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This research investigates how supply chain finance (SCF) affects the investment efficiency of new energy firms by adopting a sample of Chinese listed new energy enterprises from 2011 to 2019. With the help of data envelopment analysis (DEA) combined with the Banker-Charnes-Cooper (BCC) model, we calculate efficiency values and analyze the regression results of the Tobit model, and find that SCF significantly boosts the investment efficiency of new energy corporations by improving their cash-holding position. The results of mechanism analysis also suggest that both supply chain concentration and digital finance positively magnify the relation between SCF and corporate efficiency. After comparing the impact in the new energy firms with different characteristics, we conclude that the SCF effect in promoting corporate investment efficiency is more prominent for non-stateowned new energy enterprises located in the western region that have low equity concentration. The conclusions of this paper shed new light on the fusion of the SCF business into building a new energy industry cluster. [ABSTRACT FROM AUTHOR]

In the recent literature, energy efficiency got the attention of scholars due to its discouraging impact on CO2 emissions, which is considered the most prevalent greenhouse gas that human activities produce. Data reports that China is the leading CO2 emitting country across the globe, and still the environmental degradation is in progress. Thus, the current paper empirically investigates the impact of energy efficiency (ENEF), financial inclusion (FD), GDP, export diversification (EXD), and human capital index (HCI) on the environmental degradation of China over the period from 1988 to 2018. This study uses various time-series tests to empirically investigate the determinant of CO2 emissions, including normality tests, unit root tests, and combined cointegration tests. Besides, the long-run coefficients are analyzed via the fully modified ordinary least square (FMOLS), dynamic OLS (DOLS), and the Canonical Cointegrating Regression (CCR) estimators. The empirical findings reveal that all the variables are cointegrated in the long run. However, the coefficient estimate shows that ENEF and HCI significantly promote environmental sustainability. While GDP, FD, and EXD significantly promote environmental degradation by enhancing the CO2 level in the atmosphere. This study recommends practical policy implications based on the empirical findings: energy-efficient products and energy sources could be promoted. [ABSTRACT FROM AUTHOR]

Since its industrialization, China has been continuously promoting environmental governance, and it is worth studying whether this measure has been effective. In this paper, we use industrial pollution control to represent China's environmental governance. Further, we use growth drag caused by energy consumption to describe a win-win situation for energy conservation and economic development. This paper theoretically analyzes the impact of environmental governance on growth drag by incorporating the former into the growth drag model. Thereafter, using data from 283 cities for the period between 2003 and 2017, this paper applies the dynamic panel data model to investigate whether China's industrial pollution control can achieve a win-win situation and its transmission mechanism. The results show that industrial pollution control can alleviate growth drag, implying that China's environmental governance can achieve a win-win situation. However, the effect is more significant in Eastern China and areas with high industrial pollution control intensity. The transmission mechanism analysis shows that industrial pollution control achieves a win-win situation by improving technological innovation, promoting human capital accumulation, and optimizing manufacturing development, of which improving technological innovation is the most significant. [ABSTRACT FROM AUTHOR]

Green finance development is a comprehensive system with three aspects interacted: economic, environmental, and financial activities. Based on its internal mechanism, this paper constructs an evaluation system of green finance development, which fills the absence of existing studies on green finance development. The internal development of green finance is transformed into three subsystems by PSR (Pressure-State-Response) model, and the evaluation scores are calculated by the entropy weight method. As the applications of the evaluation system, the horizontal comparison and vertical trend of green finance development in different regions of China from 2004 to 2017 are analyzed, and the relationship between green finance and sustainable energy development can also be quantitatively analyzed. The results show that sustainable energy development can be promoted through the development of green finance, using various measures in dimensions of economic development, financial development, and environmental development. [ABSTRACT FROM AUTHOR]

Energy consumption and environmental treatment have always been hot issues. This paper focuses on these two issues in China and attempts to investigate them based on the energy-to-environment (E2E) double-process. To achieve this aim, this paper first develops two E2E double-process models. Moreover, an empirical study is conducted to evaluate the E2E double-process efficiencies based on the data of 30 provinces in China. The results show that: 1)The E2E double-process efficiency in China is stable. However, this efficiency is low with large differences among individual provinces. 2)The values of the E2E double-process efficiency and the E2E energy consumption efficiency of China are similar, and both values are lower than that of the E2E environmental treatment. 3)The E2E environmental treatment efficiency has a potential driving effect in each province of China. 4)The intermediate output is used as a complete or partial input could significantly affect the E2E double-process efficiency. [ABSTRACT FROM AUTHOR]

Based on the environmental Kuznets curve theory (EKC) and the double-dividend hypothesis of environmental tax, this paper aims to examine the relationship between environmental tax, economic growth, energy consumption, and carbon dioxide emissions in China, Finland, and Malaysia from 1985 to 2014 using panel autoregressive distribution lag (ARDL) models. This paper discovers an N-shaped relationship between the volume of carbon dioxide emissions and the value of the gross domestic product. Furthermore, this study confirms that the double-dividend effect of environmental tax exists in all three countries in the long run. Overall, this study argues that evidence from Finland and Malaysia on environmental taxes that help the country to save energy and reduce carbon dioxide emissions can provide a reference for China and other developing countries. [ABSTRACT FROM AUTHOR]

This paper constructs a dynamic computable general equilibrium model to forecast China's economy, energy use, and carbon emissions. The fossil energy sector and clean electricity sector are disaggregated in detail to obtain robust results. The analysis results show that the industry and energy structure will obviously change along with a high and stable economy growth trend by 2030. Although energy intensity and carbon emission intensity in China will decrease markedly, carbon emissions will keep rising and will not peak by 2030. Therefore, China's government must adopt effective measures to realize the commitment goal. [ABSTRACT FROM AUTHOR]

To investigate how to obtain the optimal balance between energy consumption and economic development, this paper proposes a multifactor optimization model (MFOM). Different from previous input–output optimization models, our proposed MFOM comprehensively considers the direct and indirect impacts of sectoral consumption activities on total energy consumption. The results show that MFOM achieves higher energy-saving goals by smaller adjustment to consumption activities than the previous input–output optimization models do. The results also show that the consumption of some products should be limited to achieve the energy-saving and economic growth goals, such as Non-ferrous Metal Ore Mining, Chemical Products and Ferrous Metal Ore Processing. Furthermore, the results indicate that the share of some sectors, especially high-level manufacturing sectors, significantly decreases in the consumption structure after optimization. To maintain the sustainable development of these sectors, the dependence of their production activities on energy-intensive products should be reduced. [ABSTRACT FROM AUTHOR]

This paper comprehensively evaluates the dynamic effects on China's environment and economy during the COVID-19 pandemic. Results show that the COVID-19 lockdown resulted in a temporary improvement in air quality. Furthermore, nitrogen dioxide (NO2) levels in the atmosphere in China were 36% lower than in the week after last year's Lunar New Year holiday, but this also led to an economic downturn. Moreover, the aerosol optical depth (AOD) decreased significantly. During the back-to-work period, the economy recovered and there was an increase in energy consumption, and CO2, NO2 emissions sharply increased to pre-lockdown levels. In the post-lockdown period, the AOD was lower than that of the same period last year. This study can provide reference for environmental policy making, as it demonstrates to what extent the control of pollution sources can improve air quality. Precise emission reduction and regional joint prevention and control are important and effective means for the prevention and control of O3 pollution. The health and economic benefits of COVID-19 pandemic control measures are incalculable. And this can provide an effective scientific basis and theoretical support for the prevention and control of air pollution. [ABSTRACT FROM AUTHOR]

China is vigorously promoting energy conservation and emission reduction, however, its heating industry is still characterized by high input, high energy consumption, high pollution, but low output. Addressing this issue is of great significance for green economy. This paper tries to figure out the reasons behind this phenomenon by estimating the optimal resource allocation in the industry. The results reveal that labor input plays the most important role, while capital input plays the least. Blind expansion and blind investment exist in the industry. Technological progress's impact on the heating output growth is limited. The contribution rate of scientific and technological progress is negative except 1985–1991 and 1994 indicating that the contribution rate of scientific and technological progress can become negative, and the negative effect grows with the increase in financial burden. This paper provides reference for the heating reform in China. [ABSTRACT FROM AUTHOR]

Dependency on coal consumption to maintain energy security is common to the majority of developing countries where the coal is found in abundance. China and India are the leaders in coal consumption from the developing countries group, so establishing a relationship between the coal consumption and the economic growth for these two will derive useful lessons for policy-makers. This paper re-examines the causal relationship between coal consumption and economic growth in China and India for the period 1969–2013, for the first time using a frequency domain–based Granger causality test proposed by Brietung and Candelon (2006). The empirical results support unidirectional causality running from coal consumption to economic growth for both China and India. The findings of this paper provide important policy implications for energy policies and strategies for these two countries under study. [ABSTRACT FROM PUBLISHER]

In the gray prediction, the GM(1,1) model has been applied widely, but the conventional GM(1,1) model prediction shows big errors sometimes. Many researchers improve prediction accuracy by changing the basic structure of model. The paper tries to make improvements in the models parameter estimation on the basis of new background value optimization without changing the models structure, and gives the following four methods: (1) estimating the parameter of gray model GM(1,1) with the optimized value of exponential curve as the background value; (2) estimating the parameter of gray model GM(1,1) with the optimized value of power function curve as the background value; (3) estimating the parameter of gray model GM(1,1) with the optimized value of polynomial curve as the background value; (4) estimating the parameter of gray model GM(1,1) with the optimized value of interpolation function as the background value. The last part of the paper builds the GM(1,1) model of China's total clean energy consumption with the four improved methods. The simulation and prediction results show that these methods all improve the prediction accuracy of model significantly. [ABSTRACT FROM AUTHOR]

There are differences in economic level, population size, and technical level in different stages. At the same time, as a coal-dependent country, other regions have foreign dependence on coal. Then the primary factors and influence degrees of CO2 emissions in different stages and areas with different coal dependents will be various. This paper adds urbanization rate, industrial structure, and energy consumption structure to the traditional STIRPAT model. Based on the expanded STIRPAT model, the panel data of 30 regions in China from 2005 to 2019 are used to analyze the different stages and areas with foreign coal dependence. The main influencing factors and degree of influence of CO2 emissions. Regression finds that population size, energy consumption, and industrial structure will increase regional carbon dioxide emissions. There is an "inverted U-shaped" curve relationship between economic development, technological level, and carbon dioxide emissions. The improvement of the urbanization rate can reduce carbon dioxide emissions. Carbon dioxide emissions. An "inverted U-shaped" curve relationship between per capita GDP and CO2 emissions in three research periods from 2005 to 2010, 2011 to 2015, and 2016 to 2019. At the same time, the inhibition effect of the urbanization rate is constantly strengthened, and the promotion effect of the coal consumption ratio is decreasing year by year. The influence of population size, technical level, and industrial structure on carbon dioxide emissions in the whole country and areas with different coal dependents varies with the study period. To provide a theoretical basis for local conditions and regional management in the future direction of energy-saving and carbon reduction. [ABSTRACT FROM AUTHOR]

Emissions trading schemes (ETS) area is a leading climate policy instrument worldwide and have been widely discussed and researched. However, few studies to date focus on the nexus of ETS and income inequality, an important socioeconomic phenomenon. To fill this gap, taking China as an example, this paper discusses the influence of ETS on income inequality and its dynamic changes using a time-varying differences-in-difference model combined with a propensity score matching approach. The results demonstrate that China's pilot ETS has contributed to reducing income inequality. Various robustness tests support this conclusion. Moreover, the strength of ETS's contribution to reduction in income inequality gradually increases over time. We further analyze the mediating effects of carbon intensity, energy consumption, industrial structure, and technological innovation. ETS reduces income inequality by reducing coal consumption. The regional heterogeneity analysis shows that, unlike in other regions, ETS has a positive impact on income inequality (i.e. it increases it) in the eastern region in China due to its optimized energy structure and relatively complete, open, and flexible economy system. The paper discusses the above findings and their policy implications. It is also designed to promote research on ETS and to diversify research perspectives of income inequality from both theoretical and practical aspects. Evidence from China's pilot experience with ETS shows that it contributes significantly to balancing income distribution and alleviating the increasingly acute social conflicts caused by income inequality. This provides new theoretical and decision support for the promotion of ETS in the future. The energy revolution driven by ETS promotes income redistribution, which is conducive to income equality. Governments should enforce the constraints of ETS on power generation companies; guide capital to invest more in the non-thermal power industry, especially the renewable energy power sectors; and guide and regulate the income distribution in new power sectors. Governments' revenue from ETS can and should be used to further redistribution of income and to reduce income inequality. A higher number of free quotas and a lower carbon price could be imposed on low-profit or labor-intensive industries to reduce their emission costs. [ABSTRACT FROM AUTHOR]

Comprehensively understanding how the policy influences the sustainability transition of the automotive industry is a critical focus in recent years. This paper focuses on the dual-credit policy, an underexplored but critical policy in China, and examines how it would influence the transition of automotive industry. To achieve this goal, an SD model is developed to simulate the effect of policy parameters on the policy objectives by considering the interaction of production, technology and market. The findings reveal that this policy can in general promote the sustainable development of the automotive industry by greatly decreasing its overall energy consumption. However, its impact on the market share of new energy vehicles is limited. Based on the results, some policy suggestions are proposed so as to improve the effectiveness of the dual-credit policy. [ABSTRACT FROM AUTHOR]

With the increasing penetration of renewable sources, the cogeneration integrated energy system (CIES) is much more efficient and flexible to achieve various types of energy supply for remote loads. Due to uncertainties in both sources and loads, the CIES should be carefully planned and optimised to keep it working at the suitable operation condition. Therefore, this paper proposes a multi-objective capacity allocation optimisation method for the islanded CIES, which is composed of renewable energy generation unit, electric-thermal conversion unit, electric storage, thermal storage and various loads. Firstly, three optimisation objectives are selected as typical indexes, including economic cost, solar energy utilisation, and life cycle carbon emission. An improved radar chart evaluation (RCE) solution is subsequently utilised for calculating a fitness function and building the multi-objective optimisation model. Besides, several compulsory constraints are supplemented to ensure the overall CIES performance satisfy energy supply requirement. As a mature and widely accepted algorithm, a genetic algorithm is chosen as an example to obtain the optimal capacity allocation scheme. Case study of an islanded CIES is provided on the basis of real data from the remote region of northwestern China, which successfully verifies the effectiveness of the proposed optimal capacity allocation method. [ABSTRACT FROM AUTHOR]

In this paper, we forecast the self-sufficiency rate of China's total energy and energy compositions by two-hybrid gray models: the improved non-homogeneous gray model and nash non-linear gray multivariable model, and provide some significant data for energy policy. At first, we propose newly the improved one variable gray model (INHGM-Markov) which combines the non-homogeneous gray model (NHGM(1,1)) with Markov chain model and forecast the production and consumption amount of China's total energy. The results show that the production and consumption amount increase slowly after 2012 and the values are 3660.10 and 4584.04 million tons of SCE in 2022. Next, the production and consumption percents of the energy compositions are simulated with the improved nash nonlinear gray multivariable model (INNGM(1, N)). In 2022, the production percents estimated to be 51.56, 7.55, 8.54, and 32.35%, respectively, for coal, crude oil, natural gas and others energy as the energy compositions, while the consumption percents 47.01, 21.82, 8.72, and 22,45%. The production and consumption amount of coal energy have a maximum values around 2013 and 2014, and then decrease until 1887.19 and 2154.88 million tons of SCE in 2022. Finally, the forecasting values of the self-sufficiency rates of the total energy and the energy compositions are determined to be 0.79, 0.88, 0.27, 0.78, and 1.15, which means that China government should focus on securing energy resource, especially crude oil and natural gas energy, for the sustainable development of the economy. [ABSTRACT FROM AUTHOR]

This paper develops a dual sectors dynamic equilibrium model and introduces agricultural energy consumption and agricultural water consumption in a growth model that tested by using a panel data set from 2004 to 2016 in China. It presents a theoretical prediction on the interactions between agricultural energy consumption, agricultural water consumption, and food yield. Consistent with this prediction, agricultural electricity consumption and agricultural water consumption by themselves appear to have significant effects on food yield. The fixed-effects models verify that agricultural electricity consumption, agricultural water consumption, and food yield have long-run equilibrium relationships. The results of weather-based robustness checks reveal that food yield is positively correlated with agricultural electricity consumption. Also consistent with theory, agricultural water consumption is positively associated with food yield. These results are generally stable and hold with tests of panel data unit roots, with alternative estimation strategies, and with or without controlling for covariates. [ABSTRACT FROM AUTHOR]

Energy efficiency policies can help to reduce energy use and mitigate the effects of climate change. This paper examines the U.S. and Chinese economies by applying HEM to both. Key sectors absorbing more energy from other sectors by purchasing intermediate products from them and, simultaneously, transferring more energy by selling products to the rest of the sectors are identified. This provides insights for decision-making on appropriate energy efficiency policies. It appears that the U.S. economy should focus on the service sector, and the Chinese should focus on the industrial sector. [ABSTRACT FROM AUTHOR]

Improving energy efficiency has been regarded as an important measure to reduce energy consumption, yet the rebound effect has greatly shrunken the energy saving consequences of this measure. To investigate regional rebound effect in China, a multi-region computed general equilibrium (CGE) model is established in this paper. The results show that there are obvious regional differences in the rebound effect in China. The primary energy rebound effects are positive, whereas the production-side power rebounds are below zero in most regions. We also simulated the energy subsidy reform scenarios, which indicates that reducing or even eliminating coal and oil subsidies will increase the production-side rebounds. Finally, feasible policy recommendations are put forward based on the results. [ABSTRACT FROM AUTHOR]

With the development of China's economy, more and more energy consumption has led to serious environmental problems. Faced with the enormous pressure of large amounts of carbon dioxide ( C O 2 ) emissions, China is now actively implementing the development strategy of low-carbon and emission reduction. Through the analysis of the influencing factors of C O 2 emissions in China, five key influencing factors are selected: urbanization level, gross domestic product (GDP) of secondary industry, thermal power generation, real GDP per capital and energy consumption per unit of GDP. This paper applies the Elman neural network optimized by the Firefly Algorithm (FA) to forecast the C O 2 emissions in China. And the results show that the performance of the FA–Elman is better than the Elman neural network and Back Propagation Neural Network (BPNN), verifying the effectiveness of the FA–Elman model for the C O 2 emissions prediction. Finally, we make some suggestions for low-carbon and emission reduction in China by analysing key influencing factors and forecasting C O 2 emissions using the FA–Elman model from 2017 to 2020. [ABSTRACT FROM AUTHOR]

In recent years, most rural areas in China have faced the prominent livelihood transformation of smallholder farmers. It may directly or indirectly affect the regional environment. Thus, this paper constructed a conceptual framework and chose the first Globally Important Agricultural Heritage Systems (GIAHS) site in the Qinghai-Tibet Plateau as the case for evaluating the impact of smallholder farmers' livelihood transformation on the agricultural system. From 2016 to 2019, the main direction of livelihood transformation of smallholder farmers in the case area is the non-agricultural livelihood transformation. And the average proportion of agricultural income in households has continued to decline. With the non-agricultural livelihood transformation, smallholder farmers' land use and energy use behaviour has changed. As a result, the elements in farmland and the relationship between farmland, woodland, and grassland have shown weakening trends in the structure of the case agricultural system. In addition, the ecological and sociocultural functions of the case agricultural system have declined. Still, the productive function has remained almost at a stable level and has even increased slightly. [ABSTRACT FROM AUTHOR]

Rapid growth of passenger vehicles considerably increases greenhouse gas emission and fuel consumption in China. This paper thereby intends to analyze the potentials of the mitigation of energy use and environmental emission in China’s road passenger transportation sector by assessing two available approaches, i.e. biofuel and hybrid vehicle strategies. It was found that biofuel is effective for emission reduction in only three subsubsectors. A synthesis strategy is thereby proposed to meet the state policy goals. [ABSTRACT FROM AUTHOR]

This paper documents cycles in corporate research and development corresponding with the timing of political turnover. Utilising the data on local government officials and research and development activities at the firm level in China, firms' intensity of research and development input is found to be negatively associated with a turnover in local political leaders. We investigate several potential explanations and find evidence supporting that political turnover reduces the incentives of firms to invest in research and development until the uncertainty is resolved. [ABSTRACT FROM AUTHOR]

In recent years, improving semi-urbanization has emerged as a promising approach for reducing pollutant emissions. However, the environmental impacts of semi-urbanization are under-researched in the extant literature. To this end, this paper explores how semi-urbanization affects the collective reduction of carbon and pollutant emissions. Also, to account for potential spatial spillover effects, the internal impact mechanisms through which semi-urbanization affects carbon and pollutant emissions are discussed theoretically. The main results indicate that: (1) Semi-urbanization contributes to reducing carbon and pollutant emissions of the province along with its nearby areas. Specifically, every 1% rise in semi-urbanization of the province leads to a decrease in C O 2 emissions by around 0.93% and by around 7.04% of nearby areas; every 1% rise in semi-urbanization of the province decrease SW emissions by about 1.88% and by about 7.71% of nearby areas. (2) The relationship of semi-urbanization with carbon and pollutant emissions shows a significant U-shaped pattern. (3) Semi-urbanization, energy consumption, human capital, industrial structure, and energy efficiency exert significant and varying spatial effects on carbon and pollutant emissions across regions. This investigation suggests important policy recommendations. [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]

Based on the super-SBM model, this paper studies the agricultural energy efficiency of five provinces in China from 2004 to 2015. In addition, the Malmquist index is used for dynamic analysis of agricultural energy efficiency and to identify drivers of these changes. The results show that: (1) The inland provinces have lower agricultural energy efficiency than the wealthy eastern coastal provinces; (2) Technological progress is the most important factor affecting efficiency changes, and the provinces with lower efficiency are more likely to achieve greater improvements; (3) The energy efficiency of the provinces that are agricultural intensive areas is relatively low. Therefore, adjusting the agricultural production structure and emphasizing diversified agriculture will help improve the energy efficiency of agriculture. At the same time, it is necessary to strengthen agricultural cooperation among different provinces to jointly improve agricultural energy efficiency. [ABSTRACT FROM AUTHOR]

Current housing unit design focuses on performance optimization, such as building energy use, daylighting, and occupant comfort. There is significant potential for efficient optimization in the early design stage. This paper proposed a building energy demand optimization framework that considers building design variables for housing unit design in Beijing. First, a high-rise apartment building was designed using geometric and thermal envelope parameters. Second, a thermal load simulation of the housing unit was performed. Third, sensitivity analysis and multi-objective optimization were conducted to evaluate the building's performance. Finally, a neural network was trained to predict the thermal load. A comparison of the base case and optimal cases revealed that more than 20% of energy demand could be saved. In addition, the effect of the parameters on the thermal load and the lighting schedules on the unit's energy load were analyzed. [ABSTRACT FROM AUTHOR]

The development of regional industry in China has become one of the significant factors affecting energy efficiency. This paper combined the industry agglomeration theory and the improved Stochastic Impacts model to explore the impact mechanism of producer service industry agglomeration on energy efficiency. We applied spatial econometric model to estimate the spatial effects of the agglomeration on energy efficiency with panel data of 31 provinces from 2008 to 2017 in China. The results showed that China's inter-provincial energy efficiency has a significant spatial spillover effect. Simultaneously, the specialized agglomeration and diversified agglomeration of producer services have a "U"-shaped effect on energy efficiency. Finally, we need to pay attention to the coordination and synchronization of the specialized agglomeration and diversified agglomeration of the producer service industry. An increase in the relative gap between the two can inhibit energy efficiency, but its inhibitory effect gradually weakened. [ABSTRACT FROM AUTHOR]

Most previous studies have studied the relationship among urbanization, energy use, and CO2 emissions. In this paper, Ordinary Least Square (OLS), Fixed Effects (FE), Prais-Winsten (PW), and First Differenced (FD) regression model approaches are applied to analyze the correlation among urbanization, energy use, and CO2 emissions in the interior provinces and eastern/coastal provinces of China. The results show that the impact of urbanization on CO2 emissions is not homogenous for all provinces. The eastern/coastal provinces have a different elasticity with respect to per capita Gross Domestic Product (GDP) and urbanization than the interior provinces. Also, it’s possible an Environmental Kuznets Curve (EKC) exists for the eastern provinces but not for China as a whole. [ABSTRACT FROM AUTHOR]

This paper reexamines the relationship between energy consumption and output growth in China over the period from 1969 to 2013, using an asymmetric Granger causality test proposed by Hatemi-J (2012). This article uses oil and coal as the major energy consumption variables because both coal consumption increased by more 2.3 billion over the past 10 years and oil consumption grew by 4.3% at the end of 2016. Empirical results indicate asymmetric Granger causal relationship did exist between energy consumption (for both oil and coal consumption) and output growth in China. The empirical results have important policy implications for the conduct of energy policy in China. [ABSTRACT FROM PUBLISHER]

China has relied on energy to stimulate its booming economy. As a result, its share of world energy consumption rose to 17.3% in 2009 from 7.9% in 1978. Somewhat surprisingly, through 2000 its rate of energy consumption was about half its rate of economic growth. This trend changed after 2001 as energy consumption rose about 1.3 times more rapidly than did gross domestic product through 2005. Through heavy governmental influence, energy intensity subsequently reduced through 2007, but just marginally. This paper uses the structural decomposition approach to understand key drivers behind changes in China's energy intensity and its energy consumption from 1987 to 2007. In our model, energy intensity change was decomposed into five factors: changes in energy efficiency, changes in share of value added, changes in input structure, changes in consumption structure, and changes in consumption volume. This paper provides insights into how changes in China's economic structure, technology, urbanization, and lifestyle affect energy intensity and energy consumption. [ABSTRACT FROM AUTHOR]

To explore which factors affect changes in carbon dioxide (CO2) emissions in China, based on production decomposition analysis (PDA), and data envelope analysis (DEA), this paper decomposes these changes into nine indicators. Then we measure the effects of these factors and analyze the effects at three levels: the nation, the main regions, and individual provinces. The results are as follows. First, since 2012 aggregate CO2 emissions in China have decreased, indicating the success of government efforts. Second, the effects of various factors on CO2 emissions in the eastern, central, and western regions differ significantly, emissions in the western region are high, and the eastern and central regions have the potential reduce their emissions. Third, the dominant contributors to CO2 emissions are economic growth, the structure of energy consumption, carbon emissions technology, and energy consumption efficiency, whereas the other factors are conducive to reductions in CO2 emissions. Based on our research results, we make some policy recommendations on reducing CO2 emissions in China to promote the coordinated and sustainable development of the economy and the environment. [ABSTRACT FROM AUTHOR]

China’s energy consumption structure, which relies heavily on fossil fuels, has, on the one hand, weakened environmental sustainability at the national level, and also intensified the problem of climate change at the global level, on the other hand. It is therefore essential for policy-makers to adopt immediate measures to transfer to a trajectory of sustainable energy development with low carbon emissions. Using a decoupling index that describes the difference between energy consumption and economic development, this paper studied the process of decoupling in each province in China. Results showed that there was a phenomenon of weak decoupling in China as a whole, while North, Northeast, and East China have experienced rapid economic development and improved energy utilization efficiency, leading to a high level of decoupling. Neimenggu (Inner Mongolia) Province experienced both the highest energy consumption and economic growth, while Beijing and Guizhou Province showed the strongest decoupling. [ABSTRACT FROM AUTHOR]

This paper has established the computable general equilibrium (CGE) model to analyze the effect of carbon tax policy on energy consumption and CO2emission in China. The analysis shows that with the increase of CO2mitigation, the level of carbon tax will gradually increase; meanwhile the ad valorem tax rates of coal, petroleum, and natural gas go up as well, and the coal tax rate is the highest among them. In addition, with the increase of CO2emission reductions, the demand for coal, petroleum, natural gas, and thermal power will totally decrease. The demand for coal will drop significantly. The main factor responsible for China’s CO2mitigation is coal. Moreover, the sectors of coal, heavy industries, thermal power, light industries, natural gas, and transportation contribute more to CO2emission reductions, while the other sectors contribute less. [ABSTRACT FROM PUBLISHER]

This paper attempts to apply Reistad's approach to analyze exergy utilization in Chinese transportation sector that includes five sub-sectors: highways, railways, waterways, airways, and pipeline transport. Unlike previous studies based on historical data, this paper uses the actual data for 2006 and projected data for 2030 under five scenarios to analyze exergy consumption. We find that (1) in 2030, the total exergy consumption will be 17,883-26,698 PJ, which may increase 2.26-3.78 times compared with that in 2006. (2) The effect of advanced technology is much greater than that of the choice of transport mode. (3) Highways will always be the dominant transport mode. In 2030, the percentage of exergy of oil fuels in total exergy consumption of the whole sector will account for more than 97%. (4) The weighted mean energy and exergy efficiencies will show a deteriorating trend over years, i.e., a decreasing tendency with time, except for Scenario 2. [ABSTRACT FROM AUTHOR]

By coupling algorithmic optimization with parametric modeling and performance simulation, the building design process becomes a series of informed decision-making. Algorithmic optimization helps architects find high-performance design choices which balance complicated tradeoffs among various performance objectives. Although algorithmic-optimization aided design is more competent than the traditional manual method, due to complexities in building design, optimization frameworks are not easy to formulate. Focusing on the correlation between energy efficiency, visual comfort, and construction material cost, the current author formulates a bi-phase optimization framework to search for facade fenestration geometries. Afterwards, this optimization framework is applied to one representative office building in China. Optimal design choices are found to have much lower thermal loads and construction cast, but higher visual comfort. This paper highlights how the optimization framework regarding facade fenestration is formulated and how it performs during the building design process. [ABSTRACT FROM AUTHOR]

As a consequence of the powerful changes that have occurred over the last three decades in the principal 'drivers' of economic change, there have been significant realignments in the global patterns of production and consumption of natural resources, as well as in the intensity of their use, in the quest to raise the level of material wellbeing throughout the world. In this paper, three large energy-consuming (and/or -producing) countries are examined - the USA, China and Russia - and the story of a generation's economic progress (or decline, as the case may be) is seen through the lens of energy consumption - the 'stuff' that fuels a modern 'standard of living'. After presenting data on gross domestic product, population, the observed levels and annual growth rates of consumption and production of three fuel minerals over a 35-year interval ending in 2005 for these countries and for the world, the paper includes a description of these countries' growing import dependence (or, as the case may be, their enhanced or reduced role as an exporter to the world economy) for some, or all, of these critical resources over this time period. These changing trends contribute to one of today's 'front-burner' public policy issues: energy-supply security. The last section of the paper examines the changing 'intensity-of-use' of oil and total energy. The paper concludes with some remarks on the geopolitical/environmental dilemma associated with these energy resources, which is intensifying as we approach the beginning of the second decade of the twenty-first century. [ABSTRACT FROM AUTHOR]

Limited by the climate, economic level and energy-saving awareness of rural residents in the western China, rural houses are still in a stage of high energy consumption (EC) and low comfort. The passive design strategies should be given priority to provide an optimal design mode. The challenge is to find the best combination of design parameters. In this paper, rural single-storey detached houses are taken as the research objects. Three conflicted indicators are set as the objective function, namely building EC, thermal comfort and economy. The investigated design variables include building orientation, insulating layer thickness, window width & type, and indoor design temperature. A methodology of combining EnergyPlus and MOBO is used for multi-objective optimization, thus getting the Pareto solutions and using the weighted sum method to obtain the optimum parameter combinations. The proposed methodology for simulation-based multi-objective optimization is a useful tool to facilitate decision-making in building design. [ABSTRACT FROM AUTHOR]

This paper explores the design approach of multi-atrium configurations to improve the energy efficiency of shopping malls in cold climates. A typical building prototype in northern China was considered, and an artificial neural network (ANN)-based metamodel was developed with four design variables: the atrium area ratio (r), atrium number (n), distance between adjacent atriums (d0), and distance between atrium and façade wall (d1). The proposed metamodel was used for sensitivity analysis (SA) and building design optimization (BDO) to understand the performance of multi-atrium configuration. The SA indicates that the contribution of the design variables to the building energy efficiency follows the order r > d0 > n > d1, and there are interactions between variables r and n. The BDO demonstrates that it is beneficial for energy efficiency to incorporate more atrium areas, appropriate atrium sizes, larger distances between adjacent atriums, and more west-facing atriums. [ABSTRACT FROM AUTHOR]

Nowadays, as China has become the factory of the world, China's industrial sectors have become the country's main source of energy consumption and emissions including CO2, SO2, NOx and soot. This article will use the non-radial directional dispersion function model (DDF) to explore ways to improve both the energy efficiency and the emission efficiency of China's industrial sectors. Based on current research, this article proposes a new projected input for the treatment of industrial waste gas, and optimizes the projected input and output settings. The data analysis shows that there is room for improvement in China's energy efficiency, and its regional imbalances have expanded. The Chinese government is urged to pay more attention to the improvement of energy efficiency in the central and western regions, and to provide more policy support. Simultaneously, the paper attemtps to establish measurement indexes to improve the efficiency of emission reduction. As a result, the authors suggest that increasing government expenditure can play a positive role in the overall improvement of emission reduction efficiency. [ABSTRACT FROM AUTHOR]

A reduction in the CO2 emission intensity (ton per gross domestic product) from a base year to a target year with different rates of reduction in each individual year can yield different cumulative CO2 emissions over time, which could have different effects on the climate. In this paper, an indicator is proposed to measure the extent to which the cumulative CO2 emissions are generated by a specific reduction trajectory of CO2 emission intensity, especially for emerging economies with a relatively higher economic growth rate. The proposed indicator is important for less-developed countries and regions in which economic growth is heavily reliant on energy and in which significant potential exists for improvement of energy efficiency. The indicator is applied to evaluate the CO2 emission reduction performance in China's 12th Five-Year Plan period, and the result is not encouraging, especially when the likely gap between the energy conservation goals and temperature goals is further examined. Mitigation goals should be set by considering not only the performance in the final year, but also the reduction in cumulative emissions over the evaluation period. [ABSTRACT FROM AUTHOR]

The paper introduced the concept of a multilevel microgrid (MG), which starts at the building level and creates an MG at this level. The development process of MG in China was described in detail for the first time, including the key issues and the research direction. The prediction error and uncertainty analysis of wind power, photovoltaic power generation, load, and controllable generator components are given, respectively. The uncertainty distribution model is helpful to construct the objective function of minimizing the operating cost of MG. First, an hypothetical apartment building's suitability for installation of solar panels, wind turbines, and solar thermal devices in Shanghai was analyzed, including the principles and characteristics of their electrical generation and energy collection. Compared to the analysis of a single building, the results are more comprehensive for simulating the loading of different buildings in a variety of situations. The mathematical model of peak load shaving in an MG was constructed, and the interior-point method was used to solve it. By simulation analysis, the variation of load curve and related parameters before and after peak load shaving was obtained. First, the average loading of an office building with and without the MG was compared, and the reduction rate in peak loading of a building was used to analyze whether there was additional storage and found the change rule. A neighborhood with the additional MG technologies and additional storage units is better than other existing literature in showing the effectiveness of peak- load reduction. [ABSTRACT FROM AUTHOR]

The paper examines the long-run relationship among per capita income, energy consumption, and carbon emissions in China during 1953–2008. We employ the Toda—Yamamoto procedure to test the Granger causality in a vector autoregressive (VAR) model with levels. We find strong evidence of bilateral Granger causality running between income and energy consumption and unilateral Granger causality running from carbon emissions to income. We further provide policy suggestions to address the energy and sustainable development dilemma in China. These include diversifying the energy mix and exploiting renewable energy, enhancing energy efficiency, transforming the economic growth pattern, and reducing the reliance on resource- and energy-intensive industries. [ABSTRACT FROM PUBLISHER]

This paper revisits the relationship between energy consumption and economic growth in the case of China using an autoregressive distributed lag (ARDL) bounds testing procedure for the period from 1952 to 2008. The results suggest that energy is one of the engines of growth in China, along with labor, capital, and international trade. In particular, a 1 percent increase in energy consumption leads to a 0.17 percent increase in gross domestic product. In addition to energy consumption, results also suggest that labor, capital, and international trade are also important factors stimulating China’s economic growth. [ABSTRACT FROM PUBLISHER]

Urban energy consumption is one of the most important causes of air pollution. Air pollution-oriented ecological risk assessment is of great significance to the promotion of urban environmental protection. This paper focuses on ecological risk in Xiamen city caused by air pollutant discharge from urban energy consumption. The Long-range Energy Alternatives Planning model was used to establish two scenarios of energy consumption in Xiamen city, and based on different scenarios, we estimated urban energy consumption and discharge quantity of air pollutant (DQAP). A box model and an expert scoring method were used to calculate the air pollution burden (APB) of SO2, NO2, CO, PM10 and PM2.5 and to obtain the probabilities of different air pollution loads. An ecological risk assessment model was developed and utilized to predict Xiamen city’s ecological risks in 2020. The results showed that under an energy-saving scenario, the ecological risks for PM2.5, SO2 and NO2 are high, whereas the ecological risks for CO and PM10 are low. Under a baseline scenario, the ecological risks for PM2.5, SO2 and NO2 are moderate, whereas the ecological risks for CO and PM10 are low. In addition, the APB of SO2, NO2, CO, and PM2.5, but not of PM10, is predicted to rise. In the simulation, energy generation from coal is the main source of air pollution. Although the DQAP from automobiles is not high, it is predicted to rise year-on-year. In summary, the ecological risk due to pollution in Xiamen city is high, and the main pollutants are SO2, NO2 and PM2.5. [ABSTRACT FROM AUTHOR]

The energy needs of most urban populations are serviced with centralised, fossil fuel based generation and transmission infrastructure. However, with the advent of affordable solar and storage technology, this will likely move towards an increasingly hybridised and decentralised model. While many households presently benefit from stand-alone solar photovoltaic systems, in higher density areas this technology is difficult to provide due to the way multi-dwelling buildings are governed. This paper examines a case study for a multi-dwelling, residential building called Gen Y within a bigger innovative development called WGV, in which a planning and governance structure has been developed to provide both financial incentive for the installation of renewable energy in multi-dwelling buildings, as well as to demonstrate how planning can best optimise the behind-the-meter installation and management of solar and battery technology. It suggests the building management company can become a precinct-scale utility. [ABSTRACT FROM AUTHOR]

The objective of this paper is to provide a more detailed picture of potential biomass energy production in the Chinese energy system towards 2030 and 2050. Biomass for bioenergy feedstocks comes from five sources, which are agricultural crop residues, forest residues and industrial wood waste, energy crops and woody crops, animal manure, and municipal solid waste. The potential biomass production is predicted based on the resource availability. In the process of identifying biomass resources production, assumptions are made regarding arable land, marginal land, crops yields, forest growth rate, and meat consumption and waste production. Four scenarios were designed to describe the potential biomass energy production to elaborate the role of biomass energy in the Chinese energy system in 2030. The assessment shows that under certain restrictions on land availability, the maximum potential biomass energy productions are estimated to be 18,833 and 24,901 PJ in 2030 and 2050. [ABSTRACT FROM AUTHOR]

Smart Grid presages an advanced power grid that revolutionizes the century-old traditional power grid and the way mankind uses energy. In China, the pressure on the current grid exerted by growing demand, environmental issues and the unbalanced energy use structure makes the transition to a ‘smarter’ and ‘cleaner’ grid inevitable. This paper firstly contrasts the concepts and research priorities of Smart Grid of China and other developed countries; then turns to the situation of Chinese energy and power use. China has the largest generating capacity, 79% of which is coal-fired plants. And China is also the largest carbon emitter in the world. Despite the challenges, China is also the most promising market for Smart Grid. The components of Smart Grid, especially the development of renewable energy, electric vehicles and smart substation are reinforced in the Chinese 12th Five-Year Plan (2011–2015). The paper examines also efforts by government, power utilities and research institutes. The paper concludes that developing Smart Grid will be beneficial both to China and the world. [ABSTRACT FROM PUBLISHER]

This paper is a preliminary attempt to illustrate how the shipbuilding industry in China would be influenced by the implementation of International Maritime Organization's Energy Efficiency Design Index (EEDI), a measure on the amount of CO2emitted by a ship for one unit of cargo carried. It is supposed to promote more energy-efficient ship designs and gradually reduce the emissions from the world fleet, as CO2emissions from shipping account for a larger proportion of all global emissions of the greenhouse gas (GHG). However, the implementation of EEDI is not easy given the number of stakeholders involved, the split incentives and the lack of technical knowhow in some of the major shipbuilding countries such as China. This paper identifies the characteristics of energy consumption in shipping and the stakeholders involved in the EEDI application process, analyses the relationships among stakeholders in the shipbuilding industry in China, and points out the drivers and barriers in the implementation. It also discusses the impacts of EEDI on Chinese shipbuilding industry, and explores future scenarios including the possible income and China's position in the global shipbuilding industry using the two cases of typical Chinese shipbuilding firms. Some policy recommendations are provided to the shipbuilders and the governments, to promote the objective of the GHG reduction as well as the development of Chinese shipbuilding industry. Finally, it concludes that EEDI has profound impacts on not only China but also all shipbuilding countries around the world, and it may even trigger another migration of shipbuilding industry in the future. [ABSTRACT FROM AUTHOR]