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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]

The reduction of carbon emissions in the power industry will play a vital role in global decarbonization. The power industry has three main strategies to achieve this reduction in emissions: to implement lean marketing strategies that effectively target users of power and encourage them to adopt decarbonizing technologies and services; to optimize the efficiency of these users of power; and to improve the efficiency of renewable energy sources. This paper establishes a comprehensive evaluation system of indexed data from power industry customers for the development of lean marketing strategies. This system evaluates indexes derived from customer data on renewable energy sources, carbon emissions, energy efficiency, and customer credit. It adopts the DEMATEL–CRITIC combination weight assignment and VIKOR method for system evaluation and conducts simulation experiments on customer data in a region of Northeastern China to give an example of how this method could be applied in practice to lean marketing. The results show that the evaluation system proposed in this paper can govern the lean marketing decision-making of power sales enterprises. [ABSTRACT FROM AUTHOR]

Whether renewable energy consumption is beneficial to reducing CO 2 emission intensity and carbon emissions in the context of the goal of "carbon peak and carbon neutrality" in China. To prove this conjecture, considering the spatial spillover effect of carbon dioxide, this paper adopts the spatial Dubin model for empirical analysis based on the panel data of China's 30 provinces over the period 2002–2019. This study explores the CO 2 intensity mitigation effect of China's renewable energy consumption and further investigates the mediation role of technological innovation, industrial structure upgrading and optimization, and energy efficiency in the nexus between renewable energy consumption and carbon intensity. The main findings present that: (1) China's carbon emission intensity is characterized by significant spatial correlation; (2) Renewable energy consumption can significantly reduce carbon intensity and per capita carbon emissions; (3) The mediation effect of renewable energy consumption in reducing carbon emission intensity is to promote technological innovation and industrial structure upgrading, as well as improve energy efficiency. Based on the conclusions, this paper offers several policy implications for governments to reduce CO 2 emission intensity. • The impact of renewable energy consumption on CO 2 emission intensity is explored. • Renewable energy consumption can reduce carbon emission intensity and per capita carbon emissions. • Renewable energy consumption reduces CO 2 intensity through the spatial mediation effect. [ABSTRACT FROM AUTHOR]

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

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

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]

Under the situation of global low-carbon development, the contradiction among energy consumption, economic growth, and CO2 emissions is increasingly prominent. Considering the possible two-way feedback among the three, based on the panel data of 30 regions in China from 2000 to 2017, this paper establishes a spatial Durbin model including economic growth, energy consumption equation, and CO2 emissions and studies the dynamic relationship and spatial spillover among economic growth, energy consumption, and CO2 emissions effects. The results show that the economic growth can significantly improve carbon dioxide emissions, and China's economic growth level has become a positive driving force for carbon dioxide emissions. However, economic growth will not be significantly affected by the reduction of carbon dioxide emissions. There is a two-way relationship between energy consumption (ENC) and carbon dioxide emissions (CO2). Energy consumption and carbon emissions are interrelated, which has a negative spatial spillover effect on the carbon dioxide emissions of the surrounding provinces and cities. [ABSTRACT FROM AUTHOR]

This study explores how an institutional innovation in the 20th Century – Coasean bargaining - could contribute to build a low carbon China in the 21st Century. China has surpassed all nations and become the world's largest emitter of CO 2 since 2007. A time-series analysis has revealed that crude oil and coal consumption, inter alia, are the primary factors contributing to the variations in CO 2 emissions in China. To honour China's commitments in the Paris Agreement 2015, this paper, with reference to the empirical results, estimates the impacts on various sources of energy consumption before 2030. Developed upon the Coasean bargaining framework (1960), the cap-and-trade (CAT) markets have contributed to reduce the pollutants and greenhouse gas emissions in the US and EU. This paper will illustrate how the CAT market can be complementary to administrative measures for CO 2 reduction in China. It will also discuss the institutional settings and constraints of the 7 pilot CAT markets in China, and also the national one to be rolled out in 2017. [ABSTRACT FROM AUTHOR]

The metallurgy industry plays a very important role in China's economic growth. Due to its energy concentration, the energy consumption of the industry accounts for a large proportion of China's total energy consumption, and thus contributes to carbon emissions. Whether the metallurgy industry can successfully reduce emissions is related to the future of China's carbon emissions targets. In this paper, the logarithmic mean Divisia index model is used to analyze the change in China's carbon dioxide emissions from 1991 to 2014. The empirical results show that there are three main factors affecting the carbon dioxide emissions of China's metallurgy industry. The three factors are labor productivity, energy intensity and industry size. In addition, we further analyzed the deep motivation of carbon dioxide emissions in the industry, and calculated the future emission reduction potentials. Lastly, according to the empirical results, the paper proposes policy recommendations for the future emission reduction of China's metallurgy industry. [ABSTRACT FROM AUTHOR]

Traditional energy planning methods are mostly related to newly-built area. However, in most already-built regions, the existing district energy systems (DESs) need to be ameliorated due to insufficient capacity and low efficiency. This paper investigates the methodology of expansion planning, which can offer planners a viable way to expand existing DESs. The term “expansion” aims to increase the supply capacity of the energy forms, e.g., steam, hot water and electricity, which cannot be accessed from national or urban energy supply network, and meanwhile increase energy utilization efficiency and cut CO 2 emission. Three parts of the methodology, including problem analysis in current DESs, demand side analysis and the existing DES expansion, are introduced in this paper. New concepts of load structure and evaluation system of the whole district are proposed in this methodology. A case analysis of Ningbo Hi-Tech District, China is conducted to shed light on the application of this method. [ABSTRACT FROM AUTHOR]

Accurate estimation of CO2 emissions is a prerequisite for scientific low-carbon emission policymaking. Based on 20 types of energy consumption data at the prefecture level in China, this paper re-estimates the CO2 emissions of 198 prefecture-level cities in 2016 by using the method of carbon emission coefficient. The spatial pattern and scale characteristics are analyzed, and the conclusions are as follows: (1) Overall, China's urban CO2 emissions show a certain degree of spatial separation in terms of the total amount, per capita emissions, and emission intensity. Cities with the highest CO2 emissions in China are mainly concentrated in North China, East China and Chongqing, while cities with the highest per capita CO2 emissions and emission intensity are mainly concentrated in Northwest and North China. (2) Different types of cities have different CO2 emission characteristics. Resource-based cities have a higher total amount and emission intensity; tourism and underdeveloped cities both have lower values; while super-large-sized cities and many very-large-sized cities have higher CO2 emissions, but their emission intensities are usually lower; and no obvious rules are found in other cities. (3) Spatial analysis shows that cities with higher CO2 emissions are clustered. The Beijing–Tianjin–Hebei region, the Yangtze River Delta region, Shandong Province, and Shanxi–Henan–Anhui resource-producing areas are the agglomeration areas of high-emission cities. (4) Scale analysis shows that the characteristics of CO2 emissions at different scales are different. Provincial-level research can help to identify the environmental impact and total effect of carbon emissions, while urban-scale research is helpful to explore the diversity and phases of cities. Finally, based on the main conclusions of this study, the corresponding urban low-carbon policy implications are drawn. [ABSTRACT FROM AUTHOR]

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

Abstract: With increasing attention on energy shortage and global warming, bioenergy is a promising alternative energy to mitigate CO 2 emissions. Despite the environmental friendly potential, a certain quantity of bioenergy-related CO 2 is still emitted in China. This paper investigates the temporal dynamics of bioenergy-related CO 2 emissions in 2000–2010 in China, and explores the underlying influence factors based on logarithmic mean Divisia index (LMDI). Then the core results are verified with a GIS-based approach from a spacial perspective. The results show that four impact factors: emission intensity, energy structure, energy efficiency and economic development have different impacts on bioenergy-related CO 2 emissions, of which economic development is the major factor contributing to its increase, while energy efficiency is the major determinant for the decline. Per capita bioenergy-related CO 2 emissions in different areas are verified in accordance with either economic development factor or energy efficiency factor to some extent. To achieve the dual purpose of sustainable development and CO 2 emissions reduction, this paper provides a practical policy framework for rural bioenergy and economic development. [ABSTRACT FROM AUTHOR]

Abstract As a significant basic industry for the national economic development, coal chemical industry is one of the main contributors to energy consumption and CO 2 emission. In this paper, the CO 2 emission in the time series of 2020 and 2030 was calculated and the Logarithmic Mean Divisia Index (LMDI) method was employed to explore the driving forces of CO 2 emission change. According to the industry development, the CO 2 emission in 2020 and 2030 was tentatively predicted. The results show that China's coal chemical industry has experienced a significant increase in CO 2 emission, from 177.87 million ton CO 2 (MtCO 2) to 427.19 MtCO 2 in 2005–2015, with an average annual growth rate of 9.16%. Currently, the coal-to-ammonia industry is the largest contributor. According to the decomposition analysis, the economic growth and energy intensity are the two positive factors and the industry structure is a negative factor to carbon emission change. In 2020, the CO 2 emission will be 617.34 MtCO 2 under slow development scenario and 759.69 MtCO 2 under rapid development scenario. In 2030, the CO 2 emission will reach 1041.90 MtCO 2 and 1440.13 MtCO 2 under slow and fast development scenarios, respectively. The coal-to-olefins industry will take the place of coal-to-ammonia and turn to be the largest one in 2020 and 2030 if no CO 2 capture, utilization and storage (CCUS) technologies are adopted. It is probable that the contribution from coal-to-methanol will also play important role for CO 2 emission due to its rapid development. In addition, by 2030, if coal-to-natural gas industry develops as planned, its CO 2 emission will significantly increase, which has the potential to be equivalent to that of olefins industry. Highlights • The CO 2 emission evolution trend in China's coal chemical industry is analyzed. • The major driving factors of CO 2 emission change are identified and the effect sizes of various factors are evaluated. • The CO 2 emission in 2020 and 2030 is forecasted. • Policy implications to policymakers are provided. [ABSTRACT FROM AUTHOR]

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

Abstract 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]

Reliable energy statistics serve as the foundation and starting point for understanding the climate policies of any country. As the most comprehensive sources of energy data for China, China Energy Statistics Yearbooks (ESY), published by the National Bureau of Statistics (NBS), underwent three major revisions since 2005. This paper analyzes how these three major revisions correspond to data on China's energy use from 1996 to 2012, and theirs impacts on CO 2 emissions, emission intensity and the share of non-fossil energy in total energy consumption, which are key indicators of China's climate policies. Some notable changes include CO 2 emissions for 2012, which increased by 594 Million tons – a figure equivalent to South Korea's annual emissions, which implies that China's emissions at peak level will be higher than previous estimation. Meanwhile, revised emission intensity data show a higher amount and lower decreasing rate, which means that China's achievements in decreasing emission intensity during 2005–2012 have been overestimated, while future difficulties for achieving the goal of 40–45% reduction will be greater. On the share of non-fossil fuel energy in China's total energy mix, the adjustments increased the indicator by 1.26%, reflecting the fact that China's effort in developing non-fossil energy had been underestimated. Discrepancies in reported scattered coal in different statistics versions are the main contributors to these changes. To further enhance the reliability of its energy statistics, and thereby its climate policies, China should remove incentives for misreporting through legal means, and make the technical system for data collection more comprehensive and accurate, with particular emphasis on scattered coal. [ABSTRACT FROM AUTHOR]

Rapid development of agriculture mechanization and the agro–industry in China (considered as a large agricultural country) has led to a substantial increase in energy consumption and CO 2 emissions. Majority of existing studies usually explore the driving forces of the sector's CO 2 emissions using the averaging method. However, data distribution of economic variables is often non–normal, with the tail having hidden important information. According to the average annual CO 2 emissions, this paper divides China's 30 provinces into six quantile grades, and uses the quantile regression method to investigate the driving forces of CO 2 emissions under high, medium, and low emission levels. The results show that the effects of economic growth on CO 2 emissions in the upper 90th and 75th–90th quantile provinces are higher than in the 50th–75th, 25th–50th, 10th–25th and lower 10th quantile provinces due to the differences in fixed–asset investment and agricultural processing. The impact of energy efficiency in the upper 90th, 75th–90th, and 50th–75th quantile provinces are stronger than those in the 25th–50th, 10th–25th, and lower 10th quantile provinces because of the huge difference in R&D funding and R&D personnel investments. The effect of urbanization in the higher 90th quantile provinces is higher than in the other quantile provinces, owing to the differences in the level of agricultural mechanization and human capital accumulation. Similarly, financial capacity has the largest impact on CO 2 emissions in the upper 90th quantile provinces in all quantile provinces. However, the impact of industrialization in the upper 90th quantile provinces is lower than in other quantile provinces. Thus, the heterogeneous effects of the driving forces should be taken into consideration when discussing CO 2 emissions reduction in China's agriculture sector. [ABSTRACT FROM AUTHOR]

Highlights • The input–output model and ecological network analysis (ENA) are integrated. • The control and dependence conditions of economic sectors in China are analyzed. • The key regions and sectors for carbon mitigation of China are identified. Abstract In this paper, multi-regional input–output analysis (MRIO) and ecological network analysis (ENA) are combined to assess carbon flows within China and identify key regions and sectors in the context of spatial heterogeneity for effective carbon mitigation. An interregional carbon network model is established by articulating the directions and magnitudes of carbon flows based on MRIO. ENA is then used to unveil indirect carbon flows and mutual relationships among regions. The results show that the northwest is the largest controller for most regions in China. Most carbon emissions in the rest of China are induced by the east’s final demand and substantial consumption. In addition, at sectoral level, the control and dependence abilities vary by region in China. This study provides an integrated framework to investigate interregional carbon emission structure, identify efficient pathways for coordinated emission mitigation, and reduce global carbon inequality across regions. [ABSTRACT FROM AUTHOR]

China consumes more energy and emits more carbon dioxide than any other country. The building sector accounts for nearly 1/3 of the total national energy consumption in China; thus, it is critical to find a solution for improving buildings’ energy efficiency. Under the market-oriented mechanism, constrained by the energy performance contracting (EPC) mode, energy service companies (ESCOs) play an important role in improving energy efficiency for high-energy-consumption industries, including the building sector. The aim of this study is to determine the strategy for boosting the building ESCO industry. By conducting a strength, weakness, opportunity, and threat (SWOT) analysis, this paper presented the status of the building ESCO industry in China and proposed alternative strategies. By utilizing a conventional multi-criteria decision-making method, namely, the Analytic Network Process (ANP), this study provides a quantitative basis to analytically determine the ranking of the factors in SWOT analysis and select the best strategy to promote the development of the building ESCO industry. The results showed that the ANP-SWOT is a viable and highly capable methodology that provides invaluable insights for strategic management decisions in the building ESCO industry, and a set of strategies for promoting ESCO development in the building sector were proposed based on this approach. [ABSTRACT FROM AUTHOR]

High-Carbon Consumption Behavior (HCCB) of urban residents is one of the main obstacles to the goals of low carbon development in China with the rapid development of the national economy. Among all the uptrend influences, the one caused by conspicuous consumption is worth more attention. In this paper, a structural equation model was applied to analyze the impact path of conspicuous consumption motivation on HCCB. Multiple group analysis was then used to test the moderating effect of individual face conscious and demographics on the impact. Our data originated from a social study of Xuzhou, Jiangsu province, China (n = 351). The results indicated four leading aspects. First, the raising habitual HCCB is mainly affected by three points, materialistic hedonism, interpersonal mediation and social status demonstration, and the influence is reduced in successively. While communication of belonging to/dissociation from a group and ostentation have little effect on habitual HCCB. The second, purchased HCCB of residents is mainly impacted positively by materialistic hedonism, and other factors have weak influence on it. The third, face consciousness has a significant moderating effect on the relationship between residents’ conspicuous consumption motivation and HCCB. People with strong face consciousness are more affected by the social status demonstration and interpersonal mediation; those with weak face consciousness are only driven by material hedonism. The last, gender, marital status, age, education level, and household monthly disposable income have significant moderating effects on the relationship. Among them, the HCCB from males, young people, married persons, highly educated people, and higher income groups is more affected by materialistic hedonism, interpersonal mediation, and social status demonstration, while from females with lower education, and lower income groups is more likely to be driven by social status demonstration. [ABSTRACT FROM AUTHOR]

The bottlenecks in developing high-efficiency ultra-super critical (USC) coal power technology are analyzed within the context of the growing pressure on the coal power industry to reduce carbon dioxide (CO 2 ) emissions. To meet these demands, further improving the annual average operating efficiency of coal power is essential. A cross-compound double reheat unit design characterized by an elevated and conventional turbine layout is proposed in this paper. This new design can greatly shorten the length of expensive high-temperature piping required, significantly cut piping costs as well as reducing pressure drops and heat losses, resulting in a much higher efficiency and performance-price ratio than conventional double reheat design. The engineering study demonstrates the feasibility and advantages of this design. Now this new design is being implemented on Pingshan Phase II Project as a demonstration coal power unit in China. Despite the new turbine arrangement, Pingshan Phase II Project also adopts a series of energy saving, environmental protection, efficiency preservation and safety technologies, of which some have already gained success in Shanghai Waigaoqiao No. 3 Power Plant. Based on the new design and further optimization, the unit net efficiency of Pingshan Phase II is expected to achieve 49.8% under rated conditions on a lower heating value (LHV) basis. Combined with a series of innovative technologies that can keep the efficiency from decreasing under operational conditions, the annual average net efficiency can achieve 48.8% on LHV basis. This efficiency level is high enough to meet the strict CO 2 emission standard proposed by United States Environment Protection Agency (U.S. EPA) based on the Pittsburgh #8 bituminous coal, showing significant potential for reducing CO 2 emissions. A series of low-energy-consumption and even energy-saving pollutants removal technologies are also be applied on this project to harmonize high efficiency and low emissions. [ABSTRACT FROM AUTHOR]

The Chinese government committed to reduce its national CO 2 emissions intensity by 40–45% until 2020 in response to climate change. This paper quantitatively evaluates the performance of CO 2 emissions reduction over the period 2005–2020 from the historical and prospective perspectives by using a combination of decomposition analysis and scenario analysis, aiming to provide suggestions about how to achieve the target in key emissions reduction fields. Unlike traditional index decomposition methods, this paper incorporates the total energy conversion efficiency effect into the model, and further decomposes it into a final energy mix effect and a final energy conversion efficiency effect by a multilevel decomposition procedure, allowing to measure the contributions of primary energy structure low-carbonization, the final energy mix electrification, and the energy conversion efficiency improvement. The results show that the carbon intensity could decline over the period 2005–2020 by 47.8%, 50.9%, 48.0%, 44.5% and 47.5% in the Business as Usual, S1, S2, S3 and S4 scenarios, respectively. This shows that the 40–45% target is very likely to be achieved. The final energy intensity effect is always the most important driving factor, causing carbon intensity to decrease by 24.0% and 22.1%, again respectively, from 2005–2012 to 2012–2020. Moreover, the energy conversion effect was another major driver during 2005–2012. The Chinese government needs to make more efforts to adjust the industrial structure, which could cause carbon intensity to decrease by 3.6% during 2012–2020, and to adjust the primary energy mix, which could cause carbon intensity to decrease by 7.1% during 2012–2020. [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]

Emerging economies like China, India, and Mexico are becoming the world's manufacturing leaders through the engagement in offshoring production activities. In achieving this status, however, they have met with difficult environmental issues. This paper features an analysis of industry-level panel data to examine the link between different offshoring tasks in China and carbon dioxide emissions. Through this analysis, the environmental effects of offshored production are addressed. Specifically an input–output model is presented, thereby quantifying offshored production tasks in China. The results show that iron and steel, nonferrous metals (IS) and chemicals (CH) generate the most carbon dioxide during production of processed goods. Additionally, electrical machinery (EM) and general machinery (GM) generate a higher amount of carbon dioxide during production of parts and components. The results also show that those industries characterized by higher energy consumption have higher carbon dioxide (CO 2 ) emissions induced by offshoring. Given these results, it seems that any solutions geared towards reducing the energy consumption of entire manufacturing industries would be useful. Furthermore, the results of the analyses presented here indicate that China would be responsible for working with developed countries to reduce carbon dioxide emissions through cooperative environmental regulation. A globalization perspective is adopted to offer unique insight into the environmental issues faced by China. The results of this paper would provide quantified, actionable information for formulating practical industrial policies geared towards reducing carbon dioxide leakage. [ABSTRACT FROM AUTHOR]

The surge in energy consumption and CO 2 (carbon dioxide) emissions is exacerbating global warming. The Chinese government has promised to reduce CO 2 emission by 60%–65% per unit of GDP over the 2005 level by around 2030. Analyzing the factors influencing CO 2 emissions is one of the key aspects involved in effectively reducing greenhouse gas emissions. In this paper, we add climatic factors based on socio-economic factors, and adopt the extended STIRPAT model to investigate the mechanism driving emissions by the co-action of natural and socio-economic factors. The results show that the 1995–2014 emissions in China's Zhejiang province had an upward trend with growth rates varying between intermediate periods. The order of the factors' elasticity coefficients is urbanization rate (0.181) > GDP per capita (0.180) > population (0.177) > energy intensity (0.170) > trade openness (0.170) > cooling degree days (0.127) > mean temperature anomaly (0.116). Economic development and urbanization were the main factors promoting CO 2 emissions in 1996–1999, while economic development and foreign trade were the main factors in 2000–2014. Policy makers should pay more attention to keeping a healthy pace of economic development, introducing more low energy consumption and low pollution enterprises and encouraging technological innovation. Improving the quality of urbanization, guiding a sustainable lifestyle, adjusting the structure of foreign trade and curbing energy intensity are also expected to reduce emissions. [ABSTRACT FROM AUTHOR]

This paper explores the optimization scheme of carbon trading in China based on a novel energy-saving and emission-reduction (ESER) system with carbon price constraints. With the aid of nonlinear dynamics theory, the dynamics behavior of the novel system is discussed. Genetic algorithm and back propagation neural network is used to identify the quantitative coefficients according to the statistical data of the second period in European Union (EU). Taking the actual situation in EU for instance, the variables which are sensitive to carbon trading are detailedly researched. Enlightened by the EU’s experience, an optimal road of China ’ s carbon trading is put forward. The results show that carbon emissions could be controlled by carbon trading. The investment to carbon trading hampers economic growth in the near future, and ESER technical progress is negatively correlated with carbon trading in the long run. Demand and supply relationship is closely related to carbon price, both are the important issues in carbon trading system. Excessive government control and extortionate carbon price will deliver the opposite effect and even fatal influence on carbon trading system. [ABSTRACT FROM AUTHOR]

The key distinction between production-based and consumption-based accounting lies in the way in which trade-embodied emissions are allocated between producer and consumer regions. Yet, these two regions are not necessarily directly connected to each other in supply chains, due to spatial production fragmentation. To better understand the link from the production-based to the consumption-based regional carbon inventories, this paper defines the economic length of carbon transfer (ELCT) as the number of administrative border-crossing involved in the influence process of a region’s final demand on the carbon emissions of another region. Using a multi-regional input-output analysis framework for China, we propose an approach to calculating the ELCT related to a region’s production or demand for domestic consumption or international export. We find that the average ELCT in 2010 is 1.34 and that more than a quarter of interregional carbon transfer crosses provincial borders twice or more. The provincial and sectoral analysis of ELCT reveals that spatial production fragmentation is an important challenge to be conquered for successful implementation of consumption-based climate regulations. [ABSTRACT FROM AUTHOR]

This paper proposes an approach to calculate the time series of cumulative carbon dioxide (CO 2 ) emissions between 1995 and 2014 based on industrial energy consumption data in three Eastern China jurisdictions in Shanghai, Jiangsu and Zhejiang during these two decades. Using the Hodrick-Prescott filter, the fluctuation components of the cumulative CO 2 -emission time-series data in the three provinces are obtained. Subsequently, a grey correlation-based change-point search algorithm is used to determine change-points in these data. Additionally, the CO 2 -emission time-series is divided into stages based on the change-points. The cycle characteristics of national energy policies, laws, and regulations are compared with those of the cumulative CO 2 -emission cycle of the three provinces to analyse the impact of energy policies on CO 2 emissions. This study shows that, although the industrial structure and trends in the CO 2 emission time-series data of the three provinces are different, their cumulative CO 2 -emission cycle remains the same from 1995 to 2014. The variation characteristics of the cumulative CO 2 emissions for each cycle during this period are well aligned with the stage characteristics of energy policies, laws, and regulations, indicating that energy policies play a consistent role in regulating such emissions. This study examines low-carbon production and sustainable energy development, and offers suggestions for issuing and perfecting energy policies, laws, and regulations, considering the indicators of energy consumption and CO 2 emissions. [ABSTRACT FROM AUTHOR]

The aim of this research is to examine the link between CO 2 emissions, hydroelectricity consumption, urbanisation and real GDP in China and India during the period of 1965–2013. The long-run cointegration is investigated by the autoregressive distributed lag (ARDL) bounds testing approach, which is augmented with structural breaks. We employ the ARDL cointegration test to establish long run relationship in the variables. Furthermore, we use the ARDL to show that real GDP and urbanisation have long-run positive impact on emission, while hydroelectricity consumption exerts long-run negative impact on emission in both countries. The results support the existence of environmental Kuznets curve (EKC) hypothesis in China and India. Besides, the paper assesses the causal link between the variables by using Granger causality procedures and the results show that there is long-run bidirectional relationship between the variables in both countries. [ABSTRACT FROM AUTHOR]

As one of the largest energy consumers, the transport sector generated direct and indirect emissions which significantly affect the environment, accounting for approximately one-third of the total carbon emissions. While the major impacts are from transport energy use and emissions, very few studies attempted to examine the impacts from transport infrastructure, especially at a city or country level. This paper, taking Shenzhen in China (a fast developing megacity) as the case study, is specially designed to quantify the carbon footprint of the urban roads by using streamlined life cycle assessment method. For given years (ranged from 2004 to 2013), various activities of urban roads (e.g. newly planned road construction, maintenance of road in use, and road renovation and demolition) have been examined in this study. The results show that the total carbon footprint from urban roads in Shenzhen was 260 (±20) thousand tons CO 2 e in 2013. The major contributor was the materials use (embodied impact) from newly constructed roads, which accounts for 52.3% of the total carbon footprint, followed by the maintenance stage (24.3%). The eco-design process of road construction plays a vital role in achieving the effective carbon footprint reduction. These findings help to better understand the carbon footprint from urban roads in megacities, and provide useful inputs for policy making process in terms of identifying carbon reduction opportunities for the transport sector. In addition, the methodologies are useful for the quantification of carbon footprint in other cities of China and beyond. [ABSTRACT FROM AUTHOR]

As an effective policy instrument to reduce energy consumption and CO emissions, the effects of fuel taxation on income distribution have been the critical factor that determines whether a fuel tax could be acceptable in China. This paper estimates the distributional effects of a fuel tax on households in various income groups by using the input-output model. Results indicate that the total distributional effects of fuel taxes are moderately progressive; that is, high-income households would bear more tax burden compared to low-income households. In addition, the indirect effects are larger than the direct effects. Moreover, the Kakwani and Suits indices show that fuel excise taxes are progressive, implying that a fuel tax could improve the unfair income distribution. In order to reduce the negative impact of fuel taxes on low-income households, it is necessary for the government to design a reasonable redistribution mechanism of tax revenue or adopt compensatory measures such as the transfer payments targeted on low-income groups. [ABSTRACT FROM AUTHOR]

Accurately understanding the real situation of China’s carbon emissions at the provincial level is not only crucial for realizing carbon mitigation in China, but also of great importance for tackling climate change on a global scale. This paper uses detailed energy consumption data subdivided within each fuel type and sector-specific emission factors, to calculate both direct and indirect energy-related CO 2 emissions for China’s provinces, and offers provincially-targeted policy proposals on emission reductions. The results uncover large divergences in calculation of provincial CO 2 emissions between production-based and consumption-based accounting approaches. Considering the large amount of interprovincial CO 2 emission transfers embodied in secondary energy deployment, the consumption-based accounting performs better in reflecting the actual features and responsibilities of carbon emissions in the provinces of China. From the consumption perspective, Shandong, Hebei, Jiangsu, Inner Mongolia, Guangdong, Henan, Liaoning and Shanxi contributed to the majority of China’s carbon emission growth during the period of 1996–2013, while Xinjiang, Sichuan, Anhui, Tianjin and Hunan were playing an increasingly important role. These two groups of provinces should be regarded as the key regions for national emissions abatement. Meanwhile, the energy industry was the top sectoral contributor to CO 2 emissions growth in most provinces, while service and household sectors made increasingly significant impacts on driving up provincial emissions. Together with ongoing efforts in the energy sector, the mitigation of CO 2 emissions in service and household sectors deserves much more attention, especially in the transportation and urban household sectors. Furthermore, the temporal trends of carbon emissions in various provinces, as well as their factor and sectoral driving forces, varied greatly with each other. Therefore, each of the provinces should formulate emission reduction policies according to their own situation, and target the key driving factors and sectors of carbon emissions at the current stage or in the near future. [ABSTRACT FROM AUTHOR]

The aim of this paper is to test whether income inequality contributes to environmental degradation in China and India, where both countries are giving a great concern about the implications of their unsustainable energy consumption to the environment not only to themselves but also to the global environmental sustainability. By applying the bounds test approach to cointegration we found in both countries a long-run but not a statistically significant relationship between income inequality and CO 2 emissions both in the long-run and in the short-run. The robustness of our cointegration results is also ascertained by using three different long-run tests. Furthermore, applying the variance decomposition analysis to examine the dynamic causal relationship between the Gini coefficient of income distribution and CO 2 emissions, we found that income inequality was the least important factor in determining CO 2 emissions and that there was no causality running in any direction between CO 2 emissions and income inequality in both countries. Still income and energy consumption are the major determinants of CO 2 emissions in both countries. Nevertheless, even though the evidence is not statistically significant, in the case of China it indicates that reducing income inequality can have a positive impact on environmental quality, while in India redistributing income to improve environmental degradation may not be effective. [ABSTRACT FROM AUTHOR]

Abstract: With rapid urbanization and industrialization, China has become both the largest energy consumer and CO2 emitting country in the world. As a clean and low-carbon energy source, renewable energy is a good choice to substitute for the exhausted fossil energy. The Chinese central and local governments have made a series of policies and optimistic plans to promote a rapid development of renewable energies. China′s renewable energy development has become a key to the sustainable development of socio-economic system. Unlike most of the current studies which mainly identified the challenges regarding policies and technologies around renewable energy or performed specific analyses for a certain kind of renewable energy, this paper summarizes the spatial disparity and consistency among the major renewable energies, coal resources, energy consumption and its major influencing factors in China, and reviews the positive and negative environmental impacts of major renewable energies. Based on the geographical and environmental perspectives, this paper recommends that the Chinese government: constructs the national energy production bases according to the resource distribution; integrates different energies on the basis of their natural features and spatial consistency; adjusts the overall layout of socio-economic development consistent with renewable energies; and promotes a moderate renewable energy development to maximize the environmental benefits. [Copyright &y& Elsevier]

This paper presents a forecast and analysis of population, economic development, energy consumption and CO2 emissions variation in China in the short- and long-term steps before 2020 with 2007 as the base year. The widely applied IPAT model, which is the basis for calculations, projections, and scenarios of greenhouse gases (GHGs) reformulated as the Kaya equation, is extended to analyze and predict the relations between human activities and the environment. Four scenarios of CO2 emissions are used including business as usual (BAU), energy efficiency improvement scenario (EEI), low carbon scenario (LC) and enhanced low carbon scenario (ELC). The results show that carbon intensity will be reduced by 40–45% as scheduled and economic growth rate will be 6% in China under LC scenario by 2020. The LC scenario, as the most appropriate and the most feasible scheme for China’s low-carbon development in the future, can maximize the harmonious development of economy, society, energy and environmental systems. Assuming China's development follows the LC scenario, the paper further gives four paths of low-carbon transformation in China: technological innovation, industrial structure optimization, energy structure optimization and policy guidance. [ABSTRACT FROM AUTHOR]

Abstract: As an unconventional natural gas with the advantages of great resource potential and low carbon emissions, shale gas has currently aroused a new round of development and utilization worldwide. China’s shale gas resource is enormous and has huge potential for exploitation. However, due to the late start of exploration and development, it has not yet realized industrialization. By using the SWOT analysis method, this paper studies the internal and external development environment of Chinese shale gas, then explores shale gas development status of China from four dimensions including strengths, weaknesses, opportunities and threats. Finally, according to the combinations of SWOT matrix analysis, the paper formulates four kinds of different development strategies to provide certain references to the development of China’s shale gas industry. [Copyright &y& Elsevier]

Abstract: Environmental sustainability is a topic of increasing concern among scholars, city planners, engineers and policymakers. Electricity consumption constitutes about two-thirds of a city''s carbon emissions. In high-density Hong Kong, the building sector accounts for 89% of total electricity consumption, with commercial buildings alone accounting for 67% of the total. This paper reports the results of an in-depth case study examining how Langham Place Hotel Mongkok Hong Kong (LPHKG) has successfully reduced its CO2 emissions by implementing a range of sustainability design strategies. LPHKG is a five-star hotel situated in Mongkok – one of the most densely populated districts in the world, with an estimated 130,000 people per square kilometre. In particular, the paper discusses how the hotel, in its efforts to achieve net zero-energy, has made wise use of technologies to maximise energy consumption efficiency in its existing lighting and air-conditioning systems and in the mechanical devices of the building itself. The overall implication of LPHKG''s efforts is that, although the initial investment required for such technologies is usually large, the resulting long-term cost savings can be significant. [Copyright &y& Elsevier]

Considering the significance and importance of urban sustainability in China and China's history of rapid urbanisation and industrialisation, this paper aims to incorporate the investigation of climate change and air pollution in urban sustainability research in China through a driver-pressure-state-impact-response model. The model has 12 indices: population, enterprise, registered vehicles, energy consumption, emissions and concentrations of carbon dioxide and sulfur dioxide, land use change, annual temperature, tropical nights and reforestation were selected. It was used in the analysis of 14 cities in the Liaoning Province. The results show that the model is an effective tool for urban sustainability research, allowing for the investigation of interactions of climate change and air pollution and contributing to the body of knowledge by aiding generation of realistic and practical measures. [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]

Rapid urbanization has exerted substantial pressure on China’s energy system and contributed to climate change. To find the key drivers of urban residential energy consumption and CO 2 emissions, this paper uses an extended Stochastic Impacts by Regression on Population, Affluence and Technology (STIRPAT) model that employs city-level data to examine the influences of population scale, income level, population compactness and price on house-based residential energy consumption, energy-related CO 2 emissions and private vehicle ownership. The empirical results indicate that factors such as population scale, affluence, and population compactness can lead to increases in residential energy consumption and CO 2 emissions. In terms of transportation, income and population scale positively drive the growth of private vehicle ownership, while the fuel price negatively influences private vehicle ownership. Moreover, population scale is the most important factor in residential energy consumption and CO 2 emissions. Finally, policy recommendations are suggested for China’s urban development strategy and urban design and to encourage technology innovations that reduce residential energy consumption and CO 2 emissions. [ABSTRACT FROM AUTHOR]

Climate change which is induced from energy consumption and CO 2 emissions has got people's attention; hence, many strategies and ways are being adopted to mitigate CO 2 emissions. Energy substitution is crucial to the promotion of energy conservation and CO 2 emissions reduction. The purpose of this paper is to estimate both inter-factor and inter-fuel substitution in China's iron & steel industry during the period 1985–2011. Empirical results show several conclusions for China's iron & steel industry: (1) own-price elasticity of energy is negative, so increase in energy price will reduce energy input; (2) energy and capital, and energy and labor are substitutes, and the substitution in energy/capital is relatively stronger; (3) though coal, oil and electricity are also substitutes, the substitution effect is not so obvious because of pricing distortions in China. The driving forces of energy efficiency change are further discussed and the results show that technology progress is the key factor determining energy intensity. Therefore, market-oriented reforms in terms of energy prices, improvement in energy substitution (including inter-factor and inter-fuel substation) and promotion of energy saving technologies are important means for ensuring future energy conservation and CO 2 emissions reduction practices in China's iron & steel sector. [ABSTRACT FROM AUTHOR]

The transportation sector is one of the major driving forces of carbon emissions. Identifying the factors that affect CO 2 emissions from the transportation sector is important to build a low-carbon city. Most existing research focuses on the total effect of factors on CO 2 emissions while the indirect influence is also the driving force of CO 2 emissions. Additionally, identifying the causal relationship between variables is helpful to study the mutual acting mechanism. Therefore, this paper uses the path analysis model to estimate the direct, indirect and total influences of driving factors on transportation CO 2 emissions in Beijing and investigate the causality relationships between variables. The results show that reducing energy intensity and transportation intensity are the key factors in controlling the increase of transportation-related CO 2 emissions. Population has the greatest positive impact on CO 2 emissions because an increasing population is leading to growth in energy consumption and the number of motor vehicles. However, population could indirectly affect the energy intensity and transportation intensity to reduce carbon emissions. Moreover, motor vehicles increase CO 2 emissions due to the growth in private car population and its low energy efficiency. And, the change in the economic growth pattern somewhat inhibits the growth rate of CO 2 emissions by reducing the energy intensity and transportation intensity indirectly. To further suppress the growth of transportation carbon emissions, the following steps should be taken: appropriately improve the quality of population, control the scale of motor vehicles, develop and promote clean energy, and reduce traffic energy intensity and transportation intensity. [ABSTRACT FROM AUTHOR]

China's transport sector is facing severe energy and environmental challenges. Establishing energy efficiency standards is an essential measure to cope with these challenges. This paper comprehensively reviews the energy efficiency standards in China's road, water, aviation, railway and pipeline transport sectors. Based on the review, it is suggested that (1) the integrity of policy framework should be further improved. Energy efficiency standards-based market access qualification mechanism is quite necessary for all transport sectors, especially the aviation, railway and pipeline transport sectors, where such mechanism is absent. (2) Efforts for improving energy efficiency should be balanced among different transport sectors. Priority should be determined by considering each sector's energy consumption, the cost and potential of energy efficiency improvement, etc. Especially, the major energy-consuming sectors, such as heavy-duty vehicles should have similar priority to passenger vehicles in the overall energy efficiency improvement scheme. (3) The scientific basis for the energy efficiency standards should be enhanced. Policies should be proposed with full considerations of China's context, rather than borrowing the experiences of developed countries. Intelligence from the research community should be incorporated to ensure the rationality of the policies. [ABSTRACT FROM AUTHOR]

Abstract: Due to increasing energy scarcity and pressures from climate change, Chinese iron & steel (IS) companies have struggled to implement practices to reduce their energy consumption and CO2 emissions. However, it is not clear whether these practices can improve the environmental or economic performance of these companies. The determinants that drive or hinder the implementation of these practices are also not known. Therefore, this paper describes an empirical analysis of a total of 85 questionnaires of various IS companies across China. A regression analysis was applied in this paper to verify the relationship among CO2 reduction practices, determinants and performance as reported by the IS companies. The results show that although some CO2 reduction practices can result in significant environmental performance, their impacts on the improvement of economic performance are less clear. The paper discusses some implications regarding strategies for prompting CO2 reduction practices that have been considered during the discussion about the determinants that impact on the practices. [Copyright &y& Elsevier]

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

The coal-fired power sector is the main source of CO 2 emissions in China. This paper proposes a carbon abatement cost estimate model based on computing the emissions gap between the Chinese national energy consumption standards of units (NECS) and the units' coal consumption for per unit electricity supply (CCES). By applying the proposed model, the abatement costs of four coal-fired power generation units (600 MW USC, 1000 MW USC, 265 MW IGCC, 600 MW SC CFB) with or without Carbon capture and storage (CCS) are estimated in six combined scenarios. The results show that (1) the units' total cost would increase more than one time after conducting CCS while the unit cost of carbon emissions abatement would decrease more than 64%; (2) the 1000 MW USC unit with CCS has the largest carbon reduction potential and the lowest unit abatement cost among all units in all scenarios; (3) 265 MW IGCC unit would have no carbon reduction potential after 25 service years, and its service years may be shortened; and (4) the 256 MW IGCC and 600 MW SC CFB is the most sensitive to the average annual decline rate of NECS but the four units of installed CCS are not. [ABSTRACT FROM AUTHOR]

The use of data envelopment analysis (DEA) in China’s regional energy efficiency and carbon emission efficiency (EE&CE) assessment has received increasing attention in recent years. This paper conducted a comprehensive survey of empirical studies published in 2006–2015 on China’s regional EE&CE assessment using DEA-type models. The main features used in previous studies were identified, and then the methodological framework for deriving the EE&CE indicators as well as six widely used DEA models were introduced. These DEA models were compared and applied to measure China’s regional EE&CE in 30 provinces/regions between 1995 and 2012. The empirical study indicates that China’s regional EE&CE remained stable in the 9th Five Year Plan (1996–2000), then decreased in the 10th Five Year Plan (2000–2005), and increased a bit in the 11th Five Year Plan (2006–2010). The east region of China had the highest EE&CE while the central area had the lowest. By way of conclusion, some useful points relating to model selection are summarized from both methodological and empirical aspects. [ABSTRACT FROM AUTHOR]

China has achieved significant progress in terms of economic and social developments since implementation of reform and open policy in 1978. However, the rapid speed of economic growth in China has also resulted in high energy consumption and serious environmental problems, which hindering the sustainability of China's economic growth. This paper provides a framework for measuring eco-efficiency with CO 2 emissions in Chinese manufacturing industries. We introduce a global Malmquist-Luenberger productivity index (GMLPI) that can handle undesirable factors within Data Envelopment Analysis (DEA). This study suggested after regulations imposed by the Chinese government, in the last stage of the analysis, i.e. during 2011–2012, the contemporaneous frontier shifts towards the global technology frontier in the direction of more desirable outputs and less undesirable outputs, i.e. producing less CO 2 emissions, but the GMLPI drops slightly. This is an indication that the Chinese government needs to implement more policy regulations in order to maintain productivity index while reducing CO 2 emissions. [ABSTRACT FROM AUTHOR]