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China’s paper industry consumes a lot of energy and emits huge amounts of pollutions. The Chinese government over the past decades has done a lot to promote energy efficiency of the industry. This paper studies the impact of industrial polices to improve energy efficiency. The energy efficiency change is firstly studied under a framework of total factor efficiency. On this basis, different econometric models are built to discuss the detailed energy efficiency characteristics of the paper industry. The main results are as follow: (i) ownership structure did influence the energy efficiency, but the influence is different in different conditions; (ii) energy efficiency of the paper industry can be improved by economies of scale; (iii) market competition can to some extent overcome the motivation and supervision problem that often occur in state-owned companies; (iv) energy price cannot play the role of resource allocation well in China. Finally, based on our findings, some suggestions are provided. [ABSTRACT FROM AUTHOR]

China's paper industry accounts for a larger proportion of the global paper industry and consumes large amounts of energy. Energy conservation and pollution reduction of the industry have become the focus of China's national development strategy. Energy efficiency is an important index which directly determines the amounts of energy consumption and pollution emissions. To understand the energy efficiency evolution of China's paper industry, this paper establishes an input-output data of the paper industry for 29 provinces in China and applies DEA method and econometric models to estimate and comprehensively discuss the energy efficiency issues based on the framework of total factor efficiency. Our results indicate that China's paper industry has a large energy saving potential even though its energy efficiency has improved during the period 1990–2013. The saving potential is about 65% under the meta-frontier and 44% under the group-frontier. Moreover, there are significant differences between different regions in production technology and energy efficiency. The performance of eastern China is better than other regions. But the technology gaps between the different regions are shrinking and converging over time. Finally, some policy recommendations are proposed to improve the energy efficiency of the industry. [ABSTRACT FROM AUTHOR]

• A distribution dynamics approach is employed to examine the converge of TFEE across Chinese PAA level cities. • The findings show a clear convergence in TFEE. • Convergence comes more from efficiency drops in high TFEE cities than from efficiency gains in low TFEE cities. • The environmental protection polices in key cities improved energy efficiency. • Large-sized cities show better performance in energy efficiency than small- and medium-sized cities. Improving energy efficiency is considered the most direct route to reducing carbon emissions on a massive scale. To examine the long-run trend of China's energy efficiency, this paper employs a distribution dynamics approach to analyze the convergence of total-factor energy efficiency (TFEE) across 286 Chinese cities between 2002 and 2014. The result suggests the existence of convergence, which comes more from the efficiency declines in the high TFEE cities rather than the efficiency gains in the low TFEE cities. Despite the fact that a few cities have performed well in energy efficiency, the majority of cities have converged to a low-efficiency point. Further analyses show that the inefficiency was attributed to inefficient energy use in small- and medium-sized cities. Our analysis provides strong scientific support for China's ongoing energy conservation and environmental protection policies. [ABSTRACT FROM AUTHOR]

In light of the carbon neutrality goals set post-Paris Climate Conference (COP21), this study delves into the relationship between green technology innovations, energy consumption, and CO2 emissions in China, spanning the period of 1990 to 2021. The objective of this paper is to creatively present the idea of a low-carbon digital economy from the viewpoint of digital technology. Utilizing the Stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT) model, we scrutinize this relationship, employing unit-root testing to verify the integrative attributes of the variables, inclusive of structural break data. Further analysis using the bootstrap Autoregressive Distributed Lag (ARDL) bound testing method corroborates the relationship between these key variables. The study reveals unidirectional co-integration over time among green technology innovations, renewable and non-renewable energy, per capita income, population, and CO2 emissions as per the Granger causality test. Interestingly, our findings suggest that while green technology innovation, per capita income, and renewable energy contribute to the reduction of CO2 emissions, non-renewable energy consumption and population growth exacerbate them. These insights offer valuable guidance for policymakers in formulating comprehensive strategies to enhance environmental quality through the promotion of renewable energy and green technology innovations, with a specific emphasis on the Chinese context. [ABSTRACT FROM AUTHOR]

China's Hot Summer and Cold Winter zone, with a 550 million population, accounts for 45% of China's building energy consumption; as such, building retrofits could offer substantial energy savings. This paper presents results from a dynamic thermal modeling study of a typical urban multistory residential building under three types of air conditioning (A/C) operating schedules. Seven energy-saving retrofit measures (external wall insulation, roof insulation, double-glazing, air infiltration control, window shading, communal staircase design, and energy-efficient A/C) were evaluated, and the retrofit strategy with the highest annual energy savings and lowest thermal discomfort was identified. This retrofit strategy was subsequently evaluated for other flats (apartments) with different orientations and positions in the typical building. The annual space-conditioning energy could be reduced by 59%–68%, depending on the flat location, orientation and A/C operating schedule. The findings were then scaled up to estimate the potential energy savings in the city of Chongqing. More than 320 multistory residential buildings were represented by 12 archetypes. Space-conditioning energy consumption was reduced by up to 58% (18.8 TWh). This work provides evidence of the potential energy savings of city-scale retrofit that could aid China in reducing building energy consumption and achieving net-zero carbon emissions by 2050. It was possible to explore a wide range of refurbishment options for China's highly energy-consuming Hot Summer and Cold Winter zone with hot, humid summers and mild, chilly winters using dynamic thermal models. The simulation models developed in this paper revealed that double-glazing with air infiltration control is the most effective retrofit measure for middle-floor flats, but for top-floor flats, roof insulation is the most effective; south-facing flats consume more high energy consumption than north-facing flats. Furthermore, high-rise buildings consume less energy than low-rise buildings per square meter, and one-bedroom flats consume more energy than three-bedroom flats per square meter. This study also demonstrated the procedure to develop thermal comfort evaluation methods, A/C operating schedules, and construction parameters from literature in this climate zone when there were no standards or databases available. Findings offer a tangible, clear retrofit strategy that considers different A/C operating schedules, flat locations, and building archetypes. It can assist decision-making by practitioners and homeowners aiming to upgrade the building stock of this climate zone which covers 3.4 billion m2 with a 550 million population to reduce energy consumption and improve occupant comfort. [ABSTRACT FROM AUTHOR]

The current approaches to study the coupling mechanism between economy and environment seem to fall into self-circulation, failed to reveal "economy–environment interdependence". In this context, an exogenous variable is introduced into these models for better understanding the relationship. Benzo[a]pyrene (Bap) environment inventories in different cities in China were estimated by fugacity model based on Bap concentration data collected from previous studies. An extended model, stochastic impacts by regression on population, affluence and technology (STIRPAT), generated from original IPAT (a model that expresses the idea that environmental impact (I) is the product of three factors: population (P), affluence (A) and technology (T)) was used to study the relationship between Bap environment inventory and anthropogenic factors including population, vehicle amount, affluence and energy consumption. A ridge regression has been applied to optimize the model parameters. Overall, there exist good relationships between Bap inventories and economic factors. Specifically, population and affluence are the most significant factors that influence Bap inventory. Rise of the scale of population and vehicle amount increases the Bap inventory, as growth of GDP per capita and the efficiency of energy utilization have inhibitory effect on Bap inventory. Apparently, the influences of anthropogenic factors on Bap inventory are different between north and south China. Bap inventory in north China is more sensitive to the change of population and energy consumption, while is highly correlated to GDP per capita in south China. Further, according to social-economic development prediction, with assist of the result from STIRPAT model, we find out that Bap inventory drop 31% from 2001 to 2020 in China. Our estimates are comparable with the published data and confirmed that Bap can be regarded as a chemical indicator of social-economic development in China. Image 1 • An extended STIRPAT model derived from original IPAT was developed. • Population and affluence are the key factors that influence Bap inventory. • Advance of affluence and technology level curbs Bap environmental exposure. • We predict Bap environmental inventory drop 31% from 2001 to 2020 in China. • Bap can be used as an indicator of social-economic development in China. [ABSTRACT FROM AUTHOR]

Carbon neutrality is an important policy in the current global response to climate change and has been widely recognized by various industries. In the process of promoting carbon neutrality, new energy plays a pivotal role. In this study, the definition and connotation of new energy and its role and specific operation in the energy transition of carbon neutrality are firstly explained. Promoting new energy development requires significant green and low-carbon investments. Taking China as an example, this paper analyzes the opportunities brought by the carbon neutral process to the field of green finance and analyzes the main features and development trends of green finance in China at present. Then this paper proposes policy recommendations to strengthen the development of green finance in China in terms of improving the green financial policy system, enhancing the supply capacity of green financial services, and optimizing the supporting environment for green financial development. Finally, this paper analyzes the measures and experiences of the United States in promoting low-carbon development and proposes countermeasures for China's low-carbon development on the basis of the five major relationships that need attention in China's carbon-neutral process. That is, strengthen the top-level design and improve the regulatory policy system; optimize the energy structure and increase the proportion of clean energy; optimize the industrial structure and reduce energy consumption in key industries; build a complete low-carbon technology system and promote low-carbon technology research and development and demonstration applications, and encourage local conditions to explore low-carbon development paths. The development of green finance can contribute to the advancement of new energy technologies, thus contributing to the achievement of carbon neutrality goals. [ABSTRACT FROM AUTHOR]

High carbon emissions and population aging are two obstacles to China's development as an emerging economy. It is urgent to scientifically examine the impacts of population aging on carbon emissions to discover new pathways for urban carbon emission reduction. However, existing studies face challenges in terms of focusing on and methodology for accurately capturing the role of industrial production and energy consumption in the environmental effects of population aging. This paper constructs a chain mediation analytical framework and systematically examines the intrinsic linkages between population aging and carbon emissions in Chinese cities from 2000 to 2020 using a two-way fixed effects model. This paper has three main findings. (1) The positive correlation between urban population aging and carbon emissions development is generally low, with coupling coordination degree values of 0.4233, 0.4458, 0.4220, 0.4715, and 0.4665 for each yearly cross-section. (2) For every 1% increase in the population aging rate, carbon emissions decrease by 0.3478% on average. The carbon reduction effect of population aging is significantly greater in low-emissions cities and high-income cities than in other cities. (3) The industrial upgrading (IU) path, energy conservation (EC) path and chain mediation (CM) path account for 72.43%, 7.23% and 20.34%, respectively, of the indirect effects. If the causal link between IU and EC is not considered, the EC effect will be overestimated by 281.16%. The results of the study suggest that properly coping with population aging and reducing carbon emissions are not completely opposed to each other, a conclusion that passes both endogeneity exclusion and robustness check. This paper advocates replacing the one-size-fits-all approach in carbon emissions management and investing more in policy preferences to support carbon emission reduction in both high-emissions and low-income cities. [Display omitted] •The synergistic trends of carbon emissions and population aging are not apparent. •Population aging significantly reduces carbon emissions at the city scale. •Linkage effect of industrial upgrading and energy conservation on carbon emission reduction. •Energy conservation effect of population aging amplified by industrial upgrading. [ABSTRACT FROM AUTHOR]

This paper explores opportunities for effective policy intervention for residential energy savings in southern China, by analyzing achievable potential of residential energy savings in the city of Xiamen as a case study. In contrast to static technical and economic potential analyses, the achievable potential analysis is based on dynamic energy consumption projections, which consider two real-world factors: (1) gradual ramping-up adoption process of advanced technical measures; and (2) consumers’ adoption of these measures. A bottom-up type Residential Energy Consumption (REC) projection model specifically tailored for southern China was developed in this paper, based on the general logic and calculation principles utilized in the U.S. EIA’s “National Energy Modeling System (NEMS),” and the adoption theory of advanced technical measures proposed by Kastovich. This REC projection model was then used as a policy analysis tool to quantitatively evaluate the impact of various policies on residential energy savings in the case study city of Xiamen. The analysis of the Xiamen case shows that although there is a significant technical potential for residential energy savings in the city (about 20.9–24.9%), the maximum achievable potential (MAP) in 2020 is only about 8.3–8.4% of that year’s business-as-usual baseline consumption. Moreover, with existing policies only about one-fourth to half of the calculated MAP is likely to be achieved by 2020. These findings indicate that in order to realize a larger share of achievable potential for residential energy savings in China, additional and more effective polices are needed. [ABSTRACT FROM AUTHOR]

This paper focuses on energy poverty dynamics by answering one question: Does energy poverty trap exist in Chinese cities? For this purpose, we examine the co-evolution between per capita energy consumption and income for 286 prefectural-and-above level cities in China over the period 2002 to 2014. A nonparametric joint-distribution dynamics approach is employed in the analysis. Both static and dynamic distribution analyses demonstrate significant evidence of club convergence in energy consumption across Chinese cities, and there are multiple equilibria between per capita energy consumption and income in the long-run distribution. The results also suggest that considerable cities fall into energy poverty trap, a chronic state with low income and low energy consumption. Therefore, we can argue that energy poverty is not a transitory state for those cities and support the existence of energy poverty trap in China. Our findings highlight the need to tailor policies aimed at reducing energy poverty in low-income cities. • We examine the co-evolution between per capita energy consumption and income in China. • A dataset of China's 286 prefecture-level cities during 2002–2014 is explored. • The results argue club convergence in energy consumption across Chinese cities. • Considerable cities fall into energy poverty trap. • The study supports the existence of energy poverty trap in China. [ABSTRACT FROM AUTHOR]

With the growing share of the climate-sensitive renewable energy market supply in China, estimating future energy drought risk (ED) is essential. In this paper, based on CMIP6, energy demand and power generation are estimated from 2023 to 2100 under SSP2-4.5 and SSP5-8.5 climate scenarios, and ED is defined from high demand (HD), low wind-solar generation (LWS), and residual load (RL). The results show that the ED exacerbation is relatively high under the SSP5-8.5. Between 2023 and 2100, the duration and severity of HD and RL notably increase, while LWS changes are relatively weak. We find that HD and RL exhibit high summer risks in the south and high winter risk in the north. The return periods vary significantly and extends over time in most regions. Moreover, there are few ED when the installed power generation capacity (IPGC) is increased. When the IPGC increases by 2%–5%, the LWS will decrease at least 20%–72%. With a 10% increase, the LWS will be mitigated by at least 80%, whereas the mitigation for RL is limited, approximately 3–17% at different rates. This work performs the first evaluation of future ED and provides the useful references for risk mitigation in China based on CMIP6. [ABSTRACT FROM AUTHOR]

India and China are the biggest developing economies in the world apart from being the most populous nations. The population of China is expected to increase over 1.4 billion by 2050, and India may over take China and become the most populous nation at around 1.6 billion populace. These two nations are home to about 40 % of the total population in the world. Apart from this, India and China have attained remarkable success in the economic growth denoted by higher gross domestic product (GDP). The two nations together contribute about one-fifth of the world GDP. This paper discusses about the changes in the energy consumption pattern of developing countries like China and India aiming towards the sustainable development. Furthermore, this paper also analyses the most important drivers adding to the ecological problems, and gives a further glance at the ecological impacts of these in India and China. Over the last 50-60 years we have been emitting carbon dioxide at an accelerated pace. This has had an effect on the carbon dioxide concentration and other GHG gas concentrations, in the atmosphere. The paper also discusses about the effect of pollutants like NOx, SOx, Particulate matter and Mercury on the environment. [ABSTRACT FROM AUTHOR]

This paper examines the nexus between fiscal decentralization and renewable energy demand by including income inequality, economic growth, urbanization, and economic globalization as the main determinants in the energy demand function for the case of China. Quarterly frequency data for the period 1980–2018 are used for empirical analysis. Our empirical results show fiscal decentralization positively impacts the demand for renewable energy; in other words, fiscal decentralization can help increase renewable energy demand. In addition, income inequality is negatively linked to renewable energy consumption, while economic growth is positively associated with renewable energy demand. Urbanization and economic globalization add to renewable energy consumption. This study presents Chinese authorities with new guidelines for using fiscal decentralization as an economic tool to formulate effective energy policies for long-term development of the use of renewable energy sources. [ABSTRACT FROM AUTHOR]

Energy consumption is closely related to industrial structure, economic prosperity, and population. Because of the Granger causal relationship between GDP and energy consumption, many researchers consider the regression method to predict energy consumption using economic variables. However, some other researchers regard the time series method (forecast) to estimate for energy consumption. To address the advantages and disadvantages of two methods in energy consumption prediction, we performed the deep learning (DL) based on the case of China. The experiment results show that the accuracy of time series forecast is much higher than regression methods. In addition, we also explored the relationship between industry, economy, population, and energy consumption. We found that GDP, population, secondary sector, and tertiary sector were significant to energy consumption. A tertiary sector can help to reduce energy consumption to some extent. This could give suggestions about changing industry structure. More and more attention has been paid to energy intensity. The strategic approach to sustainable development requires reducing energy intensity while developing the economy. Since China is committed to achieving carbon emission peak by 2030, this paper predicts the energy intensity of China in the next decade based on a DL algorithm. The prediction results show that energy intensity would slightly decrease in the next decade. Different types of energy represent the industrial structure behind economic growth. Therefore, this paper was conducted using ridge regression (RR) to explore the relationship between different types of energy and energy intensity. In addition, the effect (positive or negative) of different energy sources in reducing energy intensity has also been explored. We found that the best way of developing the economy and reducing energy consumption is to use natural gas and hydroelectric instead of coal. This can guide policy development about changing energy source structure. [ABSTRACT FROM AUTHOR]

• The use of GB techniques based on 106 projects was examined for future upgrading. • Water-saving and site planning categories exhibited the highest achievement. • This study identifies four main barriers limiting GB quality upgrading. • This study presents recommendations in four aspects for GB quality upgrading. • Upgrading GB projects for urban heat mitigation and urban flooding management. Building sector is one of the primary culprits of environmental deterioration and energy consumption. Green building (GB) can be an effective solution to these challenges and has been prioritised by many nations, while the quality of most GBs was still low. Therefore, this paper aims to examine the application of GB techniques. In specific, an empirical study was conducted among 106 GBs in China. Results indicate that both water-saving and site planning categories received the highest achievements, followed by indoor environmental quality and energy-saving, and the material-saving and innovation categories were the most difficult to achieve. The items in site planning, energy-saving and indoor environmental quality clusters that depended more on design techniques could be realised evenly, while the water-saving and material-saving clusters that relied more on materials and equipment witnessed two extremes: one approaching to 100% and one close to zero. There could be an increase in technique achievement from low-quality GBs to high-quality GBs. Nevertheless, the achievements of many items were extremely in both one-star, and two- and three-star groups. Some even witnessed the reduction from the low-quality GBs to the high-quality GBs. A further investigation indicated that the unavailability of GB technique checklist, the impact of economic cost, low technological operability and the unavailability of GB products constrained the GB technique application. The combining impacts of them could further lower the GB technique application. To unlock these barriers, efforts should be made from the perspective of (1) revision and localisation of GB standard, (2) extensive technical support, (3) government regulations and support, and (4) the co-benefits: integration with other programmes. Overall, this paper is of value to improve GB technique application and facilitate the transitions towards higher quality GB agenda. [ABSTRACT FROM AUTHOR]

Energy use between urban and rural areas is very important in the context of the global energy transition and climate change. However, it is difficult to measure the differences and inequalities in energy consumption due to data limitations. In this paper, a dataset distinguishing urban-rural energy consumption has been generated. We construct an energy inequality index (EI) to assess the difference in per capita energy consumption (PEC) between urban and rural areas. We find that the EI has decreased significantly from 10.42 in 2000 to 1.43 in 2020. Western China has a higher EI than the developed coastal areas. We further define 7 urban-rural types and find that the urban center has the highest PEC, while the rural cluster has the lowest. Cluster analysis shows that prefectures have different equalization trends, namely volatile decline, rapid decline, increase before decline, incremental decline. The urban-rural structure plays an important role in the different trends, and 4 modes of urban-rural energy consumption are summarized, namely urban-centered, urban-suburban double-centered, multi-centered and rural-biased. These results are valuable for understanding the energy consumption between urban and rural China. • A dataset distinguishing urban-rural per capita energy consumption (PEC) has been generated. • China's urban-rural energy inequality has decreased from 10.42 in 2000 to 1.43 in 2020. • Western China are facing a more urban-rural energy inequality than the developed coastal areas. • Among the 7 defined types, urban center ranked highest PEC, while rural cluster ranked lowest. • 4 modes of urban-rural energy consumption are summarized. [ABSTRACT FROM AUTHOR]

With the completion of the poverty alleviation task in China, the Chinese economy has made great breakthroughs. Meanwhile, the implementation of Chinese "dual carbon" goal has entered an important window period of both strategic opportunities and difficulties. The emission of carbon dioxide (CO2) leads to the greenhouse effect, which affects the sustainable development of society. Therefore, this paper proposes an improved analytic hierarchy process (AHP) with Slacks-based measure integrating data envelopment analysis (SBMDEA) (AHP-SBMDEA) based efficiency evaluation model for different provincial-level administrative regions in China, which is used to analyze and optimize the Chinese energy structure of different provincial-level administrative regions. With coal, gasoline, petroleum, fuel oil, diesel, crude oil and natural gas as inputs, the per capita Gross Domestic Product (GDP) as the desired output and the CO2 as the undesired output, after linear weighted calculation of the results of the AHP-SP model and the SBMDEA model, the energy efficiency evaluation model of different provincial administrative regions in China is established. The results show that there is a large difference in efficiency between Chinese northern and southern regions, and the overall efficiency of southern regions is higher than that of northern regions. In addition, it is easier to find out the optimal energy efficiency benchmark, which can provide suggestions and help to guide the energy consumption input structure improvement of other inefficient provincial-level administrative regions. Furthermore, the energy structure can also be adjusted through the redundant variable calculated by the SBMDEA model. For example, Sichuan Province can reduce the consumption of the coal, the gasoline, the diesel, the fuel oil, the crude oil and the natural gas by 5269.95 × 10000 tons (WT), 513.01 WT, 59.05 WT, 34.37 WT, 4,73.33 WT and 130.37 billion cubic meters (BCM), respectively. Its CO2 emissions can be reduced by 1925.4 WT, and raise the efficiency of energy utilization in the province. [Display omitted] • Novel economy and CO 2 emissions evolution model based on a AHP-SBMDEA is proposed. • The proposed model can identify the optimal energy efficiency benchmark. • GDP per capita can be increased and CO 2 emissions can be decreased. [ABSTRACT FROM AUTHOR]

In this era of global warming the importance of climate risk cannot be understated, and finding ways to reduce climate risk is a topic worthy of study. In this paper, we innovatively examine the role of renewable energy technology innovation on climate risk in China. In addition to their linear relationship, we also investigate the asymmetric and heterogeneous impact, detect the impact channels, and find that (1) increased renewable energy technology innovation can effectively alleviate the climate risk situation. Accordingly, the development of renewable energy technology innovation can make a significant contribution to CR abatement. (2) Pronounced impacts of renewable energy technology innovation on climate risk can be observed in the higher quantiles (75th and 90th) of climate risk. (3) Renewable energy technology innovation is a powerful weapon for eradicating climate risk in provinces with a higher level of government fiscal expenditure. And (4) renewable energy technology innovation has an impact on climate risk by facilitating energy consumption efficiency, which is a necessary mediator. These conclusions inspire us to put forward several corresponding policy implications for better climate risk governance and renewable energy technology innovation development. [ABSTRACT FROM AUTHOR]

This paper constructs a carbon quota allocation index that takes into account equity, efficiency and ecological construction, and calculates carbon emissions and energy consumption data in important periods based on the expected carbon emission targets and economic and social development indicators of the Chinese government. Based on the calculated carbon emissions, the zero-sum game data Envelopment model (ZSG-DEA) is used to discuss the initial allocation of regional quotas and the optimal carbon quota scheme. The results show that:(1) there is a large gap between the optimal carbon quota and the initial carbon quota allocation in Shandong, Guangdong, Jiangsu and other provinces in 2025, and the implementation of emission reduction measures should be accelerated. (2) By 2030, the final allocation of Beijing, Tianjin, Inner Mongolia, Qinghai, Shanghai, Ningxia, Liaoning and Xinjiang will be positive. The provinces with negative final allocation should carry out the work of carbon peak as soon as possible to avoid increasing the pressure of emission reduction in the future. (3) The central region faces greater pressure of emission reduction, while the western region can accept the transfer of carbon emissions from other regions over time. The research conclusions have important policy implications for establishing a fair and effective carbon quota allocation mechanism, achieving the national total carbon emission control target, stimulating the vitality of the unified carbon market, and promoting regional coordinated emission reduction. • There exist differences in carbon quota allocation among provinces in the future. • There are changes in the initial and optimal carbon quotas obtained by each province. • The role of carbon emissions between regions is changing over time. [ABSTRACT FROM AUTHOR]

The energy rebound effect is a potential threat to energy-saving targets based on energy efficiency improvements. This paper employs a stochastic energy demand frontier model to analyze the energy demand and rebound effect in China's urban residential sector. Using a panel data set of 30 Chinese provincial-level regions over the period 2001-2014, for the first time, we investigate the degrees and determinants of China's urban residential energy demand and energy rebound effect. The results show that residents' income level, energy price, temperature deviation, population scale, household size, and district heating system are significant influencing factors of residential energy consumption. Regarding the energy rebound effect, we find that energy price is negatively correlated with the rebound effect, and an inverted U-shaped relationship between residents' income level and rebound-effect size exists. The magnitude of the rebound effect varies across regions, with an average of 65.4%. The main policy implication generated by this study is that it should be in urgent need of energy pricing reform to mitigate the rebound effect in China. [ABSTRACT FROM AUTHOR]

Abstract Currently, wind and solar energy have not been well utilized in China, and the rate of abandoned wind and solar facilities in China is increasing annually. Renewable portfolio standards (RPS) are an effective system for promoting large-scale renewable energy integration and consumption and realizing the goal of renewable energy development. To clarify the interactive relationship between the different levels and multiple actors in RPS, this paper uses policy network theory to analyze the interactive relationship of stakeholders from the three aspects of network subject, network structure and network interaction. The policy network of the RPS consists of the policy community, professional network, intergovernmental network, producer network and issue network. Under the RPS, to meet their own needs, participants affect the formulation and implementation of the RPS through the actions of confrontation, alliance, competition and cooperation. In different stages of developing the RPS, the openness and integration of policy networks change accordingly. This study overcomes the limitations of past simple analyses of the actor relationship in the policy process and thereby offers certain reference significance. Highlights • The actors of RPS policy networks are analyzed. • This paper analyze the game relationship of the stakeholders from three aspects. • This research reveals the network relationship between multiple stakeholders. • This study breaks through the limitations of past analysis of actor relationship. [ABSTRACT FROM AUTHOR]

Abstract Whilst a plethora of literature has viewed technological progress as one of the critical influencing factors in relation to energy consumption and CO 2 emissions, little effort has been made to identify the sectoral differences in the relationship between technological progress and CO 2 emissions. Thereby, this paper remedies the inadequacies in the extant literature by empirically investigating the impact of technological progress on CO 2 emissions, specifically taking into account its heterogeneous effect in various economic sectors. This paper first decomposes the effect of technological progress as taking place in heavy industry, in light industry, in construction industry, and in service industry. A panel quantile regression approach and a balanced city panel data model are then applied, covering the period 2001–2013 in China. The empirical results show that technological progress in heavy industry and light industry surprisingly facilitates a higher level of CO 2 emissions, despite its prominent contribution to energy efficiency improvement. Meanwhile, as distinct from the effect it shows in the heavy and light industries, technological progress in construction and service industries exerts a negative effect on CO 2 emissions. Additionally, this paper further discovers that the strength of the multiple impacts of technological progress also varies with the level of emitters. By studying the heterogeneous effect brought about by technological progress in different economic sectors and emitters, this paper provides a comprehensive understanding of the relationship between CO 2 emissions and technological progress. Highlights • The study considers the sectoral and scale heterogeneity of technological progress in relation to CO 2 emissions. • We apply a panel quantile regression approach to balanced city-level panel data. • Technological progress within different economic sectors exerts different effects on CO 2 emissions. • The role of technological progress in moderating energy intensity varies across emitters. [ABSTRACT FROM AUTHOR]

Abstract This paper explores the effects of enforced Chinese policies regarding environmental matters at the provincial level. The paper proposes several features and explores datasets from the last four Five-Year Plans, which extensively covered the period from 1995 to 2015. As the datasets are multidimensional, dimensional reduction is applied with a control of information loss described by data variance preservation. A data-based clustering algorithm is applied to identify the similarities, and characteristics are explored in relation to the specific features. The use of this method makes it possible to identify the changes in the relevance of the features in the most recent Five-Year Plan, in which decarbonization is relevant instead of productivity. This method also makes it possible to identify specific efforts several provinces have made to introduce cleaner energy production. Following the analysis, it is concluded that the proposed features enable the proposed method to be considered a tool for analyzing the real-world effects of the adopted policies. [ABSTRACT FROM AUTHOR]

Abstract In recent years, China's wind power industry has developed rapidly, and become the global wind power leader. At the same time, China's wind power industry is also facing many problems and challenges. In this paper, a comprehensive assessment is presented to reveal the development history of China's wind power industry, power demand and cost, regional distribution of wind power, wind turbine manufacturers, and government incentives to wind power industry. Subsequently, future development and challenges are proposed, focusing on the challenge of wind power integration and consumption, the challenge of management and market competition mechanism, and the challenge of large-scale and rapid development. Finally, the corresponding measures are put forward. The fundamental goal of this paper is to understand the history, current situation and future challenges of China's wind power industry. Highlights • A comprehensive assessment on the development of China's wind power industry is presented. • The development history of China's wind power and energy demand are introduced. • Multi factors related to China's wind power industry are investigated. • Future challenges and corresponding measures of China's wind power industry are proposed. [ABSTRACT FROM AUTHOR]

Identifying the research topics of China's energy transition policy and predicting future research trends are crucial for policymakers to make informed decisions and advance the energy transition. This study applied the Latent Dirichlet Allocation (LDA) to extract 26 major research topics from the 13,976 abstracts of Chinese policy research papers in web of science (WOS), conceptualized the five most popular topics and used the ARIMA model to predict trends over the next 36 months. The results show that except for Economic and Environmental Impact of Renewable Energy Consumption (Topic13), which will first experience unanticipated fluctuations and then show strong growth capacity, all other topics will continue to remain positive growth trend. Research and Development (Topic3) is driven by the urgency of China's energy transformation. Economic and Environmental Impact of Renewable Energy Consumption (Topic13) is driven by the potential for the development of renewable energy. Economic Impact of Climate Change (Topic26) is driven by the climate change debate. Economic Growth, Urbanization, and Energy Consumption (Topic7) is driven by a discussion of their relationship and the mechanisms influencing them. Regional Efficiency and Productivity Analysis (Topic19) is driven by regional differences in China's energy policies. [ABSTRACT FROM AUTHOR]

This paper proposes an extended Solow decomposition framework with a finite mixture model, which is incorporated to account for heterogeneous regimes. The model decomposes green economy into two different components, namely, green total factor productivity and factor endowment. Then, we reestimate the growth sources of green economy and especially the importance of energy consumption in China's provincial industries over 2000-2015. The empirical results suggest that there are three green growth regimes across Chinese provinces for overall economy and different industries. Specifically, some provinces switch regime over time, while the others maintain the same regime. Furthermore, when controlling for regime heterogeneity, the contribution of factor endowment decreases and that of green total factor productivity increases. With respect to energy consumption, traditional methods overestimate its importance in the primary and tertiary industries and underestimate that in the secondary industry. In addition, the reliance of China's overall economy and the secondary and tertiary industries on energy consumption decreases as economy develops. [ABSTRACT FROM AUTHOR]

As a secondary energy, electricity is an important channel between original energy and energy consumers. Electricity price is a critical factor for the interests of all involvers in the electric power market. It also plays an important role for the sustainable development of energy and environment. Smart grid is a new conception proposed in recent years to improve the intelligent level and increase the efficiency of electric power system operation. Smart grid combines and integrates information technology, communication technology and intelligent control technology with tradition power system. To achieve the many objectives of smart grid, Demand response (DR), as an effective technique of demand side management (DSM), refers to the changes in electricity consumption behavior of users in response to the dynamic price or incentive rewards. Price based demand response (PBDR) is one of the two major DR programs. In this paper, we first introduce the pricing theories in economics, the pricing of electricity and the development of electricity pricing in China. Then, we present a detailed discussion on the PBDR strategies in the DSM of smart grid. Also, the research status of PBDR is reviewed. Finally, it gives a summary of the whole paper in the last Section. [ABSTRACT FROM AUTHOR]

A comprehensive review of the thermal power industry and the accurate forecasting of carbon emissions can provide valuable information to improve energy efficiency and act as a tool for policy makers to realize sustainable and low-carbon emissions from the thermal power industry. In this paper, we study the low-carbon development of China's thermal power industry based on an international comparison from three perspectives: review, analysis and forecast. Initially, we review both the international and national energy consumption of China; although gaps in energy efficiency still exist between China and countries with advanced thermal power technology, China's thermal power industry is gradually following a low-carbon development route. Then, we analyze low-carbon technologies for thermal power units, including ultra-super-critical technology, integrated gasification combined cycle technology, and carbon capture and storage technology and present a design for environmental protection technology for thermal power units. Carbon emissions should be effectively and successfully handled to improve the prospects of China's thermal power industry. Therefore, this paper forecasts carbon emissions by using a hybrid grey model that is optimized by the firefly algorithm and adjusted by weakening buffer operator based on the calculated carbon emissions. If China's carbon emissions from the thermal power industry increase according to the present rate, China will have difficulty in realizing its carbon reduction target by 2020. Finally, related future policies for the 13th Five-Year Plan of China are proposed based on low-carbon policies around the world with regard to financial, technological and industrial aspects to help the thermal power industry achieve healthy and low-carbon development. [ABSTRACT FROM AUTHOR]

Atmospheric reactive nitrogen (Nr) has been a cause of serious environmental pollution in China. Historically, China used too little Nr in its agriculture to feed its population. However, with the rapid increase in N fertilizer use for food production and fossil fuel consumption for energy supply over the last four decades, increasing gaseous Nr species (e.g. NH3 and NOx) have been emitted to the atmosphere and then deposited as wet and dry deposition, with adverse impacts on air, water and soil quality as well as plant biodiversity and human health. This paper reviews the issues associated with this in a holistic way. The emissions, deposition, impacts, actions and regulations for the mitigation of atmospheric Nr are discussed systematically. Both NH3 and NOx make major contributions to environmental pollution but especially to the formation of secondary fine particulate matter (PM2.5), which impacts human health and light scattering (haze). In addition, atmospheric deposition of NH3 and NOx causes adverse impacts on terrestrial and aquatic ecosystems due to acidification and eutrophication. Regulations and practices introduced by China that meet the urgent need to reduce Nr emissions are explained and resulting effects on emissions are discussed. Recommendations for improving future N management for achieving 'win-win' outcomes for Chinese agricultural production and food supply, and human and environmental health, are described. This article is part of a discussion meeting issue 'Air quality, past present and future'. [ABSTRACT FROM AUTHOR]

China has launched energy quota right trading system, as one of the sustainable operations, since 2016 to cap the total energy consumption, however the economic and energy saving effect of this new policy is unclear. Based on the input and output panel data of China's 29 manufacturing sub-industries, this paper constructs the non-parametric optimization model under the command-and-control and the energy quota right trading scenario, to compare their potential economic gains and energy savings of these two polices for Chinese manufacturing industries. Results show that, whether at overall level or at the sub-industries level, the economic potential and energy-saving potential from energy quota right trading are higher than those from command-and-control. However, a part of energy-saving potential will be squeezed out due to the negative externality of the energy market trading. We suggest the well integration of both command-and-control and the market mechanism to achieve a Win–Win development. [ABSTRACT FROM AUTHOR]

This paper examines the CO2 emissions from energy consumption in China's transport sector, conducting an empirical investigation into the spatial distribution characteristics and influencing factors of transport CO2 emissions. This study, which is based on province-level panel data covering the 30 provincial regions during the period 2001-2016, used the methods of exploratory spatial data analysis (ESDA) and the extended STIRPAT model (examined by the method of system-generalized method of moments (Sys-GMM) regression). The results indicated that the amount of CO2 emissions in China's transport sector has increased steadily during the observation period, but there was a noticeable disparity across the provinces and regions. From the perspective of spatial dimension, the spatial agglomeration characteristics of provincial transport CO2 emissions tended to be strengthened, and the pattern evolutions of spatial distribution presented a path-dependence effect to some extent. The scale of population was found to be the most important influencing factor of transport CO2 emissions, and followed by the per-capita GDP. Further, the improvement of energy efficiency was the key factor to controlling transport CO2 emissions. Compared to freight transportation, passenger transportation was more important in transport CO2 emissions reduction due to its lower efficiency of energy utilization and rapid growth. Meanwhile, electrification played an important inhibitory effect on transport CO2 emissions because of its high fuel efficiency and less pollution. Importantly, we could not support the existence of the environmental Kuznets curve (EKC) hypothesis in China's transport sector during the observation period, which describes the relationship between the environmental pressures and economic development. These findings contain some meaningful implications for policy makers: confirm the priority transport CO2 emissions reduction areas, improve transport energy efficiency, strengthen passenger transportation decarburization policy, and highlight the model shift of fuel consumption. [ABSTRACT FROM AUTHOR]

Existing studies pay little attention to when or under which conditions foreign direct investment (FDI) can spill energy-saving technologies. From a perspective of energy-biased technical change and using a two-layer nested constant elasticity of substitution (CES) production function, this paper investigates the energy-saving spillover effect of FDI on technical change (i.e., energy-saving spillovers) in China between 2002 and 2015. In particular, we consider the conditions of marketization, industry, technology, and labor mobility to examine whether and when FDI has energy-saving spillovers. The results indicate no income inequality effect, i.e., there is no evidence supporting that FDI flowing into low- and middle-income regions increases energy consumption, while FDI flowing into high-income regions conserves energy. However, there is a condition effect: FDI can improve (support the halo effect) or deteriorate (contradict the halo effect) the environmental performance under different conditions. Moreover, there is a threshold effect: the direction of FDI spillovers varies with the different levels of the threshold variables. An increasing marketization motivates enterprises to select energy-biased technologies. It is more likely to generate energy-saving spillovers in the regions with a lower specialized agglomeration level. FDI will have energy-biased spillovers when domestic technological level is relatively high with an evident energy-biased technology. In addition, a moderate labor mobility is beneficial to the energy-saving spillovers of FDI. [ABSTRACT FROM AUTHOR]

The household sector of China is responsible for 11.7% of national energy consumption and 12.6% of carbon dioxide (CO 2) emissions in 2015. Thus, revealing the determinants of household CO 2 emissions (HCE) is extremely important for national efforts towards emissions mitigation. In this context, this paper investigates the driving forces behind national and regional HCE changes employing a temporal Logarithmic Mean Divisia Index (LMDI) model. It also analyses interregional discrepancies in HCE using a spatial LMDI model. This study decomposes the changes or discrepancies of national and regional HCE from 2000 to 2015 into seven key factors. The temporal analysis indicates that household income is the predominant determinant explaining the increase of HCE, whereas energy intensity is the crucial determinant contributing to the mitigation of HCE. The spatial analysis reveals that the number of households and energy intensity are primary driving forces accountable for growing discrepancies in HCE, followed by household income, energy structure and carbon emission coefficient. The analysis also suggests that resourceful and economically developed regions generally have larger potential for mitigation of HCE. The study concludes with some policy recommendations based on the results. [ABSTRACT FROM AUTHOR]

As a non-Arctic country and a major energy consumer, China is increasingly interested in participating in Arctic energy development. This study aims to investigate potential strategies to promote China's participation in Arctic energy development. Accordingly, this study analyzes the strengths, weaknesses, opportunities, and threats (SWOT) of China's participation in Arctic energy development based on a discussion of the current status of Arctic energy development and the Arctic policies of major countries. In addition, this work develops strategies in accordance with the above analysis. The results show that China has strengths in terms of capital, energy demand, policy support, and international cooperation when participating in Arctic energy development, while its weaknesses include the lack of core technology and equipment, high carbon intensity of energy development, and geographical disadvantage. China faces opportunities stemming from conflicts among Arctic states, the advancement of global carbon neutrality, and the development of Arctic waterway while facing threats such as increased competition, international public opinion pressure, high development costs, environmental risks, and pandemic instability. Under an integrated framework, this work offers four strategies: Strength-Opportunity (SO), Strength-Threat (ST), Weakness-Opportunity (WO), and Weakness-Threat (WT). Finally, this study proposes specific measures in four areas, including strengthening policy support, promoting technical research and development, enhancing international cooperation, and improving enterprise competitiveness. [Display omitted] • This study examines China's participation in Arctic energy development. • This paper reviews the status of fossil and non-fossil energy in the Arctic. • This study compares the Arctic energy development strategies of major countries. • This study proposes four strategies, namely SO, ST, WO, and WT. [ABSTRACT FROM AUTHOR]

The decoupling analysis is a useful method to study the relationship between economic growth (GDP) and energy consumption or environment issue. However, no paper has paid attention to why does decoupling indicator changes over time? Based on the Log-Mean Divisia Index (LMDI), this paper provides a new way to study the changes of C-G (CO 2 emission-GDP) decoupling indicator in China. The changes of C-G decoupling indicator are decomposed into C-EF (CO 2 emission-Fossil energy consumption) decoupling indicator effect, EF-E (Fossil energy consumption-Total energy consumption) decoupling indicator effect, E-G (Total energy consumption-GDP) decoupling indicator effect. The main results as follows: (1) In China, energy-related CO 2 emission increased to 8858.47 Mt in 2013. (2) During the study period, coal accounted for more than 67% of total primary energy consumption. (3) The curve of energy intensity has the same trend as the CO 2 emission coefficient. (4) Over the study period, only three decoupling statuses occurred in the C-G decoupling. (5) During the study period, the E-G decoupling effect played an important role in the change of C-G decoupling indicator. However, the C-EF decoupling effect played a minor role in the change of C-G decoupling indicator over 1996–2013. [ABSTRACT FROM AUTHOR]

Sustainable consumption (SC) is key for sustainable development, but only limited studies have examined how to motivate SC among consumers in developing countries. Younger consumers tend to more sustainable consumption while whether they really understand the SC concept is not clear. To explore the role of SC understanding for motivating SC behaviors, this paper develops a concept model with hypotheses to propose that SC understanding mediates relationships between influencing factors and SC behaviors. Based on 623 usable questionnaires collected from junior high schools and senior high schools in three eastern cities of China, five influencing factors for SC behaviors are identified, they are, education, awareness & attitude, social influence, effectiveness of energy saving and emission reduction for sustainable products, and differentiation of sustainable products from regular products. Statistic results through hierarchical regression analysis demonstrate that SC understanding is necessary to motivate SC behaviors with certain influencing factors. Chinese adolescents can understand the SC concept through education and then purchase sustainable products. Only if sustainable products can show benefits of energy saving and emission reduction, Chinese adolescent would like to use these products. Environmental awareness and attitude can bring environmental treatment and disposal of products, but SC understanding is necessary. This paper contributes to extend the TPB to develop a conceptual model including education as one influencing factor for SC behaviors. It also develops three factors for SC behaviors from the product life cycle perspective. Besides, it also contributes to extend the previous studies about motivation of SC consumption to adolescents in an emergent economy of China to examine the role of SC understanding. Statistic results reveal the low implementation level of SC behaviors, and the government should highlight sustainable education to improve sustainable awareness and SC understanding. It is also shown that adolescents would like to purchase sustainable products if environmental performance of such products can be demonstrated, which also provide insights for enterprises to achieve win-win opportunities. [ABSTRACT FROM AUTHOR]

Demand Response (DR) has been extensively developed and implemented in the US and Europe. However, DR hardly exists in many developing countries for similar problems such as rigid power market and state monopoly. With the increasing imbalance between supply and demand in China's power industry, the government has issued new policies on DR and approved the first batch of pilot cities. China is setting a good example of how to encourage DR under monopolistic electric market and open up the market to aggregators and DR suppliers. This paper summarizes the current DR status, feasible DR market schemes and DR pilot projects in China. First, electric power system reform, renewable energy policies and power industry development are reviewed, highlighting the problems associated with the current dispatch mechanisms of DR policies and markets. New DR programs and DR-related policies are also introduced. On this basis, the driving forces and challenges associated with DR in China are analyzed. The major challenge is the lack of a suitable market mechanism for the current Chinese power industry. Hence, this paper presents six feasible strategies that fully utilize the existing policies. Additionally, the latest DR applications in different pilot cities are summarized and analyzed. [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]

The paper takes the industrial coupling symbiosis network (ICSN) of oil and gas resource-based urban eco-industrial parks (EIPs) as the research object. The purpose is to judge the stability of a symbiotic, one-way relying and two-way symbiosis model applied to oil and gas resource-based cities through constructing a logistic growth symbiotic network model. Through identifying and analyzing the stability model, the research concludes the stability conditions. The analytic results are as follows: In the symmetric ICSN system, it is important to maintain equal status and balanced benefit distribution among the coupled symbiotic enterprises. In the one-way-based ICSN system, the core enterprise significantly promotes the improvement of ecological efficiency the satellite enterprise while the satellite enterprise less effectively promotes the improvement of ecological efficiency of the core enterprise. In the two-way ICSN system, the core enterprise and the satellite enterprise are easily affected by the symbiotic enterprises within the network, and the stability is extremely poor. These conditions and analytic results will serve as a basis for constructing an efficient closed-loop system for ICSN of the oil and gas resource-based urban EIPs.Through the stability analysis of the industrial coupling symbiotic network of the oil and gas resource-based urban eco-industrial park, it can determine the stability conditions that affect the overall performance of the industrial park. Studies have shown that increasing network stability and improving energy efficiency in the park can improve the overall sustainability of the eco-industrial park and accelerate the effective transformation of resource-based cities. • Constructing an industrial coupling symbiotic network model. • Given stability conditions for three symbiotic modes. • Extremely poor stability of Two-way relying industry coupling symbiotic network. • Logistic growth model for network stability analysis. [ABSTRACT FROM AUTHOR]

As part of the country's efforts to achieve green development, China implemented a mandatory energy intensity reduction target in its 11th "Five-Year Plan (FYP)" in 2006, and then began to roll out a series of relevant measures. However, existing studies have paid little attention to the actual effects of China's energy intensity constraint policy (EICP). In this paper, using panel data from China's 36 industrial sub-sectors covering the years from 2001 to 2014, we adopt the difference-in-differences (DID) method to investigate for the first time the EICP's (marginal) effect on total factor energy efficiency growth (TFEEG). We also estimate the superposition effect caused by the introduction of a carbon intensity constraint policy (CICP) on TFEEG, through the difference-in-difference-in-differences (DDD) strategy. Finally, using counterfactual, re-grouping and quasi-DID analyses, we conduct a series of robustness tests of the empirical results. The results show that the TFEEG in China's industrial sector experienced an overall declining trend between 2001 and 2014. The implementation of the EICP has had a significantly negative effect on the improvement of the TFEEG of sub-sectors with higher levels of energy intensity. After the implementation of the EICP, the TFEEG rate of these sub-sectors declined by 4.31%, compared to the rate of the other sub-sectors. The results of a series of robustness tests indicate that such a negative effect is credible. The marginal effect in the first two years after the implementation of the EICP was significantly negative, while the superposition effect of the introduction of a CICP on industrial TFEEG remained negative. Thus, the Chinese government should reinforce the implementation of energy-saving policies by introducing additional market-oriented auxiliary policies to propel the green development transformation of China's industrial sector. [ABSTRACT FROM AUTHOR]

Highlights • The average compliance cost for China's fuel economy regulation by 2020 is $688. • The market share of New Energy Vehicles will be 16.9% and 34.2% by 2025 and 2030. • China's fuel saving target cannot be fully achieved using current schemes. • Vehicles will grow heavier due to the regulation's curb weight based feature. • The favorable test method will make PHEV the most promising fuel-saving technology. Abstract Under the annually strengthened fuel economy regulations for light-duty vehicles, a technology pathway provides automakers with forward-looking guidance to strategically manage their vehicle assortment and fuel-efficient technologies. Because the regulations worldwide are very different in terms of their various schemes and designs, it is difficult to calculate the optimal pathway or to evaluate a regulation's impact on the vehicle fleet without an assessment model specifically designed to do so. To date, China has issued four Phases of Corporate Average Fuel Consumption regulations; however, a bottom-up optimized technology pathway for the regulation compliance of domestic automakers is still missing. In this paper, real-world data on each vehicle model's market and technology parameters are used to describe China's passenger vehicle fleet. Employing a combinational optimization assessment model for China's regulation, this study calculates bottom-up fuel-efficient technology pathways for complying with the 2020 regulation and the potential 2025–2030 regulations. Under scenarios that do not consider the subsidy or super-credit preferential policies for New Energy Vehicles (Plug-in Hybrid Electric Vehicles and Battery Electric Vehicles in China), the average compliance costs for the three future phases of the regulations will be $687.5, $2344.4 and $3111.2. The average fuel consumption rate of passenger vehicle fleet will reach 5.28, 4.07 and 3.33 L/100 km, and the average vehicle curb weight will increase by 4.7%, 6.3% and 9.2%. These results mean that if current schemes are followed, the regulations will fail to achieve their fuel saving targets and to promote lightweighting vehicles. The technology pathway of powertrains and specific fuel-efficient technologies is analyzed in great detail. The results show that the market share of New Energy Vehicles will increase to 16.9% and 34.2% by 2025 and 2030, and that Plug-in Hybrid Electric Vehicle will be the most promising fuel saving technology due to the preferential test method in China. The sensitivity of the compliance cost and the market share of New Energy Vehicles to regulation stringency is further analyzed. For every change in regulation stringency of 0.05 L/100 km in the 2025 and 2030 regulations, the compliance cost will change by 3.03% and 2.31%, while the market share of New Energy Vehicle will change by 0.58% and 0.73%. These results indicate that if the various schemes for regulation compliance are not taken into account, only making adjustment to the regulations' stringency may have little effect on reducing automakers' compliance cost or promoting the market share of New Energy Vehicles. [ABSTRACT FROM AUTHOR]

Energy efficiency (EE) is an important strategy for China to save energy and reduce energy-related emissions. With significant regional diversities in China, it is important to conduct the EE assessment at the regional level. Usually, the regional EE assessment is applied to 30 regions in Mainland China using the data envelopment analysis (DEA) technique. With the "Belt and Road" strategy initiated by the Chinese government, it is reasonable and necessary to take Hong Kong, Macao, and Taiwan into consideration. However, such data expansion for China's regional EE assessment using DEA can reverse the relative rankings of some decision-making units, which is called the "rank reversal" phenomenon. In this paper, we illustrate in theory that rank reversal occurs in general DEA models, and apply the most popular five DEA models to assess China's regional energy efficiency from 2000 to 2014. The empirical study shows that the 30 regions in Mainland China have the least rank reversal when Tone's slack-based model (SBMT) is adopted. The main cause of ranking reversal is the addition of decision-making units lying on production frontier. Better understanding of the rank reversal phenomenon is critical for the energy efficiency assessment using DEA to inform the policy makings. [ABSTRACT FROM AUTHOR]

More and more literature are investigating the energy efficiency performance at provincial level. However, there are many problems in provincial energy balances in the officially released yearbooks, such as inconsistencies of statistical scope, the large gap between national data and sum of provincial data, and nontransparent data revision. Using yearbook data directly may result in errors and even some contradictory-to-actuality conclusions. Given this, based on the national economic census, this paper systematically revises and adjusts the 1995–2014 energy balances at province level. A four-dimension (province, year, sector, and energy type) energy dataset is constructed, which supports the structural energy efficiency research at provincial level. [ABSTRACT FROM AUTHOR]

Abstract Industrial sector is responsible for the majority of China's carbon dioxide (CO 2) emissions and contributed most to the rapid increment in the first decade of this century. However, CO 2 emissions in the industrial sector stagnated due to China's economic slowdown since 2012. This paper aims to estimate the CO 2 emissions in China's industrial sector during 2010–2016 to deliver sectoral and regional details and uncover the reasons for the emissions stagnancy. We find that the emission stagnancy is a result of decreasing energy intensity and economic slowdown. Industrial restructuring within the entire industrial sector and emission intensity (emissions per unit of energy consumption) had limited effect on the emissions reduction. From the sectoral perspective, iron & steel and nonmetal sectors accounted for most reduced emissions in China's industrial sectors during 2014–2016. From the regional perspective, the emissions decrease mainly occurred in western and northeastern provinces, rather than more developed coastal provinces. Mitigation policies are raised, including the industrial structure shift from energy-intensive sectors to other sectors and addressing the emissions mitigation in rapid industrializing provinces, such as Xinjiang, Inner Mongolia and Ningxia, so that an earlier and lower emission peak of China's industrial sectors can be achieved. Highlights • Iron & steel and nonmetal sectors accounted for most emissions reduction. • Decreasing energy intensity and economic slowdown are the main reasons. • Emissions in most energy-intensive sectors have peaked or approach the peak. • Emissions decrease occurred mainly in the western and northeastern provinces. [ABSTRACT FROM AUTHOR]

Abstract This paper examines the relationship between hydroelectricity consumption and economic growth in China, while controlling for fossil fuel consumption, financial development, capital, institutional quality and globalization and its components for the period, 1970–2014. We have employed the Bayer and Hanck, (2013) combined cointegration test to examine the long-run relationships between those variables as well as the autoregressive distributed lag method with structural breaks as a robustness check. The empirical findings demonstrate a long-run relationship between those variables. Hydroelectricity consumption, fossil fuel consumption, capital, financial development and globalization and its components have a positive influence on GDP in China. The findings also provide predominant evidence on the long-run feedback hypothesis between the variables. The findings suggest that policies should be implemented to increase the role hydropower in the energy mix for sustainable economic growth in the country. Highlights • We examine the relationship between hydropower consumption and economic growth in China. • We control for fossil fuel consumption, financial development, capital, institutions and globalization. • We employ the Bayer and Hanck, (2013) cointegration test and ARDL bounds-testing method with structural breaks. • The findings demonstrate a long-run relationship between those variables. • The explanatory and control variables have positive influence on GDP in China. [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]

Abstract To address climate change effectively, it is essential to quantify CO 2 emissions and the driving factors in high-energy-consuming countries. China is the top CO 2 -emitting country; moreover, there is a lack of comprehensive analytical studies on quantifying the contributions of key drivers to high-energy-consuming countries' CO 2 emissions. Therefore, based on data of China's energy consumption from 2005 to 2016, this paper combines the extended Kaya identity with the logarithmic mean Divisia index (LMDI) decomposition method to construct an optimized carbon emission decomposition model. Carbon emission and carbon emission intensity are measured and decomposed. Then, the results of the decomposition are discussed, and the effects of various drivers on carbon emissions from energy consumption in China are analysed. Furthermore, we demonstrate real applications of decomposition analysis in policy-making using examples from China and present some ideas to reduce CO 2. The results show that from 2005 to 2016, China's total carbon emissions accounted for nearly one-third of the world's total carbon emissions, and the intensity of carbon emissions in China was generally higher than that of worldwide. The rapid development of economy and acceleration of urbanization are not conducive to reduction of carbon emissions. Reducing the intensity of energy consumption, adjusting the internal structure of the industry and perfecting the economic policy system should be important means used to promote the development of China's low-carbon economy in the future. Graphical abstract Unlabelled Image Highlights • Economic output increase is the largest driving factor promoting the CO 2 emissions of China. • In China, CO 2 missions from energy consumption in industrial sector accounted for the greatest proportion. • Phasing out excess capacity in China reduced emissions in the industry sector. • Energy intensity reduction is a key for high-energy-consuming countries to reduce CO 2 emissions. • Promoting the transformation of the industrial structure is an efficient way to reduce CO 2 emissions. [ABSTRACT FROM AUTHOR]

With the rapid development of China's economy, CO2 emissions have surged and environmental pollution has become increasingly serious, drawing broad attention domestically and overseas. To improve China's environmental quality, the Chinese government has set a series of ambitious goals to control carbon intensity and even cut total CO2 emissions. China's energy consumption structure relies heavily on coal, which is the largest contributor to CO2 emissions in China. However, so far research on the relationship between energy consumption structure and CO2 emissions in China remains scarce. This paper investigates this topic for the first time and calculates the input-output and alternative elasticities and impacts the energy consumption structure on carbon emissions per capita on the basis of the translog production function as the theoretical framework. The empirical results suggest that to substitute coal with oil or gas may decrease CO2 emissions significantly, and replacing coal with gas is the optimal choice. As such, improving China's energy structure by increasing the share of gas and decreasing the reliance on coal would cut China's CO2 emissions remarkably and benefit China's environmental quality. [ABSTRACT FROM AUTHOR]

In this paper, we employ multi-region input-output model to investigate China's embodied energy trade in 1995-2009, and then we use hypothetical extraction method to explore the effect of Chinese foreign trade on the other countries or regions of the world after extracting the trade volume between China and the world. We find that China was a net export country of embodied energy, and there was pronounced discrepancy between the sectors in importing and exporting embodied energy, where the sector Electrical and Optical Equipment had the largest import and export in embodied energy. In 2009, China imported mainly from Korea and exported mainly to Japan. In addition, extracting trade from China and other countries not only influenced the embodied energy consumption of China but also consumption and trade of other countries. China's government should pay more attention to sector differences when adopting policies like trade tax rate, and enhance cooperation with other countries. [ABSTRACT FROM AUTHOR]