• 환경영향평가
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• 제4권3호
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• pp.73-86
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• 1995

This paper demonstrates Environmental Impact Assessment (EIA) has to be applied for development projects with regard to the ecological, economical and social aspects before any decisions made in the project. Korea has confronted various environmental problems during the last fifteen years, even though EIA has been enacted since 1981. The role of impact assessment in planning and policy processes should be emphasized to investigate the magnitude and intensity of the adverse influences of economic development. In the Seoul Metropolitan Region, it is necessary to apply EIA all urban projects to reduce the adverse effects of urbanization. Special attention should be given to the climatological effects throughout the urbanization process in Korea to keep the urban area energy-efficient. This study intends not only to establish basic data for national-and regional-based land-use policy in the environmental aspects, but also to provide the basic data for the possible climate model (scenarios) that may provide spatial and temporal variability by analyzing the actual climatic record. There is a noticeable impact of urbanization on the atmospheric environment in the Seoul Metropolitan Region. In this sense, the climatic aspect must be taken into consideration in the process of EIA to mitigate the well-known climatic alterations of urbanization. Moreover, the techniques of assessment should be improved by developing geo-reference data sets to build models of the global climate in response to the man-made environmental change.

• 한국환경복원기술학회지
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• 제18권2호
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• pp.79-88
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• 2015

Preparations need to be made for Korean pine(Pinus koraiensis) in anticipation of climate change because Korean pine is an endemic species of South Korea and the source of timber and pine nut. Therefore, climate change adaptation policy has been established to conduct an impact assessment on the distribution of Korean pine. Our objective was to predict the distribution of Korean pine while taking into account uncertainty and afforestation conditions. We used the 5th forest types map, a forest site map and BIOCLIM variables. The climate scenarios are RCP 4.5 and RCP 8.5 for uncertainty and the climate models are 5 regional climate models (HadGEM3RA, RegCM4, SNURCM, GRIMs, WRF). The base period for this study is 1971 to 2000. The target periods are the mid-21st century (2021-2050) and the end of the 21st century (2071-2100). This study used the MaxEnt model, and 50% of the presences were randomly set as training data. The remaining 50% were used as test data, and 10 cross-validated replicates were run. The selected variables were the annual mean temperature (Bio1), the precipitation of the wettest month (Bio13) and the precipitation of the driest month (Bio14). The test data's ROC curve of Korean pine was 0.689. The distribution of Korean pine in the mid-21st century decreased from 11.9% to 37.8% on RCP 4.5 and RCP 8.5. The area of Korean pine at an artificial plantation occupied from 32.1% to 45.4% on both RCPs. The areas at the end of the 21st century declined by 53.9% on RCP 4.5 and by 86.0% on RCP 8.5. The area of Korean pine at an artificial plantation occupied 23.8% on RCP 4.5 and 7.2% on RCP 8.5. Private forests showed more of a decrease than national forests for all subsequent periods. Our results may contribute to the establishment of climate change adaptation policies for considering various adaptation options.

• 한국산림과학회지
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• 제99권6호
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• pp.791-801
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• 2010

산림토양탄소모델은 산림 내 복잡한 토양탄소 순환과정을 이해하고 기후변화에 따른 토양탄소동태를 예측하는데 유용한 도구이나, 국내에서는 모델의 개발 및 활용 연구가 미흡하다. 한편 IPCC 국가보고서와 같이 국제 사회에서 탄소계정에 대한 높은 수준의 연구결과를 요구하는 반면, 이를 반영하기 위한 기존 해외 모델의 국내 적용은 여러 가지 제약과 문제가 발생할 수 있기 때문에 국내 모델 개발의 필요성이 점차 증가하고 있다. 따라서 본 연구에서는 문헌조사를 바탕으로 국내 산림에서 적용이 가능한 7가지 해외 토양탄소모델(CBM-CFS3, CENTURY, Forest-DNDC, ROMUL, RothC, Sim-CYCLE, YASSO)을 선정하여 이들의 구조, 분해기작, 초기화 과정, 입력 및 출력 자료에 대하여 비교 분석하고, 모델의 국내 적용 가능성을 입력 자료 이용 가능성, 모델의 성능, 지역적 보정 가능성의 세 가지 기준을 토대로 평가하였다. 또한, 이를 기반으로 새로운 모델을 개발하고 적용하기 위한 일련의 과정을 제시하였다.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2011년도 학술발표회
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• pp.18-18
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• 2011

Climate change is impacting and will increasingly impact both the quantity and quality of the world's water resources in a variety of ways. In some areas warming climate results in increased rainfall, surface runoff, and groundwater recharge while in others there may be declines in all of these. Water quality is described by a number of variables. Some are directly impacted by climate change. Temperature is an obvious example. Notably, increased atmospheric concentrations of $CO_2$ triggering climate change increase the $CO_2$ dissolving into water. This has manifold consequences including decreased pH and increased alkalinity, with resultant increases in dissolved concentrations of the minerals in geologic materials contacted by such water. Climate change is also expected to increase the number and intensity of extreme climate events, with related hydrologic changes. A simple framework has been developed in New Zealand for assessing and predicting climate change impacts on water resources. Assessment is largely based on trend analysis of historic data using the non-parametric Mann-Kendall method. Trend analysis requires long-term, regular monitoring data for both climate and hydrologic variables. Data quality is of primary importance and data gaps must be avoided. Quantitative prediction of climate change impacts on the quantity of water resources can be accomplished by computer modelling. This requires the serial coupling of various models. For example, regional downscaling of results from a world-wide general circulation model (GCM) can be used to forecast temperatures and precipitation for various emissions scenarios in specific catchments. Mechanistic or artificial intelligence modelling can then be used with these inputs to simulate climate change impacts over time, such as changes in streamflow, groundwater-surface water interactions, and changes in groundwater levels. The Waimea Plains catchment in New Zealand was selected for a test application of these assessment and prediction methods. This catchment is predicted to undergo relatively minor impacts due to climate change. All available climate and hydrologic databases were obtained and analyzed. These included climate (temperature, precipitation, solar radiation and sunshine hours, evapotranspiration, humidity, and cloud cover) and hydrologic (streamflow and quality and groundwater levels and quality) records. Results varied but there were indications of atmospheric temperature increasing, rainfall decreasing, streamflow decreasing, and groundwater level decreasing trends. Artificial intelligence modelling was applied to predict water usage, rainfall recharge of groundwater, and upstream flow for two regionally downscaled climate change scenarios (A1B and A2). The AI methods used were multi-layer perceptron (MLP) with extended Kalman filtering (EKF), genetic programming (GP), and a dynamic neuro-fuzzy local modelling system (DNFLMS), respectively. These were then used as inputs to a mechanistic groundwater flow-surface water interaction model (MODFLOW). A DNFLMS was also used to simulate downstream flow and groundwater levels for comparison with MODFLOW outputs. MODFLOW and DNFLMS outputs were consistent. They indicated declines in streamflow on the order of 21 to 23% for MODFLOW and DNFLMS (A1B scenario), respectively, and 27% in both cases for the A2 scenario under severe drought conditions by 2058-2059, with little if any change in groundwater levels.

• 대기
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• 제34권1호
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• pp.55-67
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• 2024

This paper aims to provide a detailed introduction to the concept of the Ratio of Predictable Component (RPC) and the Signal-to-Noise Paradox. Then, we derive insights from them by exploring the paradoxical features by conducting a seasonal and regional analysis through ensemble expansion in KMA's climate prediction system (GloSea). We also provide an explanation of the ensemble generation method, with a specific focus on stochastic physics. Through this study, we can provide the predictability limits of our forecasting system, and find way to enhance it. On a global scale, RPC reaches a value of 1 when the ensemble is expanded to a maximum of 56 members, underlining the significance of ensemble expansion in the climate prediction system. The feature indicating RPC paradoxically exceeding 1 becomes particularly evident in the winter North Atlantic and the summer North Pacific. In the Siberian Continent, predictability is notably low, persisting even as the ensemble size increases. This region, characterized by a low RPC, is considered challenging for making reliable predictions, highlighting the need for further improvement in the model and initialization processes related to land processes. In contrast, the tropical ocean demonstrates robust predictability while maintaining an RPC of 1. Through this study, we have brought to attention the limitations of potential predictability within the climate prediction system, emphasizing the necessity of leveraging predictable signals with high RPC values. We also underscore the importance of continuous efforts aimed at improving models and initializations to overcome these limitations.

• 한국환경과학회지
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• 제25권7호
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• pp.1029-1042
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• 2016

The initial and boundary conditions are important factors in regional chemical transport modeling systems. The method of generating the chemical boundary conditions for regional air quality models tends to be different from the dynamically varying boundary conditions in global chemical transport models. In this study, the impact of real time Copernicus atmosphere monitoring service (CAMS) re-analysis data from the modeling atmospheric composition and climate project interim implementation (MACC) on the regional air quality in the Korean Peninsula was carried out using the community multi-scale air quality modeling system (CMAQ). A comparison between conventional global data and CAMS for numerical assessments was also conducted. Although the horizontal resolution of the CAMS re-analysis data is not higher than the conventionally provided data, the simulated particulate matter (PM) concentrations with boundary conditions for CAMS re-analysis is more reasonable than any other data, and the estimation accuracy over the entire Korean peninsula, including the Seoul and Daegu metropolitan areas, was improved. Although an inland area such as the Daegu metropolitan area often has large uncertainty in PM prediction, the level of improvement in the prediction for the Daegu metropolitan area is higher than in the coastal area of the western part of the Korean peninsula.

• 신재생에너지
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• 제20권1호
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• pp.88-94
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• 2024

This study explored the potential and implementation of renewable energy sources in Sri Lanka, focusing on the theoretical potential of solar and wind energy to develop self-reliant energy models. Using advanced climate data from the European Centre for Medium-Range Weather Forecasts and Global Solar/Wind Atlas provided by the World Bank, we assessed the renewable energy potential across Sri Lanka. This study proposes off-grid and minigrid systems as viable solutions for addressing energy poverty in rural regions. Rural villages were classified based on solar and wind resources, via which we proposed four distinct energy self-reliance models: Renewable-Dominant, Solar-Dominant, Wind-Dominant, and Diesel-Dominant. This study evaluates the economic viability of these models considering Sri Lanka's current energy market and technological environment. The outcomes highlight the necessity for employing diversified energy strategies to enhance the efficiency of the national power supply system and maximize the utilization of renewable resources, contributing to Sri Lanka's sustainable development and energy security.

• 대기
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• 제25권4호
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• pp.693-706
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• 2015

A shift of first fowering date (FFD) of spring blossoms (cherry, peach and pear) over the northest Asia under global warming is investiaged using dynamically downscaled daily temperature data with 12.5 km resolution. For the study, we obatained gridded daily data with Historical (1981~2010), and Representative Concentration Pathway (RCP) (2021~2100) 4.5 and 8.5 scenarios which were produced by WRFv3.4 in conjunction with HadGEM2-AO. A change on FFDs in 21st century is estimated by applying daily outputs of WRFv3.4 to DTS phonological model. Prior to projection on future climate, the performances of both WRFv3.4 and DTS models are evaluated using spatial distribution of climatology and SCR diagram (Normalized standard deviation-Pattern correlation coefficient-Root mean square difference). According to the result, WRFv3.4 and DTS models well simulated a feature of the terrain following characteristics and a general pattern of observation with a marigin of $1.4^{\circ}C$ and 5~6 days. The analysis reveals a projected advance in FFDs of cherry, peach and pear over the northeast Asia by 2100 of 15.4 days (9.4 days). 16.9 days (10.4 days) and 15.2 days (9.5 days), respectively, compared to the Historical simulation due to a increasing early spring (Februrary to April) temperature of about $4.9^{\circ}C$ ($2.9^{\circ}C$) under the RCP 8.5 (RCP 4.5) scenarios. This indicates that the current flowering of the cherry, peach and pear over analysis area in middle or end of April is expected to start blooming in early or middle of April, at the end of this century. The present study shows the dynamically downscaled daily data with high-resolution is helpeful in offering various useful information to end-users as well as in understanding regional climate change.

• 한국지역지리학회지
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• 제20권1호
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• pp.70-91
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• 2014

세계 각국은 기후변화에 대응하기 위한 노력을 기울이고 있으며, 우리나라 또한 예외가 아니다. 세계의 저탄소 녹색도시가 고유한 모델과 실천전략을 통해 다양한 모습으로 실행되어 왔음에 비추어, 우리나라 또한 우리나라의 풍토와 지형적 특성에 맞는 한국형 녹색도시의 모델 및 실천 전략이 필요하다. 이에 본 연구는 우리나라의 전통적인 공간 사유체계인 풍수에 주목하여, 풍수 논리의 현대적 해석을 통해 한국형 녹색 도시 조성 방안을 고찰하고자 한다. 이를 위해, 우선 과거 도시 및 전통마을과 현대 도시의 차이점을 파악하여, 과거의 풍수 논리를 현대 도시의 관점에서 재해석한다. 풍수 논리의 현대적 해석을 바탕으로, 풍수논리에 담겨 있는 입지선정과 공간계획 체계가 한국형 녹색도시 조성에 어떻게 적용될 수 있는지를 모색하고자 한다.

• 한국환경복원기술학회지
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• 제18권6호
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• pp.1-13
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• 2015

This study was conducted to develop an environmental index for assessing the vulnerability of areas with invasive alien plants. To that end, "Regional Vulnerability Numerical Index" (RVNI) was developed with a spatial statistical technique and applied to Seoul and Gyeonggi-do area first. The results are as follows. First, RVNI was high in stream areas. Second, RVNI was lowest in mountain areas. It indicates that stream areas are vulnerable to invasive alien plants. In terms of regions, Guri City is most vulnerable and Gapyeong-gun is the least vulnerable. To expand and manage the invasive alien plants, a control protocol should be developed by considering the physiology and ecology by invasive alien plant. Also, related policies should be pursued based on the results. Thus, the findings of this study can be used as baseline data for setting policies for invasive alien species management.