scholarly journals Extended Yearly LMDI Approaches: A Case Study of Energy Consumption

2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Jiandong Chen ◽  
Ming Gao ◽  
Ding Li ◽  
Malin Song ◽  
Qianjiao Xie ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Carbon Emissions ◽  
Environmental Research ◽  
Logarithmic Mean ◽  
Divisia Index ◽  
Amount Of Information ◽  
Annual Changes ◽  
Mathematical Relationships ◽  
Research Period

Although the logarithmic mean Divisia index (LMDI) approach has been widely used in the field of energy and environmental research, it has a shortcoming. Since the LMDI approach only focuses on the base year and reporting year, in situations in which the research period is long, the annual changes during the research period may be difficult to capture. In particular, if there were huge fluctuations in the indicators (such as the energy consumption and carbon emissions) or their drivers during the middle of a research period, a substantial amount of information about the fluctuations will be ignored. Therefore, we propose four extended yearly LMDI approaches, including pure LMDI, weighted LMDI, comprehensive LMDI, and scenario LMDI approaches to better capture fluctuations and compensate for the original LMDI approach’s shortcomings. Additionally, we found that there are mathematical relationships among the four extended LMDI approaches. We further compare these four approaches’ advantages, disadvantages, and applicable situations and analyze a case study on China’s energy consumption based on the four proposed approaches.

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.

scholarly journals Multi-scale decomposition of energy-related industrial carbon emission by an extended logarithmic mean Divisia index: a case study of Jiangxi, China

2019 ◽  
Vol 12 (8) ◽  
pp. 2161-2186 ◽  
Author(s):  
Junsong Jia ◽  
Huiyong Jian ◽  
Dongming Xie ◽  
Zhongyu Gu ◽  
Chundi Chen
Keyword(s):  
Carbon Emission ◽  
Logarithmic Mean ◽  
Divisia Index ◽  
Industrial Carbon ◽  
Multi Scale

scholarly journals Decomposition Analysis of Carbon Emissions from Energy Consumption in Beijing-Tianjin-Hebei, China: A Weighted-Combination Model Based on Logarithmic Mean Divisia Index and Shapley Value

2018 ◽  
Vol 10 (7) ◽  
pp. 2535 ◽  
Author(s):  
Yi Liang ◽  
Dongxiao Niu ◽  
Weiwei Zhou ◽  
Yingying Fan
Keyword(s):  
Economic Development ◽  
Energy Consumption ◽  
Carbon Emissions ◽  
Emission Reduction ◽  
Carbon Emission ◽  
Industrial Structure ◽  
Logarithmic Mean ◽  
Consumption Structure ◽  
Consumption Intensity ◽  
Weighted Combination

The Beijing-Tianjin-Hebei (B-T-H) region, who captures the national strategic highland in China, has drawn a great deal of attention due to the fog and haze condition and other environmental problems. Further, the high carbon emissions generated by energy consumption has restricted its further coordinated development seriously. In order to accurately analyze the potential influencing factors that contribute to the growth of energy consumption carbon emissions in the B-T-H region, this paper uses the carbon emission coefficient method to measure the carbon emissions of energy consumption in the B-T-H region, using a weighted combination based on Logarithmic Mean Divisia Index (LMDI) and Shapley Value (SV). The effects affecting carbon emissions during 2001–2013 caused from five aspects, including energy consumption structure, energy consumption intensity, industrial structure, economic development and population size, are quantitatively analyzed. The results indicated that: (1) The carbon emissions had shown a sustained growth trend in the B-T-H region on the whole, while the growth rates varied in the three areas. In detail, Hebei Province got the first place in carbon emissions growth, followed by Tianjin and Beijing; (2) economic development was the main driving force for the carbon emissions growth of energy consumption in B-T-H region. Energy consumption structure, population size and industrial structure promoted carbon emissions growth as well, but their effects weakened in turn and were less obvious than that of economic development; (3) energy consumption intensity had played a significant inhibitory role on the carbon emissions growth; (4) it was of great significance to ease the carbon emission-reduction pressure of the B-T-H region from the four aspects of upgrading industrial structure adjustment, making technological progress, optimizing the energy structure and building long-term carbon-emission-reduction mechanisms, so as to promote the coordinated low-carbon development.

CASE STUDY OF THE OPERATIONAL ENERGY CONSUMPTION AND CARBON EMISSIONS FROM A BUILDING IN NANJING BASED ON A SYSTEM DYNAMICS APPROACH

2016 ◽  
Vol 11 (3) ◽  
pp. 126-142
Author(s):  
Changhai Peng ◽  
Jianqiang Yang ◽  
Jinfu Huang
Keyword(s):  
Energy Consumption ◽  
System Dynamics ◽  
Carbon Emissions ◽  
Office Building ◽  
Qualitative And Quantitative ◽  
Operational Energy ◽  
The Difference ◽  
Global Energy Consumption ◽  
Sd Model

Buildings are responsible for more than forty percent of global energy consumption and as much as one third of global greenhouse gas emissions. Meanwhile, the energy conservation and exhaust reduction of a building can be easily understood by accurately calculating a building's carbon emissions during its operational stage. In the present study, a system dynamics (SD) approach to calculate the energy consumption and carbon emissions from a building during its operational stage is quantitatively developed through a case study on an office building in Nanjing. The obtained results demonstrate that: a) the difference between the results of SD and that of EnergyPlus is so small that a SD approach is acceptable; b) the variation between the real monitored data and that of simulation by SD and EnergyPlus is reasonable; c) the physical meanings of the variables in the SD model are clear; d) the parameters of the SD model and the relationships between the variables can be determined by a qualitative-and-quantitative combined analysis.

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