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Nowadays, BRICS (i.e., Brazil, Russia, India, China, and South Africa) becomes more and more important in the world in terms of not only economic development, but also energy consumption. The purpose of this paper is to study occurrence of a decoupling between economic growth and energy-related CO emission in BRICS countries from 1995 to 2014. Furthermore, the LMDI theory is utilized to find the decoupling reasons. The main conclusions drawn from the present study may be summarized as follows: (1) During the study period, China was the largest CO emitter among BRICS countries; per capita energy-related CO emission in Russia was the largest in BRICS countries. (2) The share of fossil energy to total energy consumption for South Africa accounted for more than 96 %. However, the share of fossil energy to total energy consumption for Brazil accounted for about 60 % over the study period. (3) For Brazil, Russia, and South Africa, five decoupling status occurred during the study period. However, only three decoupling status occurred in China and India. (4) The energy intensity effect played a positive role in decreasing CO emission in all five BRICS countries. [ABSTRACT FROM AUTHOR]

Understanding the causal relationships among economic growth, energy consumption, and CO emission is important for formulating energy conservation and emission reduction policies. In this paper, we explore the causal relationships among economic growth, energy consumption, and CO emission in China during 1978-2012 by using both the linear and nonlinear causality tests. The obtained results show that the links examined by the linear and nonlinear causality tests are not all same. Both linear and nonlinear causality tests indicate a unidirectional causality from CO emission to GDP and a bi-directional causality between energy consumption and CO emission. Linear causality test indicates a unidirectional causality from energy consumption to GDP, while nonlinear causality test indicates a unidirectional causality from GDP to energy consumption. Finally, policy recommendations are proposed for achieving the target of coordinated, sustainable development of China. [ABSTRACT FROM AUTHOR]

With the growing demand, China's iron and steel industry has obtained rapid development since the 1990s. China's steel output reached 220 million tons for the first time in 2003, becoming the first country whose annual production exceeded 200 million tons. The iron and steel is an industry of high energy consumption, high pollution and high emissions which has attracted deep concern of Chinese government. Previous research has estimated the direct CO emissions in individual processes of iron and steel production, while research on the indirect CO emissions from the related sectors of the iron and steel industry is scarce. To explore the whole CO emissions, this paper evaluates the direct and indirect carbon emissions in the iron and steel industry and carbon emission deduction by building an economic input-output life cycle assessment (EIO-LCA) model based on the latest available data of the input-output extension table in 2010 and China's Energy Statistical Yearbook in 2011. The results show that coke and coal produce the most direct CO emissions and raw chemical materials, medical and chemical fiber manufacturing, transportation storage and the postal industry, the electricity heat production and supply industry, nonmetal mineral production, petroleum processing of coke and nuclear fuel processing, coal mining and dressing are the six sectors that produce the largest indirect CO emissions among the 35 sectors in the iron and steel industry. Based on the results, we suggest that China should (1) improve the quality of coke and coal, increase the efficiency of coke and coal, coal blending technology and the cokes' strength, and employ the scrap or cities' minerals as main raw materials in the production, and at the same time, the government and enterprises may increase to invest in technology innovation; (2) and use high-strength iron and steel instead of the ordinary one. Meanwhile, the spatial distributions of the six sectors are mainly concentrated in Shandong Province, Jiangsu Province, Zhejiang Province and Shanxi Province. Shandong Province, Jiangsu Province, Zhejiang Province and Shanxi Province may adjust their industrial structure by increasing the proportion of the third industry and accelerating the development of high-tech industries and services. [ABSTRACT FROM AUTHOR]

China has a large number of rural-urban migrant workers in the 'semi-urban' states, and their consumption pattern differs from that of rural residents and urban residents. To ensure that society develops sustainably and stably, it is necessary to be concerned about the issues of migrant workers. Based on the data gathered and processed, this paper focuses on the impacts of the consumption of China's migrant workers on energy use and CO emissions using the input-output method. The results show that: the living conditions, health care and allocation of educational resources have not been effectively ensured for migrant workers. The total CO emission per capita of migrant workers is relatively low, at two-thirds of the national average and less than one-third that of urban residents. Marginal energy consumption and marginal carbon emission coefficients of migrant workers are slightly lower than the national average level, at 4.9 tce (tonne of standard coal equivalent) per million yuan and 11.6 t CO per million yuan lower than those of urban residents. The sectors of food manufacture, and production and distribution of electricity make the greatest contributions to the total carbon emissions of migrant workers, at up to 36.3 %. The citizenization of migrant workers will lead to an increase of 272 million tons of CO emissions of primary energy, and the top ten sectors, led by the sectors of electricity production and distribution, and health, will produce more than 60 % of the total increase in carbon emissions. With the acceleration of urbanization and citizenization, the total carbon emissions embodied in the consumption of migrant workers are likely to rise. Further efforts are required to control and reduce the indirect carbon emission, such as by improving energy price mechanism and optimization of the power structure. [ABSTRACT FROM AUTHOR]

To offer a scientific basis and reference for policy makers when developing the regulation framework for Chinese national carbon market, this research analyzes the environmental and economic effects of the carbon market from a mid- to long-term perspective in China. Through a computable general equilibrium model, with technological progress as an endogenous variable, this study provides a comprehensive investigation on the relationships between the price of carbon, technological development, emission reduction and economic growth in low, mid- and high emission reduction scenarios. Furthermore, it analyzes the potential of price-setting mitigation measures to create incentives for technological progress. The results indicate that the carbon market will have a positive impact on the R&D investment in China and in turn would promote technology development. Consequently, it is vital that the carbon price is high enough; otherwise, the pressure on technological development will not be sufficiently strong; there is compatibility between carbon intensity reduction and mid- and long-term GDP growth, but it seems impossible to realize the positive effects on both emission reduction and economy development at the early stage. Hence, the carbon market alone will not be a cost-effective instrument for emission abatement and other auxiliary policies will also be needed in the early stages. Meanwhile, selection of reasonable emission reduction scenarios will play a crucial role in achieving the pre-2020 and post-2020 carbon reduction commitments efficiently in China. [ABSTRACT FROM AUTHOR]

As the world's third largest carbon dioxide (CO) emitter, India has long been believed to mostly compromise with international environmental obligation. Using annual data for the period 1970-2013, the study investigates the impact of population density, energy consumption, economic growth and trade openness on CO emissions in India. It applies the autoregressive distributed lag bounds testing approach to cointegration for establishing the existence of a long-run relationship and uses vector error correction model to determine the direction of causality between the variables. The results indicate that there is a meaningful long-run relationship between CO emissions and socioeconomic factors. We find that population density, energy consumption and economic growth have statistically significant positive effect on CO emissions both in the short-run and long-run. Among these three drivers, population density proves the main influencing factor of CO emissions changes. Therefore, a cautious population stabilization policy in the country would assist in reducing CO emissions and sustaining long-run economic growth. The findings further support the continued policy actions to develop the alternative energy sources such as renewable, and to use green and clean technologies to curb CO emissions without reducing energy consumption. [ABSTRACT FROM AUTHOR]