Search Results (16)

Mangrove forests support coastal resilience, biodiversity, and significant carbon sequestration, yet they face escalating threats from climate change, urban expansion, and land-use change. Traditional remote sensing workflows often struggle with large data volumes, complex preprocessing, and limited computational resources. Google Earth Engine (GEE) addresses these challenges through scalable, cloud-based computation, extensive, preprocessed imagery catalogs, built-in algorithms for rapid feature engineering, and collaborative script sharing that improves reproducibility. To evaluate how the potential of GEE has been harnessed for mangrove research, we systematically reviewed peer-reviewed articles published between 2017 and 2022. We examined the spectrum of GEE-based tasks, the extent to which studies incorporated mangrove-specific preprocessing, and the challenges encountered. Our analysis reveals a noteworthy yearly increase in GEE-driven mangrove studies but also identifies geographic imbalances, with several high-mangrove-density countries remaining underrepresented. Although most studies leveraged streamlined preprocessing and basic classification workflows, relatively few employed advanced automated methods. Persistent barriers include limited coding expertise, platform quotas, and sparse high-resolution data in certain regions. We outline a generalized workflow that includes automated tidal filtering, dynamic image composite generation, and advanced classification pipelines to address these gaps. By synthesizing achievements and ongoing limitations, this review offers guidance for future GEE-based mangrove studies and conservation efforts and aims to improve methodological rigor and maximize the potential of GEE. Full article

Farmer professional cooperatives are the focus objects of agricultural carbon emission reduction; with the use of the advantages of scale economy and technology, one can promote the development of low-carbon agriculture. In order to study the influencing factors of agricultural carbon emission reduction on farmer professional cooperatives, we explore the interaction effects of carbon emission reduction behavior between farmer professional cooperatives and farmers under government interventions. This paper introduces a carbon transaction mechanism as well as reward and punishment polices into a tripartite evolutionary game model between farmer professional cooperatives, governments, and farmers. Based on the model, we identify a stable evolution strategy and perform simulation analysis. The results indicate that the carbon transaction mechanism can effectively suppress the negative effect of increased costs through higher revenues of the carbon transaction, and carbon prices above 60 CNY/ton enable cooperatives to reduce regional emissions. Higher revenues can promote positive carbon emission reduction behaviors of farmer professional cooperatives and farmers. The sharing ratio increases from 20% to 80%, and farmers gain additional benefits by cooperating in the farmer professional cooperative practices to reduce emissions. Rational regulation of carbon transaction price and quota can promote the participation of farmer professional cooperatives in carbon emission reduction practices and promote the farmers’ inclusion into farmer professional cooperatives. Full article

Carbon asset management has become an important way to reduce carbon costs. There are three main carbon asset management modes, including carbon quota compliance, carbon asset autonomous management, and custody. A key challenge faced by capital-constrained enterprises is how to scientifically select a carbon asset management mode based on actual needs. This paper considers the impacts of setup costs of carbon asset management departments, carbon asset appreciation, custody costs, and revenue sharing, maximizes the enterprises’ profits, develops optimization models for three modes, and provides the optimal low-carbon production strategies. This paper provides evidence for enterprises to choose optimal modes under different capital levels and carbon emissions by comparing modes. The conclusions are as follows. When setup costs are low, the carbon asset autonomous management mode is suggested for the optimal profit. With higher setup costs, either carbon asset compliance or custody mode is recommended. Under abundant capital, the carbon asset custody mode is suggested. Given a certain amount of capital and low setup costs, high-emission enterprises are encouraged to adopt the carbon asset autonomous management mode for a win–win of profits and carbon emissions. The carbon asset custody and compliance modes are suggested for medium-emission and low-emission enterprises, respectively. 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

To better construct an energy consumption model for the asphalt mixture production stage, this study divides the production process into four phases: aggregate dust removal, aggregate drying, asphalt heating, and mixture blending. Utilizing measured data from various regions in Anhui Province, the model considers factors such as season, mixture type, and energy consumption type. The study quantitatively compares and analyzes the energy consumption results obtained from three calculation methods: the theoretical method, the quota method, and the energy consumption model method. The results indicate that the total energy consumption shares of the aggregate dust removal, aggregate drying, asphalt heating, and mixture blending phases are 4.23%, 69.50%, 17.75%, and 8.52%, respectively. The primary energy consumption during the asphalt mixture production stage is concentrated in the aggregate drying and asphalt heating phases. The energy consumption model based on on-site measurements effectively reflects the actual energy consumption levels during the asphalt mixture production stage. Moreover, the total energy consumption calculated by the three methods follows the order quota method > energy consumption model method > theoretical method. By constructing an energy consumption model based on measured data, it is possible to more accurately assess the energy usage during the asphalt mixture production process. This helps optimize production techniques, reduce energy consumption and carbon emissions, and provide a scientific basis for sustainable road construction. Full article

The forestry carbon offset policy has been implemented for a short time, and in order to study its optimization mechanism and pressure-sharing emission reduction effect, this paper applies the directional distance function to calculate the marginal abatement cost of each province/city based on the panel data of 30 provinces/cities in China from 2000 to 2020. Then, we utilize the synthetic control method to analyze the forestry carbon offset policy by taking Beijing, Guangdong, and Fujian as a natural experiment. Finally, placebo tests and differences-in-differences tests were used to verify the experiment’s effectiveness. The study has the following results. (1) The forestry carbon offset policy is a Pareto improvement after integrating multiple benefits. The proportion of FCS offset should be increased, and government subsidies should be reduced when carbon quotas are tightened, followed by the gradual inclusion of more industries and enterprises in the scope of mandatory emission reductions. (2) The impact of forestry carbon offset policy on sharing the abatement pressure has regional heterogeneity, which is affected mainly by geographical location, economic level, and industrial structure. It can be obtained that the forestry carbon offset policy has shared the pressure for emission reductions in Guangdong and Fujian. This study provides a theoretical basis for promoting forestry carbon offset policies and their coupling with other carbon-reduction policies. Full article

As is well known, limiting carbon emissions is an important link in mitigating global climate change. Carbon quotas are a widely used policy tool by governments around the world without increasing the financial burden on the government. To study the impact of carbon quota policies on the clean transformation of the key carbon emitting industry—the power industry, we established a duopoly model and conducted an analysis and numerical simulation. The research has found that the effectiveness of carbon quota policies is closely related to the level of competition within the power supply chain and is also influenced by the market share of clean energy power generation enterprises. Moreover, in some cases, it may have the opposite effect. Full article

In order to maximize the utilization efficiency of renewable energy resources and reduce carbon costs in multi-park integrated energy systems (MIESs), this paper proposes an electricity–carbon energy scheduling method for MIESs, where a electricity–carbon joint trading market is established to allow energy interactions between IESs so as to satisfy their energy deficiencies and surpluses. Simultaneously, through leveraging differences in carbon prices among regions, carbon quotas are shared between all IESs, thereby reducing the overall carbon trading costs within the region. The paper also suggests that to encourage carbon cooperation between IESs, incentive measures such as government subsidies could be provided to foster collaboration. The simulation results demonstrate that the proposed electricity–carbon energy scheduling method for MIESs can effectively improve the utilization flexibility of various energy resources and obtain the higher economic benefits, compared with the traditional method where each IES operates independently. Full article

This paper studies the impact of diverse carbon emission regulations on optimal operation decisions by exploiting the economic production lot model of a multi-manufacturer system in a low-carbon environment. The optimal production planning for multiple enterprises in terms of cost optimization and carbon emission optimization are presented in various scenarios of the fully decentralized system under carbon taxation, cap and trade, and mandatory carbon cap. We prove a unified framework for modeling the scenarios enabled by carbon tax and cap-and-trade policies. Furthermore, the decision vector of the optimal production lot is obtained by analyzing the joint decision scenario based on shared carbon emission caps. We give a comparative analysis of two settings of fully decentralized and carbon quota sharing. The results show that the decision of joint production and stock preparation can reduce the total operational costs of the multi-enterprise system, but the realized carbon emissions may not change or only increase slightly. Our study provides a useful reference for government carbon emission regulation and enterprise operation decision optimization under carbon neutrality and a carbon peak environment. Full article

Under the background of a circular economy, this paper examines multi-tiered closed-loop supply chain network competition under carbon emission permits and discusses how stringent carbon regulations influence the network performance. We derive the governing equilibrium conditions for carbon-capped mathematical gaming models of each player and provide the equivalent variational inequality formulations, which are then solved by modified projection and contraction algorithms. The numerical examples empower us to investigate the effects of diverse carbon emission regulations (cap-and-trade regulation, mandatory cap policy, and cap-sharing scheme) on enterprises’ decisions. The results reveal that the cap-sharing scheme is effective in coordinating the relationship between system profit and carbon emission abatement, while cap-and-trade regulation loses efficiency compared with the cap-sharing scheme. The government should allocate caps scientifically and encourage enterprises to adopt green production technologies, especially allowing large enterprises to share carbon quotas. This study can also contribute to the enterprises’ decision-making and revenue management under different carbon emissions reduction regulations. Full article

To mitigate climate change, the governments of various countries have formulated and implemented corresponding low-carbon emission reduction policies. Meanwhile, consumers’ awareness of the necessity of environmental protection is gradually improving, and more consumers pay attention to the environmental attributes of products, which all encourages enterprises to have great power to implement low carbon technology. As rational decision makers, members tend to show the characteristics of risk aversion. How to meet the needs of consumers and reduce their own risks has become a key point of low-carbon supply chain management. Considering carbon quota policy, in this paper, the optimal pricing decision-making process of a supply chain system is discussed under risk-neutral and risk-avoidance decision-making scenarios by game theory, and a cost-sharing contract is used to coordinate the decision-making process of a supply chain system. By analyzing the influence of the risk aversion coefficient on the optimal strategies of participants, we find that when the manufacturer has the risk aversion characteristic, the risk aversion coefficient will further reduce the carbon emission rate, the wholesale price of the product and the manufacturer’s profit but increase the product order quantity and the retailer’s profit. In addition, if consumers have a high preference for low-carbon products, the manufacturer’s risk-aversion coefficient will lead to a lower selling price than in the centralized decision-making situation, and the profit of the supply chain system will also be further reduced. When the cost-sharing contract is adopted for coordination, the Pareto improvement of supply chain members’ profits can be achieved when the parameters of the cost-sharing contract are appropriate, regardless of the manufacturer’s risk-neutral decision or risk-aversion decision. Full article

The paper analyzes the main issues of power market development for clean energy production within the broader framework of ensuring the country’s energy security. In addition, special attention is paid to the technologies aimed at reducing emissions of toxic substances and greenhouse gases by the fossil-fired power plants. Even though the future electricity markets would most likely depend on the high shares of renewable energy sources (RES) in the electricity system, energy efficiency such as the one based on the near-zero emission technologies might also play a crucial role in the transition to the carbon-free energy future. In particular, there are the oxy-fuel combustion technologies that might help to reduce the proportion of unburned fuel and increase the efficiency of the power plant while reducing the emissions of flue gases. Our paper focuses on the role and the place of the near-zero emission technologies in the production of clean energy. We applied economic and mathematical models for assessing the prospects for applying oxy-fuel combustion technology in thermal power plants, taking into account the system of emission quotas and changes in the fuel cost. Our results demonstrate that at the current fuel prices, it is advisable to use economical combined cycle gas turbines (CCGT). At the same time, when quotas for greenhouse gas emissions are introduced and fuel costs increase by 1.3 times, it becomes economically feasible to use the oxy-fuel combustion technology which possesses significant economic advantages over CCGT with respect to the capture and storage of greenhouse gases. Full article

Industrial companies are responsible for most of the energy consumption and carbon emissions in China’s urban agglomerations. Some scholars have allocated CO₂ emissions to China’s industrial sectors in reaching national reduction targets, yet industrial sectors’ burden-sharing problem for carbon mitigation at the provincial level has not been well addressed. Given the goal of realizing China’s national carbon mitigation target by 2030, we applied a nonlinear quota allocation model to obtain the optimal allocation of emission reduction quotas among 37 industrial sectors in the Jing-Jin-Ji urban agglomeration in China (comprising Beijing, Tianjin, and Hebei). Compared to Beijing and Tianjin, the secondary industry in Hebei bears the highest reduction responsibilities, given that Hebei will experience the largest carbon emissions, at 0.42 billion tons in 2030, which is 80.04% of the total emissions in the Jing-Jin-Ji urban agglomeration. Energy production and heavy manufacturing sectors serve as the major carbon emitters and have relatively high carbon intensities, which indicates that they have significant potential and major responsibilities for impacting carbon mitigation. Based on differences in urban function and development mode, the same industrial sectors in the three provinces have different obligations for emission reductions. This study is vital to allocate reduction responsibilities among industrial sectors and to discrete key sector categories bearing a higher mitigation burden. Full article

The initial allocation of carbon emission quotas should be of primary concern when establishing China’s unified carbon emission trading market. Essentially, the issue of national carbon quota allocation is an allocation among China’s provinces. The novel bi-level allocation scheme that is based on weighted voting model is put forward, which divides allocation process into two levels, given that there are great regional differences in China. At the first level, k-means clustering is employed to cluster 29 provinces into four categories that are based on emission abatement responsibility, potential, capacity, pressure, and motivation. Subsequently, the national carbon quotas are allocated to the four classes. At the second level, carbon quotas of a class are allocated to each region in this class. The weighted voting models are constructed for the two levels, where each region selects their preferable scheme from three fundamental allocation schemes that are based on their voting rights. The comprehensive index method quantifies each region’s voting rights, which utilizes the information entropy method at the first level and the analytic hierarchy process (AHP) at the second level. The carbon trading market is simulated and welfare effects obtained from carbon trading market under different allocation schemes are measured to verify the rationality of the proposed model. The results indicate: (1) the emission abatement burdens are borne by all provinces in China, but the burden shares are different, which are related to their respective carbon emission characteristics. (2) The differences in carbon intensity among regions in 2030 have narrowed on the basis of the results of 2005, which means that the proposed scheme can balance corresponding differences. (3) When compared with three fundamental allocation schemes, the bi-level allocation scheme can obtain the most welfare effects, while the differences in the welfare effect among regions under this scheme are the smallest, which indicates that the proposed model is feasible for policy-maker. Full article

This research studied the duopoly manufacturers’ decision-making considering green technology investment and under a cap-and-trade system. It was assumed there were two manufacturers producing products which were substitutable for one another. On the basis of this assumption, the optimal production capacity, price, and green technology investment of the duopoly manufacturers under a cap-and-trade system were obtained. The increase or decrease of the optimal production quantity of the duopoly manufacturers under a cap-and-trade system was decided by their green technology level. The increase of the optimal price as well as the increase or decrease of the maximum expected profits were decided by the initial carbon emission quota granted by the government. Our research indicates that the carbon emission of unit product is inversely proportional to the market share of an enterprise and becomes an important index to measure the core competitiveness of an enterprise. Full article