• Journal of the Computational Structural Engineering Institute of Korea
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• v.26 no.5
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• pp.335-342
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• 2013

Since the seriousness of environmental pollution came to the fore recently, various efforts have been made globally for the reduction of the environmental load. In particular, in the field of construction, an industry responsible for a considerable amount of pollution, studies have been actively conducted to reduce $CO_2$ emissions and energy consumption. However, most conventional research about pollution as it relates to construction is focused on the maintenance stages where $CO_2$ emissions are the greatest. Research related to the design stage is in its infancy, as it has only been conducted thus far on steel buildings and RC buildings. In fact, in order to achieve environmentally friendly construction considering the Life Cycle Assessment(LCA), the building design should be derived to reduce the $CO_2$ emissions from the early building design stage, and structural engineers should be able to suggest a design plan considering its environmental friendliness. In this study, optimal structural design method for steel reinforced concrete(SRC) columns considering $CO_2$ emissions is presented. The trends of $CO_2$ emissions in SRC columns according to the variations of steel shapes, concrete strengths and loads are investigated.

• Journal of Climate Change Research
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• v.4 no.1
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• pp.27-39
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• 2013

In this study, the anthracite coal being used as fuel in Korea were classified into different types. These types include the domestically produced anthracite, imported anthracite used as raw material, and imported anthracite used as fuel. Each of the calorific values and greenhouse gas emission factors were calculated. The calculation of greenhouse gas emission factors resulted in the domestically produced anthracite as $111,477{\pm}4,508kg\;CO_2/TJ$, the imported anthracite used as raw material as $108,358{\pm}4,033kg\;CO_2/TJ$, and anthracite used as fuel was displayed as $103,927{\pm}8,367kg\;CO_2/TJ$. Additionally, the amount of greenhouse gas emission based on these calculated emission factors was displayed as $6,216,942ton\;CO_2$, which resulted as 12.7% lower than the green house gas emission amount which was calculated without distinguishing anthracite coal in details. Therefore, collecting activity data through a detailed classification of anthracites facilitate a more accurate calculation of greenhouse gas emission amount compared to collecting activity data through combination. Furthermore, since the anthracite coal used domestically possesses characteristics differing from the anthracite coal proposed by the IPCC, anthracite coal should be classified for each purpose and calculated for the improvement of the national greenhouse gas inventory.

• Journal of Environmental Policy
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• v.12 no.2
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• pp.33-57
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• 2013

This paper test the relationship among determinants of environmental investments, level of environmental investments, eco-efficiency (carbon productivity). The results show that profitability, leverage and R&D costs have a negative impact on environmental investments, and controlling ownership have a positive impact on environmental investments as well as environmental protection costs. The analysis also show that firms increasing environmental investments are able to gain superior environmental performance ($CO_2$ emission), but are negatively relationship with financial performance. Finally, the findings prove that differences exist in the relationship between determinants and effect of environmental investments when grouped by industry characteristics.

• Environmental and Resource Economics Review
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• v.19 no.4
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• pp.733-752
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• 2010

This study applies the Luenberger indicator approach to estimate productivity of the Korean fossil-fueled power plants. A panel data set of 25 power plants was used. The method incorporates $CO_2$ emission as an undesirable output and shows that ignoring $CO_2$ emission overestimates the productivity change. There are two sources of overestimation. First, the usual method estimates productivity change ignoring the increase in $CO_2$ emission that occurred during the study period. Second, the productivity change estimated by the usual method that does not incorporate $CO_2$ emission is very sensitively affected by the change in operation rate. The paper decomposes the productivity change into the efficiency change and the technical change. The results show that the two sources contribute to the productivity change almost equally. It is also shown that the size and the pattern of productivity change are dependent on the plants' fuel types. Non-LNG power plants which saved their energy consumption and thereby reduced their $CO_2$ emission have achieved relatively high rate of productivity improvement.

• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.73-73
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• 2019

지구 표면의 약 2%에 해당하는 담수에서 육상계 전체가 흡수하는 탄소의 50%가 배출되며, 이는 토양표면에서 배출되는 탄소량에 비해 더 큰 수치로 전 지구적 탄소순환 해석에 중요한 역할을 한다. 특히, 내륙수역과 대기의 경계면에서 $CO_2$ 이동은 전 지구적 탄소순환의 중요한 구성요소로 평가되고 있다. 호수와 저수지 같은 담수 저류시설은 육상에서 기인한 탄소의 운송 및 처리 역할을 한다. 하지만, 저수지에서 온실가스배출량을 평가할 수 있는 명확한 방법론이 부족하며, 전지구 규모 GHGs배출량에 대한 추정에 대한 불확실성이 상당히 큰 상황이다. 본 연구에서는 몬순기후대에 위치한 인공저수지를 대상으로 보다 신뢰도있는 온실가스 배출량 추정을 위해 $CO_2$ NAF 산정하고, 산정에 영향을 미치는 인자들을 분석 하였다. 분석을 위해 $CO_2$ NAF 산정에 필요한 수리 및 수질 인자들을 2017년부터 2018년까지 수집하고, 기초통계량 및 상관분석을 실시하였다. 또한, 주성분분석(PCA) 및 다중선형회귀모델(MLR)과 랜덤포레스트(RF) 기법을 사용해 변수 중요도를 평가하였으며, $CO_2$ NAF 산정 주요인자인 기체교환 계수를 경험적 모델 3종(Cole and Caraco, Crusius, Vachon), 표면갱신형 모델 4종(Heiskanen, Maclntyre, Read, Soloviev)을 비교, 검토하였다. 조사기간 동안 기체교환계수 산정 결과 Crusius 모델 예측값이 평균 $0.342(0.047{\sim}4.323)cm\;hr^{-1}$으로 검토한 모델중 가장 낮은 평균값을 보였으며, Heiskane 모델이 $2.135(0.337{\sim}5.152)cm\;hr^{-1}$으로 가장 큰 평균값을 보였다. 대상 수체는 연주기로 완전혼합되며 수온성층이 약화되는 시기에 저수지 표층 아래에 축적된 탄소가 표층으로 전달되어 높은 수준의 p$CO_2$를 보이며, 수표면에 큰 난류 강도가 작용하는 기간에 대기중으로 배출(pulse emission) 기작이 나타난다. NAF 산정결과 경험적 모델의 NAF값($-1246.0{\sim}6510.3mg-CO_2m^{-2}day^{-1}$)은 표면갱신형 모델 NAF값($-1436.1{\sim}8485.7mg-CO_2m^{-2}day^{-1}$)보다 낮은 수준을 보였으며, 풍속의 함수만을 이용하는 경험적 모델보다 부력 플럭스와 난류 혼합의 영향을 고려하는 Macintyre, Heiskanen모델이 성층 저수지의 $CO_2$ NAF 산정에 적합한 것으로 나타났다. $CO_2$ NAF 산정의 주요인자로 MLR모델은 Tw, EC, pH, Chla, TOC, Alk, RF모델은 EC, DO, TOC가 중요 변수로 평가되었다. PCA 분석결과, 수온이 낮고 성층이 약화되며 pH가 낮은 상태에서 NAF가 큰 것으로 나타났다.

• Convergence Security Journal
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• v.13 no.3
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• pp.39-46
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• 2013

Recently, the problem of global warming has become a globally important issues. and To solve these problems, has been receiving increasing attention for the Green IT. In these situation, IT techniques are evolving with variety services and hacking techniques. so, it is inevitable to the use of a many and diverse secure system. As a result, Carbon Dioxide emissions are expected to increase. Therefore, in this paper is analyzed the factors of security system's $CO_2$ emissions through Experiments and A case study. and is proved that is reducing $CO_2$ emissions by improving the functional restructuring of the security system. In a future, this paper is expected to serve as a valuable Information for security network design and performance improvements and to reduce Carbon Emissions in the Field of IT.

• Journal of Energy Engineering
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• v.28 no.2
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• pp.1-17
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• 2019

This article analyzes causal relationships among gross domestic product(GDP), electricity consumption, carbon dioxide($CO_2$) emission and foreign direct investments(FDI) inflow of Korea over the period from 1976 to 2014, using unit root test, cointegration test, and vector error correction model(VECM). As the results, this article found (1) a long-run bi-directional causality between GDP and electricity consumption, which may imply a negative impact of electricity consumption-saving policy on economic growth, (2) uni-directional short- and long-run causalities running from $CO_2$ emission to GDP, and a uni-directional long-run causality running from $CO_2$ emission to electricity consumption, which can result in a negative impact of $CO_2$ emission reduction policy on economic growth and electricity consumption, (3) a uni-directional long-run causality running from FDI to GDP, and uni-directional short- and long-run causalities running from FDI to electricity consumption, which may result from relatively lower electricity prices than investing countries, (4) no causality between FDI and $CO_2$ emission, which is based on the characteristics of FDI composed of service industries. Considering the above causal relationships among the four variables, the policy implication needs to focus on the electricity demand management based on the relevant R&Ds, and on the gradual transition from fossil fuel- to renewable-energy. Adaptive policy to increase the FDI inflow is also needed.

• Journal of Climate Change Research
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• v.4 no.4
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• pp.359-369
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• 2013

In this paper, correlations between driving parameters and $CO_2$ of light-duty vehicles have been analyzed. Three test vehicles equipped with PEMS (Portable Emission Measurement System) have been driven in real-road in urban areas of Seoul. Averaged vehicle speed, RPA(Relative Positive Acceleration) and stop ratio have been selected as main driving parameters. The analysis have been conducted in interrupted and uninterrupted road types. Averaged values in various driving conditions have been calculated with distance based moving averaging window method. The multiple linear regression method have been applied to account for correlation between driving parameters and $CO_2$ emissions. This approach has shown statistically that $CO_2$ emission per distance (g/km) have tendencies to be increased as decreased averaged vehicle speed and increased RPA and stop ratio. Compared with uninterrupted traffic, interrupted traffic have shown the lower vehicle speed and the higher RPA and stop ratio. These characteristics of driving parameters in interrupted traffic should cause the higher $CO_2$ emission per distance.

• Environmental and Resource Economics Review
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• v.15 no.4
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• pp.591-642
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• 2006

This paper intends to analyze economic impacts of commitment period and initial allocation in emissions trading using computable general equilibrium (CGE) modeling. The fully dynamic CGE model with perfect foresight assumption is employed to illustrate (i) how a model displays economic impact of $CO_2$ regulation upon different commitment periods: one-year budget clearing vs. 5-year commitment period, (ii) how major 8 energy-intensive industries respond to different ways to allocate initial allowances. According to the results of the analysis, it IS found that market players are motivated to bank the permits and tend to sell permits in earlier stage and to buy permits in later stage of commitment period. This implies that banking allows permit trading within a commitment period, which supports the conclusions of Kling and Rubin (1997). Other findings are related to efficiency. That is, emissions trading surpasses command and control, in terms of economic efficiency and longer terms of commitment period converge on lower permit price, In long term, initial allocation based on value-added performs the lowest GDP loss among different initial allocations.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.29 no.5
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• pp.429-436
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• 2016

In this study, the genetic algorithm based optimal structural design method is proposed. The objective functions are to minimize the cost and $CO_2$ emissions, simultaneously. The cost and $CO_2$ emissions are calculated based on the cross-sectional dimensions, length, material strength, and reinforcement ratio of beam and column members. Thus, the cost and $CO_2$ emissions are evaluated by using the amounts of concrete and reinforcement used to construct a building. In this study, the cost and $CO_2$ emissions calculated at the phases of material transportation, construction, and building operation are excluded. The constraint conditions on the strength of beam and column members and the inter-story drift ratio are considered. The linear static analysis by using OpenSees is automatically conducted in the proposed method. The genetic algorithm is employed to solve the formulated problem. The proposed method is validated by applying it to the 4-story reinforced concrete moment frame example.