Exploring the effect of cap-and-trade mechanism on firm's production planning and emission reduction strategy

This paper considers a carbon emission cap and trade market, where the carbon emission cap for each entity (either government or firm) is allocated first and then the carbon trading price is decided interdependently in the carbon trading market among the non-cooperative entities which make their production decision. We assume that there are n entities emitting carbon during the production process. After allocating the carbon (emission) cap for each participating entity in the carbon cap and trade market, each participant makes a production decision using the Newsvendor model given carbon trading price determined in the carbon trading market and trades some amount of its carbon emission, if its carbon emission is below or above its own carbon cap. Here, the carbon trading price depends on how carbon caps over the entities are allocated, since the carbon trading price is determined through the carbon (emission) trading market, which considers total amount of carbon emission being equal to total carbon caps over entities and some fraction of total carbon emission should be from each entity participating in the carbon cap and trade market. Thus, we can see the interdependency among the production decision, carbon cap and carbon trading price. We model this as a non-cooperative Stackelberg game in which carbon cap for each entity is allocated in the first stage and each entity’s production quantity is decided in the second stage considering the carbon trading price determined in the carbon trading market. First, we show the monotonic property of the carbon trading price and each entity’s production over the carbon cap allocation. In addition, we show that there exists an optimality condition for the carbon cap allocation. Using this optimality condition, we provide various results for carbon cap and trade market.

Based on different carbon quota trading mechanisms, the price and emission reduction strategies of oligopoly manufacturers in the low-carbon market and the government carbon quota mechanism are considered. A dynamic game evolution model of the two oligopoly manufacturers with competitive relations is established. The stability of the equilibrium point of the game model, the price adjustment speed of the decision variable, the impact of carbon emission reduction investment, and the government carbon quota on the system are discussed. Through nonlinear dynamics research, it is found that the advantage of the grandfathering method is that it is conducive to maintaining market stability when the government’s carbon quota decision changes; the advantage of the benchmarking method is that when manufacturers formulate price adjustment strategies, the benchmarking method carbon quota mechanism has a stronger stability range for the market, the manufacturer’s profit price adjustment speed is positively correlated, and the government carbon quota decision and emission reduction investment are also positively correlated. Decision makers need to choose appropriate carbon quota mechanisms and manufacturers’ emission reduction strategies according to actual market changes to maintain supply chain stability.

Market incentives, carbon quota allocation and carbon emission reduction: Evidence from China's carbon trading pilot policy.

Cap-and-trade regulation (CTR) is universally considered as one of the most environmentally friendly approaches to reducing carbon emission. In this paper, the newsvendor with a warranty service is regarded as the benchmark model firstly. Then, we study extended models about the newsvendor’s carbon footprint under CTR in the carbon trading market. Specifically, the carbon footprint exists in the four stages: production, sale, residual disposal, and return warranty service. And we adopt low-carbon technologies to improve the carbon footprint. Thirdly, we derive the newsvendor’s optimal production quantity, emission abatement level, and the expected profit. Interestingly, improving the carbon footprint in the sale and return warranty stages leads to a sharply higher profit in the carbon trading market. Finally, results and discussion are addressed in detail by numerical examples. We discover that optimal production quantity with an improved carbon footprint is larger than that with an original carbon footprint and earns more. Besides, the warranty service cost is negatively related to both the newsvendor’s optimal production quantity and profit. In the carbon trading market, the newsvendor is supposed to improve carbon footprint by carbon reduction investment. Besides, carbon quotas provided by the government do no affect the optimal production quantity but affects the profit of carbon trade.

Under low carbon environment, a multi-period emissions reduction problem for manufacturer is investigated in the paper, where we assume that the government sets mandatory carbon emissions limit to all the enterprises by free of charge and allows the carbon emission quota to be traded or banked inter-temporally in the carbon trading market. Using discrete-time optimal control theory, the optimal emission reduction strategies for each period are firstly explored for maximizing the sum of net profit under cap-and-trade. The optimal carbon emissions, permit trading quantity, and the number of buying Certified Emission Reduction (CER) are obtained in each period. Furthermore, the effects of carbon price and initial carbon quota given by the government on the firm’s emission reduction strategies are discussed. Finally, numerical examples are illustrated to verify the proposed model, and some managerial inferences for a multi-period emission reduction are provided in conclusions.

With the continuous growth in the volume of global air transportation, the carbon emissions of the civil aviation industry have received increasing attention. Carbon emission reduction in civil aviation is an inevitable requirement for achieving sustainable social development. This article aims to use system dynamics (SD) methods to establish a carbon emission model for the civil aviation industry that includes economic, demographic, technological, policy, and behavioral factors; analyze the key factors that affect carbon emissions; and explore effective emission reduction strategies. Researchers have found that SD-based carbon emission prediction has a high accuracy and is suitable for predicting carbon emissions in civil aviation. Through different scenario simulations, it has been found that any single emission reduction measure will struggle to effectively contribute to the expected carbon reductions in China’s civil aviation. Simultaneously adopting measures such as improving fuel efficiency, adopting clean energy, and using new-power aircraft is an effective way to reduce carbon emissions from civil aviation. In addition, policy intervention and technological innovation are equally crucial for achieving long-term emission reduction goals. The research results not only provide a scientific basis for the sustainable development of the aviation industry but also provide a reference for policymakers to formulate comprehensive emission reduction strategies.

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.

As a significant carbon dioxide-emitting country globally, China has set a concrete short-term target of carbon dioxideemissions peak in 2030 and an ambitious long-term plan to reach carbon neutrality by 2060. One essential policy is toset up a carbon trading market to reduce high-pollution enterprises’ carbon emissions by rationally allocating carbonquotas among different firms and regions and setting carbon quotas trading market.In reality, firms obtain carbon quotas in three ways, initial allocation from the government, carbon market trading, andpurification. By using carbon quotas, firms are required to meet the limitation of carbon emissions by regulations. Tohelp firms make the cost-optimal decision in both short-term and long-term management, this paper focuses on theimpact and trading of carbon quota for emission-depending firms.The short-term optimal production model suits firms less than a year from meeting emission limitation requirements. Itis considered that during this time, firms cannot upgrade production equipment with less carbon emission but can onlysell or buy carbon quotas in the carbon trading market. Furthermore, this paper builds a carbon quota price predictingmodel based on the long-short-term memory neural networks(LSTM) method to help firms develop a better tradingstrategy. In the long term, firms can update their technique to less carbon-emitting production technology. Therefore,a long-term optimal production model is established, and variable purifying levels are discussed. Finally, this papercalculates the optimal production strategy under different restraints of carbon emission.

A carbon credit is a permit to allocate specific carbon emissions and can also be converted into a traded commodity through the carbon trading market (CTM). For government agencies and private enterprises, these carbon credits can be traded on the CTM. Under this trading mechanism, the institutions with low‐carbon emissions can obtain the specific benefits and rewards from fossil fuel consumption reduction, carbon emission reduction, and remaining carbon emissions credits, thereby incentivizing them to reduce greenhouse gas (GHG) emissions and achieve the overall carbon reduction goals. Carbon emissions can be reduced from either power generation ends or high‐level pollution electricity‐consumer ends. Under the schemes of regulated and voluntary markets, the target of carbon emission reduction can be achieved within a foreseeable timeframe by using the power generation proportions adjustment, saving energy on the electricity‐consumer ends, strengthening energy management and efficiency, and increasing renewable energy penetration in the electrical grid. However, power generation significantly has major contributions to carbon dioxide (CO2) and other GHG emissions. For economic dispatch (ED) and carbon emission allocation, this study investigates the ED benefits of power generation proportions adjustment with increasing the generation capacity of natural gas and renewable energy in perspective of power generation end. Four typical scenarios are designed and advanced strategy with different power generation proportions to obtain the fuel cost of various generation units, the carbon emissions of various fuel units, and the benefits of carbon emission reductions, which are used to validate the benefits of increasing the proportions of natural gas generations and renewable energy as decreasing the proportions of oil fuel generations. Considering various scenarios, fuel costs, pollution emissions, and increasing renewable energy, the power generation, carbon emissions, and allowable carbon emissions of various generating units can be estimated by using the swarm intelligence optimization algorithm, such as the particle swarm optimization algorithm (PSOA), which can offer the carbon credit allocation and trading information in the CTM.

Impacts of carbon emissions allowance limitations on carbon price with power generation rights trading in China

As global climate change accelerates, countries worldwide are adopting measures to curb carbon emissions and promote sustainable development. China, a major emitter, has actively implemented carbon reduction policies, with carbon tax and carbon trading markets as key mechanisms. The carbon tax raises the cost of emissions, encouraging enterprises to reduce their emissions, while the carbon trading market enhances the allocation of emission resources through market-driven pricing mechanisms, thereby improving overall reduction efficiency. This study aims to explore the synergistic effect between Chinas carbon tax and carbon trading market, analyzing their interaction in promoting carbon emission reduction and assessing their influence across different industries and regions. Based on a review of relevant literature and data from government carbon emissions statistics, the study examines the synergy between carbon tax and the carbon trading market. The results indicate that the implementation of the carbon tax increases the cost of carbon emissions for enterprises, thus prompting them to adopt more proactive reduction measures while providing stable demand for the carbon trading market. Besides, the carbon trading market improves overall emission reduction efficiency by optimizing the market-driven allocation of carbon allowances. After the carbon tax was implemented, corporate emissions dropped, market activity increased, and price fluctuations signaled emission reduction. In addition, it reveals that the synergistic effect of carbon tax and carbon trading market varies across different industries and regions, suggesting that policy adjustments should be tailored to specific circumstances.

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