Search

Effective forecasting of energy consumption structure is vital for China to reach its "dual carbon" objective. However, little attention has been paid to existing studies on the holistic nature and internal properties of energy consumption structure. Therefore, this paper incorporates the theory of compositional data into the study of energy consumption structure, which not only takes into account the specificity of the internal features of the structure, but also digs deeper into the relative information. Meanwhile, based on the minimization theory of squares of the Aitchison distance in the compositional data, a combined model based on the three single models, namely the metabolism grey model (MGM), back-propagation neural network (BPNN) model, and autoregressive integrated moving average (ARIMA) model, is structured in this paper. The forecast results of the energy consumption structure in 2023–2040 indicate that the future energy consumption structure of China will evolve towards a more diversified pattern, but the proportion of natural gas and non-fossil energy has yet to meet the policy goals set by the government. This paper not only suggests that compositional data from joint prediction models have a high applicability value in the energy sector, but also has some theoretical significance for adapting and improving the energy consumption structure in China. [ABSTRACT FROM AUTHOR]

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]

Expanding the supplies of new energy can not only reduce CO2 emissions, but also alleviate energy shortage. This paper applies the quantile regression to investigate the new energy industry in China. The results show that economic growth exerts the greatest effect on the new energy industry in the lower 10th quantile province. This is because these provinces have the developed economies, demand for a higher ecological environment and new energy resources. Foreign energy dependence has a minimal impact on the new energy industry in the 25th-50th quantile province, due to their minimal oil importation. The contribution of technological progress to the upper 90th quantile province is the lowest, because their R&D capabilities are the weakest. The impact of energy consumption structure decreases in steps from the lower 10th quantile provinces to the upper 90th quantile provinces. The agricultural sector promotes the new energy industry in most provinces. [ABSTRACT FROM AUTHOR]

As an essential energy and chemical base in China, carbon reduction in the Energy "Golden Triangle" (EGT) area is significant. This paper used the logarithmic mean Divisia index (LMDI) method to analyze the drivers of carbon emissions from secondary industry energy consumption (CESEC) in EGT from 2005 to 2019 and then used the GM (1,1) method to simulate carbon emissions in 2030. Meanwhile, the decoupling relationship between carbon emissions and economic development was also analyzed using the two-dimensional decoupling model to test the effectiveness of carbon reduction by the region's government. This paper showed the following: (1) CESEC in the EGT area increased from 1.89×108t to 2.617×108 t; (2) the economic output effect is the main factor influencing carbon emissions in the EGT area, followed by population effect and energy structure effect, while energy intensity effect mitigates carbon emissions; and (3) CESEC will peak at 12.362×108t in 2030, leaving an arduous task on carbon reduction. The two-dimensional decoupling condition between carbon emissions and economic growth in the EGT area is low level-weak decoupling (WD-LE) for 2005–2019. The decoupling condition in Yulin and Ningdong is concentrated in low level-expansion connection (EC-LE) and low level-weak decoupling (WD-LE). Furthermore, Erdos reached high level-expansion negative decoupling (END-HE) condition during 2015–2019. Based on the above findings, a low-carbon development strategy for EGT should consider improving emission reduction technologies for high-carbon energy sources like coal, adjusting the energy consumption structure and seeking government policy support for carbon reduction. [ABSTRACT FROM AUTHOR]

In the context of the joint operation of China's intra-provincial markets and inter-provincial trading, how to meet the load demand and energy consumption using inter-provincial renewable energy trading is a key problem. The combined operation of intra-provincial and inter-provincial markets provides a new way for provincial power companies to optimize and clear the intra-provincial power market, complete the intra-provincial consumption responsibility weight index, and consume renewable energy across provinces and regions. This paper combines power generation and consumption within the province, uses inter-provincial renewable energy trading to meet the load demand within the province and completes the index of intra-provincial consumption responsibility weights. The intra-provincial market trading and inter-provincial market clearing are respectively taken as the upper and lower levels of the model. Under the two-level electricity market operation framework, the upper-level model aims to minimize the expected total operating cost within the province considering the carbon emission cost and the weight of the consumption responsibility, while the lower-level model aims to minimize the inter-provincial renewable energy purchasing cost. Finally, the influence of inter-provincial transaction mechanism, risk aversion coefficient, voucher price, and responsibility weight on operating cost is analyzed. Simulation is used to verify that the proposed model can meet the requirements of the provincial load power consumption and the consumption responsibility weight index, and promote the consumption of renewable energy. [ABSTRACT FROM AUTHOR]

This study used a double machine learning model (based on the random forest algorithm) and spatial Durbin DIDs model to conduct quasi-natural experiments. The results are as follows: (1) innovation and reform policy regarding regional industrial chains as well as their resilience can significantly and positively address the development of China's impossible triangle coupling of energy; (2) implementing the innovation and reform policy for regional industrial chains in other regions can have a significant positive spatial transmission effect on the impossible triangle coupling coordinated development of energy in the region; (3) regional industrial chain resilience can produce a significant positive mediating effect between the innovation and reform policy of regional industrial chains and the safety, reliability, and economic feasibility of green and clean energy systems; (4) under the counterfactual framework, the mechanism path "innovation and reform policy of the regional industry chain→regional industry chain resilience→coordination degree of impossible triangle coupling of energy" has significantly positive direct and indirect effects in both the treatment group and the control group. However, "innovation and reform policy of the regional industrial chain→regional industrial chain resilience→the energy sector's impossible triangle coupling coordination degree" and "innovation and reform policy of the regional industrial chain→leading power of the regional industrial chain→the energy sector's impossible triangle coupling coordination degree" have significantly positive direct and indirect effects in the treatment group, but only the direct effect is significant in the control group. [ABSTRACT FROM AUTHOR]

Purpose: As a typical resource energy-intensive industry, the scale of construction industry has been expanding rapidly owing to the large-scale urbanization and the economic booming in China, which results in a sharp increase in the energy consumption of construction industry. However, it is infeasible to mitigate the energy consumption by reducing the production activities of construction industry. Therefore, improving the energy efficiency of construction industry is essential for energy saving. Construction industry has close relationships with other industries. The production activities have not only consumed a great deal of energy but they have also generated a massive energy consumption from other industries. Previous literature studied the efficiency of energy consumed directly by the construction industry. However, no research has been found focusing on the efficiency of energy consumed directly by the construction industry and indirectly by the related industries. The purpose of this paper is to put forward a total energy efficiency evaluation framework to measure the energy efficiency of construction industry in depth. Design/methodology/approach: This paper employs the data envelopment analysis (DEA) method and the framework of embodied energy efficiency (EEE) to establish a total energy efficiency evaluation model. Next, the comprehensive analysis of direct energy efficiency (DEE) and EEE in different provinces with various levels of urbanization and various economic levels is conducted. Findings: The results show that the embodied energy intensity and its regularities differ greatly between provinces. From the comparison of DEE and EEE, the provinces of Zhejiang and Jiangsu remain DEA-effective and Hainan is the only province in which the EEE is higher than DEE in 2002, 2007 and 2012. Besides, the DEE and EEE in the provinces with higher levels of urbanization and high economic levels are not more effective than those in the provinces with relatively lower levels of urbanization and low economic levels. Originality/value: Previous literature studied the efficiency of energy consumed directly by the construction industry while ignoring the energy consumed indirectly by the related industries. Besides, no research has been found focusing on the regulation of energy efficiency in different provinces with different levels of urbanization and different economic levels. It can be concluded that the increasing levels of urbanization and higher economic levels have not brought development and benefits for improving DEE and EEE. Therefore, under the condition that the self-regulation of construction industry and market fail to facilitate the improvement of DEE and EEE in China, policymakers should develop policies and market incentive mechanism to encourage construction industry for employing new technologies to improve the energy efficiency. Since the EEE can reveal the energy efficiency in depth, the evaluation method of EEE should be paid more attention. Besides the fact that the EEE is lower than the DEE in almost all provinces, except Hainan province, the industrial structure is essential to develop the EEE. Hence, improving the energy structure, increasing the energy efficiency and developing new and renewable energy are the basic energy strategies in China. [ABSTRACT FROM AUTHOR]

In light of the integration of digitalization and the energy revolution, digitalization can be integrated into the energy industry to develop energy-saving technologies and improve resource allocation efficiency. On the basis of 2013–2019 Chinese provincial panel data, this paper measures the level of green energy efficiency based on the super-EBM-DEA model and analyzes the linear relationship, nonlinear relationship, and potential mechanism between digitalization and green energy efficiency. The findings indicate that (1) overall, both China's digitalization and green energy efficiency formed a steady upward trajectory during the sample period. Digitalization showed a spatial characteristic of extending and spreading from the eastern region to the central and western regions. Green energy efficiency was characterized by obvious regional heterogeneity. (2) Progress in digitalization has a significant driving effect on green energy efficiency. Subdimensional analysis shows that this driving effect mainly comes from digital development and digital transactions. (3) The impact of digitalization on green energy efficiency presents a threshold effect of economic agglomeration (with a threshold of 0.0257 and a marginally increasing, positive driving trend) and population agglomeration (with a threshold of 4.2750 and a marginally decreasing, positive driving trend). (4) Decomposing changes in green energy efficiency into scale efficiency and pure technical efficiency, this study shows that pure technical efficiency gains due to digitalization are the main driver of green energy efficiency improvements. Finally, some specific policy recommendations are proposed. [ABSTRACT FROM AUTHOR]

The contradiction between increasing energy demand, decreasing water availability, and deteriorating ecological environment indicates the urgent necessity for an energy-water-climate nexus management (EWCM) system. The contribution of this paper is to propose a posterior probability-based multi-stage cooperative game and type-2-fuzzy interval-stochastic programming model of the EWCM (PMCTFSP-EWCM) to determine the optimal solutions for sustainable development under ambiguities and uncertainties. The type-2-fuzzy sets and multi-stage interval-stochastic programming are combined to deal with objective and subjective uncertainties of partial parameters with flexible constraints. Moreover, multi-stage cooperative game was adopted to reflect the cooperation and competition between energy subsystem and water resources subsystem. Then, the model was applied to a case study to investigate the EWCM in the Yellow River Basin (YRB), China. Improving water availability satisfaction and feasibility degree can reduce external energy dependence costs from 84.9 , 126.4 × 10 9 $ to 12.7 , 14.3 × 10 9 $ . Furthermore, when considering the objective function of cost, target revenue functions, and corresponding constraints of the EWCM mutual feedback relationship, the proportion of fossil energy supply in the YRB was reduced to 63.28%-71.79%. These measures could reduce the generation of negative values, which has long-term significance for the healthy and sustainable development of EWCM. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Railway Science & Engineering is the property of Journal of Railway Science & Engineering Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Despite market-oriented reforms, China's energy sector is subject to energy price distortions, which are believed to be a crucial determinants of energy efficiency in China. This paper investigates the impact of energy price distortions on energy efficiency in China from the perspective of spatial correlation. Using the nonradial directional distance function approach, we first estimate the provincial-level energy efficiency in China. Paying attention to spatial correlation among the provinces of China, in stage two, we identify the determinants of energy efficiency. Our empirical results suggest that price distortions have a significant impact on energy efficiency in China. This impact holds when the cross-region effect is considered, i.e., besides its own energy price distortion, a region's energy efficiency is also correlated to the adjacent provinces' energy price distortions. Furthermore, we found that the levels of energy efficiencies in adjacent provinces are highly correlated. This spatial relationship can be decomposed into the 'spillover effect' and 'warning effect'. These two effects work together, determining the spatial relationship among the province-level energy efficiencies. [ABSTRACT FROM AUTHOR]

Renewable energy is regarded as an effective method to alleviate environmental pollution and accelerate the green transition in China. This paper systematically investigates the impact of financial inclusion on renewable energy demand by using S-GMM model based on provincial data in the green finance era. This paper also analyzes the asymmetry, heterogeneity, and mediating mechanism in the nexus between financial inclusion and renewable energy demand, and highlights the following findings: (1) Improved financial inclusion can promote renewable energy development in China and present the characteristics of green finance; (2) the impact of financial inclusion on renewable energy demand is asymmetric and heterogeneous; specifically, this impact is much higher in northern China and the regions with higher renewable energy development; and (3) wind and photovoltaic power generation are effective mediators between financial inclusion and renewable energy industry, while the mediation effects of hydropower and nuclear power are not significant. New evidence in this study is presented for the achievement of green transition in China, as well as practical policy implications for improving financial inclusion and increasing renewable energy consumption. For instance, fiscal and tax incentives and green investment subsidies in the renewable energy sector need to be further improved. • This study explores the impact of financial inclusion (FI) on renewable energy demand (RED) in China. • Asymmetry, heterogeneity, and the mediating mechanism are further discussed. • Increased FI can promote RED , which presents the characteristics of green finance. • The impact of FI on RED is asymmetric and heterogeneous. • Wind and photovoltaic power are effective mediators between FI and RED. [ABSTRACT FROM AUTHOR]

• The informal sector can play a role in sustainable development. • Competition from the informal sector can significantly improve the energy efficiency of formal firms, and this result is robust. • Instrumental variable and property score matching method are used to address possible endogeneity issues. • Innovation has a significant mediating effect. Based on micro-evidence, this paper investigates the role of the informal sector in sustainable development. In particular, this paper examines the impact of competition from the informal sector on the energy intensity of firms based on Chinese manufacturing enterprise data. The results indicate that firms reduce their energy intensity in the face of fiercer competition from the informal sector. Competition from the informal sector has a more obvious effect on reducing energy intensity especially for firms with higher energy intensity. The subsample regression results imply prominent regional and enterprise ownership heterogeneity. The mechanism test indicates that competition from the informal sector reduces firm energy intensity by promoting the product innovation, production cost innovation, R&D (Research and Development) activities of formal firms. However, there is no evidence of a crowding-out effect, that is, competition from the informal sector has not been found to squeeze out firms' output and reduce energy intensity. [ABSTRACT FROM AUTHOR]

During 2013–2017, the new energy industry in China experienced prosperous growth with the financing support of the government. To evaluate the real performance of this industry and the government subsidy effect during this period, this paper measures both the original and adjusted industry efficiencies and investigates the non-linear impact of the government subsidy. Applying a four-stage data envelopment analysis (DEA) method to a sample of listed companies during 2013–2017, we find that: (1) China's new energy industry obtains relatively a high efficiency while showing a noticeable decline after a rising trend; (2) the industry efficiency presents a downward adjustment after eliminating the environmental factors; (3) a single threshold of government subsidy is identified, indicating a shackle after a short-term positive impact; (4) the positive mediating effect of cash flow and R&D investments are identified; and whereas the management self-interest presents a negative mediating effect, (5) the regional and ownership endogeneity of the government subsidy effect are recognized. [ABSTRACT FROM AUTHOR]

The low-carbon transformation of the power industry is of great significance to realize the carbon peak in advance. However, almost a third of China's CO2 emissions came from the power sector in 2019. This paper aimed to identify the key drivers of CO2 emissions in China's power industry with the consideration of spatial autocorrelation. The spatial Durbin model and relative importance analysis were combined based on Chinese provincial data from 2003 to 2019. This combination demonstrated that GDP, the power supply structure and energy intensity are the key drivers of CO2 emissions in China's power industry. The self-supply ratio of electricity and the spatial spillover effect have a slight effect on increasing CO2 emissions. The energy demand structure and CO2 emission intensity of thermal power have a positive effect, although it is the lowest. Second, the positive impact of GDP on CO2 emissions is decreasing, but that of the power supply structure and energy intensity is increasing. Third, the energy demand of the industrial and residential sectors has a greater impact on CO2 emissions than that of construction and transportation. For achieving the CO2 emission peak in advance, governments should give priority to developing renewable power and regional electricity trade rather than upgrading thermal power generation. They should also focus on promoting energy-saving technology, especially tapping the energy-saving potential of the industry and resident sectors. [ABSTRACT FROM AUTHOR]

As a developing country, extensive carbon and sulfur emissions are associated with China’s rapid social and economic development. Chief among them are the emissions from coal and oil consumption. This paper focuses on the demand side, attempting to regulate the range of relative price of oil to coal at the consumption level. Through the adjustment of the relative price, the goal of reducing the emissions of carbon and sulfur could be achieved in the market of energy consumption. Data regression is applied to investigate the functional relationship between emissions and energy prices. The results indicate that when the coal price is less than 300, the higher relative price leads to less carbon and sulfur emissions; when the coal price is more than 300 and less than 500, there exists an optimal relative price which has the least carbon emissions, and this value is not more than 11.5; when the coal price is more than 500, the smaller relative price is beneficial to decline carbon and sulfur emissions. The changed trend of relative price-sulfur emissions is very similar to relative price-carbon emissions. Compared to the present energy situation in China, the relative price of oil to coal still need to be reduced especially when coal price is more than 500. [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]

This manuscript aimed to seek influencing factors of energy consumption in China's energy-intensive industries employing the generalized logarithmic mean Divisia index (LMDI) and input-output analysis. The research stated clearly that decomposition factors covered energy structure, energy intensity, industry structure, complete demand, final demand structure, and final demand total effect. The results showed that the decrease of energy consumption in energy-intensive industries heavily relied on energy intensity and industry structure. However, final demand total effect, which specifically involved the investment demand and export expansion, was a dominant element driving energy consumption growth. Accordingly, speeding up the industrial structure adjustment, improving the import and export mix, and reducing energy intensity have been the primary approaches to decrease energy consumption in energy-intensive industries. These approaches would accelerate the target of a 16% decline in energy intensity compared with 2010 in China's Twelfth Five-Year Plan. Moreover, this research has crucial theoretical and practical significance on the implementation of energy policy in China. [ABSTRACT FROM AUTHOR]

The essence of industrial chain structure optimization is to strengthen the synergy and division ability among sectors. It is a crucial factor in reducing energy intensity and achieving carbon neutrality goals. This paper completed the China's non-competitive input-output table from 2000 to 2020, constructed industrial synergy and division index using structural path analysis method and examined its development trend. Combining with a two-way fixed effects model, we explored the influence of industrial synergy and division on energy intensity. The research found that China's industrial synergy and division development level shows an upward trend. The proportion of the low-layer industrial chain decreases, and the peak contribution rate moves to the high-layer industrial chain. Secondly, industrial synergy and division significantly reduces sectoral energy intensity, the results are robust after endogeneity test. Finally, heterogeneity analysis showed that industrial synergy and division can reduce the energy consumption intensity of all sectors, and it is more obvious for sectors with high energy dependence. This research can provide targeted policy suggestions for China to optimize its industrial structure. It also has a reference significance for other countries. • The impact of industrial synergy and division on energy intensity is explored. • This paper extracts China's non-competitive IO table from the global MRIO table. • SPA is applied to construct industrial synergy and division index. [ABSTRACT FROM AUTHOR]

As a result of China's rapid economic growth, energy demand has increased significantly in recent years. Consequently, energy pricing has become increasingly prominent. This paper defines reasonable energy price ratios and establishes models to analyze them from the aspects of input/output standards, economic standards, and international standards according to the structure of the energy prices. Furthermore, based on the socioeconomic conditions in China, prices of coal, natural gas, and electric power are selected as examples for analyzing the price ratios of regulated and nonregulated energy prices under three evaluation criteria. Finally, reasonable energy price ratios in China are determined through a comprehensive analysis. The paper concludes that these ratios are significant for developing countries undergoing energy market oriented reforms such as China. [ABSTRACT FROM AUTHOR]

In order to explore effective ways for energy conservation and emission reduction, seven correlated variables are selected in this paper according to the government statistics with the extended STIRPAT model, and the impact of China's industrialization and urbanization on carbon emission intensity of energy consumption is studied. The study found that urbanization rate and urban population employment rate are the main factors affecting per capita carbon emission of energy consumption in China;the industrialization has a reverse impact on per capita carbon emission of energy consumption, indicating that China's industrialization is relatively low and is not the main factor affecting per capita carbon emission of energy consumption; the service industry added value rate and the agricultural industry added value rate also have reverse effects on China's per capita carbon emission of energy consumption, and the degree of impact is relatively small. Therefore, China is supposed to develop industry vigorously in the future, to appropriately control the development speed of urbanization and to increase the agricultural industry added value rate moderately, so as to achieve effective control of per capita carbon emission intensity of energy consumption. [ABSTRACT FROM AUTHOR]

Understanding the rapidly rising demand for energy in China is essential to efforts to reduce the country's energy use and environmental damage. In response to rising incomes and changing prices and demographics, household use of various fuels, electricity and gasoline has changed dramatically in China. In this paper, we estimate both income and price elasticities for various energy types using Chinese urban household micro-data collected by National bureau of Statistics, by applying a two-stage budgeting AIDS model. We find that total energy is price and income inelastic for all income groups after accounting for demographic and regional effects. Our estimated electricity price elasticity ranges from -0.49 to -0.57, gas price elasticity ranges from -0.46 to -0.94, and gasoline price elasticity ranges from -0.85 to -0.94. Income elasticity for various energy types range from 0.57 to 0.94. Demand for coal is most price and income elastic among the poor, whereas gasoline demand is elastic for the rich. [ABSTRACT FROM AUTHOR]

To analyze the operational efficiency of Chinese power sector at the provincial level, this paper studies the convergence of technical efficiency and productivity growth of electricity across 29 Chinese provinces during the period 1996-2008 using several convergence models. Depending on the model being employed, we find evidence of convergence of operational efficiency towards either a national steady state or towards their own steady states, with the latter process occurring more rapidly. In essence, our study provides evidence of negative effects of government intervention. Additionally, we use the nonparametric distribution dynamics approach to analyze intra-distributional dynamics of technical efficiency and productivity. We find some support for productivity convergence while technical efficiency does not converge for provinces with relatively low levels. We discuss policy implementations based on our model results and highlight several aspects for policy making in the power sector reforms currently being undertaken. [ABSTRACT FROM AUTHOR]

A good grasp of the relations between rapid economic development of China and stable energy supply is an important means to achieve coordinated development among energy, economy and society. This paper uses cointegration test, Granger causality test and vector error correction model, and other empirical method to analyze the relationship between the total amount of energy consumption and energy trade from 2000 to 2013, reveals that energy has a high degree of dependence on imported trade. The results showed that energy consumption has relatively strong positive impact on the energy business in the short term, then a weak negative effect in the long term. The impact of energy trading on the energy consumption is not significant in the short or long term. [ABSTRACT FROM AUTHOR]

China's rural solar photovoltaic projects (SPVPs), as an innovative initiative to improve livelihoods through clean energy, have played a positive role in poverty reduction. However, whether this measure can enhance energy services for rural families remains unconfirmed. This paper employs a quasi-experimental method from the perspectives of energy service accessibility and affordability to quantify the net contribution of China's rural SPVPs to enhancing family energy services. The results indicate: (1) SPVPs can significantly improve family energy services, with a net effect of 14.7 % on the energy service accessibility and a net effect of 44.5 % on the energy service affordability. (2) SPVPs can increase the energy consumption capacity, energy supply capacity and energy equipment utilization rate by 2.6 %, 7.1 % and 5 %, respectively. Furthermore, these initiatives can effectively slash the energy costs of rural families by 4.3 %, bolster the energy access affordability by 3.9 %, and catapult energy investments by an impressive 44.9 %. (3) These projects also perform well in the family energy consumption cleanliness. (4) The effect of SPVPs in providing energy services presents a regional difference, with the best performance observed in 'Type III' solar resource areas. Meanwhile, the implementation of China's rural SPVPs does not involve "elite capture." • We analyze the changes of energy accessibility and affordability in rural China. • We quantify the energy services effect of solar PV projects (SPVPs). • SPVPs perform well in improving family energy consumption cleanliness. • The energy services effect of solar PV projects has spatial heterogeneity. • The implementation of China's rural SPVPs does not involve "elite capture.". [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]

Shared‐energy storage (SES) can break the energy interaction barrier between the demand side and the supply side, which is becoming an option for improving the flexibility of energy systems. This study designed a novel structure for the shared‐energy aggregator (SEA), incorporating a microgrid (MG), prosumer and SES. Then, a two‐level market transaction optimization model for SEA, considering the robust stochastic optimization method, is proposed; namely, at the day‐ahead stage, a robust stochastic operation optimization model is constructed to achieve the dispatching plan from the demand side under the objective of achieving the minimum energy consumption cost for the prosumer, and at the real‐time market stage, a robust stochastic operation optimization model from the supply side is constructed to arrange the optimal dispatching strategy under the objective of the maximum aggregator benefits of MG and SES. Finally, an industrial park micro‐grid in Qinghai Province, China, is selected as an example for analysis. [ABSTRACT FROM AUTHOR]

Aims: China is the largest energy consumer and producer in the world. Energy is crucial for the enduring and healthy development of China. Promoting urbanization has been regarded as a strategic measure for China to release the potential of domestic demand against the background of enduring international financial crisis. Usually, urban areas are more energy intensive than rural ones. Therefore, it's very meaningful to understand the relationship between energy and urbanization. The main aim of the paper is to study the relationship between energy and urban developments based on the analysis of China's energy and urban development, and provide a clear picture of the impacts of urbanization on energy development, which contributes to forming a base for further study of urban and energy relevant policies.Scope: The paper presents a thorough analysis of China's energy development and urbanization. Then it conducts a systematic and in-depth study of the impacts of urbanization on energy development quantitatively and qualitatively. Finally, some helpful recommendations are provided for the coordinated development of China's energy industry and urbanization.Core findings: (1) Urban development will bring about interregional impacts on energy flow pattern. The new pattern is likely to be described as remaining stable in the eastern region, speeding up in the central and gradually increasing in the western. (2) Urban development will promote to form new intraregional energy systems. The city will be the most energy-intensive in the new system. The layout of the urban industrial system will be a "U-shape" in terms of energy intensity. The urban industrial system can be divided into three parts, namely, the core zone including the city itself, suburb zones and exurban zones. The core zone is the most energy intensive among the three. The exurban zones are more intensive than the suburb zones. (3) Urban development will increase energy consumption. In the period of 2015~2020, the incremental energy consumption effected by urban development will be 664 million tce; in the period of 2021~2030, that will be 774 million tce. (4) Urban development will influence energy mix thanks to people's awareness of environmental and eco-system protection, and implementing such technologies as smart grid, UHV transmission and so on. Also, urban development will increase electricity consumption.Conclusions: Urbanization and energy development are two strategically important issues. By 2030, hundreds of millions of people will transfer from village to city. Many new cities and city clusters will emerge, which will give rise to the transfer of industry and influence the development of energy. China's urban development both provides a precious opportunity and constitutes an immense challenge for its energy development. Firstly, the plan for urban development and that for energy development should be coordinated in terms of infrastructure layout, energy mix, energy supply and distribution, etc. Secondly, give full play to smart grid in such aspects as integrating renewables, promoting energy conservation, leading to consumption habits and meeting the demand of divers and multilateral services, accommodating electric vehicles and so on. Thirdly, adhere to such principles as advocating environmental and eco-system protection, developing in a way of being driven by innovation, and taking urban and rural situations into account accordingly. Fourthly, combine the transformation of its energy production and consumption with the development of urbanization, more organically, systematically and efficiently. [ABSTRACT FROM AUTHOR]

In this paper, we assess 13 process technologies to improve energy efficiency in the Chlor-Alkali sector of Shandong province in China up to 2025 using a technoeconomic approach. The results show energy efficiency improvement (EEI) potentials of 9% in the caustic soda and 38% in the polyvinyl chloride (PVC) production process compared to a frozen-efficiency development. The most influential technologies are energy-efficient electrolysis technology in brine electrolysis step and heat recovery technology in Vinyl Chloride Monomer synthesis (VCM) step. The energy savings can be translated into mitigated CO2 emissions of 10 Mt in 2025. The larger part of this potential is found to be cost-effective from a firm's perspective. In conclusion, significant saving potentials are still available. However, to achieve the all potentials, additional energy policies are needed. [ABSTRACT FROM AUTHOR]

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

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]

This paper constructs a two-stage undesirable and desirable congestion model, which distinguishes purely technical inefficiency from congestion, to study the energy congestion of 30 transportation sectors in China from 2011 to 2020. The Heckman model is used to analyze the influence mechanism of various factors on the undesirable congestion of energy, which avoids sample selection bias. The results show that: (1) The undesirable congestion of energy mainly exists in the transport sector of the western region, while the desirable congestion of energy only exists in the transport sectors of the eastern and central regions. (2) Purely technical inefficiency in the transportation sector does not usually occur in isolation. (3) Population density and the proportion of clean freight turnover have a negative impact on the undesirable congestion of energy. • A two-stage undesirable and desirable congestion model is designed innovatively. • Energy efficiency in transport sector is assessed from the perspective of congestion. • The factors affecting the undesirable congestion in transport sectors are analyzed. • Rational allocation of energy in transport sector is realized based on congestion. [ABSTRACT FROM AUTHOR]

This study uses two empirical approaches to explore the asymmetric effects of oil and coal prices on renewable energy consumption (REC) in China from 1970 to 2019. As a conventional approach, we used the nonlinear autoregressive distributed lags (NARDL) model, while machine learning was used as a non-conventional approach. The empirical findings of the NARDL indicate that oil and coal price fluctuations have a significant effect on REC for both the short and long term. The results of the non-conventional approaches based on machine learning indicated that the SVM model was more efficient than the KNN model in terms of accuracy, performance, and convergence. Referring to the SVM model findings, the results show that an increase in the coal price has a higher ability to predict REC than the oil price. As a robustness check, we also find that an increase in Brent prices significantly decreases REC. The findings of this study support the view that there is a substitution effect from oil to coal before initiating the use of renewable energy in China. [ABSTRACT FROM AUTHOR]

When talking about energy conservation, "Rebound Effect" (RE) is always concerned, which defined as the increasing energy consumption relative to the counterfactual predicted by technological progress because of efficiency induced decrease in the real price of energy services. In this paper, we try to find a way to figure out the RE through calculating the substitution relations accord with the definition. Based on the trans-log cost function and considering the asymmetric impact on energy-cost share equation, the paper applies Allen-Uzawa substitution elasticity to establish the price-oriented analysis diagram of fossil-energy consumption RE. Using time series data, applying the joint method of the dynamic OLS (DOLS) and the seemingly unrelated regressions (SUR), the RE in China's electricity generation sector is estimated. The results showed that the RE is 11.6% in China's electricity generation sector if allowing for asymmetric price effects, which indicates that China's power generation sector generally displays a feature of energy saving. [ABSTRACT FROM AUTHOR]

Against the backdrop of increasingly serious global climate change and the development of the low-carbon economy, the coordination between energy consumption carbon emissions (ECCE) and regional population, resources, environment, economy and society has become an important subject. In this paper, the research focuses on the security early warning of ECCE in Hebei Province, China. First, an assessment index system of the security early warning of ECCE is constructed based on the pressure-state-response (P-S-R) model. Then, the variance method and linearity weighted method are used to calculate the security early warning index of ECCE. From the two dimensions of time series and spatial pattern, the security early warning conditions of ECCE are analyzed in depth. Finally, with the assessment analysis of the data from 2000 to 2014, the prediction of the security early warning of carbon emissions from 2015 to 2020 is given, using a back propagation neural network based on a kidney-inspired algorithm (KA-BPNN) model. The results indicate that: (1) from 2000 to 2014, the security comprehensive index of ECCE demonstrates a fluctuating upward trend in general and the trend of the alarm level is "Severe warning"-"Moderate warning"-"Slight warning"; (2) there is a big spatial difference in the security of ECCE, with relatively high-security alarm level in the north while it is relatively low in the other areas; (3) the security index shows the trend of continuing improvement from 2015 to 2020, however the security level will remain in the state of "Semi-secure" for a long time and the corresponding alarm is still in the state of "Slight warning", reflecting that the situation is still not optimistic. [ABSTRACT FROM AUTHOR]

With the raise of 'The Green Industrial Revolution' and the growing demand for low-carbon energy, determining the method for assessing energy usage has become an important problem. In this paper, an assessment method of energy is proposed based on the combination of several models. The study of energy efficiency in China is conducted. First, the data related to the energy efficiency in 24 provinces for the last 9 years is gathered. Meanwhile the key factors for ensuring effective energy utilization in two provinces is determined through feature recognition. Then, the comparative analysis on the categories-fusion model's goodness of fit is performed, which was also used to predict the energy efficiency. Subsequently, the provinces with high and low energy efficiency based on the clustering strategies with multiple models merged are differentiated. Finally, corresponding recommendations for the development problem in China are presented based on the summary of the experimental results. The experimental results show that in comparison with the single-model approach, the merged multiple models has better performance than other methods. Therefore, this approach has a good engineering value. [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]

China's economy has developed rapidly relying on a large amount of production factors input. It has caused excessive consumption of fossil energy which led to a series of social problems. Although Chinese government adopted various measures to reduce energy use, the existence of the energy rebound effect affects the results of energy saving. Therefore, it is necessary to study and carry out the energy rebound effect of various industries in China. This paper works out ten hybrid energy input-output tables (value type) based on the ten input-output tables and energy consumption of the sub-sector from 1987 to 2012. Relying on the supply-driven Ghosh input-output model, this paper calculates the energy rebound effect of industries from 1987 to 2012 in China, and then analyzes the factors which may affect the energy rebound effect value. The results show that: The energy indirect rebound effect is much higher than direct energy rebound effect in most sectors; the higher energy efficiency, the lower direct energy rebound effect; the higher forward linkage degree of industry, the greater indirect rebound effect of energy. • Independent preparation of a hybrid energy input-output table. • Explore the energy rebound effect values of sectors and influencing factors. • The indirect rebound effect is higher than direct rebound effect in most sectors. • The higher the energy efficiency, the smaller the direct rebound effect. • Industry "forward linkage" degree increases the indirect energy rebound effect. [ABSTRACT FROM AUTHOR]

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

In the global context of intensive energy resource consumption and substantial greenhouse gas emissions, as the energy sector with the highest share of carbon emissions, the power generation industry is destined to play a central role in China's efforts to promote energy conservation and emission reduction. With the emergence of local carbon pilot projects and the implementation of a national carbon market, key emission units in the power industry, in addition to the electricity market business, also need to fulfill and pay carbon emission rights on schedule. The power generation rights are a market-based mechanism for clean energy units to replace conventional energy units in electricity generation, which can promote carbon emission reduction by incorporating the actual carbon emissions from conventional energy units. This paper establishes an optimized social welfare model that incorporates the interdependency between the thermal power generation unit market and the electric carbon market. It is based on the social welfare model of power generation rights and the initial allocation of carbon emission rights for the units, while considering the cost increase of excess emission under monthly forecasted power generation by the thermal power units. Taking a certain hydropower province as the simulation object, it was verified that the optimized model has a higher transaction rate of power generation rights, greater social welfare, and no reduction in unit revenue. • A groundbreaking linkage between power generation rights trading and carbon emissions trading is introduced. • A novel market optimization objective function is presented to enhance social welfare and encourage participation. • An innovative matching method is proposed to boost the transaction rate in power generation rights trading. • The proposed model is corroborated through a real case study in southwestern China. [ABSTRACT FROM AUTHOR]

Integrated energy system is an important approach to promote large-scale utilization of renewable energy. Under the context of energy market reformation and technology advancement, the economic operation of integrated energy system confronts new challenges, in terms of multiple uncertainties, multi-timescale characteristics of heterogeneous energy, and coordinated operation of hybrid energy storage system. To this end, this paper investigates the multi-timescale rolling optimization of integrated energy system with hybrid energy storage system considering the above challenges. Firstly, a basic framework of an integrated energy system with hybrid energy storage system (consisting of battery and hydrogen storage) is proposed, and the typical devices are modeled in detail. Secondly, the parameters and variables are divided into fast/slow timescale according to dispatch needs, and the multi-timescale problem of heterogeneous energy and the coordinated operation of the hybrid energy storage system can be solved simultaneously through two-stage optimization. Thirdly, the dispatch model is incorporated into the framework of model predictive control, the uncertainty of price, renewable energy and load can be effectively handled. Finally, a case study is conducted using an industrial park in the southern coastal region of China, the comparison with the rule-based method shows 60.65% reduction in the operating cost of hybrid energy storage system, the comparison with robust optimization shows 7.01% reduction in the total cost of the system, thus the feasibility and effectiveness of the proposed method are verified. • The application of HESS in IES is considered and modeled in a more detailed way. • Based on the two-stage approach, the heterogeneous energy multi-timescale scheduling problem and the HESS coordinated operation problem of IES can be solved simultaneously. • The dispatch model is incorporated into MPC for rolling optimization, and multiple uncertainties are effectively handled. • Using an industrial park in the southern coastal region of China as case study, the feasibility and effectiveness of the proposed method are verified. [ABSTRACT FROM AUTHOR]

Improving the deployment and penetration of renewable energy is considered to be the fundamental way to solve environmental problems, but whether higher penetration of renewable energy means higher energy efficiency remains to be empirically tested. To reveal the relationship between cleanliness and efficiency in the energy sector, this paper first uses the three-stage data envelopment analysis (DEA)method to measure the total factor energy efficiency (TFEE) of 30 provinces in China, and then applies static and dynamic panel threshold regression (PTR)models to estimate the nonlinear effect of renewable energy share on TFEE. The results show that renewable energy is usually beneficial for improving TFEE, but there are prominent heterogeneity and nonlinear characteristics in net electricity exporting and net electricity importing provinces. Renewable energy in low rather than high regimes can significantly improve energy efficiency, indicating that provinces with lower levels of economic development and energy consumption receive higher marginal energy efficiency and are more likely to achieve sustainable development goals. More renewable energy quotas should be given to economically developed and high energy consuming provinces, and comprehensive energy efficiency guarantees and improvement measures must be provided to achieve optimal emission mitigation. [ABSTRACT FROM AUTHOR]

The green and low-carbon transformation of the iron and steel industry stands as a pivotal cornerstone in the development of China. It is an inevitable trajectory guiding the future of industry. This study examined the energy consumption and carbon emission trends in the iron and steel industry. Variations under different scenarios were analyzed while emphasizing production control, changes in production structure and energy efficiency improvement. The analysis integrated the extreme energy efficiency model. This study proposed methods to enhance energy efficiency in the iron and steel industry. The costs of energy efficiency improvement and production structure changes were assessed using marginal energy saving and abatement cost curves. The findings showed that the carbon emission reduction contribution of crude steel production decline is the highest, while energy efficiency improvement technology offers the smallest, whose contribution, however, is substantial and cannot be overlooked by 2030. Energy efficiency improvement in the Chinese iron and steel industry results in an average unit energy saving and abatement cost of 27.0 yuan. It results in a total abatement cost of 21.02 billion yuan and a potential abatement of 780 Mt. Considering abatement potential, altering production structure offers significantly higher cumulative abatement compared to energy efficiency improvement technology. This is because the per unit abatement cost of production structure change is 702.7 yuan. However, this high cost poses a challenge to widespread adoption. The integration of the iron and steel industry into the carbon trading system necessitates reinforcing market constraints and expediting process adjustments. These steps are crucial to achieving the green and low-carbon transformation of the industry. [ABSTRACT FROM AUTHOR]

The author comments on a paper by Shujie Yao et al which analyzes the evolution of energy efficiency in the Chinese economy and the importance of transforming the country's economic structure. He explains the distinction between energy efficiency and energy intensity. He suggests that the data presented by the authors indicate that the Chinese economy has become less energy intensive. He argues that the link between policy recommendations and the descriptive analysis is missing in the paper.

Emissions trading scheme (ETS) is one of the effective measures to realize energy conservation and emission reduction. In order to set up a nationwide carbon emissions trading mechanism, seven ETS pilots have been launched in China. Firstly, based on empirical investigation and research of seven pilots, this paper analyzed the market efficiency of ETS pilots from four aspects: carbon price, trading volume, market liquidity, and information transparency. The result showed that the market efficiency of ETS pilots is not satisfactory in spite of the fact that system designs of ETS have achieved preliminary result. Then, the reason for low market efficiency of ETS pilots was discussed from some factors such as institutional arrangements, market participants, the supply and demand, etc. Finally, this paper puts forward some policy suggestions to improve the market efficiency of China׳s carbon trading market. [ABSTRACT FROM AUTHOR]

Listed energy companies play an important role in both the energy financial market and energy commodity market. As owners of listed energy companies, shareholders can influence the stability of the energy stock market by increasing or decreasing their holdings. To analyze the evolutionary features and stability of shareholders’ co-holding behavior, we constructed a derivative holding-based structural equivalence network of the shareholders (holding-based network) based on the primitive shareholding network of the listed companies and their shareholders. The main data used in this paper are the semi-annual reports from 2003 to 2012 that contain information about Chinese listed energy companies’ top 10 shareholders. The holding-based network takes the shareholders as nodes, whether holding the same listed energy companies’ stock at the same time as the edges, and the number of listed energy companies co-held as the weights. Due to the unique topological features of the holding-based network, we improved the Heuristic Algorithm to find the associated maximal connected sub-graph of the network, which is the main group of shareholders with shareholding consistency of the listed energy companies. This paper creates a new approach to analyze the relationships in the energy stock market, presenting a new method to analyze shareholder behavior. [ABSTRACT FROM AUTHOR]

China becomes the largest energy consumer in 2010 but its energy productivity is well below the world average. To meet China's fast growing energy using, energy efficiency should be especially emphasized under China's energy policy. This paper focuses on the regional level of energy efficiency change in China. And we analyze total factor energy efficiency for 30 Chinese provinces over the period 1998-2009 using Malmquist index method and Tobit analysis. The Malmquist estimation results suggest there is a dropping change trend of energy productivity growth. Chinese energy efficiency still faces with huge regional disparity, but the energy technical efficiency reflects convergence in the nationwide and west region. As a result of Tobit regression, we find that industrial structure, energy consumption structure and institutional factor have different influences on energy efficiency. [ABSTRACT FROM AUTHOR]

China has surpassed the United States to be the world's largest energy consumer, but a lot of energy was used to produce products for exporting to other countries. Presently, China faces a great challenge in energy security and environmental protection. This paper focuses on the energy embodied in China's foreign trade with a multi-regional input–output approach. Three versions of the GTAP (Global Trade Analysis Project) database were used to capture the trend and distribution of the embodied energy flows for China during 2001–2007. The results indicate that the energy embodied in the global trade is increasing rapidly, growing faster than the total direct energy exported in the same period. China is shown as an energy exporter in terms of embodied energy, and the embodied energy trade surplus increased from 156 million tons of oil equivalents (Mtoe) in 2001 to 514 Mtoe in 2007, with a proportion of domestic energy consumption increased from 14% to 23%. This paper also studies the effects of the energy-intensive industry restrictive export policy of China, and we find that this policy could reduce the national energy consumption and promote industrial structure upgrades effectively. However, the expansion of energy-intensive industries in other countries may reduce China's efforts for global energy saving and global warming alleviation. Our simulation shows that carbon leakage is about 50%. [ABSTRACT FROM AUTHOR]

China is vast, abundant and particularly plentiful in energy sources, due to which it has obtained remarkable achievements on economy. However, its energy structure is too simple to support the sustainable development of economy as coal still contributes to the majority of energy consumption in China. As a consequence, Renewable Energy Law was enacted in 2005, and Chinese government announced a series of policies to boom renewable energy industry. Subsidy policy is one of the major forms of these policies. This paper aims to present these subsidy policies and to analyze their effects according to relative data in energy industry 2005–2013, to find out the deficiencies and enlighten possible policy improvements. The original intentions and abstracts of 5 different levels of subsidy related policies are summarized, and the effects in reality are attentively analyzed. It can be concluded that subsidy policies have different short-term effect on different renewable energies, and they all show some negative effect to a certain extent. 6 core problems are summarized in this paper, and remedy strategies are suggested. [ABSTRACT FROM AUTHOR]

Nearly thirty years after the inception of reform in early 1979, China replaced Japan as the world's second largest economy. Its population grew from 962.3 million in 1978 to 2011's 1.34 billion. For the period 1979 through 2011, at constant prices, China's real GDP rose from 1978's 3.55 trillion Yuan to 2010's 31.46 trillion Yuan. However, paralleling China's rapid economic growth has been a phenomenal surge in energy consumption and needs. Disconcerting for developed economies of the West has been how China's growing needs for energy imports, especially for petroleum, is to impact the future of the world's markets for conventional sources of fossil fuels. A dozen years after China's economy began to thrive, China imported 0.776 million tons. By 2010, however, imports of the same accelerated to 294.4 billion tons. It was a 39-fold increase in petroleum imports during a brief two-decade period. The objective of this paper is to advance a proposition that, despite China's rapid increases in energy demands in recent decades, the evolving scenario in China is not to markedly affect world energy prices in the future due to the government's energy policy. [ABSTRACT FROM AUTHOR]