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In the context of low-carbon economic development, carbon productivity has effectively integrated the two major objectives of carbon reduction and economic growth, and increasing carbon productivity has become the main approach to address global climate change. Using data from China's input–output table for 2002–2017, this study measures the evolutionary characteristics and influencing factors of carbon productivity from the perspective of embodied carbon emission in China's industrial sector. The results indicate that, first, China's industrial sectors' carbon productivity shows an increasing trend from 25.22 to 65.3 million yuan/10,000 tons of CO2 in 2002–2017, but the overall level is low. The energy efficiency factor is a major element affecting improvement in carbon productivity. Second, the carbon productivity of the 28 industrial sectors shows an increasing trend. There is a significant gap in the carbon productivity between different industrial sectors. The energy efficiency factor in all industrial sectors is positive, indicating that energy efficiency is a positive factor in increasing carbon productivity. Third, from largest to smallest in the carbon productivity are the primary, tertiary, and secondary industries. Finally, this paper recommends several approaches to improve carbon productivity from the perspectives of technology, differentiated policies of carbon emission reduction, and industrial structure adjustment. [ABSTRACT FROM AUTHOR]

With the convening of the annual global climate conference, the issue of global climate change has gradually become the focus of attention of the international community. As the largest carbon emitter in the world, China is facing a serious situation of carbon emission reduction. This paper uses the IPCC (The Intergovernmental Panel on Climate Change) method to calculate the carbon emissions of energy consumption in China from 1996 to 2016, and uses it as a dependent variable to analyze the influencing factors. In this paper, five factors, total population, per capita GDP (Gross Domestic Product), urbanization level, primary energy consumption structure, technology level, and industrial structure are selected as the influencing factors of carbon emissions. Based on the expanded STIRPAT (Stochastic Impacts by Regression on Population, Affluence, and Technology) model, the influencing degree of different factors on carbon emissions of energy consumption is analyzed. The results show that the order of impact on carbon emissions from high to low is total population, per capita GDP, technology level, industrial structure, primary energy consumption structure, and urbanization level. On the basis of the above research, the carbon emissions of China′s energy consumption in the future are predicted under eight different scenarios. The results show that, when the population and economy keep a low growth rate, while improving the technology level can effectively control carbon emissions from energy consumption, China′s carbon emissions from energy consumption will reach 302.82 million tons in 2020. [ABSTRACT FROM AUTHOR]

Abstract: The Chinese government has promulgated a wide variety of low-carbon initiatives to control the rapid growth of energy consumption and carbon emissions in the cities. Past records, however, show that the central government's policies are often poorly implemented or distorted by local officials. Using a case study from the city of Changchun, this paper examines how and why the issue of poor implementation persists despite the establishment of the Energy Conservation Target Responsibility System (ECTRS). As a key institutional mechanism providing local officials with political incentives to implement low-carbon policies, the ECTRS has been constrained by a number of problems, including a poorly designed scoring system, weak targets, the use of energy intensity instead of absolute energy consumption as a policy objective, and the lack of reliable local energy statistics. [Copyright &y& Elsevier]

The international community is facing the challenge of climate change, and the rapid increase of energy consumption plays a central role in the increasing carbon dioxide emissions. With 31 provinces, municipalities and autonomous regions in mainland China, this article establishes an impact model of carbon intensity, identifies key influencing factors on carbon intensity, and quantifies the effect of primary energy consumption, coal share, economic growth and technological innovation on carbon intensity in Eastern, Central and Western China. Results show that 1% of the increase in primary energy consumption in these three areas is attributable to a 0.738%, 0.975% and 0.742% increase in carbon intensity; 1% of the decrease in coal share is attributable to a 0.346%, 0.604% and 0.508% decrease in carbon intensity; and 1% of the increase in productivity efficiency should induce a 0.926%, 1.042% and 0.851% decline in carbon intensity, respectively. The results suggest that it is critical to integrate means for energy conservation, technological and productivity efficiency innovation, and adjust energy structure measures to fully implement a carbon intensity reduction strategy for China in the future. [ABSTRACT FROM AUTHOR]