Carbon Quota Research Articles

Competitive firms’ low-carbon technology diffusion under pollution regulations: A network-based evolutionary analysis

To investigate the diffusion degree of low-carbon technology in competitive firms and the influence of different pollution regulations, we constructed an evolutionary game model representing three environmental mechanisms: total amount control and trading, carbon tax, and subsidy, within a complex firm network. By analyzing the effects of carbon quotas, tax rates, and subsidy rates, we comprehensively assessed the performance of these mechanisms in terms of diffusion degree, firm profits, consumer surplus, environmental damage, and social welfare. The study results demonstrated distinct outcomes for each environmental mechanism. Under the subsidy mechanism, low-carbon technology exhibited the highest diffusion degree, suggesting its efficacy in promoting widespread adoption. However, it is worth noting that the higher the subsidy, the more environmental pollution it led to, which presents a trade-off between environmental benefits and financial incentives. On the other hand, the carbon tax mechanism resulted in minimal pollution, reflecting its potential as an effective tool for environmental regulation. Finally, the cap-and-trade mechanism emerged as the most favorable option, as it maximized social welfare while effectively addressing environmental concerns.

Carbon emission quotas and a reduction incentive scheme integrating carbon sinks for China's provinces: An equity perspective

Allocation of carbon emission rights, which is fundamental to incentive mechanisms such as quota trading, carbon sink construction, and emission reduction, and related to the development space of some traditional industries, must balance efficiency and equity with economic benefit and environmental protection. We apply the entropy right method and integrate the four principles of fairness, responsibility, efficiency, and security from an equity perspective to analyze the allocation of carbon quotas among China's provinces. We integrated carbon sinks and carbon emission rights into the same accounting system to comprehensively identify surplus space, and use it to propose carbon offset and carbon emission rights trading scheme. An empirical study of China's provinces revealed that the carbon-sink-based allocation scheme achieved compensation from developed provinces with carbon deficits to less-developed provinces with carbon surplus. From an equity perspective, the emission reduction scheme realizes the original intentions of making developed regions take greater responsibility for emission reduction, giving less-developed regions scope for emission reduction and strengthening penalties for excessive carbon emissions. The findings reflect the direct impact of carbon sinks on carbon emission rights allocation and encourage the construction of carbon sinks while contributing to coordinated regional development.

An inter-provincial carbon quota study in China based on the contribution of clean energy to carbon reduction

Energy consumption is the main source of carbon dioxide emissions. Vigorously promoting the development and utilisation of clean energy and the reasonable distribution of carbon amounts between regions is an important measure for carbon emission reduction. In this paper, the geodetector method is used to quantitatively analyse the impact of the development and utilisation of clean energy on China’s overall carbon emissions. And the carbon quota calculated under the three principles of efficiency, responsibility, and comprehensiveness are compared, and a reasonable inter-provincial carbon quota allocation scheme considering the contribution of clean energy carbon reduction is put forward. Research indicates: (1) Among the driving factors studied in this paper, the proportion of clean energy power generation has the greatest impact on carbon emissions. (2) The development and utilisation of clean energy has a strong impact on the carbon quota in low-value regions. (3) The comprehensive principle carbon quota allocation (which takes into responsibility principle reflecting clean energy factors and efficiency principle) is the most reasonable. A carbon quota scheme that reflects the contribution of clean energy to carbon emission reduction is of great significance for advancing the realization of China's regional and national carbon peaking targets.

The impact of carbon quota allocation and low-carbon technology innovation on carbon market effectiveness: a system dynamics analysis.

As the problems of "valuing compliance over trading" and quota over-allocation seriously affect the effectiveness of China's national carbon emission trading (CET) market, the quota auction mechanism will be introduced timely to solve these problems. Since implementing the quota auction means reduced free quotas, regulated enterprises are more motivated to pursue low-carbon technology innovation (L-CTI). On these grounds, by establishing a system dynamics model of the national CET market and designing seven scenarios for simulation analysis, this paper investigates the impact of quota auction and L-CTI on the emission reduction effectiveness and cost effectiveness of the national CET market. The results indicate that for the national CET market, introducing quota auction is conducive to decreasing the CET price and improving its liquidity and emission reduction effectiveness, which is one of the quota allocation mechanisms to improve the CET market effectiveness at present. However, the quota auction will increase the abatement cost and reduce the cost effectiveness. Therefore, to improve the institutional performance of China's CET system, it is necessary to conduct L-CTI to alleviate the increasing abatement cost caused by quota auction, and thus improve the emission reduction effectiveness and cost effectiveness of the national CET market.

Leveraging opportunity of low carbon transition by super-emitter cities in China

Chinese cities are core in the national carbon mitigation and largely affect global decarbonisation initiatives, yet disparities between cities challenge country-wide progress. Low-carbon transition should preferably lead to a convergence of both equity and mitigation targets among cities. Inter-city supply chains that link the production and consumption of cities are a factor in shaping inequality and mitigation but less considered aggregately. Here, we modelled supply chains of 309 Chinese cities for 2012 to quantify carbon footprint inequality, as well as explored a leverage opportunity to achieve an inclusive low-carbon transition. We revealed significant carbon inequalities: the 10 richest cities in China have per capita carbon footprints comparable to the US level, while half of the Chinese cities sit below the global average. Inter-city supply chains in China, which are associated with 80% of carbon emissions, imply substantial carbon leakage risks and also contribute to socioeconomic disparities. However, the significant carbon inequality implies a leveraging opportunity that substantial mitigation can be achieved by 32 super-emitting cities. If the super-emitting cities adopt their differentiated mitigation pathway based on affluence, industrial structure, and role of supply chains, up to 1.4 Gt carbon quota can be created, raising 30% of the projected carbon quota to carbon peak. The additional carbon quota allows the average living standard of the other 60% of Chinese people to reach an upper-middle-income level, highlighting collaborative mechanism at the city level has a great potential to lead to a convergence of both equity and mitigation targets.

Joint Optimal Production Planning in Supply Chains under Diverse Low-Carbon Policies

This paper studies the impact of diverse carbon emission regulations on optimal operation decisions by exploiting the economic production lot model of a multi-manufacturer system in a low-carbon environment. The optimal production planning for multiple enterprises in terms of cost optimization and carbon emission optimization are presented in various scenarios of the fully decentralized system under carbon taxation, cap and trade, and mandatory carbon cap. We prove a unified framework for modeling the scenarios enabled by carbon tax and cap-and-trade policies. Furthermore, the decision vector of the optimal production lot is obtained by analyzing the joint decision scenario based on shared carbon emission caps. We give a comparative analysis of two settings of fully decentralized and carbon quota sharing. The results show that the decision of joint production and stock preparation can reduce the total operational costs of the multi-enterprise system, but the realized carbon emissions may not change or only increase slightly. Our study provides a useful reference for government carbon emission regulation and enterprise operation decision optimization under carbon neutrality and a carbon peak environment.

Subsidy policy and carbon quota mechanism of the Chinese vehicle industry

Subsidy policy and carbon quota mechanism of the Chinese vehicle industry

Design and selection of carbon quota mechanisms from the perspective of carbon trading

AbstractThe research shows that when the initial carbon emission per unit product and the emission reduction cost coefficient achieve a certain combination range, the two carbon quota mechanisms will be effective, and its feasible range will be larger. Further, compared with the carbon quota mechanism based on output, manufacturers and retailers will always increase the sales price and wholesale price of products under the carbon quota mechanism based on emission reduction technology but will reduce the emission reduction per unit product. The government will also reduce its total carbon quota under the carbon quota mechanism based on emission reduction technology.

Technology spillover and incremental cost effects of carbon transfers on optimal carbon quotas in supply chains

A fair and effective allocation of carbon quotas is crucial for China to achieve its “Double Carbon” goals and the effective operation of its carbon trading market. By constructing a differential game model, this study explored the effects of the technology spillovers and incremental costs of carbon transfers on the allocation of carbon quotas under centralised and decentralised decision-making scenarios with the purpose of maximizing social welfare. This paper proposes a cost-sharing contract to coordinate a supply chain for the loss of social welfare under decentralised decision-making. The results show that the effects of spillovers and incremental costs on carbon quota allocation depend upon the enterprises' abatement costs. The suppliers' carbon quotas are negatively correlated with the spillover effects. The incremental cost effects will be more pronounced for suppliers when their abatement costs are high and they could obtain more carbon quotas accordingly. When the manufacturer's abatement costs are low (high), its carbon quotas decrease (increase) with the spillover effects but increase (decrease) with the incremental costs. The cost-sharing contract achieves Pareto improvements based on improved social welfare and increased carbon quotas for both the manufacturer and supplier. Given the effects of carbon transfer on enterprises with different abatement costs, this paper can provide the government with a reference for designing an allocation mechanism for carbon quotas.

Carbon allowance auction design of China's ETS: A comprehensive hierarchical system based on blockchain

This study proposes a blockchain-based optimization framework for carbon allowance allocation auctions. First, the study assesses the status quo of carbon trading, pinpointing barriers, future development trends, and identifying carbon quota auction standards and methods pertinent to the Chinese context. Second, based on China's carbon market needs and the technical characteristics of blockchain, this study reconfigures the functions and responsibilities of each participant and creates a framework for a carbon allowance auction system to optimize the carbon trading process. Third, an algorithm for the carbon allowance auction system is constructed, and the corresponding smart contract is created and simulated. The results illustrate that our proposed system framework facilitates universal carbon allowance auctions, efficiently addresses potential disputes during the auction process, enhances market transparency and credibility, and offers comprehensive privacy protection with flexible information disclosure options for corporations. Blockchain's role in fostering paid distribution and incentivizing participation in the carbon market is further recognized. A blockchain-based carbon trading system safeguards transaction security and efficiency, maintains precise transaction records, and provides automated settlement. Ultimately, this paper presents policy suggestions for the development of a national carbon market in China.

Counterparty Risk Contagion Model of Carbon Quota Based on Asset Price Reduction

Driven by the “double carbon” goal, the sale of financial assets at reduced prices by firms due to carbon emission constraints is bound to aggravate the uncertainty and volatility of carbon trading among firms, and potentially create counterparty risk contagion. In view of this, this paper considers the sensitivity of the transaction of corporate financial assets, the transaction price of carbon quotas, and corporate carbon performance; constructs a network model for the risk contagion of carbon quota counterparties; theoretically discusses the risk formation and infection mechanism of carbon quota counterparties; and calculates and simulates the evolutionary characteristics of the risk contagion of carbon quota counterparties. The main research conclusions are as follows. (1) In the interfirm debt network, the sensitivity to the price of selling the financial asset, the probability of credit risk contagion of carbon quotas among firms, the cumulative proportion of assets sold, and the proportion of rational investors in the financial market exert a decreasing phenomenon on the risk of carbon quota counterparties. In addition, the corporate carbon performance shows a marginal increasing phenomenon. (2) When multiple factors intersect, the proportion of rational investors in the financial market has the greatest influence on the formation of the carbon quota counterparty risk, whereas the effect of corporate carbon performance has the least. Corporate carbon risk awareness has the greatest effect on the risk contagion of carbon quota counterparties, whereas the trading price of the carbon quota has the least influence. In addition, the total score of the interfirm assessment has a great impact on the trend and range of the risk contagion of carbon quota counterparties. (3) Corporate carbon risk awareness and the carbon quota trading price have a marginally decreasing effect on the risk contagion of carbon quota counterparties, and corporate carbon performance and the total score of interfirm assessment have a marginally increasing effect. This study has important theoretical and practical significance for preventing interfirm counterparty risk contagion under the double carbon target.

Multi-objective optimal scheduling of an integrated energy system under the multi-time scale ladder-type carbon trading mechanism

Given the ladder-type carbon tax in the carbon quota market is a relatively macroscopic large-time scale concept, and the volatility and uncertainty of new energy generation output and the load, it is currently difficult to accurately predict and control carbon trading cost in the multi-time scale scheduling of integrated energy system (IES), there is a lack of in-depth research on dynamic adjustment and ground implementation in small time scale. To address the challenges of these problems, this paper proposes a multi-objective optimal scheduling model for IES considering the multi-timescale ladder-type carbon trading mechanism. Optimization models and algorithms were developed for day-ahead, intraday and real-time scheduling time scales, enhancing scheduling accuracy and usability. Day-ahead scheduling minimizes comprehensive cost and pollutant emissions while considering the ladder-type carbon trading mechanism; intraday scheduling dynamically adjusts carbon trading cost functions based on day-ahead results and equipment output; and real-time scheduling establishes new carbon trading ladder-type cost functions according to intraday results and emissions. A novel particle swarm optimization algorithm was introduced, integrating uncertainty models for wind, photovoltaic power, and load, along with electric vehicle charging strategies. The multi-time scale model in ladder-type carbon trading exhibits approximately 5% more economic advantage and 2% more environmental benefit.

Operational research models for green technology cross‐licensing with known carbon quota trading prices

AbstractGreen finance contributes significantly to the openness and transparency of carbon quota trading prices, which is conducive to the development of green technology innovation. With known carbon quota trading prices, we construct game‐based operational research models to analyze fixed‐fee and mixed‐fee cross‐licensing strategies for green technologies between two competing firms under the cap‐and‐trade policy. We compare the equilibrium outcomes of no‐licensing, fixed‐fee, and mixed‐fee cross‐licensing strategies. The findings reveal that product pricing under the fixed‐fee cross‐licensing strategy is beneficial to consumers. The mixed‐fee cross‐licensing strategy is optimal in terms of firms' total profits. When the degree of product substitutions is large and the improvement in carbon emissions is small, firms are more inclined to the no‐licensing strategy. We further introduce the revenue‐sharing contract, which can extend the Pareto improvement domain and improve the performance of green technology cross‐licensing strategies.

CO2 Emission Allocation for Urban Public Buildings Considering Efficiency and Equity: An Application at the Provincial Level in China

China is currently recognized as the leading global energy consumer and CO2 emitter. A significant amount of carbon emissions can be attributed to urban public buildings. Establishing an equitable and efficient carbon emission allocation mechanism is a crucial step to meeting the ambitious targets in China’s 2030 carbon peak plan. In this study, we estimate the total amount of CO2 emissions from urban public buildings by 2030 and propose a preliminary scheme of carbon quota assignment for each province. By means of applying the zero-sum gains data envelopment analysis (ZSG-DEA) model, the carbon emission quotas allocation of urban public buildings in China’s 30 provinces is proposed, and the corresponding pressure to reduce provincial carbon emissions is analyzed. The results indicate that Qinghai has the lowest carbon emission rate (0.01%) for urban public buildings, while Guangdong has the highest (9.06%). Among the provinces, Jiangsu, Jiangxi, and Tianjin face the least pressure in reducing carbon emissions from urban public buildings. On the other hand, Hebei, Beijing, and Anhui are under great pressure to decrease carbon emissions. Notably, Hebei is predicted to have the highest emission reduction requirement of 95.66 million tons. In terms of pressures on carbon emissions reduction for urban public buildings, Jiangsu, Jiangxi, and Tianjin exhibit the least pressure. Hebei, Beijing, and Anhui are facing intense pressure to decrease carbon emissions. These findings offer policymakers valuable insights into developing a fair and efficient carbon allowance allocation strategy, while also contributing to China’s efforts to mitigate carbon emissions and combat climate change.

How does a scarcer allowance remake the carbon market? An evolutionary game analysis from the perspective of stakeholders

The carbon market has been playing an increasingly important role in mitigating carbon emissions. However, with the tightening of the carbon allowance, where the carbon market will evolve is still unclear. Abstracting three agents—Government, Carbon-supplier(‘CS’), Carbon-buyer(‘CB’), this paper intends to investigate the operation mechanism of carbon market from the perspective of the stakeholders. Based on the simulation analysis, it is suggested that: 1) the carbon market in China may become a major “seller's market” when carbon quota experienced dramatic reduction; 2) when the carbon price is constant, CS with excessive carbon productivity will crowd out and exploit CB in the carbon market competition; 3) strict administrative penalties and information disclosure would help promote proactive participation of CS and CB in the carbon market; and 4) the interaction between CS and CB in different strategic scenarios is influenced by the carbon price and the coefficient of demand variation for carbon quota. In contrast with previous studies, this paper has uncovered a dynamic strategic evolution mechanisms of stakeholders in the carbon market at the micro-level, contributing to carbon market governance and providing stakeholders with tailor-made climate policy tools and strategic choices.

A Bi-objective cap-and-trade model for minimising environmental impact in closed-loop supply chains

A Closed-Loop Supply Chain (CLSC) is a complex network with unique environmental features and attributes that requires specific managerial policies and strategies. Quantitative models can provide a solid basis for these policies and strategies. This study expands the work of Shoaeinaeini et al. (2021) on Green Supply Chain Management. We propose a bi-objective facility location, demand allocation, and pricing model for CLSC networks. The proposed model considers two conflicting objective functions: maximising profits and minimising emissions. We show consumer environmental awareness can predict the products’ rate of return and determine a more suitable price for new products and the acquisition price for used products. The cap-and-trade policy has been implemented at its fullest potential, allowing the trading of carbon quotas. Therefore, companies may decide to produce less to sell more quotas or vice-versa, effectively picking the most profitable option. The model is solved and tested with the commercial solver BARON. The model effectively shows the trade-off between generating profits and emission reduction. Companies are able to turn a profit while abiding by the government’s intention of reducing emissions. The comparison with a single-objective version of the model highlights that the concurrent optimisation of economic and environmental objectives yields better results. The acquisition price of used products is a value worthy of monitoring. The government should focus on policies to assist the reverse flow of used products.

Carbon quota allocation modeling framework in the automotive industry based on repeated game theory: A case study of ten Chinese automotive enterprises

Carbon quota management system is a long-term effective mechanism to promote the sustainable development of automotive industry. However, issues such as the total amount and allocation mechanism of carbon quotas hinder countries' implementation of carbon quota policies in the automotive industry. To address these issues, this study uses the GREET model and system dynamics model to predict carbon emissions in the automotive industry and sets the total carbon quota for China's automotive industry. Furthermore, based on the ZSG-DEA model and Gini coefficient model, this study applies repeated game theory to propose a carbon quota allocation modeling framework for the automotive industry. The results show that the proposed allocation modeling framework achieves a balance between equity and efficiency while taking into account the interests of both the government and enterprises, and achieves an equitable allocation of carbon quotas among 10 representative automotive enterprises. This study can provide reference for the design of carbon quota management system in the automobile industry.

Optimal production with carbon trading market in China

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.

Study on Low-Carbon Technology Investment Strategies for High Energy-Consuming Enterprises under the Health Co-Benefits of Carbon Emission Reduction

The excessive use of fossil energy has led to a yearly increase in carbon dioxide and atmospheric pollutant emissions, and climate change has become increasingly prominent, seriously affecting people’s daily lives and physical and mental health. According to statistics, rising temperatures and extreme weather phenomena due to climate change have led to a 68% increase in heat-related deaths today compared to the period between 2000 and 2004, and a 61% increase in the number of days humans face high fire risks in the same period. Currently, in order to achieve synergistic economic and environmental development and enhance the health co-benefits of carbon emission reduction, it is urgent for high-energy-consuming enterprises to make sound low-carbon technology investment decisions. Therefore, in this paper, under the carbon quota and trading policy and carbon tax policy, and considering the existence of low-carbon preferences of consumers, the financial constraints of upstream high energy-consuming enterprises and sufficient funds of downstream retailers, a low-carbon technology investment decision model under intra-supply chain financing is constructed using Stackelberg game theory. Moreover, by applying the inverse induction method, we solve the optimal decision of low-carbon technology investment with three different subsidy methods: no subsidy, cost subsidy and product subsidy. Finally, the validity of the model is verified by numerical simulation, and the effects of different influencing factors on low-carbon technology investment are analyzed. The results show that: (1) the reasonable formulation of carbon trading price, carbon tax rate, cost subsidy ratio and product subsidy coefficient are important factors to promote enterprises’ low-carbon technology investment; (2) the improvement of consumers’ low-carbon preference level and the reduction in repayment interest rate can promote enterprises’ investment; (3) compared with no subsidy, cost subsidy and product subsidy can effectively improve enterprises’ low-carbon technology investment enthusiasm, and the effect of product subsidy is better than that of cost subsidy. The effect of product subsidies is better than that of cost subsidies. This paper aims to provide suggestions for the government to refine low-carbon technology investment incentive policies and for enterprises to optimize low-carbon technology investment decisions, so as to enhance the healthy co-benefits of carbon emission reduction and achieve green and sustainable economic development.

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.