Allocation Of Carbon Emission Allowances Research Articles

A Novel Centralized Allocation Data Envelopment Analysis Model for Carbon Emission Allocation Under a Heterogeneous Abatement Cost: Application Within the Chinese Industrial Sector

This paper presents a mathematical approach to analyzing carbon abatement costs and the allocation of carbon emission allowances in China’s industrial sectors. We utilize input–output data from 30 Chinese provinces between 2009 and 2018 to estimate carbon abatement costs by applying the slack-based measure (SBM) efficiency model and its dual form. The SBM model captures inefficiencies and offers a rigorous framework for measuring abatement costs. Using these costs, we develop a centralized allocation data envelopment analysis (DEA) model, which maximizes sectoral benefits through optimal reallocation. This DEA model is formalized as a linear programming problem, with the aim of determining the efficient allocations of carbon allowances while maintaining the system’s economic productivity. Furthermore, we construct intertemporal, interregional, and spatiotemporal allocation DEA models to examine the dynamics of carbon emission allowance allocation over time, space, and combined spatiotemporal dimensions. These models offer insights into the efficiency of carbon markets under varying conditions. Our proposed new mathematical formulations reveal optimal allocation strategies that can balance emission reductions with industrial productivity. This study also provides novel mathematical frameworks for analyzing the carbon allowance distribution and contributions to both the theory and application of mathematical optimization in environmental policy design. Our findings reveal that China’s industrial carbon abatement costs exhibit significant interprovincial and regional differences. Developed provinces with higher levels of industrial development have higher carbon abatement costs, while provinces with less-developed industrial sectors have lower costs. Under the interregional allocation scenario of carbon emission allowances that consider abatement costs, developed provinces have smaller industrial carbon emission reductions, whereas less-developed provinces have larger reductions. In the intertemporal allocation scenario, provinces with larger industrial economies face greater emission reduction tasks. Under the combined interregional and intertemporal allocation scenario, industrial sectors in coastal developed provinces have lower carbon emission reductions, while those in inland less-developed provinces have higher reductions, mirroring the spatial allocation results of carbon emission allowances.

Cooperative operation for multiple virtual power plants considering energy-carbon trading: A Nash bargaining model

With the development of the energy and carbon markets, it has become a trend for multiple virtual power plants (MVPP) that aggregate distributed resources from different regions to participate in market trading through cooperative operation. In order to study the energy-carbon interactions between VPPs and the supply-demand interactions for MVPP and users, this paper introduces a load aggregator (LA) and establishes a cooperative alliance consisting of MVPP and LA. Firstly, a carbon emission allowance allocation and transaction mechanism for MVPP is proposed based on the modified Shapley value method, which considers the impact of energy interactions within the alliance on the carbon emissions. Then, a cooperation model for the MVPP-LA alliance is established based on Nash bargaining theory, and it is decomposed into two subproblems of the maximal alliance benefits and the optimal benefit distribution. In terms of benefit distribution, this paper modifies the bargaining mechanism based on the contribution of each VPP to the alliance benefit. A dynamic penalty factor-based alternating direction method of multipliers (DP-ADMM) is used to solve the two subproblems in a distributed manner. Finally, the validity of the proposed trading mechanism, allocation method and solution algorithm are verified through several cases.

Analysis and Optimization Suggestions on Allowance Allocation Methods of the Power Industry in the Carbon Market

The initial allocation of carbon emission allowances is an important component of the carbon market. An equitable, scientific, and operational quota allocation method and quota management system are the cornerstones for ensuring the healthy operation of the carbon market. Owing to the high emissions, simple process, and good data foundation, the pilot and national carbon market in China have initially included the power industry in allowance management and introduced a common and differentiated quota allocation method. In this study, we compared the allowance allocation methods for the power industry and summarized the methods for key issues such as unit classification, correction factor, product measurement, and quota carry-over. We observed that there were concerns, such as lagging issuance time, lack of carry-over provisions, lack of regulatory mechanisms, and imperfect methods, in the first performance cycle of the national carbon market quota allocation. We improved the allowance allocation system for the power industry in the carbon market from the methodological and management perspectives, including establishing a total allowance constraint, clarifying quota carry-over provisions, improving the quota verification method for co-firing units, optimizing correction factors' selection, and introducing a compensatory distribution system in a timely manner.

Optimization of Initial Carbon Emission Allowance Allocation in Industrial Industries: A Case Study of Zhejiang Province, China

The construction of carbon market is one of the important means for China to reach the goal of carbon peaking and carbon neutrality, and the allocation of initial carbon emission right quota is the key link in carbon market transaction. At present, the historical method is the commonly used allocation method of initial carbon emission rights in China, and the use of this method is unfair and inefficient. Therefore, this paper proposes an allocation optimization model, selects a number of indicators, and optimizes the allocation of initial carbon emission rights based on the hierarchical analysis method and entropy weight method. Example analysis shows that the allocation optimization model helps to share the carbon emission responsibility and improve the allocation efficiency, realizes the optimal allocation of initial carbon emission rights among industrial sectors, and provides support for the emission reduction of industrial sectors.

An integrated zero-sum game and data envelopment analysis model for efficiency analysis and regional carbon emission allocation

As the global economic environment changes, the concept of green and sustainable development has become the international community’s consensus. As a participant in the worldwide emission reduction plan, China is also under great pressure to reduce carbon emissions. As an example, this study constructs an optimal scheme for regional carbon emission allowance allocation in Hunan Province, China. We first forecast the total carbon emissions in 2030 for each city, state, and major industry in Hunan Province through a scenario and then innovatively use the mass function allocation theory in marketing to sort out the logical ideas of the optimization model. More importantly, we combine the zero-sum game theory to build the zero-sum game-data envelopment analysis model to continuously reallocate the carbon emission allowances of each city and state and major industries in Hunan Province until the optimal allocation scheme is reached. From the perspective of each city and state, the initial carbon emission efficiency level of fourteen cities in Hunan is high, but there are still some differences. From the perspective of industries, the initial efficiency of carbon emission of six major industries in Hunan is lower, and the difference in efficiency values is evident.

Carbon emission allowance allocation based on a bi-level multi-objective model in maritime shipping

To mitigate carbon emissions from maritime shipping, this study investigates the strategies and performance of allocating carbon emission allowances (CEAs) with the cap-and-trade mechanism among shipping companies. Using a bi-level model solved by the multi-objective particle swarm optimization algorithm based on Pareto solution set, the interactions between decisions of the government and shipping companies are well characterized. The results of the benchmark scenario indicate that all shipping companies’ optimal carbon emissions decrease annually during the planning period, and a larger company usually exhibits a better emission reduction performance. However, economic benefits of shipping companies and the society display an annually declining trend due to additional carbon emission reduction costs. The sensitivity analysis demonstrates that the decreasing carbon prices lead to more emissions, while the optimal total carbon emissions decrease as carbon reduction costs increase. These findings create implications for multiple stakeholders to formulate their own carbon emissions mitigation strategies under the cap-and-trade mechanism.

Greenhouse gas emission indicators, energy consumption efficiency, and optimal carbon emission allowance allocation of the EU countries in 2030

The 2030 Climate Target Plan of the European Union (EU) has set a goal of reducing carbon emissions by 55%, but while carbon emissions have attracted the attention of scholars, past research has two shortcomings. Studies have focused on carbon emission allocation that occurred in the past, but seldom forecasted carbon emission allocation in the future. Moreover, most research has focused on carbon dioxide emissions with other greenhouse gases receiving less attention. To fill this gap in the literature, this research has two contributions. First, it uses the entropy method to design greenhouse gas emission indicators and to evaluate the weight of each greenhouse gas in carbon emissions. Second, this study applies data envelopment analysis to predict the optimal carbon emission allocation for the EU in 2030. This paper presents the following results. (1) Energy consumption efficiency and carbon emission efficiency for Denmark, Greece, Ireland, Luxembourg, Malta, Sweden, and United Kingdom are the best. (2) Non-renewable energy consumption efficiency in most countries needs to be improved.

Allocation of provincial carbon emission allowances under China's 2030 carbon peak target: A dynamic multi-criteria decision analysis method

To balance China's socio-economic development and emission reduction goals, a fair and effective provincial carbon emission allowance (CEA) allocation is necessary. By considering the implied emissions of inter-provincial power transfer, this study designed a dynamic multi-criteria CEA allocation model based on four criteria-egalitarianism, historical responsibility, emission reduction capability, and emission efficiency-to calculate the provincial CEA year by year before 2030. The efficiency and fairness of the CEA scheme were evaluated through the Data envelopment analysis (DEA) model, the environmental Gini coefficient, and its grouped decomposition method. The national overall CEA, the results revealed, will peak during the 15th Five-Year Plan (FYP) period. Specifically, the CEA for eastern and central China is expected to peak first during the 14th FYP period, while the northeast region's CEA remains stable and that of the western region continues to grow. Provinces with high carbon emissions, high carbon emission intensity and high per capita carbon emissions and provinces with particularly high carbon emissions will face great pressure regarding emission reduction, and their CEA peaks are expected to arrive before 2025 and 2030 respectively. The CEA of the less-developed provinces will have a surplus. In terms of time, the high-emission provinces face greater emission reduction pressure during the 15th FYP period than during the 14th FYP period. In terms of scheme evaluation, the scheme achieved a double improvement in fairness and efficiency compared with the current actual emissions of various provinces. Reducing the differences in per capita CEA between the different regions and provinces in the western and eastern regions will help improve the scheme's fairness. This study overcomes the existing researches' shortcomings on the large differences in the distribution of emission reduction pressures in key provinces and is more feasible in practice.

A comparative analysis of China's provincial carbon emission allowances allocation schemes by 2030: A resource misallocation perspective

Carbon emission allowance (CEA) has become a scarce resource against global climate change. Hence, the CEA allocation scheme is critical to improving its utilization efficiency and balancing regional development. However, most of the existing literature mainly focused on the formulation of allocation schemes but ignored the examination of CEA misallocation, which may damage productivity and regional development. This study intends to conduct a comparative analysis of Chinese provincial CEA allocation schemes by 2030 from a perspective of resource misallocation. For this purpose, 15 provincial CEA allocation schemes by 2030 based on the indicator method are developed first. Then a CEA misallocation index deriving from the extended Gini coefficient is proposed to examine the CEA misallocation of proposed schemes. Finally, an empirical analysis of China's provincial CEA allocation by 2030 is conducted. The results indicate that provincial CEA misallocation indeed occurs under the proposed allocation schemes with the CEA misallocation index ranging from 0.209 to 0.311, and the scheme based upon the efficiency principle has a relatively minimum misallocation index at 0.209. Furthermore, CEA misallocation is related to the carbon intensity reduction rate, and the scheme based on the efficiency principle could further achieve optimal CEA allocation when the carbon intensity reduction rate decreases. We suggest relevant decision-makers focus on the efficiency principle when developing a provincial CEA allocation scheme as it has strength in avoiding CEA misallocation.

An Optimization Study of Provincial Carbon Emission Allowance Allocation in China Based on an Improved Dynamic Zero-Sum-Gains Slacks-Based-Measure Model

In order to achieve its 2030 carbon emission peak target, China needs to adjust and allocate energy consumption and initial carbon emission allowances for each province in a phased and planned manner. Thus, this study applied an improved dynamic undesirable zero-sum-gains slacks-based-measure (ZSG-SBM) model to evaluate provincial CO2 emission reduction scenarios and energy allocation for 2015–2019 and calculate the optimal allocation values of carbon emission allowances for each province in 2030. The results showed that China’s allocation efficiency values for total energy exhibited rising and then declining trends during 2015–2019 and that most input–output term efficiency values had room for improvement. Furthermore, after four adjustment iterations of the improved dynamic undesirable ZSG-SBM model, the modeled China achieved optimal carbon emission efficiency for the whole country. In the final model, 19 provinces were allowed to increase their carbon emissions in 2030, while the remaining 11 provinces needed to reduce their emissions. The findings of this paper can help regulators to establish fairer and more effective policy solutions to promote regional synergistic emission reduction, achieve the national goal of peak total carbon emissions, and promote the green, coordinated, and sustainable development of China’s economy.

Auction design for the allocation of carbon emission allowances to supply chains via multi-agent-based model and Q-learning

Auction design for the allocation of carbon emission allowances to supply chains via multi-agent-based model and Q-learning

How can national ETS affect carbon emissions and abatement costs? Evidence from the dual goals proposed by China's NDCs

China has committed to goals of reducing its carbon intensity by 60%–65% in 2030 above the 2005 levels and peaking its carbon emissions by latest 2030. While a unified national emission trading scheme (ETS) has been recognized as the crucial instrument to fulfill these ambitious dual goals, its potential performance remains underexplored. This paper quantifies China's need for emission reduction under the dual goals in 2030 by setting three scenarios for peak emissions. Four initial allocation schemes of carbon emission allowance (CEA) are compared according to the emission abatement costs (EACs) of China and its 30 provinces. By estimating the provincial marginal abatement cost curves, China's ETS is simulated through a nonlinear programming aimed at minimizing its total EACs. We find that in achieving the dual goals it makes economic sense to operationalize the ETS that would reduce China's EACs by 61.41%–80.33% in 2016–2030, at a carbon price of 394.55–425.75 RMB per ton CO2. Peaking China's emissions in 2030 is the preferred choice that will trigger the largest GDP in 2016–2030. The historical responsibility scheme is recommended for the CEA allocation because of the lowest initial EACs without ETS. To allow more room for economic growth after China peaks emissions, there is a need for overfulfilling the goal of carbon intensity reduction by 2030, which is consistent with China's latest climate mitigation targets. This research not only highlights the role of ETS in realizing China's dual goals, but provides a scientific framework for evaluating the environmental policies towards multiple goals in a cost-effective manner.

Effects of European emission unit allowance auctions on corporate profitability

During Phase 3 of the EU Emission Trading System (ETS), to remedy the so-called windfall profits obtained by companies that benefited from the free allocation of emission permits, the EU introduced an auction-based method for the allocation of carbon emission allowances. We estimate the effect on firms' profits from participating in auctions during Phase 3 of the EU ETS using a propensity score matching approach. The work shows that the introduction of the new market mechanism for allocating carbon emission allowances has no significant effect on corporate profits, whatever the measure of profitability used. From a policy standpoint, this result seems to suggest that this new allocation mechanism might fail to improve the incentives for companies to increase their production cost efficiency or to invest in breakthrough technologies that reduce CO2. The rather flat auction price trend seems to support this conclusion.

Windfall profits in the power sector during phase III of the EU ETS: Interplay and effects of renewables and carbon prices

Abstract Since power utilities were originally grandfathered into the EU ETS by way of a free allocation of carbon emission allowances (EUA), the issue of windfall profits accruing to producers with carbon-intensive generation portfolios has been the subject of critical analysis. One of the chief aims of the switch to a predominantly auction-based allocation system at the onset of Phase III of the EU ETS was to negate the incidence of windfall profits. The following analysis examines the merits of this policy aim. Drawing on economic theory of power markets, a linear optimisation model covering the electricity market of the EU member states is deployed to investigate this question. Scenarios reflecting developments over a medium-term horizon (10 years) are developed, with which carbon prices are endogenously determined. Their effects on the contribution margins of producers in the member states are subsequently evaluated. The overall findings indicate that the incidence of windfall profits in the power sector remains prevalent in the overwhelming majority of EU countries. The analysis suggests that the carbon intensiveness of the respective generation fleet is not the deciding factor as to whether producers earn windfall profits but rather the fundamental generation structure of the power plant fleet. The results raise questions about the capacity of the current EU ETS regime to provide the desired decarbonising effect on power producers’ generation portfolios in European power markets.

Analysis of driving factors and allocation of carbon emission allowance in China

China's “13th Five-Year Plan” proposes that carbon emissions per unit of GDP be reduced by 18% from their 2015 levels. In this context, the present study uses grey relational analysis to explore the correlation degree between carbon emissions and economic, energy and population effects. This study also quantitatively analyzes the contribution rate of each driving factor by using logarithmic mean Divisia index. Results show that per capita GDP and energy consumption per unit of GDP are the key factors that lead to changes in carbon emissions. Then, the input-oriented BCC model in data envelopment analysis (DEA) is used to evaluate the efficiency of the primary carbon emission allowance allocation scheme in the “13th Five-Year Plan”. The results show that the average score of technical efficiencies is only 0.7409. Finally, the zero-sum-gains DEA model is used to adjust and optimize the scheme under the premise of constant total carbon emissions. Thereafter, a scientific carbon-emission allowance allocation scheme is proposed. We verified that the optimal scheme can ensure the compatibility of the carbon emission allowances of provincial-level administrative regions with their economy, energy, and population from the perspective of efficiency.

How can China achieve its Intended Nationally Determined Contributions by 2030? A multi-criteria allocation of China’s carbon emission allowance

Accelerating global warming has suggested the importance of controlling greenhouse gas emissions associated with human activities. In striving to fulfill the Paris Agreement, China has announced its Intended Nationally Determined Contributions (INDCs) aimed at reducing its carbon dioxide (CO2) emission intensity by 60–65% in 2030 against the level of 2005. However, China’s INDCs cannot be fulfilled without formulating appropriate schemes for the allocation of carbon emission allowance (CEA) at sub-national scales. To help close the gap in our knowledge, this paper starts with measuring the overall CEA of China by 2030, and then proposes a science-based scheme for CEA allocation by developing an improved zero sum gains-data envelopment analysis (ZSG-DEA) model. It demonstrates that the final CEA of some northern provinces can be cut down as compared to their initial shares and, conversely, most southern provinces experience an increase in their CEA. Comparing the final share of CEA by province with current carbon emissions, we observe that provinces with abundant energy reserves, such as Shanxi, Inner Mongolia and Shaanxi, tend to be operating in a state of overshoot in terms of space for carbon emissions (SCE). In contrast, there remains SCE when it comes to Guangdong, Hunan, Fujian, etc. The remaining provinces, such as Heilongjiang, Hebei and Ningxia, are close to the break-even point. In view of the differing SCE of individual provinces, common but differentiated policies for CO2 emission control would be the key to achieving China’s INDCs. The research findings lay a scientific basis for the Chinese government to make its INDCs come true through inter-provincial collaboration on emission reduction, but also serve as a reference for fueling further scientific discussions and development of schemes for the allocation of responsibility for carbon emissions at multiple scales within and beyond China.

Carbon emission allowance allocation with a mixed mechanism in air passenger transport

Air passenger transport carbon emissions have become a great challenge for both governments and airlines because of rapid developments in the aviation industry in recent decades. In this paper, a mixed mechanism composed of a cap-and-trade mechanism and a carbon tax mechanism is developed to assist governments in allocating carbon emission allowances to airlines operating on the routes. Combined this mixed mechanism with an equilibrium strategy, a bi-level multi-objective model is proposed for an air passenger transport carbon emission allowance allocation problem, in which a government is considered as a leader and the airlines as the followers. An interactive solution approach integrating a genetic algorithm and an interactive evolutionary mechanism is designed to search for satisfactory solutions of the proposed model. A case study is then presented to show its practicality and efficiency in mitigating carbon emissions. Sensitivity analyses under different tradable and taxable levels are also conducted, which can give the government insights as to the tradeoffs between lowering carbon intensity and improving airlines' operations. The computational results demonstrate that the mixed mechanism can assist greatly in carbon emission mitigation for air passenger transport and therefore, it should be established as part of air passenger transport carbon emission policies.

Forecasting the Allocation Ratio of Carbon Emission Allowance Currency for 2020 and 2030 in China

Many countries and scholars have used various strategies to improve and optimize the allocation ratios for carbon emission allowances. This issue is more urgent for China due to the uneven development across the country. This paper proposes a new method that divides low-carbon economy development processes into two separate periods: from 2020 to 2029 and from 2030 to 2050. These two periods have unique requirements and emissions reduction potential; therefore, they must involve different allocation methods, so that reduction behaviors do not stall the development of regional low-carbon economies. During the first period, a more deterministic economic development approach for the carbon emission allowance allocation ratio should be used. During the second period, more adaptive and optimized policy guidance should be employed. We developed a low-carbon economy index evaluation system using the entropy weight method to measure information filtering levels. We conducted vector autoregressive correlation tests, consulted 60 experts for the fuzzy analytic hierarchy process, and we conducted max-min standardized data processing tests. This article presents first- and second-period carbon emission allowance models in combination with a low-carbon economy index evaluation system. Finally, we forecast reasonable carbon emission allowance allocation ratios for China for the periods starting in 2020 and 2030. A good allocation ratio for the carbon emission allowance can help boost China’s economic development and help the country reach its energy conservation and emissions reduction goals.

Carbon emission allowance allocation with cap and trade mechanism in air passenger transport

With the rapid development of the aviation industry over the last decade, carbon emissions in air passenger transport have become an increasing concern. By combining the equilibrium strategy with a cap and trade mechanism, this paper proposes a bi-level multi-objective model for carbon emission allowance allocations in air passenger transport, in which a government and airlines are considered as the leader and follower decision makers respectively. Compared with previous studies, this model has the ability to describe the interactions of multiple stakeholders and balance their conflicts. To solve the proposed model, a solution method which integrates an interactive evolutionary mechanism and a fuzzy logic controlled genetic algorithm is developed. Then a numerical example is provided to demonstrate the practical applicability and effectiveness of the method for carbon emission mitigation. Results show that the cap and trade mechanism plays a vital role in mitigating air passenger transport carbon emissions and thus it should be effectively applied to air passenger transport. Results of carbon emission allowance allocations also indicate that the proposed method can provide efficient ways of mitigating carbon emissions for air passenger transport, and therefore assisting decision makers in formulating relevant strategies under multiple scenarios.

Carbon emissions and stock returns: Evidence from the EU Emissions Trading Scheme

Abstract This paper provides an empirical investigation of the effect of the European Union’s Emissions Trading Scheme on German stock returns. We find that, during the first few years of the scheme, firms that received free carbon emission allowances on average significantly outperformed firms that did not. This suggests the presence of a large and statistically significant “carbon premium,” which is mainly explained by the higher cash flows due to the free allocation of carbon emission allowances. A carbon risk factor can also explain part of the cross-sectional variation of stock returns as firms with high carbon emissions have higher exposure to carbon risk and exhibit higher expected returns.