Emission Trading Mechanism Research Articles

The Role and Prospect of Emission Trading in the Optimal Allocation of Environmental Resources

The emission trading system is an important institutional innovation which effectively uses market mechanisms to improve the efficiency of environmental governance, and plays an important role in exploiting the potential of emission reduction for government and enterprise, which would realize the optimal allocation of environmental resources. The study analyses the design mechanism of emission trading system, the crucial parts including verification of emission rights, paid use for resources, emission trading, reserve and control mechanism, as well as management and incentive policies. Thereby, the current problems of emission trading system in China have been found out, including the deficiency of top-level design, ineffective cohesive mechanism between different systems, inactive trading market, and insufficient supporting policy guarantee policy. Based on the development trend of national policies and the practical problems faced by emission trading, the study proposes four prospects for the emission trading efforts. First, the issuance of guidance documents for deepening the emission trading system at the national level is an important foundation for the development of the emission trading system. Second, convergence between the emission rights trading and the emission permit system is the inevitable trend of the development of the system. Third, working on promoting the construction of a trading system dominated by market mechanisms is the focus of the optimal allocation of resources and environment. Last, establishing and improving relevant supporting mechanisms is an important guarantee for the stable development of the emission rights trading market and the efficient allocation of environmental resources.

The synergetic competition of cross-regional integrated energy systems with low-carbon technology heterogeneity under carbon emission trading mechanism to achieve carbon reduction target

The integration of renewable and fossil energy in a Region Integrated Energy System (RIES) is recognized as an effective measure for carbon emission reduction. The emergence of carbon emission trading (CET) markets worldwide has raised the need to combine RIES optimal planning with CET to achieve carbon reduction targets. This study focuses on the synergetic competition of a cross-RIES system with low-carbon technology heterogeneity under the CET mechanism. A cross-RIES model is constructed, incorporating fossil Carbon Capture System (fossil-CCS), renewable Combined Cooling Heating and Power (renewable-CCHP), and cleaner production paradigms. An improved version of the Non-dominated Sorting Genetic Algorithm-II (NSGA-II) is used to propose a bi-level multi-objective optimal planning framework for the cross-RIES model, employing a grandfather permit allocation method. Comparative analysis is conducted between cross-RIES optimal planning with and without considering the CET mechanism, with a focus on environmental indexes such as carbon emission, carbon intensity, and marginal abatement cost. Sensitivity studies are also performed to explore the impact of key CET design parameters on the system's environmental performance. The simulation results demonstrate that the CET mechanism effectively reduces carbon emission, primary energy consumption, and carbon intensity by promoting synergetic competition among the low-carbon technology heterogeneity of RIESs. Furthermore, the environmental performance varies among the three types of RIES. In terms of CET parameter design, lowering the cap constraint, reducing the allowance allocation ratio of fossil-CCS RIES, and increasing the trading price contribute significantly to reducing carbon emission and carbon intensity, albeit at the expense of higher marginal abatement cost.

Two-Stage Robust Optimization of Integrated Energy Systems Considering Uncertainty in Carbon Source Load

Integrated Energy Systems (IESs) interconnect various energy networks to achieve coordinated planning and optimized operation among heterogeneous energy subsystems, making them a hot topic in current energy research. However, with the high integration of renewable energy sources, their fluctuation characteristics introduce uncertainties to the entire system, including the corresponding indirect carbon emissions from electricity. To address these issues, this paper constructs a two-stage, three-layer robust optimization operation model for IESs from day-ahead to intra-day. The model analyzes the uncertainties in carbon emission intensity at grid-connected nodes, as well as the uncertainty characteristics of photovoltaic, wind turbine, and cooling, heating, and electricity loads, expressed using polyhedral uncertainty sets. It standardizes the modeling of internal equipment in the IES, introduces carbon emission trading mechanisms, and constructs a low-carbon economic model, transforming the objective function and constraints into a compact form. The column-and-constraint generation algorithm is applied to transform the three-layer model into a single-layer main problem and a two-layer subproblem for iterative solution. The Karush–Kuhn–Tucker (KKT) condition is used to convert the two-layer subproblem into a linear programming model. A case study conducted on a park shows that while the introduction of uncertainty optimization increases system costs and carbon emissions compared to deterministic optimization, the scheduling strategy is more stable, significantly reducing the impact of uncertainties on the system. Moreover, the proposed strategy reduces total costs by 5.03% and carbon emissions by 1.25% compared to scenarios considering only source load uncertainty, fully verifying that the proposed method improves the economic and low-carbon performance of the system.

Source-Storage-Load Flexible Scheduling Strategy Considering Characteristics Complementary of Hydrogen Storage System and Flexible Carbon Capture System

In the current literature, there exists a lack of analysis regarding the coordination of the spinning reserve and time-shift characteristics of hydrogen storage systems (HSS) and flexible carbon capture systems (FCCS) in terms of low-carbon economic operation. They are presently used solely as a tool to capture carbon dioxide, without fully utilizing the advantages of their flexible operation. The coordination and complementarity of the FCCS and HSS can ensure stable power supply and improve renewable energy (RE) consumption. Combined with demand side response (DSR), these factors can maximize the RE consumption capacity, reduce carbon emissions, and improve revenue. In this paper, a source-storage-load flexible scheduling strategy is proposed by considering the complementary nature of FCCS and HSS in terms of rotating standby and time-shift characteristics. First, the operational mechanisms of FCCS, HSS, and demand side response (DSR) are analyzed, and their mathematical models are constructed to improve flexibility in grid operation and regulation. Next, deficiencies in FCCS and HSS operation under rotating reserve requirements are analyzed to design a coordinated operation framework for the FCCS and HSS. This operational framework aims to enable the complementarity of the rotating reserve and time-shift characteristics of FCCS and HSS. Finally, based on the carbon emission trading mechanism, a three-stage ladder carbon emission trading cost model is constructed, and a source-storage-load flexible scheduling strategy is established to achieve an effective balance between low carbon emissions and economic performance. The simulation results demonstrate that the strategy reduces the overall cost by 8.57%, reduces the carbon emissions by 35.33%, and improves the renewable energy consumption by 3.5% compared with the unoptimized scheme.

Operation Optimization of Regional Integrated Energy Systems with Hydrogen by Considering Demand Response and Green Certificate–Carbon Emission Trading Mechanisms

Amidst the growing imperative to address carbon emissions, aiming to improve energy utilization efficiency, optimize equipment operation flexibility, and further reduce costs and carbon emissions of regional integrated energy systems (RIESs), this paper proposes a low-carbon economic operation strategy for RIESs. Firstly, on the energy supply side, energy conversion devices are utilized to enhance multi-energy complementary capabilities. Then, an integrated demand response model is established on the demand side to smooth the load curve. Finally, consideration is given to the RIES’s participation in the green certificate–carbon trading market to reduce system carbon emissions. With the objective of minimizing the sum of system operating costs and green certificate–carbon trading costs, an integrated energy system optimization model that considers electricity, gas, heat, and cold coupling is established, and the CPLEX solver toolbox is used for model solving. The results show that the coordinated optimization of supply and demand sides of regional integrated energy systems while considering multi-energy coupling and complementarity effectively reduces carbon emissions while further enhancing the economic efficiency of system operations.

Research on the Impact of Carbon Emission Trading Market on Regional Economic Development: A Case Study of East China

This article delves into the impact of carbon emission trading mechanism on regional economy, especially in East China, and focuses on analyzing how this mechanism promotes green transformation and high-quality development of the economy by influencing green technology innovation of enterprises. Research has found that carbon emission trading not only incentivizes companies to reduce greenhouse gas emissions, but also guides capital and technological innovation to flow towards low-carbon areas through market mechanisms, thereby promoting the optimization of industrial structure and sustainable economic development. This article also discusses the impact of different quota allocation methods on green innovation in enterprises, pointing out that the benchmark method can more effectively stimulate the innovation drive of enterprises compared to the historical method. Therefore, according to the research findings, it is necessary to improve the construction of carbon markets, scientifically formulate quota allocation systems, avoid negative impacts on early green innovation enterprises, and provide policy support to reduce innovation costs for enterprises.

How carbon emission trading mechanism and supply chain digitization affect manufacturing enterprises’ competitiveness? Evidence from China

Under the background of digitalization and green development concept, exploring the road of manufacturing power is an important hand to promote the high-quality development of economy. The article constructs a triple difference model based on the list of emission-control enterprises of carbon emissions trading mechanism and China's pilot cities of supply chain innovation and application, and empirically investigates the impact of policy synergies of carbon emissions trading mechanism and supply chain digitization on the competitiveness of manufacturing enterprises by using the data of listed companies in the manufacturing industry from 2010 to 2022. The results show that the policy synergy effect of carbon emissions trading mechanism and supply chain digitization can improve the competitiveness of manufacturing enterprises. The impact mechanism test shows that the policy synergy effect of carbon emissions trading and supply chain digitization can enhance the competitiveness of manufacturing enterprises by alleviating the degree of cost-price incomplete transmission, promoting technological innovation, and improving the efficiency of resource allocation in the manufacturing industry. The direct impact of product quality on carbon emissions trading mechanism and supply chain digitization has a "U"-shaped moderating effect, when product quality is below the bottleneck of 0.418, exacerbating the fluctuation of production costs of enterprises, carbon emissions trading mechanism and supply chain digitization will have an inhibitory effect on the competitiveness of manufacturing enterprises. The conclusion confirms that the policy synergy effect of carbon emissions trading mechanism and supply chain digitization can promote manufacturing enterprises to improve competitiveness. However, manufacturing enterprises should pay attention to product quality, and if product quality is not dominant, carbon quota constraints and supply chain digitization will likewise inhibit the competitiveness of manufacturing enterprises. This study provides important policy insights for countries to actively promote the construction of carbon emissions trading mechanisms and stimulate the momentum of digitalization and high-quality transformation of manufacturing industries.

Research the synergistic carbon reduction effects of sulfur dioxide emissions trading policy

Since General Secretary Xi Jinping pledged the “30·60” targets to the world, the importance of pollution reduction and carbon reduction has become increasingly prominent. The previous focus on the pollution reduction effects of emission trading systems, while overlooking their carbon reduction impacts, as well as the limitations of research methods and scope, is no longer suitable for the needs of the new era. Therefore, this paper constructs a CGE model to study the synergistic effects, simulating the synergistic emission reduction effects of sulfur dioxide emission trading policies, and comes to the following conclusions: After the implementation of the sulfur dioxide emission trading mechanism, under different sulfur price scenarios, the synergistic reduction amounts of SO2 and CO2 vary greatly. As the sulfur price increases, the reduction amount becomes larger. In the five sulfur price scenarios set in this paper, the maximum reduction of SO2 can reach about 111,400 tons, and the maximum for CO2 is about 399 million tons. The CO2 reduction rate is approximately 1.0767 times that of SO2. This indicates that the sulfur dioxide emission trading policy is a very effective path for synergistic pollution and carbon reduction, with good reduction effects. In addition, sulfur dioxide emission trading will reduce the consumption of fossil energy, decrease industry output, raise product prices, cause GDP loss, and lead to reduced social welfare to varying degrees.

Complex dynamics of dual oligopoly demand uncertainty under carbon emission trading mechanism

The international community's growing focus on energy conservation and emission reduction has led businesses to prioritize low-carbon operations and the marketing of environmentally friendly products during their production processes. On the one hand, with the reform of carbon emissions trading, carbon emission trading has become a potential profit point for enterprises. On the contrary, the consumer market is influenced by the uncertain external environment. And consumers' environmental awareness increases the uncertainty of product demand. Therefore, the intricate dynamics of dual oligopoly demand uncertainty within the framework of a carbon emission trading mechanism are explored in this scholarly analysis. The best market Porter's generic strategies, including emission reduction investment and product pricing how can carbon quotas, uncertainty in market demand, and consumer environmental preferences improve expected profits? The results show that technology emission reduction costs, carbon emission trading prices and consumer preferences for low-carbon products. It is an important factor that affects the competitive strategy of the two enterprises. The different values of the above factors will change the relative intensity of emission reduction investment and the relative profitability of the two. Complete company statement in a balanced state. This article also investigates the complexity of adjusting the dynamic evolution path of competitive strategies between two organizations. Feedback controllers can effectively suppress unstable equilibrium states and provide effective references for their stable operation.

Operational Model Innovation of Hainan Green Logistics Park under the Carbon Emission Trading Mechanism

Operational Model Innovation of Hainan Green Logistics Park under the Carbon Emission Trading Mechanism

Expansion decision making of waste-to-energy combined heat and power project: A growth option perspective

Combined heat and power is an inevitable trend in the development of waste-to-power industry. Many waste incineration power generation projects that have already put into operation in China are waiting for transition and upgrading to combined heat and power projects. From a growth option perspective, this paper considers the irreversible process and uncertainty in economic benefits, introduces carbon emission trading mechanism and develops the growth option theory to design the expansion decision making model of waste-to-energy combined heat and power projects, so as to obtain the project value and find the optimal expansion timing. In this paper, a case study is carried out on the expansion decision making of a waste-to-energy combined heat and power project in Shandong Province in China. And two scenarios with specific and flexible expansion times are developed from European and American options separately, as European options require investors to expand at a certain time but American options not. The results indicate that 1) real option approach successfully improves the project value through considering uncertainty, and American option can achieve the optimal expansion time, 2) under the carbon emission trading mechanism, the carbon price affects the expansion index, which has a positive effect on the project value, 3) the linear nature of the income and cost expansion index can help investors make judgments on expansion investments. The effectiveness of the case study implies the practicality of the expansion option method for similar projects to reach dual carbon targets in cost and benefit analysis.

Supply chain coordination: the application of consignment and zero wholesale price contracts under customized cap-and-trade and consumers' environmental awareness

PurposeWithin a framework of supply chain (SC) coordination, this paper analyzes a green SC consisting of a retailer and a manufacturer, under government incentives and legislations and the consumer environmental awareness. To mitigate carbon emissions and promote the sustainability of the SC, a customized carbon emission trading mechanism is developed.Design/methodology/approachA game-theoretical decision model formulated determines the optimal sustainability level and the optimal quota of carbon credit from the ceiling capacity set by the government. In order to coordinate the SC and optimize environmental decisions, a novel combination of consignment and zero wholesale price contracts is proposed.FindingsAnalytical and numerical analyses conducted highlight that the proposed contract generates a Pareto improvement for both channel members, boosts the profit of the green SC, enhances the sustainability level of the channel and contributes to a reduction in the requested carbon emission credit by the manufacturer.Social implicationsWith the proposed mechanism, governments can protect their industries and, more importantly, comply with European Union (EU) rules on annually reducing emission ceilings allocated to industries.Originality/valueDifferent from previous studies on cap-and-trade strategies, the proposed mechanism enables companies to select lower emission quota/allowances than the maximum amount set by the government, and in return, companies can benefit from several incentive strategies of the government.

Optimal Scheduling Framework of Integrated Energy System Based on Carbon Emission in Electricity Spot Market

Micro coal-fired units (MCFU) and combined heat and power plants (CHP) in integrated energy system (IES) will emit a large amount of carbon dioxide when providing loads to customers, which will lead to higher operating costs of IES. To solve this challenge, an optimal dispatch model of power-to-gas (P2G) and methane reactor (MR) considering the reward and punishment costs based on carbon emission trading mechanism is proposed, to reduce carbon emissions of IES and enhance the accommodation of renewable energy (RE). Subsequently, considering the uncertainty of RE, a combination optimization method for MCFU and CHP units is developed based on the Lagrange multiplier method. Finally, considering the mechanism of electricity spot market (ESM), a transaction strategy for IES participating in ESM is proposed to further enhance the accommodation of RE. The effectiveness of the proposed framework is demonstrated through simulations.

The role of green reputation, carbon trading and government intervention in determining the green bond pricing: An externality perspective

Green bonds, due to their inherent externalities, pose challenges in achieving equilibrium prices under optimal public resource allocation and social welfare without governmental intervention. While numerous studies have explored green bond pricing via government subsidies and other strategies, this paper diverges by targeting the equilibrium price of green bonds as the optimal public resource allocation, specifically from an externality's standpoint. We integrate factors such as the cap-and-trade system, carbon taxes, government subsidies, and green reputation into the fractional jump-diffusion model. This is further combined with real options theory and the fast Fourier transform method to derive the green bond pricing equation. Through optimization techniques, we delve into the influences of various factors and the interplay of different governmental strategies. Numerical findings suggest that, in an ideal scenario where the government grants adequate carbon allowances to green bond issuers, the carbon emission trading mechanism can facilitate the bond in achieving its ideal equilibrium price. Conversely, when the government is restricted by carbon constraints, preventing green bond issuers from acquiring ample carbon allowances, supplementary measures like government subsidies and carbon tax policies can complement the cap-and-trade system, ensuring green bonds attain their ideal equilibrium price. Furthermore, given the carbon emission reduction level of green projects, our model can determine the optimal government subsidy ratio and the ideal carbon tax price.

Achieving the goal of net-zero requires both resource efficiency and efficient business management

This research study uses the ARDL technique to examine the impact of corporate management index and energy utilization on carbon emissions in Chinese listed companies. The sample consists of 500 firms that participated in China's Carbon Emission Trading Mechanism between 2016 and 2021. The results indicate that an improved corporate management index leads to significant reductions in carbon emissions, with a decrease of approximately 0.24% in the short term and 0.54% in the long term. On the other hand, increased energy expenditure contributes to higher carbon emissions, with an increase of around 0.28% in the short term and 0.33% in the long term. Additionally, the study emphasizes the importance of ICT and total assets in addressing carbon emissions. To achieve the goal of zero net carbon, practical policies that focus on resource efficiency and effective corporate management, such as setting ambitious carbon reduction targets, adopting renewable energy, and promoting collaboration among stakeholders, are recommended for Chinese listed companies.

Stochastic optimal scheduling strategy of cross-regional carbon emissions trading and green certificate trading market based on Stackelberg game

Under the urgent goal of "carbon peaking and carbon neutralization" in China and based on the distribution characteristics of renewable energy, it is essential to promote the large-scale consumption of renewable energy and increase the proportion of large-scale renewable energy in market transactions. Therefore, a stochastic optimal scheduling model that combines the Stackelberg game, cross-regional carbon emissions trading, and tradable green certificate transaction to consider the uncertainty of renewable energy power generation is proposed. To encourage more market participants to participate in the tradable green certificate trading, the model uses Stackelberg game theory to analyze the complex interest relationship between different market participants and obtain a scheduling scheme that balances the interests of different participants. To give full play to the role of the trading mechanism on the cross-regional system, the tradable green certificate trading mechanism and the carbon emission trading mechanism are combined to optimize the overall allocation of green certificates and carbon emission rights, to stimulate renewable energy generation, limit the carbon emission of traditional thermal power units and promote energy conversion. Finally, the modified IEEE 39-bus system and Hami power grid (in Western China) are used as examples to illustrate the feasibility and effectiveness of the proposed scheduling model. The results show that the proposed strategy improves the cross-regional system economy and reduces emissions, fully reflects the monetary value of the external characteristics of renewable energy, guides renewable energy investment and power grid planning, and promotes the consumption of renewable energy.

Low-carbon economic scheduling strategy for active distribution network considering carbon emissions trading and source-load side uncertainty

The double uncertainty of the source-load side poses a new challenge to the reliability of the low carbon scheduling in the active distribution network (ADN) system. In this study, a low-carbon economic scheduling model of the ADN system is proposed, which considers step-type carbon emissions trading (CET) mechanism and source-load side uncertainty. The multi-dimensional discrete probability sequences of source-load side are converted into the global equivalent load (EL) by the proposed discretized step transformation (DST) and the convolutional sequence operation (CSO) method, and the predicted value of EL is expressed by the expected value of the EL probability sequence. By setting the probability constraint of the spinning reserve capacity, the influence of power prediction error on the ADN system is fully considered. On this basis, the chance constraint problem (CCP) is further converted to a deterministic mixed-integer linear programming (MILP) problem by linearizing power flow constraints. The proposed strategy is verified based on the IEEE 33-bus ADN system. The experimental results indicate that the system can further realize the synergy of economic benefits and environmental benefits. In addition, compared with other intelligent algorithms, the solution time of the proposed strategy is significantly reduced, and the optimization effect is greatly improved.

Assessing the policy synergy among power, carbon emissions trading and tradable green certificate market mechanisms on strategic GENCOs in China

The establishment of carbon emissions trading (CET) and tradable green certificate (TGC) markets in China will cause great alterations in the bidding behavior for generation companies (GENCOs) and affect the low-carbon transformation of power industry. In this paper, a Nash bargaining game model is constructed to assess the synergy of power, CET and TGC markets on decision behavior of non-renewable energy GENCOs, renewable energy GENCOs and power purchasers. The simulation results show that there is transition incentive effect, price interaction effect and profit blocking effect between three markets. With the introduction of emissions trading scheme and renewable portfolio standard (RPS), the scheduled power of renewable energy GENCOs will increase by 21.43%, and transaction prices will reduce to 449.58 CNY/MWh; while the scheduled power of non-renewable energy GENCOs will reduce by 4.66%, and transaction prices will increase to 443.71 CNY/MWh, which make all power generation types compete at equivalent price level. Under the current installed capacity distribution and load demand, it is the critical point when RPS is 18.7% and the benchmark value of free carbon quota for units above and below 300 MW are 0.857 tCO2/MWh and 0.959 tCO2/MWh. Once exceeded, it will affect social benefits and emission reduction efficiency.

Green Bond Pricing and Optimization Based on Carbon Emission Trading and Subsidies: From the Perspective of Externalities

In this paper, we establish a model based on real options theory and fractional Brownian motion (FBM) with jumps to price green bonds, and thus alleviate the externalities of green bonds. We assume that the floating value of green bonds is linked to the carbon price. The carbon emission trading mechanism and government subsidy policy are introduced into this model, and the expression is derived from the stochastic differential utility framework based on the fast Fourier transform method. Based on the numerical analysis and the simulations, this paper analyzes when governments are facing financial and carbon emission constraints and how policymakers balance the allocation between carbon allowances and government subsidies to help green bonds reach the exogenous equilibrium price. Our results have implications in terms of optimizing the distribution of economic resources by the reasonable pricing of green bonds. It is in line with the current theme of global energy conservation and emission reduction, and also has certain guiding significance for the development of the carbon emission trading market.

Climate ambitions for European aviation: Where can sustainable aviation fuels bring us?

This paper assesses the costs of policies to promote the uptake of sustainable aviation fuels to reduce the greenhouse gas emissions of aviation in the EU. Different policies for attaining a minimum sustainable aviation fuel share are assessed, taking into account sustainability requirements and the costs and potential of feedstock supply. The cost-effectiveness of these policies is compared to simpler CORSIA-type emission trading schemes, using a model that combines the demand functions for road, rail and maritime transport fuels, the supply functions of the related feedstocks as well as the environmental sustainability characteristics of the fuels. For aviation a distinction is made between fuel demand for intra-EU flights and for incoming and outbound EU flights. It is shown that policies that aim to achieve a minimum share of 3.5% or 5.25% sustainable aviation fuels by 2030 in the EU are 5–10 times more expensive to reduce greenhouse gas emissions than a simpler emission trading mechanism like CORSIA.