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This study aims to elucidate the profound implications of industrial transformation and upgrading in mitigating dependence on fossil fuels, which holds paramount significance in shaping energy transition strategies—an aspect that is currently missing in existing studies. Leveraging data spanning from 2000 to 2020, encompassing fossil energy consumption and economic development, this paper developed a second-order classification model as a new measure of energy elasticity. Comparing regional variations in fossil energy resilience, an in-depth analysis was conducted on four representative provinces to understand the evolution of their fossil energy consumption structures over time. Correlation analysis was employed to reveal the impact of industrial structures on the reduction of fossil energy dependence. The results indicate distinct spatial variations in the energy transition effect, with the southwest inland region retaining a pronounced reliance on fossil energy sources. However, approximately 80% of the provinces have made substantial progress in reducing fossil energy dependence from 2000 to 2020. Notably, the financial sector and the accommodation and catering industry contribute positively to mitigating fossil energy dependence, while the industrial sector exhibits the opposite effect. Urban agglomeration planning attributes the uneven regional energy transition to the delineation of urban industrial functions. Suggestions for narrowing the energy transition gap include measuring the sustainability of the industrial chain from a life-cycle perspective, avoiding the singular functional division of cities, and developing systematic policies. In the catering industry, adopting alternative cooking energy and implementing the conversion and recycling of catering waste can help prevent risks. This study underscores the positive role of the accommodation and catering industry in the energy transition, along with its potential risks. The study also makes efforts toward advancing the application of the widely used energy elasticity assessment method. [Display omitted] • A second-order classification model is developed as a widely used energy elasticity assessment method. • 80% of China's provinces have successfully reduced their reliance on fossil fuels. • The financial sector and the accommodation and catering sector play pivotal roles in diminishing reliance on fossil fuels. • In the forthcoming years, the catering industry has the potential to engender a reliance on fossil fuels. [ABSTRACT FROM AUTHOR]

The five major power generation corporations dominate the power industry in China, and play vital roles in China's carbon trading scheme. Under this circumstance, this paper studies the allocation of carbon emission quotas to China's five major power generation corporations based on the fairness and efficiency principles, which proves the primary prerequisite for setting up the national carbon market. Specifically, a bi-level programming model is developed to optimally allocate carbon emission quotas to the corporations, and then a zero sum gains data envelopment analysis (ZSG-DEA) model is adopted to evaluate the efficiency of the allocation so as to adjust towards the optimal solution. The results indicate that power generation has significantly positive influence on the allocation of carbon emission quotas. Moreover, the difference between the sum of optimal carbon emissions and the sum of carbon quotas allocated is 1.431 billion tons, which implies that the emission reduction potential of the five major power generation corporations is tremendous. Finally, the bi-level model in this paper can well capture the context of China's power industry and provide effective results for the allocation of carbon quotas. [ABSTRACT FROM AUTHOR]

Recognizing the industrial sector's high energy use and vast potential for energy saving, many national governments have established voluntary or negotiated agreements that set quantitative energy-saving targets for individual industrial enterprises. The most commonly used energy-saving targets worldwide are volume and energy intensity targets. Since 2006, the Chinese government has set mandatory, enterprise-level energy-saving targets in terms of the “amount of energy saved”; this represents a unique category that differs from both volume and energy intensity targets. Based on first-hand data collected at ten case enterprises, this paper represents one of the first attempts to verify the reliability of the amount of energy saved data reported by the Chinese government and to rigorously and systematically investigate the inherent weaknesses of the amount of energy saved targets through a comparison with the mainstream categories of energy-saving targets. The ten case enterprises reported four different types of amount of energy saved. While all of the case enterprises claimed full achievement of their amount of energy saved targets, four enterprises exaggerated their performance by violating the National Standard for Calculating the Amount of Energy Saved of Enterprises. The paper thus hypothesizes that the National Top-1000 Enterprise Program's alleged achievement of performance 65% higher relative to its amount of energy saved target is likely an overestimation. Although amount of energy saved targets constitute an innovative energy-saving indicator, they do not represent a step forward from conventional volume and intensity targets because of the following four weaknesses: 1) amount of energy saved targets provide limited potential for comparison given the different types of amount of energy saved and the different calculation methods, 2) they generate uncertain environmental outcomes as it is possible to meet a portion of an amount of energy saved target through production volume expansion, 3) they are difficult to enforce due to the complexity of data verification on the part of local government agencies, and 4) they are poorly correlated with the national target for reducing energy intensity. Amount of energy saved targets should therefore be replaced with “double-control” targets that impose both volume and intensity targets on industrial enterprises. [ABSTRACT FROM AUTHOR]

Abstract Theses on China's low-carbon economy focus on the driving forces of carbon emissions, energy–carbon efficiency, and the carbon–economy nexus. Meanwhile, comprehensive frameworks that assess China's green economy and also analyze its driving forces are lacking. This paper constructs a green productivity index based on the Global Malmquist–Luenberger productivity index to evaluate the development of the low-carbon economy in China. A panel vector auto-regression model is adopted to further analyze the endogenous interactions and dynamic relationships among aspects of the green economy and its influencing factors. Empirical results show that China has seen a balanced development of green economic growth in 2000–2016, achieved in a series of clear stages. To maintain the sustainable growth of the low-carbon economy in the future, China must rely more on technological progress. This research also makes some important discoveries that have not been found in previous studies: the impact of China's industrial structure and energy consumption structure on the green economy are short term, having a duration of impact of approximately four years. Finally, we provide an assessment of provincial green economy development and describe the corresponding policy implications. Graphical abstract Image Highlights • A comprehensive analysis of China's green economy. • A slack-based Global Malmquist–Luenberger index is adopted to calculate the Green Productivity Index in China. • The stage characteristics of green economic development are identified. • A panel vector autoregressive model is used to analyze the interactions among aspects of the environmental economic system. • The findings that the impact duration of energy structure, industry structure, and urbanization on the green economy is about four years. [ABSTRACT FROM AUTHOR]

For the past three decades, the notion of sustainable cities has become central in planning and managing urban areas in the world and the large-scale city formation has been formed in big cities. As a result of economic growth and urban transformation, Shanghai, a major Chinese international metropolis, faces ongoing issues with resource waste and low energy utilization. Therefore, this paper aims to consider the availability of water for energy production from a consumption-based perspective and estimate the water footprint of the energy supply using a regional input-output analysis approach for Shanghai. As a result, we conclude that the water footprint of the energy supply of Shanghai is about 1.28 billion m 3 in 2007, with 46.1% of water used for electricity and heat supply. The total water withdrawal by the energy sector is about 2.35 billion m 3 and additional water withdrawal needed is about 35% of the total water withdrawals by the energy sector in Shanghai. Furthermore, an energy self-sufficiency scenario was developed, and the scenario analysis reveals that 55% more water would be required to ensure a self-sufficient energy sector. To guarantee future regional energy security, it is important to manage water resources effectively by allocating water resources among sectors. [ABSTRACT FROM AUTHOR]

To achieve green development, ample environmental subsidies have been invested into many energy-intensive firms (such as thermal power firms) in China. Investigations of the effects of this kind of subsidy can help to provide specific and important implications for ongoing regulations. Unlike previous studies on the national, regional or sectoral level, this paper measures green efficiency and its compositions of thermal power firms and studies the impact of environmental subsidies on green efficiency by using the classical Slacks-based Measure and Tobit model. The results show that the average green efficiency ranges from 0.509 to 0.663 during 2010–2015, which is much lower than the general efficiency. The green scale efficiency is the main reason for the low green efficiency, thus indicating large room for improvement. Environmental subsidies negatively affect green efficiency and its decompositions from 2010 to 2013. The negative effect becomes weak and insignificant in 2014, and the environmental subsidies start to significantly promote green efficiency and its decompositions in 2015. According to our findings, some implications relating to improving green scale efficiency, increasing the intensity of environmental subsidies to firms and strengthening their supervision are proposed. [ABSTRACT FROM AUTHOR]

The inter-provincial inequality of per capita CO 2 emissions in China's electricity sector means that their responsibilities for CO 2 emission reduction are different. Considering the spatial separation of CO 2 emissions in power production and consumption, with respect to the large scale inter-provincial electricity trade in China, this paper innovatively investigates the sub-national inequality and polarization degree of per capita CO 2 emissions in China's electric power sector from the perspectives of both production and consumption. The overall tendencies of the sub-national polarization degrees of per capita CO 2 emissions embodied in the both electric power consumption and production in China show an increasing trend. The results indicate that the polarization distribution of per capita CO 2 emissions is still one of the important factors leading to difficulties in achieving the new reduction arrangements. The evolution of the bi-polarization analysis shows that the grouping results of per capita CO 2 emissions are different from production and consumption perspectives, as well as the high- and low-emission groups have significantly different characteristics. The inequality and polarization degree of per capita CO 2 emissions in China's electric power sector have changed as the CO 2 emissions embodied in the electricity trade had been taken into account. One-Size-Fits-All Strategies are unlikely to be successful in advancing the provincial cooperation on CO 2 emissions reduction. [ABSTRACT FROM AUTHOR]

Understanding the driving factors behind energy consumption changes provides insights about consumption patterns and can inform targeted energy saving polices. This paper applies a joint decomposition approach, introducing an index decomposition analysis (IDA) method into a production theoretical decomposition analysis (PDA). This integrated approach decomposed energy consumption changes into eight drivers. A subsequent empirical study of China resulted in three key findings. First, regardless of the geographic area considered, potential economic development was the largest factor driving energy consumption growth. Second, the technological change effects associated with economic development and energy savings both played significant roles in reducing energy consumption. Third, the efficiency change effects of energy use and economic development were generally unable to relieve the pressure of increases in energy consumption, especially in the eastern regions. [ABSTRACT FROM AUTHOR]

Improvement of coal consumption efficiency is very important both for China in solving its problems of energy security and environmental pollution and for the world in addressing the issue of greenhouse gas emissions. Using a total-factor framework, this paper employs a data envelopment analysis (DEA) approach to evaluate the coal consumption efficiency of six energy intensive sub-industries in China in 2015. Coal consumption efficiency is factorized into economic efficiency and environmental efficiency, with sulfur dioxide, nitrogen oxide, and industrial smoke, dust and soot emissions treated as undesirable outputs of energy consumptions. The results show the following. (1) Of the six energy intensive sub-industries studied, two exhibit both DEA-effective coal economic efficiency and coal environmental efficiency. Coal economic efficiency is found to be greater than coal environmental efficiency, indicating that the benefits of economic efficiency have masked the negative effects of the environmental impact. China should therefore pay more attention to the clean utilization of coal. (2) Low environmental efficiency mainly resulted from the joint effects of pure technical efficiency and scale efficiency; therefore, enterprises in these industries must engage in management efforts to improve their ability to manage large enterprises. (3) The energy intensive industries characterized by coal environmental efficiency that failed to achieve pure technological effectiveness all exhibited input redundancy or output inadequacy of varying degrees while showing a potential for energy conservation and emissions reductions. [ABSTRACT FROM AUTHOR]

The 2015 Paris climate change negotiations represents the most ambitious worldwide effort to date to combat climate change. As the largest energy consumer and carbon emitter, China pledges 60–65% cut in carbon intensity below 2005 levels by 2030. To accelerate China's climate efforts, China has also committed to cap its primary energy use at 4.8 billion tons of coal equivalent in 2020. This paper proposes an equitable and efficient scheme to disaggregate this national goal among provinces. A three-step disaggregation procedure is proposed which takes into account the initial allocation, national redistribution and inter-provincial adjustment. First, this study allocates the incremental energy quota, taking 2010 as the base year. Second, part of the energy quota is set aside by the central government for redistribution purposes, while an incremental energy quota index comprising equity and efficiency criteria is used for initial allocation among provinces. Finally, historical efforts and inter-provincial energy flows are considered for inter-provincial adjustment. This disaggregation scheme is flexible and can be easily extended to allocation and management of other resource and environmental targets. The empirical findings can assist decision-makers in identifying which provinces are likely to over-consume the energy quota relative to the proposed allocation and which provinces are likely to perform better in energy conservation. Moreover, the results show that the energy cap set for 2020 is unachievable without further action. Market-based instruments, such as an energy allowance trading market, are strongly recommended to achieve the energy use target in an equitable and cost-effective manner. [ABSTRACT FROM AUTHOR]

Emerging economies account for a fast-growing share of the global energy market. In particular, energy use in China has become significant from both economic and environmental standpoints. This trend makes it necessary to balance the need for affordable, reliable electricity supply with the need to ensure that the power infrastructure is environmentally sustainable. As such, this paper presents a multi-dimensional pinch analysis (MDPA) of the power generation sector in China; the analysis considers five key indices: carbon footprint, energy return on investment (EROI), water footprint, land footprint, and risk to humans. By simultaneously quantifying five different indices under a common methodological framework, we are able to coherently assess the impact on five different environmental concerns. This approach provides a more complete picture of the true environmental impact of China's power sector. This information can thus help policymakers avoid the problem of shifting environmental impacts to other domains, which can occur when the analytic procedure used focuses on a single environmental dimension. [ABSTRACT FROM AUTHOR]

The super efficiency slack-based measure (SBM) with undesirable outputs was used in this paper to determine the energy efficiency of the service industry in various provinces from 2007 to 2017. The different characteristics of the energy efficiency of service industry in different provinces were obtained from the perspective of heterogeneous resource endowment. The findings show that: ⅰ) China's service industry's overall energy efficiency fluctuates in a 'W' shape. Provinces with varying resource endowments demonstrated significant variation in energy efficiency. Provinces with a high concentration of technology and energy had the highest and lowest levels, respectively, indicating an upward and downward trend. ⅱ) Energy efficiency improvements in China's service sector were primarily a result of technological advancements. Technological advancement and technical efficiency were the primary causes in technology- and labor-intensive provinces, respectively, whereas the combined effect of both factors was the primary cause in energy-intensive provinces. ⅲ) Foreign investment and environmental regulation may both contribute to the improvement of energy efficiency in the service industry, while energy structure and government intervention may work against it. Additionally, a U-shaped relationship was observed between the service industry's development level and energy efficiency. As a result, policymakers should develop targeted promotion strategies based on the resource endowment and development stage of the service industry in various provinces. • Undesirable super efficiency SBM model and Malmquist–Luenberger index are used. • China's service industry's overall energy efficiency fluctuates in a 'W' shape. • Static and dynamic analysis of the service industry's energy efficiency is provided. • The service industry's energy efficiency in provinces with different resource endowment is heterogeneous. [ABSTRACT FROM AUTHOR]