Carbon Trading Policy Research Articles

The impact of China's carbon trading policy on enterprises' energy-saving behavior

This paper mainly investigates whether emissions trading for pollutant permits more effective. By employing difference-in-differences method and a compressive firm-level dataset, we evaluate the impact of carbon trading system pilot cities policy on enterprises' energy-saving behavior. The findings indicate that after carbon trading system pilot cities policy, enterprises’ coal consumption and coal intensity decreased by almost 34 % and 33 % respectively. The policy effect is more pronounced for larger companies and for firms in energy-intensive sectors. Moreover, the policy effect becomes stronger over time. Our results satisfy the common trend assumption. Meanwhile, the investment in equipment and output are increased, which prove emissions marketization could bring about substantial improvements in productivity.

Farm biomass photovoltaic distributed generation system delivers positive economic performance under carbon trading policy

Farm biomass photovoltaic distributed generation system delivers positive economic performance under carbon trading policy

Farm biomass photovoltaic distributed generation system delivers positive economic performance under carbon trading policy

Farm biomass photovoltaic distributed generation system delivers positive economic performance under carbon trading policy

Remanufacturing closed-loop supply chain decision comparison under multiple carbon policies

Abstract This article constructs a closed-loop supply chain system including a single manufacturer and a single retailer and studies the optimal decision problem of enterprises under three different carbon reduction policies. Three supply chain game models were constructed to research the impact of different carbon reduction policies on the decisions of supply chain members. The results revealed that:(1) The carbon emission reduction level of the manufacturer is negatively correlated with the recycling price of used products and the abatement cost factor;(2) When the carbon trading price is equal to the tax rate, the carbon cap and trade policy is more conducive to promoting the manufacturer to improve the level of carbon emission reduction;(3) When the carbon trading price is low, mixed carbon policy is more favorable for the manufacturer to increase its carbon emission reduction. The research results of this study can provide certain suggestions for the government to implement a reasonable carbon reduction policy.

考虑碳排放成本的多车型农资配送路径优化研究

Agriculture is the foundation of the national economy, and agricultural materials are the basis of agricultural development. As the three rural issues (agriculture, countryside, and farmers) become increasingly important, the distribution of agricultural materials attracts extensive attention. Given the slow development of rural logistics, the traditional agricultural material distribution process encounters many problems, such as cumbersome distribution links, high distribution costs, and low profit for enterprises, which in turn cause high production costs and low income for farmers. In consideration of battery energy consumption and soft time window constraints, this study adopted the agricultural material distribution route as the study object and established an optimization model of the agricultural material distribution route with fixed , transportation, energy consumption, time window penalty, and carbon emission costs as the objective functions. With regard to the algorithm, the operation of differential update and chaotic disturbance was innovatively enhanced and applied to the improved ant colony algorithm to simulate the model and obtain the optimal distribution route optimization model. Results show that the traditional ant colony algorithm improved by differential updating and chaotic disturbance has the advantages of low distribution cost, reasonable route, small number of activated vehicles, and short convergence time. Compared with the traditional ant colony algorithm, the improved ant colony algorithm can converge to the global optimum faster. This study provides guidance and suggestions on route selection and vehicle configuration to reduce costs and increase efficiency and offers certain theoretical support to alleviate urban traffic pollution and implement carbon trading policies in the future.

How do carbon emissions trading impact the financialization of non-financial companies? Evidence from a quasi-natural experiment in China.

This study examines whether and how carbon trading policy impacts the financialization of non-financial firms, using China emission trading scheme as a quasi-natural experiment. We find that the carbon trading policy exerts a substantial and enduring inhibitory effect on corporate financialization. Our findings are robust to possible result bias and more precise control group. Additionally, we explore potential channels through which carbon trading policy can affect financialization, and find that it curbs financialization by reducing financing constraints. Finally, we demonstrate that the relationship between carbon trading policy and financialization of non-financial companies is moderated by company's ownership, region, and industry competition.

A novel three-way decision-making method for logistics enterprises’ carbon trading considering attribute reduction and hesitation degree

Currently, against the background of carbon trading policies, carbon dioxide is attributed commodity properties for market trading within carbon trading. Relevant data show that, in recent years, logistics enterprises have been facing continuously growing demand and carbon emissions have continuously increased; therefore, enterprises urgently need to strengthen their green transformation. Scientific and rational decision-making tools play a meaningful role in helping enterprises improve their competitiveness. In this context, a new three-way decision-making model based on attribute reduction and hesitation degree is proposed. First, an attribute reduction is performed. The attributes of three types of logistics enterprises are simplified according to the carbon emission evaluation attributes proposed in this study to determine their respective minimum attribute sets. Subsequently, the decision and loss function matrices are established considering the hesitation degree. The conditional probability is calculated using intuitionistic fuzzy similarity, and the probability threshold is calculated using the loss function matrix considering the hesitation degree. Finally, case studies and comparative analyses are conducted to illustrate the practicality and rationality of the proposed method.

Smooth sailing ahead? Policy options for China's new energy vehicle industry in the post-subsidy era

The Chinese government views the development of new energy vehicles (NEVs) as a key measure to achieve sustainable development. In 2020, the government proposed the development goals of achieving carbon peak in the automotive industry around 2028 and ensuring NEV sales account for over 50 % by 2035 (referred to as the “two objectives”). Against the backdrop of the cancellation of NEV purchase subsidies in 2023, it is crucial to investigate the direction and intensity of various industry policies' effects and actively adjust industrial policies to achieve the “two objectives”. From the perspective of the Multi-level Perspective (MLP), the technological transition in the automotive industry is a process of legitimacy transfer between new and old technologies driven by the interaction of socio-technical landscape, socio-technical regime, and niches at three levels. This paper, based on the MLP, constructs a system dynamics (SD) model that includes four loops: research and development (R&D), production, sales, and legitimacy competition. Using the SD model, we analyze the direction and intensity of existing policies, in addition to five potential policies, to achieve the objectives. Our findings indicate that without policy adjustments, China's current measures will not meet the “two objectives” in a timely manner. Prioritizing battery recycling, curtailing fuel vehicle (FV) production, facilitating scrapping of FVs and enacting carbon trading policies are pivotal for progress, contrasting with the modest impact of R&D subsidies. A coordinated policy strategy coupled with expedited carbon trading initiatives is essential for the NEV sector's post-subsidy transition to meet the objectives.

Optimal integration of electricity supply chain and sustainable closed-loop supply chain

This study presents an innovative multi-objective robust mixed-integer linear model to integrate an original capacitated Electricity Supply Chain (ESC) and a Closed-Loop Supply Chain (CLSC). The multifaceted relationships between the three dimensions of sustainability, different Carbon Emission Schemes (CES), and robustness have been carefully examined considering the Decision Maker’s (DM’s) various risk preferences. Results demonstrate the direct effect of the selected CES on the network configuration. Under each CES, the total cost increases by increasing the conservatism of the DM. At lower carbon emission capacity, the Carbon Cap Policy (CCP) has lower emissions at the highest cost compared to other policies. However, the emission capacity does not affect the emission under the Carbon Tax Policy (CTP) and Carbon Cap and Trade Policy (CCTP) but increases the network cost in both policies. A conservative DM is willing to adopt CTP with lower cost and emission at a higher emission capacity. At any level of emission capacity, CCTP has a higher priority than CTP only for non-conservative carbon-sensitive DM. The higher the DM conservatism, the lower the carbon credits sold under the CCTP, and the higher the need to purchase credits. Contrary to the insignificant effect of CESs, increasing the DM’s conservatism improves the robustness.

A Novel Individual Carbon Emission Evaluation and Carbon Trading Model for Low-Carbon University Campuses

Individual carbon accounting and trading is significant for building and achieving low-/zero-carbon university campuses. This manuscript examines various aspects of individual carbon trading on campus, such as assessing personal carbon emissions, students’ willingness to participate in individual carbon trading on campus, and its influencing factors, policy setting, and emission reduction benefits. Based on the Theory of Planned Behavior, this manuscript uses the conditional process analysis method and conducts a questionnaire survey on a university campus in Beijing to evaluate individuals’ carbon emissions on campus and explore their willingness to trade personal carbon. Moreover, a system dynamics approach is adopted to propose a simulation model of individual carbon trading on the campus and assess its feasibility and emission reduction benefits. The results indicate an average annual emission reduction of 8.18% per person, providing a theoretical foundation to implement and promote the individual carbon trading pilot on campus. These findings highlight the potential benefits of individual carbon trading policies that may effectively reduce carbon emissions on university campuses.

Public willingness to pay for personal carbon trading of green travel: based on survey data from five capital cities in eastern China

Personal carbon trading is a form of pollution rights trading that is worth exploring as an innovative tool to cut back carbon emissions from travel. This paper proposes a policy scenario in which car users who exceed the average distance traveled quota are required to purchase travel credits from those who do not reach the quota and pay for them on a per hundred kilometer basis. Willingness to pay (WTP) for personal carbon trading is introduced to calculate the travel cost and its influencing factors are analyzed from the perspective of green travel. Using the double-bounded dichotomous choice contingent valuation method (DBDC), 2712 residents’ data from five provincial capital cities in eastern China is obtained. Based on this, this study first uses a binary logistic regression model to analyze the characteristics of people who are not willing to pay for green travel carbon trading, and then leverages an interval regression model to explore the willingness and intrinsic motivation of being willing to pay more or less for green travel. The results suggest that perceived usefulness is a key influencing factor of residents’ willingness to pay or pay more for green travel; Personal habits have a significant positive effect among those willing to pay; Subjective norms and moral norms can well account for the unwillingness to pay; Attitudes, perceived behavioral control, and environmental awareness fail to predict the willingness to pay among those who are unwilling to pay. In addition, WTP is also affected by demographic variables such as income and educational background. The empirical results as well indicate that the final average level of respondents’ WTP is 39.95 yuan per 100 km. The findings of this paper can provide a pricing basis while formulating personal travel carbon trading policies.

Simulation analysis of the three-party evolutionary game of green building market players under carbon trading policy.

Previous studies mainly focus on the game analysis of green building development under carbon tax policy, while carbon trading, as one of the important means to promote low-carbon development, is rarely mentioned in promoting the development of the green building market. Based on this, to study the impact of carbon trading policy on the development of the green building market, this study combines prospect theory for carbon trading to build a three-way evolutionary game model of developer-government-consumer. It studies the influencing causes of green building market development under the carbon trading mechanism from the whole perspective. The study shows the existence of a carbon trading policy helps the development of the green building market. In the presence of a carbon trading market, the government's punishment, subsidies, and the setting of carbon prices influence the development of the green building market. In addition, the percentage of carbon emissions bought, the potential benefits, and the selling price also affect the chance of consumers buying green buildings to a greater or lesser extent. This study introduces prospect theory into the developer-government-consumer three-way evolutionary game model, which enriches the research perspective of each subject's behavior in the green building market. It provides theoretical support for developers, governments, and consumers to collaborate to promote the coordination and development of the green building market. It has policy implications for promoting the green and high-quality development of the construction industry.

Carbon Trading in China Reduces the Dependence of Household Waste Electrical and Electronic Equipment Recycling on Government Subsidies.

China's enterprises of waste electrical and electronic equipment (WEEE) recycling suffer from low profitability that is highly dependent on government subsidies. This low economic gain impedes the sustainable growth of China's WEEE-recycling sector and also adds to the government's financial burden. Prior life-cycle studies have approved the carbon reduction potentials or net carbon credit of recycling WEEE. However, policymakers fail to know whether the revenue from selling carbon credits can offset the government's financial subsidy. We performed life-cycle and cost-benefit analyses for a case recycling enterprise that processes six categories of household appliances. The results show that the reduction potentials of greenhouse gases range from 930-3450 kgCO2e by recycling per ton of household appliances and materials substitution. The recycling enterprise would gain extra revenue ranging from 32 to 160 RMB per ton of appliance if the carbon credits were sold at China's current carbon price, i.e., 45-60 RMB tCO2e-1. Recycling waste refrigerators exhibits the highest carbon revenue, offsetting 6-17% of the government's financial subsidy. Microcomputers, by contrast, indicate the lowest carbon revenue, equivalent to 1-3% of its highest government subsidy. For each household appliance category, when the carbon price reaches 270-600 RMB tCO2e-1, selling carbon credits can fully offset the government's financial subsidy. Constrained by the processing capacity of the case enterprise, optimizations for appliance-recycling composition contribute a 15-25% profit growth to the current economic gains. Interpreting the specific profit depends on the predefined scenarios of carbon price and the substitution rate of the regenerated materials for the virginal ones. Our findings show that raising the profitability of WEEE recycling enterprises through the carbon trading policy contributes to the sustainable growth of China's WEEE-recycling sector while alleviating the government's financial burden.

Repurchase or pledge? Financing and production decisions of engineering machinery remanufacturing firms

Under carbon cap and trade policy, engineering machinery firms have engaged in remanufacturing and invested in carbon emission reduction technologies. However, they often struggle with a lack of funding, but carbon quota financing offers a solution. Taking a capital-constrained engineering machinery remanufacturer as the research object, this paper first formulates four decision models, i.e. (no capital constraints, no financing), (capital constraints, no financing), (capital constraints, carbon quota repurchase financing) and (capital constraints, carbon quota pledge financing), then the equilibrium results are compared. Finally, the numerical simulations are performed to study the impact of carbon emission reduction and quality uncertainty of recycled products. The results show that if remanufacturers possess adequate carbon quotas, carbon quota pledge financing can always improve profits effectively, otherwise, the effectiveness of financing strategies depends on the difference between extra profits and financing costs. Both financing strategies can increase the output of new products and reduce that of remanufactured products. Increasing the quality threshold of recycled products is beneficial for remanufacturing, environmental protection and profits. Investing in carbon emission reduction benefits remanufacturing and the environment, however, it reduces remanufacturers' profits in the short term.

Spatial spillover effects of a carbon trading policy on green technology innovation in China.

A carbon market is a widely used policy tool worldwide. This study employs a difference-in-differences (DID) model to estimate the impact of a carbon trading policy on green technology innovation and applies a spatial DID (SDID) model to investigate its spatial spillover effects. The findings suggest that China's carbon market effectively promotes green technology innovation, as green invention patent applications for listed enterprises increase by 28.8% when implementing the carbon trading policy. Moreover, implementing a carbon trading policy promotes local green technology innovation and has spatial spillover effects on neighboring cities. Furthermore, heterogeneity test results show that the spatial spillover effects differ by geographical region, economic development levels, ownership type (state-owned and non-state-owned enterprises), and degree of government intervention. Therefore, we suggest enhancing enterprises' technological innovation by providing policy support and prioritizing the development of carbon markets in regions with high economic development levels.

Natural resources, carbon trading policies and total factor carbon efficiency: A new direction for China’s economy

The role of natural resources is important not only for carbon emissions but also for the overall sustainable development of an economy. With the dual pressure of the worsening global climate problem and the deteriorating domestic environment, carbon emissions and other greenhouse gas emissions must be solved urgently. Consequently, assessing China’s “carbon trading” policies' effect on total factor carbon efficiency is essential to achieving China’s carbon neutrality objectives. Using the Difference-in-Difference estimation model and panel data in 30 provincial-level administrative regions within China from 2000 to 2020, this study examines the effect of “carbon trading” policy on total factor carbon efficiency. The study’s findings indicate that the carbon trading policy encourages total carbon efficiency development. Additionally, the conclusions are robust. Moreover, the results show that the mediation effect analysis indicates that a “carbon trading” policy promotes increasing total factor carbon efficiency through decreasing total energy consumption, optimizing the energy structure, increasing technological innovation, and increasing forest coverage. The heterogeneity analysis reveals that enacting carbon trading policies in the central and western regions is more effective at fostering the enhancement of total factor carbon efficiency. Based on these findings, policy recommendations are made to promote the enhancement of total factor carbon efficiency and attain China’s “Carbon peaking and carbon neutrality” objective.

Estimation of Above-Ground Carbon Storage and Light Saturation Value in Northeastern China’s Natural Forests Using Different Spatial Regression Models

In recent years, accurate estimation and spatial mapping of above-ground carbon (AGC) storage in forests have been crucial for formulating carbon trading policies and promoting sustainable development strategies. Forest structure complexities mean that during their growth, trees may be affected by the surrounding environment, giving rise to spatial autocorrelation and heterogeneity in nearby forest segments. When estimating forest AGC through remote sensing, data saturation can arise in dense forest stands, adding to the uncertainties in AGC estimation. Our study used field-measured stand factors data from 138 forest fire risk plots located in Fenglin County in the Northeastern region, set within a series of temperate forest environments in 2021 and Sentinel-2 remote sensing image data with a spatial resolution of 10 m. Using ordinary least squares (OLS) as a baseline, we constructed and compared it against four spatial regression models, spatial lag model (SLM), spatial error model (SEM), spatial Durbin model (SDM), and geographically weighted regression (GWR), to better understand forest AGC spatial distribution. The results of local spatial analysis reveal significant spatial effects among plot data. The GWR model outperformed others with an R2 value of 0.695 and the lowest rRMSE at 0.273, considering spatial heterogeneity and extending the threshold range for AGC estimation. To address the challenge of light saturation during AGC estimation, we deployed traditional linear functions, the generalized additive model (GAM), and the quantile generalized additive model (QGAM). AGC light saturation values derived from QGAM most accurately reflect the actual conditions, with the forests in Fenglin County exhibiting a light saturation range of 108.832 to 129.894 Mg/ha. The GWR effectively alleviated the impact of data saturation, thereby reducing the uncertainty of AGC spatial distribution in Fenglin County. Overall, accurate predictions of large-scale forest carbon storage provide valuable guidance for forest management, forest conservation, and the promotion of sustainable development strategies.

Repositioning shared bikes under low-carbon policies

Low-carbon policies implemented by the Chinese government have a significant impact on third-party logistics, particularly for bike-sharing operators. This study investigated the static bike repositioning problem under low-carbon policies. Repositioning shared bikes under low-carbon policies such as emission cap, carbon trading, carbon offset, and carbon tax requires strict emission limitations and complicated routing plans. Therefore, a mixed-integer linear programming (MILP) model was formulated for the integrated planning of vehicle routes and bike allocation, aiming to minimize the repositioning cost and total imbalance penalty. An improved variable neighborhood search (IVNS) is proposed to solve this problem. The algorithm includes a route generation strategy heuristic and an improved neighborhood search operator for optimizing the route design, and a greedy heuristic for tackling loading and unloading instructions along the route. Numerical experiments show that (i) the proposed IVNS algorithm outperforms the GUROBI solver and existing method in striking a balance between solution quality and computational time; and (ii) the carbon trading policy is more flexible, not only effectively reducing emissions but also encouraging the further development of the bike-sharing industry.

Innovation spillover effect of the pilot carbon emission trading policy in China

In today's society, environmental protection and sustainable development have become the focus of global attention. Carbon emission trading, as an effective means to reduce greenhouse gas emissions, has been adopted by many countries and regions. In China, the launch of pilot policies for carbon emissions trading is of great significance in promoting economic transformation, promoting industrial upgrading and protecting the environment. Therefore, it is of great value to study the innovation effect of the pilot carbon trading policy and its transmission path for evaluating the effect of the policy, optimizing the policy design and building the carbon market in the future. Based on the production network theory, this paper constructs a difference in difference model, and uses empirical analysis to evaluate the direct innovation effect and innovation network spillover effect of the pilot carbon emission trading policies. In the empirical analysis, a variety of data sources are used, including public data from the National Bureau of Statistics, annual reports of enterprises, and industry associations, to ensure the reliability and validity of the data. At the same time, SPSS, Stata and other statistical software are applied to process and analyze the data in order to better understand and interpret the research results. The results show that the pilot carbon emission trading policy has a positive effect on improving the innovation level of both regulated and non-regulated industries in the pilot areas. Specifically, this policy can promote the technological innovation and management innovation of the regulated industries, but also promote the technological progress and market development of the non-regulated industries. In addition, the policy will also have an innovation network spillover effect, that is, the innovation results of the policy will be transmitted to the surrounding regions and industries, thus promoting the innovation and development of the entire region and industry. Further, this paper also discusses the transmission path of the innovation spillover effect of pilot carbon emission trading policies. It is found that the policy has a negative impact on the innovation of the relative upstream industry, but significantly promotes the innovation of the downstream industry. This is because the upstream industry, after being impacted by policies, often takes measures to reduce costs and improve efficiency to deal with the challenges, which may have a certain negative impact on the downstream industry. However, downstream industries are more likely to benefit from the innovation spillover effects of policies because they are more closely linked to the carbon emission trading market. Finally, this paper also tests the mechanism of the pilot carbon emission trading policy. It is found that the innovation spillover caused by this production-end shock is mainly realized through the price transmission of finished products. In addition, the inclusion of industries with strong bargaining power and close links with downstream industries in the national pilot carbon emission trading policy is more conducive to the innovation spillover effect of the policy. This is because these industries have stronger market influence and bargaining power, and can better promote the construction and development of the carbon emission trading market.

Does Carbon Emissions Trading Policy Improve Inclusive Green Resilience in Cities? Evidence from China

With the impact of external globalization uncertainties and the pressure of internal national environmental policies and markets, maintaining inclusive green resilience while coordinating economic, environmental, and social systems is critical for achieving green and sustainable urban development. We define inclusive green resilience for cities in this research and build a system of inclusive green resilience indicators. The DID model and entropy approach were used to examine the impact of carbon trading policies on inclusive green resilience in 184 representative Chinese cities from 2008 to 2018, and PSM-DID was utilized for further validation. According to the findings of the study, carbon emissions pricing policies can considerably increase inclusive green resilience in cities. Mechanism verification demonstrates that carbon trading programs improve inclusive green resilience in cities through industrial restructuring, technical innovation capability, and employment benefits. According to the city heterogeneity study, the implementation of the carbon emissions trading system has a scale effect and significant urban functional differences, and its impact on inclusive green resilience of cities is greater in large and medium-sized cities and non- resource-based cities. This research offers a new way of thinking about inclusive green resilience as well as empirical data for future sustainable policy development.