Search Results (285)

Water-intensive industries in the Mediterranean face supply stress and decarbonisation pressure simultaneously. We develop an operations-research decision-support framework that treats the firm as one node of a small industrial resource cluster and prices the cost and carbon-equivalent emissions of five alternative supply trains—municipal water, river water, groundwater, rainwater harvesting and brewery wastewater reuse—within a multi-objective Linear Program. Each train carries engineering-grounded expenditures, energy intensities and grid emissions, and a weighted-sum scalarisation is solved daily for 365 days under three managerial scenarios. On a Cretan microbrewery whose 2022 demand of 5250 m³ is met from the municipal network, the balanced and cost-focused scenarios coincide on a single optimum that cuts the Levelised Cost of Water by 25.3% and emissions by 40.7%, while the eco-friendly scenario yields a 19.3% cost and 51.7% emissions reduction. LP duality, shadow prices and an extended sensitivity programme (diversification, capacity, grid factor, discount rate, RO recovery and demand profile) turn the optimisation into a decision-support package: optimal daily allocations, shadow-price signals on capacity and demand, and robustness diagnostics for capital planning, dispatch and risk management. Results are site-specific, but the framework and its diagnostics transfer in structure to clusters sharing the same convex-polytope source geometry; transposition to energy cooperatives is future work. Full article

Environmental pollution is becoming an urgent global issue. Countries are implementing various solutions and establishing legal frameworks and institutional policies to promote the use of green energy sources and thereby minimize the adverse environmental impact of economic growth, investment, and consumption. The goal of economies worldwide, including in Asia, is to implement policies that promote sustainable development while optimizing economic performance. The purpose of this study is to evaluate the impact of green energy consumption and institutional quality on environmental quality. Using data from 29 selected Asian countries over the period 1970–2021, the empirical results indicate that green energy consumption does not have a statistically significant impact on environmental quality across the full sample. Improvements in institutional quality can enhance environmental quality and accelerate progress toward carbon neutrality and net-zero emissions targets. The Climate Change Conferences (COPs) have helped raise global awareness of the dangers of climate change, fostering greater international cooperation to protect the planet and promote sustainable development. To capture the influence of international climate commitments, this study employs a dummy variable for the COP period (coded 0 before COP2 in 1996 and 1 thereafter). This variable is interacted with green energy consumption and institutional quality to examine whether the implementation of COP commitments moderates their effects on CO₂ emissions. The empirical results show that greater political stability, particularly during the implementation of carbon emission reduction commitments, contributes to reducing greenhouse gas emissions and promoting sustainable development. The study also confirms that institutional quality plays a significant role in improving environmental quality and accelerating countries’ progress toward carbon neutrality and net-zero emission goals. Full article

Allocating scarce budgetary resources across the strategic objectives of the balanced scorecard (BSC) and the sustainability balanced scorecard (SBSC) is a central problem in sustainability-oriented strategic management. Existing approaches typically operate at the level of aggregated perspectives, rely on subjective weighting schemes, or ignore the causal structure of the strategy map. This article formalizes the problem as a cooperative game in which each strategic objective is a player and the value of every coalition combines the individual performance of its members with the synergies arising from the causal relationships of the strategy map, estimated through the decision-making trial and evaluation laboratory (DEMATEL). The Shapley value is adopted as the allocation rule. The resulting game is shown to be superadditive and convex, the Shapley value belongs to the Core, and the rule satisfies exhaustiveness, fairness, sensitivity to the strategy map, monotonicity, and convergence to the proportional rule. Computational experiments and sensitivity analyses support the robustness of the model. In an illustrative case—a sustainability balanced scorecard with ten objectives organized in five perspectives, whose dedicated sustainability perspective hosts a carbon-emission and an employee-safety objective, and a budget of USD 1M—the framework shifts $2.7\%$ of the total budget relative to a proportional allocation (individual objectives change by up to $12.3\%$), funds employee safety above financial cost reduction for any synergy weight $\gamma \ge 0.15$, keeps the combined share of the sustainability objectives stable within $0.6$ percentage points across the entire synergy range, and grants seed funding to sustainability objectives that enter the map without a measured baseline, providing a transparent and auditable basis for sustainable budget allocation. Full article

To trace carbon footprint information, applying blockchain technology has irreplaceable advantages for improving the green trust level of consumers, but it requires a large investment cost. Cooperative coalitions can be formed among manufacturers to reduce the burden of blockchain investment cost. In this paper, the operational strategies of three manufacturers in terms of emission reduction competition are explored under different coalition structures concerning the green trust level of consumers, and the Largest Consistent Set concept is used to analyze the stable structure of the farsighted coalition of manufacturers. The results show that when the green trust is at a particularly high or low level, the structure of a single manufacturer applying blockchain is farsightedly stable; when the green trust level is low, a coalition involving two manufacturers applying blockchain is a farsightedly stable coalition structure; and when the green trust level is high, the structure of all manufacturers applying blockchain is farsightedly stable. Compared with cooperative coalitions, a single manufacturer applying blockchain is more likely to become a farsighted stable structure, and this possibility will increase with the improvement of the green trust level. As the green trust level rises, consumer surplus and social welfare are not always the highest when all manufacturers jointly apply blockchain, and achieving optimal consumer surplus or social welfare does not mean that the coalition is farsighted and stable. Full article

This paper investigates carbon reduction and pricing decisions in a green supply chain composed of a government, a manufacturer, and a retailer, under the joint influence of carbon tax policies and consumer environmental awareness. A game-theoretic framework is developed to systematically compare four cooperation structures: non-cooperation, emission reduction cooperation, pricing cooperation, and full cooperation. The results show that consumer environmental awareness significantly influences firms’ green investment, pricing strategies, and the government’s carbon tax policy. The analysis further reveals several nonlinear effects under different cooperation modes. In particular, when environmental performance is evaluated in terms of emission intensity, emission-reduction investment improves per-unit environmental performance, although demand expansion under strong consumer environmental awareness may weaken the extent of this improvement. In less environmentally sensitive markets, green investment translates more directly into environmental improvement. Pricing cooperation provides strong incentives for firms to reduce emissions, whereas full cooperation achieves a better balance between environmental and economic performance. This study enriches the theoretical foundation of green supply chain coordination and offers practical insights into carbon tax design and sustainable collaboration strategies. Full article

The “Green ICT @ FMD” competence center brings together the expertise in resource-efficient information and communications technology from 11 Fraunhofer and two Leibniz institutes, which have joined forces to form the Research Fab Microelectronics Germany (FMD). The competence center offers industry a broad portfolio of services focused on the future development of ICT applications, infrastructures, and microelectronic components with a view on resource-efficient production, energy efficiency, and the reduction in greenhouse gas emissions. Various cooperation opportunities have been initiated to support a wide range of companies in responding to customer needs and regulatory requirements through innovative and resource-efficient ideas and developments. We now present the initial results from the success models of the “Green ICT Space” startup and SME program, as well as selected “Validation Projects” with companies that all pursue the common goal of more resource-efficient production and use of ICT. Full article

Background: Green logistics requires decision-support approaches that jointly address cost efficiency, emissions reduction, service reliability, and reporting transparency under dynamic operating conditions. Existing studies often treat optimization, predictive updating, stakeholder coordination, and emissions traceability separately, limiting integration. Methods: This study develops a simulation-based integrated decision-support framework that combines multi-objective mixed-integer linear programming (MILP), machine learning-based travel-time prediction in a rolling-horizon setting, cooperative allocation using a Shapley value mechanism, and ISO 14083:2023-aligned emissions accounting. A permissioned blockchain layer is included as a post-decision governance mechanism to support traceability. The framework is evaluated using industry-calibrated synthetic scenarios over a 30-day planning horizon with 50 independent simulation runs. Results: Under the tested scenarios, the integrated configuration reduced average CO₂ emissions per route by 27.6% (±2.4%), improved the cost index by 17.3% relative to the baseline, and increased on-time delivery to 96.8%. Robustness analyses showed average key performance indicator (KPI) deviations below 5%. Component-level analysis suggests that the main operational gains arise from the interaction between predictive updating and prescriptive optimization, while the blockchain layer mainly improves auditability. Conclusions: The framework improves environmental and operational performance under the tested simulation scenarios, although real-world validation remains necessary before deployment-level conclusions can be drawn. Full article

Developing countries participating in the Warsaw Framework for Reducing Emissions from Deforestation and Forest Degradation Plus (REDD+) (WFR) are eligible to receive financial incentives linked to verified reductions in greenhouse gas emissions from forest-related activities. It is necessary to strategically select priority countries among the WFR participants to achieve REDD+ cooperation and mutual benefits between recipient and donor countries. This study evaluates the mitigation potential of 71 developing countries registered under the WFR (December 2025) using two dimensions: national measurement, reporting, and verification (MRV) capacity and the need-effectiveness of official development assistance (ODA) in strengthening MRV capacity. Countries were ranked and classified into six typological groups based on MRV capacity and ODA need-effectiveness. The results show that countries with an intermediate MRV implementation capacity and high ODA need-effectiveness can transition to the MRV implementation phase through policy and financial interventions, suggesting high potential to achieve emission reductions and become priority countries for cooperation. Meanwhile, those with an intermediate MRV implementation capacity but low ODA need-effectiveness were interpreted as types where medium- to long-term cooperation possibilities can be reviewed based on improvements to MRV components. Our findings suggest a two-stage cooperation strategy that integrates short-term MRV-based engagement with long-term ODA-driven capacity-building to expand REDD+ mitigation outcomes under the WFR. Full article

Improving environmental sustainability while maintaining economic viability is a major challenge for Mediterranean cereal production, where conventional systems are associated with high input use, elevated greenhouse gas emissions, and strong cost pressures. Although Conservation Agriculture (CA) and Precision Agriculture (PA) are widely promoted as promising solutions, evidence on their combined environmental and economic performance under real farming conditions remains limited. This study evaluated CA, PA, and their combined application (CPA) in winter cereal systems in Greece, using three years of farmer-managed field data from four representative sites. Agronomic and environmental performance and economic outcomes were assessed under actual farm sizes and a scaled 300 ha scenario. Across sites and years, no systematic yield differences were observed among CA, PA, and CPA, indicating that alternative systems can maintain yield stability under real farmer-managed conditions. Environmental performance was driven primarily by tillage intensity: CA reduced CO₂eq emissions by 212–238 kg ha⁻¹ relative to conventional tillage, while CPA achieved the largest reductions (262–332 kg ha⁻¹), accompanied by surface-layer SOM increases of 0.30–0.56% over three years. PA applied within conventional tillage resulted in only modest emission reductions (41–82 kg ha⁻¹), but consistently improved NUE, with variable-rate fertilization increasing NUE by approximately 5–7% relative to uniform application. Despite these environmental benefits, economic performance remained constrained due to high fixed machinery costs, high input prices, and low grain values resulting in negative net profits across all systems. CA reduced total costs by 3.8–11.8%, PA delivered only marginal improvements, while CPA achieved the largest cost reductions (5.0–12.6%) delivering also the most stable net profit mitigation. Carbon credit revenues increased profitability by only 2–3%. Scaling to 300 ha improved competitiveness through fixed-cost dilution, but profitability remained unattainable. Overall, integrated CA–PA systems offer substantial environmental benefits but require targeted policy support, cooperative machinery use, and service-based solutions to enable economically viable adoption in Mediterranean cereal systems. Full article

Hydrocarbon-dependent economies face a critical challenge: sustaining economic growth while reducing carbon emissions. This study examines whether structural energy transition has begun to weaken the growth–emissions relationship in four Gulf Cooperation Council (GCC) economies: Saudi Arabia, United Arab Emirates, Qatar, and Bahrain, over the period 2008–2023. The analysis integrates three complementary approaches: Tapio elasticity-based decoupling analysis, a composite Energy Transition Performance Index (ETPI), and fixed-effects panel regression. This multi-method framework distinguishes between short-term cyclical decoupling and longer-term structural transition dynamics. The results show that strong decoupling is concentrated during crisis periods (2009 and 2020), indicating that emissions reductions are often cyclical rather than structural. More consistent, though moderate, weak decoupling emerges after 2015, coinciding with gradual improvements in renewable energy adoption and carbon efficiency. However, persistent fossil fuel dependence and rising electricity demand continue to constrain bigger structural change. The ETPI reveals significant cross-country variation, with the UAE demonstrating relatively stronger transition performance. Panel regression results indicate that renewable energy expansion is associated with lower carbon intensity, but its impact remains constrained by fossil-based energy systems and demand-side pressures. Overall, the findings suggest that energy transition in GCC economies is progressing but remains partial and uneven, requiring deeper structural reforms to achieve sustained decoupling. Full article

Against the background of carbon neutrality, the government’s carbon regulations have had a profound impact on the distributed energy sharing behavior of industrial parks. To deeply explore the interactive relationship between distributed energy sharing in industrial parks and government regulation, this paper constructs a three-party evolutionary game model composed of the government, core enterprises and supporting enterprises; endogenizes government behavior; and integrates inter-enterprise contractual mechanisms into the evolutionary framework. By establishing a revenue payment matrix and a replication dynamic equation, the stability conditions and system evolution paths of the strategy choices of each subject are analyzed, and numerical simulations are conducted. The results show that there are multiple evolutionary stable equilibria in the system, among which the equilibrium where core enterprises actively share, supporting enterprises actively share, and the government actively regulates carbon is the ideal state. Cost-sharing contracts and cooperative penalty contracts play a significant role in promoting the participation of supporting enterprises in sharing and curbing “free-riding” behavior, respectively. The changes in government subsidy rates and carbon tax rates have a crucial impact on the evolution of corporate strategies. Quantitatively, the carbon tax rate exhibits a threshold effect; enterprises shift to positive energy sharing when the tax rate exceeds 0.8, while a subsidy rate above 0.4 leads the government to withdraw from regulation. This indicates that a reasonable design of carbon regulations can help achieve coordinated energy emission reduction between the government and enterprises. The findings provide theoretical support for optimizing carbon regulations and designing cooperation strategies. Full article

Driven by the global mandates of the United Nations Sustainable Development Goals (particularly SDG 13 and SDG 17) and the climate targets established at COP summits, China strives to achieve its carbon peaking target by 2030 but faces significant challenges due to substantial regional disparities in abatement capacities. This paper proposes a cost-based inter-provincial cooperation mechanism to optimize carbon emission reduction (CER) task allocation. Using a marginal abatement cost curve model, we simulate provincial CER tasks from 2020 to 2030 under various cooperation scenarios. The results indicate that: (1) Cooperation significantly reduces the national total abatement cost compared to independent implementation. Specifically, the cost-saving ratio can reach approximately 60–70% when the cooperation proportion is high (80%). (2) There is a trade-off between economic efficiency and regional peaking targets. While an 80% cooperation proportion is economically optimal for 2020–2028, and a 60% proportion for 2029–2030, a 40% cooperation proportion is ultimately recommended as the balanced optimal ratio to ensure that most provinces achieve their carbon peaks before 2030. (3) The mechanism effectively narrows the disparity in abatement costs across regions. By offering a scalable paradigm for inter-regional climate collaboration, this study provides a theoretical basis for designing differentiated cooperation strategies to fulfill COP commitments and advance the global SDGs. Full article

Wing–diesel hybrid ships are a practical approach to sustainable maritime transport that harnesses wind energy to supplement diesel propulsion and reduce carbon emissions. The core optimization problem addressed in this study is the global energy efficiency optimization of path planning and propulsion system cooperative control for wing–diesel hybrid ships under two typical sail operation statuses (sail-deployed and sail-stowed) with dynamic changes in complex maritime meteorological and hydrological conditions. To address this issue, this paper proposes a global energy efficiency optimization framework based on an improved Deep Q-Network (DQN) and D*Lite algorithm. Firstly, the D*Lite algorithm is reconstructed with an incremental replanning mechanism and risk-aware cost function to generate real-time safe path constraints. Secondly, the DQN is improved by adopting a dueling network, noisy exploration and prioritized experience replay, and a differentiated reward function dynamically weighted by sail statuses is designed for it. Finally, a fuel consumption prediction model based on the gradient boosting algorithm is integrated into the reward function to realize an accurate energy efficiency assessment. Empirical results confirm that the framework achieves remarkable carbon reduction effects: the optimized routes reduce the total fuel consumption by 5.02%, cut carbon dioxide emissions by 140.66 tons, and improve the energy efficiency operational index by 7.50%. This framework provides an effective technical solution for the dynamic energy efficiency optimization of wing–diesel hybrid ships under different sail operation statuses. Full article

Coordinating multiple electric–hydrogen regional energy systems (EHRESs) under renewable uncertainty while ensuring rational benefit allocation remains a significant challenge. To address this issue, this paper proposes a cooperative energy mutual-assistance strategy for multiple EHRESs. An electric–hydrogen coupled operational framework integrating power-to-hydrogen technology is established, and a tiered carbon trading mechanism is incorporated to curb carbon emissions. Renewable-generation uncertainty is modeled using chance constraints. To solve the coordinated operation problem in a distributed manner, the cooperative model is decomposed into two tractable subproblems and solved using ADMM. In addition, an asymmetric Nash bargaining-based payoff allocation method incorporating aggregated contribution rates is developed to reflect heterogeneous participant contributions. Case studies are conducted to evaluate convergence, economic performance, emission reduction, and payoff allocation. The results show that the proposed method supports contribution-aware energy trading and benefit sharing among EHRESs while reducing carbon emissions by 8.54% and operating costs by up to 17.17%. Full article

The exponential growth in demand for data storage and computing has led to a rapid expansion in the energy consumption and carbon emissions of data centers (DCs). Hybrid energy systems that integrate renewable energy sources are regarded as a sustainable and low-carbon solution for powering the DCs. This study proposes an optimal cooperation scheduling strategy for the hybrid energy system powering the DC and electric vehicles (EVs). The strategy is based on load transferring and operates within a carbon trading mechanism, explicitly addressing the coupling between computational loads and power consumption. An optimization model is constructed that considers economic objectives, including operational cost and a stepped carbon trading cost, to obtain optimal energy dispatch and computational task allocation strategies. This framework ensures the economic interests of EVs’ owners while satisfying the energy demands of both the DC and the EVs. The results of a case study based in Shanghai demonstrate that the proposed hybrid energy system with multiple sources has significant economic and environmental advantages in spite of operational complexity. Furthermore, the collaborative strategy further enhances the cost reduction and carbon emission reduction. Specifically, the cooperative strategy achieves a 5.21% reduction in total cost compared to Case 1 (without V2G) and a 22.80% reduction compared to Case 2 (without computing task transferring). By adopting the optimal scheduling solution, carbon emissions can be reduced by 16.74% relative to Case 1 while remaining at a level comparable to Case 2. Furthermore, the impact of the carbon trading mechanism on the system’s cost and carbon emissions is analyzed. The results indicate that while a stricter carbon trading mechanism leads to an increase in the total cost, it also results in a reduction in carbon emission from the DC’s hybrid energy system. Full article