Search Results (40)

Between 2013 and 2020, China had implemented a pilot cap-and-trade carbon emissions trading system (ETS) in some cities. Previous research has reported that this policy significantly reduces air pollution in the policy-implementing districts. However, whether and to what extent there are spatial spillover effects of this policy on air pollution in other regions has not been sufficiently analyzed. The research objective of this study is to quantitatively assess the spatial spillover effects of China’s carbon ETS on air pollution. Based on data from 288 Chinese cities between 2005 and 2020, this study employs a multiple linear regression approach to estimate the policy effects. Our study finds that the policy significantly reduces the concentrations of black carbon (BC), nitrogen dioxide (NO₂), organic carbon (OC), particulate matter less than 1 micron in size (PM₁), fine particulate matter (PM_2.5), and particulate matter less than 10 microns in size (PM₁₀) in non-ETS regions. This indicates that the carbon ETS has beneficial impacts on air quality beyond the areas where the policy was implemented. The heterogeneity tests reveal that the beneficial spatial spillover effects of the ETS can be observed across cities with different levels of industrialization, population density, economic development, resource endowments, and geographical locations. Further mechanism analyses show that although the policy does not affect the degree of environmental regulation in other regions, it promotes green innovation, low-carbon energy transition, and industrial structure upgrading there, which explains the observed spatial spillover effects. Full article

Promoting carbon emission reduction in road freight transportation is important to achieve low-carbon development. The carbon trading mechanism is an effective market mechanism to promote carbon emission reduction. The digital and networked features of the online freight platform (OFP) service supply chain (SSC) not only help the platform reduce carbon emissions but also facilitate the government’s achievement of efficient and economic supervision of carbon emissions. Therefore, this paper proposes two types of carbon trading mechanism based on the OFP SSC to investigate the carbon emission reduction decision of the OFP, namely an absolute emission cap-based allocation (AC) model and an intensity-based allocation (IC) model. By using game theory, we then analyze the optimal solutions of the OFP SSC under the non-participation in carbon trading market (NC model), the AC model, and the IC model. By comparing these decisions, we explore the impact of the carbon trading mechanism on the OFP SSC. Results show the following: (1) Carbon trading mechanisms reduce OFP emissions, particularly under IC models with high free allowances. (2) High initial allowances and low service costs under the carbon trading mechanism enhance the OFP’s profit. (3) The carbon trading mechanism can reduce the carbon emissions of the road freight sector when initial allowances are sufficient or the off-platform trucker’s carbon emission coefficient is low. The study concludes that the IC model optimizes emission cuts while maintaining platform profitability. From a managerial perspective, the government should adopt dynamic allowance policies and incentivize the OFP’s participation through data integration. OFPs must balance network growth with low-carbon technology adoption to align commercial and environmental objectives. Full article

This study examines the price dynamics of the UK Emission Trading Scheme (UK ETS) by integrating advanced computational methods, including deep learning and statistical modelling, to analyze and simulate carbon market behaviour. By analyzing long-memory effects and price volatility, it assesses whether UK carbon prices align with theoretical expectations from carbon pricing mechanisms and market efficiency theories. Findings indicate that UK carbon prices exhibit persistent long-memory effects, contradicting the Efficient Market Hypothesis, which assumes price movements are random and fully reflect available information. Furthermore, regulatory interventions exert significant downward pressure on prices, suggesting that policy uncertainty disrupts price equilibrium in cap-and-trade markets. Deep learning models, such as Time-series Generative Adversarial Networks (TGANs) and adjusted fractional Brownian motion, outperform traditional approaches in capturing price dependencies but are prone to overfitting, highlighting trade-offs in AI-based forecasting for carbon markets. These results underscore the need for predictable regulatory frameworks, hybrid pricing mechanisms, and data-driven approaches to enhance market efficiency. By integrating empirical findings with economic theory, this study contributes to the carbon finance literature and provides insights for policymakers on improving the stability and effectiveness of emissions trading systems. Full article

The transition to low-carbon economies presents unique challenges for emerging markets, particularly in developing effective carbon pricing mechanisms that balance environmental objectives with economic development needs. This study examines the ratio legis of carbon pricing policies through a comparative analysis of China and South Korea’s established systems, utilizing the FASTER (Fairness, Alignment, Stability, Transparency, Economic efficiency, Reliability) principles evaluation framework. Using qualitative doctrinal methodology integrated and comparative policy analysis legislative frameworks and market data from 2015–2023, this paper examines Malaysia as a representative case study wherein carbon market initiatives remain in voluntary phase with approximately 150,000 carbon credits traded. The comparative results demonstrate that a choice between China’s intensity-based approach and South Korea’s absolute cap system should be guided by the following: (1) development stage, with industrializing economies benefiting from China’s flexible model; (2) institutional capacity, where limited monitoring capabilities favor phased approaches; (3) economic structure, with emissions-intensive economies requiring growth-accommodating systems; (4) policy landscape complexity; and (5) market size. The research proposes a structured implementation framework for emerging markets, demonstrated through Malaysia’s context, that enables effective emission reduction while maintaining economic competitiveness during the transition to low-carbon economies. Full article

With the rapid growth of global energy demand, the fossil fuel-dominated electric power industry has led to serious environmental problems. Tradable green certificates (TGC) and carbon emission trading (CET) have become key mechanisms for promoting sustainable development of the electricity market by serving as market-oriented policy tools. To deeply analyze the impact of TGC and CET on the sustainable development of China’s electricity market and provide a scientific basis for policymakers. This study uses system dynamics (SD) methods to construct a policy synergy analysis framework for TGC and CET. It explores the impact mechanism of dual policy incentives on the sustainable development of the electricity market. Firstly, the current application status of TGC and CET in China was reviewed. Based on the literature analysis, identify key factors that affect the sustainable development of the electricity market. Then, by deconstructing the interaction between TGC policy and CET policy, an SD model was established that includes multidimensional feedback such as policy, technology, funding, and market, and the dynamic functional relationships in the SD model were quantified. Finally, Vensim PLE software 7.3.2 was used to simulate the evolution of sustainable development in the electricity market under different policy scenarios. The research results indicate that (1) the adjustment of the TGC quota ratio can change the supply and demand mechanism to form a price leverage effect, effectively stimulate the growth of renewable energy generation capacity, and accelerate the low-carbon transformation of power enterprises; and (2) the CET market changes the cost structure of power generation through carbon price signals. When the carbon emission cap target tightens, CET prices quickly rise, leading to a significant trend of carbon reduction in the electricity market; (3) the application of policy combinations can significantly promote the sustainable development of the electricity market, but the unreasonable setting of policy parameters can trigger market risks. Therefore, policy design should focus on flexibility and implement appropriate policy combinations at different stages of electricity market development to promote green transformation while ensuring smooth market operation. This study innovatively reveals the synergistic effect of TGC and CET in the sustainable development of the electricity market from a systems theory perspective. The research results provide a scientific basis for decision-makers to formulate policy adjustment plans and have essential reference value for achieving the dual goals of energy structure transformation and electricity market stability. Full article

To address environmental challenges, governments globally have implemented a range of carbon reduction policies. Based on their mechanisms of action, this study categorizes these policies into regulatory (e.g., carbon taxes and cap-and-trade) and supportive measures (e.g., production cost subsidies, low-carbon technology subsidies, and low-carbon product subsidies). By integrating these approaches, six distinct policy combinations were identified. A supply chain network equilibrium model, incorporating manufacturers, retailers, and demand markets, was developed using variational inequality theory to assess the effectiveness of these combinations. Numerical simulations were conducted with a modified projection algorithm, and the Borda method was applied to evaluate equilibrium outcomes, specifically production levels and emission reductions, under each policy combination, revealing synergies between policies. The analysis revealed three key findings: (1) Among supportive policies, the combination of low-carbon product subsidies with regulatory policies is the most effective, while production cost subsidies are relatively weaker; (2) carbon tax policies combined with supportive policies outperform carbon trading; (3) a higher intensity of regulatory policies enhances the incentive effects of supportive policies. This research offers valuable guidance for governments seeking to design evidence-based policy portfolios that effectively balance emission reduction goals with economic development priorities. Full article

Cap-and-trade is widely recognized as an effective mechanism for curbing carbon emissions, and it significantly influences the operational decisions within supply chains. This study investigates a three-echelon closed-loop supply chain (CLSC) consisting of one original equipment manufacturer, one traditional retailer, and one independent third-party collector. The manufacturer invests in cleaner technologies to produce green products and remanufactures new products from used items recycled by the third-party collector. Considering different channel power structures, three Stackelberg game models are developed, and their optimal solutions are derived using the backward induction. Additionally, the combined effects of remanufacturing-related and carbon-related parameters on economic and environmental benefits as well as social welfare are investigated under different settings. Moreover, the derived results are validated via numerical simulation. The findings indicate that: (1) Each channel member is incentivized to act as the leader role within the CLSC to maximize profits. (2) A loose cap-and-trade regulation is conducive to enhancing the emission abatement rate, collection rate, and overall performance for the CLSC. (3) The retailer-led model is the best option for capturing more economic benefits and social welfare, while the third party-led model can always achieve the best environmental performance regardless of carbon trading price. These research findings can provide valuable insights for policymakers and decision makers engaged in CLSC. Full article

The global pursuit of carbon neutrality requires the reduction of carbon emissions in logistics and distribution. The integration of electric vehicles (EVs) and drones in a collaborative delivery model revolutionizes last-mile delivery by significantly reducing operating costs and enhancing delivery efficiency while supporting environmental objectives. This paper presents a cost-minimization model that addresses transportation, energy, and carbon trade costs within a cap-and-trade framework. We develop a multi-depot mixed fleet, including electric and fuel vehicles, and a drone collaborative delivery routing optimization model. This model incorporates key factors such as nonlinear EV charging times, time-dependent travel conditions, and energy consumption. We propose an adaptive large neighborhood search algorithm integrating spatiotemporal distance (ALNS-STD) to solve this complex model. This algorithm introduces five domain-specific operators and an adaptive adjustment mechanism to improve solution quality and efficiency. Our computational experiments demonstrate the effectiveness of the ALNS-STD, showing its ability to optimize routes by accounting for both spatial and temporal factors. Furthermore, we analyze the influence of charging station distribution and carbon trading mechanisms on overall delivery costs and route planning, underscoring the global significance of our findings. Full article

The carbon quota trading mechanism is considered one of the most effective incentives for carbon reduction to address global climate change. Currently, the EU has adopted this mechanism to intervene in the zero-carbon transition of shipping companies. Unlike other businesses, the shipping market experiences cyclical changes and high uncertainty, with many factors and complex systems involved in the zero-carbon transition process. Research on the impact of dynamic penalty mechanisms combined with government incentive policies on the zero-carbon transition of shipping companies is relatively scarce. To explore this process under such mechanisms, an evolutionary game model of shipping companies’ zero-carbon transition considering dynamic penalties and carbon quota trading was constructed. The model analyzes the effects of factors such as carbon trading prices, emission reductions resulting from zero-carbon transition, government supervision costs, supervision intensity, subsidy values, and penalty caps on the transition process and performs a simulation analysis. The results indicate the following: (1) Under dynamic penalty mechanisms, the evolutionary trajectories of both government and shipping companies spiral towards a unique evolutionary stable strategy, addressing the shortcomings of static penalty mechanisms. (2) Government supervision costs negatively impact the zero-carbon transition of shipping companies, while supervision intensity has a positive effect. Government subsidies positively affect transition strategies but have a minor impact. Increasing the penalty cap benefits the zero-carbon transition of companies. (3) There is a critical point for carbon trading prices corresponding to changes in zero-carbon transition strategies, providing a basis for companies to decide whether to buy or sell carbon emission trading rights. Additionally, government regulatory changes lag behind the changes in companies’ zero-carbon transition behaviors. The results provide significant insights for government strategy formulation and investment in zero-carbon transition under the carbon quota trading mechanism. Full article

This is the first review study that focuses on the interplay between China’s regulated and voluntary carbon markets, the Emissions Trading System (ETS), the China Certified Emission Reduction (CCER) scheme, and their combined influence on the development of renewable energy in the country. Through a comparative literature review of 52 peer-reviewed academic papers published between 2009 and 2024, this study aims to elucidate how these market mechanisms interact to drive renewable energy deployment. The findings indicate that both the ETS and the CCER system positively affect China’s renewable energy landscape. The ETS, with its Cap-and-Trade (CaT) mechanism, sets a cap on total emissions and allows for the trading of emission quotas, thereby creating financial incentives for companies to reduce emissions and invest in renewable energy. The CCER scheme complements the ETS by allowing companies to use the CCER scheme for a capped share of their ETS certificates, whereby the lower CCER price diverts investments to where the saved ton of CO₂ in China is cheapest, further incentivizing investments in renewable energy. This dual mechanism allows for a more flexible and cost-effective approach to achieving emission reduction targets, thereby fostering an environment conducive to investment in renewable energy. It will stimulate additional investment in renewable energy projects in the long run, particularly in economically underdeveloped regions, contributing to both local economic development and national emission reduction targets. Full article

Based on different carbon quota trading mechanisms, the price and emission reduction strategies of oligopoly manufacturers in the low-carbon market and the government carbon quota mechanism are considered. A dynamic game evolution model of the two oligopoly manufacturers with competitive relations is established. The stability of the equilibrium point of the game model, the price adjustment speed of the decision variable, the impact of carbon emission reduction investment, and the government carbon quota on the system are discussed. Through nonlinear dynamics research, it is found that the advantage of the grandfathering method is that it is conducive to maintaining market stability when the government’s carbon quota decision changes; the advantage of the benchmarking method is that when manufacturers formulate price adjustment strategies, the benchmarking method carbon quota mechanism has a stronger stability range for the market, the manufacturer’s profit price adjustment speed is positively correlated, and the government carbon quota decision and emission reduction investment are also positively correlated. Decision makers need to choose appropriate carbon quota mechanisms and manufacturers’ emission reduction strategies according to actual market changes to maintain supply chain stability. Full article

To address the growing demand for green development, governments worldwide have introduced policies to promote a green economy. Among these policies, the carbon cap-and-trade mechanism is adopted as an effective approach to control carbon emissions. Additionally, blockchain may increase transparency in the industrial process. Despite focusing on improving its own green standards, the supply chain needs to establish stable cooperative relationship. Thus, we focus on a supply chain consisting of a dominant manufacturer and a retailer, where the manufacturer opts for implementing blockchain and the retailer selects their stance on fairness. We construct a Stackelberg game model and use backward induction to obtain the equilibrium solutions. In the supply chain, the highest profits can be achieved when the manufacturer adopts blockchain technology, provided that the cost of application is relatively low. For manufacturer and retailer, when the cost of applying blockchain is relatively low, they can both obtain maximized profits without applying blockchain and the retailer does not have fairness concerns. However, as the cost of inducing blockchain and the product’s reduction in carbon emission increase, the optimal strategies for manufacturer and retailer begin to diverge, which may affect the stability of the supply chain. Full article

As global climate change intensifies, nations around the world are implementing policies aimed at reducing emissions, with carbon-trading mechanisms emerging as a key market-based tool. China has launched carbon-trading markets in several cities, achieving significant trading volumes. Carbon-trading mechanisms encompass cap-and-trade markets and voluntary markets, influenced by various factors, including policy changes, economic conditions, energy prices, and climate fluctuations. The complexity of these factors, coupled with the nonlinear and non-stationary nature of carbon prices, makes forecasting a substantial challenge. This paper proposes a dynamic weight hybrid forecasting model based on a dual sliding window approach, effectively integrating multiple forecasting models such as LSTM, Random Forests, and LASSO. This model facilitates a thorough analysis of the influences of policy, market dynamics, technological advancements, and climatic conditions on carbon pricing. It serves as a potent tool for predicting carbon market price fluctuations and offers valuable decision support to stakeholders in the carbon market, ultimately aiding in the global efforts towards emission reduction and achieving sustainable development goals. Full article

Canadian provinces are required to regulate their power sectors using carbon pricing systems that meet national minimum stringency standards, which are set by the federal government. A diverse set of systems has emerged as a result. However, there has been limited assessment of how different pricing mechanisms impact the evolution of Canada’s electricity system. To address this gap, we use an electricity system planning model called COPPER and a scenario-based approach to assess if, and to what extent, different policy regimes impact power sector greenhouse gas emissions and costs. Our results show that carbon pricing systems currently in place lead to significant carbon reductions over the long term, provided that free emissions allocations are reduced. However, the cost-optimal pathway for the power sector differs across provinces depending on the carbon pricing mechanism. Some provinces achieve least-cost emissions reductions by switching from high-carbon technologies to renewables, while others are better served by replacing high-carbon technologies with low-carbon fossil fuel alternatives. Further, provinces that implement cap-and-trade systems may affect the transitions of interconnected jurisdictions. Power sector climate policy design should reflect the heterogeneity of available assets, resources, and neighbouring approaches. Full article

The development of e-commerce and the green economy has prompted suppliers of green products to introduce internet channels by which products are directly sold to consumers. However, the emergence of “price wars” and “free riding” between the two channels after the introduction of online channels may affect the stability of the green supply chain. This paper uses optimization theory to investigate the impact of service spillover effects and different channel structures on the optimal decision of supply chain members in a Stackelberg game. By comparing the equilibrium outcomes of the single-channel and dual-channel supply chain in a setting with and without retail services, we observe that the supplier prefers to encroach on the market when services that retail locations provide largely spillover to and benefit the direct sales channel. Contrary to popular belief, a higher degree of service spillovers is beneficial for the retailer to achieve more returns under the dual-channel structure, whereas supplier encroachment will lead to a decline in the service level if the spillover degree is relatively low. In addition, the emission reduction level of products under supplier encroachment is always higher than that employed in the single-channel structure if consumers have both low-carbon preference and a high degree of service sensitivity. Finally, we expand our discussion by introducing the carbon cap-and-trade (CCT) mechanism to compare the conditions for achieving Pareto improvement under supplier encroachment. These results can provide helpful insights for decision-makers in supply chain management to implement effective channel selection and achieve sustainable development. Full article