Search Results (218)

The livestock sector in Serbia has been experiencing a prolonged period of structural and economic challenges, characterized by decreasing animal numbers, low productivity, and reduced competitiveness in both domestic and EU markets. This study analyses the key structural, technological, economic, and policy factors shaping these trends to provide strategic recommendations for sustainable sector revitalization. The methodology integrates macroeconomic analysis, agricultural economic accounts, and international trade data, applying regression modelling to examine relationships between domestic food prices, exchange rates, and agri-food import volumes. The results indicate that livestock’s share of agricultural gross value added remains below 35%, significantly lower than EU averages, while export quotas remain underutilized and the trade balance for animal products is persistently negative. Contributing factors include fragmented farm structures, outdated production technologies, limited adoption of innovations, demographic decline in rural areas, and insufficient alignment with EU CAP Strategic Plans and Green Deal objectives. Climate change impacts, such as droughts and heat stress, alongside animal disease outbreaks and macroeconomic pressures, further exacerbate these vulnerabilities. The study recommends modernizing production systems through investment in technological upgrades, strengthening farmer organizations and cooperatives, enhancing biosecurity and animal welfare standards, and improving policy frameworks to align with EU sustainability objectives. Emphasis is placed on developing integrated approaches that simultaneously address productivity, economic resilience, and environmental sustainability. Implementing these strategic measures is essential for enhancing food security, supporting rural development, and ensuring Serbia’s successful integration into the EU market as part of a more sustainable and resilient agri-food system. Full article

China, facing severe saline–alkali land degradation, is grappling with the paradox of technically adequate but systemically deficient land consolidation. In response to the existing evaluation system’s over-reliance on physicochemical indicators and neglect of socioeconomic value, this study proposes the use of the Optimal Land Use Value (OLV) to construct a comprehensive benefit evaluation indicator system for saline–alkali land consolidation that encompasses ecosystem resilience, supply–demand balancing, and common prosperity. Considering a case project implemented from 2019 to 2022 in the Western Songnen Plain of China—one of the world’s most severely affected soda saline–alkali regions—this study combines the land use transition matrix with a comprehensive evaluation model to systematically assess the effectiveness and sustainability of land consolidation. The results reveal systemic deficiencies: within ecological spaces, short-term desalination succeeds but pH and organic matter improvements remain inadequate, while ecosystem vulnerability increases due to climate fluctuations and grassland conversion. In production spaces, cropland expansion and saline land reduction are effective, but water resource management proves unsustainable. Living spaces show improved infrastructure and income but face threats due to economic simplification and intergenerational unsustainability. For the investigated case, recommendations include shifting from technical restoration to systemic governance via three strategies: (1) biological–engineering synergy employing green manure to enhance soil microbial activity; (2) hydrological balancing through groundwater quotas and rainwater utilization; (3) specialty industry development for rural economic diversification. This study contributes empirical evidence on the conversion of saline–alkali land, as well as an evaluation framework of wider relevance for developing countries combating land degradation and pursuing rural revitalization. Full article

In the Kubernetes edge computing environment, Resource Quota plays a vital role in efficient limited resource management because it defines the maximum resources that each service or tenant can use. Therefore, when edge nodes serve multiple services simultaneously, resource quota prevents any single service from monopolizing resources. However, the manual resource quota configuration mechanism in current Kubernetes-based management platforms is not dynamic enough to handle fluctuating resource demands of services over time. Slow quota extension during surge traffic prevents scaling up necessary pods and degrades service performance, while over-allocating quotas during light traffic might occupy valuable resources that other services may need. This study proposes a Dynamic Resource Quota Auto-scaling Framework, combining proactive scaling based on workload predictions with reactive mechanisms to handle both inaccurate predictions and unforeseeable events. This framework not only optimizes resource allocation but also maintains stable performance, reduces deployment failures, and prevents over-allocation during scaling in high-demand periods. Full article

To overcome the absence of a standardized budget quota system for high-standard farmland projects and the resultant extended compilation cycles and high workloads, this study systematically analyzes quota consumption and innovatively proposes an integrated DEMATEL-ISM-BN and gray clustering analytical model. Through a literature review and engineering feature analysis, a hierarchical factor system was established, encompassing six dimensions (environmental, technical, labor, machinery, material, and management) and 24 indicators. The DEMATEL-ISM method quantified factor weights and structured them into a five-level hierarchy, while Bayesian networks (BNs) enabled probabilistic productivity predictions (29% conservative, 45% moderate, and 26% advanced). Gray clustering was integrated to derive a comprehensive representative consumption value, and validation across six regions demonstrated a comprehensive productivity index of 0.986 (CV = 2.6%) for 17 earthwork projects, confirming model robustness. This research constructs a standardized “factor structure analysis–probabilistic deduction–regional clustering” framework, providing a theoretical foundation for precise budget compilation in high-standard farmland and proposing a novel methodological paradigm for quota consumption research. Full article

With the proposal of China’s “dual carbon” goal, the carbon market has become a vital tool for controlling carbon emissions. This study constructs a system dynamics model encompassing carbon trading, the economy, energy, population, and the environment, and conducts simulation analysis against the backdrop of China’s national carbon market’s implementation. The results indicate that the implementation of China’s national carbon market significantly promotes carbon emissions reduction, albeit at the cost of some economic development in the short term. However, the suppressive effect of the carbon market on carbon emissions is stronger than its negative impact on economic growth. The effects of carbon reduction strengthen with increases in carbon price, quota auction, CCER price, penalty severity, and the quota reduction rate and weaken with a higher CCER offset ratio. A moderate reduction in the tightening quota reduction rate is more conducive to achieving coordinated development across the multiple objectives of carbon reduction, economic development, and energy structure. Under the constraints of multiple objectives involving carbon reduction, economic development, and energy structure, the reasonable range for carbon prices is between CNY 77.9 and CNY 118.9 per ton, with the maximum quota auction of 23.4%. Additionally, the reasonable range for the quota reduction rates is between 0.84% and 2.18%, with the penalty severity set at 7. Full article

Chinese public building carbon emissions trading system (CETS) pilots have employed different carbon quota methods over more than ten years. However, there are few quantitative comparisons on CETS emission reduction effects in different pilots based on the carbon quota analysis. This paper first calculates the annual carbon quotas of public buildings based on carbon quota allocation methodologies from municipal policy documents. Then, the factors affecting the carbon quotas of public buildings are analyzed. Finally, the emission reduction effects are analyzed and compared between the pilots. The findings are concluded as follows: (1) Public building stock area and energy efficiency demonstrate significant effects on the carbon quota. (2) The average annual carbon quota deficits of public buildings were 929,800 tons in Beijing and 596,000 tons in Shanghai, while the carbon quota was an annual surplus of 296,400 tons in Shenzhen, indicating that carbon quota allocations in Beijing and Shanghai pilots are more conducive to promoting the active participation of high-emission enterprises. (3) The emission reduction effect in Beijing is most pronounced, followed by Shanghai and finally Shenzhen. Accordingly, the reasons for the difference in emission reduction effects are analyzed. This study contributes to the carbon quota allocation and emission reduction of public buildings. Full article

The scientific investment decision of Park-level Integrated Energy System (PIES) projects is of great significance to energy enterprises for improving the efficient utilization of funds, promoting green and low-carbon transformation, and achieving the goal of carbon neutrality. This paper proposed a two-stage investment framework that integrates a multi-objective 0–1 programming model with a multi-criteria decision-making (MCDM) technique to determine the optimal PIES project investment portfolios under the constraint of quota investment. First, a multi-objective (MO) 0–1 programming model was constructed for typical PIES projects in Stage-I, which considers economic and environmental benefits to obtain Pareto frontier solutions, i.e., PIES project portfolios. Second, an evaluation index system from multiple dimensions was established, and a hybrid MCDM technique was adopted to comprehensively evaluate the Pareto frontier solutions in Stage-II. Finally, the proposed model was applied to an empirical case, and the simulation results show that the decision framework can achieve the best overall benefit of PIES project portfolios with maximal economic benefit and minimum carbon emissions. In addition, the robustness analysis was performed by changing the indicator weights to verify the stability of the proposed framework. This research work could provide a theoretical tool for investment decisions regarding PIES projects for energy enterprises. Full article

In the context of the intensifying global climate crisis, the power industry, as a significant carbon emitter, urgently needs to promote low-carbon transformation using market mechanisms. In this paper, a multi-objective stochastic optimization scheduling framework for regional power grids integrating carbon trading (CET) and green certificate trading (GCT) is proposed to coordinate the conflict between economic benefits and environmental objectives. By building a deterministic optimization model, the goal of maximizing power generation profit and minimizing carbon emissions is combined in a weighted form, and the power balance, carbon quota constraint, and the proportion of renewable energy are introduced. To deal with the uncertainty of power demand, carbon baseline, and the green certificate ratio, Monte Carlo simulation was further used to generate random parameter scenarios, and the CPLEX solver was used to optimize scheduling schemes iteratively. The simulation results show that when the proportion of green certificates increases from 0.35 to 0.45, the proportion of renewable energy generation increases by 4%, the output of coal power decreases by 12–15%, and the carbon emission decreases by 3–4.5%. At the same time, the tightening of carbon quotas (coefficient increased from 0.78 to 0.84) promoted the output of gas units to increase by 70 MWh, verifying the synergistic emission reduction effect of the “total control + market incentive” policy. Economic–environmental tradeoff analysis shows that high-cost inputs are positively correlated with the proportion of renewable energy, and carbon emissions are significantly negatively correlated with the proportion of green certificates (correlation coefficient −0.79). This study emphasizes that dynamic adjustments of carbon quota and green certificate targets can avoid diminishing marginal emission reduction efficiency, while the independent carbon price mechanism needs to enhance its linkage with economic targets through policy design. This framework provides theoretical support and a practical path for decision-makers to design a flexible market mechanism and build a multi-energy complementary system of “coal power base load protection, gas peak regulation, and renewable energy supplement”. Full article

The planting area of the maize–soybean strip intercropping system has been increasing annually in the Hexi Corridor oasis irrigation area of China. However, long-term irrational water resource utilization and the excessive mono-application of fertilizers have led to significantly low water and nitrogen use efficiency in this cropping system. To explore the sustainable production model of high yield and high water–nitrogen productivity in maize–soybean strip intercropping, we established three irrigation levels (low: 60%, medium: 80%, and sufficient: 100% of reference crop evapotranspiration) and three nitrogen application levels (low: maize 230 kg ha⁻¹, soybean 29 kg ha⁻¹; medium: maize 340 kg ha⁻¹, soybean 57 kg ha⁻¹; and high: maize 450 kg ha⁻¹, soybean 85 kg ha⁻¹) for maize and soybean, respectively. Three irrigation levels without nitrogen application served as controls. The effects of different water–nitrogen combinations on multiple indicators of the maize–soybean strip intercropping system, including yield, water–nitrogen productivity, and quality, were analyzed. The results showed that the irrigation amount and nitrogen application rate significantly affected the kernel quality of maize. Specifically, the medium nitrogen and sufficient water (N2W3) combination achieved optimal performance in crude fat, starch, and bulk density. However, excessive irrigation and nitrogen application led to a reduction in the content of lysine and crude protein in maize, as well as crude fat and crude starch in soybean. Appropriate irrigation and nitrogen application significantly increased the yield in the maize–soybean strip intercropping system, in which the N2W3 treatment had the highest yield, with maize and soybean yields reaching 14007.02 and 2025.39 kg ha⁻¹, respectively, which increased by 2.52% to 138.85% and 5.37% to 191.44% compared with the other treatments. Taking into account the growing environment of the oasis agricultural area in the Hexi Corridor and the effects of different water and nitrogen supplies on the yield, water–nitrogen productivity, and kernel quality of maize and soybeans in the strip intercropping system, the highest target yield can be achieved when the irrigation quotas for maize and soybeans are set at 100% ET0 (reference crop evapotranspiration), with nitrogen application rates of 354.78~422.51 kg ha⁻¹ and 60.27~71.81 kg ha⁻¹, respectively. This provides guidance for enhancing yield and quality in maize–soybean strip intercropping in the oasis agricultural area of the Hexi Corridor, achieving the dual objectives of high yield and superior quality. Full article

Wake steering has emerged as a promising strategy to mitigate turbine wake losses, with existing research largely focusing on the aerodynamic optimization of yaw angles. However, many prior approaches rely on static look-up tables (LUTs), offering limited adaptability to real-world wind variability and leading to non-optimal results. More importantly, these energy-focused strategies overlook the mechanical implications of frequent yaw activities in pursuit of the maximum power output, which may lead to premature exhaustion of the yaw system’s design life, thereby accelerating structural degradation. This study proposes a supervisory control framework that balances energy capture with structural reliability through three key innovations: (1) upstream-based inflow sensing for real-time capture of free-stream wind, (2) fatigue-responsive optimization constrained by a dynamic actuation quota system with adaptive yaw activation, and (3) a bidirectional threshold adjustment mechanism that redistributes unused actuation allowances and compensates for transient quota overruns. A case study at an offshore wind farm shows that the framework improves energy yield by 3.94%, which is only 0.29% below conventional optimization, while reducing yaw duration and activation frequency by 48.5% and 74.6%, respectively. These findings demonstrate the framework’s potential as a fatigue-aware control paradigm that balances energy efficiency with system longevity. Full article

In the context of global climate governance and the low-carbon energy transition, virtual power plant (VPP), a key technology for integrating distributed energy resources, is urgently needed to solve the problem of decentralization and lack of synergy in electricity, carbon, and green certificate trading. Existing studies mostly focus on single energy or carbon trading scenarios and lack a multi-market coupling mechanism supported by blockchain technology, resulting in low transaction transparency and a high risk of information tampering. For this reason, this paper proposes a synergistic optimization strategy for electricity/carbon/green certificate virtual power plants based on blockchain cross-chain transactions. First, Latin Hypercubic Sampling (LHS) is used to generate new energy output and load scenarios, and the K-means clustering method with improved particle swarm optimization are combined to cut down the scenarios and improve the prediction accuracy; second, a relay chain cross-chain trading framework integrating quota system is constructed to realize organic synergy and credible data interaction among electricity, carbon, and green certificate markets; lastly, the multi-energy optimization model of the virtual power plant is designed to integrate carbon capture, Finally, a virtual power plant multi-energy optimization model is designed, integrating carbon capture, power-to-gas (P2G) and other technologies to balance the economy and low-carbon goals. The simulation results show that compared with the traditional model, the proposed strategy reduces the carbon emission intensity by 13.3% (1.43 tons/million CNY), increases the rate of new energy consumption to 98.75%, and partially offsets the cost through the carbon trading revenue, which verifies the Pareto improvement of environmental and economic benefits. This study provides theoretical support for the synergistic optimization of multi-energy markets and helps to build a low-carbon power system with a high proportion of renewable energy. Full article

Amid intensified global climate mitigation efforts, integrating rail freight into carbon emissions trading schemes became critical under China’s “Dual-Carbon” strategy. Despite rail’s significantly lower emissions intensity compared to road transport, existing pricing frameworks inadequately internalized its environmental externalities, which limited its competitive advantage. To address this gap, this study systematically reviewed international and domestic practices of integrating transport into carbon trading systems and developed a novel “four-layer, three-dimensional” emissions trading scheme (ETS) framework tailored specifically for China’s rail freight sector. Employing a Stackelberg bilevel optimization model, this study analyzed how carbon quotas and pricing influenced rail operators’ pricing and investment decisions. The results showed that under optimized quotas and carbon prices, railway enterprises were able to generate surplus carbon credits, creating new revenue streams and enabling freight rate reductions. This “carbon revenue–freight rate feedback loop” not only delivered environmental benefits but also enhanced rail’s economic competitiveness. Overall, this study significantly advances the understanding of carbon-based pricing mechanisms in railway freight, providing robust theoretical insights and actionable policy guidance for achieving sustainable decarbonization in China’s transport sector. Full article

From the perspective of biogas plant (BGP) operators, it is highly challenging to make a profitable decision on optimal biomethane production and allocation across interconnected markets. The aim of this study is to analyze the dynamics of biomethane markets, develop the gas allocation portfolio (GAP) for BGPs, investigate the impact of GHG quota price on the market dynamics and substrate mix consumption, and evaluate the profitability of the biomethane market system under various demand-based scenarios. A two-step optimization approach based on linear programming is adopted. Firstly, the optimized substrate mix and corresponding GAP are determined for all BGPs. Secondly, by leveraging the options flexibility created by the interconnected nature of biomethane markets, the BGPs’ GAP is further developed. Through an in-depth sensitivity analysis, the effects of GHG quota price variations on the market dynamics are assessed. The results indicate that integrated production, obtained by implementing the improved GAP across all BGPs, maximizes the profitability of the system. At higher quota prices, the consumption of manure, residuals, and grass is encouraged, while the use of energy crops declines. Furthermore, higher quota prices lead to a substantial increase in biomethane price in the EEG market, highlighting the need for further governmental support for biomethane CHP units. The anticipated competition between hydrogen and biomethane to achieve a greater share in the heating sector could pose risks to long-term investments in biomethane. The system achieves its highest profitability, a total contribution margin of EUR 2254.8 million, under the Transport Biofuels Expansion scenario. Generally, policies and regulations that raise the quota price (e.g., the 36. BImSchV) or promote biomethane demand in the heating sector (e.g., the GEG) can provide both economic and ecological benefits to the system. Full article

To achieve low-carbon economic dispatch and collaborative optimization of carbon capture efficiency in power systems, this paper proposes a flexible carbon capture power plant and generalized energy storage collaborative operation model under a dynamic carbon quota mechanism. First, adjustable carbon capture devices are integrated into high-emission thermal power units to construct carbon–electricity coupled operation modules, enabling a dynamic reduction of carbon emission intensity and enhancing low-carbon performance. Second, a time-varying carbon quota allocation mechanism and a dynamic correction model for carbon emission factors are designed to improve the regulation capability of carbon capture units during peak demand periods. Furthermore, pumped storage systems and price-guided demand response are integrated to form a generalized energy storage system, establishing a “source–load–storage” coordinated peak-shaving framework that alleviates the regulation burden on carbon capture units. Finally, a multi-timescale optimization scheduling model is developed and solved using the GUROBI algorithm to ensure the economic efficiency and operational synergy of system resources. Simulation results demonstrate that, compared with the traditional static quota mode, the proposed dynamic carbon quota mechanism reduces wind curtailment cost by 9.6%, the loss of load cost by 48.8%, and carbon emission cost by 15%. Moreover, the inclusion of generalized energy storage—including pumped storage and demand response—further decreases coal consumption cost by 9% and carbon emission cost by 17%, validating the effectiveness of the proposed approach in achieving both economic and environmental benefits. Full article

Summer maize is an important grain crop in the North China Plain, but the problem of irrational application of water and fertilizer is becoming increasingly serious. Optimizing water and nitrogen management not only improves yield but also reduces water and fertilizer waste and environmental pollution. The Aquacrop model was calibrated and validated using a two-year summer maize field trial, and 16 different water and nitrogen scenarios were simulated and analyzed. In particular, the field trials were divided into 10 water–nitrogen treatments. The results showed that (1) the model has good applicability to the growth process of summer maize in the North China Plain. (2) Excessive water and nitrogen application would reduce yield by 5.6–33.7%, nitrogen bias productivity by 8.1–32.5%, and water use efficiency by 6.4–84.6%. (3) The optimal irrigation and nitrogen application program for furrow-irrigated summer maize is an irrigation quota of 360 mm in conjunction with nitrogen application of 240 kg/ha. This study provides a theoretical basis for a water-saving, fertilizer-saving, high-yield water and fertilizer management system for summer maize in the North China Plain. Full article