Carbon Trading Scheme Research Articles

A review of policy levers to reduce meat production and consumption

It is increasingly apparent that we require a substantial reduction in animal production and consumption for the sake of the environment and public health. In this paper, we conducted a systematic review to explore the policy levers available for governments to reduce animal farming and the consumption of meat. The policy levers generated by the review are categorised by four main types of interventions: Financial measures, Command- and-control, Informational, and Behavioural. First, we explore four financial measures: taxes on meat is the most-studied intervention, and the least publicly accepted in polling, sometimes being implemented indirectly via measures such as carbon taxes or rescinding VAT exemptions; subsidies for animal product alternatives are considered as a more publicly acceptable alternative approach, and would reduce long-term demand for meat by making alternatives more competitive; agricultural carbon trading schemes are discussed, and may represent a politically feasible way to hold livestock producers accountable for negative externalities; and buyouts of animal farms can be an impactful way to compensate producers to leave the industry, but must be done with care to avoid unintended social and market consequences. Second, we explore two command-and-control measures: regulating animal production with standards such as animal welfare requirements and health and safety rights for agricultural workers is amongst the most well-supported policies, and is an impactful way to ensure minimum standards of production are met; however, restrictions on animal consumption, such as meat–free days in public catering, are less publicly accepted. Third, we discuss three informational measures: food product labels, such as animal welfare or environmental impact labels, fulfil consumers’ expectations to have this information, and although there is limited evidence that they impact consumer behaviour directly, such labels may nonetheless incentivise producers to competitively improve; likewise, national dietary guidelines appear to have little direct impact on food choices, but can impact other institutions such as schools and medical institutions; policies on information campaigns can help or hurt meat reduction efforts, with some jurisdictions prohibiting meat advertisements, while others spend millions on campaigns to promote meat consumption. Fourth, we explore a range of behavioural measures which could be implemented in public catering settings and/or incentivised in food service, including presentation and positioning of meat- and plant-based dishes, and altering the food options on offer – we find that adding more high-quality plant-based options to menus and presenting these options as the default wherever the format allows are highly impactful and tractable behavioural policies that could reduce meat consumption. Informational and behavioural measures can complement traditional fiscal and command-and-control measures to reduce animal production and consumption. We discuss the implications for researchers and policymakers.

Can carbon market efficiency promote green technology innovation for Chinese companies?

The carbon trading scheme is a major institutional innovation for China to promote green and low-carbon economic development. This paper studies the relationship between the carbon market efficiency and enterprises' green technology innovations. First, we assess the efficiency of China's pilot carbon markets using the entropy-based TOPSIS model. Then, we adopt a continuous multi-period difference-in-differences model to explore the effects of carbon market efficiency on firms' green technological innovation. In addition, we analyze the heterogeneous effects of carbon market efficiency with regard to green patent types, industry types, and enterprise ownership. Finally, we examine how carbon market efficiency impacts firms' green innovation. We find that carbon market efficiency can increase enterprises' green patent applications, but the effect is limited. Carbon market efficiency has no discernible impact on green invention patents; it can only enhance green utility model patents. This phenomenon is more prominent in low-energy-consuming industries and private enterprises. We document that carbon market efficiency can enhance enterprises' R&D intensity and policy subsidies, thereby boosting green technology innovation. Our findings have important implications for improving the carbon market efficiency and firms' green technology innovation.

The Efficiency of China’s Carbon Trading Schemes: A Tale of Seven Pilot Markets

The Efficiency of China’s Carbon Trading Schemes: A Tale of Seven Pilot Markets

Low-carbon optimal scheduling of an integrated electricity, heat-and-gas energy system considering a biomass gas and carbon capture power plant

Abstract In light of enhancing the extraction level of biomass energy and rectifying the efficiency of integrated energy system (IES) operations in the backdrop of the “ twin carbon” policy, we present an enhanced scheduling methodology for IES incorporating biomass gas and carbon absorption power plants, addressing the constraints of linear carbon trading. Initially, an organizational blueprint for the combined exploitation of biomass-laden gas, electricity-to-gas, and carbon absorption power plants is established. Secondly, we devise a ladder-like configuration of carbon trading mechanisms to counterbalance the inadequacies of standard persistent carbon trading schemes. Subsequently, this advanced form of carbon trading is incorporated into the IES framework and is optimized using the ultimate goal of minimizing system expenditures. Lastly, evaluations across diverse scenarios demonstrate that the proposed sequential carbon trading significantly enhances the economic viability of the system, and the accompanying simulation corroborates the validity of our proposed model.

Considering the Tiered Low-Carbon Optimal Dispatching of Multi-Integrated Energy Microgrid with P2G-CCS

The paper addresses the overlooked interaction between power-to-gas (P2G) devices and carbon capture and storage (CCS) equipment, along with the stepwise carbon trading mechanism in the context of current multi-park integrated energy microgrids (IEMGs). Additionally, it covers the economic and coordinated low-carbon operation issues in multi-park IEMGs under the carbon trading system. It proposes a multi-park IEMG low-carbon operation strategy based on the synchronous Alternating Direction Method of Multipliers (ADMM) algorithm. The algorithm first enables the distribution of cost relationships among multi-park IEMGs. Then, using a method that combines a CCS device with a P2G unit in line with the tiered carbon trading scheme, it expands on the model of single IEMGs managing thermal, electrical, and refrigeration energy. Finally, the comparison of simulation cases proves that the proposed strategy significantly reduces the external energy dependence while keeping the total cost of the users unchanged, and the cost of interaction with the external grid is reduced by 56.64%, the gas cost is reduced by 27.78%, and the carbon emission cost is reduced by 29.54% by joining the stepped carbon trading mechanism.

Impact of policy interventions on low‐carbon technology innovation diffusion in supply networks

AbstractThe promotion of sustainability and innovation in the current dynamic landscape of global industry in the context of climate change has become imperative. This research paper explores the critical role of policy interventions in facilitating the diffusion of low‐carbon technologies through intricate supply networks. As countries endeavor to meet environmental goals and transition to a more sustainable economy, it becomes critical to understand how policies can effectively shape the diffusion of these technologies through the supply chain. This study employs game theory and evolutionary game theory to investigate the intricate interactions within supply networks, with a particular focus on the nuanced effects of policy on the diffusion of low‐carbon technology innovations. The findings suggest that dynamically adjusted policies have the potential to significantly increase the uptake of low‐carbon technologies. In particular, an effective subsidy scheme not only promotes the diffusion of innovations, but also demonstrates the ability of government subsidies to be distributed efficiently. In addition, the implementation of dynamic carbon trading schemes is considered to be an important mechanism for promoting firms' decarbonization and stabilizing strategic decision‐making processes within firms. This study highlights the significance of tailored dynamic policy frameworks in promoting the adoption of sustainable technologies in supply chains, thus making a significant contribution to the broader goal of achieving a sustainable future.

Enhanced Management of Unified Energy Systems Using Hydrogen Fuel Cell Combined Heat and Power with a Carbon Trading Scheme Incentivizing Emissions Reduction

In the quest to achieve “double carbon” goals, the urgency to develop an efficient Integrated Energy System (IES) is paramount. This study introduces a novel approach to IES by refining the conventional Power-to-Gas (P2G) system. The inability of current P2G systems to operate independently has led to the incorporation of hydrogen fuel cells and the detailed investigation of P2G’s dual-phase operation, enhancing the integration of renewable energy sources. Additionally, this paper introduces a carbon trading mechanism with a refined penalty–reward scale and a detailed pricing tier for carbon emissions, compelling energy suppliers to reduce their carbon footprint, thereby accelerating the reduction in system-wide emissions. Furthermore, this research proposes a flexible adjustment mechanism for the heat-to-power ratio in cogeneration, significantly enhancing energy utilization efficiency and further promoting conservation and emission reductions. The proposed optimization model in this study focuses on minimizing the total costs, including those associated with carbon trading and renewable energy integration, within the combined P2G-Hydrogen Fuel Cell (HFC) cogeneration system. Employing a bacterial foraging optimization algorithm tailored to this model’s characteristics, the study establishes six operational modes for comparative analysis and validation. The results demonstrate a 19.1% reduction in total operating costs and a 22.2% decrease in carbon emissions, confirming the system’s efficacy, low carbon footprint, and economic viability.

Decentralized energy market integrating carbon allowance trade and uncertainty balance in energy communities

With sustained attention to carbon neutrality, the personal carbon trading (PCT) scheme has been embraced as an auspicious paradigm for scaling down carbon emissions. To facilitate the simultaneous clearance of energy and carbon allowance inside the energy community while hedging against uncertainty, a joint trading framework is proposed in this article. The energy trading is implemented in a peer-to-peer (P2P) manner without the intervention of a central operator, and the uncertainty trading is materialized through procuring reserve of conventional generators and flexibility of users. Under the PCT scheme, carbon allowance is transacted via a sharing mechanism. Possible excessive carbon emissions due to uncertainty balance are tackled by obliging renewable agents to procure sufficient carbon allowances, following the consumption responsibility principle. A two-stage iterative method consisting of tightening McCormick envelope and alternating direction method of multipliers (ADMM) is devised to transform the model into a mixed-integer second-order cone program (MISOCP) and to allow for a fully decentralized market-clearing procedure. Numerical results have validated the effectiveness of the proposed market model.

Low‐carbon demand response program for power systems considering uncertainty based on the data‐driven distributionally robust chance constrained optimization

AbstractThe demand response (DR) program is an effective solution to promote the low‐carbon operation of power systems with increasing penetration of renewable energy sources (RESs). This paper proposes a low‐carbon DR program for power systems to enhance both the environmental friendliness and uncertainty resilience of the system operation. The system operator aims to minimize both the system's operation cost and carbon trading cost. To handle the uncertainty associated with stochastic RES generation power and load consumption power, a data‐driven method named the two‐sided distributionally robust chance‐constrained (TS‐DRCC) approach is adopted to enhance the system's uncertainty resilience. A ladder‐type carbon trading scheme is utilized to calculate the carbon emission cost of the system. Comprehensive analyses of case studies have been conducted to validate that the proposed strategy can effectively reduce the total carbon emissions and total operation costs with good uncertainty resilience performance. The proposed low‐carbon DR program is verified to achieve 63.64% more carbon emission reduction compared with the conventional DR program. Besides this, the proposed low‐carbon DR program can also achieve 4.39% carbon‐intensive generation power reduction and 5.52% RES power consumption compared with the conventional DR program.

Deciphering Stakeholder Strategies in Electric Vehicle Battery Recycling: Insights from a Tripartite Evolutionary Game and System Dynamics

Given that the global fleet of electric vehicles is expanding rapidly, leading to a surge in demand for power batteries, the significance of battery recycling has come sharply into focus. In this paper, we develop a tripartite evolutionary game model coupled with a system dynamics simulation approach to analyze the behavioral mechanisms of stakeholders in electric vehicle battery recycling and to identify the key factors influencing their strategic transformations. The model involves three key stakeholders: local governments, battery cathode manufacturers, and battery pack manufacturers. Through profit analysis and the formulation of a replicator dynamics system, coupled with the application of Vensim for system dynamics modeling, we analyze the effects of ten crucial exogenous variables on stakeholder strategies. Our research highlights the crucial role of government actions, such as subsidies and penalties, in directing corporate strategies. Notably, excessively high subsidies (over 2.1 million Chinese Yuan) may lead to dependency among cathode manufacturers. Market factors, including increased battery sales and the preference for low-carbon procurement by electric vehicle manufacturers, are shown to significantly motivate cathode manufacturers to adopt recycling strategies and encourage pack manufacturers to develop recyclable designs. Additionally, the introduction of EU battery regulations and the integration of cathode manufacturers into carbon trading schemes have been identified as positive catalysts for strategic shifts, especially for cathode manufacturers, while exerting minimal influence on pack manufacturers. This paper elucidates the intricate interaction of the behavioral patterns and key motivators affecting stakeholder strategies in electric vehicle battery recycling.

Low-carbon energy transition multi-agent network evolutionary under carbon trading scheme.

Transitioning to low-carbon energy is key for reaching carbon neutrality and modernizing our energy systems, but it presents significant cost-related challenges for energy businesses. To foster optimal outcomes, this paper develops a game model including power generators, high-energy businesses, and consumers in the carbon trading framework. The model explores how different entities evolve their low-carbon strategies under social learning influence to optimize utility. Stability analysis of strategy and simulation experiments reveal the following findings: (1) Greater carbon quotas reduce power generators' low-carbon transition willingness while high-energy-consuming enterprises and consumers remain unchanged. (2) Higher prices for low-carbon products offered by high-energy-consuming enterprises boost low-carbon transition motivation across all parties. (3) Increased green premiums enhance revenue for all parties but are constrained by policy and carbon pricing. (4) Both direct and indirect increases in carbon emissions negatively impact the revenue and utility for all stakeholders. (5) Increasing social learning effect fosters a shift towards low-carbon strategies, accelerating the attainment of game equilibrium, and enhancing market stability and sustainability. This research provides decision support for carbon trading policy design and low-carbon transition of energy enterprises.

Investigating the carbon curse of natural resource dependence: A carbon trading scheme

Fossil-based natural resources are carbon-intensive, and over-reliance on them often leads to persistent high carbon emissions at national or regional levels, resulting in the carbon curse. Based on the panel data of 114 resource-based cities in China from 2007 to 2020, this paper examines the carbon curse and solutions for these cities from the perspectives of total and intensity of carbon emissions. The results show that: Firstly, due to the different stages of urban development, resource endowment, degree of resource dependence, and policy background, there is a heterogeneity of carbon curse in China's resource-based cities. Secondly, the carbon emission trading policy can effectively mitigate the carbon curse in China's resource-based cities, and the robustness tests demonstrate the validity of this finding. Thirdly, under the carbon emission trading policy, industrial structure upgrading and digital transformation can play a secondary moderating role in resolving the carbon curse in resource-based cities, further strengthening the inhibitory effect of the carbon emission trading scheme on the carbon curse. In contrast, green technology innovation exhibits no enhancement in the impact of the policy. These findings contribute to the existing research on the carbon curse, offering valuable insights and policy implications for effectively addressing this challenge.

Cooperative operation of multiple low-carbon microgrids: An optimization study addressing gaming fraud and multiple uncertainties

To achieve efficient utilization of renewable energy and facilitate the development of a more equitable and harmonious power market, an optimization study is conducted focusing on peer-to-peer (P2P) power sharing within multiple low-carbon microgrids (LCMGs). Firstly, the coordinated operation mechanism of a LCMG is proposed involving a step-type carbon trading scheme as well as flexible supply and demand. Then, an optimization model of multi-LCMG cooperative operation is formulated based on the Nash bargaining theory. The original Nash bargaining problem is equivalently transformed into a subproblem of maximizing alliance benefits and a subproblem of maximizing the benefits of power trading. In the first subproblem, a combination of opportunity constraints and robust optimization method is employed to address these multiple uncertainties from renewable generation and electricity prices. The second subproblem addresses the issue of gaming fraud among LCMGs with a third-party intermediary model applied to achieve a fraud equilibrium. Further, to solve these problems efficiently, an improved adaptive parametric alternating direction method of multipliers (AP-ADMM) algorithm is used to protect the privacy of each party. Finally, a case study was conducted to validate the efficacy of the proposed method in enhancing the stability and cost-effectiveness of cooperative optimization within multi-LCMG systems.

Sustainable supply chain planning with the flexible provisions of inter-period emission credits borrowing and banking under a multi-period carbon trading scheme

Although the carbon emission trading regulation proves its advantage of reducing abatement costs, the timing of operating activities makes overage or shortage of allocated emission allowances quickly happen in single-year compliance, thus increasing abatement costs. The provision of inter-period emission credits banking and borrowing in a multi-period compliance phase can give emitters flexibility in emission compliance, which practices world-widely. In this study, we investigate the impact of carbon trading with inter-temporal emission credits borrowing and banking on a production–inventory–distribution system’s supply chain network decision-making and its compliance strategies by proposing a novel two-stage stochastic programming. A scenario-based robust optimization approach is presented with a post-optimization stage to obtain robustness-profit-environment balanced decision-making considering uncertain demand and stochastic carbon-trading price. The results suggests emitters should adopt specific greener techniques to reduce related emissions with priority under carbon-trading policies. The results also show the provision of carbon credits borrowing and banking has a positive influence on enhancing the efficiency in supply chain economic and ecological performance. Besides, given the flexible provisions, the manager can reallocate emission credits according to its business’s operation, and transfer more emission credits to periods of higher carbon-trading price. This findings also suggest banking in early periods instead of carelessly borrowing from future, for uncertainty in future business might make it harder or impossible to comply with emission regulation at last. To regulators, it should prevent borrowing explicitly or allow it only to a limited extent.

Computable general equilibrium analysis of neutral carbon trading scheme and revenue recycling impacts on income distribution in China

Utilizing a dynamic computable general equilibrium (CGE) model, this paper critically assesses the potential distortions and efficacy of various revenue-neutral carbon emission trading schemes (ETSs) in China, through government subsidies and value-added tax (VAT) relief strategies aimed at achieving peak carbon emissions before 2030. The analysis reveals that reallocating market revenues to the production sector, either through government subsidies or VAT reductions, can feasibly attain carbon peaking before 2030, with minimal impact on GDP. Notably, both government subsidies and VAT cuts foster output growth in the oil, gas, and ETS-covered sectors. Moreover, directing carbon market revenue toward ETS-covered industries via VAT relief emerges as the most effective approach to reducing income disparities. In contrast, redistributing carbon market revenue to non-ETS-covered industries via VAT relief is found to be the least effective in promoting social equity. The study emphasizes that the reallocation of carbon market revenues to ETS-covered sectors is paramount. This strategy not only regulates the overall energy consumption effectively but also steers the nation towards a more sustainable and optimized energy consumption pattern. In light of these findings, this paper offers detailed insights and tailored policy recommendations, aiming to assist policymakers in striking a balance between environmental goals and economic and social imperatives.

How does the carbon trading scheme promote the decarbonization of China’s power sector?

Evaluating the effect of the carbon emissions trading scheme (ETS) on the decarbonization of the power sector is a basic task in the construction of China’s ETS. We use the energy flow relationship between the power and heat sectors to develop a more accurate accounting framework for CO2 emissions in the power sector and employ the difference-in-differences method to evaluate the impact of China’s ETS on CO2 emissions in the power sector and its dynamic effect. On this basis, we explore the mechanisms by which the ETS facilitates the decarbonization of the power sector, as well as its heterogeneous impacts. We find that the ETS has significantly promoted the decarbonization of the power sector, reducing its CO2 emissions in the pilot provinces by approximately 24.53 Mt compared to the non-pilot provinces. The decarbonization effect of the ETS was continuous and strengthened. In addition, the ETS promotes decarbonization of the power sector through technological advances in power generation and electricity utilization. Finally, the ETS’s decarbonization effect on the power sector is influenced by the heterogeneity of regions, carbon prices and quota allocation methods. Our findings have beneficial implications for the construction of carbon markets in the context of carbon neutralisation and carbon peaking.

Space-time mapping of soil organic carbon stock and its local drivers: Potential for use in carbon accounting

The measurement and tracking of changes in soil organic carbon (SOC) stocks and its underpinning drivers are important in greenhouse gas accounting and carbon trading schemes. While repeated direct measurement of a location over time is the ‘gold standard’ for SOC stock change estimation, this is currently unfeasible at scale due to sample collection and analysis costs. Here, we used a data-driven, space–time digital soil mapping modelling approach (ST-DSM) coupled with an interpretive machine learning (IML) technique to both predict and quantify the relative contributions of covariates to annual SOC stocks and their uncertainty at 0–30 cm depth and at a 90 m spatial resolution for Australia between 1990 and 2018. A quantile regression forest model was calibrated using data from a datacube comprising of SOC stock values collected over the prediction years and a suite of dynamic and static environmental covariates. The evaluation of the ST-DSM model on a test set was satisfactory. Long-term annual mean (Mg C/ha), and total (Pg C) topsoil SOC stock were 37.6 (12.3 – 101.1, 90 % PI) and 28.3 (9.25 – 83.1, 90 % PI) respectively. The mean annual rate of SOC stock change over the Australian continent was 0.11 (±0.22) Mg C/ha yr−1 and the total net change was 23.5 Tg C yr−1, indicating Australia’s soils were a net sink of SOC over the 29-year period. However, SOC stocks declined in the montane ecoregion, a great concern given its fragility and high SOC stock. The long-term mean fraction of photosynthetic vegetation was the most important individual local contributor to SOC stock prediction in many parts of Australia. The aggregated effect of covariates based on the soil forming factors indicates vegetation as the principal local driver of SOC stock across most of the Australian continent, followed by climate. The evaluation of our results against independent, temporally paired field data and estimates from a nationally accepted SOC process-based model yielded promising results. Our approach demonstrates the use of readily available and inexpensive covariates to estimate SOC stock changes, as well as the underlying drivers over a larger area but at a spatial resolution suitable for decision making. This approach presents a new monitoring and verification possibility for carbon projects and national carbon accounting especially with the growing number of existing profile observations in soil databases.

Thermoelectric Optimization of Integrated Energy System Based on Bidirectional Electricity-to-Hydrogen Technology

Abstract Addressing the challenges of high energy consumption and low efficiency in integrated energy systems, this research develops an optimal scheduling strategy that takes into account the dynamic operational conditions of the system and the complementary nature of electricity, hydrogen, and heat energies. Through the innovative application of variable efficiency gas turbines and solid oxide batteries, our model adeptly converts between these forms of energy. Moreover, we introduce a demand response strategy that seeks to balance efficiency with low-carbon generation and integrates a tiered carbon trading scheme to influence user electricity use and curb system-wide carbon footprints. Empirical results validate the effectiveness of our method in significantly enhancing energy use efficiency, cost savings, and emissions reductions.

Evolutionary game analysis of forest carbon note system in China

The Forest Carbon Note System (FCNS) is a novel carbon trading scheme for China's forestry sector. It aims to engage more social actors in forest ecosystem conservation, while pursuing both regional carbon neutrality and poverty alleviation. To explore the dynamics of FCNS, this study examines the roles of local governments, companies, and forest farmers, and develops an evolutionary game model to identify the key determinants of FCNS adoption and the interplay and equilibrium among different stakeholders. The main findings of this study are: (1) The FCNS can reach three stable equilibrium strategies under certain conditions, namely (01,0), (0,1,1), and (1,1,1). (2) The local governments' motivation to promote the FCN depends on factors such as political performance, administrative costs, and transaction subsidies. (3) The companies' participation is influenced by factors such as mandatory and voluntary carbon offset amounts, branding benefits from joining the FCNS, and government penalties for exceeding carbon emission limits. (4) The forest farmers' participation is affected by the development costs of FCN projects and government subsidies. (5) The FCN price should be reasonable, covering the forest farmers' costs of developing and trading the FCN, while keeping the companies' interest, enabling the forest farmers to increase their income, and the companies to reduce their carbon emissions at a fair cost. (6) A higher social awareness of green development will lead to more involvement from the government, companies, and forest farmers. This study fills the research gap on the experiential synthesis and institutional analysis of FCN, and offers policy recommendations for improving the FCNS.

Towards a greener future: Assessing the impact of carbon emission trading on urban carbon efficiency in China

The pursuit of a low-carbon transition is central to achieving green development worldwide, and China has embraced carbon emissions trading (CET) with the aim of achieving high-quality economic development. Despite its critical policy importance, the question of whether and how CET promotes carbon efficiency remains unclear. Using unique panel data covering prefecture-level cities in China from 2007 to 2020, this study first fills this gap by constructing the Global-EBM model and taking carbon dioxide as an undesirable output to innovatively evaluate the total factor carbon emission efficiency (TFCEE) of China's cities. Second, as an extension of the existing provincial evidence, we treat the carbon trading scheme in urban China as a quasi-natural experiment and confirm the boosting effect of CET on TFCEE in the pilot cities. Third, the mediating roles of both green technology innovation and industrial structure upgrading in the process of promoting carbon efficiency are identified, further demonstrating the channel influences. Finally, the heterogeneous impact of the CET policy is further investigated and found to be stronger in eastern and developed cities. Our findings have important policy implications for China's green transition.