scholarly journals Study on influencing factors of carbon emissions for industrial energy consumption in Dalian based on LMDI model

2017 ◽  
Vol 64 ◽  
pp. 012043
Author(s):  
Bo Lai ◽  
Hongbo Zheng
Keyword(s):  
Energy Consumption ◽  
Influencing Factors ◽  
Carbon Emissions ◽  
Industrial Energy ◽  
Industrial Energy Consumption

The Study on Carbon Emission Influencing Factors of Industrial Energy Consumption of Changchun City

2012 ◽  
Vol 164 ◽  
pp. 302-305
Author(s):  
Zhuo Ma ◽  
Xiao Gang He ◽  
Xun Zhou Tong ◽  
Hai Yan Duan ◽  
Xian En Wang ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Influencing Factors ◽  
Carbon Emissions ◽  
Industrial Development ◽  
Carbon Emission ◽  
Low Carbon ◽  
Industrial Energy ◽  
Emission Changes ◽  
Major Factors ◽  
Industrial Energy Consumption

To make great efforts for energy saving and promote low-carbon transition of industrial development pattern have been the most crucial tasks for Changchun industrial developmen. Using Logarithmic Mean Divisia Index (LMDI) mode decomposes the carbon emission influencing factors of the industrial department in Changchun, and study on the effects of factors on the carbon emissions of industrial energy consumption. The result shows that the major factors for carbon emissions of industrial energy consumption in Changchun are economic development, the population size and the industrialization rate, and the key factors for the carbon emission changes in industrial department of Changchun are the energy consumption structure and the energy intensity.

Analysis of Hubei Province Industry’s Carbon Emissions Based on the LMDI

2014 ◽  
Vol 675-677 ◽  
pp. 1865-1868 ◽  
Author(s):  
Han Li ◽  
Lin Wu
Keyword(s):  
Energy Consumption ◽  
Carbon Emissions ◽  
Hubei Province ◽  
Hunan Province ◽  
Carbon Intensity ◽  
Logarithmic Mean ◽  
Coal Consumption ◽  
Industrial Carbon ◽  
Industrial Energy ◽  
Industrial Energy Consumption

LMDI (Logarithmic Mean Divisia Index) was used to estimates the carbon emission of industrial energy consumption in Hunan Province with collected data on industrial energy consumption in 2000-2012. The results showed that carbon emissions of industrial energy consumption present the overall upward trend in Hubei Province, where the carbon emissions of coal consumption are the main factors, this shows that the industry of Hubei is extensive development withhigh energy consumption. In addition, industrial carbon intensity has a fluctuated downward trend in 2011-2012; this shows that Hubei province has made ​​a positive change on control carbon emissions of energy consumption.

Accounting of Carbon Emissions in Key Fields of Dongying City, Shandong Province

2013 ◽  
Vol 361-363 ◽  
pp. 123-126
Author(s):  
Zi Jun Li ◽  
Can Juan Gong
Keyword(s):  
Energy Consumption ◽  
Carbon Emissions ◽  
Emission Reduction ◽  
Carbon Emission ◽  
Statistical Data ◽  
Low Carbon ◽  
Industrial Energy ◽  
Dongying City ◽  
Industrial Energy Consumption ◽  
Important Significance

Industry, construction and transportation are the key fields of carbon emission. Based on the reality of Dongying City, and combined with relevant statistical data, carbon emissions in industry, construction and transportation of Dongying City are accounted objectively. The results show that carbon emission in key fields of Dongying City has a fast increasing tendency from 2005 to 2009. Among which, carbon emissions of industry account for the largest proportion with the five-year average of 82.04%, followed by the construction and transportation, with the five-year average of 12.77% and 5.19% respectively. Therefore, adjusting and optimizing industrial energy consumption in the key fields is crucial to carbon emission reduction of Dongying City. This has an important significance for Dongying City to achieve energy conservation, emission reduction and build a low-carbon ecological city.

Industrial Carbon Emissions Accounting from Energy and Non-Energy Consumption and Input-Output Model Construction for Trans-Sector Carbon Emissions Shift Assessment, China

2013 ◽  
Vol 703 ◽  
pp. 328-331
Author(s):  
Shun Shun Yang ◽  
Huan Zhi Wang
Keyword(s):  
Energy Consumption ◽  
Carbon Emissions ◽  
Industrial Process ◽  
Input Output ◽  
Output Analysis ◽  
Industrial Carbon ◽  
Industrial Energy ◽  
Carbon Emissions Accounting ◽  
Improved Model ◽  
Industrial Energy Consumption

This paper describes an industrial energy combustion use and industrial process emissions accounting method. By utilizing three set of widely used energy combustion carbon emission factors, Chinas industrial energy consumption carbon emissions are calculated. By using the methods provided by the IPCC, the industrial process carbon emissions for extractive industries, chemical industries and metal industries are calculated. The results show that in 2010 China's industrial energy consumption carbon emissions reached approximately 6.91×108 t C (2.53×109 t CO2), 85% from coal burning. The industrial process emitted approximately 9.47×108 t C (3.48×109 t CO2). About 5.55×108 t C (2.04×109 t CO2) is emitted by providing heat and power to industrial processes. In addition, this paper also proposed an improved model coupling industrial carbon emissions data and input-output analysis. It will help to quantify and evaluate the trans-sector carbon emissions shift.

Carbon Emissions Measurement of Jiangsu Province Industrial Energy Consumption Based on LMDI Method

2014 ◽  
Vol 1010-1012 ◽  
pp. 1932-1936
Author(s):  
Sun Xi Xiao ◽  
Lin Wu
Keyword(s):  
Energy Consumption ◽  
Carbon Emissions ◽  
Carbon Emission ◽  
Scale Effects ◽  
Jiangsu Province ◽  
Intensity Effect ◽  
Industrial Carbon ◽  
Industrial Energy ◽  
Industrial Energy Consumption ◽  
Consumption Intensity

Energy consumption is the major source of industrial carbon emissions. Energy consumption carbon emission factor method and LMDI (Logarithmic Mean Divisia Index) method was used to analyze the carbon emission evolution of industrial economy energy consumption in Jiangsu Province with collected data on industrial energy consumption in 1995-2012. Results showed that Jiangsu province economic industrial carbon emissions keep increasing in 1995-2012 years. The results of carbon emission increase analysis of energy consumption structure effects, industrial energy consumption intensity effects and output scale effects in 1999-2012 showed that energy consumption intensity effect has the maximum contribution to carbon emissions in industrial carbon emissions Jiangsu Province. Therefore, the main way to control carbon emissions of industrial energy consumption in Jiangsu Province is reasonably control the growth of energy consumption.

Performance and decomposition analyses of carbon emissions from industrial energy consumption in Tianjin, China

2014 ◽  
Vol 64 ◽  
pp. 590-601 ◽  
Author(s):  
Chaofeng Shao ◽  
Yang Guan ◽  
Zheng Wan ◽  
Caixia Guo ◽  
Chunli Chu ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Carbon Emissions ◽  
Industrial Energy ◽  
Industrial Energy Consumption

scholarly journals The carbon emissions of Chinese cities

2012 ◽  
Vol 12 (3) ◽  
pp. 7985-8007 ◽  
Author(s):  
H. Wang ◽  
J. Bi ◽  
R. Zhang ◽  
M. Liu
Keyword(s):  
Economic Growth ◽  
Energy Consumption ◽  
Carbon Emissions ◽  
Carbon Emission ◽  
Industrial Processes ◽  
Emission Inventories ◽  
Chinese Cities ◽  
Industrial Energy ◽  
Per Capita ◽  
Industrial Energy Consumption

Abstract. As increasing urbanization has become a national policy priority for economic growth in China, cities have become important players in efforts to reduce carbon emissions. However, their efforts have been hampered by the lack of specific and comparable carbon emission inventories. Comprehensive carbon emission inventories, which present both a relatively current snapshot and also show how emissions have changed over the past several years, of twelve Chinese cities were developed using bottom-up approach. Carbon emissions in most of Chinese cities rose along with economic growth from 2004 to 2008. Yet per capita carbon emissions varied between the highest and lowest emitting cities by a factor of nearly 7. Average per capita carbon emissions varied across sectors, including industrial energy consumption (64.3%), industrial processes (10.2%), transportation (10.6%), household energy consumption (8.0%), commercial energy consumption (4.3%) and waste processing (2.5%). The levels of per capita carbon emissions in China's cities were higher than we anticipated before comparing them with the average of global cities. This is mainly due to the major contribution of industry sector encompassing industrial energy consumption and industrial processes to the total carbon emissions of Chinese cities.

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