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Energy efficiency is one of the most powerful strategies to mitigate the impacts of climate change by reducing energy demand, which in turn reduces the emissions of Green House Gases (GHG), as well as reducing the burden on the supply side renewable generation expansion. Because electric motors systems represent such a large share of the overall electricity consumption (over 50%), large savings potential could be made available by the use of energy-efficient motor systems both in new installations and by accelerating the replacement of old inefficient motors. Since electric motors are very reliable, their lifetime is long (according to recent studies it may exceed 20 years) which translates into a very inefficient existing stock despite worldwide policy efforts. This paper analyzes the current efficiency of the installed stock and the causes for its low efficiency, possible policy options to increase its the efficiency, the role of new technologies and improvements possible by targeting the entire motor system at the time of motor replacement. The paper presents an innovative analysis of the estimated impact of increasing the uptake of high-efficiency motors and motor systems; effective policies could translate into 100 TWh/year in the European Union if additional measures, such as addressing oversizing, proper controls (VSDs) and digitisation, are also implemented. If similar measures were adopted globally, the savings triggered could be at least tenfold reaching over 1000 TWh/year. [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]