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• Carbon emissions from energy consumption of 282 prefecture-level cities in China were calculated. • A new method for calculating carbon emission factors for electricity is proposed. • Extending the Atkinson Index to the application of Carbon Fairness. • Measured the inequality and fairness indicators of carbon emissions from energy consumption at the prefecture-level city level in China. This paper focuses on the conceptualization and quantification of carbon emission inequality and fairness from energy consumption. In order to more accurately measure the carbon emissions generated by electricity consumption in each city, we firstly propose a new method for calculating the carbon emission factor for electricity, and calculates the carbon emissions from energy consumption in 282 prefecture-level cities in China from 2003 to 2019. Through the application of the Theil-Kaya decomposition mechanism and the improved Atkinson index, we conducted an in-depth study of the carbon emission inequality and fairness indicators from energy consumption. The results show that (1) Although China's overall inequality has declined, it remains significant in the western region, with its inequality indicator fluctuating from 0.548 in 2003 to 0.683 in 2019.(2) The decomposition of the drivers of inequality indicators shows that the contribution of GDP per capita to inequality is increasingly being replaced by energy intensity and the energy carbon emission factor, with energy intensity emerging as the main driver, contributing more than 40% to inequality in 2019, both overall and in the three regions.(3) The results for the fairness indicator, on the other hand, show a certain degree of divergence. Further Dynamic Time Warping fitting analysis shows that regardless of how the public's sensitivity to carbon emissions varies, the change trends of the fairness and inequality indicators for carbon emissions in the eastern region show a high degree of convergence, even in the two most extreme cases. The fit is poorest in the western region, but improves significantly if public's sensitivity to carbon emissions increases. (4)To sum up, some policies that are consistent with the context of the times, such as the East-West regional counterparts and the construction of a new type of power system, are worthy of priority consideration by the Government. [ABSTRACT FROM AUTHOR]

• The high-quality development index is introduced into STIRPAT model. • The average yield of ecological footprint is updated. • High-quality development can effectively reduce the increase of ecological footprint. • The improvement of population quality helps ease pressure on the environment. • Lower energy consumption intensity helps improve ecological quality. It is urgent to coordinate the development of economy and environment under the "dual carbon" goal. As China's new development stage and mode, high-quality development takes into account both the speed and quality of economic, providing the possibility of achieving a "win-win" situation for the economy and the environment. In order to test the practical impact of high-quality development on ecological, based on the STIRPAT model, this paper introduces high-quality development index instead of per capita GDP, so as to measure the current economic situation in China, and explore the relationship between high-quality development and ecological footprint, and demonstrates the feasibility from theory and practice. At the same time, it pays attention to the complex effects of population and technology on environmental quality. The results show that the contradiction between economy and ecology still exists in China. The ecological footprint index of 30 provinces in the past 21 years has increased as a whole, and the fworst ecological footprint has concentrated in the Yellow River basin. But since 2012, the growth of the footprint has slowed. The slow down time and low value region of ecological footprint were observed, and it was found that they overlapped with the proposed time and the high value area of high-quality development. The level of high-quality development in China has also continued to rise, with regional differences but gradually narrowing. Among them, green development and shared development contribute more to the improvement of high-quality development level. Compared with the traditional economic development mode, high-quality development can reduce the increase of ecological footprint, and the longer the time, the smaller the increase, more conducive to long-term sustainable development. In addition, population and technology factors are also profoundly affecting China's ecological pattern. The increase in population size and population density, as well as the increase in the proportion of coal-based energy consumption structure, will lead to increased environmental pressure. The improvement of population quality and the reduction of energy consumption intensity will help alleviate ecological pressure. The research is helpful to provide policy guidance and path combination reference for China's sustainable development, and also provide new ideas for the global coordination of the relationship between economy and environment. [ABSTRACT FROM AUTHOR]

This paper combines the concept of Ecological Footprint (EF) with the framework of total-factor energy efficiency to develop a new index of total-factor ecology efficiency ( TFEcE ), which is constructed as the ratio of the target EF input obtained from SBM (slack-based measure) model to the actual ecology input under the consideration of labor and capital inputs. This paper computes the TFEcE of 28 provinces in China for the period 2000–2012. Findings show that China’s TFEcE remains a low level of 0.5, which urgently needs to be improved. China’s regional TFEcE is extremely unbalanced and the eastern area ranks first with the highest score. Compared with total-factor energy efficiency and traditional single-factor ecological efficiency, The TFEcE index evaluates ecology efficiency more comprehensively through taking EF in conjunction with the total-factor framework. [ABSTRACT FROM AUTHOR]

• Analyze the synergy of CO 2 emission factors of energy-intensive industries via EMD. • Synergy of CO 2 emission factors: long-term trend, short-term volatility. • Elastic coefficient model is used to reveal the heterogeneity of the 10 factors. • Six industries are divided into "stable and balanced" and "sensitive and uneven". Carbon emission is a global problem that countries around the world are paying attention to and urgently need to be resolved. Under the requirements of China's high-quality economic development and the carbon peaking and carbon neutrality goals, energy-intensive industries, as a key link in the industrial chain and the main source of China's CO 2 emissions, have attracted much attention. This paper made a statistical analysis of the scale development of six energy-intensive industries, and explored the fluctuation characteristics of their carbon emissions. The empirical mode decomposition (EMD) model was further introduced to analyze the and synergistic effect among the driving factors of carbon emission, revealing the synergistic mechanism of long-term trend and short-term volatility of factors. Then, the elastic sensitivity analysis model of carbon emissions in energy-intensive industries was constructed to study the heterogeneity of driving effects of factor indicators. From the perspective of factors driving, this article reveals the heterogeneity of the driving effects of ten key factor indicators including economic level (GDP), urbanization level (UP), industrial structure (IS), technological innovation (TI), and environmental regulation (ER); from the perspective of industry development, this paper summarized the "stable and balanced" and "sensitive and uneven" trends presented by the heterogeneity of the six energy-intensive industries. Combining the characteristics of industry emission fluctuations, driving factors' synergies and heterogeneity, from the perspective of short-term and long-term development, four targeted emission reduction control strategies were proposed to provide reference for the low-carbon development of energy-intensive industries. [ABSTRACT FROM AUTHOR]

Energy productivity is a key indicator to evaluate energy efficiency. However, few researchers focus on China’s energy productivity at the city level or its spatial patterns. The aim of this paper is to investigate the determinants and spatial character of changes to China’s energy productivity at the city level. The change in energy productivity is decomposed using a distance function approach, and its spatial character is identified through exploratory spatial data analysis, based on data from 248 cities between 2010 and 2014. The study revealed that China’s overall energy productivity exhibited a downward trend caused primarily by the effects of technological and technical efficiency changes at the city level. Additionally, significant spatial autocorrelation existed in energy productivity, although most cities did not show significant spatial clustering. Based on the above results, we provide relevant suggestions for policymakers. [ABSTRACT FROM AUTHOR]

Eco-efficiency is of great significance in facilitating a region’s sustainable development. However, there are some inconsistencies among the concepts and also relationships of eco-efficiency and its relevant efficiencies in recent studies. This paper integrates eco-efficiency and three related-efficiencies (economic efficiency, energy efficiency, and environmental efficiencies) into a total-factor analysis framework, regarding them as composite eco-efficiency indicators. Employing a new data envelopment analysis approach, named Meta-US-SBM, which considers meta-frontier, undesirable outputs, super efficiency, and slacks simultaneously, the measure system of these four efficiencies is established. An empirical study is conducted using Chinese provincial data from 2001 to 2014. Results indicate that, overall, the regional economic efficiency is better than other related efficiency indicators. Furthermore, different provinces are adopting different development modes, as denoted by significant heterogeneity among eco-efficiency indicators. [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]

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]

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]

Abstract: The sustainability of Chinese economy has attracted attentions from all over the world since China''s reform & opening up policy. This paper attempted to evaluate the relationships among Chinese economy, energy and its impact of emissions during 1991–2009 using several novel indicators based on emergy, energy and monetary units. The results show that NH3-N in wastewater has taken main responsibility for impact of emissions, the hidden environmental cost per unit economic output has been continuously reduced, education and R & D investment has cut pollutants generating intensity since 1997, and environmental protection investment has cut emission intensity since 1996. Generally speaking, the coordination degree of structure and scale of China''s economy has been improved to different degree from 1991 to 2009. However, the growth of education and R & D investment and environmental protection investment has not prevented impact of emissions from increase caused by economic aggregate growth, and the turning point has not appeared in this period. Finally, this paper discusses some related issues and puts forward the corresponding suggestions. [Copyright &y& Elsevier]

• GDIM is used to investigate the influencing factors of energy-related PM 2.5 emissions in China. • A novel decoupling indicator is constructed based on GDIM decomposition results. • The increase of PM 2.5 emissions is primarily due to output scale and energy use effects. • Emission intensity and emission coefficients are the main factors decreasing PM 2.5 emissions. • Technical effect plays an important role in promoting the decoupling of PM 2.5 emissions. Haze pollution has become a severe threat to China's sustainable development. It is crucial to provide a complete explanation for the mechanism behind the changes in PM 2.5 pollution and explore how to decouple economic growth from PM 2.5 pollution. Compared with the traditional decomposition analysis methods, the Generalized Divisia Index Method (GDIM) integrates multiple influencing factors and provides a fuller understanding of the influence mechanism of PM 2.5 pollution. In addition, the decomposition of the monitored PM 2.5 concentration in previous studies leads to ambiguous economic meanings of some relative impact indicators. In this paper, GDIM decomposition is applied to study the driving factors of energy-related PM 2.5 emissions changes in China. Then, based on the GDIM decomposition results, this paper constructs a novel decoupling indicator to study the decoupling relationship between PM 2.5 emissions and economic growth, and the contributions of the technical and non-technical factors to the decoupling indicator are quantified. The main results are summarized as follows. (1) The output scale effect and energy use effect are the main reasons for the increase of PM 2.5 emissions, while the emission intensity effect and emission coefficient effect make major contributions to decreasing PM 2.5 emissions. The effects of population, per capita emissions, per capita output, and energy intensity are relatively minor. (2) China and its three economic regions move from strong decoupling in 1998–2000 to weak decoupling during 2000–2010, and then into strong decoupling over the period of 2010–2014. (3) Technical effect plays an important role in promoting the decoupling between PM 2.5 emissions and economic growth, but its contribution shows a downward trend over time. In contrast, non-technical effect hinders the decoupling process, and its contribution is decreasing from 2000 to 2014. This paper is supportive for formulating emissions reduction policies and improving China's air quality. [ABSTRACT FROM AUTHOR]

• Household indirect energy consumption is decomposed by input-output subsystem method. • Indirect consumption is 1.3 and 1.65 times of direct in 2012 and 2017 respectively. • Coal indirect consumption accounts for 50.2%, 54.6% in 2012 and 2017 respectively. • Spillover effect is the most one among the four components. • Ferrous metal smelting and rolling sector is most affected by household activities. In recent years, China's rapid economic development and steady growth of household consumption have contributed to the continuous growth of energy consumption. In addition to considering direct household energy consumption, the indirect effects of people's consumption activities on energy consumption in other productive sectors can't be ignored. According to the input-output analysis framework and consumer lifestyle analysis, this paper mainly studies the direct and indirect consumption of energy by Chinese household consumption ways and the relationship between energy structure and lifestyle. From the perspective of structural analysis, the input-output subsystem model (scale component, own internal component, feed-back component and spillover component) is used to analyze the energy supply and demand relations among 36 sectors of the national economy related to the lives of household in 2012 and 2017, revealing the change trend and transmission mechanism. This paper also focuses on the impact of household consumption ways on energy consumption of industrial sector and changing consumer lifestyles on energy saving, meanwhile it also forecasts China's future household energy consumption under four scenarios. The results show that in 2012 and 2017, total consumption of energy which is influenced by household consumption ways in China is 28461.82 PJ and 44759.96 PJ, respectively, accounting for 26.9% and 34.1% of total consumption of final energy. The indirect energy consumption is 1.3 times and 1.65 times of direct, respectively. The coal consumption accounts for the majority of indirect energy consumption. The smelting and pressing of ferrous metals is the industrial sector which is most affected by the household consumption ways. The scale component, own internal component, feed-back component and spillover component has accounted for 18.5%, 1.3%, 0.1% and 80.0%, from 17.5%, 2.0%, 0.2% and 80.3% of energy consumption in total, respectively. Under the four scenario development modes (NN, NA, LN and LA), it is predicted that the indirect energy consumption in household life in 2025 is 43740.56PJ, 34922.93PJ, 39149.37PJ and 31257.28PJ, respectively. The implementation of low-carbon consumption mode and the accelerated decline of energy intensity will help to reduce energy consumption. [ABSTRACT FROM AUTHOR]

This paper proposes a metafrontier slack-based efficiency measure (MSBM) approach to model ecological total-factor energy efficiency. This new advanced approach incorporates group heterogeneities of regions, total slacks, and undesirable outputs simultaneously into energy efficiency analysis. We incorporate global environmental technology into the proposed model so as to improve its discriminating power. We conduct an empirical analysis of regional ecological energy efficiency by incorporating carbon dioxide (CO 2 ) and sulfur dioxide (SO 2 ) emissions and the chemical oxygen demand (COD) of China during 2001-2010. The results indicate that most of the provinces are not performing at high ecological energy efficiency. Significant regional technology gaps in ecological energy efficiency exist in three areas. We present some policy suggestions based on the empirical results. [ABSTRACT FROM AUTHOR]

This paper adopts data envelopment analysis method to calculate the regional energy efficiency from the perspective of total-factor energy efficiency. The Markov chain and spatial Markov chain are the common methods to test the club convergence of regional energy efficiency in China. Results indicate that the regional energy efficiency in China has been globally characterized by “club convergence” since 1999, and the energy efficiency transitions in China are closely connected with regional characteristics. A high level of energy efficiency has a positive influence on a region, whereas a low level of energy efficiency has a negative influence. This empirical analysis provides a spatial explanation to the “convergence clubs” of regional energy efficiency in China. [ABSTRACT FROM AUTHOR]

The growing conflict between economic growth, energy and environment in China has restrained the country's economic development. In this work we investigated the interaction among the Chinese economy, energy production and consumption and the impacts of concomitant air emissions from 2000 to 2011, using an indicator system based on energy, emergy and money units. The results show that China's rapid economic growth has promoted tremendous expansion in energy production and consumption, which have led to increasing the impact of emissions in this study period. During the time examined, energy production and use efficiencies and the structure of the energy sector improved slightly; the self-sufficiency of energy use fluctuated, as petroleum took on an increasingly strong dependence on imports; fossil energy, mainly coming from coal, still has a majority share in energy production and consumption of the nation; the environmental loading intensity of energy consumption decreased slightly while that of energy production increased; most of the impacts of energy-related emissions are derived from their impact on human health; the impact of emissions from energy production made an increasing contribution to the total impact. Generally speaking, China's economic growth still heavily depends on energy-intensive industries that put great pressure on energy supply and pollution control. Although China has made obvious progress in energy mix optimization to save energy and reduce emissions, the pace of improvement still fell behind that of economic growth. Finally, this paper discussed some related issues and presented corresponding suggestions to further coordinate the relationship between the economy, energy production and consumption and the environment. [ABSTRACT FROM AUTHOR]

• Assessing the Environmental Performance of china's Three Urban Agglomerations. • Using the dynamic DEA model based on the input–output perspective. • The total environmental efficiency exhibits a wave-like development trend. • PM2.5 is the best unexpected output after strict prevention from 2013 to 2017. • Industrial smoke and dust emissions need to strengthen management in the future. As a special form of a cluster city, urban agglomeration has become an important platform to support national economic growth and to participate in international competition and cooperation, but it faces severe environmental problems. This research thus selects panel data of 60 cities in the Beijing-Tianjin-Hebei urban agglomeration (BTH), Yangtze River Delta (YRD), and Pearl River Delta (PRD) from 2013 to 2017. Based on the input–output perspective, labor and energy consumption per GDP are selected as input indicators, GDP, PM2.5, SO 2 , industrial smoke and dust emissions, and wastewater discharged as output indicators, and fixed assets as a carry-over variable in the dynamic DEA model to evaluate and analyze the environmental efficiencies of these three urban agglomerations. Findings show that their total environmental efficiency exhibits a wave-like development trend, and that the total efficiency score of BTH is better than that of PRD and YRD. From the viewpoint of a sub-efficiency index, PM2.5 is the lowest in unexpected output, where its average five-year efficiency score is 0.9847, while the average score of industrial smoke and dust emissions efficiency is the lowest at 0.6199. Finally, this paper offers suggestions for different problems facing the three urban agglomerations. [ABSTRACT FROM AUTHOR]

Abstract: This paper reports China''s eco-efficiency trends and the cause of their dynamic behavior during the period 1978–2010. We show three main results. First, in general, eco-efficiency indicators increased for resource utilization, energy consumption and emissions for air and water, and relative decoupling occurred in China at a high level in the global context. Second, decoupling from economic growth has been absolute for the discharge of soot, chemical oxygen demand (COD) and ammonia nitrogen. Third, during the years 2001–2010, the decoupling level was very low, and resource utilization was almost coupled with GDP due to the high consumption and dramatic increase of mineral extraction. The causes of the observed dynamics of eco-efficiency and decoupling were also explored, with the conclusion drawn that the effect of technology was the predominant positive factor while structure effects were the negative factors for resource and energy efficiency; the technological effect of pipe-end treatment played a dominant role in the improving eco-efficiency of pollutant emissions and decoupling from economic growth. Furthermore, implications for further policymaking to setting proper targets for the relative decoupling of resource use, especially for mineral resource use and economic growth, are suggested. [Copyright &y& Elsevier]

Abstract: This paper analyzes the interactions among China''s economic growth and energy consumption and emissions during 1978–2007. Conventional energy and emergy are applied to quantify energy consumption and emissions’ impact respectively. Several indicators, based on emergy, energy and monetary units, are applied to depict the relationships among economic growth and energy consumption and emissions’ impact. The results show that energy consumption and emissions’ impact rise simultaneously. Therein, nonrenewable energy resources possess absolute share in total energy consumption and undertake primary responsibility for increasing emissions’ impact, and NH3–N in wastewater leads to the most emissions’ impact on environment. Energy mix and energy efficiency and pollution control make some achievements, but their improvements fall far behind economic growth rate. As a result, the structure of China''s economy has been obviously optimized; however, the improvement of the relationship between China''s economy, energy and environment is far behind that of its economic structure in this period. Therefore, China will continue to face huge pressure on resources and environment its rapid economic growth brings about in future. Those study results imply that enhancing energy efficiency, optimizing economic structure and strengthening pollution control will still be the main tasks for China''s governments in future. [Copyright &y& Elsevier]

• Urban spatial structure is an important source for improving total-factor energy efficiency. • A poly-centric structure can improve total-factor energy efficiency. • The impact is constrained by regional differences, development stages and city size. International experience shows that the urbanization rate between 30% and 70% is a stage of rapid urban development, which means that more people in China will enter cities in the future. Along with this urbanization process, an important theoretical and practical question posed is whether China should choose a development path that is dominated by large cities or small and medium-sized cities. That is, whether China chooses a mono-centric structure or a poly-centric structure, which is more conducive to the improvement of economic efficiency? The reasonable distribution of urban systems is not only a necessary condition for optimizing the spatial allocation of resources and coordinating the development of regional economies, but it is also an important source for improving total-factor energy efficiency. In this paper, a modified Super-SBM model is used to measure China's total-factor energy efficiency. The mechanism and effect of urban spatial structure on total-factor energy efficiency is then empirically tested using the Dynamic Spatial Panel Model (DSPM). The study found that, for provinces, a poly-centric structure is more conducive to improvements in total-factor energy efficiency with research conclusions still valid following a series of robustness tests. However, the impact of urban spatial structure on total-factor energy efficiency is constrained by regional differences, development stages and city size. On the one hand, compared with the Central and Western regions, the adoption of a mono-centric structure in Eastern provinces is more conducive to improvements in total-factor energy efficiency. On the other hand, improvements in degree of both urbanization and city scale can effectively alleviate the negative impact of a mono-centric structure on total-factor energy efficiency [ABSTRACT FROM AUTHOR]

• We measure the green growth degree of China's industrial sectors by considering the constraint of total energy consumption. • We proposed a new common equilibrium efficient frontier, which considers each DMU's own adjustment strategy on fixed-sum energy input. • The proposed approaches are applied to analyze the green growth and energy and environmental efficiency of 36 of China's industrial sectors. Tight energy constraints and severe environmental pollution are two main problems affecting economic growth and sustainable development. As an important economic growth mode, green growth seeks to achieve both economic growth and environmental sustainability. Previous studies on the efficiency evaluation of green growth ignored fixed-sum energy consumption; this is a significant omission because this constraint is general in China: the government has set targets to reduce energy consumption by 20% and 16% per unit of GDP during its the eleventh (2006-2010) and twelfth (2011-2015) five-year plans. To fill this gap, we propose a new data envelopment analysis (DEA) model to analyze the green growth degree of China's industrial sectors. The proposed DEA model considers the constraint of total energy consumption in order to conform to the policy of energy and emission reduction. Previous theoretical studies on fixed-sum output construct the common equilibrium efficient frontier (CEEF) only by considering the minimal reduction strategy for the fixed-sum output of all decision making units (DMUs), while ignoring each DMU's adjustment strategy for fixed-sum input/output. In this paper, we construct a new CEEF by considering each industrial sector's adjustment of energy consumption. The new CEEF not only guides the industrial sectors to alter their energy consumption structure to achieve green growth but also allows a more accurate evaluation of the energy and environmental efficiency (EEE) of industrial sectors. Last, our proposed model is applied to analyze the green growth and EEE of 36 of China's industrial sectors. [ABSTRACT FROM AUTHOR]