Search

The transportation sector is the main energy consumer and carbon emitter in China. To accurately evaluate the dynamic changes in the energy-carbon performance of the sector and to propose alternatives for sustainable development, this paper proposes an approach incorporating the meta-frontier method, global benchmark technology, and non-radial directional distance function. Using this approach, the paper proposes a new definition, named the global meta-frontier non-radial Malmquist energy-carbon performance index (GMNMECPI). GMNMECPI can be decomposed into technical efficiency change (EC), best-practice gap change (BPC), and technology gap change (TGC). This new method was then used to estimate the dynamic changes of energy-carbon performance in China's transportation sector from 2006 to 2015. The paper also identifies the effect of current policies. The empirical results show that the energy-carbon performance of China's transportation sector decreased annually by 1.636% during the study period. This reduction was mainly caused by a significant technology lag in the central area while primarily influenced by deterioration in efficiency in both the east and west. There is a distinct heterogeneity in technology across China's three areas. Based on the findings, the paper closes with policy implications. [ABSTRACT FROM AUTHOR]

In order to explore the decoupling relationship and its influence factors between economic growth and carbon emissions in China, the decoupling elasticity decomposition quantitative model of carbon emissions based on extended Log-Mean Divisia Index and Tapio decoupling models is established in this paper. The carbon emissions induced by household (HOU) sector ranked fifth among the nine sectors; hence, we analyzed the HOU sector with the production (PRO) sector together. The results show that, first, the carbon emissions increased from 3.95 billion tons in 1996 to 10.49 billion tons in 2012, and the contributions of manufacturing sector and electric power, gas and water production and supply sector to carbon emissions account for approximately 81 %. Second, the economic output effect is the main contributor, and the energy intensity effect is the major inhibitor factor to the carbon emissions in both the PRO sector and HOU sector, respectively. Third, the decoupling state of the PRO sector mainly stayed at weak decoupling, while the decoupling state of HOU sector mainly stayed at strong decoupling. Fourth, the impact factors of the carbon emissions and the decoupling elasticity values are in complete agreement. At the end of this paper, we present some policy recommendations for China's government to realize the decoupling between CO emissions and economic growth in the near future. [ABSTRACT FROM AUTHOR]

This paper explores China's strategies for addressing climate change on the industrial level. Focusing on six energy-intensive industries, this paper applies gray relational analysis theory to the affecting factors to CO emissions of each industry after calculating each industry's CO emissions during 2001-2010. Further research based on GM(1, 1) model is conducted to forecast the trend of the factors, the energy consumption and each industry's CO emissions during the 12th Five-Year Plan period. As a breakthrough in previous conclusions, energy consumption structure was divided into the respective proportion of coal, oil, natural gas and electricity in the primary energy consumption, with which industrial output and energy intensity are combined to analyze each of their impacts on the energy-intensive industries. It turns out that all the factors' impacts on emissions of the six major energy-intensive industries are significant, despite their differentiated extents. It is worth noting that, contrary to previous findings, industrial output is not the leading affecting factor to CO emissions of the energy-intensive industries compared with the proportion of coal and electricity in the primary energy consumption. The GM(1, 1) forecast results of energy consumption and CO emissions by the end of 2015 show that coal and electricity will remain a large proportion in primary energy consumption. This research may shed some light on China's adjustment of energy structure under the pressure of addressing climate change and hence provide decision support for the acceleration of renewable energy utilization in the industrial departments. [ABSTRACT FROM AUTHOR]

Agriculture produced the largest methane emissions in China. It is of great importance to investigate effect of fertilizer using intensity on the environmental efficiency of China’s agriculture. This paper mainly investigates the determinants of environmental efficiency of China’s agriculture. First, we estimate environmental efficiency of China’s agriculture of 30 provinces from 1997 to 2014 through metafrontier SBM super efficiency with undesirable outputs, which allow for technology heterogeneity in different regions. Then, we compare environmental efficiency in different regions. Furthermore, we also analyze whether heterogeneity of environmental technology widened or decreased. Last, we also explore the determinants of environmental efficiency of China’s agriculture through bootstrap truncation regression. We find that fertilizer intensity negatively affects environmental efficiency. Urbanization has significant positive (1.454) effect on environmental efficiency under metafrontier in the east. It is significant use more organic fertilizer to decrease CO2 (carbon dioxide) emissions. It is important to enhance environmental innovation for China’s agriculture. [ABSTRACT FROM AUTHOR]

Technological advancement plays a crucial role in CO emissions mitigation and has attracted great attention around the world. A multitude of literatures mainly focused on single technological impact on environmental issues at national level, while comprehensive studies concerning technological factors at regional level are rare. This paper employs environmental learning curve model to investigate the learning effects of different technological channels on CO emissions at the national and regional levels using panel data of China's 29 provinces from 1997 to 2014. The technological advancement is disaggregated into indigenous research and development (R&D), foreign technology import and technological revolution. Furthermore, to comprehend the characteristics of various provinces with regard to CO emissions and emission efficiency, China's 29 provinces are divided into four regions according to the features of 'CO emissions-efficiency'. Empirically results manifest that technical renovation is the paramount driver to mitigate the national CO emissions. The CO learning abilities of indigenous R&D in high emissions regions are greater than those in the low ones, while boosting the investment of foreign technology import in low emission regions has significantly positive impacts on CO emissions, and the technical renovation is effective in abating CO emissions in all regions. The findings not only enrich technology innovation theories, but also deserve special attention from policymakers. [ABSTRACT FROM AUTHOR]

This paper aims to evaluate the carbon dioxide (CO) emissions reduction performance of 30 mainland provinces in China over 2005-2009. First, the log-mean Divisia index (LMDI) technique is used to decompose the changes in CO emissions at the provincial level into 4 effects that are carbon intensity effect, energy mix effect, energy intensity effect and gross domestic product (GDP) effect. Next, two indicators, decoupling index and rescaled decoupling index, are implemented to evaluate the performance of 30 provinces in CO emission reduction from 2005 to 2009. The decomposition result shows that the GDP growth is mainly responsible for the CO emissions increase, while the energy intensity effect is the key factor for the decrease in CO emissions in each province. Moreover, according to the evaluation, the performance of each province in what concerns the CO emission reduction varies significantly. Most provinces in China made significant efforts in emissions reduction during 2005-2009, while some provinces only made weak efforts or even no efforts in decoupling progress. [ABSTRACT FROM AUTHOR]

Under the background of low-carbon economy, carbon productivity is a core criterion of the quality of economy growth. Based on panel data released from 1998 to 2012, carbon productivity in industrial sector is measured by the data envelopment analysis method based on directional distance function, under total factor productivity framework. For technological progress is an important impetus of productivity improvements, we do an analysis of technological progress route alternative issue about carbon productivity promotion in China's industrial sector. Our main findings are as follows. Firstly, the carbon productivity, which is estimated under the research framework of total factor productivity, is significantly lower than the single element carbon productivity. Secondly, the major representation of technological progress in China's industrial sector lies in capitalized embodied progress. Finally, capitalized embodied technological progress has a tremendous impact on carbon productivity. Looking ahead, the Chinese government should adopt measures to increase the amount of imported advanced equipment and improve domestic manufacturing level of equipment. [ABSTRACT FROM AUTHOR]

This paper analyzed dual perspectives of production and resident, and quantified factors affecting the energy-related per capita carbon emission from cities. Tianjin is the largest coastal city in northern China with rapid economic development and urbanization. Analysis of the CO emission generated by driving forces in Tianjin can provide guidance for policy decisions on the CO emission mitigation in global metropolises. Using LMDI and Kaya extension methods, this study built a decomposition model of economic output, economic structure, energy intensity of the production sectors, energy mix of the production sectors, population structure of urban and rural distribution, energy consumption per capita and energy mix of the household sectors to analyze the per capita carbon emission factors. The empirical study of Tianjin from 2005 to 2011 showed: Economic output played a positive role in the per capita carbon emission increasing, while economic structure, energy intensity of the production sectors and energy mix of the production sectors played a negative role; population structure of urban and rural distribution and energy consumption per capita promoted in the per capita carbon emission increasing, while energy mix of the household sectors inhibited the per capita carbon emission increasing. [ABSTRACT FROM AUTHOR]

Since the reform and opening up in 1978, China's foreign direct investment (FDI) and foreign trade have grown rapidly. At the same time, China's carbon dioxide (CO) emissions surged and China has become the world's biggest CO emitter. The purpose of this paper is to investigate the relationship between FDI, foreign trade and carbon dioxide emissions in China. Using a two-equation model adapted from Halkos and Paizanos (Ecol Econ 91:48-56, ), the total impacts of FDI and foreign trade on emission are divided into the direct and indirect impacts and estimated accordingly. The estimation results suggest that the total impact FDI on per capita CO emissions is negative. Concretely, the negative direct effect of FDI on carbon emissions dominates the positive indirect effect through FDI's influence on per capita GDP. However, for foreign trade, both direct and indirect impacts on CO emissions are insignificant after taking consideration of potential endogeneity and introducing dynamics. [ABSTRACT FROM AUTHOR]

China's petrochemical industries are playing an important role in China's economic development. However, the industries consume large amounts of energy and have become primary sources of carbon emission. In this paper, the change in carbon emissions from China's petrochemical industries between 2000 and 2010 was quantitatively analyzed with the Log-Mean Divisia Index method, which was decomposed into economic output effect, industrial structural effect and technical effect. The results show that economic output effect is the most important factor driving carbon emission growth in China's petrochemical industries; industrial structural effect has certain decrement effect on carbon emissions; adjustment of industrial structure by developing low-carbon emission industrial sectors may be a better choice for reducing carbon emissions; and the impact of technical effect varies considerably without showing any clear decrement effect trend over the period of year 2000-2010. The biggest challenge is how to make use of these factors to balance the relationship between economic development and carbon emissions. This study will promote a more comprehensive understanding of the inter-relationships of economic development, industrial structural shift, technical effect and carbon emissions in China's petrochemical industries and is helpful for exploration of relevant strategies to reduce carbon emissions. [ABSTRACT FROM AUTHOR]

Carbon finance is considered one of the most efficient methods to address the issue of climate change. The problem of how to establish and improve China's carbon financial system requires theoretical study as well as practical policies. A literature review of the effects of financial macroenvironment on carbon emissions was conducted. The purpose is to investigate the relationships of long-run equilibrium and short-run dynamics through the ARDL-ECM model among carbon intensity and macroenvironment factors including financial development, financial innovation, stock market turnover and foreign direct investment. And the former three are proven as long-term drivers of carbon intensity decline while FDI are insignificant to mitigate it. There is also a short-term dynamic adjustment among them. A main contribution to the literature in China studies the methods to reduce carbon intensity by taking into account the role of financial macroenvironment, especially the financing environment. Considering establishing an efficient carbon finance system, indirect financing tools represented by financial development could be more significant than direct financing ones represented by stock market turnover. [ABSTRACT FROM AUTHOR]

Recognition of key emission sectors is crucial for carbon reduction. This study identifies key emission sectors and analyzes driving and driven effects of these sectors in the context of China. The Input-Output approach is used to identify key emission sectors. The data used for analysis are collected from Input-Output Table and Energy Statistical Yearbook issued by the National Bureau of Statistics of China for the period of 1990-2012. Three types of key emission sectors are classified in this study, namely overall key sectors, driving-dominant sectors, and driven-dominant sectors. The major overall key emission sectors include Coal Mining and Dressing; Petroleum Processing and Coking; Chemical Products; Metals Smelting and Pressing; Production and Supply of Electric Power, Gas and Water; and Transportation, Storage, Postal and Telecommunications Services. There is one driving-dominant sector, which is Nonmetal Mineral Products. The major driven-dominant sectors include Petroleum and Natural Gas Extraction; Wholesale, Retail Trade, Lodging and Catering Services; and Others (such as finance, property, research and development, entertainment, health, education, and public facilities). Suggestions from policy implications for emission reduction are proposed. The research findings provide important references for the Chinese government to adopt appropriate emission reduction measures, particularly in addressing these key emission sectors. [ABSTRACT FROM AUTHOR]

This study uses the total-factor energy productivity change index (TFEPCH) to investigate the changes in energy productivity of construction industry for 30 provincial regions in China from 2006 to 2015, adopting the improved Luenberger productivity index combined with the directional distance function. In addition to traditional economic output indicator, this study introduces building floor space under construction as a physical output indicator for energy productivity evaluation. The TFEPCH was decomposed into energy technical efficiency change and energy technical progress shift. Results indicate that, first, energy productivity of China’s construction industry decreased by 7.1% annually during 2006-2015. Energy technical regress, rather than energy technical efficiency, contributed most to the overall decline in energy productivity of China’s construction industry. Second, energy productivity in the central region of China decreased dramatically, by a cumulative sum of approximately 77.1%, since 2006, while energy productivity in the eastern and western regions decreased by over 54.3 and 65.3%, respectively. Only two of the 30 provinces considered—Hebei and Shandong—improved their energy productivity during 2006-2015. The findings presented here provide a basis for decision-making and references for administrative departments to set differentiated energy efficiency goals and develop relevant measures. Additionally, the findings are highly significant for energy and resource allocation of Chinese construction industry in different regions. [ABSTRACT FROM AUTHOR]

Productive building energy efficiency work is a non-ignored booster to achieve the sustainable development in China, and evaluating the driving forces of carbon emissions in Chinese public buildings (CECPB) plays a crucial role in China building energy efficiency work. Nevertheless, China building energy efficiency work is currently challenged by the lack of effective approaches to evaluating the driving forces affecting CECPB at a quantitative level. To improve the carbon emission control strategy of Chinese public buildings, this study utilized the Stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT) model and ridge regression analysis to evaluate the driving forces affecting CECPB from 2000 to 2015. This study has three main results: (1) All of the five driving forces (i.e., population, urbanization level, floor area per capita of existing Chinese public buildings, GDP index in the Chinese tertiary industry sector, and carbon emission intensity in Chinese public buildings) have positive contributions to CECPB during the period of 2000-2015. (2) The different contributions of the aforementioned driving forces can be expressed by their different β values in decreasing order, as follows: floor area per capita of existing Chinese public buildings (21.12%), population (20.98%), urbanization level (20.81%), carbon emission intensity in Chinese public buildings (20.20%), and GDP index in the Chinese tertiary industry sector (19.44%). (3) The goodness of fit for the final ridge regression analysis proves that the proposed evaluation method is also applicable for evaluating these driving forces at a subitem level. Furthermore, this study demonstrates the feasibility of evaluating the driving forces affecting CECPB using the STIRPAT model and ridge regression analysis and fills the research gap. The discoveries of this study can impel the development of the carbon emission control strategy of Chinese public buildings for the upcoming phase. [ABSTRACT FROM AUTHOR]

In China, carbon capture and storage (CCS) is recognized as one of the most promising technologies through which to achieve a large reduction in CO emissions in future. The choice among different CCS technologies is critical for large-scale applications. With the aim of developing instructive policy suggestions for CCS development, this study proposed an interval programming model to select the optimal CCS technology among the different CCS technologies available in China. The analysis results indicate that the selection of CO capture technologies should be based on the actual situation of the project and industry being targeted. If the government implements mandatory CO emission reductions, storage in deep saline aquifers is the optimal choice for CO sequestration when oil prices are low and the number of available CO emission permits is large. In contrast, enhanced oil recovery is the optimal choice when oil prices increase and the availability of CO emission permits decreases. It is critical that the government reduce the operating cost and the cost of CO capture in particular. [ABSTRACT FROM AUTHOR]

The power industry is a major contributor to CO emissions in China and thus plays a critical role in achieving the targets of CO emission reduction. This study analyzes the historical trajectory and feature of CO emissions in China's power industry, explores the driving factors of CO emission change using LMDI method, and develops two emission reduction scenarios to evaluate the reduction potential of CO emissions. Results show the following: (1) China's power industry has experienced a significant but unstable increase in CO emissions from 343.18 Mt in 1985 to 3447.57 Mt in 2013, a growth rate of 904.60%. (2) Industrial-scale effect plays a dominant role in promoting CO emission growth in China's power industry, and the corresponding contribution degree reaches 111.73%. Energy intensity effect contributes most to the decrease in CO emissions, with a contribution degree of −16.82%. Capital productivity effect is another important factor leading to the increase in CO emissions. (3) The aggregate CO emission reduction in China's power industry would reach 18,031.62 Mt in the ideal scenario and 15,466.03 Mt in the current policy scenario during 2014-2030. Finally, this study provides policy implications for energy-saving and CO emission reduction in China's power industry. [ABSTRACT FROM AUTHOR]

Under the framework of meta-frontier, we employ the slacks-based measurement (SBM)-Undesirable approach to explore China's provincial energy efficiencies and meta-technology ratios (MTRs) of eight major economic regions during 2000-2014. The results obtained show that: firstly, the SBM-Undesirable model involving a undesirable output of CO emission is more reasonable than the SBM model for measuring China's provincial energy efficiencies. Secondly, there are severe imbalances of energy efficiencies between regions due to their imbalanced energy technologies. Thirdly, energy efficiencies of the southern, eastern and northern coastal regions are high with advanced energy technologies. Energy technology gaps between regional and meta-technologies of southwest, eastern coastal and northern coastal regions are shrinking; however, the ones of remaining regions are widening. Fourthly, energy technology of overall China has a U-shaped trend; however, the ones of provinces in each region are characterized as a club convergence. [ABSTRACT FROM AUTHOR]

The Chinese government committed to reduce carbon dioxide emissions per unit gross domestic product by 60-65 % from the 2005 level in a document submitted to the Secretariat of the United Nations Framework Convention on Climate Change. China has also proposed a strategy for a new type of urbanization. We employ static spatial econometrics and panel co-integration models to investigate the relationship between regional carbon emission intensity (CEI), and the level of urbanization, energy mix (EM) in China. The results suggest that spatial distributions for CEI exhibit a regional spillover effect in 29 provinces. A spatial lag model indicates that urbanization and EM have a positive impact on CEI. Co-integration analysis presents both CEI-urbanization elasticity and CEI-EM elasticity are greatest in Central China, followed by Western China and Eastern China. [ABSTRACT FROM AUTHOR]

According to the combined principles of fairness and efficiency, a comprehensive allocating indicator system is developed, and the TOPSIS approach is applied to allocate China's 40-45 % carbon emission intensity (carbon emission per unit of GDP) reduction target by 2020. The results indicate that, first of all, the unequally weighted indicator system outperforms the equally weighted one according to regional developing situation in China; and the most important indicator affecting the allowance allocation is carbon reduction responsibility, followed by future development right and emission reduction efficiency. Second, China's carbon emission intensity should be cut, but its absolute carbon emission volume may inevitably increase in the future due to the continuous economic growth, and we confirm that the western provinces may take the highest shares to increase carbon emissions, followed by the central, northeast and eastern provinces. Finally, in order to achieve the national target of carbon emission intensity reduction, the northeast and eastern provinces require reducing carbon emission intensity significantly from 2013 to 2020, while the central and western provinces should be given more developing room. [ABSTRACT FROM AUTHOR]

China's transport industry is a priority area for energy conservation and CO emission reduction due to its great carbon emissions. Based on the data of 1980-2012, this study first analyzes the CO emission differences among China's four transport sub-sectors, i.e., road, waterway, aviation and railway, using the σ-convergence and β-convergence methods. Subsequently, it explores the influencing factors for CO emissions in China's four transport sub-sectors, respectively, with the logarithmic mean Divisia index method. The following results are obtained. First, road and waterway are the major sources for China's transport CO emissions, and the road sector acts as the relatively largest CO emitter. In 2012, the CO emissions of road, waterway, aviation and railway accounted for 65.21, 29.07, 3.61 and 2.11 % of the total, respectively. Second, the CO emission differences among China's transport sectors gradually shrank during the period 1980-1996, while gradually widened during 1996-2012. Third, the economic growth served as one of the most important factors, driving China's transport CO emission growth over the period 1980-2012. In this period, the CO emissions of road, waterway, aviation and railway sectors increased by 561.71, 265.27, 54.07 and 28.28 Mt, respectively. [ABSTRACT FROM AUTHOR]

Human activities have become a major source of Earth's climate change, which brings the rise of surface air temperature and subsurface ocean temperature. Therefore, promoting sustainable consumption and production patterns is imperative to minimize the use of natural resources and reduce emissions of pollutants. This study uses Economic Input-Output Life-Cycle Assessment method and structural decomposition model to identify the driving forces that influence the changes in carbon emissions from China's residential consumption in the context of sustainable consumption. The findings of the study are as follows: (1) indirect carbon emissions from Chinese household consumption increase rapidly over time; (2) the largest carbon dioxide emitting sector turns from agriculture sector in 1992 into service sector in 2007; (3) the consumption level and the emission intensity are the main drivers that influence the change in indirect carbon emissions; and (4) the factor of consumption level presents positive effect on the emissions, while the emission intensity effect plays a negative role. Besides, the factors of urbanization, production structure, population size and consumption structure also promote the rapid increase in carbon emissions. [ABSTRACT FROM AUTHOR]