Search

Carbon trading market is a central policy tool for promoting cleaner enterprises' energy consumption and investment behaviors. It is crucial for enterprises to establish a green and low-carbon development model by clarifying carbon trading impact mechanism on enterprise behaviors and the interactive relationship between entities in the carbon market. China's contract-based carbon market is still in the development stage, the impact of the mainstream allowance mechanism and government regulation on enterprises' energy behaviors has yet to be determined. In view of this, this paper describes mathematical mechanisms of the influence of carbon prices and carbon quotas on enterprises' energy consumption and investment, and the evolutionary game model of government-enterprise behaviors is constructed, the evolution process and appropriate strategies of enterprises' energy behaviors in the development of the carbon market are discussed. This paper uses real data of China carbon market to simulate the model, it is found that strategies such as relaxation of carbon quotas and carbon subsidies dynamization are needed during the initial development of the market. In the mature stage of the carbon market, strategies are needed to increase the proportion of government carbon revenue and reduce its regulatory cost. The higher the initial willingness of government-enterprise, the better the effect of strategies and the constraints of public willingness. The model and results have theoretical implications for enterprises' energy transformation and government regulation, and provide a reference for the development of China's carbon market. • Constructed benefit-cost analytical framework for enterprises' energy behaviors. • Described mechanisms of carbon trading affecting enterprises' energy behaviors. • Constructed government-enterprise behaviors model by the evolutionary game theory. • Found new conclusions of enterprises' energy behaviors under the carbon market. [ABSTRACT FROM AUTHOR]

Accurately predicting carbon price can promote the rational allocation of carbon resources, reducing carbon emissions and contributing to green development. The decomposition integration framework is widely applied for carbon price forecasting, but several problems remain. Thus, this paper innovatively proposes an enhanced decomposition integration model for deterministic and probabilistic carbon price forecasting, which combines two-stage feature extraction and intelligent weight optimization. In order to decrease the complexity of the data and fully extract the characteristics, two decomposition approaches are utilized. For reconstruction, fuzzy entropy is applied to balance model complexity and computing efficiency. Next, the combination forecasting model based on two deep learning models is built to circumvent the constraints of the single forecasting model, and the cuckoo search optimization method (CS) is utilized to find the weight of the combination model adaptively. Considering the differences in the contributions of each component, the optimal weighting strategy based on CS is then used to derive the final forecast. Ultimately, considering the probability interval can provide more helpful information, the decomposition integration framework is supplemented with Gaussian process regression relying on the mixed kernel function for interval prediction. In an empirical study of five carbon trading markets, the hybrid model developed in this paper exceeded all baseline models regarding prediction stability, proving that the developed model can make effective forecasting for the carbon trading business. • An enhanced decomposition integration model is developed for carbon price prediction. • Both deterministic and uncertainty carbon price prediction are performed. • The two-stage feature extraction technique well balances model complexity and computational efficiency. • Intelligent weight prediction integrated model greatly improves the accuracy of prediction results. • The proposed model has excellent performance in carbon price prediction. [ABSTRACT FROM AUTHOR]

Carbon trading, one of the key policy instruments for reducing carbon emissions, can significantly contribute to the government's goal of achieving "peak carbon" and "carbon neutrality". Thus, under pressure from the government to implement carbon trading policies, enterprises often seek new low-carbon production technologies or business models. Meanwhile, outsourcing remanufacturing is often considered an effective means of promoting carbon reduction. Therefore, based on an outsourced remanufacturing model, we investigated the impact of carbon trading on the manufacturing/remanufacturing supply chain (SC) by constructing a game model involving an original equipment manufacturer (OEM) and an outsourced remanufacturer (OR) under decentralized versus centralized decision-making conditions. Furthermore, we designed a coordination mechanism to address the loss of benefits for the overall SC under decentralized decision-making conditions. We drew the following conclusions: (1) Whether in a decentralized or centralized decision-making model, there is a feasibility boundary condition when a government implements the carbon trading policy. Namely, the policy fails when the carbon trading price is greater than a certain threshold. (2) The decentralized decision-making approach reduces the sales of remanufactured goods and the recycling rate for used goods compared to the centralized decision-making paradigm, resulting in a marginal loss of profit. And, as the price of carbon trading rises, carbon trading regulations tend to expand the room for coordination of interests in the decentralized decision-making paradigm. (3) A single cost-sharing contract, while increasing revenues for OEM and SC, reduces revenues for OR. Profit-sharing contracts and fixed-cost contracts increase OEM and OR revenues, but overall SC profits are still lower than in the centralized decision-making model. Therefore, this paper combines revenue-sharing, cost-sharing, and fixed-fee outsourcing contracts to effectively achieve SC coordination. [ABSTRACT FROM AUTHOR]

In order to probe collaborative environmental governance (CEG) in China's "1 + N" policy framework for carbon peak and carbon neutrality, this paper applies the Actor-network theory (ANT) as an analytical framework to explore carbon reduction policy coordination. We then model ANT's relations with an evolutionary game theory (EGT) model to examine the evolutionarily stable strategies in CO 2 emission reduction by various actors including the central government, local governments, commercial banks, and polluting enterprises. Our objective is to examine policy coordination as the key enabler for governing success via an ANT-based mechanism design in China's institutional context. Combining the strength of ANT with a four-party EGT model, we investigate how to improve policy coordination to mobilize the actor-network for promoting CEG. Simulations are conducted to examine the effectiveness of policy coordination involving multiple policy instruments for controlling carbon emissions. The central government fulfills leadership in translating the interests of other actors and shaping the desired collaborative network. Without proper coordination, environmental policies may counteract each other. Government transfers and subsidies have direct impacts, but in the long run enhanced competitiveness and profitability of enterprises represent the intrinsic key to CEG success. From a methodology perspective, policy simulation in an EGT framework represents a novel addition to the research toolbox that expands ANT. [ABSTRACT FROM AUTHOR]

The sustained growth of global aviation emissions has highlighted the urgent need for using Sustainable Aviation Fuels (SAFs) to replace traditional aviation fuels to mitigate emissions. SAFs can potentially reduce greenhouse gas emissions by 50%–90% compared to conventional jet fuels. This paper collected aviation emissions data from South American routes between 2019 and 2021, and the GWP100 method was used to convert CH 4 and N 2 O emissions into CO 2 equivalents. Additionally, emissions from the South American route between 2023 and 2070 were predicted, as well as the amount of subsidy required to promote the use of SAFs under four different scenarios. The result shows that adopting SAFs could reduce approximately 69.3 million to 113.53 million tons of CO 2 -equivalent emissions in South America by 2070. However, the South American aviation industry will likely embrace using SAFs only if the carbon trading price exceeds 0.273 times the difference between SAFs and jet fuel prices. • This study calculates the emission reduction effects under four scenarios. • The GWP100 method is used to convert non-CO 2 emissions into CO 2 equivalent emissions. • SAFs can reduce 69.3–113.53 million tons of CO 2 -equivalent emissions by 2070. • Using SAFs is profitable when carbon price exceeds 0.273 times SAFs-kerosene price gap. • Using SAFs earlier will increase subsidies by $3.65–4.56 billion every five years. [ABSTRACT FROM AUTHOR]

Under the background that China will achieve the goal of carbon neutrality by 2060, analyzing the impact of carbon neutral target constraints on the welfare of urban and rural residents is an important part of the design of a carbon emission reduction policy mechanism, in this paper, the dynamic recursive CGE(Computable general equilibrium) model is used to simulate the changes in welfare level, income consumption, and CO2 emissions of residents and their urban-rural heterogeneity under the policy of imposing a carbon tax on the fossil energy industry from 2022 to 2060. The results show that: compared with the BAU scenario, by 2060, first the income and consumption of residents will decrease slightly. Second, the target constraint of carbon neutrality makes the equivalent variation and compensate variation of urban and rural residents' welfare decrease slightly, and the equivalent variation and compensate variation of urban residents decrease more than those of rural residents. The following conclusions are drawn: first, the carbon-neutral target constraint makes the welfare of urban and rural residents decline slightly, but it will not have a strong impact on residents' income and consumption. Second, this constraint has a greater impact on the income, consumption and savings of urban residents than those of rural residents. [Display omitted] • A five-layer nested dynamic recursive CGE model is established to analyze residents' welfare. • Carbon taxes are incorporated into production decisions as a policy cost for energy companies. • The heterogeneity of the impact of carbon tax policy constraints on the welfare of urban and rural residents was analyzed. • The government needs to improve the intensive and diversified energy supply in rural areas to reduce the urban-rural gap. [ABSTRACT FROM AUTHOR]

With the deterioration of natural resources and the aggravation of environmental pollution, there is a growing imperative to implement industrial green reform through green technology investment (GTI). This paper constructs a nonlinear dual-objective function by drawing on the theory of two-sided matching under the carbon trading regulation, aiming to examine GTI selection decisions made by two oligarchic manufacturers (i.e., oligarchs) and a monopoly supplier (i.e., supplier). The supplier offers multiple green technologies, while oligarchs rack their brains to buy green technologies in an attempt to exploit their social, economic and environmental potentials. Available technologies vary in terms of their environmental efficiency and cost. Then, a two-sided matching mechanism is constructed to explore the availability of stable matchings and examine the impacts of the carbon price and green improvement coefficient on GTI, product pricing decisions and profits within a competitive environment. Finally, a Monte-Carlo experiment is designed to analyze the impact of uncertain market risks on supplier's decisions. The results show that there is a two-sided matching mechanism that enables oligarchs and suppliers to obtain stable matching solution sets. Higher carbon prices lead to higher product prices, lower market demand, and improved environmental performance. Product price and market demand are positively correlated with investment volumes of oligarchs themselves and negatively correlated with those of their competitors. Investment risk has a certain negative impact on suppliers' profitability. [ABSTRACT FROM AUTHOR]

Towards the target of carbon neutrality, the need for deep decarbonization in iron and steel industry is increasingly recognized. Existing studies rarely mention the effects of collaboration with its source industries for carbon emission reduction in ISI. Furthermore, the fundamental laws of CO 2 emission reduction capacity with cost change of source substitutions for various steel production routes under market economics are unclear. To avoid the blind substitution of clean sources for meeting the urgent requirements for decarbonization in China's steel industry, which may result in increased carbon emissions and uneconomical carbon reduction from a lifecycle perspective. This paper integrates the production and utilization processes of source resources into the steel production process, establishes coupling models of carbon and value flows for four main types of steel production routes, and aims to quantitatively analyze the specific CO 2 emission reduction potential and costs. Three economic market development scenarios from 2021 to 2060 are set, and the marginal carbon prices of various source substitutions are determined. Subsequently, decarbonization pathways with the goal of minimizing production costs are developed. Finally. The future resource demand and the carbon emission reduction contributions of source industries collaborated are predicted. The results show that (1) about 81.7–89.9 % of CO 2 emissions could be reduced in the scenarios; (2) the demands of electric power and hydrogen energy will reach 54.48–511.90 BkWh and 7.47–10.31 Gt in 2060, respectively; and (3) collaboration with source industries could make 18.3–18.3% of CO 2 emission reduction contributions. All in all, this study could provide scientific support for the low-carbon transformation of China's steel industry. • Carbon and value flows of BF-BOF, Scrap-EAF, DRI-EAF, MOE-EAF routes are analyzed. • CO 2 emission reduction potential with marginal carbon price is determined. • Decarbonization paths during 2021–2060 for China's steel industry are developed. • Quantify the contribution of collaborative carbon reduction with source industries. [ABSTRACT FROM AUTHOR]

This paper presents an energy-sharing market coupled with carbon emission trading to quantify peer-to-peer energy-sharing markets' economic and environmental influences. We establish a bi-level peer-to-peer energy sharing market considering the interaction between energy prosumers and the system operator. An interaction algorithm and generalized Nash game are thus applied in this work. With the simulation results, we find that the daily disutility of provincial systems is reduced by about 7 ¥ when time-of-use electricity rates are applied. This pricing strategy can encourage prosumers to participate in energy-sharing transactions. The subsidies of electricity rates, carbon prices, and renewable energy investments can improve the social welfare of the whole system. Considering the development of power generation technology and emission reduction targets, the change of optimization parameters in the next 30 years is analyzed in the example. It can be concluded that the total CO2 emission in 2050 will be reduced to almost half of that in 2020 in the energy-sharing markets. The subsidy of renewable energy generation and stricter CO2 emission constraints may accelerate the reduction of carbon emissions. [Display omitted] • It is the first time to assess the environmental effect of peer-to-peer energy trading with actual data. • We analyze the peer-to-peer energy trading impacts on the carbon emission amount in China. • We compare the market participants' revenue and CO2 emission considering the different scenarios. • We develop a bi-level coupled emission right trading market to verify whether total emission is reduced. • The development of technologies and various energy structures are considered quantitatively. [ABSTRACT FROM AUTHOR]

Balancing environmental protection and economic development is critical in climate policy-making. The carbon trading policy is an important market-based climate strategy that aids in achieving the national carbon neutrality goals. However, empirical evidence at the industry level has not yet demonstrated whether there is an employment dividend. In this study, we constructed a theoretical framework to analyze the employment effects of carbon trading policies. We quantitatively evaluated the employment effects of policies in the pilot region using the differences-in-differences model. And we considered and explained the adjustment paths of employment dividends from the industry-level onwards. We found a "two-eight split" phenomenon in the employment effects of the carbon trading policy in China—the overall employment level of the region increases while employment in some regulated industries is inspired and it is hindered in others, shifting to other regulated industries and non-regulated regions. The empirical results revealed the following points. (1) After controlling economic and demographic factors, carbon trading policies can bring significant employment dividends to pilot areas. (2) While implementing such policies can improve the employment level of the paper industry, they can also seriously impact the employment development of the petrochemical and building materials industries. (3) Both energy consumption and technology levels effectively dampen the policy's negative employment effects and promote employment in the pilot areas. (4) The high carbon price levels within the range of carbon price fluctuation have inhibited the employment levels of the pilot industries. However, it still promoted the overall employment levels of the pilot areas through the employment transfer effect. As future carbon prices increase, the policy's regional employment dividend may decrease or disappear. Our findings illustrate the employment effect of industry-level carbon trading policies and provide a reference for improving carbon market construction. [ABSTRACT FROM AUTHOR]

Carbon emission trading mechanism is an important market-based instrument to address global climate change. The auction ratio and price of carbon emission allowances (CEA) are cores of the carbon emission trading mechanism. What combination of CEA auction ratio and auction price is most conducive to carbon emission reduction for emission control enterprises? There are still relatively few studies conducted on this issue, and there is no clear answer from the views of theory and practice. In this paper, the AIM/Enduse model was used to analyze the changes and differences of installed power capacity, power supply, energy consumption and carbon emissions in the Guangdong-Hong Kong-Macao Great Bay Area (GBA) with different combinations of CEA auction ratios and prices. Moreover, the best pathway of energy transition was explored in the power industry of the GBA, and the best combination of CEA auction ratios and prices was identified in the GBA. The results show that: (1)The carbon emission constraint starts to work only when the auction ratio of CEA is increased to 50% and the auction price is increased to 60 CNY/ton (Scenario p 3). When the auction ratio of CEA is 100% and the auction price reaches 120 CNY/ton (Scenario p 5), a low-carbon transition of the power sector in the GBA can be achieved. (2) Under scenario p 5 , the total cost of power transition rises and then falls. And the cost of carbon in the power sector increases exponentially as the auction ratio of CEA and the auction price rise. However, the growth in the cost of power supply is relatively flat, which shows that appropriate carbon trading mechanism can improve the economic benefits of power sectors. With the increase of installed capacity of clean low-carbon energy generation and power supply, as well as the decrease of local power cost in the GBA, the proportion of outsourcing power can be appropriately reduced in the future, with an aim to reduce the external dependence of electricity to ensure the security of energy supply. In the end, it suggests that cities in the GBA should give full play to their regional advantages and establish a unified carbon emission trading market in the GBA as soon as possible. This study provides a theoretical basis for the supplementation and improvement of China's carbon emission trading mechanism. • What is the best combinations of CEA auction ratios and auction prices in the GBA? This paper gives a clear answer. • The best transition pathway of the power industry under technological progress and carbon trading policy was suggested. • With the decrease of local power cost, the proportion of outsourcing power can be appropriately reduced in the future. • Provides a theoretical basis for the supplementation and improvement of China's carbon emission trading mechanism. [ABSTRACT FROM AUTHOR]

Emission trading scheme (ETS) is considered as a tool to reduce emissions at a low cost, which can effectively promote the carbon peak and carbon neutrality. As the main participants in the carbon emission trading (CET) market, the behavior and strategies for governments and different types of enterprises affect the final emission reduction performance. Taking the national carbon market as an example, this paper constructs a tripartite evolutionary game model including governments and power generation enterprises with different emission reduction capacity to analyze the possible game situations in the development process of the CET market. The results show that with the development of the CET market, the governments and power generation enterprises will have different game results. In order to achieve the optimal stable equilibrium and maximize carbon emission reduction, governments should improve regulatory efficiency and formulate appropriate incentive strategies for excess emission reduction and punishment strategies for insufficient emission reduction. In addition, the initial willingness will not affect the final strategy choice of the three parties. Reasonable free carbon quota ratio, lower technology emission reduction cost and higher carbon price can stimulate the enthusiasm of governments and enterprises to reduce emissions. The above results provide a reference for coordinating the relationships between governments and power generation enterprises with different emission reduction capacity in the construction of the CET market in the future. [ABSTRACT FROM AUTHOR]

Sharing resources and curbing emissions are critical for promoting the adoption of cleaner logistics technologies and improving environmental sustainability. However, little research has examined reducing the impact of carbon emissions on the environment by considering transfer between depots. Hence, this study investigated the impact of carbon emissions on a multi-depot collaborative pickup and delivery network with time windows and transfers (MDCPDPTW-Ts) and proposed a carbon emissions measurement to describe the relationship between fuel consumption and carbon emissions. Then, a two-stage heuristic framework was proposed to simplify MDCPDPTW-Ts and generate high-quality delivery routes. Finally, a case study from Dalian, China, was used to verify the effectiveness of the research methodology. The results demonstrated the following: (1) The multi-depot transfer network constructed in this paper is significantly better than the traditional no-transfer scheme, reducing the cost by 26.64%. (2) Sharing transfer facilities among different depots is the most attractive mode of realizing clean logistics, reducing the emission cost by 59.2% compared with the traditional depot-based transfer scheme. (3) Reasonable carbon prices and carbon quotas are highly significant to establishing a sustainable carbon trading market. As carbon prices increase, carbon emissions first show a sharp reduction trend and then gradually tend to remain unchanged. Therefore, this work can provide practical and theoretical implications for the sustainable development of multi-depot collaborative logistics. [Display omitted] • Transfer locations reduce complexity of the multi-depot collaboration system. • Adaptive iterated local search improves quality of solutions. • Minimizing transportation cost simultaneously reduces fuel and carbon emissions. • The proposed transfer scheme has lower emissions than the traditional scheme. • Carbon quotas and prices to conserve energy and curb emissions are discussed. [ABSTRACT FROM AUTHOR]