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Abstract: The objective of this paper is to estimate the energy saving potential in China's paper industry by determining energy intensity under different scenarios. Cointegration model and stability test are applied to formulate the equilibrium equation. Results show that energy price, industry structure, profit margin and technology have significant impact as they are negatively correlated to changes in energy intensity. Three scenarios (BAU (business as usual), intermediate and active) are designed to estimate the future trend of energy intensity in paper industry. In 2010, the energy intensity (energy consumption per unit of value added) was 4 tce/10,000 RMB, and by the scenarios it is expected to considerably decline. According to the BAU (business as usual) scenario, the energy intensity will decrease to 2.56, 1.43 and 0.70 tce/10,000 RMB by 2015, 2020 and 2025, respectively. With respect to the intermediate scenario it is expected to drop further to 0.44 tce/10,000 RMB. Yet by the active scenario, the energy intensity is expected to considerably decline to 0.36 tce/10,000 RMB by 2025. Using the BAU forecast as a baseline, the quantity of energy savings is estimated to be 185.6 billion tce by 2025. Considering this important potential, we also provided some policy suggestions. [Copyright &y& Elsevier]

Abstract: The pulp and paper industry is one of the most energy-intensive industries worldwide. In 2007, it accounted for 5% of total global industrial energy consumption and 2% of direct industrial carbon dioxide (CO2) emissions. An energy audit is a primary step toward improving energy efficiency at the facility level. This paper describes a plant-wide energy audit aimed at identifying energy conservation and CO2 mitigation opportunities at a paper mill in Guangdong province, China. We describe the energy audit methods, relevant Chinese standards, methods of calculating energy and carbon indicators, baseline energy consumption and CO2 emissions of the audited paper mill, and nine energy-efficiency improvement opportunities identified by the audit. For each of the nine options, we evaluate the energy conservation and associated CO2 mitigation potential. The total technical energy conservation potential for these nine opportunities is 967.8terajoules (TJ), and the total CO2 mitigation potential is equal to 93,453tonnes CO2 annually, representing 14.4% and 14.7%, respectively, of the mill’s total energy consumption and CO2 emissions during the audit period. [Copyright &y& Elsevier]

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

Cities have emerged as critical and challenging places for promoting the green and low-carbon transformation of the economy and society in the context of the "dual carbon" targets. Meanwhile, fiscal policy is also an indispensable component of the public policy framework supporting the green and low-carbon transformation. This paper uses the pilot project of "Comprehensive Demonstration Cities for Energy Conservation and Emission Reduction Fiscal Policies" ("ECER-CD" policy) implemented in China since 2011 as a quasi-natural experiment. This research theoretically analyzes and empirically tests the energy conservation and emission reduction effects of fiscal policies supporting green and low-carbon transformation utilizing methodologies such as time-varying DID and multiple periods and multiple groups of DID. The study finds that the pilot cities effectively reverse the behavioural bias of local governments and promote energy conservation and emission reduction efforts. This conclusion holds after undergoing robustness tests such as parallel trend analysis and heterogeneity treatment effects. The effectiveness of the pilot policy is attributed to the upgrade of industrial structure, improvement of energy efficiency, and the effects of green technology innovation. However, cities' geographic location and resource dependency can interfere with the effective implementation of policies. This paper also further explores the environmental dividends and economic consequences of the policy and finds that the pilot cities have certain environmental dividends and do not significantly restrain economic and social development. This study broadens the research perspective on fiscal policies in energy conservation and emission reduction and clarifies the pathways through which fiscal policies promoting green, low-carbon transformation drive energy conservation and emission reduction in cities. Moreover, it also improves the use of the Difference-in-Differences method in evaluating policy effects in scenarios such as the overlapping implementation of pilot policies and policy withdrawal. Finally, this paper proposes policy recommendations to provide more empirical evidence for China to accelerate the green and low-carbon transformation of the economy and society. [ABSTRACT FROM AUTHOR]

Energy quota trading is critical to both energy conservation and the achievement of dual-carbon goals. However, little remains to be done on total factor productivity and economic potential for Chinese industry. The purpose of this paper is to counterfactually model and explore the effects of energy quota trading on total factor productivity and economic potential in industrial sector. We propose a command-controlled DEA model and an energy quota trading DEA model through non-parametric linear programming based on two policy strategies of energy consumption control. We then assess total factor productivity and its growth sources for 35 two-digit industrial sector in China, as well as examine economic potential and optimal path forecasts for carbon peaking. The results show that total factor productivity and economic potential for energy quota trading are higher than those for command-controlled energy policy. Energy-saving effect can be achieved for energy quota trading because the total energy input is lower. Additionally, the sources of productivity growth differ in timing. The average economic potential and total factor productivity of different industries differ due to the heterogeneity of the production conditions and scale of development of individual market players. Moreover, the catch-up emission reduction path with an increase of 8% in output and 4.76% in energy consumption is the optimal carbon peaking path under energy quota trading. Our findings shed valuable light on China's efforts to expand energy quota trading for high-quality development in the context of carbon peaking. • Propose a command-controlled DEA model and an energy quota trading DEA model. • Assess TFP and its growth sources for industrial sector in China. • Compare the impact of different energy policies on economic potential and TFP. • Estimate the energy saving and emission reduction potential of energy quota trading. • Examine the optimal energy-saving and emission-reduction path forecasts for carbon peaking.. [ABSTRACT FROM AUTHOR]

This paper demonstrates the feasibility of using a ceramic medium stirring mill to reduce the energy consumption of grinding operations through an industrial verification experiment. Compared with the original two-stage ball milling process, the cost of grinding power consumption is significantly reduced by about 50.16%, which provides a reference for the subsequent research on energy saving and consumption reduction in ball milling operations. The optimal grinding parameters were determined to be grinding concentration of 50%, material ball ratio of 0.6, 3:2:5 media ratio (10:15:20 mm) of 3:2:5, medium filling rate of 90%, as well as stirring speed of 110 rpm. Under the optimum grinding parameters, an iron concentrate with an iron grade of 68.18% and an iron recovery rate of 94.17% were obtained by two-stage magnetic separation. The successful case of ceramic medium stirring mill replacing two-stage ball grinding provides a feasible solution for energy conservation and consumption reduction in mines in China. [Display omitted] • An industrial validation test of reducing energy consumption in grinding operations. • The applicable grinding parameters were determined by experiment. • A 36-h stable operation experiment was carried out. • The ceramic media stirring mill were studied. [ABSTRACT FROM AUTHOR]

This paper explores the salient factors driving the changes in energy consumption in China's nonferrous metal industry during the 2000–2014 period. We employ the logarithmic mean Divisia index (LMDI) method to decompose the change in energy consumption into the energy structure effect (Δ E ES ), the energy intensity effect (Δ E EI ), the industrial structure effect (Δ E S ), the labour productivity effect (Δ E G ) and the industrial scale effect (Δ E L ). The main results revealed the following: (1) from 2000 to 2014, China's nonferrous metal industry's energy consumption increased by approximately 69.08 million tons of coal equivalent (tce); (2) Δ E G increased energy consumption in all years and was the largest contributor to the increase in energy consumption (followed by Δ E L ), whereas Δ E EI was the dominant factor in reducing energy consumption over the same period, accounting for 104.07% of the change in the absolute value of total energy consumption; and (3) Δ E ES and Δ E S contributed 0.24% and 1.45% to the change, respectively. At present, the decline in Δ E EI cannot completely offset the increases resulting from the other four effects. This paper then provides several policy recommendations based on these results. [ABSTRACT FROM AUTHOR]

Facing the challage of energy conservation and emission reduction in the building sector, most energy saving strategies of central heating only focus on the performance improvement of building envelope, ignoring the impact of energy use behavior. This paper proposed a building energy conservation strategy based on energy use behavior analysis, which provides a perspective for in-depth exploration of building energy conservation. After investigating a typical university in the northern China, the energy use behaviors were characterized and two different DeST energy consumption models before or after considering energy use behavior were established. By comparing the results calculated by these two models, the impact of energy use behavior analysis on building energy consumption was quantitatively analyzed. The results show that the heating energy consumption and carbon emission can be reduced by 23.28% and 23% respectively through the proposed strategy based on energy use behavior. Therefore, the analysis of energy use behavior can provide a theoretical basis for heating operators to make decisions on energy supply regulation. With central cooling and heating further popularizing in the future, the research methodology of this paper has more extensive reference value for energy conservation and emission reduction strategies in the building sector. [ABSTRACT FROM AUTHOR]

It is highly important to clarify the determinants of China's energy consumption for the smooth implementation of energy conservation. For this purpose, this paper discusses the contribution of China's different economic sectors to decoupling progress. Then, it uses an extended logarithmic mean Divisia index (LMDI) method to decompose China's energy consumption into seven factors. The major findings indicate that during the 2000–2016 period, (1) the decoupling status between China's economy and energy consumption were determined largely by the secondary industry; (2) the positive contribution of three sectors to the decoupling process was ranked as follows: primary industry>tertiary industry>secondary industry; (3) China's energy consumption showed a growing trend, and the expansion of per capita fixed asset investment was the main factor responsible for the energy consumption increase, especially in some provinces whose investment structure was skewed towards energy-intensive industries. Additionally, population growth had mild positive impacts on the energy consumption increase; (4) declines in energy intensity and investment efficiency were two major contributors to energy-saving. However, economic structure, energy structure, and spatial structure adjustment failed to reduce energy consumption but had overall positive impacts on the energy consumption increase. Finally, several policy recommendations related to reducing energy consumption are proposed. • The empirical analysis was conducted at both national and provincial levels. • Decoupling status was determined largely by the secondary industry. • Per capita fixed asset investment was dominant for energy consumption increase. • The decline in energy intensity and investment efficiency contributed to energy-saving. [ABSTRACT FROM AUTHOR]

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

For many years, China has invested effort into achieving resource conservation and environmentally friendly economic development. The measures implemented include promoting technological innovation, market-oriented reform and industrial structure adjustment. But there are open questions: What have the effects of these measures been? Have they helped China achieve win-win development in terms of its resources, environment, and economy? This paper aims to answer these questions by using a newly proposed global three-hierarchy meta-frontier Luenberger index that can quantify the effects of promoting technological innovation, industrial restructuring, etc., on economic growth, energy conservation and emissions reduction. The results show that (1) during 2001–2016, China's energy efficiency, economic efficiency, and emissions efficiency improved, indicating that China's efforts have brought about the win-win development of resources, the environment, and the economy; (2) the implemented measures have heterogeneous effects on economic growth, energy conservation, and emissions reduction. The implemented measures are generally beneficial to energy conservation and emissions reduction but potentially harmful to the economy; (3) the effects of these measures on economic growth, energy conservation and emissions reduction across China's regions and provinces are also quite different, indicating that local provincial governments should have a clear understanding of their own characteristics before implementing the relevant policies and measures. • A global three-hierarchy meta-frontier Luenberger index was proposed for the study. • It can quantify the effects of China's efforts on economy, energy, and emissions. • Results show that China's efforts have brought about a win-win development. • There are the heterogeneities of China's pathways to economic growth, energy conservations and emissions reductions. • The future strategies for China's win-win development should take the heterogeneities into account. [ABSTRACT FROM AUTHOR]

The energy conversion efficiency of coal utilization is a focal point in modern energy management practices and in academic literature. This paper explores life cycle energy efficiency of coal (LEEC), which encompasses six distinct stages from the design of coal mines to the comprehensive reuse of resources. First, the study analyzes improvements to the evaluation of efficiencies in energy systems. Secondly, it proposes a multi-stage energy efficiency analysis and constructs an innovative LEEC model for coal exploitation and utilization. Thirdly, the energy efficiency of coal exploitation and utilization was evaluated, and found that total efficiency in China increased from 33.11% in 2010 to 37.69% in 2014, saving 126 Mtce of energy. Finally, this study found that mine design is the most important stage in improving energy efficiency, followed by the coal processing stage. Moreover, we found that coal processing has an indirect contribution to other stages in the life cycle utilization of coal, such as reducing transportation capacity. The primary research contribution is the development of a comprehensive LEEC model for the entire life cycle of coal, rather than just single-stage evaluation. This lays the foundation for further studies on energy efficiency of industrial chains and across entire systems. • Exploration of energy efficiency across the entire coal life cycle. • The energy efficiency of coal exploitation and utilization increased annually. • Analysis shows the implicit contribution of coal processing to life cycle. • Mine design is a crucial stage for overall life cycle energy efficiency. [ABSTRACT FROM AUTHOR]

Improving energy efficiency helps achieve energy conservation and emission reduction. Examining whether China's SO2 trading emission system (TES) reform can enhance energy efficiency will provide empirical evidence for the institutional benefit of market-oriented environmental regulation in environmental governance. This paper employs the difference-in-differences (DID) method to examine the effect of SO2 TES on energy efficiency using panel data from 285 Chinese cities from 2003 to 2018. The empirical results indicate that: (1) SO2 TES significantly promoted green total factor energy efficiency and reduced energy intensity. This conclusion is still valid after the prerequisite assumption test and robustness test. (2) SO2 TES significantly promotes local energy efficiency and has significant spatial spillover effects on surrounding cities. (3) Promoting green technological progress, resource allocation, and curbing energy consumption, are the primary mechanisms for SO2 TES to improve energy efficiency. (4) SO2 TES's improvement in energy efficiency comes more from eastern, developed, small, resource-based, and non-old industrial cities. • SO2 trading emissions system (TES) improves energy efficiency. • TES has a spatial spillover effect on nearby cities. • Green innovation, resource allocation and energy saving effects are the channels. • The effect of the TES on energy efficiency is heterogeneous. [ABSTRACT FROM AUTHOR]

[Display omitted] • Calculate carbon emissions of energy consumption by using annual emission factors of indirect energy. • Put forward quantitative indicators of mine intelligence. • Impact of intelligence on carbon emissions of energy consumption in mining industry. • Prediction of carbon emissions in mining industry based on intelligent scenario analysis. The intelligent construction of the mining industry has become an emerging trend in its future development plans. As a traditional high energy consumption industry, its energy conservation and emissions reduction have become particularly urgent concerns. Therefore, it is of great significance to study the impact of intelligence on the carbon emissions from energy consumption in the mining industry. This paper first uses dynamic indirect energy emissions factors to build an accounting model for carbon emissions from energy consumption in the mining industry and calculates the related carbon emissions from 2001 to 2020 by sector. Then, an expandable stochastic environmental impact assessment (STIRPAT) model is established to analyze the impact of intellectualization on the carbon emissions intensity of China's mining industry. At the same time, many other important factors are included in the model, and the model is fitted using ridge regression. The results show that the order of influence, from large to small, is as follows: energy intensity, industrial output value, per capita output value, the proportion of output value of large and medium-sized enterprises, per capita stock of fixed assets, average enterprise output value, R&D intensity and proportion of indirect energy. Each 1% increase in the above factors will increase the corresponding carbon emissions intensity by 0.2005%, −0.1271%, −0.1207%, 0.7467%, −0.0595%, −0.09813%, 0.1143% and −0.1419%, respectively. Then, the prediction values of the independent variables are obtained by using the scenario analysis method and grey prediction model, and 12 scenarios are set up to predict the carbon emissions intensity of the mining industry energy consumption from 2021 to 2035 by using the expanded STIRPAT model. By analyzing the prediction results, we conclude that Scenario 8, Scenario 9, Scenario 10, Scenario 11 and Scenario 12 can achieve the emissions reduction goals of the mining industry in 2025 and 2030; the optimal path of emissions reduction is given for various scenarios. Finally, a development strategy for emissions reduction in China's mining industry is proposed. [ABSTRACT FROM AUTHOR]

The iron and steel sector is energy-intensive, and it consumed 18% of the world's total industry final energy consumption in 2013. At present, according to the statistical data of International Energy Agency (IEA) published in 2012, the iron and steel industry has the technical potential to reduce its current total energy consumption by approximately 20% by applying the best available technology (BAT), and more than half of this technical potential may be obtained in China, where more energy-efficiency technologies/measures should be implemented in the steel plants. So a review of energy-efficiency technologies/measures in steel industry could be helpful for steel plants to improve their energy efficiency. Therefore, this paper presents a list of energy-efficiency technologies and practices applicable to the steel industry, which includes case studies around the world and information of energy savings and cost when available. Also, a brief overview of the steel industry around the world, details and energy use conditions of different steel manufacturing processes, types of energy use and specific energy consumption of steel industry and details of secondary energy are also included in this paper to give readers a clear understanding of the energy use situation of the steel industry. [ABSTRACT FROM AUTHOR]

Abstract A full understand of the influential mechanism concerning electricity consumption has a crucial political reference significance for the implementation of energy conservation and consumption reduction policies. To solve the lack of correlation between the empirical results of the research regions in present researches, this paper takes China's electricity consumption from 1995 to 2016 as the research subject, uses Multi-period ST-LMDI model by setting a unified reference province as a benchmark for different regions in China to completely decompose the changes in China's electricity consumption, and further analyzes the influence mechanism of China's electricity consumption changes by combining the characteristics of the departments and regions. As the result, it's found that the economic growth has a strong impetus for power consumption while the technological progress can effectively curb it. Meanwhile, results of studying electricity consumption from the perspective of industry and region show that the economic structure and consumption intensity have obviously different influences in the eastern, central and western regions. So when it comes to formulate the policy for electricity development and reform, the characteristics of industrial structure as well as the regional differences must be taken into consideration. Highlights • We apply Multi-period ST-LMDI to decompose China's electricity consumption. • The expansion of the economy is the main factor for the growth of electricity consumption. • Decline in electricity consumption intensity restrain the growth of power consumption. • All industrial sectors basically had positive effects on electricity consumption. [ABSTRACT FROM AUTHOR]

Abstract The construction industry is one of the largest energy consumers and CO 2 emitters in China. This paper primarily aimed to explore the driving forces of energy-related CO 2 emissions (ECE) from the construction industry. Adopting a comprehensive decomposition approach, this study decomposes the changes in ECE into eight factors. The main results provide the following findings. (1) Industrial activity was the largest factor pushing the growth of CO 2 emissions, driving up CO 2 emissions in all years and contributing to a 174.65 Mt CO 2 emissions increase in total. (2) In contrast, advances in industrial output technology represented the dominant factor inhibiting CO 2 emissions, cumulatively reducing CO 2 emissions by 99 Mt. (3) The effects of potential energy intensity changes and industrial output technical efficiency fluctuated in different years but exerted positive effects on CO 2 emissions over the entire period. (4) Additionally, changes in spatial structure, energy-saving technology, and energy consumption structure as well as energy usage efficiency all contributed to emissions reductions to varying degrees. The CO 2 emissions of the construction industry increased in all provinces, while emissions changes and their factor effects varied distinctly across provinces. Highlights • Direct and indirect CO 2 emissions in China's construction industry are calculated. • Impacts of driving factors are quantified by combining the PDA and IDA methods. • Industrial activity is mainly responsible for CO 2 emissions increase. • Industrial output technology change is the dominant curbing factor. • Factor effects of China's construction industry vary distinctly across provinces. [ABSTRACT FROM AUTHOR]

Highlights • Parameters of 60 electricity-saving measures and 16 abatement measures are compiled. • Synergies of electricity use in China's chemical sector at grid level are assessed. • Efficient use of power can cut 154 Mt CO 2eq , 295 kt SO 2 , 322 kt NO x and 64 kt PM 2.5. • North and Northwest grids have the largest economic benefits on emissions reduction. • Grid with high electricity price is more sensitive to price change than other grids. Abstract Industry is a large electricity user. China's chemical industry (globally the largest based on sales) contributes 7% to China's GDP, while it consumes 11% of the total electricity consumption in industry and is responsible for 40% of total CO 2eq , 40% of SO 2 , 59% of NO x and 18% of PM-emissions of the chemical industry emissions. The heterogeneity of GHG and air pollutant emissions across electricity grids (within a country) is rarely included in analyses. In this paper, electricity conservation supply curves are developed (distinguishing the grids) to estimate the cost-effective and technical potentials of electricity conservation in China's chemical industry. The emission factors per grid for GHG (i.e. CO 2 , CH 4 and N 2 O) and air pollutants (i.e. SO 2 , NO x and PM 2.5) are calculated and used to quantify the emissions mitigation achieved by electricity saving technologies in the chemical industry for the period 2012–2035. Results show that significant multiple benefits can be obtained by implementing electricity efficiency measures. There are large differences among the six grids in terms electricity savings and emissions abatement of GHG and air pollutants. 83% of the total electricity saving potential is contributed by the North, Northwest and Central grids, equal to 32% of baseline electricity consumption in 2035. In 2035, 129 Mt of CO 2 , 33 kt CO 2eq of CH 4 , 571 kt CO 2eq of N 2 O, 235 kt of SO 2 , 275 kt of NO x and 52 kt of PM 2.5 in these three grids can be avoided as a result of electricity savings (a reduction of 31–33% compared to baseline emissions). When decision-makers set targets for energy saving and emission reduction, the multiple benefits and grid heterogeneity should not be ignored. [ABSTRACT FROM AUTHOR]

This paper investigates the public attitude toward and willingness to accept six energy-saving measures in the residential sector in Beijing, China. The qualitative results derived from questionnaires show that financial incentives and the desire to reduce energy consumption are the most significant factors driving the public to adopt the measures and that the unavailability of electric vehicle (EV) chargers is a crucial barrier to the promotion of EVs. The quantitative results indicate that socioeconomic variables have a greater impact on technical energy-saving measures than behavioral ones. Renters or individuals with a high risk preference have a lower willingness to accept energy-efficient air conditioners. The price of gasoline, convenience of EV chargers, EV policy package, and environmental concern can significantly influence willingness to purchase an EV. With regard to behavioral energy-saving measures, control of the heating system and the influence of nearby people (spillover effect) significantly increase the preference for closing windows when the heating is on. The public transportation convenience, high gasoline prices and the congestion charge have significant effects on residents’ willingness to use public transportation. Infrastructure upgrades to heating and transportation would remove adoption barriers and facilitate energy conservation. Price policies and preferential policies related to EVs could have a significant impact on household choice of transportation mode. Finally, increasing the public energy-saving awareness and environmental concern is recommended to facilitate the promotion of energy-saving options. [ABSTRACT FROM AUTHOR]

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]

Coal mining not only produces, but also consumes a large amount of energy. Coal production has an extremely high energy efficiency potential, and benchmarking is critical to discover this potential. To address problems such as ambiguity of coal production (e.g. underground mining), benchmarking range and absence of both indicators and standards for energy efficiency benchmarking, this paper makes use of product-based and process-based benchmarking. These two techniques are used to construct a benchmarking system for coal production with high energy efficiency, and improve the standards used at the eight coal mines owned by the Yankuang Group. Comparison and analysis of benchmarking in enterprises indicates that energy use during raw coal production could be reduced by 22.77%. Across China energy savings from coal production could reach 15.98–32.98 Mtce, with an equivalent 42–87 Mt of CO 2 emissions saved. Lastly, this paper provides measures to improve coal production energy efficiency. [ABSTRACT FROM AUTHOR]

As an important path to realizing carbon neutrality in China, digital development may also lead to the growth and rebound of energy demand. Investigation of digital rebound effect is important to evaluate whether digital development can effectively conserve energy. Thus, this paper examines the impact of digital development on electricity consumption and its heterogeneity among Chinese cities, and further evaluates the sizes of energy rebound effect triggered by digital development. The results show that, first, electricity consumption in Chinese 285 cities increases by 7%–20% due to digital development, and this positive influence tends to increase with the increase in electricity consumption. Second, in the eastern, high-income, and high-tertiary industry share regions, digital development has a greater role in promoting electricity consumption. Third, the digital development of Chinese cities induces the rebound effect of electricity consumption, and even induces the backfire effect in the early stages of digital development. Finally, the energy rebound effect tended to decrease over time, with a partial rebound in electricity consumption, and the minimum rebound effect was 22%. The results highlight the necessary attention on digital rebound effect, and the importance of low-carbon digital development. • Electricity consumption increased 7%–20% due to digital development in China • The positive influence tends to increase with the increase in electricity consumption • Digital development in Chinese cities leads to energy rebound effect • The energy rebound effect tended to decrease over time, with a partial rebound [ABSTRACT FROM AUTHOR]

• The data requirements of quota methods are summarized, and a city-scale database containing 670 credible government office buildings is established. • By comparing the processes, the results and applicability, the selection basis of quota methods under different conditions is refined. • A flow chart of the formulation process and method selection of city-level building energy consumption quotas is constructed. • It is proposed that special attention should be paid to the outliers, and the characteristics of outliers in Chongqing are summarized. Energy consumption quota policies are effective management measures to promote energy conservation and emission reduction in China. Cities need to choose an appropriate method to formulate local energy consumption quota standards. This paper is based on the data of 670 government office buildings in Chongqing and the selected quantile method (QM), quota-level method (QLM) and multiple linear regression (MLR) method, which are widely used in the formulation of city-level energy quotas. By comparing their interpretability, evaluation, consistency and stability, the application conditions and applicability of each method are summarized. MLR has the strongest explanatory power but the highest requirements for the technology and information dimensions. The QLM is more explanatory and stable than the QM and is more suitable for the initial stage of energy quota management. When using the QLM, we should consider scientific classifications and reasonable quota levels. Special attention should be given to "outliers" with abnormal evaluations of the quota results. The outliers in Chongqing are characterized as buildings that have been used for more than 10 years and have an area of less than 5000 m2. Finally, this paper constructed a flow chart of the formulation process and method selection to help policymakers better understand how to choose the most appropriate method and identify inefficient buildings. [ABSTRACT FROM AUTHOR]

This paper estimated the cost curve of energy saving and CO 2 emissions reduction in China's iron and steel sector. Forty-one energy saving technologies which are widely used or popularized are selected, their investments, operation costs, energy savings and CO 2 abatement are collected and the data in 2010 are taken as a baseline. Then energy conservation supply curve and CO 2 conservation supply curve under two different discount rates are calculated in the paper. These 41 technologies result in a saving contribution of 4.63 GJ/t and a CO 2 abatement contribution of 443.21 kg/t. Cost-effectiveness of technologies was analyzed based on the fuel price and an estimated CO 2 price. When comparing the result with the promoted technologies during the 12 th five-year-plan, we found that some promoted technologies are not cost-effective in current situation. Three scenarios are set through changing the diffusion rate of technologies and the share of BOF and EAF, based on this energy saving potentials of technologies in 2020 and 2030 are forecasted. At the same time, we compared the change of the CSC depending on the year and the energy saving potentials in three scenarios of 2020 and 2030, respectively. [ABSTRACT FROM AUTHOR]

China's energy conservation has received extensive attention. As the most important sector of the economy, the manufacturing industry plays a vital role in China's energy issues. Conserving energy in China's manufacturing industry (CMI) is of great significance for both China and the world. In this paper, the co-integration method is applied to test the long-term equilibrium relationship among energy consumption and three explanatory variables during the period 1980–2013. Furthermore, we use scenarios analysis method to forecast the energy demand of CMI. The results show that if the government does not properly manage the economy, the energy demand of CMI will reach 2558.97 Mtce in 2020 and 2594.18 Mtce in 2030. On the contrary, if the government attaches importance to energy conservation and takes necessary actions, energy demand in the industry will reduce to 1113.79 Mtce by 2030, which implies a large energy conservation potential for CMI. [ABSTRACT FROM AUTHOR]

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

The direct rebound effect offsets part of energy savings brought about by energy efficiency, causing academics and governments to re-examine the relationship between energy efficiency and conservation. Although suppressing the rebound effect contributes to energy conservation, how to implement it is debatable. This paper puts forward a framework to character the direct rebound effect, and develops non-linear models to explore the impacts of urbanization on the direct rebound effect based on a panel dataset of 30 Chinese provinces. The results show that, first, the magnitude of the direct rebound effect is much smaller in urban areas than that in rural areas. Second, urbanization could restrain the direct rebound effect in urban areas, where employment and environmental consciousness play important roles while the impact of agglomeration is relatively weak. The impacts of urbanization on direct rebound effect are not substantial in rural areas. In addition, our findings reject the saturation effect caused by income. Income promotes the direct rebound effect in rural areas while it could not restrain the direct rebound effect in urban areas. Therefore, the reason that the average direct rebound effect tends to decline with income growth seems to be the urbanization rather than the saturation effect. • This paper puts forward a framework to character the RE and explore its evolution. • A new urbanization that looks at its quality rather than its growth is conducted in this paper. • The relationship between income and the RE is re-examined and it has the urban-rural heterogeneity. • The RE of urban areas decreases with urbanization mainly in the employment and environment dimensions. [ABSTRACT FROM AUTHOR]

• A new urban building energy modeling tool-AutoBPS was developed. • AutoBPS calculated urban building energy demands, analyzed energy retrofit and rooftop PV potential via EnergyPlus. • AutoBPS automatically generated multi-zone models, considering shading from surrounding buildings. • A downtown district of 3633 buildings in Changsha, China, was simulated to demonstrate the tool's features. • All three energy conservation measures and PV installation could save 38.6% of total energy demand. China has promised to peak carbon emissions by 2030 and become carbon neutral before 2060. Achieving this target requires actions from all sectors, especially the building sector, which accounts for 33 % of the total energy consumption in China. Within this scenario, this paper introduces a new urban building energy modeling tool, Automated Building Performance Simulation (AutoBPS), to calculate urban building energy demands and to analyze energy retrofit and rooftop photovoltaic (PV) potential. AutoBPS uses a building-by-building approach to automatically generate multi-zone (one zone per floor) models based on the city building dataset, considering the shading effect by surrounding buildings. The tool simulates building energy use and PV generation via EnergyPlus. A downtown district of 3633 buildings in Changsha, China, was selected as a case study to demonstrate the features of the tool. Firstly, annual baseline energy uses of 1793 GWh were simulated by inputting Geographic Information System (GIS) data. Then, different energy conservation measures (covering envelope, lighting, cooling system upgrade, etc.) and roof PV generation systems were adopted to explore energy saving potential. The results showed that the window upgrade was the most energy-efficient individual measure for residential buildings, while the lighting upgrade was that one for commercial buildings. Altogether three measures could save 2.7 ∼ 30.7 % of annual site energy use intensity per building. The total energy demand could be reduced by 18.5 % by combining all measures and saved by 38.6 % when PV installation was added. AutoBPS can be easily applied to other cities, supporting urban energy efficiency plans for carbon reduction goal implementation. [ABSTRACT FROM AUTHOR]

Abstract: In March 2011, China’s central government set a new challenging target of reducing its energy intensity by 16% during 2011–2015, after it had achieved a reduction of 19.1% during 2006–2010. And this new target was assigned to provincial authorities in August 2011. However, China’s provincial energy-economic developments are unbalanced and different provinces have different key sectors for energy conservation. Most previous studies focused on provincial energy efficiency at the aggregate level, or the three-industry level (or one-digit level). However, whether for policy decision or academic research, it is necessary to further subdivide the sectors. In this paper, we use three indicators (Gini Coefficient, energy consumption share and energy intensity) to compare provincial energy conservation potentials at the two-digit sector level. To our knowledge, this paper is the first one to identify the keys for energy conversation across the 31 provinces×65 sectors. And the results are shown in visualized maps and matrix tables to help identify the key province×sectors for energy conservation easier. This also helps the central and provincial governments to distinguish key sectors when they monitor the energy conservation progress. [Copyright &y& Elsevier]

Following the impressive economic achievements in the past decades, China is faced with energy and environmental challenges. To carry out more effective and targeted energy policies, the heterogeneities of different industrial sectors are of great importance. The energy consumption of China’s light industry in 2012 was 316 million tons of coal equivalents, which is about the energy consumption of South Korea. The paper explored the substitution relationships between various input factors and fuel sources, and showed that electricity price reform is crucial for energy conservation in China’s light industry. Then, the dynamics of energy intensity change is examined by decomposing energy intensity into budget effect, substitution effect, output effect and technology advance effect. The result revealed that the substitution effect between input factors is a key driving force. However, technology progress seems to contribute very little. For future energy policy alternatives, promoting the implementation of new conservation technology and electricity price reform may be effective measures. [ABSTRACT FROM AUTHOR]

As a market-based mechanism which can actively promote energy efficiency, Energy Performance Contracting (EPC) is now universally accepted throughout China and has been incorporated into various business models. Four of these business models are frequently adopted in China: the Share Savings Model, the Guaranteed Savings Model, the Energy-cost Trust Model and the Finance Lease Model. The choice of a suitable business model has been recognized as one of the most important factors in the effective implementation of EPC projects. In this paper, the selection of EPC business models is formulated as a multi-criteria decision making (MCDM) problem. When selecting an EPC business model, it is natural for decision-makers (DMs) to express their preferences/opinions in linguistic terms. Given the characteristics of EPC projects, taking DMs' psychological behavior into account is of considerable and realistic significance. TODIM (an acronym in Portuguese of interactive and multicriteria decision making) has been verified as an effective behavioral decision-making method. To address the problem of EPC business model selection, an extended TODIM method based on multi-granularity linguistic terms and entropy measure is proposed. The sensitivity and comparison analyses show that DMs' psychological behavior can affect the selection order with respect to the given EPC business models. One case of a real-life campus EPC project demonstrates that the validity and applicability of the proposed extended TODIM method for solving the EPC business model selection problem. [ABSTRACT FROM AUTHOR]

Is it the heavy industry or light industry that performs better in energy efficiency incorporating undesirable outputs? Energy efficiency is the gap between actual and target energy inputs, thus the more energy intensive heavy industry is not necessarily the less energy efficient one. The purpose of this paper is to evaluate and compare the ecological total-factor energy efficiency (ETFEE) of the heavy and light industries as well as to assess their technology gaps. Considering the slack-bias of conventional DEA models and technological heterogeneity between heavy and light industries, the slack-based DEA model (SBM) and meta-frontier technology have been combined. The empirical results show that: (1) China's industries did not perform efficiently. Among them, heavy industry, albeit has more advanced technology, demonstrates lower energy efficiency than light industry. Thus, China needs to stimulate heavy industry to achieve its potential in efficiency improvement. (2) Compared with light industry, governmental stimulus induced expansion has promoted technological advancement in heavy industry, but it still has had no effect on the utilization of existing technologies by, for example, improving the managerial efficiency. Greater pressure on environmental standards is needed to motivate factories in heavy industry to utilize existing technologies more sufficiently. (3) Technological gap among industries has enlarged, thus more attention should be paid on encouraging technology spillover from heavy industry to light industry. [ABSTRACT FROM AUTHOR]

Strengthening the implementation of environmental regulation is one of the key measures to prevent further energy depletion and environmental deterioration. This paper focuses on complicated relation between environmental regulation and fossil energy consumption. We theoretically identified the direct and indirect paths of environmental regulation that affect fossil energy consumption and analyzed the relationship between the two. To identify the indirect impact of environmental regulation on fossil energy consumption, we incorporated three types of technology (e.g., production technology, pollution abatement technology, and backstop technology) into our model. On the theoretical basis, we then evaluated the impact of environmental regulation on fossil energy consumption in China by applying both non-spatial models and spatial econometric models. In the direct path, energy-saving effect of environmental regulation in China is dynamic and yields complex results from the “Green Paradox” and “compliance cost”. As for indirect effects, we find that current environmental regulations have promoted technological progress in production to induce energy savings but failed to drive technological advancements in pollution abatement and backstop to guarantee a sustainable energy development. Based on the findings, some corresponding policy implications are provided. [ABSTRACT FROM AUTHOR]

Energy conservation is a major strategy for China to shift to a low-carbon economy and achieve sustainable development. The heating industry uses coal as its main fuel source in China. Energy consumption of China's heating industry grew at an average annual growth rate of 7.75% over 1980–2011. We use the co-integration method to explore the long-run relationship between energy consumption of the heating industry and the factors including GDP, urban population density, central heating supply areas and fuel price. The results indicate that 1% GDP growth yields 2.24% increase in energy consumption of the heating industry. 1% urban population density growth and 1% central heating areas growth result in 0.56% and 0.36% decline in energy consumption of the heating industry, respectively. Under the BAU scenario, energy consumption of the heating industry will be 157.11 Mtce in 2020. Energy conservation potential is estimated to be 22.16 Mtce under the moderate scenario and 43.6 Mtce under the advanced scenario. Moreover, this paper holds the view that the central heating system can be considered as an effective heating method for cities with dense population, both in the south and north. At last, policy recommendations for energy conservation in the heating industry are provided. [ABSTRACT FROM AUTHOR]

China has been the world’s largest cement producer and the cement production has led to increased energy consumption and CO 2 emissions, which greatly affect the country’s social and economic development. In this paper, an integrated assessment framework was developed by combining the Stock-based model and the Integrated MARKAL–EFOM System model of China (China TIMES), and it was used in China’s cement sector to simulate the trends of energy consumption and CO 2 emissions during 2010–2050, under a reference scenario and three carbon tax scenarios. The modeling results show that: (1) the cement production in China will increase from 1.8 billion tons in 2010, to a peak of 2.5 billion tons in around 2017, and then gradually decrease to 1.5 billion tons in 2050; (2) Through the adoption of three alternative abatement measures (i.e., switching the fuel types, implementing the energy-efficient measures and CCS), China’s cement sector could potentially achieve a great reduction in CO 2 emissions; (3) In the near future, the cement sector’s decarbonisation will mainly rely on energy efficiency improvement; while the use of alternative fuel use and CCS will be of great significance from a long-term perspective. Additionally, based on the modeling results, we build the energy-saving and emission-reduction technologies roadmap for China’s cement sector. [ABSTRACT FROM AUTHOR]

Improving energy efficiency sustainability is a target of the Chinese government. However, the effectiveness of energy conservation policy is affected by the energy rebound effect under which energy efficiency improvement reduces the effective price of energy services, thereby completely or partially offsetting the energy saved by efficiency improvement. Based on the output distance function, this paper develops an improved estimation model of the energy rebound effect, which is logically consistent with the quantities of energy savings and energy rebounds induced by technological progress. Results show that the aggregate energy rebound effect of 36 industrial sectors in China over 1998–2011 is 88.42%, which implies that most of the expected energy savings are mitigated. Investment-driven economic growth is not conducive to energy-saving and results in a strong energy rebound effect in the following year. The equipment and high-end manufacturing sectors have low levels of rebound effect, indicating that increasing the proportion of such firms in the total manufacturing sector can improve the performance of energy conservation. The high level and heterogeneity in rebound effects strongly suggest that varies strategies are necessary for energy conservation among China’s industrial sectors. [ABSTRACT FROM AUTHOR]

This paper uses a meta-frontier slack-based DEA model to measure the ecological total-factor energy efficiency as well as the energy conservation potential of China’s four energy intensive subsectors. We incorporate both desirable and undesirable output together in the period, 2000–2013. The conclusions are: firstly, under the meta-frontier, the four subsectors of energy intensive industries have low average level of ecological total-factor energy efficiencies. They are 0.137, 0.212, 0.238, and 0.307 in the non-metallic mineral products manufacturing industry, raw chemical materials and chemical products manufacturing industry, smelting and pressing of ferrous metals industry, and smelting and pressing of non-ferrous metals industry, respectively. Secondly, the ecological energy efficiency in East China is the highest among three regions. Central China and West China are behind, but they are extremely close to each other. Thirdly, East China almost has no technology gap pertaining to energy efficiency, while Central China and West China almost have the same gap. Finally, Sichuan is considered to be the best province in West China under group frontier due to its perform in the three energy intensive subsectors. For Central and East China, no province has higher ecological energy efficiency in more than two energy intensive subsectors. [ABSTRACT FROM AUTHOR]

• POE was carried out to compare the design target and operational effect after use. • A Large Irregular Green Commercial Building was chosen for in-depth analysis. • We recommend the building energy saving and carbon emission reduction strategy. Commercial buildings, especially large irregular commercial buildings with complex space and dense occupation, have high energy consumption and carbon emissions. Moreover, the actual operating performance differs significantly from its design, in terms of energy conservation and carbon emissions. This study selected an irregular large-scale green commercial building in Dalian, a coastal city in the cold zone of China. The running energy consumption and indoor physical environment were investigated and analyzed, and a satisfaction survey was conducted using the Post-occupancy evaluation (POE) methods. The promotion strategies of holistic design were proposed by comparing the operational building performance with the design target. The research shows that the energy consumption of the building was 68.02 kWh/m2, which failed to meet the standard requirements. The carbon emission was 74.76 kgCO 2 /m2. Less than 10 % of humidity in summer fell in the expected range, and the lowest value of PM 2.5 concentration in winter was 28.3 %. The score of indoor environmental quality and service satisfaction was low. This paper identifies the problems and analyzes the differences between the operation stage and design phase. It provides recommendations and guidelines for optimizing the carbon emission and indoor environment based on the performance improvement of building operational conditions. [ABSTRACT FROM AUTHOR]

Abstract: Charging heating fees based on floor space in China leaves building developers no economic returns on the investment to weatherize the buildings and install regulation devices with terminal equipment. Therefore, they lack incentives to improve the thermal insulation properties of the buildings. Tenants also lack incentives to efficiently use heat, opening windows to cool down rooms when they are overheated, without concern for the amount of heat wasted. In response, over the past decade, the Chinese government has invested large amounts of resources in an effort to promote energy conservation with heating systems by trying to change the fee method based on floor space to amount of heat used, but with little effect. The major issues related to reform with the heat-metering system are elaborated in this paper by comparing the pros and cons of several metering methods. Firstly, room temperatures are unable to be effectively adjusted using the current methods, meaning that the original intention to save energy cannot be achieved. Secondly, current heat-metering methods are not acceptable to users, which creates its own problems. Heat metering based on households in apartment buildings, the primary living space for Chinese people, causes two problems: the energy consumed by households located at the top or at the corner of buildings is two to three times higher than households located elsewhere within the building; heating fees may increase by 20–30% if surrounding households are not heated. Current metering methods are unable to effectively resolve these two problems, therefore, they are not accepted. To overcome these difficulties, a proper metering and charging method must be developed which is both acceptable to users and able to guarantee good room temperature control at the same time. To achieve this goal, this paper presents a new method: the total heating fee of a building is allocated according to the accumulated on-time as well as the floor space of each household. Not only can this new method control the user behavior of opening windows or setting the starting point too high, but also resolve problems caused by location and heat transfer between households. It is also effective in promoting energy saving by users and appears to be acceptable to users. Survey results show that it is acceptable to a large number of users. It seems that this is the most practical way to reform the current methods for heat metering based on household use. [Copyright &y& Elsevier]

Abstract: There are many kinds of methods to estimate the energy requirement or fuel consumption in the optimal design and minimize the life cost of a building. The bin method is one of the most popular ways to estimate the energy performance of a building, which is based on the hourly-based outdoor dry-bulb temperatures of all days in a whole year. There is lack of information about the bin weather data in China. In this paper, the ambient temperature bin data for 26 cities in China are generated. Based on the method used in this paper, the bin data can be calculated with the long-term daily weather record or TMY weather data, the deviation between them is acceptable. The bin data given in this paper may have the positive impact on building energy conservation in China. [Copyright &y& Elsevier]

Renewable energy consumption has a strong driving force for promoting energy conservation and emission reduction, and is a new way to achieve clean and low-carbon development. Based on this, this paper uses the data of renewable energy consumption, carbon productivity, GDP, population, energy efficiency and technological innovation of 30 provinces in China from 2011 to 2020, and empirically analyzes the impact of renewable energy consumption on carbon productivity in 30 provinces in China, using STIRPAT model, comprehensively considers spatial horizontally and temporal vertically dimension. The empirical results show that: (1) China's carbon productivity shows a significant spatial spillover effect, its impact can spill over to adjacent areas within 1000 km; (2) China's renewable energy power consumption plays a significant role in promoting the improvement of carbon productivity. (3) Renewable energy consumption in the western region plays the most important role in driving carbon productivity. Finally, according to the temporal and spatial relationship between renewable energy consumption and carbon productivity in different regions, we provide specific regional policy suggestions. • The STIRPAT model is employed to explore temporal and spatial impact, while it considers sub regions. • Spatialy, the impact can spill over to adjacent areas within 1000km. Temporally, the impact fluctuates and rises. • The positive role of renewable energy consumption is found in China's western region. [ABSTRACT FROM AUTHOR]

The rapid development of the magnesia refractory industry has caused serious problems of resource and energy waste and environmental pollution. Cleaner Production and Cleaner Production Audit are considered effective tools for energy conservation and emission reduction in the industry. This study presents an application of cleaner production and cleaner production audit in a typical large-scale magnesia raw material production plant in Liaoning, China and the results of their implementation. Through the 7 steps of a cleaner production audit (planning and organization, pre-assessment, assessment, option generation and screening, feasibility analysis, implementation, and maintenance of cleaner production), the resource and energy consumption and environmental emissions of the enterprise are investigated, the key auditing procedures are identified, and the cleaner production opportunities are analyzed. 28 cleaner production options, including raw material and energy substitution, technology improvement, facility maintenance and updates, process optimization and control, waste reutilization, management, and staff training and motivation, have been developed and implemented in a feasible way. After complete implementation of these options, great environmental and economic benefits are expected to be achieved: increased utilization of magnesite tailing powder by 281,000 t per year; annual savings of 25,000 t of magnesite ore; savings of 384,000 kW h of electricity; a 21.7% reduction in magnesite consumption per ton of FM product; improvement of the wastewater utilization rate from 70% to 100%; the removal of dust, SO 2 and NO x emissions produced by burning coal or producer gas; savings of 1.066 million USD per year. The results demonstrate that implementing cleaner production can not only bring huge environmental benefits, but also significant economic gains. Moreover, factory staff have recognized the benefits that cleaner production can bring to the plant, and plan to continue the process. Since there are few studies on the application of cleaner production in the magnesia refractory industry, this paper provides scientific guidelines for its implementation in other similar enterprises, and a theoretical and practical basis for promoting the sustainable development of the industry. [ABSTRACT FROM AUTHOR]

Following several decades of rapid economic growth, China has become the largest energy consumer and the greatest emitter of CO 2 in the world. Given the complex development situation faced by contemporary China, Chinese policymakers now confront the dual challenge of reducing energy use while continuing to foster economic growth. This study posits that a better understanding of the relationship between economic growth, energy consumption, and CO 2 emissions is necessary, in order for the Chinese government to develop the energy saving and emission reduction strategies for addressing the impacts of climate change. This paper investigates the cointegrating, temporally dynamic, and casual relationships that exist between economic growth, energy consumption, and CO 2 emissions in China, using data for the period 1990–2012. The study develops a comprehensive conceptual framework in order to perform this analysis. The results of cointegration tests suggest the existence of long-run cointegrating relationship among the variables, albeit with short dynamic adjustment mechanisms, indicating that the proportion of disequilibrium errors that can be adjusted in the next period will account for only a fraction of the changes. Further, impulse response analysis (which describes the reaction of any variable as a function of time in response to external shocks) found that the impact of a shock in CO 2 emissions on economic growth or energy consumption was only marginally significant. Finally, Granger casual relationships were found to exist between economic growth, energy consumption, and CO 2 emissions; specifically, a bi-directional causal relationship between economic growth and energy consumption was identified, and a unidirectional causal relationship was found to exist from energy consumption to CO 2 emissions. The findings have significant implications for both academics and practitioners, warning of the need to develop and implement long-term energy and economic policies in order to effectively address greenhouse effects in China, thereby setting the nation on a low-carbon growth path. [ABSTRACT FROM AUTHOR]

The rapid growth of energy consumption in China has led to increased emissions of CO 2 . As a response, the Chinese government has proposed a series of carbon mitigation strategies, such as switching the production structure and implementing energy-saving and emission–reduction technologies in energy-intensive sectors. In this paper, an integrated assessment approach was developed by combining the Stock-based model, the China-TIMES model and the co-benefits analysis model. The approach was applied to China’s steel sector to simulate the trends of energy consumption and air emissions (CO 2 , SO 2 , NO x , and PM 10 ) during 2010–2050, under a reference scenario and three alternative carbon mitigation scenarios. The model quantified the air emission reductions, water conservation, and associated co-benefits during the study period. The modeling results show that by switching the production structure and implementing energy-saving and emission–reduction technologies, China’s steel sector can achieve significant co-benefits of carbon mitigation, water conservation, averted mortality and averted morbidity. Despite certain limitations and uncertainties associated with the elements of the integrated assessment approach, the results demonstrate that substantial social benefits and health effects could be realized through carbon mitigation strategies in China’s steel sector. [ABSTRACT FROM AUTHOR]

Starting with the 11th Five-Year Plan (FYP) and continuing in the 12th FYP, quantitative and binding targets have been set for energy-efficiency improvement in China. Drawing on international experience in burden-sharing on climate change, this paper presents a framework for provincial-level disaggregation of energy-saving targets in China. Based on principles of equity and efficiency, four scenarios have been established by weighting different choice preferences of responsibility, capacity, and potential. In addition, nonlinear and linear allocation models have been developed by considering or ignoring marginal energy-saving cost. When this framework was applied to the disaggregation of the national energy saving target of 16% during the 12th FYP, the results show that the final allocation schemes are largely determined by the policy maker's choice preferences. The extreme reduction target of 37.26% fell to Shanghai under responsibility preferring (RP) using the linear allocation method, while the capability preferring (CP) scenario considering marginal energy-saving cost is the closest to the actual scheme accepted by the 30 provinces. Development of such a framework may serve as a feasible policy instrument to help China achieve its conservation targets in a cost-effective way and in accordance with its regional development strategies. [ABSTRACT FROM AUTHOR]

China is currently experiencing rapid economic growth as a result of industrialization and urbanization. In the next 20 years, China's energy demand will increase substantially, and energy conservation will become imperative for the country's low carbon economic transformation. Since 1998, China's chemical fiber production has ranked first in the world. In 2011, China's chemical fiber production accounted for about 70% of the world's total output. Therefore, energy saving is important for China's chemical fiber industry, and can provide immense benefits, and hence the need for thorough and intense research. In this paper, the co-integration method is used to test the relationship between energy consumption and its influencing factors such as GDP, energy prices, population and R&D expenditures. The results show that there is a long-term relationship between the variables. Based on this, we estimate energy demand and predict the energy-saving potential for the industry under different scenarios. We apply the Monte Carlo simulation method to verify the reliability of the prediction. Scenario analysis is adopted to predict energy demand and energy saving in the industry under different scenarios. Finally, we propose some policy suggestions on energy saving based on the research. [ABSTRACT FROM AUTHOR]

In this study, the feasibility of constructing multi-energy complementary systems in rural areas of China is examined. First, the rural energy structure and energy utilization in the eastern, central, and western regions of China are analyzed, and the development and utilization modes of multi-energy complementary systems in different regions are evaluated based on the differences in the resource endowment in different regions. Second, the input-output status of the multi-energy complementary mode in different regions is analyzed. Then, based on the assumption of technical feasibility, the feasibility of the multi-energy complementary system is analyzed in terms of various dimensions, such as economic, energy conservation, environmental protection, and social benefit. Finally, an empirical study is conducted by comparing the proposed multi-energy complementary system with traditional energy supply system. The results show that the development of a multi-energy complementary system in each region is feasible from the perspective of multiple dimensions to reduce environmental pollution, create employment opportunities, and improve the economy. Moreover, the system can significantly reduce the peak-valley difference and improve energy efficiency. • This paper analyzes the differences in energy structure in the different regions of China. • Construct a multi-energy complementary system in each region. • Demonstrate the feasibility of constructing a multi-energy complementary system. [ABSTRACT FROM AUTHOR]

Electric power industry is a typical industry with high energy consumption and high emissions in China. To relieve the increasing environmental pressures and promote the sustainable development of China’s economy and society, it is urgent to take actions to reduce energy consumption and pollution emissions of China’s electric power industry. In this paper, we first present an overview of the development status of China’s electric power industry, including the total power generating capacity and proportions of different power generation methods, the development of renewable energy power generation, as well as the average utilization hours of different power generation equipment. Then, the development of energy conservation and emissions reduction of China’s electric power industry is studied. The indicators of energy conservation include coal consumption for power supply, power consumption rate of power plants and comprehensive line loss rate; while the contents of emissions reduction include desulfurization, emissions control and the comprehensive utilization of solid waste. Finally, suggestions in five aspects to promote energy conservation and emissions reduction of China’s electric power industry are presented. The five suggestions are improving power generation technologies, expanding renewable energy power generation, optimizing power generation process, strengthening monitoring and regulation, and promoting power generation rights and emissions trading. [ABSTRACT FROM AUTHOR]

With low energy intensity and great potential for growth, the commercial sector has become one of the key sectors for energy conservation and emission reduction in the context of China's rapid urbanization process. Based on the EIA (Energy Information Administration) statistical methods, this paper calculates the energy consumption of China's commercial sector from 1981 to 2012, specifies the determinants of commercial energy demand, forecasts future energy consumption and estimates the energy conservation potentials using the Johansen co-integration methodology. The results indicate: (i) GDP (Gross Domestic Product) and urbanization have positive effects on the energy consumption of the commercial sector while labor productivity and energy price contribute to reduction in the sector's energy consumption. (ii) Under the basic scenario, energy consumption of the commercial sector will be 317.34 and 469.84 Mtce (million tons of coal equivalent) in 2015 and 2020 respectively. (iii) Under the moderate and advanced scenario, about 187.00 and 531.45 Mtce respectively of the energy consumption of the commercial sector can be conserved from 2013 to 2020. The findings have important implications for policy-makers to enact energy-saving policies. [ABSTRACT FROM AUTHOR]

The electrolytic aluminium industry is a typical energy-intensive industry, and one of the six largest energy-consuming industries in China. The energy consumption of China’s electrolytic aluminium industry (CEAI) in 2011 accounted for 0.91% of China’s total energy consumption and 22.7% of the total energy consumption of the non-ferrous metal industry. In consideration of the bulk of energy used in the smelting process in the non-ferrous metal industry, CEAI assumes the corresponding obligation of energy conservation and emissions reduction. Using the co-integration method, the long-term equilibrium relationship among the energy consumption of CEAI, output, electricity price and average enterprise scale is obtained. Thereafter the Monte-Carlo simulation is used to forecast energy consumption and energy conservation potential of CEAI under different energy conservation scenarios, and conduct risk analysis. The research shows that increase in the price of electricity and enterprise scale is helpful to reducing the total energy consumption of CEAI. The future energy conservation potential of CEAI is large. According to the result of the analysis the energy conservation potential of CEAI in 2020 will reach 30.51 Mtce under the moderate energy conservation scenario and 49.93 Mtce under the advanced energy conservation scenario. Some corresponding policy suggestions are recommended in this paper. [ABSTRACT FROM AUTHOR]