospective agenda for progressing adaptive capacity for climate adaptation planning with education at its core is outlined. [ABSTRACT FROM AUTHOR]

Once released into the environment, herbicides can move through soil or surface water to streams and groundwater. Filters containing adsorbent media placed in fields may be an effective solution to herbicide loss in the environment. However, to date, no study has investigated the use of adsorbent materials in intervention systems at field-scale, nor has any study investigated their optimal configuration. Therefore, the aim of this paper was to examine the efficacy of low-cost, coconut-based activated carbon (CAC) intervention systems, placed in streams and tributaries, for herbicide removal. Two configurations of interventions were investigated in two agricultural catchments and one urban area in Ireland: (1) filter bags and (2) filter bags fitted into polyethylene pipes. Herbicide sampling was conducted using Chemcatcher® passive sampling devices in order to identify trends in herbicide exceedances at the sites, and to quantifiably assess, compare, and contrast the efficiency of the two intervention configurations. While the Chemcatcher® passive sampling devices are capable of analysing eighteen different acid herbicides, only six different acid herbicides (2,4-D, clopyralid, fluroxypyr, MCPA, mecoprop and triclopyr) were ever detected within the three catchment areas, which were also the only acid herbicides used therein. The CAC was capable of complete herbicide removal, when the water flow was slow (0.5–1 m3 s−1), and the interventions spanned the width and depth of the waterway. Overall, the reduction in herbicide concentrations was better for the filter pipes than for the filter bags, with a 48% reduction in detections and a 37% reduction in exceedances across all the sampling sites for the filter pipe interventions compared to a 13% reduction in the number of detections and a 24% reduction in exceedances across all sampling sites for the filter bag interventions (p < 0.05). This study demonstrates, for the first time, that CAC may be an effective in situ remediation strategy to manage herbicide exceedances close to the source, thereby reducing the impact on environmental and public health. [Display omitted] • First reported field-scale assessment of in situ herbicide remediation technology. • Ideal environmental conditions include low flow rates to maximise contact time. • Systems showed capability for herbicide removal to below maximum allowable level. • Optimum configuration for herbicide removal identified as a filter pipe system. • Filter pipe system 35% more effective than the filter bags. [ABSTRACT FROM AUTHOR]

• A high spatial resolution model for estimating N 2 O emissions at the farm level. • Findings indicate a 5% reduction in farm-level N 2 O emission estimates. • There is an increase in the variation of N 2 O emissions of 20% at the local level. • Statistical significance of environmental factors in N 2 O emissions estimation. • Substituting 20% of CAN with protected urea reduces 15% of N 2 O emissions. This paper aims to define a high spatial resolution model for estimating nitrous oxide (N 2 O) emissions from agricultural soils in Ireland. In 2020, N 2 O emissions from the management of agricultural soils represented 10% of the total national agricultural Greenhouse Gas (GHG) emissions. The high spatial resolution model employed here takes account of environmental factors that influence N 2 O emissions at a more disaggregated spatial scale than the Intergovernmental Panel on Climate Change (IPCC) national inventory-reporting framework. Activity data from the EU Farm Accountancy Data Network (for Ireland) is used in conjunction with biophysical and climatic data in a geographic information system (GIS) framework to estimate N 2 O emissions at a sub-national level. Results indicate that N 2 O emissions are 5% lower by applying this high spatial resolution modelling approach at the farm level compared to the baseline model (Tier 2). Nevertheless, 25% of the farms in the sample analysed had an overestimation in their N 2 O emissions of 20%, and another 25% of the farm sample had an average underestimation in their N 2 O emissions by 19%, a consequence of the variation of environmental factors among farms. Using a data panel regression, results confirm that the environmental factors examined are statistically significant within the model proposed, and with a simulation, we assessed the switching of 20% of CAN fertiliser for protected urea. According to the high spatial model, this mitigation measure can reduce N 2 O emissions from inorganic fertilisers by up to 15%. However, the reduction is conditioned by local factors and environmental conditions. [ABSTRACT FROM AUTHOR]