• Journal of Energy Engineering
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• v.27 no.3
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• pp.10-20
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• 2018

Due to cheap electricity tariff on agricultural use, electricity consumption in agricultural sector has grown dramatically. We evaluated the negative effects of the cheap electricity tariff such as electricity over-consumption, increased dependency on electricity, decreased electricity productivity, and unequal distribution of the benefit. We also estimated the effects of agricultral output growth, structural change, and electricity intensity change on sharp electricity consumption increase in agricultural sector between 1998 and 2016 using the Log Mean Divisia Index decomposition method. The findings reinforce the necessity of raising the electricity tariff for agricultural use.

• Environmental and Resource Economics Review
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• v.26 no.1
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• pp.1-35
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• 2017

This study investigates a decomposition analysis of the determinants of the reduced $CO_2$ emissions in seven OECD countries that implemented carbon taxes from 1995 to 2013. Recent studies on decomposition analysis of changes in $CO_2$ emissions focused on technology-based physical factors; however, this study analyzes the effects of a carbon tax as an economic factor. According to the results obtained by using the Log Mean Divisia Index, the energy intensity effect and the carbon tax effect contributed the most towards the reduction of total $CO_2$ emissions in the seven OECD countries. The results for each country show that the emissions decreased due to the energy intensity effect, while the effects of carbon tax and carbon tax revenues differed by policy and environment of the countries.

• Environmental and Resource Economics Review
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• v.19 no.2
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• pp.243-282
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• 2010

In this paper, we analyze the components and trends of carbon emissions using the Logarithmic Mean Divisia Index decomposition method in Korean electricity industry during the period 1991~2007. In the demand side, carbon emissions are affected by electricity intensity and structural shift and especially electricity intensity is identified as the major factor which has lead carbon emissions decreasing. In the supply side, the result in variations of carbon emission for electric power generation depends on the influences of fossil fuel mix, fuel intensity, generation mix and so on. As a result fuel intensity is the most negative effect on both carbon emission intensity and the amount of carbon emission while the change of generation mix has a positive effect on increasing carbon emissions. And to conclude it needs to make the strategic policies to improve electricity intensity in the demand and to rise emission efficiency as well as to substitute thermal power generation in supply side.

• Environmental and Resource Economics Review
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• v.24 no.1
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• pp.189-224
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• 2015

To meet sectoral emission target by 2020 and prepare for the emission trading scheme from 2015, decomposition analysis of energy consumption and GHG emission is required by 18 subsectors in industry sector where emission targets are established. Log Mean Divisia Index decomposition method was used to analyze factors' effects on energy and emission in the industry sector and by 18 subsectors from 2004 to 2011. Industrial energy consumption was increased due to the production effect and energy intensity effect. However structure effect contributes to the decrease of energy consumption. In terms of emissions (including indirect emission due to electricity consumption) in the industry sector, only structure effect contributed to the emission reduction. Factors' effects by subsectors were different. Cement industry, which is included at Nonmetal shows different results from those of Nonmetal industry and machinery industry, which is a subsector of Fabricated Metal, was also similar. In this regard, we should not apply the policy implications from decomposition analysis of aggregated industry such as Nonmetal or Fabricated Metal to its subsectors uniformly and develop a differentiated policy for each subsector industry.

• Journal of the Korean Society for Railway
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• v.15 no.3
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• pp.286-293
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• 2012

Korean government is enforcing 'Greenhouse gas target management' in order to achieve Greenhouse gas reduction target. To attain Greenhouse gas reduction target, companies in Korea must establish their GHG inventory system and analysis their GHG emissions characteristics for deduction of mitigation measures. LMDI(Log Mean Divisia Index) decomposition analysis is widely used to understand characteristics of GHG emission and energy consumption. In this paper, the characteristics of GHG emission from the line of railroad in Korea is respectively analyzed in terms of conversion effect, intensity effect, production effect and distance effect. Data of railroad GHG emission from 2000 to 2007 are used. As a result, total effect of railroad's GHG emission is $96,813tCO_2eq$. Production effect ($39,865tCO_2eq$) and distance effect ($327,923tCO_2eq$) affect increase of railroad GHG emissions while Conversion effect ($-158,161tCO_2eq$) and intensity effect ($-112,814tCO_2eq$) influence decrease of the emissions.

• Environmental and Resource Economics Review
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• v.10 no.4
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• pp.569-589
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• 2001

We examine historical contributions of inter fuel substitution, changes in carbon efficiency and energy intensity, growth of economy and population to Korea's $CO_2$ emissions from 1970 to 1998 using the log mean weight Divisia index method. The study reveals that economic growth is the most significant factor to $CO_2$ emissions growth among the five factors. Changes in the fuel substitution and carbon coefficient are found negative contributors to $CO_2$ emissions growth. Energy intensity, which played dominant role in halting $CO_2$ emissions growth in the 1980s, began to play reversed role in the 1990s. When evaluated with the log mean Divisia index technique, deterioration of energy intensity in the 1990s is found worse and expected to contribute $CO_2$ emissions growth further.

• Environmental and Resource Economics Review
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• v.18 no.4
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• pp.557-586
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• 2009

Although energy demand management policy attracts attention internationally and domestically, the importance of local government in this policy is not so much as central government. But local government can do a role with regard to this policy because it is close to energy consumers not like central government. So local energy plan should be based on the understanding local energy consumption characteristics to activate local energy demand management policy. This paper tries to analyze energy characteristics of 16 local governments by decomposing energy consumption into population, production and intensity factors. The result of index decomposition analysis shows that energy intensity improvement has offset the increase of energy consumption caused by economic growth in the metropolitan cities, while it couldn't offset in the other provinces because of industrialization based on the manufacturing. In conclusion, this paper suggests that it will be necessary to switch to low energy society by carrying out concrete energy efficiency improvement projects in the metropolitan cities while it will be helpful to make a local development plan for low energy intensive industrialization in the other provinces.