In order to solve the rapidly increasing domestic delivery volume and various problems in the recent metropolitan area, domestic researchers are conducting research on the development of “Urban Logistics System Using Underground Space” using existing urban railway facilities in the city. Safety analysis and scenario analysis should be performed for the safe system design of the new concept logistics system, but the scenario analysis techniques performed in previous studies so far do not have standards and are defined differently depending on the domain, subject, or purpose. In addition, it is necessary to improve the difficulty of clearly defining the control structure and the omission of UCA in the existing STPA safety analysis. In this study, an improved scenario table is proposed for the AGV horizontal transport device, which is a key equipment of an urban logistics system using underground space, and a process model is proposed by linking systematic STPA safety analysis and scenario analysis, and UCA and Control Structure Guidelines are provided to create a safety analysis.

Social welfare facilities are used by a wide range of local residents, including vulnerable populations such as the elderly, children, and people with disabilities. During emergencies like fires, confusion can arise as these individuals try to evacuate. Evacuation simulation results have shown that utilizing evacuation systems based on specific evacuation scenarios can significantly decrease the time required for evacuation compared to general evacuation procedures. By anticipating potential fires based on changes in social and facility environments, appropriate evacuation scenarios can be developed and applied to evacuation systems, thus contributing to the safety and security of individuals during emergencies. In conclusion, for social welfare facilities that serve a large number of people, it is necessary to expand the focus on performance-based design depending on the size of the facility, and to continuously develop and train for appropriate evacuation scenarios that align with changing facility environments.

Climate change is a major global problem. Oysters, one of the most representative farmed fish in Korea, are attracting attention as candidates for blue carbon, an alternative to carbon neutrality. This study is analyzed by the SSP scenarios to determine the impact of oyster aquaculture production according to climate change. Based on the analysis, future productions of oysters are predicted by the SSP scenario. Significant differences by the SSP scenario are confirmed through predictive power tests among scenarios. Regression analysis was conducted from January 2001 to December 2014. As a result of the analysis, water temperature, water temperature quadratic term, salinity, salinity quadratic term, and month × water temperature cross term were estimated as significant variables. Oyster production which is predicted by the SSP scenario based on the significant variables from 2015 to 2022 was compared with actual production. The model with the highest predictive power was selected by RMSE and MAPE criteria. The predictive power was compared with the MDM test to determine which model was superior. As a result, based on RMSE and MAPE, the SSP1-2.6 scenario was selected as the best model and the SSP1-2.6, SSP2-4.5, and SSP3-7.0 scenarios all showed the same predictive power based on the MDM test. In conculusion, this study predicted oyster aquaculture production by 2030, not the distant future, due to the short duration of the analytical model. This study was found that oyster aquaculture production increased in all scenarios and there was no significant difference in predictive power by the SSP scenario.

Various social and environmental problems have recently emerged due to global climate change. In South Korea, coniferous forests in the highlands are decreasing due to climate change whereas the distribution of subtropical species is gradually increasing. This study aims to respond to changes in the distribution of forest species in South Korea due to climate change. This study predicts changes in future suitable areas for Pinus koraiensis, Cryptomeria japonica, and Chamaecyparis obtusa cultivated as timber species based on climate, topography, and environment. Appearance coordinates were collected only for natural forests in consideration of climate suitability in the National Forest Inventory. Future climate data used the SSP scenario by KMA. Species distribution models were ensembled to predict future suitable habitat areas for the base year (2000-2019), near future (2041-2060), and distant future (2081-2100). In the baseline period, the highly suitable habitat for Pinus koraiensis accounted for approximately 13.87% of the country. However, in the distant future (2081- 2100), it decreased to approximately 0.11% under SSP5-8.5. For Cryptomeria japonica, the habitat for the base year was approximately 7.08%. It increased to approximately 18.21% under SSP5-8.5 in the distant future. In the case of Chamaecyparis obtusa, the habitat for the base year was approximately 19.32%. It increased to approximately 90.93% under SSP5-8.5 in the distant future. Pinus koraiensis, which had been planted nationwide, gradually moved north due to climate change with suitable habitats in South Korea decreased significantly. After the near future, Pinus koraiensis was not suitable for the afforestation as timber species in South Korea. Chamaecyparis obtusa can be replaced in most areas. In the case of Cryptomeria japonica, it was assessed that it could replace part of the south and central region.

기후변화 시나리오는 기후변화로 인한 미래 영향을 평가하여 피해를 선제적으로 최소화하기 위한 기후변화 대응 및 적응정책 수립을 위한 과학적인 근거로 활용 되어 왔다. IPCC 6차 평가보고서(AR6)에 사용된 SSPs(Shared Socioeconomic Pathways, 공통사회경제경로) 시나리오는 기존 RCP(Representative Concentration Pathways, 대표농도경로) 시나리오에 사용된 복사강제력 개념과 함께 미래의 완화 와 적응 노력에 따른 5개의 사회경제 시나리오를 추가로 고려하였다. 가나는 국가 발전용량의 54%를 수력발전에 의존하고 있어 기후변화에 따른 강수량의 감소로 전력 부족을 경험하고 있다. 또한 강우특성의 변화로 인해 주요 작물인 카사바, 옥수수, 코코아의 생산량이 감소할 것으로 예측된다. 한편, IPCC 6차 보고서의 기 준 시나리오로 채택된 SSPs 시나리오는 5차 보고서에서 채택된 RCPs 시나리오에 비해 대기 중 CO2 농도 전망을 비관적으로 평가하고 있다. Business as usual(BAU) 시나리오(RCP8.5, SSP5-8.5)에 따르면 2050년대 CO2 농도는 RCPs 시나 리오의 경우 541 ppm, SSPs 시나리오는 565 ppm으로 SSPs 시나리오가 RCPs 시나 리오에 비해 대기중 CO2 농도 증가 속도가 빠른 것으로 전망하고 있다. 따라서 본 연구에서는 기후변화 시나리오의 통계적 상세화 방법인 Simple Quantile Mapping(SQM)을 사용하여 Coupled Model Intercomparison Project phase 6(CMIP6) 18개 General Circulation Model(GCM)을 활용하여 가나지역의 미래기후 변동과 불 확실성을 평가하였다.

최근 급격한 변화를 겪고 있는 자율주행 자동차 분야의 미래 기술 및 시장 전 망 예측에 대한 요구와 관심이 집중되고 있다. 자동차 산업의 특성상, 복합적 요인의 상관관 계가 미치는 영향력이 크고 요인 간의 복잡도가 높으므로, 체계적인 미래 예측 방법론 적용 을 통한 미래 전망분석 및 전략 수립이 시급하다. 본 연구에서는 자동차 분야에 적합한 미래 예측 방법론 중 필드 변칙 완화기법(Field Anomaly Relaxation)과 다중관점 개념 기법 (Multiple Perspective Concept)을 복합적으로 적용하여, 자율주행 자동차 분야의 핵심기술 및 산업 동향에 관한 미래 시나리오들을 개발하여 실증하였다. 도출된 3개의 시나리오는 전 문가 평가 체크리스트를 통하여 타당성을 검증하였다. 본 연구 결과는 자율주행 자동차 산업 과 같은 다양한 변동성이 존재하는 분야의 미래 예측 방법 중 한 가지로 적용될 수 있다는 점에 의의가 있다.

Global warming has a major impact on the Earth’s precipitation and temperature fluctuations, and significantly affects the habitats and biodiversity of many species. Although the number of alien plants newly introduced in South Korea has recently increased due to the increasing frequency of international exchanges and climate change, studies on how climate change affects the distribution of these alien plants are lacking. This study predicts changes in the distribution of suitable habitats according to RCPs climate change scenarios using the current distribution of the invasive alien plant Conyza sumatrensis and bioclimatic variables. C. sumatrensis has a limited distribution in the southern part of South Korea. Isothermality (bio03), the max temperature of the warmest month (bio05), and the mean temperature of the driest quarter (bio09) were found to influence the distribution of C. sumatrensis. In the future, the suitable habitat for C. sumatrensis is projected to increase under RCP 4.5 and RCP 8.5 climate change scenarios. Changes in the distribution of alien plants can have a significant impact on the survival of native plants and cause ecosystem disturbance. Therefore, studies on changing distribution of invasive species according to climate change scenarios can provide useful information required to plan conservation strategies and restoration plans for various ecosystems.

This study was carried out to compare the DMY (dry matter yield) of IRG (Italian ryegrass) in the southern coastal regions of Korea due to seasonal climate scenarios such as the Kaul-Changma (late monsoon) in autumn, extreme winter cold, and drought in the next spring. The IRG data (n = 203) were collected from various Reports for Collaborative Research Program to Develop New Cultivars of Summer Crops in Jeju, 203 Namwon, and Yeungam from the Rural Development Administration (1993 – 2013). In order to define the seasonal climate scenarios, climate variables including temperature, humidity, wind, sunshine were used by collected from the Korean Meteorological Administration. The discriminant analysis based on 5% significance level was performed to distinguish normal and abnormal climate scenarios. Furthermore, the DMY comparison was simulated based on the information of sample distribution of IRG. As a result, in the southern coastal regions, only the impact of next spring drought on DMY of IRG was critical. Although the severe winter cold was clearly classified from the normal, there was no difference in DMY. Thus, the DMY comparison was simulated only for the next spring drought. Under the yield comparison simulation, DMY (kg/ha) in the normal and drought was 14,743.83 and 12,707.97 respectively. It implies that the expected damage caused by the spring drought was about 2,000 kg/ha. Furthermore, the predicted DMY of spring drought was wider and slower than that of normal, indicating on high variability. This study is meaningful in confirming the predictive DMY damage and its possibility by spring drought for IRG via statistical simulation considering seasonal climate scenarios.