Energy, Sustainability and Society最新文献

Background

Achieving climate neutrality in cities is a major challenge, especially in light of rapid urbanization and the urgent need to combat climate change. This paper explores the role of advanced computational methods in the transition of cities to climate neutrality, with a focus on energy supply and transportation systems. Central to this are recent advances in artificial intelligence, particularly machine learning, which offer enhanced capabilities for analyzing and processing large, heterogeneous urban data. By integrating these computational tools, cities can develop and optimize complex models that enable real-time, data-driven decisions. Such strategies offer the potential to significantly reduce greenhouse gas emissions, improve energy efficiency in key infrastructures and strengthen the sustainability and resilience of cities. In addition, these approaches support predictive modeling and dynamic management of urban systems, enabling cities to address the multi-faceted challenges of climate change in a scalable and proactive way.

Main text

The methods, which go beyond traditional data processing, use state-of-the-art technologies such as deep learning and ensemble models to tackle the complexity of environmental parameters and resource management in urban systems. For example, recurrent neural networks have been trained to predict gas consumption in Ljubljana, enabling efficient allocation of energy resources up to 60 h in advance. Similarly, traffic flow predictions were made based on historical and weather-related data, providing insights for improved urban mobility. In the context of logistics and public transportation, computational optimization techniques have demonstrated their potential to reduce congestion, emissions and operating costs, underlining their central role in creating more sustainable and efficient urban environments.

Conclusions

The integration of cutting-edge technologies, advanced data analytics and real-time decision-making processes represents a transformative pathway to developing sustainable, climate-resilient urban environments. These advanced computational methods enable cities to optimize resource management, improve energy efficiency and significantly reduce greenhouse gas emissions, thus actively contributing to global climate and environmental protection.

Background

Citizen participation is integral to the governance of sustainability transformations. Long-term participatory processes undergo various phases of opening up and closing down various scopes of the participation—with significant consequences for the legitimacy and impact of the participation process.

Methods

To gain a better understanding of these processes, we address the question of how and why participation processes are opened up or narrowed down. Through document analysis and key-informant interviews, we evaluate a case of long-term citizen participation linked to the development of a sustainable neighborhood energy system in northwestern Germany.

Results

Results show that normative, substantive, and instrumental imperatives contribute to opening-up dynamics in participation processes. Closing-down dynamics were observed in the narrowing of thematic, spatial, temporal, and methodological scopes, as well as in the range of the actors involved. Reasons for closing down were financial and temporal restrictions, conflicting interests, the need for expert input in decision making about highly technological questions, the institutionalisation of participation, and stakeholder fatigue.

Conclusions

This study provides a new framework for analysing citizen participation while highlighting the complexities and interrelations associated with citizen participation within the context of technological and urban development.

Background

The greenhouse gas (GHG) mitigation quota is a unique instrument in Europe that redistributes money from high emission to low emission fuel markets while forcing fuel distributors to reduce the average emissions of their fuels. This paper presents the design of the German 2022 GHG quota, places it in the context of environmental policy instruments, and examines its impact on the affected fuel markets in relation to other environmental policy instruments. We aim to provide insights that can be applied in industry and policymaking, and to provide a basis for further research, to highlight GHG quota trading as an alternative to allowance trading and carbon taxes. Field research was conducted in the form of expert interviews. Furthermore, intermediaries and brokers were contacted via email and asked for transaction data. In addition, a qualitative literature review was conducted and publications of responsible authorities as well as relevant legal texts were used to gather information.

Results

We find that the GHG quota trading overlaps with the structures behind emission standards and emission trading schemes and, therefore, falls under the category of tradable performance standards. However, it also contains aspects of a subsidy and interacts directly or indirectly with several different markets.

Conclusions

While the GHG quota trading system shows potential as an environmental policy tool, its effectiveness is hindered by market complexities and external disruptions. Addressing these challenges through targeted research and policy adjustments could enhance its impact and alignment with broader climate goals.

Background

Research on portfolio optimization for energy generation often does so from a financial perspective. This study addressed a unique challenge: determining which companies, amidst a globalized electricity market, should be retained for climate risk preservation during specialization. Utilizing weather and generation data from 106 power plants across Argentina, we adapted integer-portfolio-optimization tools. Originally designed for financial index funds, these tools helped us construct a portfolio of power plants for a resilient energy mix.

Results

Our findings revealed optimal companies for retention by analyzing different portfolio configurations, where the number of plants was adjusted iteratively. In each iteration of the model, we selected a set of representative plants that minimize climate risk, which sometimes resulted in a plant being included in one portfolio but not another. This approach identified the specific companies and technologies essential for a diversified and climate-resilient energy portfolio while ensuring a strategic transition toward specialization and stabilizing generation risk in the face of variable weather conditions.

Conclusions

This paper presents a groundbreaking solution for specialization in a globalized energy market. Through portfolio optimization, we identified pivotal companies for each stage of the transition in Argentina. Firms like Parque Eólico La Genoveva and Complejo Hidroeléctrico Centrales Cacheuta Alvarez Condarco, showcased the balance needed for wind and hydroelectric sources. These insights should be used to guide policymakers to ensure a controlled and effective transition while maintaining stable generation risk.

Background

Sustainability aspects have become a main criterion for design next to performance of material and product. Particularly the emerging field of energy storage and conversion is striving towards more sustainable solutions. However, implementing sustainability considerations during the design and development phase of energy materials and products is challenging due to the complexity and broadness of the different dimensions of sustainability.

Results

Here, we demonstrate that by using the principles of Safe-and-Sustainable-by-Design (SSbD), a concept can be formulated. This concept served as the basis for selecting and evaluating criteria and performance parameters aimed at enhancing the safety and sustainability aspects of redox active molecules in an organic redox flow battery. Following an iterative approach, the collected data provided valuable insights enabling us to fine-tune and enhance the materials and processes in alignment with the identified parameters. (Social) life cycle assessment focused on the workflow from sourcing, processing and generation of intermediate products to the quinone used in the redox flow batteries and revealed important insights, highlighting critical steps in the process chain. Additionally, we identified two specific points of intervention regarding solvent and quinone choice, based on sustainability parameters. The proposed solvent change resulted in a greener alternative [changed from tetrahydrofuran (THF) to 2-methyl-tetrahydrofuran (MTHF)], and the ecotoxicity testing revealed MGQ and MHQS to be improved options. However, we also faced severe challenges regarding access to reliable LCA data on the raw material sourcing.

Conclusion

Taken together, the modified designs led to safer and more sustainable redox active materials for both humans and the environment at lab scale. Implementing the results mentioned above to further expedite the technology will ultimately pave the way to more sustainable energy storage applications. This study proved the value of implementing of an SSbD concept in battery development is the main result of this study.

Background

Problems such as climate change, environmental pollution, nuclear disposal and unsustainable production and consumption share a common feature: they pose long-term challenges because of their complex nature, potentially severe consequences, and the demanding problem-solving paths. These challenges may have long-lasting impacts on both present and future generations and, therefore, require to be addressed through a long-term governance perspective, i.e., coherent and consistent policy-making across sectors, institutions, and temporal scales. Dealing with these challenges is a core task of policy-making in modern societies, which requires problem-solving skills and capabilities. In this context, we identify long-term governance traces in the literature, illustrate the case of energy transition towards renewable energy systems as a long-term governance case, and elaborate on the scope and definition of long-term governance and its research.

Main text

We elaborate an analytical framework for long-term governance (LTG), based on five building blocks: the ‘environment’, which details the policy-making arena; the ‘policy issues’, which elaborates on the problems to be dealt with by LTG; the ‘key challenges and driving force’, revealing LTG mechanisms; the ‘key strategies’, in which promising approaches for LTG are identified; and the ‘policy cycle’, where governance impacts on different policy phases are discussed. In essence, we understand long-term governance at its core as a reflexive policy-making process to address significant enduring and persistent problems within a strategy-based decision-making arena to best prepare for, navigate through, and experiment with a changing environment.

Conclusions

The framework does not describe specific processes or individual cases in detail. Instead, it should be understood as an illustration of long-term governance characteristics at a more general level. Such a framework may help to structure the field of long-term policy-making, guide future research on conceptual, comparative, and empirical in-depth studies, and may provide orientation and action knowledge for making our governance system sustainable. Stimulating and broadening research on long-term issues seems indispensable, given the existence of several ‘grand challenges’ that require successful long-term governance.

Background

Although Germany’s biogas capacity accounts for almost 7% of its installed worldwide capacity, the expansion of biogas plants has stagnated owing to the expiry of Germany’s Renewable Energy Sources Act Erneuerbare–Energien–Gesetz (EEG) subsidies for existing biogas plants. Indeed, without alternative concepts such as power-to-gas (P2G) ensuring their continuing operation, many existing biogas plants must close down to ensure their continuous operation. A detailed spatial register of biogas plant sites must be developed to evaluate the potential for further operation (and thereby promote Germany’s sustainable energy transition). In particular, Lower Saxony, a German federal state, was hit hardest by the expiry of subsidies, as there is a lack of spatially high-resolution information to identify which biogas plants have P2G potential as an end-of-subsidy strategy. This study discusses the development of a geographic information system-based register for these plants.

Methods

A register was developed using geographic information system (GIS). Spatial data on existing biogas plants in Lower Saxony were selected from the Digital Landscape Model (DLM) data, with additional information coming inter alia from the Marktstammdatenregister, the Germany-wide core energy market data register. The data were merged into a single register for Lower Saxony, and aerial photographs were used to validate the biogas plant site.

Results

A total of 1704 biogas plant sites were identified throughout Lower Saxony. Spatially resolved plant information on production capacity suggests that three quarters are suitable for inclusion in a methanization concept. Because plants at 85% of the sites will no longer be subsidised by 2035, end-of-subsidy strategies will soon become relevant.

Conclusions

The GIS-based analysis is a reliable and low-error method for identifying biogas plant sites in Lower Saxony. Almost all plants were included in the registry. The greatest advantages over existing registers and at the same time the unique characteristics of our register were the exact spatial localisation of the plants and the highly up-to-date nature of the data. The register enables the initial (spatial) identification, characterisation, and analysis of potential sites for P2G end-of-subsidy strategies. Overall, the register has significant potential as an advisory basis.