Energy Consumption in Tunisia over 1990–2008: A Decomposition Analysis Using Logarithmic Mean Divisia Index Technique

2015 ◽  
pp. 147-161
Author(s):  
Sana Essaber Jouini
Energy ◽  
2014 ◽  
Vol 67 ◽  
pp. 617-622 ◽  
Author(s):  
Wenwen Wang ◽  
Xiao Liu ◽  
Ming Zhang ◽  
Xuefeng Song

2021 ◽  
Vol 13 (16) ◽  
pp. 9285
Author(s):  
Yueyue Rong ◽  
Junsong Jia ◽  
Min Ju ◽  
Chundi Chen ◽  
Yangming Zhou ◽  
...  

Currently, household carbon dioxide (CO2) emissions (HCEs) as one of the leading sources of greenhouse gas (GHG) have drawn notable scholarly concern. Thus, here, taking six provinces in the period of 2000–2017 of Central China as a case, we analyzed the characteristics and the driving factors of HCEs from direct energy consumption and three perspectives: Central China as a whole, urban-rural differences, and inter-provincial comparison. The drivers of direct HCEs were analyzed by the Logarithmic Mean Divisia Index (LMDI). The σ convergence was adopted for analyzing the trend of inter-provincial differences on the HCEs. The key findings are as follows. First, all the direct HCEs from three perspectives had an obvious growth trend. The total direct HCEs grew from 9596.20 × 104 tonnes in 2000 to 30,318.35 × 104 tonnes in 2017, with an increase of 2.16 times. Electricity and coal use were the primary sources. The urban and rural increases of direct HCEs were up 2.57 times and 1.77 times, respectively. The urban-rural gap of direct HCEs narrowed first and then widened. The direct HCEs in the six provinces varied significantly, but the gap was narrowing. Second, as a whole the per capita consumption expenditure and energy demand were the main drivers to the increment of HCEs, with cumulative contribution rates of 118.19% and 59.90%. The energy price effect was mainly responsible for the mitigation of HCEs. Third, the similar drivers’ trend can also be seen from the perspective of inter-provincial comparison. However, from the perspective of urban and rural difference, the population urban-rural structure effect played a reverse influence on both urban and rural areas. Thus, raising the energy prices appropriately, upgrading the residents’ consumption to a sustainable pattern, controlling the growth of population size reasonably, and optimizing the household energy structure might effectively mitigate the growth of HCEs in Central China.


2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Jiandong Chen ◽  
Ming Gao ◽  
Ding Li ◽  
Malin Song ◽  
Qianjiao Xie ◽  
...  

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.


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