Analysis on the Influence Factors of CO2 Emission in France - Based on LMDI Approach

2012 ◽  
Vol 616-618 ◽  
pp. 1537-1540 ◽  
Author(s):  
Shuo Wang

This article uses Logarithmic Mean Divisia Index Method (LMDI) to analyze influence factors of emission in France during last 50 years, including energy use, GDP, carbon density, energy structure and population. Energy structure problem is proposed at the end of the article.

2016 ◽  
Vol 847 ◽  
pp. 321-327
Author(s):  
Yan Cui Cao ◽  
Feng Gao ◽  
Zhi Hong Wang ◽  
Xian Zheng Gong ◽  
Xiao Qing Li

Magnesium is a promising lightweight and green metallic engineering material, but the environmental impact of primary magnesium production stage, especially greenhouse gas (GHG) emissions cannot be ignored. In this study, the life cycle energy consumption and GHG emissions caused by the production of primary magnesium in the years of 2003-2013 in China were calculated; the factor decomposition was conducted to analyze the GHG emissions of magnesium production process by using logarithmic mean Divisia index method (LMDI), including energy GHG emission factors, energy structure, energy consumption per ton of primary magnesium, production, emissions per unit of dolomite and ferrosilicon, and dolomite and ferrosilicon consumptions per ton of primary magnesium. The results showed that GHG emissions of primary magnesium production increased 260.29*104 t CO2eq in total from 2003 to 2013. The variety magnesium production contributed the biggest part of GHG emissions, accounting for 418.17%. The energy structure took second place on the contribution of GHG emissions, accounting for-161.49%. The nest part was energy consumption per ton of primary magnesium, accounting for-138.97%. While, the contribution of energy GHG emission factors, emissions per unit of dolomite and ferrosilicon, and dolomite and ferrosilicon consumptions per ton of primary magnesium was relatively small, which were 0.88%, 0.00% -2.72% -4.73% and-11.13%, respectively. Thus, it is the key methods to reduce GHG emissions by optimizing the energy structure and decreasing the energy consumption.


2014 ◽  
Vol 5 (5-6) ◽  
pp. 579-586 ◽  
Author(s):  
Jianyi Lin ◽  
Yuan Liu ◽  
Yuanchao Hu ◽  
Shenghui Cui ◽  
Shengnan Zhao

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.


Sign in / Sign up

Export Citation Format

Share Document