Based on the statistical data from 1997 to 2017, with utilization of IPCC carbon accounting method, Tapio decoupling model, and Logarithmic Mean Divisia Index (LMDI), temporal evolution characteristics Qinghai’s energy-related emissions, relationship, its driving factors were analyzed. The results indicated that 1) emissions Qinghai showed a trend first slowly increasing, then rapidly finally f...

In this paper, LMDI method is used to analyze the driving factors of industrial solid waste production in Yangtze River Economic Belt from 2005 2018, and decoupling state analyzed by Tapio indicator. We found that:①Industrial pollution intensity effect structure inhibited production, while regional output population size played a role increasing pollution; ②in different periods, states were wea...

China has a large manufacturing industry and shoulders the responsibility of reducing carbon emissions. Smart grid technologies can integrate multiple renewable energy technologies, which possess significant potential in To estimate emission reduction smart China’s industry, this paper applies temporal logarithmic mean Divisia index (LMDI) method to analyze driving forces changes whole 28 sub-i...

Forests and the forest products industry contribute to climate change mitigation by sequestering carbon from atmosphere storing it in biomass, fabricating that substitute other, more greenhouse-gas-emission-intensive materials energy. This study investigates primary wood-working industries (panel, furniture, pulp paper) order determine development of emissions China during last two decades. The...

The energy consumption of Korea’s manufacturing sector has sharply increased over the past 20 years. This paper decomposes the factors influencing energy consumption in this sector using the logarithmic mean Divisia index (LMDI) method and analyzes the specific characteristics of energy consumption from 1991 to 2011. The analysis reveals that the activity effect played a major role in increasin...