• Journal of Climate Change Research
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• v.8 no.4
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• pp.357-367
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• 2017

Electricity generation in Korea mainly depends on thermal power and nuclear power. Especially the coal power has led to the increase in $CO_2$ emissions. This paper intends to analyze the current status of $CO_2$ emissions from electricity generation in Korea during the period 1990~2016, and apply the logarithmic mean Divisia index (LMDI) technique to find the nature of the factors influencing the changes in $CO_2$ emissions. The main results as follows: first, $CO_2$ emission from electricity generation has increased by $165.9MtCO_2$ during the period of analysis. Coal products is the main fuel type for thermal power generation, which accounts about 73% $CO_2$ emissions from electricity generation. Secondly, the increase of real GDP is the most important contributor to increase $CO_2$ emissions from electricity generation. The carbon intensity and the electricity intensity also affected the increase in $CO_2$ emission, but the energy intensity effect and the dependency of thermal power effect play the dominant role in decreasing $CO_2$ emissions.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.5
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• pp.1871-1885
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• 2013

In this study, spatio-temporal distribution of future drought in South Korea was predicted by using the meteorological data generated from GCMs on which a variety of climate changing scenarios are applied. Drought phenomena was quantitatively analyzed using SPI(Standardized Precipitation Index). In addition, potential drought hazard maps for different drought duration and return period were made for the South Koreaby drought frequency analysis after deriving SDF(Severity-Duration-Frequency) curves using the 54 weather stations throughout the country. From the potential drought hazard maps, drought is expected to be severer in Nakdong River basin and Seomjin River basin under A2 scenario. It was also predicted that drought would be severe in the Han River basin by RCP8.5 scenario. In the future, potential drought hazard area would be expanded until the Eastern part of Nakdong River basin as compared with that of past under A2 scenario condition. Research results indicated that future drought would be extensively occurred all areas of South Korea not limiting in the southern part of country.

• Korean Chemical Engineering Research
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• v.47 no.1
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• pp.65-71
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• 2009

In this study, performance and economic analysis of natural gas/syngas fueled 100 MWth chemical-looping combustion (CLC) combined cycle plant were performed. Net efficiency of both cases was 53~54%, corresponding to previous research. We used Chemical Engineering Plant Cost Index and Guthrie method to evaluate plant cost. For syngas fueled CLC combined cycle plant, the plant cost was higher since lower heating value(LHV) of syngas was lower than that of natural gas and cost of electricity(COE) was also higher since the cost of syngas was higher than that of natural gas. By sensitivity analysis, it was shown that the cost of syngas should be less than 5.3 $/GJ in order to make COE lower than 5.8 ¢/kWh which was COE of natural gas fueled CLC combined cycle plant.

• Journal of the Korean Geographical Society
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• v.33 no.3
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• pp.377-394
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• 1998

The magnetic record of loess deposits may be one of the most detailed and useful records of Quatermary climate change on the continents. Stratigraphic variations of magnetic parameters define alternating zones of high and low concentrations of magnetic minerals. All the concentration-sensitive magnetic parameters show an increase within the interstadial Gilman Canyon Formation and interglacial Brady soil and a systematic decrease within the Wisconsinan Peoria loess. The influence of climate change on magnetic records is confirmed by a high correlation between the magnetic parameters and biological proxies. Rock magnetic data appear to be better correlated with temperature-sensitive biological proxies than does a precipitation-sensitive index such as the aridity index derived from opal phytoliths. Simultaneous, higher resolution sampling of magnetic and biological proxies proved to be a better sampling tactic, and enhanced the feasibility of rock magnetic parameters as independent climate proxies.

• Korean Journal of Soil Science and Fertilizer
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• v.50 no.1
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• pp.1-11
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• 2017

In order to assess risk of high temperature damages about corn during reproduction stages in the future, we carried out analysis of climate change scenarios RCP (Representative Concentration Pathway) 4.5 and RCP8.5 distributed by KMA (Korea Meteorological Administration) in 2012. We established two indexes such as average of annual risk days of high temperature damage which express frequency and strengthen index of high temperature damage. As results of producing maps for 157 cities and counties about average of annual risk days of high temperature damage during total periods of scenarios, the risk of high temperature in RCP8.5 was evaluated to increase at all over nation except inland area of Gangwon province, while RCP4.5 showed similar to present, or little higher. The maps of annual risk days of high temperature damage with 10 years interval in RCP8.5 prospected that the risk for damaging corn growth would increase rapidly from 2030's. The largest risk of high temperature damage in the future of RCP8.5 was analyzed at Changnyeong county located east-south inland area in Kyeongnam province, while the smallest of risk counties were Pyeongchang, Taebaek, Inje, and Jeongseon. The prospect at 12 counties which is large to produce corn at present and contains large plains have been showed that there will be only a little increase of risk of high temperature at Goesan, Yangpyeong, Hongcheon, Seosan, and Mooju until 2060's. But considering strengthen index of high temperature damage, most regions analyzed would be prospected to increase rapidly after 2030's. To cope with high temperature damage of corn in the future, we should develop various practical technologies including breeding adapted varieties and controlling cultivation periods.

• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.334-334
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• 2019

기후변화에 능동적으로 대처하기 위해서는 기후변화에 따른 수자원가용량의 변화를 정량적으로 평가할 수 있어야 한다. 평가결과의 신뢰도를 높이기 위해서 기후변화 시나리오는 지역기후 및 유역특성에 적합한 결과를 포함하여야 한다. 또한, 기후변화가 유역의 물순환계에 미치는 영향이 있다면, 물순환 개선 기술을 통해 지속가능한 유역 물환경을 구축하는 것이 필요하다. 유역 물순환 개선 기술은 기후변화가 진행 중에 있거나 예상되는 지역에 대하여 강우로부터 발생되는 유출을 지연, 저류, 침투시켜 지속가능한 물순환 체계를 유지하고 회복하도록 하는 기법이라 할 수 있다. 한국건설기술연구원에서는 기후변화에 따른 영향을 평가하고 적응 대책을 수립하기 위한 실무적인 유역 물순환 개선 및 평가 모형인 CAT3(Catchment hydrologic cycle Assessment Tool 3)을 개발하였으며 본 모형은 침투시설, 저류시설, 습지, 빗물저장시설과 같은 물순환 개선시설에 대한 효과를 정량적으로 평가할 수 있다. 본 연구에서는 팔당댐 상류의 경안천 유역을 대상으로 APCC 기후변화 시나리오 통계적 상세화 자료를 활용하여 물순환 개선 기술의 적용성을 평가하였다. 통계적 상세화 자료는 APCC에서 개발된 AIMS(APCC Integrated Modeling Solution) 플랫폼을 이용하였다. AIMS는 다양한 기후정보를 기반으로 사용자 관점에서 상세화를 수행할 수 있는 장점이 있다. 상세화 기법은 SDQDM(Spatial Disaggregation Quantile Delta Mapping) 방법을 이용하였다. 상세화된 기후자료는 과거자료의 재현성 및 미래 기간에 대한 왜곡도를 평가하기 위해 극한기후지수(Climate Index)를 이용하는데 본 연구에서는 장기간에 걸친 수자원가용량의 평가 및 예측을 위해 연강수량(PRCPTOT)을 사용하였으며 증발산량의 평가 및 예측에 영향을 미치는 온도 관련 극한기후지수는 평균기온 개념의 DTR(TMAX&TMIN)을 이용하였다. 통계적 상세화 과정을 통해 최종적으로 HadGEM2-CC, INMCM4, CanESM2 시나리오를 선택하였으며 각 시나리오별 물순환 개선 기술을 적용한 후 미래의 수문학적 변동성을 평가하였다.

• Proceedings of the National Institute of Ecology of the Republic of Korea
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• v.3 no.3
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• pp.149-153
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• 2022

The degree distribution of the plant-pollinator network was identified by analyzing the data in the ecosystem and reproduced by a model of the growing bipartite mutualistic networks. The degree distribution of pollinator shows power law or stretched exponential distribution, while plant usually shows stretched exponential distribution. In the growth model, the plant and the pollinator are selected with probability P_p and P_A=1-P_p, respectively. The number of incoming links for the plant and the pollinator is l_p and l_A, respectively. The probability that the link of the plant selects the pollinator of the existing network given as $A_{k_i}=k^{{\lambda}_A}_i/{\sum}_i\;k^{{\lambda}_A}_i$, and the probability that the pollinator selects the plant is $P_{k_i}=k^{{\lambda}_p}_i/{\sum}_i\;k^{{\lambda}_p}_i$. When the nonlinear growth index is 𝛌_X=1 (X=A or P), the degree distribution follows a power law, and if 0≤𝛌_X<1, the degree distribution follows a stretched exponential distribution. The cumulative degree distributions of plants and pollinators of 14 empirical plant-pollinators included in Interaction Web Database were calculated. A set of parameters (P_A,P_P,l_A,l_P) that reproduces these cumulative degree distributions and a growth index 𝛌_X (X=A or P) were obtained. We found that animal takes very heterogenous connections, whereas plant takes a more flexible connection network.

• Korean Journal of Environment and Ecology
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• v.25 no.6
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• pp.903-910
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• 2011

The research was carried out in order to find climate factors which determine the distribution of Machilus thunbergii, and the potential habitats under the current climate and three climate change scenario by using classification tree (CT) model. Four climate factors; the minimum temperature of the coldest month (TMC), the warmth index (WI), summer precipitation (PRS), and winter precipition (PRW) : were used as independent variables for the model. The model of distribution for Machilus thunbergii (Mth-model) constructed by CT analysis showed that minimum temperature of the coldest month (TMC) is a major climate factor in determining the distribution of M. thunbergii. The area above the $-3.3^{\circ}C$ of TMC revealed high occurrence probability of the M. thunbergii. Potential habitats was predicted $9,326km^2$ under the current climate and $61,074{\sim}67,402km^2$(South Korea: $58,419{\sim}61,137km^2$, North Korea: $2,655{\sim}6,542km^2$) under the three climate change scenarios (CCCMA-A2, CSIRO-A2, HADCM3-A2). The Potential habitats was to predicted increase by 51~56%(South Korea: 49~51%, North Korea: 2~5%) under the three climate change scenarios. The potential expand of M. thunbergii habitats has been expected that it is competitive with warm-temperate deciduous broadleaf forest. M. thunbergii is evaluated as the indicator of climate change in Korea and it is necessary for M. thunbergii to monitor of potential habitats.

• Journal of Korea Water Resources Association
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• v.48 no.4
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• pp.309-319
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• 2015

River characteristics in South Korea has been affected by seasonal climatic variability due to climate change and by remarkable land cover change due to rapid economic growth. In this regard, the roles of river management is getting more important to eco-system and human community in watersheds of South Korea. Understanding river characteristics including direct runoff and baseflow, the first step of river management, can give a significant contribution to sustainable river environment. Therefore, the objective of this study is to quantify the contributions of the direct runoff and baseflow to river streamflow. For this, we used the BFLOW and WHAT programs to conduct baseflow separation for 71 streamflow gauge stations in Han River system, South Korea. The results showed that baseflow index for 71 stations ranges from 0.42 to 0.78. Also, gauge stations which have baseflow index more than 0.5 occupied 76% of a total stations. However, baseflow index can be overestimated due to human impacts such as discharge from dams, reservoirs, and lakes. This study will be used as fundamental information to understand river characteristics in river management at the national level.

• Korean Journal of Remote Sensing
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• v.37 no.5_1
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• pp.959-974
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• 2021

Forel-Ule Index (FUI) is an index which classifies the colors of inland and seawater exist in nature into 21 gradesranging from indigo blue to cola brown. FUI has been analyzed in connection with the eutrophication, water quality, and light characteristics of water systems in many studies, and the possibility as a new water quality index which simultaneously contains optical information of water quality parameters has been suggested. In thisstudy, Ocean Colour-Climate Change Initiative (OC-CCI) based 4 km FUI was spatially downscaled to the resolution of 500 m using the Geostationary Ocean Color Imager (GOCI) data and Random Forest (RF) machine learning. Then, the RF-derived FUI was examined in terms of its correlation with various water quality parameters measured in coastal areas and its spatial distribution and seasonal characteristics. The results showed that the RF-derived FUI resulted in higher accuracy (Coefficient of Determination (R²)=0.81, Root Mean Square Error (RMSE)=0.7784) than GOCI-derived FUI estimated by Pitarch's OC-CCI FUI algorithm (R²=0.72, RMSE=0.9708). RF-derived FUI showed a high correlation with five water quality parameters including Total Nitrogen, Total Phosphorus, Chlorophyll-a, Total Suspended Solids, Transparency with the correlation coefficients of 0.87, 0.88, 0.97, 0.65, and -0.98, respectively. The temporal pattern of the RF-derived FUI well reflected the physical relationship with various water quality parameters with a strong seasonality. The research findingssuggested the potential of the high resolution FUI in coastal water quality management in the Korean Peninsula.