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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]

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

This paper estimates the linkages among total Sulphur dioxide (SO 2) emissions, total GDP and energy efficiency using China's provincial panel data from 2002 to 2015. We investigate total emissions rather than per capita emissions or ambient concentrations since it is total emissions that the environment cares about. Energy efficiency is estimated using stochastic frontier analysis and decomposed into both persistent and transient efficiency. We then investigate the long-run dynamics among SO 2 emissions, economic growth, and energy efficiency by employing the panel-based error correction model and taking the effects of cyclical variations into account. Our analysis shows that GDP has a positive impact on total SO 2 emissions in the short run and gains in energy efficiency have a significant negative effect on emissions in the long run. By controlling the effects of the business cycle, the effects of GDP on emissions remain positive in both the short and long run. The cross-sectional analysis provides similar insights. We argue that economic growth itself is an emission generator. Therefore, the government needs to establish a long-run strategy to curb emissions by improving energy efficiency. Image 1029 • We estimate the linkages among sulphur dioxide emissions, GDP and energy efficiency. • Energy efficiency is estimated by SFA and decomposed into persistent and transient efficiency. • We employ the panel-based error correction model with cyclical variations and structural break. • GDP has a positive impact on emissions in both the short and long run. • Gains in energy efficiency affects emissions negatively in the long run. [ABSTRACT FROM AUTHOR]

Abstract Since the beginning of China's reform and opening up in late 1970s, the contradiction between environmental quality and economic development has become increasingly acute. As the main driving force of development, China's fixed asset investment (FAI) has grown rapidly. In the meanwhile, China's energy consumption surged and the environmental pressures mounted. The surge in FAI may have great influences on the environmental quality. On the one hand, the rapid increase in FAI facilitated the development of the secondary industry especially energy- and pollution-intensive industries, which brought about significant amount of energy-related pollution. On the other hand, growing investment on environmental investment is expected to slow environmental deterioration. Moreover, the environmental quality and domestic investment may have potential spatial correlations. In this paper, after fully accounting for the spatial dependence, the relationship between domestic investment and environmental quality in China is quantitatively investigated. Using CO 2 and SO 2 as two representative pollutants, the estimation results indicate that the spatial dependence indeed exists, and total effects of FAI on pollutant emissions are positive. However, there is no evidence that environmental protection investment had expected effects to effectively curb pollutant emissions in China. [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 In recent years, urban energy efficiency has received much attention from researchers. However, ignorance of the competitive relationships among regions results in inaccurate energy efficiency. Game cross-efficiency data envelopment analysis (DEA), which can account for the competitive relationships, is a reliable method to measure energy efficiency. First, this paper applies game cross-efficiency DEA to analyze the urban total factor energy efficiency (UTFEE) of 26 Chinese prefectural-level cities from 2005 to 2015 under environmental constraints. Then, a comparative analysis and a concrete analysis are conducted based on the urban energy efficiency. Finally, a Tobit model is used to examine the effects of 10 potential influence factors. The measurement results show that the urban energy efficiency considering the competitive relationship is lower than the traditionally calculated efficiency. Additionally, the urban energy efficiency did not improve during the research period. Furthermore, regression analysis suggests that economic development and city scale can promote urban energy efficiency, while government expenditure, industrial structures, energy prices, foreign investments, research investments and production endowment have negative impacts on urban energy efficiency. According to our results, some implications of theory and practice are discussed for researchers and policy makers. [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]

To perform better future trend prediction for an economy-energy-environment (3E) system and address the shortcomings of traditional multivariate grey models, this paper introduces a spatial correlation term into the multivariate discrete grey model, thus creating the SLDGM(1,n) model, and improves the final calculation of the model according to the priority of new information. The validity of the SLDGM(1,n) model is assessed using data from the 3E system in North China, and the SLDGM(1,n) model is applied to predict the future trends of the 3E system in North China. The following conclusions are obtained. First, the introduction of the spatial correlation term and the improvement of the final calculation method are reasonable; the prediction accuracy of the multivariate grey model is improved, and multiple systems are modeled simultaneously. Second, the SLDGM(1,n) model calculates the spatial spillover effect, and according to the simulation results for North China from 2010 to 2019, Hebei's energy consumption and carbon emissions are subject to the largest influence from other provinces, while its economic development level is subject to the smallest influence, and the carbon emissions of Shanxi and Inner Mongolia are subject to a negative spatial influence effect. Third, the prediction results indicate that under the effect of spatial correlation, the energy consumption of all five provinces in North China will continue to rise; the carbon emissions of Beijing will gradually decline while the carbon emissions of the other four provinces will all gradually rise, and the per capita GDP of the five provinces is expected to increase by more than 50% by 2025. [ABSTRACT FROM AUTHOR]

With its continuing socio-economic development, China faces the challenge of meeting the growing energy demand. Industrial parks with combined cooling, heating, and power (CCHP) achieve better comprehensive economic and environmental benefits due to energy cascade utilization. A new enterprise entering an industrial park with CCHP needs to select a reasonable cold and heat source scheme (CHSS). Therefore, this paper presents a method for new enterprises to select an appropriate CHSS. This method is based on comprehensive economic and environmental benefit, using minimal annual average cost in operation optimization mode as a quantitative indicator, and the calculation process uses the improved differential evolution algorithm using the MATLAB software. Finally, a cloud computing center of an industrial park with CCHP in Chongqing is used as a case study to assess the method. Results show that the scheme of lithium bromide absorption refrigerator driven with steam can be accepted by the cloud computing center only steam price below 112.6yuan/t, which can promote energy cascade utilization in the industrial park. This method assists new enterprises entering the industrial park in selecting their energy system scheme. In addition, the method can assist energy supply enterprises to determine energy trade prices and also expand their user base. [ABSTRACT FROM AUTHOR]

For the past three decades, the notion of sustainable cities has become central in planning and managing urban areas in the world and the large-scale city formation has been formed in big cities. As a result of economic growth and urban transformation, Shanghai, a major Chinese international metropolis, faces ongoing issues with resource waste and low energy utilization. Therefore, this paper aims to consider the availability of water for energy production from a consumption-based perspective and estimate the water footprint of the energy supply using a regional input-output analysis approach for Shanghai. As a result, we conclude that the water footprint of the energy supply of Shanghai is about 1.28 billion m 3 in 2007, with 46.1% of water used for electricity and heat supply. The total water withdrawal by the energy sector is about 2.35 billion m 3 and additional water withdrawal needed is about 35% of the total water withdrawals by the energy sector in Shanghai. Furthermore, an energy self-sufficiency scenario was developed, and the scenario analysis reveals that 55% more water would be required to ensure a self-sufficient energy sector. To guarantee future regional energy security, it is important to manage water resources effectively by allocating water resources among sectors. [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]

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

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

An industrial park is characterized as a cluster of industries designed to meet compatible demands of different economic organizations within one location, which is pivotal to drive the regional economic growth of developing countries. The concentrated industrial activities inevitably result in substantial resource consumption and corresponding environmental emissions. Environmental auditing, which is used for the checking and verification of environmental performance, is an effective tool for investigating environmental emissions and resource consumption status and alleviation potential in industrial parks. As one of the environmental auditing technologies, emergy analysis, which provides a systematic approach in identifying the balance between socioeconomic development and natural environment, is employed in this paper. Specifically, a ternary emergetic environmental performance auditing framework was proposed to evaluate the behavior (preliminary work), ecological-economic efficiency (Level 1), environmental impact (Level 2), and mitigation effect (Level 3) of a typical industrial park in Beijing. The result showed that the concerned industrial park mainly depends on labor and service inputs and has a relatively high economic efficiency. However, the large dependence on purchased emergy exerted great pressure on the resource and environment, and affect the stability of the industrial park. The proposed framework may help reveal the value that free environmental services and resources offer to a specific system and thus can be complementary to the existing environmental performance auditing tools. [ABSTRACT FROM AUTHOR]

China intends to rely on urbanization policies to increase its economic growth even against the backdrop of new constraints on energy consumption. This paper investigates the impact of urbanization on economic growth and energy consumption using data from China’s 266 prefecture-level cities over the 2000–2010 period and examines the heterogeneity of this impact across income and urbanization groups. The main results of our empirical estimation indicate that: (1) the effect of urbanization on economic growth is positive and significant for the entire sample, although it is positive and significant only for high- and middle-income groups (and not the low-income group); (2) the impact of urbanization on energy consumption is positive and significant for all groups when the sample is divided into three urbanization groups based on the Northam curve, indicating that urbanization will lead to large increases in energy consumption. In summary, our empirical results show that urbanization targets will be difficult to achieve in terms of increasing GDP per capita under energy consumption constraints. [ABSTRACT FROM AUTHOR]

As buildings are constructed to be more energy-efficient and environmental friendly, the building construction industry, which is a basic and leading industry of the national economy development, has become one of the key sectors for energy conservation and emission reduction in China. This paper aims at quantifying both inter-factor and inter-energy substitution for China's building construction industry and investigate the main driving forces behind energy efficiency changes as well as the CO 2 abatement effect of a uniform carbon tax in this sector. The model is established employing provincial pooled data over 2003–2012 in China by regions; hence, results between different regions are compared. The main findings indicate that: (i) energy and non-energy are substitutes whereas individual energy inputs are complementary in China's building construction industry. The substitution effect varies across regions due to different factor endowments and marketization levels. (ii) Energy price increase and construction scale expansion leads to energy efficiency improvement while substitution and technology present negative influences on energy efficiency. (iii) Approximately 3% of the CO 2 emissions in China's building construction industry can be reduced by carbon taxation based on the integrated own- and cross- price elasticities of each energy. [ABSTRACT FROM AUTHOR]

The environmental impact of materials and energy is an important concern when cities and regions produce goods and services. To examine this requires an evaluation tool which can deal with the complex system of resources, energy inputs, products and wastes involved. This paper evaluates the urban material and energy flow efficiencies of 31 cities in China using a combination of the Data Envelopment Analysis model and Principal Component Analysis method. The results show that the urban flow system is composed of several input and output principal components, including energy, materials, urban capital investment, overall output, wastes, and others. In 2010, 16 cities were efficient as judged by the material and energy inputs and outputs. The remaining 15 cities were not efficient, primarily due to product shortfalls and waste excesses. Since 2000, half of the analyzed cities experienced a decline in the urban flow efficiencies, while only six cities showed a positive trend. The reasons include excess inputs of coal, coke, electricity, cement, investment, as well as output shortfalls in terms of overall output, wastes, services, agriculture and transport. We conclude that key priorities for improving urban systems with material and energy flow inefficiency are the use of urban renewable supplies, focus on sustainable endogenous development model, and improvement management of waste output, in order to increase efficiency and sustain economic growth. [ABSTRACT FROM AUTHOR]

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

Chinese nonmetallic mineral products industry is one of the largest electricity consumer in China and has a large impact on overall electricity consumption in China. This paper examines the impact of economic variables on the demand for electricity in Chinese nonmetallic mineral products industry where economic growth, sectoral value added per worker, sectoral R&D intensity, and energy price were utilized to analyze sectoral electricity consumption, with an application of quantile model. The paper's estimates unveiled the varying effects of economic variables across the spectrum of sectoral electricity consumption where the coefficient of economic growth was positive and significant across all quantiles, while sectoral value-added per worker had both positive and negative significant coefficients. An increase in income level and sectoral value added per worker will increase the electricity consumed by the industry, however, the latter will also enhance a decreasing trend in few regions across China and did not influence high energy efficiency but rather enhanced the production of additional outputs, while sectoral R&D intensity and energy price will ensure a substantial decrease in sectoral electricity consumption with the latter having a greater impact. Increase in investment for sectoral R&D intensity will boost technological advancement and is recommended as a cornerstone to ensuring decline in sectoral energy consumption that will buttress sectoral value added per worker coupled with a robust energy price. [ABSTRACT FROM AUTHOR]

Abstract: With the world’s largest population and consistently rapid rates of economic growth, China faces a choice of whether it will move towards a more sustainable development trajectory. This paper identifies the different factors driving innovation in the fields of green chemistry and green engineering in China, which we find to be largely driven by energy efficiency policy, increasingly strict enforcement of pollution regulations, and national attention to cleaner production concepts, such as “circular economy.” We also identify seven key barriers to the development and implementation of green chemistry and engineering in China. They are (1) competition between economic growth and environmental agendas, (2) regulatory and bureaucratic barriers, (3) availability of research funding, (4) technical barriers, (5) workforce training, (6) industrial engineering capacity, and (7) economic and financial barriers. Our analysis reveals that the most crucial barriers to green chemistry and engineering innovations in China appear to be those that arise from competing priorities of economic growth and environmental protection as well as the technical challenges that arise from possessing a smaller base of experienced human capital. We find that there is a great deal of potential for both the development of the underlying science, as well as its implementation throughout the chemical enterprise, especially if investment occurs before problems of technological lock-in and sunk costs emerge. [Copyright &y& Elsevier]

Abstract: In China, Rapid economic growth has stimulated fast urban expansion and rural household income and consumption expenditure. In current paper, an input–output method is used to determine the impact of China’s increased urban and rural household consumption on carbon emissions. The results shows that the direct and indirect CO2 emission from household consumption accounted for more than 40% of total carbon emissions from primary energy utilization in China in 1992–2007. The population increase, expansion of urbanization and the increase of household consumption per capita all contribute to an increase of indirect carbon emissions, while carbon intensity decline mitigates the growth of carbon emissions. Therefore, at the domestic level, household consumption is of great significance for CO2 emission, which could be mitigated through changing the composition of goods and services consumed by households, and switching to consumption pattern of less carbon-intensive products. The government must consider the substantial contribution of household consumption to carbon emissions when China is encouraging consumption in order to address the current global financial crisis. [Copyright &y& Elsevier]

Renewable energy technological innovation is greatly influenced by renewable energy markets and policies. In this regard, the paper decomposes nine influencing factors of patents of a specific renewable energy technology using the extended logarithmic mean Divisia index (LMDI) method from 2001 to 2015. The differences in a specific renewable energy technological innovation and development during the three Five-Year Plan periods is prioritized at the national level. The contribution of the increase in patents of renewable energy technologies mainly lies in the patents of solar energy technology and wind energy technology, but during the 12th Five-year Plan period, the increments of their patent counts significantly decline. Due to priority given to the development of innovation in a specific renewable energy technology, the improvement in the efficiency of R&D spending, the increases in the share of R&D spending and the share of renewable energy, low carbon economy concept advocacy and carbon scale expansion, the patent counts of a specific renewable energy technology will increase. Additionally, the factors affecting innovation in a specific renewable energy technology at the different economic development levels, as well as different resource distribution levels are investigated. • The extended LMDI method is used to decompose nine factors. • Focusing on renewable energy innovation during the three Five-Year Plan periods. • Discussing the issue based on the economic development levels. • Discussing the issue based on resource distribution levels. [ABSTRACT FROM AUTHOR]