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Abstract: Waste heat recovery technologies play an important role in enhancing energy efficiency and supporting sustainable energy production. This study investigates the utilization of waste heat from aluminium production through an Organic Rankine Cycle (ORC) system to generate electricity and heat simultaneously. Based on operational data from an aluminium plant, the system is firstly optimized from both the thermodynamic and economic perspectives. To maximize performance and to identify optimal configurations, a mathematical model is developed and solved using GAMS, capturing the complex interdependencies between the operational, economic and thermodynamic parameters. The environmental impact of the optimized scenarios is subsequently evaluated using a Life Cycle Assessment (LCA), considering a broad range of impact categories. The results indicate a maximum power output of 830.9 kW and a maximum net present value (NPV) of 51.71 M€, confirming the system’s technical and economic viability. The environmental assessment demonstrates the potential of ORC systems as sustainable energy solutions, with significant environmental unburdening under optimized operating conditions (up to -606.0 kg CO2 eq./h). A sensitivity analysis indicates that the greatest environmental benefits occur under the optimal thermodynamic scenario, achieved through the utilization of higher-energy flue gas streams (up to -515.0 kg CO2 eq./h), and under the optimal economic scenario by balancing the electricity and heat prices optimally for simultaneous heat and power production (up to -696.7 kg CO2 eq./h). These findings highlight the importance of the thermal input quality and availability in maximizing ORC performance. With the ability to prioritize electricity, heat, or both, the optimized ORC systems support flexible energy solutions tailored to specific applications and environmental conditions, offering a promising pathway for unburdening the environment through the efficient utilization of industrial waste heat.
Keywords: waste heat recovery, aluminium production, organic rankine cycle, environmental impact, life cycle assessment, sustainable energy solutions
Published in DKUM: 13.06.2025; Views: 0; Downloads: 5
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Abstract: Higher education (HE) is a significant factor in a country’s economic prosperity and plays a vital role in addressing sustainability issues and actively promoting sustainable development. While many EU member countries have well-developed education systems in terms of rankings and SDGs’ attainment, little is known about the progress of other European countries. The goal of this research is to estimate the efficiency of higher education in the attainment of Sustainable Development Goals (SDGs) in 40 European countries. The method used to estimate efficiency is Data Envelopment Analysis (DEA) with output-orientation and variable returns to scale approach. In the final model specification, two input variables and one output variable are used. Results indicate that the average technical efficiency of the 40 European countries is relatively high and equal to 0.94. Nine countries emerge as fully efficient in achieving SDG 4 with a coefficient equal to 1. The four largest higher education systems achieved an aboveaverage efficiency score of 0.97 or higher. Six countries are recognized as the worst performing. However, more analysis is necessary to examine the sources of inefficiency in the worst-performing countries. Due to specific data limitations indicated in this research, it remains a challenge to evaluate the precise impact of higher education and its contribution to SDGs.
Keywords: sustainable development goals (SDGs), higher education, data envelopment analysis, SDG4, European countries
Published in DKUM: 28.05.2025; Views: 0; Downloads: 2
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Abstract: The European Union (EU) has long emphasized sustainable development as a fundamental policy goal, particularly within its tourism industry, which accounts for approximately 10% of the EU’s GDP. This thesis explores the legal frameworks that promote sustainable tourism development in the EU, analyzing their effectiveness, challenges, and future directions. The study examines the interplay between sustainability principles and tourism regulation, focusing on EU treaties, directives, and strategies such as the European Green Deal, the Circular Economy Action Plan, the European Tourism Indicators System (ETIS) and others. The research assesses how legal mechanisms influence environmental protection, economic growth, and social inclusion within the tourism sector. It also investigates the implementation of EU green policies, analyzing their impact on tourism businesses and local communities. The study highlights best practices from member states, such as sustainable tourism initiatives in Slovenia, Spain, and Germany, illustrating the successful integration of environmental and economic objectives. Findings indicate that while the EU has made significant progress in promoting sustainable tourism, regulatory fragmentation, inconsistent enforcement across member states, and financial constraints hinder full implementation. Recommendations include enhancing regulatory harmonization, strengthening stakeholder collaboration, and leveraging digital tools to monitor sustainability performance thus contributing to the broader discourse on balancing economic growth with environmental responsibility.
Keywords: Sustainable Development, Tourism Industry in the EU, European Green Deal, Sustainable Tourism Governance, Policy Implementation
Published in DKUM: 20.05.2025; Views: 0; Downloads: 9
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Abstract: The main problem this research addresses is the EU energy policy, which focuses on a critical analysis of strategic energy management in all process phases. Particular emphasis is placed on strategic control, which is a key phase of the management process. Strategic control includes evaluating the effectiveness of implementing planned measures and making decisions about necessary adjustments or changes. The purpose of the study is to assess how well EU energy management strategies are aligned with policy objectives, in particular, to ensure energy security, sustainability and economic competitiveness, and at the same time to identify areas where improvements are needed to address current challenges. Energy management in the European Union is a crucial aspect of its energy policy, which focuses on ensuring energy security, sustainability and efficiency. Since the middle of the 20th century, organisations' increasing energy intensity has emphasized the need for a comprehensive and flexible approach. Energy management involves controlling the entire life cycle of energy - from extraction, conversion and distribution to consumption and waste disposal - in a complex environment shaped by various external factors. These challenges become even more pronounced in regions that experience frequent environmental, economic or geopolitical changes. Designing a universal model for global energy management is difficult because of the different conditions, regulations, and energy needs worldwide. Adaptable and adaptive strategies are essential to respond to supply and demand fluctuations, integrate renewable energy sources, manage geopolitical risks and achieve sustainability goals. Therefore, energy management must evolve to respond to a dynamic global environment. The EU prioritizes energy security but lacks a unified approach, which creates challenges in defining and measuring energy security. The absence of standardized criteria makes it difficult to strategically evaluate policies and make decisions, which could have long-term consequences for both energy and national security. Initially, energy security was focused on stable supply for economic growth, but global changes – such as rising demand, geopolitical tensions and environmental concerns – have made it more complex. The recent years have underscored significant vulnerabilities in global energy security and the sustainability of energy systems, particularly in Europe. The dual crises of the COVID-19 pandemic and the conflict in Ukraine have highlighted the urgency of addressing these challenges, pushing the European Union to accelerate its efforts toward more sustainable and secure energy practices. In response, the EU has diversified energy sources and strengthened energy security to reduce its dependence on politically unstable suppliers. Given the complexity of the geopolitical situation, disrupted supply chains and the EU's clear official commitment to decarbonisation by 2050, the above should be viewed from different angles. EU energy policy (short-term and long-term) is conditioned by the action of many factors, which differ in type, intensity of action and effect (positive or negative) - but the need to analyse existing and define new methodologies for evaluating the effectiveness of EU energy policy is evident. The doctoral dissertation examines the above and suggests improvements.
Keywords: Energy management, sustainable management, energy security, aggregate index, composite indicator
Published in DKUM: 10.04.2025; Views: 0; Downloads: 18
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Abstract: This study develops and evaluates advanced predictive models for the trajectory planning of autonomous vehicles (AVs) in roundabouts, with the aim of significantly contributing to sustainable urban mobility. Starting from the “MRoundabout” speed model, several Artificial Intelligence (AI) and Machine Learning (ML) techniques, including Linear Regression (LR), Random Forest (RF), Support Vector Regression (SVR), Gradient Boosting Regression (GBR), and Neural Networks (NNs), were applied to accurately emulate human driving behavior and optimize AV trajectories. The results indicate that neural networks achieved the best predictive performance, with R2 values of up to 0.88 for speed prediction, 0.98 for acceleration, and 0.94 for differential distance, significantly outperforming traditional models. GBR and SVR provided moderate improvements over LR but encountered difficulties predicting acceleration and distance variables. AI-driven tools, such as ChatGPT-4, facilitated data pre-processing, model tuning, and interpretation, reducing computational time and enhancing workflow efficiency. A key contribution of this research lies in demonstrating the potential of AI-based trajectory planning to enhance AV navigation, fostering smoother, safer, and more sustainable mobility. The proposed approaches contribute to reduced energy consumption, lower emissions, and decreased traffic congestion, effectively addressing challenges related to urban sustainability. Future research will incorporate real traffic interactions to further refine the adaptability and robustness of the model.
Keywords: sustainable mobility, autonomous vehicles, machine learning, roundabouts, artificial intelligence, ChatGPT
Published in DKUM: 04.04.2025; Views: 0; Downloads: 1
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