Search

The excessive carbon emissions not only intensify the global climate change, but also seriously restrict the sustainable development of social economy. However, improving industrial carbon emissions efficiency is the most directly effective way to reduce emissions. Therefore, accurate measurement and analysis of carbon emissions efficiency and evolution characteristics of China's industrial system is the basis for China to improve carbon emissions efficiency. Based on this, we adopted energy consumption method and input-output method to calculate and analyze the industrial carbon emissions efficiency and evolution characteristics of China from 2002 to 2015. The results show that (1) If carbon emissions from cement production are ignored and only energy-related carbon emissions are considered, the calculation results of carbon emissions efficiency of heavy industry will be overestimated about 30%. (2) Compared with 2002, China's industrial carbon emissions efficiency increased by about twice in 2015. Specifically, the optimization of carbon emissions efficiency in agriculture, construction, light industry and service industry is very obvious, which has increased by 5.65, 5.00, 4.69 and 4.68 times respectively; The optimization of carbon emissions efficiency in power sector, heavy industry, transportation and chemical industry was obvious, which increased by 2.55, 2.01, 1.86 and 1.47 times respectively; The carbon emissions efficiency of the fossil energy sector has decreased by 0.36 times. (3) The carbon emissions efficiency of various industries has significant differences. Among them, agriculture, service industry, light industry and construction industry are generally industries with higher carbon emissions efficiency, while power sector, fossil energy sector, transportation industry, chemical industry and heavy industry are generally industries with lower carbon emissions efficiency, especially power and fossil energy sectors. Based on these, this paper provides policy implications and scientific evidence for accurately improving carbon emissions efficiency from the perspective of carbon emissions efficiency. [ABSTRACT FROM AUTHOR]

Abstract: The automobile industry in China has rapidly developed in recent years which resulted in an increase in gasoline usage and greenhouse gas (GHG) emissions. Focus on climate change has also accelerated to grow pressure on reducing vehicle weight and improving fuel efficiency. Aluminum (Al) as a light metal has demonstrated a great potential for weight savings in applications such as engine blocks, cylinder heads, wheels, hoods, tailgates etc. However, primary Al production requires intensive energy and the cost of Al is more than traditional steel, which may affect the total benefits realized from using Al in automobiles. Therefore, it is very essential to conduct a study to quantify the life cycle GHG emissions and energy consumption if the plan is to achieve fleet-wide Al intensive vehicles. This paper describes a life cycle assessment (LCA) methodology and the general modeling assumptions used to evaluate the impact of Al intensive vehicle on GHG emissions and energy consumption. The results indicated that the reductions in life cycle GHG emissions and energy consumption were not significant when the maximum Al content in an automobile is 145 kg, which is the average level of Al usage in automobiles in North America. A neural network methodology was used to forecast the vehicle stock in China from 2010 to 2020 and a vehicle fleet model was established to track GHG emissions and energy consumption of the vehicle fleet. A material availability factor was also introduced into the LCA methodology to further assist decision makers in providing rational proposals for a widespread implementation of Al in automobiles. A sensitivity analysis was also conducted to study the impact of the Al content in a vehicle on the final outcomes. The GHG emissions and energy consumption could be further reduced when the Al content in an automobile increases. [ABSTRACT FROM AUTHOR]

Abstract: This paper uses multivariate co-integration Granger causality tests to investigate the correlations between carbon dioxide emissions, energy consumption and economic growth in China. Some researchers have argued that the adoption of a reduction in carbon dioxide emissions and energy consumption as a long term policy goal will result in a closed-form relationship, to the detriment of the economy. Therefore, a perspective that can make allowances for the fact that the exclusive pursuit of economic growth will increase energy consumption and CO2 emissions is required; to the extent that such growth will have adverse effects with regard to global climate change. [ABSTRACT FROM AUTHOR]