• Title/Summary/Keyword: global climate model

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Sensitivity Analysis on Ecological Factors Affecting Forest Fire Spreading: Simulation Study (산불확산에 영향을 미치는 생태학적 요소들간의 민감도 분석: 시뮬레이션 연구)

  • Song, Hark-Soo;Lee, Sang-Hee
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.15 no.3
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    • pp.178-185
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    • 2013
  • Forest fires are expected to increase in severity and frequency under global climate change and thus better understanding of fire dynamics is critical for mitigation and adaptation. Researchers with different background, such as ecologists, physicists, and mathematical biologists, have developed various simulation models to reproduce forest fire spread dynamics. However, these models have limitations in the fire spreading because of the complicated factors such as fuel types, wind, and moisture. In this study, we suggested a simple model considering the wind effect and two different fuel types. The two fuels correspond to susceptible tree and resistant tree with different probabilities of transferring fire. The trees were randomly distributed in simulation space with a density ranging from 0.0 (low) to 1.0 (high). The susceptible tree had higher value of the probability than the resistant tree. Based on the number of burnt trees, we then carried out the sensitivity analysis to quantify how the forest fire patterns are affected by wind and tree density. The statistical analysis showed that the total tree density had greatest effect on the forest fire spreading and wind had the next greatest effect. The density of the susceptible tree was relatively lower factor affecting the forest fire. We believe that our model can be a useful tool to explore forest fire spreading patterns.

The Study of Model Biogas Catalyst Reforming Using 3D IR Matrix Burner (3D IR 매트릭스 버너에 의한 모사 바이오가스 촉매 개질 연구)

  • Lim, Mun Sup;Chun, Young Nam
    • Journal of Korean Society of Environmental Engineers
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    • v.34 no.12
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    • pp.840-846
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    • 2012
  • Global climate changes caused by $CO_2$ emissions are currently debated around the world; green sources of energy are being sought as alternatives to replace fossil fuels. The sustainable use of biogas for energy production does not contribute to $CO_2$ emission and has therefore a high potential to reduce them. Catalytic steam reforming of a model biogas ($CH_4:CO_2$ = 60%:40%) is investigated to produce $H_2$-rich synthesis gas. The biogas utilized 3D-IR matrix burner in which the surface combustion is applied. The ruthenium catalyst was used inside a reformer. Parametric screening studies were achieved as Steam/Carbon ratio, biogas component ratio, Space velocity and Reformer temperature. When the condition of Steam/Carbon ratio, $CH_4/CO_2$ ratio, Space velocity and Refomer temperature were 3.25, 60% : 40%, $14.7L/g{\cdot}hr$ and $550^{\circ}C$ respectively, the hydrogen concentration and methane conversion rate were showed maximum values. Under the condition mentioned above, $H_2$ yield, $H_2$/CO ratio, CO selectivity and energy efficiency were 0.65, 2.14, 0.59, 51.29%.

Prediction Model for Gas-Energy Consumption using Ontology-based Breakdown Structure of Multi-Family Housing Complex (온톨로지 기반 공동주택 분류체계를 활용한 가스에너지 사용량 예측 모델)

  • Hong, Tae-Hoon;Park, Sung-Ki;Koo, Choong-Wan;Kim, Hyun-Joong;Kim, Chun-Hag
    • Korean Journal of Construction Engineering and Management
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    • v.12 no.6
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    • pp.110-119
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    • 2011
  • Global warming caused by excessive greenhouse gas emission is causing climate change all over the world. In Korea, greenhouse gas emission from residential buildings accounts for about 10% of gross domestic emission. Also, the number of deteriorated multi-family housing complexes is increasing. Therefore, the goal of this research is to establish the bases to manage energy consumption continuously and methodically during MR&R period of multi-family housings. The research process and methodologies are as follows. First, research team collected the data on project characteristics and energy consumption of multi-family housing complexes in Seoul. Second, an ontology-based breakdown structure was established with some primary characteristics affecting the energy consumption, which were selected by statistical analysis. Finally, a predictive model of energy consumption was developed based on the ontology-based breakdown structure, with application of CBR, ANN, MRA and GA. In this research, PASW (Predictive Analytics SoftWare) Statistics 18, Microsoft EXCEL, Protege 4.1 were utilized for data analysis and prediction. In future research, the model will be more continuous and methodical by developing the web-base system. And it has facility manager of government or local government, or multi-family housing complex make a decision with definite references regarding moderate energy consumption.

Economic Impacts of Sea-level Rise and Optimal Protection on Jeju Island (해수면 상승에 따른 경제적 피해 비용 및 최적 해안 방어 비율 추정 -제주도를 대상으로-)

  • Min, Dongki;Cho, Kwangwoo
    • Environmental and Resource Economics Review
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    • v.22 no.1
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    • pp.127-145
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    • 2013
  • This study estimates the economic impact of sea-level rise on Jeju island and suggests the optimal protection level based on the FUND model. There exist a number of studies that estimate the impacts of sea-level rise on global scale, but their results are of limited use for local scale such as Korea. Therefore, this study applies some specific indicators and data of Korea into to FUND model for deriving site specific estimates. The results show that 2.01%~2.25% of land could be inundated by sea-level rise until 2100. The value of affected land is about 6.4%~7.2% of total land value. The discrepancy between the figures indicates that the area affected by sea-level rise is much more valuable than the rest of Jeju island. The optimal protection level in Jeju city is higher than that in Seguipo city, even though the coastal length of Jeju city is longer than that of Seguipo. This is due to the fact that the economic value of Jeju city is much higher than that of Seoguipo city.

Predicting Habitat Suitability of Carnivorous Alert Alien Freshwater Fish (포식성 유입주의 어류에 대한 서식처 적합도 평가)

  • Taeyong, Shim;Zhonghyun, Kim;Jinho, Jung
    • Ecology and Resilient Infrastructure
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    • v.10 no.1
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    • pp.11-19
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    • 2023
  • Alien species are known to threaten regional biodiversity globally, which has increased global interest regarding introduction of alien species. The Ministry of Environment of Korea designated species that have not yet been introduced into the country with potential threat as alert alien species to prevent damage to the ecosystem. In this study, potential habitats of Esox lucius and Maccullochella peelii, which are predatory and designated as alert alien fish, were predicted on a national basis. Habitat suitability was evaluated using EHSM (Ecological Habitat Suitability Model), and water temperature data were input to calculate Physiological Habitat Suitability (PHS). The prediction results have shown that PHS of the two fishes were mainly controlled by heat or cold stress, which resulted in biased habitat distribution. E. lucius was predicted to prefer the basins at high latitudes (Han and Geum River), while M. peelii preferred metropolitan areas. Through these differences, it was expected that the invasion pattern of each alien fish can be different due to thermal preference. Further studies are required to enhance the model's predictive power, and future predictions under climate change scenarios are required to aid establishing sustainable management plans.

Monitoring of Atmospheric Aerosol using GMS-5 Satellite Remote Sensing Data (GMS-5 인공위성 원격탐사 자료를 이용한 대기 에어러솔 모니터링)

  • Lee, Kwon Ho;Kim, Jeong Eun;Kim, Young Jun;Suh, Aesuk;Ahn, Myung Hwan
    • Journal of the Korean Association of Geographic Information Studies
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    • v.5 no.2
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    • pp.1-15
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    • 2002
  • Atmospheric aerosols interact with sunlight and affect the global radiation balance that can cause climate change through direct and indirect radiative forcing. Because of the spatial and temporal uncertainty of aerosols in atmosphere, aerosol characteristics are not considered through GCMs (General Circulation Model). Therefor it is important physical and optical characteristics should be evaluated to assess climate change and radiative effect by atmospheric aerosols. In this study GMS-5 satellite data and surface measurement data were analyzed using a radiative transfer model for the Yellow Sand event of April 7~8, 2000 in order to investigate the atmospheric radiative effects of Yellow Sand aerosols, MODTRAN3 simulation results enable to inform the relation between satellite channel albedo and aerosol optical thickness(AOT). From this relation AOT was retreived from GMS-5 visible channel. The variance observations of satellite images enable remote sensing of the Yellow Sand particles. Back trajectory analysis was performed to track the air mass from the Gobi desert passing through Korean peninsular with high AOT value measured by ground based measurement. The comparison GMS-5 AOT to ground measured RSR aerosol optical depth(AOD) show that for Yellow Sand aerosols, the albedo measured over ocean surfaces can be used to obtain the aerosol optical thickness using appropriate aerosol model within an error of about 10%. In addition, LIDAR network measurements and backward trajectory model showed characteristics and appearance of Yellow Sand during Yellow Sand events. These data will be good supporting for monitoring of Yellow Sand aerosols.

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The Effects of Learning Transfer on Perceived Usefulness and Perceived Ease of Use in Enterprise e-Learning - Focused on Mediating Effects of Self-Efficacy and Work Environment - (지각된 유용성과 사용용이성이 기업 이러닝 교육의 학습전이에 미치는 영향에 관한 연구 -자기효능감과 업무환경의 매개효과를 중심으로-)

  • Park, Dae-Bum;Gu, Ja-Won
    • Management & Information Systems Review
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    • v.37 no.3
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    • pp.1-25
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    • 2018
  • This research performed the empirical test for the effects of learning transfer on perceived usefulness, perceived ease of use, self-efficacy and work environment using 390 employees who have experienced e-learning in domestic and foreign companies. Analyzed the mediating effects of self-efficacy and work environment in addition to direct effect of each factor on learning transfer. The results showed that perceived usefulness and perceived ease-of-use of e-learning learner had a positive(+) effect on self-efficacy and a positive influence on supervisor and peer support and organizational climate. Self-efficacy showed a positive effect on learning transfer, and supervisor support, peer support and organizational climate had a positive influence on learning transfer as well. Perceived usefulness also had a positive effect on learning transfer. However, perceived ease-of-use had no significant effect on learning transfer. As a result of the mediating effect analysis, self-efficacy and work environment were analyzed to have mediating effects between perceived usefulness, perceived ease of use, and learning transfer. The implications of this study are as follows. First, this study designed a new research model that reflects factors influencing the effect of learning transfer on acceptance of e-learning that is common in corporate education. It has derived a research model of perceived usefulness and perceived ease-of-use, which were used as mediating variables for external characteristics factors, as independent variables, using self-efficacy and work environment as mediating variables, which were studied as external factors. Second, most of the studies on technology acceptance model and learning transfer are conducted in a single country. The reliability was enhanced by testing the study models using different samples from 26 countries. Third, perceived usefulness and ease-of-use in existing studies have been considered as key determinants of acceptance intention and learning transfer. This study explored the mediating effects of learner and environmental factors on the accepted information technology and strengthened and supplemented the path of learning transfer of perceived usefulness and ease-of-use. In addition, based on the sample analysis of various countries used in this study, it is expected that future international comparative studies will be possible.

Study of the Construction of a Coastal Disaster Prevention System using Deep Learning (딥러닝을 이용한 연안방재 시스템 구축에 관한 연구)

  • Kim, Yeon-Joong;Kim, Tae-Woo;Yoon, Jong-Sung;Kim, Myong-Kyu
    • Journal of Ocean Engineering and Technology
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    • v.33 no.6
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    • pp.590-596
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    • 2019
  • Numerous deaths and substantial property damage have occurred recently due to frequent disasters of the highest intensity according to the abnormal climate, which is caused by various problems, such as global warming, all over the world. Such large-scale disasters have become an international issue and have made people aware of the disasters so they can implement disaster-prevention measures. Extensive information on disaster prevention actively has been announced publicly to support the natural disaster reduction measures throughout the world. In Japan, diverse developmental studies on disaster prevention systems, which support hazard map development and flood control activity, have been conducted vigorously to estimate external forces according to design frequencies as well as expected maximum frequencies from a variety of areas, such as rivers, coasts, and ports based on broad disaster prevention data obtained from several huge disasters. However, the current reduction measures alone are not sufficiently effective due to the change of the paradigms of the current disasters. Therefore, in order to obtain the synergy effect of reduction measures, a study of the establishment of an integrated system is required to improve the various disaster prevention technologies and the current disaster prevention system. In order to develop a similar typhoon search system and establish a disaster prevention infrastructure, in this study, techniques will be developed that can be used to forecast typhoons before they strike by using artificial intelligence (AI) technology and offer primary disaster prevention information according to the direction of the typhoon. The main function of this model is to predict the most similar typhoon among the existing typhoons by utilizing the major typhoon information, such as course, central pressure, and speed, before the typhoon directly impacts South Korea. This model is equipped with a combination of AI and DNN forecasts of typhoons that change from moment to moment in order to efficiently forecast a current typhoon based on similar typhoons in the past. Thus, the result of a similar typhoon search showed that the quality of prediction was higher with the grid size of one degree rather than two degrees in latitude and longitude.

Estimation of the Flood Warning Rainfall with Backwater Effects in Urban Watersheds (도시 유역의 배수위 영향을 고려한홍수 경보 강우량 산정)

  • Kim, Eung-Seok;Lee, Seung-Hyun;Yoon, Ki-Yong
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.16 no.1
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    • pp.801-806
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    • 2015
  • The incidence of flood damage by global climate change has increased recently. Because of the increased frequency of flooding in Korea, the technology of flood prediction and prevalence has developed mainly for large river watersheds. On the other hand, there is a limit on predicting flooding through the most present flood forecasting systems because local floods in small watersheds rise quite quickly with little or no advance warning. Therefore, this study estimated the flood warning rainfall using a flood forecasting model at the two alarm trigger points in the Suamcheon basin, which is an urban basin with backwater effects. The flood warning rainfall was estimated to be 25.4mm/120min ~ 78.8mm/120min for the low water alarm, and 68.5mm/120min ~ 140.7mm/120min for the high water alarm. The frequency of the flood warning rainfall is 3-years for the low water alarm, and 80-years for the high water alarm. The results of this analysis are expected to provide a basic database in forecasting local floods in urban watersheds. Nevertheless, more tests and implementations using a large number of watersheds will be needed for a practical flood warning or alert system in the future.

A Case Study of Calculating Flood Inundation Area by HEC-GeoRAS (HEC-GeoRAS 모형에 의한 침수면적산정 사례연구)

  • Kim, Chang-Soo;Lee, Young-Dai;Lee, Hwan-Woo
    • Journal of Korean Society of societal Security
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    • v.2 no.4
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    • pp.43-48
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    • 2009
  • During the past few years, Korea has experienced extraordinary floods, which have caused many damages of lives and properties. Flooding caused by typhoon is the most common disastrous phenomenon of nature among all catastrophes. As the average temperature of the earth has been increasing by global warming, the possibility of typhoon is also increased by abnormal climate changes. Along with the river improvement as a part of flood control, the time of concentration has been decreased, so the pick discharge has been increased. Moreover, with the land development activities, the area of storage has been diminishing, and the damages from inundation have been continuously increasing. There were a lot of damages to farmland in 1960's, industrial and public facilities in 1970's, and a lot of sufferings from the windstorm in 1980's. In 1990's, however, the amount of damages was increased substantially. So, there is need to decrease the number of the victims and loss of properties by applying preventive measures against natural calamities. This study has employed a simulation system to calculate the depth and amounts of inundation areas to forecast and prevent from flood damage by using rainfall-runoff model. In this study, a case study method is adopted to show inundation by using rainfall-runoff model, HEC-GeoRAS and Arcview. It is hoped that, this study would be conducive to professionals and organizations working in the field of disaster management.

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