Search Results (44)

Against the background of carbon neutrality, the impact of carbon quota allocation mechanism on supply chain’s decision-making of emission reduction has received increasing attention. This study analyzes the optimal decision-making behavior of manufacturing supply chains under three mechanisms: completely free, complete auction and hybrid. Meanwhile, the abatement cost-sharing contract is introduced and the backward induction method is applied to solve the optimal equilibrium solution under each mechanism. Combined with numerical simulation, this study further investigates the impacts of market demand and cost-sharing coefficient changes on the system profit. The result shows that the abatement cost-sharing contract can significantly improve the level of manufacturers’ abatement and the total profit of the supply chain. Among the mechanisms analyzed, the hybrid mechanism realizes the balance between efficiency and incentives and demonstrates stronger adaptability and policy flexibility. 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

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

The building sector significantly contributes to global resource depletion and greenhouse gas emissions, necessitating integrated approaches to evaluate both environmental and economic performance. This study developed a sustainability-oriented assessment framework—applied in a Chinese context—that integrates life cycle assessment (LCA), life cycle costing (LCC), and carbon financial optimization to evaluate the life cycle performance of prefabricated steel buildings. Using publicly available databases (CEADs, Ecoinvent, and the Chinese Life Cycle Database), the framework quantified cradle-to-grave environmental impacts across raw material extraction, prefabrication, transport, on-site assembly, operation, and end-of-life stages. Emissions were monetized using standardized emission factors and official cost coefficients, enabling environmental costs to be expressed in financial terms. A dynamic financial simulation module was incorporated to assess the effects of carbon price fluctuations and quota allocation schemes. Sensitivity analyses were performed to examine the influence of key variables such as retrofit investment costs, emission reduction efficiency, and carbon policy scenarios on financial returns. The results show that material production and operational energy use dominate life cycle carbon emissions, jointly contributing more than 90% of the total impacts. Moderate decarbonization investments—such as HVAC upgrades and improved insulation—can achieve positive net economic returns under baseline carbon pricing. This integrated, data-driven framework serves as a practical decision-support tool for policymakers and industry stakeholders. It is adaptable across different regions and material systems, supporting the global transition toward low-carbon and financially viable construction practices. Full article

The intensifying impacts of climate change induced by carbon emissions necessitate the implementation of urgent mitigation strategies. Given that the power sector is a major contributor to global carbon emissions, strategic decarbonization planning in this sector is of paramount importance. This study proposes a synergistic planning framework for low-carbon power systems that integrates coal-fired power plants (CFPPs) and a carbon and green certificate market coupling mechanism, thereby facilitating a “security–economic–low-carbon” tri-objective transition in power systems. The proposed framework facilitates dynamic decision-making regarding the retrofitting of CFPPs, investments in renewable energy resources, and energy storage systems. By evaluating three distinct CFPP retrofitting pathways, the framework enhances economic efficiency and reduces carbon emissions, achieving reductions of 28.67% in total system costs and 2.96% in CO₂ emissions. Implementing the carbon–green certificate market coupling mechanism further unlocks the market value of green certificates, thereby providing economic incentives for clean energy projects and increasing flexibility in the allocation of carbon emission quotas for enterprises. Relative to cases that consider only carbon trading or only green certificate markets, the coupled mechanism reduces the total cost by 10.96% and 15.56%, and decreases carbon emissions by 27.10% and 47.36%, respectively. The collaborative planning framework introduced in this study enhances economic performance, increases renewable energy penetration, and reduces carbon emissions, thus facilitating the low-carbon transition of power systems. Full article

China is a leading producer and consumer of coal, with coal being the dominant energy source. The accurate calculation of the mass carbon emission factor (EF_m) of coal is crucial as the carbon emissions from its combustion influence carbon emission assessment and policy formulation. However, discrepancies in EF_m values across documents, due to varying net calorific values (NCVs), carbon contents (CCs), and carbon oxidation factors (COFs), have posed challenges for enterprises in carbon emission calculations. By analyzing different coal types, it is found that for anthracite, the EF_m difference in different documents can reach 38.5%; for bituminous coal, it can reach 42.3%; and for lignite, it can reach 18.6%. These differences significantly affect carbon emission calculation accuracy, carbon allowance allocation fairness, and enterprise costs under the Carbon Border Adjustment Mechanism (CBAM). For instance, in 2023, the calculated carbon emissions of anthracite vary by over 300 million tons depending on the EF_m used. To address these issues, relevant departments should establish a unified EF_m release system, build a data sharing platform, and standardize enterprise testing standards to enhance the accuracy of carbon-related calculations and drive the low-carbon development of the coal industry. Full article

The carbon emissions trading market is an important policy tool for the implementation of the “double carbon” goal, and the study of carbon emission quotas is an important topic for promoting green transformation, energy savings, and emission reduction in enterprises. This paper surveys the development and construction history of China’s carbon trading market, uses the VOS-viewer measurement tool to analyze the keywords co-occurrence and evolution trend of the literature about the carbon trading market from 2005 to 2024, analyzes the research hotspots, and reviews the principles of the initial carbon quota allocation, carbon quota distribution methods, and the carbon trading market carbon quota mechanism under the model construction, etc. The following conclusions can be drawn: (1) The most commonly used principles for allocating initial carbon quota are the principle of equity, the principle of efficiency, and the principle of synthesis. The equity principle focuses on the capacities and burdens of different participants; the efficiency principle maximizes incentives for participants to reduce carbon emissions; the comprehensive principle allocates carbon allowances from the perspective of enterprises, with less consideration for social responsibility and economic benefits. (2) In terms of carbon quota allocation, the initial quota should be gradually tightened, and the proportion of paid quotas should be increased. (3) The types of participants in the carbon emission reduction supply chain model are relatively simple. This paper analyzes the current situation of the research on carbon emission quota, discusses its development rules and problems, and puts forward theoretical and practical suggestions for the better development and construction of China’s unified carbon market in the future. Full article

Formulating a scientifically sound and efficient approach to allocating carbon quota aligned with the carbon peaking goal is a fundamental theoretical and practical challenge within the context of climate-oriented trading in the power sector. Given the highly irrational allocation of carbon allowances in China’s power sector, as well as the expanding role of renewable energy, it is essential to rationalize the use of green energy in the development of carbon reduction in the power sector. This study addresses the risk of “carbon transfer” within the power industry and develops a predictive model for CO₂ emission based on multiple influential factors, thereby proposing a carbon quota distribution scheme adapted to green energy growth. The proposed model employs a hybrid of the gray forecasting model-particle swarm optimization-enhanced back-propagation neural network (GM-PSO-BPNN) for forecasting and allocating the total carbon quota. Assuming consistent total volume control through 2030, carbon quota is distributed to regional power grids in proportion to actual production allocation. Results indicate that the PSO algorithm mitigates local optimization constraints of the standard BP algorithm; the prediction error of carbon emissions by the combined model is significantly smaller than that of the single model, while its identification accuracy reaches 99.46%. With the total national carbon emissions remaining unchanged in 2030, in the end, the regional grids received the following quota values: 873.29 million tons in North China, 522.69 million tons in Northwest China, 194.15 million tons in Northeast China, 1283.16 million tons in East China, 1556.40 million tons in Central China, and 1085.37 million tons in the Southern Power Grid. The power sector can refer to this carbon allowance allocation standard to control carbon emissions in order to meet the industry’s emission reduction standards. Full article

We construct a Stackelberg differential game model in which industries with varying degrees of market rivalry are the followers, and the government is the leader, describing their long-term dynamic optimal decision-making behaviors, and we research how the government establishes the unit carbon trading price based on feedback from various industries in the early stages of carbon trading market establishment. We also examine how to decrease the peaking period and lower the peak value of the industry’s overall carbon emissions by modifying the pivotal parameters. Furthermore, the impacts of relevant parameters on the optimal feedback strategy are also analyzed. In light of this, policymakers may obtain the optimal carbon trading price for various industries based on the actual market competition levels in those sectors, achieving the goal of reducing carbon emissions while growing the economy. The government can incentivize companies to reduce carbon emissions by reasonably allocating carbon emission quotas. This approach helps achieve a win-win situation for environmental protection and economic development, thereby promoting sustainable societal progress. Full article

Considering the supply chain composed of a power battery supplier and a new energy vehicle manufacturer, under the carbon cap-and-trade policy, this paper studies the different cooperation modes between the manufacturer and the supplier as well as their strategies for green technology and power battery production. Three game models are constructed and solved, respectively, under the collaboration mode of wholesale purchasing, patent-licensed manufacturing, and own R&D + Wholesale purchasing. The equilibrium analysis is carried out. Finally, the influence of relevant parameters is explored through numerical simulation. It is found that (1) the manufacturer’s choice of optimal battery production strategy is influenced by the input cost of green technology, the production cost of power battery, the carbon trading price, and the free carbon quota allocated by the government; (2) the cost coefficient of technological innovation affects negatively the optimal decision-making of the supply chain members, the market demand, and the optimal profit, and it has no impact when the cost coefficient reaches a certain value; (3) carbon cap-and-trade policy can, to a certain extent, incentivize suppliers and manufacturers to carry out technological innovation to reduce carbon emissions in the production process, but we cannot ignore the negative impacts of excessively high carbon trading price on the level of emission reduction and the market demand; and (4) the government should reasonably control the carbon price and carbon quota. The above conclusion will provide reference suggestions for new energy vehicle manufacturers and related suppliers. Full article

The carbon quota allocation method serves as the foundation for the design of the carbon trading mechanism, which has a significant impact on supply chain production decisions and the operational efficiency of the carbon trading market. To analyze the behavioral decision problem of supply chain members under different carbon quota allocation methods, the low-carbon reference effect is introduced to characterize the effect of consumers’ low-carbon preference on market demand. On this basis, three differential game models are constructed, namely, no emissions penalty, trading under the grandfathering principle, and trading under the benchmarking principle. The results indicate that the implementation of carbon trading policies enhances consumers’ low-carbon reference levels, the carbon emission reduction levels of manufacturers, and the low-carbon publicity levels of retailers. Moreover, the enhancement of the low-carbon reference effect becomes a positive driver of profit growth. Manufacturers are observed to make more efforts in carbon reduction under the benchmarking principle compared to the grandfathering principle. In contrast, the level of low-carbon publicity by retailers remains unchanged. The above findings can provide a scientific basis for the decision-making of emission reduction in low-carbon supply chain enterprises, which has certain theoretical significance. Full article

Achieving the target of carbon neutrality has been an important approach for China to mitigate global climate change. Enterprises are major carbon emitters, and a well-designed early warning system is needed to ensure that their emissions align with carbon neutrality goals. Therefore, this study utilized electricity big data to construct an early warning model for enterprise carbon emissions based on carbon quota allocation. Taking key carbon-emitting enterprises in Guangxi as a case study, we aim to provide insights to support China’s dual carbon goals. Firstly, we established the Carbon Quota Allocation System, enabling carbon quota allocation at the enterprise levels. Secondly, we developed the Enterprise Carbon Neutrality Index, facilitating dynamic warnings for carbon emissions among enterprises. The main conclusions are as follows: (1) In 2020, Guangdong received the highest carbon quota of 606 million tons, representing 5.72% of the national total, while Guangxi only received 2.63 billion tons. (2) Only 39.34% of enterprises in Guangxi are able to meet the carbon neutrality target, indicating significant emission reduction pressure faced by enterprises in the region. (3) Over 90% of enterprises in Guangxi receive Commendation and Encouragement warning levels, suggesting that enterprises in Guangxi are demonstrating a promising trend in emission reduction efforts. Full article

As the international community attaches importance to environmental and climate issues, carbon dioxide emissions in various countries have been subject to constraints and limits. The carbon trading market, as a market tool to reduce greenhouse gas emissions, has gone through a development process from a pilot carbon market to a national carbon market in China. At present, the industries included in the national carbon market are mainly the electric power industry, and the carbon emissions of the electric power industry account for about 40% of the national carbon emissions. According to the construction history of foreign carbon markets, China’s future carbon quota allocation will gradually transition from free allocation to auction allocation, and the auction mechanism will bring a heavy economic burden to the electric power industry, especially the thermal power generation industry. Therefore, this study takes Guangdong Province as an example to optimize the power generation mix with the objective of minimizing the total economic cost after the innovative introduction of the carbon quota auction mechanism, constructs an optimization model of the power generation mix based on the auction ratio by comprehensively applying the system dynamics model and the multi-objective linear programming model, systematically researches the power generation structure under different auction ratios with the time scale of months, and quantitatively evaluates the economic inputs needed to reduce the greenhouse gas emissions. The results of the study show that after comprehensively comparing the total economic cost, renewable energy development, and carbon emissions, it is the most scientific and reasonable to set the auction ratio of carbon allowances at 20%, which achieves the best level of economic and environmental benefits. Full article

Supported by the coordinated development strategy, the Beijing–Tianjin–Hebei (BTH) region has achieved rapid development but also faces severe energy consumption and environmental pollution problems. As the main responsibility of emission reduction, the coordinated and orderly implementation of carbon emission reduction in Beijing, Tianjin, and Hebei is of great significance to the realization of the carbon neutrality target. Based on this, this study comprehensively uses the expanded STIRPAT model, optimized extreme learning machine (ELM) network, entropy method, and zero-sum gains DEA (ZSG-DEA) model to explore the carbon emission drivers, long-term emission reduction pathway, and carbon quota allocation in the BTH region. The results of the driving factor analysis indicate that the proportion of non-fossil energy consumption is a significant driving factor for Beijing’s carbon emissions, and the improvement of the electrification level can inhibit the carbon emissions. The total energy consumption has the greatest impact on the carbon emissions of Tianjin and Hebei. The simulation results reveal that under the constraint of the carbon neutrality target, Beijing, Tianjin, and Hebei should formulate more stringent emission reduction measures to ensure that the overall carbon emission will reach its peak in 2030. The cumulative emission reduction rate should exceed 60% in 2060, and negative carbon technology should be used to offset carbon emissions of not less than 360 million tons (Mt) per year by 2060. Furthermore, the allocation results show that Beijing will receive a greater carbon quota than Hebei. The final allocation scheme will greatly promote and encourage carbon emission reduction in Hebei Province, which is conducive to achieving the goal of carbon neutrality. Full article

To enhance the low-carbon level and economic performance of microgrid systems while considering the impact of renewable energy output uncertainty on system operation stability, this paper presents a robust optimization microgrid model based on carbon-trading mechanisms and demand–response mechanisms. Regarding the carbon-trading mechanism, the baseline allocation method is utilized to provide carbon emission quotas to the system at no cost, and a ladder carbon price model is implemented to construct a carbon transaction cost model. Regarding uncertainty set construction, the correlation of distributed generation in time and space is considered, and a new uncertainty set is constructed based on historical data to reduce the conservative type of robust optimization. Based on the column constraint generation algorithm, the model is solved. The findings indicate that upon considering the carbon-trading mechanism, the microgrid tends to increase the output of low-carbon units and renewable energy units, and the carbon emissions of the microgrid can be effectively reduced. However, due to the increase in power purchase from the distribution network and the increase in carbon transaction costs, the operating costs of the microgrid increase. Secondly, through the utilization of demand–response mechanisms, the microgrid can achieve load transfer between peaks and troughs. It is imperative to establish appropriate compensation costs for demand and response that balances both economic efficiency and system stability. At the same time, due to the time-of-use electricity price, the energy storage equipment can also play a load transfer effect and improve the system’s economy. Finally, sensitivity analysis was conducted on the adjustment parameters of distributed power sources and loads that have uncertain values. A comparison was made between the deterministic scheduling model and the two-stage robust optimization model proposed in this study. It was proved that this model has great advantages in coordinating the economy, stability and low carbon level of microgrid operations. Full article