• 한국수자원학회논문집
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• 제40권3호
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• pp.191-204
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• 2007

본 연구에서는 기후변화가 국내 수자원에 미치는 영향을 평가하기 위해 고해상도($27km\;{\times}\;27km$)의 SRES A2 시나리오와 LARS-WG를 이용하여 국내 139개 소유역별 기후시나리오를 생산하였다. 본 연구에서 사용된 고해상도 시나리오는 약 350km 수평해상도의 ECHO-G 자료를 NCAR/PSU MM5를 이용하여 27km 수평해상도로 상세화한 것이다. A2 시나리오는 우리나라의 공간적 강수특성을 비교적 잘 모사하였으나, 한강과 금강유역의 강수량이 적게 모의되는 문제점을 보였다. 이러한 기후모형의 한계를 극복하고 유역스케일의 신뢰성 높은 기후시나리오를 생산하기 위해 일기상발생기인 LARS-WG를 선정하고 국내 기후모의에 대한 적요성을 평가하였다. LARS-WG를 이용한 기후모의 결과 월평균최대.최소기온과 월평균강수량은 관측치에 평균에서는 ${\pm}20%$, 표준편차에서는 ${\pm}50%$ 이내로 기후변화에 따른 수자원 영향평가의 목적으로 적용성이 높다고 판단되었다. 또한 LARS-WG를 이용하여 유역별 시나리오를 생산하고 관측치와 비교한 결과 기후모형에서 모의하지 못하는 지역적인 기후특성을 잘 반영하는 것으로 분석되었다.

• 한국기후변화학회지
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• 제6권1호
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• pp.1-10
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• 2015

Climate change lead to environmental pollution caused by the radical economic growth and development of industry. The amount of damage from abnormal climate is increasing rapidly for this reason in Korea. In particular, the cities is a lot of carbon emission quantity from the radical growth. Thus the government present "low carbon green growth" for eco-friendly city planning. As one of the important factors effecting climate change, active researches on land use change is performed. In this study, we knew land use change of each scenarios using land use equilibrium model which is kind of predictive model of land use in Japan. First, we selected study area to Jeju lsland. For this study, indicators for input data were selected and spatial data for input data were established using GIS program. Second, we established future scenarios based in 2040s. There are 2 future scenarios: dispersion scenario, compact scenario. Third, we compared with residential area of current and residential area for future scenarios. Results showed that residential area of the difference between current and dispersion scenario were 1,230 ha and residential area of the difference between current and compact scenario were 1,515 ha. Finally, for comparing carbon dioxide absorption volume between dispersion scenarios and compact scenarios, we calculated carbon dioxide absorption volume according to residential area decreased of each future scenarios. Results showed that carbon dioxide absorption volume in dispersion scenario was 477,878 ton and carbon dioxide absorption volume in compact scenario was 588,606 ton. Therefore, the study showed that land use equilibrium model is expected to put to use for future enhancement in creating data for climate change stabilization. And it is also expected to be utilized for city planning research in Korea.

• Communications for Statistical Applications and Methods
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• 제27권1호
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• pp.109-128
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• 2020

A climate-impact projection usually consists of several stages, and the uncertainty of the projection is known to be quite large. It is necessary to assess how much each stage contributed to the uncertainty. We call an uncertainty quantification method in which relative contribution of each stage can be evaluated as uncertainty decomposition. We propose a new Bayesian model for uncertainty decomposition in climate change impact assessments. The proposed Bayesian model can incorporate uncertainty of natural variability and utilize data in control period. We provide a simple and efficient Gibbs sampling algorithm using the auxiliary variable technique. We compare the proposed method with other existing uncertainty decomposition methods by analyzing streamflow data for Yongdam Dam basin located at Geum River in South Korea.

• 한국농공학회논문집
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• 제55권1호
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• pp.31-38
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• 2013

The purpose of this study was to evaluate climate change vulnerability over the agricultural infrastructure in terms of flood and drought using principal component analysis. Vulnerability was assessed using vulnerability resilience index (VRI) which combines climate exposure, sensitivity, and adaptive capacity. Ten flood proxy variables and six drought proxy variables for the vulnerability assessment were selected by opinions of researchers and experts. The statistical data on 16 proxy variables for the local governments (Si, Do) were collected. To identify major variables and to explain the trend in whole data set, principal component analysis (PCA) was conducted. The result of PCA showed that the first 3 principal components explained approximately 83 % and 89 % of the total variance for the flood and drought, respectively. VRI assessment for the local governments based on the PCA results indicated that provinces where having the relatively large cultivation areas were categorized as vulnerable to climate change.

• 한국수소및신에너지학회논문집
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• 제29권1호
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• pp.117-123
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• 2018

The long-term perception investigation of environment is needed for the persistence of each country's policy on climate change, which is greatly influenced by external factors. Long term data on perception and attitudes of people's thought can be a big data point for climate change and consistent policies can be implemented with the need for public demand. Information on the perception of the general public regarding the environment should be carried out as a basis for the national environmental policy.

• 국제학술발표논문집
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• The 6th International Conference on Construction Engineering and Project Management
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• pp.740-741
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• 2015

the downscaled air temperature data over study region for the projected 2001 - 2099 period were then ensemble averaged, and the ensemble averages of 6 realizations were compared against the corresponding historical downscaled data for the 1961 - 2000 period in order to assess the impact of climate change on air temperature over study region by graphical, spatial and statistical methods. In order to evaluate the seasonal trends under future climate change conditions, the simulated annual, annual DJF (December-January-February), and annual JJA (June-July-August) mean air temperature for 5 watersheds during historical and future periods were evaluated. From the results, it is clear that there is a rising trend in the projected air temperature and future air temperature would be warmer by about 3 degrees Celsius toward the end of 21^st century if the ensemble projections of air temperature become true. Spatial comparison of 30-year average annual mean air temperature between historical period (1970 - 1999) and ensemble average of 6-realization shows that air temperature is warmer toward end of 21^st century compared to historical period.

• 한국자원식물학회:학술대회논문집
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• 한국자원식물학회 2018년도 추계학술대회
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• pp.32-32
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• 2018

Flora investigations in Korea have been conducted by many researchers for diverse purposes. Accumulated flora investigation data has not been utilized efficiently because there is no accessible database for comparison. To overcome this shortcoming, we constructed web-based database of flora investigation, named as the Integrated Korean Flora Database (IKFD; http://www.floradb.net/intro.php). Until now, 284 flora references (263 papers, 14 reports and books, and 7 unpublished papers written in between 1962 and 2017) were digitalized into the database. From 134,711 records, 4,301 species belonging to 228 families and 1,079 genera were identified via mapping with two major Korean plant species lists. Polygon areas originated from references were used for distribution of plant species, identifying precise distribution area. It will be a better index to show plant ecological characteristics. Collected micro-climate data provided by Korea Meteorology Administration were also integrated in IFKD for understanding correlation between distribution of plants and micro-climate. Cold hardiness zone which has been utilized for classifying climate zones. 12 out of 26 zones identified based on micro-climate data in Korea were mapped with distribution of plants. More than half species were appeared in zone 6a, 6b, 7a, and 7b. Taken together with these results, IKFD will be a fundamental platform for understanding plants in Korea flora investigation as well as a new standard for classifying distribution of plants. Moreover, Biodiversity Observation Database (BODB; http://www.biodiversitydb.info/intro.php) which integrates plant distribution data was also integrated for further studies.

• 대한간호학회지
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• 제50권5호
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• pp.658-670
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• 2020

Purpose: This study aimed to identify the predictors of blood and body fluid exposure (BBFE) in multifaceted individual (sleep disturbance and fatigue), occupational (occupational stress), and organizational (hospital safety climate) factors, as well as infection prevention behavior. We also aimed to test the mediating effect of infection prevention behavior in relation to multifaceted factors and the frequency of BBFE. Methods: This study was based on a secondary data analysis, using data of 246 nurses from the Shift Work Nurses' Health and Turnover study. Based on the characteristics of zero-inflated and over-dispersed count data of frequencies of BBFE, the data were analyzed to calculate zero-inflated negative binomial regression within a generalized linear model and to test the mediating effect using SPSS 25.0, Stata 14.1, and PROCESS macro. Results: We found that the frequency of BBFE increased in subjects with disturbed sleep (IRR = 1.87, p = .049), and the probability of non-BBFE increased in subjects showing higher infection prevention behavior (IRR = 15.05, p = .006) and a hospital safety climate (IRR = 28.46, p = .018). We also found that infection prevention behavior had mediating effects on the occupational stress-BBFE and hospital safety climate-BBFE relationships. Conclusion: Sleep disturbance is an important risk factor related to frequency of BBFE, whereas preventive factors are infection prevention behavior and hospital safety climate. We suggest individual and systemic efforts to improve sleep, occupational stress, and hospital safety climate to prevent BBFE occurrence.

• 대한공간정보학회지
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• 제19권2호
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• pp.19-27
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• 2011

본 연구의 목적은 기후변화에 따른 잠재 산림분포 예측에 이용되는 기상 자료의 효과적인 구축 및 규모변환(Down Scaling) 방법을 제시 하는 것이다. 잠재 산림분포 예측을 위해 한국형 산림 분포 모형 TAG(Thermal Analogy Group)의 예측 방법과 HyTAG(Hydrological and Thermal Analogy Group)에서 정의한 식생 기능성 유형(PFT: Plant Functional Types)을 함께 적용하였다. 이를 위해 20km 공간해상도의 기상자료를 1km의 공간해상도에 부합하도록 보간 하였다. 이러한 보간 및 규모변환의 한 가지 방법으로 고도에 따른 기온감율을 적용 및 비적용하여 각각의 과거 잠재 산림분포를 예측하였다. 현존 산림분포도와 비교한 정확도 검증에서 기온감율을 적용한 잠재 산림분포가 약 38% 더 정확한 것으로 나타났다.

• 환경영향평가
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• 제20권4호
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• pp.523-538
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• 2011

This study analyzes the changes in the surface area of each forest cover, based on temperature data analysis and satellite imagery as the basic methods for the impact assessment of climate change on regional units. Furthermore, future changes in the forest cover are predicted using the double exponential smoothing method. The results of the study have shown an overall increase in annual mean temperature in the studied region since 1990, and an especially increased rate in winter and autumn compared to other seasons. The multi-temporal analysis of the changes in the forest cover using satellite images showed a large decrease of coniferous forests, and a continual increase in deciduous forests and mixed forests. Such changes are attributed to the increase in annual mean temperature of the studied regions. The analysis of changes in the surface area of each forest cover using the statistical data displayed similar tendencies as that of the forest cover categorizing results from the satellite images. Accordingly, rapid changes in forest cover following the increase of temperature in the studied regions could be expected. The results of the study of the forest cover surface using the double exponential smoothing method predict a continual decrease in coniferous forests until 2050. On the contrary, deciduous forests and mixed forests are predicted to show continually increasing tendencies. Deciduous forests have been predicted to increase the most in the future. With these results, the data on forest cover can be usefully applied as the main index for climate change. Further qualitative results are expected to be deduced from these data in the future, compared to the analyses of the relationship between tree species of forest and climate factors.