• 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.

• Journal of Climate Change Research
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• v.9 no.4
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• pp.407-421
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• 2018

In this paper, I analyze the GHG (greenhouse gas) emission factor of the domestic railway transportation sector using the LMDI (Log Mean Divisia Index) methodology. These GHG factors are the emission factor effect, energy intensity effect, transportation intensity effect, and economic activity effect. The analysis period was from 2011 to 2016, and the analysis objects were an intercity railway, wide area railway, and urban railway. The results show that the GHG emission of railway transportation sector decreased during these 6 years. The factors decreasing the GHG emission are the emission factor effect, energy intensity effect, and transportation intensity effect, while the factor increasing the GHG emission is the economic activity effect.

• 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.20 no.2
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• pp.229-254
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• 2011

In this paper, we decomposed Greenhouse-Gas emissions of Korea's manufacturing industry using LMDI (Log Mean Divisia Index) method. Changes in $CO_2$ emissions from 1991 to 2007 studied in 5 different factors, industrial production (production effect), industry production mix (structure effect), sectoral energy intensity (intensity effect), sectoral energy mix (energy-mix effect), and $CO_2$ emission factors (emission-factor effect). By results, the structure effect and intensity effect has a role of reducing GHG emissions and The role of structure effect was bigger than intensity effect. The energy mix effect increased GHG emissions and emission-factor effect decreased GHG emissions. By time series analysis, IMF regime affected the GHG emission pattern. the structure effect and intensity effect in that regime was getting worse. After 2000, in the high oil price period, the structure effect and intensity effect is getting better.

• Journal of Energy Engineering
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• v.24 no.1
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• pp.137-148
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• 2015

So far, the phenomenon of "electrification" has been deepened in Korean industry and especially direct heating energy which accounted for 44.0%(2010) of total energy consumed in Korean manufacturing has been significantly electrified. This paper decomposed electricity consumption for direct heating in Korean manufacturing from 1992 to 2012 using LMDI(Log Mean Divisia Index). This paper includes 4 different factors such as electricity proportion effect, direct heating proportion effect, energy intensity effect and added value effect. And this paper compared the consumption pattern by business type. As results, electricity proportion effect had contributed the most to the increase of electricity consumption for direct heating in Korean manufacturing. And Petrol-Chemical and Iron & Steel had the most electrification of direct heating.

• 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.

• 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.31 no.4
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• pp.825-848
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• 2022

This paper analyzed the factors for increasing energy consumption in the domestic manufacturing sector using the LMDI (Log mean division index) decomposition method for the period from 1999 to 2019. Among the LMDI decomposition analysis methods, both additive and multiplicative factor decomposition methods were used. in this analysis. According to the result of the analysis, the factor that increased energy consumption in the domestic manufacturing industry was the production effect, and the structure effect and intensity effect were found to be the factors that decreased energy consumption. In particular, the reduction of energy consumption due to the structure effect was greater than that of energy consumption effect due to the intensity effect. By period, it can be seen that energy consumption increased rapidly due to the production effect until 2011, but after that, the increase in energy consumption due to the production effect slowed down. On the other hand, after that, the energy reduction effect due to the structure effect and the intensity effect became prominent. In order to save energy in the manufacturing sector in the future, energy diagnosis and management through EMS (Energy management system) and FEMS (Factory energy management system) are more necessary. In addition, restructuring into a low-energy consumption industry seems more necessary.

• Journal of Korean Society on Water Environment
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• v.38 no.5
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• pp.240-246
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• 2022

Water and energy are inextricably linked and referred to as 'Water-Energy Nexus'. Recently, this topic has been drawing a lot of attention from various studies due to the exacerbated water availability. Korea's water and energy consumption has been increasing consistently, which calls for better management. This paper aims to identify changes in electricity consumption in relation to water intake and purification processes. Using Log Mean Divisia Index (LMDI) Decomposition Analysis method, this study attributes the changes to major factors such as; Total population (population effect), household/population (structure effect), GDP/household (economic effect), and water-related energy use/GDP (unit effect). The population effect, structure effect, and economic effect contributed to an increase in water-related electricity consumption, while the unit effect contributed to a decrease. As of 2019, the economic effect increased the water supply sector's electricity consumption by 534 GWh, the population effect increased by 73 GWh, and the structure effect increased by 243 GWh. In contrast, the unit effect decreased the electricity consumption by -461 GWh. We would like to make the following suggestions based on the findings of this study; first, the unit effect must be improved by increasing the energy efficiency of water intake and purification plants and installing renewable energy power generation facilities. Second, the structure effect is expected to increase over time, and to mitigate it, water consumption must be reduced through water conservation policies and the improvement of water facilities. Finally, the findings of this study are expected to be used as foundational data for integrated water and energy management.