Search Results (727)

Against the global transition toward sustainable energy systems and the rapid development of green electricity trading and green certificate systems, traditional regional average electricity emission factors are no longer sufficient to accurately reflect the carbon emission responsibilities associated with enterprises’ actual electricity consumption. This may lead to the double counting of renewable electricity attributes and the overestimation of emission reduction effects. To address this issue, this study focuses on electrical equipment products. Building upon the existing life-cycle accounting framework, a method for constructing provincial residual electricity emission factors coupled with green electricity and green certificate attribute verification mechanisms is proposed. By excluding non-fossil electricity volumes whose environmental attributes have already been claimed through market-based mechanisms, an accounting factor capable of characterizing the actual emission intensity of “residual electricity” is established, together with an accounting model for indirect electricity emissions during the production stage. Furthermore, eleven typical categories of electrical equipment, including transformers, electricity meters, conductors, and power cables, are selected to conduct an empirical cradle-to-gate carbon footprint analysis and evaluate their carbon reduction potential under a 50% green electricity substitution scenario. The results indicate that provincial residual electricity emission factors incorporating renewable electricity attributes can improve the accuracy and transparency of product carbon footprint accounting. This approach provides methodological support for sustainable manufacturing, green procurement, low-carbon supply chain management, and the development of product carbon footprint standards. Full article

This study examines how double materiality is structured and disclosed during the early implementation of the European Union’s Corporate Sustainability Reporting Directive (CSRD) and the corresponding European Sustainability Reporting Standards (ESRS). While prior research has primarily focused on the identification of material topics, less attention has been given to the way these elements are organized within corporate reporting systems. To address this gap, the concept of disclosure architecture is adopted as an analytical lens. The analysis is based on sustainability statements published for the 2024 reporting period by seven large European oil and gas companies. Employing qualitative content analysis, the study applies an ESRS-based analytical framework operationalized through a structured coding scheme. Given the transitional nature of the 2024 reporting cycle, this framework provides a common analytical basis for examining how companies structure and present double materiality disclosures despite differences in reporting approaches. The framework captures two related aspects of reporting: disclosure content, specifically impact and financial materiality, and disclosure structure, including formal double materiality framing and the use of transition-related tools. The findings indicate a clear asymmetry in double materiality disclosure. Impact-related disclosures are highly standardized across companies, reflecting a shared reporting baseline shaped by regulatory expectations and industry norms. In contrast, notable differences emerge in financial articulation, formal double materiality framing, and the positioning of transition-related tools. These patterns suggest that differences emerge less in the disclosed topics themselves and more in how disclosure elements are structured and connected within sustainability statements. Building on these observations, the study identifies recurring disclosure architecture configurations observed within the sample, described as Structured Integrators, Emerging Integrators, and Selective Adopters. These recurring disclosure patterns help illustrate the different ways companies present and connect regulatory requirements, financial considerations, and transition-related elements within disclosures. The study contributes to the literature by shifting the focus from disclosure content to disclosure structure. In doing so, it provides a framework for examining how double materiality is represented and structured within reporting systems and offers insights into the coexistence of convergence and variation in sustainability disclosures examined through an ESRS-based analytical lens during the early phase of CSRD implementation. Full article

To address the insufficient exploitation of the carbon reduction value of hydrogen energy in hydrogen-integrated virtual power plants under multi-market trading environments, as well as the low solution efficiency of existing Stackelberg game methods, this paper constructs a Stackelberg game optimization model for hydrogen-integrated virtual power plants under the coupling of carbon, green certificate, and CCER markets. First, multi-stage hydrogen utilization modes, including power-to-hydrogen, hydrogen-to-methane, and hydrogen-to-heat-and-power conversion, are introduced into each virtual power plant. Demand response is also considered to optimize demand-side energy consumption, thereby improving the hydrogen utilization chain from production and storage to conversion and utilization. Second, the carbon reduction value generated by hydrogen participation in CCER trading is incorporated into the market mechanism, and a carbon–green certificate–CCER multi-market coupling mechanism is established. Finally, a dynamically corrected Kriging metamodel is adopted to approximately replace the lower-level energy management model, so as to improve the solution efficiency of the Stackelberg game model. the case study results show that, after the introduction of CCER trading, the total system cost is reduced by 2.77%, and carbon emissions decrease from 5446 kg to 5344 kg, achieving coordinated improvement in system economy and low-carbon performance. Full article

The Circular Economy (CE) offers an alternative to the traditional “take–make–dispose” model and is increasingly important in hospitality due to the sector’s high resource consumption. This systematic review analyzes 159 studies published between 1995 and 2024, sourced from ABI, BSP, and WoS, and consolidates scattered knowledge on CE practices in hotels. It outlines five strategies for transitioning to CE: energy efficiency, renewable energy, water management, waste reduction, and carbon footprint reduction. These are supported by green procurement, local supply chains, eco-certifications, and regenerative branding, all of which help hotels fulfill stakeholder expectations and support local economies. Guest engagement—through nudges, incentives, co-creation, and digital tools for monitoring and feedback—is becoming increasingly important. The review shows that CE adoption is driven by internal factors such as leadership, staff training, culture, and resources, as well as external factors such as regulation, institutional pressure, and consumer demand for authenticity. Effective collaboration among managers, staff, suppliers, policymakers, and certifiers is essential for achieving systemic adoption. CE is moving from operational efficiency to broad innovation benefiting the environment, economy, and society, despite financial, regulatory, and behavioral challenges. Future research should prioritize establishing measurement standards, addressing scalability issues, and evaluating the global effectiveness of implementation. Full article

This study was developed within the framework of the GOLL (Green Olympic Living Lab and Environment Change) project, promoted by the Municipality of Coimbra, Portugal. The project uses the Mário Mexia Multisport Pavilion (MMMP) and the Olympic Swimming Pools Complex (OSPC) as living lab case studies for sustainability-oriented sports infrastructure management. The study combines a review of best practices in sustainable sports facilities with an applied case study focusing on infrastructure characterisation and the identification of intervention requirements (InRs). The review addresses the environmental, economic, and social dimensions of sustainable sports facilities, including energy and water efficiency, digital technologies, renewable energy integration, waste management, mobility, certification systems, and user inclusion. The adopted methodology integrates a literature review, technical inspections, and the analysis of building systems and resource consumption. The findings highlight the significant potential for improving operational performance, resource efficiency, and overall sustainability by adopting more integrated maintenance and management approaches. However, practical implementation remains dependent on overcoming challenges related to costs, data integration, and stakeholder engagement. The paper also discusses the potential adoption of integrated maintenance approaches, including the potential adoption of tailored digital management solutions and certification schemes, which may support more structured and proactive management. Within the GOLL living lab environment, this contributes to more informed technical, operational, and policy decision-making for the sustainable rehabilitation and management of sports facilities. Full article

This study proposes a novel hybrid mathematical framework that integrates the Time-Varying Parameter Vector Autoregression (TVP-VAR) connectedness approach with Long Short-Term Memory (LSTM) deep learning networks to analyze, forecast, and manage volatility spillovers in green financial markets. The framework is motivated by the increasing complexity of risk transmission across sustainable assets, including green bonds, renewable energy stocks, carbon markets, and conventional energy assets. The proposed methodology follows a two-stage structure. First, the TVP-VAR model is employed to quantify dynamic connectedness and time-varying spillover effects across markets. Second, the extracted connectedness measures are used as inputs to an LSTM network to forecast future systemic risk dynamics and generate forward-looking variance–covariance matrices for portfolio optimization and hedging purposes. Using daily data from 2015 to 2025, the empirical results reveal that renewable energy stocks are the dominant transmitters of volatility within the system, exerting substantial spillover effects on green bonds and other sustainable assets. The forecasting evaluation demonstrates that the proposed hybrid TVP-VAR-LSTM framework significantly outperforms traditional econometric models (ARIMA and GARCH) as well as conventional machine-learning benchmarks (SVR, Random Forest, and XGBoost), reducing the Root Mean Squared Error (RMSE) by more than 46% in out-of-sample forecasting. Moreover, the enhanced forecasting accuracy translates into economically meaningful benefits, leading to substantial reductions in realized portfolio risk and improved hedging effectiveness. The findings further highlight the importance of carbon pricing mechanisms and standardized green bond certification in mitigating volatility transmission across sustainable financial markets. Overall, this study contributes to the literature on financial mathematics, systemic risk modeling, and machine learning in green finance by providing a unified framework for volatility spillover analysis, forecasting, and dynamic portfolio optimization. Full article

As one of the top contributors to global environmental impact, the building and construction sector has significant potential to mitigate resource consumption both during and after construction. The Leadership in Energy and Environmental Design (LEED) certification has formalized this mitigation process, but it remains unclear whether the operational performance of LEED-certified buildings matches their theoretical design in reducing environmental impacts and advancing sustainable development in the built environment. This study contributes to the growing body of knowledge on real-world building performance by evaluating the operational energy use of LEED-certified buildings in Philadelphia relative to their immediate urban neighbors. The methodology includes identifying buildings from the Philadelphia Large Building Energy Benchmarking dataset, along with U.S. Green Building Council (USGBC) certification records, and analyzing LEED-certified buildings in comparison with their functionally similar non-LEED buildings in proximity. The research employs a multi-dimensional analytical framework grounded in the Energy and Atmosphere (EA) credit structure of LEED. In raw city-wide terms, certified buildings used far more energy per floor area than non-certified buildings (79.4 vs. 22.7 kWh/sq ft), but this gap largely reflects differences in building function, size, and location. After structural clustering and geographically constrained matching, certified buildings still showed a higher mean energy use intensity, by roughly 56 to 59 kWh/sq ft across all neighborhood sizes (k = 3, 5, 10). However, none of these differences was statistically significant at the 95% level. This apparent gap was not uniform: it was concentrated in large, service-intensive types such as healthcare and public/cultural facilities, rather than observed across all building categories. The results therefore provide no evidence that certified buildings outperform comparable non-certified peers in operational energy use, rather than positive evidence that they underperform. By utilizing large-scale benchmarking data and comparative analytical methods, this work enhances understanding of the effectiveness of LEED-related energy interventions and supports evidence-based decision-making for policymakers, designers, contractors, and building owners seeking to improve energy performance in existing buildings. Full article

As green building concepts continue to expand into public cultural spaces, green concert halls not only serve functions of cultural communication and artistic services, but also play an important role in shaping urban residents’ psychological experiences and well-being. However, existing studies on green buildings have mainly focused on energy performance and technical indicators, while limited attention has been paid to how green cultural buildings are associated with residents’ well-being through environmental perception. In the Chinese context, research specifically examining green concert halls remains scarce. Based on environmental psychology and restorative environment theory, this study takes the Chengdu City Concert Hall, which has received China’s Three-Star Green Building certification, as the research object. A conceptual model of “green concert hall design perception–perceived nature connectedness–perceived restorativeness–residents’ well-being” was constructed to explore the underlying mechanisms linking green concert hall design perception and residents’ well-being. Green concert hall design perception was conceptualized as a second-order construct consisting of four dimensions: green design legibility, eco-environmental comfort, green aesthetic integration, and green cultural symbolism. Perceived nature connectedness and perceived restorativeness were introduced as mediating variables. A survey was conducted among 879 Chengdu residents with concert-hall attendance experience, and structural equation modeling (SEM) was employed for empirical analysis. The results indicate that (1) green concert hall design perception is significantly and positively associated with residents’ well-being; and (2) perceived nature connectedness and perceived restorativeness both play significant mediating roles in the relationship between green concert hall design perception and residents’ well-being, while also forming a significant sequential mediating effect. The findings suggest that green concert halls are associated with more positive environmental experiences through ecological and aesthetic characteristics, and that residents’ well-being may be further linked to strengthened nature connectedness and restorative perceptions. This study extends research on green public cultural buildings from the perspective of residents’ psychological perception, and provides theoretical support and practical implications for human-centered green concert hall design and the development of urban green cultural spaces. Full article

Industrial process systems must reduce energy use and carbon emissions while maintaining productivity under binding constraints. Energy-use rights trading (EURT), also referred to as energy-consuming rights trading, energy quota trading, or energy-consumption permit trading, converts administrative energy-consumption control into tradable entitlements. This narrative and integrative review uses a transparent search-and-screening audit and reframes EURT primarily through the Chinese pilot experience, while using international energy-efficiency certificate and obligation schemes as comparative context. The review examines how quota scarcity, quota prices, monitoring, reporting and verification, trading liquidity and policy coordination may influence process-level energy management, production scheduling, heat integration, waste-heat recovery, equipment renewal, fuel substitution, electrification, digital monitoring and low-carbon retrofit decisions. It compares EURT with carbon-emissions trading, pollution-permit trading, white-certificate or energy-efficiency-obligation schemes, water-rights trading and renewable-energy certificates. Evidence suggests that EURT can support pollution reduction, carbon mitigation, and green productivity improvement when quota scarcity is binding, markets are liquid, monitoring is reliable, and policy coordination is credible, but findings remain heterogeneous and vulnerable to contamination from overlapping policies. A stylized process-system illustration shows how quota prices can alter the ranking of retrofit investments. Future research should integrate transaction records, equipment-level energy data, process simulation and multi-policy identification strategies. Full article

Hybrid additive manufacturing (HAM) integrates additive and subtractive processes within a unified production system, combining the geometric flexibility and material efficiency of additive manufacturing with the dimensional accuracy and surface quality of conventional machining. This review provides a comprehensive analysis of HAM technologies through a proposed four-criterion classification framework encompassing process integration strategy, additive manufacturing process type, machine architecture, and application domain. DED-based, PBF-based, and polymer-based hybrid systems are examined alongside integrated hybrid machines, retrofit solutions, and robotic architectures. A comparative analysis of representative commercial platforms evaluates build envelope, integration strategy, and monitoring capability. Documented performance outcomes across aerospace, automotive, energy, and biomedical sectors confirm substantial improvements in surface quality, fatigue performance, dimensional accuracy, and material efficiency relative to conventional manufacturing routes. Current limitations are critically assessed across technical, process integration, and economic dimensions, and a structured near-to-long-term research roadmap is proposed, prioritising in-process sensing and toolpath standardisation, digital twin-based adaptive process planning, and ultimately autonomous hybrid manufacturing cells with lifecycle certification. These findings position HAM as a central enabling technology for intelligent, flexible, and sustainable production within Industry 4.0 and Industry 5.0 paradigms. Full article

In contrast to the development of conventional civil aircraft propulsion systems, novel propulsion technology or non-standard energy sources disclose a lack of flexibility in the current aviation certification framework. Additionally, aircraft certification in 2025 relies heavily on manual effort, causing major difficulties in maintaining the traceability of data across vast sets of regulation documents. One promising solution to overcome such challenges is offered by the field of artificial intelligence (AI), particularly large language models (LLMs). This paper introduces an AI-aided framework designed to streamline the certifiability of novel aircraft propulsion systems. To meet the AI trustworthiness demands set by the European Union Aviation Safety Agency (EASA), the framework proposes a concept for achieving data and model transparency in machine learning (ML) applications. To address the demand for data transparency, aviation regulatory context data will be unified and stored in a Unified Regulations Database (URD). This unified data is classified and enriched with related information for ML purposes. The URD enables the creation of modern, transparent AI features for civil aircraft certification. This AI-aided framework will enable certification measures for the development and allows for certifiability checks for novel aircraft technologies. Both the aviation industry and regulatory authorities may equally benefit from the existence of the URD as a starting point for certifying AI features. Full article

Towards achieving carbon neutrality, it is important to produce carbon-free hydrogen from renewables at an acceptable cost. At the same time, power retailers that own renewables must manage their imbalances between planned and actual generation. This paper proposes an economically viable carbon-free hydrogen method for such retailers, utilizing both positive imbalances of renewables and electricity from the market with non-fossil certificates. The proposed method enables geographically flexible hydrogen production through the power grid while utilizing renewable imbalances within actual power business operations. This paper develops solutions to an optimization problem that minimizes the hydrogen variable cost and offsets the imbalances using an electrolyzer and a battery while accounting for imbalance uncertainty. The case study in Tokyo, Japan demonstrates that imbalance compensation reduces the hydrogen variable cost by 30%. The minimum levelized cost of hydrogen (LCOH) is approximately 60 JPY/Nm³ when the electrolyzer operates at a 40% capacity factor. Furthermore, sensitivity analysis of market prices indicates that the LCOH can decline to 50 JPY/Nm³ under lower price conditions. The results suggest that market-independent cost components, such as wheeling and renewable energy charges and non-fossil certificates, remain major obstacles to further reducing hydrogen costs. Full article

The increasing adoption of renewable energy sources introduces significant variability in power generation, requiring effective strategies to ensure maintain grid stability. Incentive-based demand response programs provide a practical solution for balancing supply and demand, however disputes may arise over energy data integrity. The existing solutions frequently rely on centralized authorities, exposing a single point of failure, or high costs and privacy limitation of recording granular data on-chain. To address this challenge, we propose a decentralized framework that separates cloud storage from integrity certification. This system employs a community aggregator to collect high-frequency energy measurements, store the raw data in the cloud, while anchors unique cryptographic hashes for batch of raw data to a public blockchain. This process creates an auditable and tamper-evident record of data. By recording only hashes on chain, our approach achieves privacy and scalability. Evaluation using a real-world Australian dataset confirms that the system enables transparent dispute resolution, with blockchain transaction costs consistently representing less than 0.10% of the total incentives awarded to participants. Full article

Field-programmable gate array (FPGA)-based reconfigurable system-on-chip (SoC) platforms are increasingly deployed in safety-critical domains such as autonomous driving and industrial automation, yet the existing literature lacks a systematic assessment of how these designs address functional safety requirements. This paper presents a systematic review of 36 peer-reviewed studies (core period 2010–2024, with historical context from 1998) on FPGA-based reconfigurable parallel processing SoCs, analyzed through three frameworks: a convergence–divergence analysis (CDA) that provides a structured exploratory lens for identifying research trajectory trends and informing hypothesis generation; a safety-critical gap analysis benchmarked against a three-layer standard framework comprising ISO 26262 (functional safety), ISO 21448/SOTIF (safety of the intended functionality), and ISO/PAS 8800 (AI safety properties); and a four-dimensional design space taxonomy spanning reconfigurability granularity, parallelism exploitation, design automation level, and safety criticality. The analysis reveals that 33 of the 36 surveyed studies (92%) ignore safety certification entirely. While recent work has begun establishing worst-case execution time (WCET) bounds for FPGA SoC platforms, none of the surveyed FPGA-based AI accelerator studies provide WCET bounds, although recent analytical models for multi-DPU architectures demonstrate the feasibility of such analysis. FPGA CNN accelerators achieve energy efficiencies of up to 60 GOPS/W, and dynamic partial reconfiguration (DPR) yields 2–5× throughput improvements, yet these gains remain unsupported by the formal verification or uncertainty quantification mandated for safety certification. The CDA framework reveals strong convergence between DPR, network-on-chip (NoC), and high-level synthesis research threads (scores 0.72–0.91), indicating maturation toward integrated design flows. We identify conformal prediction as a distribution-free hardware-compatible framework for uncertainty quantification on resource-constrained FPGAs, motivated by requirements from ISO 21448 (triggering event identification) and ISO/PAS 8800 (runtime confidence monitoring), and propose a prioritized research agenda to bridge the gap between FPGA performance optimization and safety-certified deployment in transportation systems. Full article

Improving residential energy efficiency is essential to meeting UK net-zero targets, yet retrofit uptake in the private rented sector (PRS) remains limited. While many studies examine retrofit measures or Energy Performance Certificates (EPCs), few integrate comparative technology performance, cost–benefit outcomes, and landlord–tenant perspectives within a single housing context. This paper addresses that gap through a mixed-methods case study of a professionally managed private rented housing portfolio in South London, assessing four retrofit technologies: photovoltaic (PV) panels, air source heat pumps (ASHPs), double glazing (DG), and insulation. Quantitative analysis showed that ASHPs delivered the greatest EPC improvement, with 54.5% of properties achieving a two-band uplift, while PV panels offered the strongest financial return, with an average payback period of 11.7 years. Houses achieved the strongest overall results, with combined PV + ASHP retrofits delivering the best technical and financial performance; however, this pairing was only feasible in houses because of the physical requirements for both roof space and external unit installation, whereas flats and maisonettes were more constrained by space and installation feasibility. Stakeholder analysis findings revealed knowledge and incentive gaps: many tenants overestimated the effectiveness of double glazing, while landlords identified high upfront costs and delivery challenges as key barriers. Wider PRS decarbonisation will therefore require stronger policy support, streamlined retrofit delivery, and improved tenant awareness. Full article