Search

With breakthroughs in big data, communication networks, artificial intelligence, and other next-generation information technologies, intelligent production methods and digital lifestyles have risen rapidly. Digital economy has become a significant force in promoting regional low-carbon development as a new economic form in the important period of the intersection of digitalization and "carbon peaking and carbon neutrality goals." This paper empirically explores the moderating role and threshold role of human capital in digital economy and regional carbon productivity by systematically measuring digital economy indicators. Research shows that China's digital economy development index is rising annually. However, the development of digital economy varies significantly between different regions. The results of moderating effect showed that human capital accumulation could dramatically strengthen the role of digital economy in promoting regional carbon productivity. The results of the threshold effect showed that human capital plays an important threshold role in the relationship between digital economy and regional carbon productivity. This paper provides a practical reference for exploring power sources, policy design, and path selection of low-carbon development. [ABSTRACT FROM AUTHOR]

China's rural energy consumption structure has dominated by coal, and carbon dioxide emissions are relatively large. Under the dual historical responsibilities of the carbon peak, the carbon neutral dual-carbon, and the rural revitalization strategy, the rural energy transition is imminent. This paper conducts an in-depth study on the green entrepreneurship of migrant workers returning to their hometowns and carefully analyzes the factors affecting the return of migrant workers to green entrepreneurship. This paper establishes a regression model to clarify that the green entrepreneurial guidance mechanism can effectively increase entrepreneurial opportunities, promote the rational allocation of regional resources, increase the success rate of entrepreneurship, and promote the construction of new rural areas in China with proper healthcare. The implementation of the scientific guidance mechanism for migrant workers' green entrepreneurship should adhere to the scientific development concept, correctly guide farmers to return to their hometowns to start businesses, and provide them with a green channel for fiscal taxation. Green entrepreneurship can improve the entrepreneurial ability of migrant workers in order to effectively increase the success rate of migrant workers in entrepreneurship, ensure the rational use of regional resources, and promote the harmonious and stable development of society. [ABSTRACT FROM AUTHOR]

With the rapid development of the economy, carbon neutral and carbon peak are on the agenda in China, and the reform of intelligent construction and assembly building is in full swing in the Chinese construction industry. In order to further explore and study the relationship between the textural structural issues of the envelope structure and the overall energy consumption situation of the house, and further bridge the gap between the actual energy-saving design scheme and the actual application scheme, therefore, this paper takes a certain place as a research object to study the phenomenon of design assembly energy saving, based on dozens of assembly building enterprises researched, selected samples of envelope components studied, selected BIM technology for premodeling optimization, used neural network algorithm for analysis of influencing factors, and studied the application in the study of energy-saving optimization of assembly building envelope in the western Sichuan plain area, and used OpenStudio was used to build a model to simulate the heating and air conditioning load of the assembled building numerically and to fit the quantitative relationship between the variable factors and the building energy consumption. On this basis, the relationship between multifactor and single-factor variables is identified and evaluated using relevant variables means. [ABSTRACT FROM AUTHOR]

This paper carries out the quasi-natural experiment on China's carbon emissions trading pilot policy to assess the impact of China's carbon emissions trading pilot policy on the export product quality of enterprises in the pilot areas by using the data of listed companies and China Customs, and employing the DDD method. Meanwhile, it analyzes the heterogeneity of the impact under different ownership attributes and energy-intensive attributes of enterprises. The empirical results are as follows. First, due to the implementation of the carbon emissions trading pilot policy, the enterprises in the included industries bear the emission reduction cost. The export product quality of the enterprises in the included industries in the pilot areas is negatively affected compared with that of nonincluded enterprises in the nonpilot areas. Second, the impact of the carbon emissions trading pilot policy on the export product quality of enterprises may be heterogeneous due to the different ownership attributes of enterprises. The carbon emissions trading pilot policy significantly reduces the export product quality of non-state-owned enterprises, but has no significant effect on state-owned enterprises. Third, the impact of the carbon emissions trading pilot policy on the export product quality of enterprises is heterogeneous due to different energy-intensive attributes of enterprises. The carbon emissions trading pilot policy significantly reduces the export product quality of enterprises in energy-intensive industries, but it does not have a significant impact on enterprises in non-energy-intensive industries. [ABSTRACT FROM AUTHOR]

Driven by the emission peak and carbon neutrality targets, traditional cruising taxis are also under pressure to reduce emissions, and reducing taxi vacant time is an effective way to reduce emissions. This paper aims to examine the influence mechanism of built environment characteristics on vacant time of taxi trips from the supply-side perspective. To do so, the study uses a one week of taxi trajectory data of 2019 provided by a taxi company in Chongqing, a megacity in China. We take the divided square grid cell as the study units, calculate the taxi vacant time of 168 (7 × 24) hourly slots for each grid, and then calculate the built environment indicators of the grids with Point of Interest (POI) and vector road network data. A generalized additive model (GAM) based on panel data is constructed to investigate the influence mechanism of built environment on taxi vacant time. The results show that the time-varying trend of taxi vacant time is opposite to the time-varying trend of taxi trips and is similar to taxi trips in spatial distribution with significant spatial dependence. Taxi vacant time is negatively correlated with taxi trips. POI mixture, the number of enterprises, governmental agencies, and shopping services are negatively correlated with vacant time, while the number of sports and leisure services, hotel services, healthcare services, financial and insurance services, and living services are positively correlated with vacant time. An interesting finding is that metro stations significantly increase the vacant taxi time in the region. Average traffic flow speed, road density, the number of bus stops, catering services, residence communities, and motor vehicle services show strong nonlinear relationships with taxi vacant time, and their influence effects are alternately positive and negative. The study provides useful insights for understanding mechanisms of the role of built environment on taxi vacant time and has important implications for driver searching strategy improvement, taxi management measures development, spatial and temporal scheduling of taxi capacity resources, and urban transportation facilities layout planning. [ABSTRACT FROM AUTHOR]

According to China's 14th Five-Year Development Plan, China aims to peak its carbon emissions by 2030 and achieve carbon neutral by 2060, which will be a major strategy for China to implement in the coming period of time. All kinds of industries need to take the industry characteristics into account and gradually form relative carbon reduction targets according to the National Carbon Summit Action Program. Under the constraints of carbon emission reduction, enterprises face trade-off when making emission reduction decisions. How to systematically optimize the profitable and environmentally friendly decisions, under the consideration of carbon emission production, is gradually becoming a main concern of regulated enterprises. In this paper, a Cournot game model is constructed to explore optimal production carbon abatement decisions for two oligopolistic firms, under the governance of a cap-and-trade mechanism. Real case data collected from China's airlines is an example to test the validity of our model. The qualitative analysis shows that, through a reasonable output and emission reduction investment, companies are capable of efficiently minimizing the negative impact brought about by the carbon trading system. A numerical experiment indicates that the companies on one side can reach a decision equilibrium in some circumstances, but on the other side, there exists a lack of incentive to reduce their emissions. Additional government incentives or increased investment in technological improvements will be needed to encourage companies to further reduce carbon emissions. In this paper, while analyzing the choice of emission reduction strategy for enterprises under the carbon trading system, it also provides effective emission reduction approaches for the government and industry managers, hoping to provide some references for the establishment of emission reduction system and policy formulation. [ABSTRACT FROM AUTHOR]

China's rapid economic growth is accompanied by industrial agglomeration (IA) and environmental pollution. Although IA has played an important role in reducing environmental pollution, its effect on carbon emissions is still debatable and deserves further study. In this context, this paper constructs a two-sector general equilibrium model including households and firms to explore the mechanisms of IA on carbon emissions and finds that IA mainly affects carbon emissions through the agglomeration effect and congestion effect. Then, based on the balanced panel data for 30 Chinese provinces from 2003 to 2019, this study employs the dynamic spatial panel model to investigate the nexus between different types of IA and carbon emissions. The empirical results reveal that a significant positive spatial dependence is verified in the regional carbon emissions of China, indicating that carbon emissions exhibit a remarkably spatial spillover effect. Meanwhile, there are significant variations in the influence of different types of IA on carbon emissions. Specifically, specialized agglomeration (SA) positively affects carbon emissions, while the impact of diversified agglomeration (DA) on carbon emissions is negative, implying that China's DA may contribute to carbon emission control. In addition, there is regional heterogeneity in the effect of IA on carbon emissions, with the western region having a significantly greater effect than the eastern and central regions. Therefore, the Chinese government should follow the notion of integrating territory administration and interregional communication and formulate regionally differentiated environmental governance policies to promote carbon emission reduction in the future. [ABSTRACT FROM AUTHOR]

The most significant global challenge is global climate change; carbon emission reduction and carbon neutralization are the last way to solve global climate change. Achieving carbon neutrality will significantly impact the global economy and the national economy. The "dual carbon goals" proposed by China will also substantially impact the global economy and regional economic development. Focusing on regional economic development, achieving carbon neutrality is not only an opportunity for regional economic development but also a challenge. To achieve the goal of carbon neutrality, there must be institutional innovation and management innovation, which will provide new opportunities for balanced development among regions. With the development of inclusive finance, financial services for many disadvantaged groups and small and medium-sized enterprises have been further developed, thereby promoting economic development. With the development of Internet finance, big data, cloud computing, and other technologies, the development of inclusive finance, etc., the concept has also emerged. However, due to the short time of digital financial inclusion, the imperfect regulatory system, and the low degree of public participation, it is worth investigating whether the development of digital financial inclusion has a catalytic effect on the improvement of economic growth. Using the data of 31 provinces to build a panel regression model, this paper studies the market development, the development degree of digital financial inclusion, and the impact of digital financial inclusion on the relationship between factor markets and product markets and regions from the perspective of factor markets and product markets. [ABSTRACT FROM AUTHOR]

Since China's reform and opening up, the social economy has achieved rapid development, followed by a sharp increase in carbon dioxide (CO2) emissions. Therefore, at the 75th United Nations General Assembly, China proposed to achieve carbon peaking by 2030 and carbon neutrality by 2060. The research work on advance forecasting of CO2 emissions is essential to achieve the above-mentioned carbon peaking and carbon neutrality goals in China. In order to achieve accurate prediction of CO2 emissions, this study establishes a hybrid intelligent algorithm model suitable for CO2 emissions prediction based on China's CO2 emissions and related socioeconomic indicator data from 1971 to 2017. The hyperparameters of Least Squares Support Vector Regression (LSSVR) are optimized by the Adaptive Artificial Bee Colony (AABC) algorithm to build a high-performance hybrid intelligence model. The research results show that the hybrid intelligent algorithm model designed in this paper has stronger robustness and accuracy with relative error almost within ±5% in the advance prediction of CO2 emissions. The modeling scheme proposed in this study can not only provide strong support for the Chinese government and industry departments to formulate policies related to the carbon peaking and carbon neutrality goals, but also can be extended to the research of other socioeconomic-related issues. [ABSTRACT FROM AUTHOR]

This review proposes a performance evaluation system of low-carbon economic development based on multiobjective analysis in low-carbon environment. This is a modeling method combining super efficiency and relaxation-based measurement model (super-SBM model), which can effectively measure green innovation efficiency with unexpected outputs and traditional innovation efficiency without unexpected outputs. Using the Malmquist–Luenberger index method to dynamically analyze the efficiency of green innovation, a multiobjective model is obtained, including economic scheduling target considering wind power cost and low-carbon scheduling target considering carbon trading. The efficiency of green innovation considering unexpected output is obviously lower than that of traditional innovation without considering unexpected output. This phenomenon is more pronounced in some areas of central and western China. Technical efficiency improves the innovation level of environmental protection economy in China and the impact of technological progress is greater than that of technical efficiency. In this review, the output super SBM model is used to study the development of China's low-carbon industry, and the correlation between the prediction model and the performance change of low-carbon economic development is analyzed. The Malmquist–Luenberger (ML) index of environmental protection product development efficiency in China is not less than 1. Due to the improvement of the efficiency of scientific and technological development, the combination of the two will eventually lead to the improvement of the development of green products and environmental economic products in China. Combining with the empirical analysis, this paper puts forward some methods to promote the low-carbon economy in the economic zone. [ABSTRACT FROM AUTHOR]

Today, cities account for the majority of global energy consumption and CO2 emissions. The interaction between cities is critical for regional low-carbon development. At this time, China has turned to the full opening of the carbon trading market as an important policy tool for achieving its ambitious emission reduction goals. This paper attempts to explore the spatial relationships among cities from the perspective of carbon trading. A "multiscenarios across different spatial scales" analysis framework applied to the allocation and trading of CO2 emission quotas among cities in China is proposed. Based on this framework, the carbon trading networks of 182 cities in China are specifically simulated under four different scenarios, with a comparative analysis of the networks' complexity made from different perspectives. The results of the study are as follows: firstly, significant spatial network correlations exist between the cities' carbon trading under each scenario. Secondly, on a national scale, there are more inner connections in carbon trading networks, with stronger correlations and robustness, while the degree of connection of intercity carbon trading is higher overall on a regional scale. Thirdly, on a national scale, no obvious core nodes exist in the network, while core nodes do exist in the overall network and in each region under the regional scale. Fourthly, cities in the central region have the highest core position overall. Finally, based on the research results, practical guidance in using the framework for achieving carbon reduction, promoting economic growth, and balancing regional development, as well as the important inspiration for policy formulation, is further discussed. [ABSTRACT FROM AUTHOR]

In China, driven by the national "3060" double carbon targets (i.e., reaching peak carbon emissions by 2030 and carbon neutrality by 2060), green housing has become one of the major fields to reduce carbon emissions, facilitating the achievement of the double carbon targets. Promoting the growth of green housing is an important way for the real estate industry to achieve low-carbon transformation and improve the quality of housing. Meanwhile, the construction industry also can benefit from green housing to achieve its energy conservation and emission reduction targets. Therefore, it is critical to boost and maintain the sustainable growth of the green housing market in China. However, the literature has not focused attention on the market behavior of the green housing market in China. This study proposes a tripartite evolutionary game model to investigate the subject behavior of the green housing market in China. This model consists of three major subjects in a green housing market: developers, consumers, and governments. Based on this model, this study analyzes the stability of the strategy options for each stakeholder and identifies the stable conditions of strategy portfolios to reach the equilibrium points of the game system. The validity of the proposed tripartite evolutionary game model is tested through the simulation of the impacts from various factors on system evolution. According to the impacts of factors and the stable conditions of strategies, this paper puts forward relevant policy suggestions for the healthy and sustainable growth of China's green housing market. [ABSTRACT FROM AUTHOR]

Aiming at the problem of insufficient peak shaving capacity of the power system after large-scale renewable energy such as wind power and photovoltaics is connected to the grid, a new energy-pumped storage combined system low-carbon economic operation strategy is proposed. First, the energy storage characteristics of pumped storage are studied; wind power and photovoltaic output are shifted in time and space; and a new energy-pumped storage combined system model with photovoltaics, wind power, and pumped storage as the main body is established. Second, the carbon trading mechanism was introduced, and the reward and punishment ladder carbon trading cost model was established. Then, via the new energy-pumped storage combined system, the upper optimization target with the smallest investment cost and the lower optimization target with the largest system benefit are established, and a two-layer optimization model solution method based on linearly decreasing inertia weight particle swarm optimization and sequential quadratic programming algorithm is proposed. Finally, via the operating data of a pumped storage power station on an island in northern China, the new energy-pumped storage combined system low-carbon economic operation strategy was simulated and verified. The simulation results show that the low-carbon economic operation strategy of the new energy-pumped storage combined system proposed in this paper can effectively suppress load fluctuations, reduce the impact of wind and wind anti-peak regulation characteristics on the power grid, increase the utilization rate of renewable energy, and improve system economy. [ABSTRACT FROM AUTHOR]

China has already committed to peaking carbon dioxide emissions by 2030 and achieving carbon neutrality by 2060 (referred to as the 30·60 Target), which has brought both daunting challenges and great opportunities to the automobile industry in China. However, there is still a lack of comprehensive and in-depth studies on the challenges, paths, and strategies for reducing carbon emissions to fulfill the 30·60 Target in automobile industries. Therefore, this paper proposes low-carbon development strategies for China's automobile industry. This study's method is to integrate the results from different literature to summarize the status, challenges, opportunities, and refine the coping strategies for carbon emission of the automobile industry. The results indicated that the paths for achieving the 30·60 Target include joint carbon emission reduction by upstream and downstream enterprises inside the industry. It also needs cross-industry and cross-sector coordinated decarbonization outside the industry. Meanwhile, the low-carbon policy and regulation system should be established to provide a direct driving force and fundamental guarantee for the low-carbon development of China's automobile industry. [ABSTRACT FROM AUTHOR]

With the continuous expansion scale of carbon market and the development of carbon trading mechanism, carbon emission right, as a new financial asset, is being brought into the category of asset allocation by more and more investors. As the burning of coal is the major source of carbon dioxide, China is facing serious ecological and environmental problems, which restrict the development of low-carbon economy. In order to reach the carbon dioxide emission reduction targets and promote the development of green investment market, the carbon market should be a good emission reduction measure. The correlation and dynamic volatility spillover among coal, carbon, and green investing markets are becoming a hot topic for current research. The paper applies both VAR-GARCH-DCC and VAR-GARCH-BEKK models to draw some significant conclusions. (1) The green investment market, coal market, and Shenzhen carbon market show obvious time-varying correlation, and the volatility of the green investment market is higher. (2) There is a bidirectional Granger causality between green investing and coal markets. (3) The investment portfolio and hedging mechanism of the market are established to reduce the risk and help investors obtain higher returns. [ABSTRACT FROM AUTHOR]

With the development of carbon market, the complex dynamic relationship between electricity and carbon market has become the focus of energy research area. In this paper, we applied a new developed multifractal detrended cross-correlation analysis method to investigate the cross-correlation and multifractality between electricity and carbon markets. We analyze the daily return of electricity and carbon prices over a period of 6 years to do the research. The results show that, firstly, we find that there is a strong negative correlation between domestic carbon price and electricity price and a significant cross-correlation between the return series of electricity and carbon markets. Secondly, through multifractal detrended fluctuation analysis, it is proven that there are obvious multifractal characteristics in the return series of electricity and carbon markets, and the results of traditional linear analysis are unreliable. We also find that, based on multifractal detrended cross-correlation analysis, the law cross-correlation between electricity and carbon markets exists significantly. The long-range correlation of small fluctuations and large fluctuations and the fat tail distribution of return series are the reasons for the formation of multifractality. [ABSTRACT FROM AUTHOR]

To achieve the goal of carbon dioxide emission reduction in 2030 promised to the United Nations, China unified the Carbon Trading System (CTS) in 2017 since carbon dioxide quota allocation is one of the core issues of carbon trading. It is imperative to establish a flexible carbon quota allocation system based on the unbalanced characteristics of resource endowment and economic development in different regions. Unlike previous distribution research, this paper considers five principles, which are fairness principle, efficiency principle, feasibility principle, development principle, and innovation principle. The maximum deviation method is used to research the carbon emission quota allocation in 30 provinces of China, and the results are compared with those under the single principle and the information entropy method. The results reveal that the distribution under the single principle is severely unbalanced, making the region have a strong sense of relative deprivation. The maximum deviation method is better than the information entropy method to achieve carbon intensity by 2030. It is also conducive to promote the coordinated development of the regional economy, narrow the poverty gap, and achieve sustainable development. [ABSTRACT FROM AUTHOR]

To achieve the emission reduction target in 2020, China plans to establish a nationwide carbon trading market during 2016–2019. It is therefore an important but difficult task for policymakers to set emission allowances and allocate them among entities. There are three alternative allocation rules, which vary from free of charge to full auctioning. For business managers, the question is whether one of these rules meets the emission cap at the minimum cost. Based on China’s emission-abatement target, this paper examines the optimal investment and analyzes its implementation in different allocation rules. A new model is developed to formulate enterprises’ emission reduction pathways and the cost-minimization problem with the emission cap. The results show that the magnitude of enterprises’ emission reduction is positively related to their innovation potential; neither auctioning nor being free of charge can make enterprise’s individual emission-abatement investment in accordance with the optimal level; enterprise’s individual emission-abatement investment is sensitive to efficiency, budget cap, and environmental benefit. This paper discusses simultaneously their policy implications for China. [ABSTRACT FROM AUTHOR]

Climate change is one of the defining challenges facing the planet. Voluntary forest carbon offset project which has the potential to boost forest carbon storage and mitigate global warming has aroused the global concern. The objective of this paper is to model the game situation and analyze the game behaviors of stakeholders of voluntary forest carbon offset projects in China. A stakeholder model and a Power-Benefit Matrix are constructed to analyze the roles, behaviors, and conflicts of stakeholders including farmers, planting entities, communities, government, and China Green Carbon Foundation. The empirical analysis results show that although the stakeholders have diverse interests and different goals, a win-win solution is still possible through their joint participation and compromise in the voluntary forest carbon offset project. A wide governance structure laying emphasis on benefit balance, equality, and information exchanges and being regulated by all stakeholders has been constructed. It facilitates the agreement among the stakeholders with conflicting or different interests. The joint participation of stakeholders in voluntary forest carbon offset projects might change the government-dominated afforestation/reforestation into a market, where all participators including government are encouraged to cooperate with each other to improve the condition of fund shortage and low efficiency. [ABSTRACT FROM AUTHOR]

China's construction industry makes important contributions to energy consumption and pollution emissions. It is significant to improve energy efficiency in the construction industry. Since 2011, the introduction of China's carbon emission trading policy has had a great impact on energy conservation and emission reduction. The implementation of the carbon emission trading policy provides us with an opportunity to find solutions to improve the energy efficiency of the construction industry (EECI) in China. In this article, the implementation of carbon emission trading is regarded as a quasi-natural experiment, and the impact of the carbon emission trading policy on the energy efficiency of the construction industry is evaluated by analyzing the panel data related to the energy of the construction industry in 30 provincial regions from 2008 to 2016 through a difference-in-differences method. The main conclusions are as follows. First, the carbon emission trading policy can improve EECI. Second, the carbon emission trading policy can achieve the policy effect of improving EECI by optimizing the allocation of construction machinery resources and enhancing regional technical innovation. At the same time, strengthening government environmental regulation can strengthen the policy effect as well. Finally, some policy implications based on the study are proposed. [ABSTRACT FROM AUTHOR]

China is a large agricultural country, where agricultural activities and rural life cause a large amount of greenhouse gas (GHG) emissions. In the process of crop growth, production, and processing, a large number of crop straws and agricultural wasted products are produced, which become one of the important sources of biomass resources. However, few detailed studies focused on the potential of China's agricultural biomass energy conversion and carbon emission reduction, and fewer studies proposed GHG emission reduction strategies from the perspective of making full use of China's agricultural waste resources. In this study, the quantity calculation index of agricultural biomass energy was given, and the GHG emission reduction potential calculation index of agricultural biomass energy was constructed, with which the amount of GHG emissions caused by agricultural waste use in China was measured and the potential of GHG emission reduction caused by agricultural waste use would be easily speculated. Based on the statistical data of China, the quantity and GHG emission reduction potential of agricultural biomass resources in China in the recent 10 years (2009∼2018) were clarified. According to the research, the amount of agricultural waste equivalent to standard coal in China from 2009 to 2018 reached 280,0711 million tons. If all these resources were used to replace coal, a total of 4,474,483 million tons of carbon dioxide emissions could be saved. Assuming that these wastes are anaerobic, carbonized, or fully burned as fuel, CH4 emissions could be reduced by up to 12.024 million tons and N2O emissions by up to 185,000 tons. It can be seen that the effective utilization of agricultural biomass resources can replace coal, reduce backwardness such as land burning, and then reduce CO2, CH4, N2O, and other greenhouse gas emissions, and promote the realization of carbon peak and carbon neutrality. [ABSTRACT FROM AUTHOR]

China's economic growth has entered "new normal," and the task of reducing carbon emissions has become more onerous. Hence, this study aimed to explore whether China's carbon emissions trading pilot policy stimulated corporate green innovation capabilities. The data pertained to the green patent data of the listed companies in Shanghai and Shenzhen stock exchanges during 2008-2018. Using a difference-in-difference-in-differences (DDD) method, the study took advantage of the variations across regions, across enterprises, and across years and obtained several novel findings. First, the pilot carbon emissions trading policy significantly stimulated the green innovation capabilities of emission control companies in the pilot areas compared with enterprises in nonpilot areas and the nonemission control list. Second, the effect of the policy on the improvement in corporate green innovation capabilities might be driven by the improvement in corporate input factor allocation efficiency and the additional benefits that could be obtained from the carbon trading market. Third, the positive effect of the policy on the green innovation capabilities of state-owned enterprises was more significant. Therefore, the establishment and promotion of a unified national carbon emissions trading market and supporting mechanisms should be accelerated to achieve the balance of stable economic growth and carbon emission task. [ABSTRACT FROM AUTHOR]

Hydropower offers significant value for global carbon peak and carbon neutrality. However, the construction of hydropower stations leads to significant changes in land use and cover structure in reservoir areas, which affect ecosystem services including carbon balance. Furthermore, the development and operation of hydropower project require vast investment. However, the reservoir ecosystem's carbon storage and carbon emission reduction caused by hydropower could offer economic benefits when the official carbon market trading in China was launched in 2021. Therefore, it is necessary to assess comprehensively the changes in carbon storage and its value to the ecosystem in reservoir areas. The evaluation is of great importance for carbon loss reduction, land management, and hydropower development. This study provides a comprehensive and effective framework for evaluating changes in carbon storage and has its value to the reservoir ecosystem. It combines land utilization classification data obtained from remote sensing image interpretation and the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) carbon storage model. Based on the case study of the Xiluodu reservoir area, they were evaluated from two aspects: physical quantity and value quantity. The results show that the carbon storage in the Xiluodu reservoir area increased by 8,504.42 Mg from 2000 to 2018. The spatial distribution of the carbon storage shows a trend of high in the north and west, but low in the south and east. The construction of hydropower stations and the rise of reservoir water level covered a large amount of land, which led to the loss of carbon storage in reservoir areas. By implementing soil and water conservation and vegetation protection policies, parts of the cultivated land and grassland were converted into forestland, which was the main source for increasing the ecosystem's carbon storage. Moreover, carbon emission reduction was achieved by hydropower. In terms of the monetary value, the carbon storage value of the reservoir ecosystem increased to 19 million RMB during the construction period (2005–2015). The carbon storage value of the reservoir ecosystem increased to 611 million RMB during the operation period (2015–2018). The latter was greater than the maintenance cost of the hydropower station and exceeded the amortized cost of hydropower development, indicating the feasibility and economic benefits of hydropower development. These findings provide guidance for future hydropower development decisions in Jinsha River Basin and also others. [ABSTRACT FROM AUTHOR]

Summary: The development of carbon emission reduction technologies and clean energy utilisation are two critical drivers for reducing and controlling greenhouse gas (GHG) emission from human activities. Carbon capture, utilisation, and storage (CCUS) is an established and crucial emission reduction technology capable of achieving near‐zero‐emission from fossil fuels. Hydrogen, a zero‐carbon fuel, provides energy security while improving air quality. However, hydrogen is commonly derived from fossil fuels with significant associated CO2 emission. Hence, this study investigates the feasibility of integrating CCUS in the hydrogen industry, particularly from technical, sustainability, and policy perspectives. This study also critically reviews existing CCUS and hydrogen production technologies and discusses the prospects and challenges of each. Studies show that CO2 enhanced oil recovery (CO2‐EOR) and CO2 enhanced coal‐bed methane recovery (CO2‐ECBM) are promising CCUS technologies in China, while producing clean hydrogen from fossil fuels with CCUS and water electrolysis are ideal development route. Specifically, this study proposes the coupling technical route of CCUS + SMR (steam methane reforming) and CCUS + CTH (coal‐to‐hydrogen) to accelerate carbon emission reduction by 2050 considering their promising carbon reduction potential and the ratio of hydrogen with CCUS. Besides, CO2 hydrogenation integrated chemical production is becoming increasingly popular to achieve carbon emission reduction and low‐carbon economy. However, the relatively high costs and lack of hydrogen transportation infrastructure is currently the major bottleneck restricting the development of CCUS and hydrogen industry. Therefore, government subsidies, standardised operation of the carbon market, and technological innovation are useful strategies to address this issue. [ABSTRACT FROM AUTHOR]

China declared a long-term commitment at the United Nations General Assembly (UNGA) in 2020 to reduce CO2 emissions. This announcement has been described by Reuters as "the most important climate change commitment in years." The allocation of China's provincial CO2 emission quotas (hereafter referred to as quotas) is crucial for building a unified national carbon market, which is an important policy tool necessary to achieve carbon emissions reduction. In the present research, we used historical quota data of China's carbon emission trading policy pilot areas from 2014 to 2017 to identify alternative features of corporate CO2 emissions and build a backpropagation neural network model (BP) to train the benchmark model. Later, we used the model to calculate the quotas for other regions, provided they implement the carbon emission trading policy. Finally, we added up the quotas to obtain the total national quota. Additionally, considering the perspective of carbon emission terminal, a new characteristic system of quota allocation was proposed in order to retrain BP including the following three aspects: enterprise production, household consumption, and regional environment. The results of the benchmark model and the new models were compared. This feature system not only builds a reasonable quota-related indicator framework but also perfectly matches China's existing "bottom-up" total control quota approach. Compared with the previous literature, the present report proposes a quota allocation feature system closer to China's policy and trains BP to obtain reasonable feature weights. The model is very important for the establishment of a unified national carbon emission trading market and the determination of regional quotas in China. [ABSTRACT FROM AUTHOR]