• Journal of Korean Society of Forest Science
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• v.112 no.3
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• pp.340-351
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• 2023

Landslides are major natural geological hazards that cause enormous property damage and human casualties annually. The vulnerability of mountainous areas to landslides is further exacerbated by the impacts of climate change. Soil depth is a crucial parameter in landslide and debris flow analysis, and plays an important role in the evaluation of watershed hydrological processes that affect slope stability. An accurate method of estimating soil depth is to directly investigate the soil strata in the field. However, this requires significant amounts of time and money; thus, numerous models for predicting soil depth have been proposed. However, they still have limitations in terms of practicality and accuracy. In this study, 71 seismic survey results were collected from domestic mountainous areas to estimate soil depth on hill slopes. Soil depth was estimated on the basis of a shear wave velocity of 700 m/s, and a database was established for slope angle, elevation, and soil depth. Consequently, the statistical characteristics of soil depth were analyzed, and the correlations between slope angle and soil depth, and between elevation and soil depth were investigated. Moreover, various soil depth prediction models based on slope angle were investigated, and corrected linear and exponential soil depth prediction models were proposed.

• Korean Chemical Engineering Research
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• v.61 no.1
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• pp.142-154
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• 2023

As the importance of the environment has been recognized worldwide, the need to calculate and reduce carbon emissions has been drawing an increasing attention throughout various industrial sections. Thereby the discipline of LCA (Life Cycle Assessment) involving raw material preparation, production processes, transportation and installation has been established. There is a clear research gap between the need and the practice for Korean Case of renewable energy industry, particularly wind power. To bridge the gap, this study conducted LCA research on wind power generation in the Korean area of Yeongdeok, an example of a domestic onshor wind power complex using SimaPro, which is the most widely used LCA system. As a result of the study, the energy recovery period (EPT) of one wind turbine is about 10 months, and the GHG emitted to generate power of 1 kwh is 15 g CO₂/kWh, which is competitive compared to other energy sources. In the environmental impact assessment by component, the results showed that the tower of wind turbines had the greatest impact on various environmental impact sectors. The experience gained in this study can be further used in strengthening the introduction of renewable energy and reducing the carbon emission in line with reducing climate change.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.94-94
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• 2020

최근 정부의 신북방정책 추진에 따라 수자원분야에서는 동북아지역 국제 공유하천을 중심의 물 정보 및 연구협력 기회 확보와 지정학적 특성을 고려한 지역 현안해결 중심의 연구가 재조명 되고 있다. 두만강은 이러한 동북아의 중심에 위치하고 있으며, 중국, 북한, 러이사의 국경을 따라 흐르며 지역 수자원의 대부분을 공급하는 국제하천이다. 또한, 지난 2018년 5월에는 하구유역이 람사르(Ramsar) 습지로 승인됨에 따라 철새 등을 포함한 생태가치의 중요성도 크게 증가하였다. 하지만 이 지역은 유역의 지정학적 민감성과 접근이 제한된 관측 정보들로 인해 그 수자원·환경 효용성을 정확하게 파악할 수 없을 뿐만 아니라, 최근 기후변화에 따른 영향으로 홍수, 가뭄 등의 수재해와 수질오염 등의 문제가 발생하고 있어 가용한 기술기반의 직·간접적 접근을 통한 장기수문 및 환경변화 등에 대한 분석과 관리방안 수립 등의 연구가 필요하다. 본 연구에서는 이러한 미계측 두만강 유역을 대상으로 우선, 가용한 위성자료 및 광역지표모형(MERRA-2) 기반 NASA POWER(Prediction of Worldwide Energy Resource) 수문기상 자료와 SWAT(Soil and Water Assessment Tool) 모형을 활용하여 장기 수문영향을 평가하고자 한다. SWAT 모형은 전 지구적으로 활용 가능한 격자 해상도 약 30m의 위성기반 수치표고모형(DEM), 광역 토양도, 지역 토지이용도 자료를 활용하여 두만강 유역을 전체 19개 소유역 및 18개 하도, 138개 HRUs의 수문분석 단위로 구축하였으며, 모의는 미국 NOAA NCDC(National Climate Data Center) 및 중국 CMDC(China Meteorological Data Service Center)의 주요 관측지점에서 선별한 총 13개소의 위치에 대해 재분석된 기후/기상자료들(NASA POWER 강수, 기온, 풍속, 상대습도 및 일사량)을 적용, 1990년에서 2019년까지의 30개년도 연속자료를 구축활용 하였다. 한편, 모형의 검·보정은 앞서 언급한 관측 자료의 부재로 과거 문헌 등을 통해 파악할 수 있는 연 단위 수자원 총량 등을 활용해 진행코자한다. 아울러, 향후는 최근 활용 가능한 장기 위성관측 강수량을 적용, 재분석 자료 결과와의 비교를 통해 상호 분석 오류를 줄여나갈 수 있을 것으로도 판단된다.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.28 no.4
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• pp.121-132
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• 2023

Marine heatwaves (MHWs), referring to anomalously high sea surface temperatures, have drawn significant attention from marine scientists due to their broad impacts on the surface marine ecosystem, fisheries, weather patterns, and various human activities. In this study, we examined the impact of the distribution of Changjiang diluted water (CDW), a significant factor causing oceanic property changes in the East China Sea (ECS) during the summer, on MHWs. The surface salinity distribution in the ECS indicates that from June to August, the eastern extension of the CDW influences areas as far as Jeju Island and the Korea Strait. In September, however, the CDW tends to reside in the Changjiang estuary. Through the Empirical Orthogonal Function analysis of the cumulative intensity of MHWs during the summer, we extracted the loading vector of the first mode and its principal component time series to conduct a correlation analysis with the distribution of the CDW. The results revealed a strong negative spatial correlation between areas of the CDW and regions with high cumulative intensity of MHWs, indicating that the reinforcement of stratification due to low-salinity water can increase the intensity and duration of MHWs. This study suggests that the CDW may still influence the spatial distribution of MHWs in the region, highlighting the importance of oceanic environmental factors in the occurrence of MHWs in the waters surrounding the Korean Peninsula.

• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.6
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• pp.543-551
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• 2023

As climate change continues to prompt an increasing demand for advancements in disaster and safety management technologies to address abnormal high water temperatures, typhoons, floods, and droughts, sea surface temperature has emerged as a pivotal factor for swiftly assessing the impacts of summer harmful algal blooms in the seas surrounding Korean Peninsula and the formation and dissipation of cold water along the East Coast of Korea. Therefore, this study sought to gauge predictive performance by leveraging statistical methods and deep learning algorithms to harness sea surface temperature data effectively for marine anomaly research. The sea surface temperature data employed in the predictions spans from 2018 to 2022 and originates from the Heuksando Tidal Observatory. Both traditional statistical ARIMA methods and advanced deep learning models, including long short-term memory (LSTM) and gated recurrent unit (GRU), were employed. Furthermore, prediction performance was evaluated using the attention LSTM technique. The technique integrated an attention mechanism into the sequence-to-sequence (s2s), further augmenting the performance of LSTM. The results showed that the attention LSTM model outperformed the other models, signifying its superior predictive performance. Additionally, fine-tuning hyperparameters can improve sea surface temperature performance.

• Environmental and Resource Economics Review
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• v.33 no.1
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• pp.1-32
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• 2024

The emissions trading system stands as a pivotal climate policy in Korea, incentivizing abatement equivalent to 87% of total emissions (as of 2021). As the system likely has a far-reaching impact, it is crucial to understand how the real economic activity, energy sector, as well as environment would be influenced by its implementation. Employing a macroeconometric model, this paper is the first study analyzing the effects of the Korean emissions trading policy. It interconnects the Korean Standard Industrial Classification (Economy), Energy Balance (Energy), and National Inventory Report (Environment), enhancing its real-world explanatory power. We find that a 50% increase in emission permit price over four years results in a decrease in greenhouse gas emissions (-0.043%) and downward shifts in key macroeconomic variables, including real GDP (-0.058%), private consumption (-0.003%), and investment (-0.301%). The price increase in emission permit is deemed crucial for achieving greenhouse gas reduction targets. To mitigate transition risk associated with price shocks, revenue recycling using auction could ensure the sustainability of the economy. This study confirms the comparative advantage of expanded current transfers expenditure over corporate tax reduction, particularly from an economic growth perspective.

• Journal of Korea Water Resources Association
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• v.54 no.8
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• pp.577-587
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• 2021

Drought is generally considered to be a natural disaster caused by accumulated water shortages over a long period of time, taking months or years and slowly occurring. However, climate change has led to rapid changes in weather and environmental factors that directly affect agriculture, and extreme weather conditions have led to an increase in the frequency of rapidly developing droughts within weeks to months. This phenomenon is defined as 'Flash Drought', which is caused by an increase in surface temperature over a relatively short period of time and abnormally low and rapidly decreasing soil moisture. The detection and analysis of flash drought is essential because it has a significant impact on agriculture and natural ecosystems, and its impacts are associated with agricultural drought impacts. In South Korea, there is no clear definition of flash drought, so the purpose of this study is to identify and analyze its characteristics. In this study, flash drought detection condition was presented based on the satellite-derived drought index Evaporative Stress Index (ESI) from 2014 to 2018. ESI is used as an early warning indicator for rapidly-occurring flash drought a short period of time due to its similar relationship with reduced soil moisture content, lack of precipitation, increased evaporative demand due to low humidity, high temperature, and strong winds. The flash droughts were analyzed using hydrometeorological characteristics by comparing Standardized Precipitation Index (SPI), soil moisture, maximum temperature, relative humidity, wind speed, and precipitation. The correlation was analyzed based on the 8 weeks prior to the occurrence of the flash drought, and in most cases, a high correlation of 0.8(-0.8) or higher(lower) was expressed for ESI and SPI, soil moisture, and maximum temperature.

• Korean Journal of Environment and Ecology
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• v.32 no.5
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• pp.469-477
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• 2018

Hanabusaya asiatica is an endemic species whose distribution is limited in the mid-eastern part of the Korean peninsula. Due to its narrow range and small population, it is necessary to protect its habitats by identifying it as Key Biodiversity Areas (KBAs) adopted by the International Union for Conservation of Nature (IUCN). In this paper, we estimated potential natural habitats for H. asiatica using maximum entropy model (MaxEnt) and identified candidate sites for KBA based on the model results. MaxEnt is a machine learning algorithm that can predict habitats for species of interest unbiasedly with presence-only data. This property is particularly useful for the study area where data collection via a field survey is unavailable. We trained MaxEnt using 38 locations of H. asiatica and 11 environmental variables that measured climate, topography, and vegetation status of the study area which encompassed all locations of the border region between South and North Korea. Results showed that the potential habitats where the occurrence probabilities of H. asiatica exceeded 0.5 were $778km^2$, and the KBA candidate area identified by taking into account existing protected areas was $1,321km^2$. Of 11 environmental variables, elevation, annual average precipitation, average precipitation in growing seasons, and the average temperature in the coldest month had impacts on habitat selection, indicating that H. asiatica prefers cool regions at a relatively high elevation. These results can be used not only for identifying KBAs but also for the reference to a protection plan for H. asiatica in preparation of Korean reunification and climate change.

• Horticultural Science & Technology
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• v.33 no.6
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• pp.829-838
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• 2015

Garlic (Allium sativum L.), one of the oldest cultivated crops, is the most widely used Allium species belonging to the family Lilliaceae. In this study, growth characteristics, photosystem II activity, and antioxidative enzyme activity were investigated in five temperatures ($10-30^{\circ}C$) during early growth stage of garlic to determine the optimum temperature for cultivation and assess the effects of high temperature on early growth of garlic. Vegetative growth (e.g., shoot height, number of leaves) of garlic plants was greater in the temperature ranges of $15-25^{\circ}C$. However, dry weight (of shoot, bulb, and total plant) of garlic was significantly greater at $20^{\circ}C$, compared to either below or above $20^{\circ}C$. $F_v/F_o$ and $F_v/F_m$ values were highest at $15-20^{\circ}C$, and decreased above $25^{\circ}C$. The chlorophyll a fluorescence induction OKJIP transient was also considerably affected by high temperature; the fluorescence yields $F_i$ and $F_P$ decreased considerably above $25^{\circ}C$, with the increase of $F_k$ and $W_k$. Activities of catalase and superoxide dismutase in leaves and peroxidase in roots were high in $20-25^{\circ}C$, and decreased significantly in $30^{\circ}C$. These results indicate that a growth temperature of $30^{\circ}C$ inhibits early growth of garlic and that it is desirable to culture garlic plants near $20^{\circ}C$. Fluorescence parameters such a $F_v/F_o$, $F_v/F_m$, $F_k$, $ET_o/CS_m$, and $PI_{abs}$ were significantly correlated with dry weight of whole garlic plants (p < 0.01), indicating that these fluorescence parameters can be used for early assessment of high temperature effects even though the damage to the plant is not very severe.

• Journal of Korean Society of Forest Science
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• v.102 no.1
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• pp.82-89
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• 2013

Harvest is one of the major disturbances affecting the soil carbon (C) dynamics in forests. However, researches on the long-term impact of periodic harvest on the soil C dynamics are limited since they requires rigorous control of various factors. Therefore, we adopted a modeling approach to determine the long-term impacts of harvest interval, harvest intensity and post-harvest residue management on soil C dynamics by using the Korean Forest Soil Carbon model (KFSC model). The simulation was conducted on Pinus densiflora S. et Z. stands in central Korea, and twelve harvest scenarios were tested by altering harvest intervals (50, 80, and 100-year interval), intensities (partial-cut harvest: 30% and clear-cut harvest: 100% of stand volume), and the residue managements after harvest (collection: 0% and retention: 100% of aboveground residue). We simulated the soil carbon stock for 400 years for each scenario. As a result, the soil C stocks in depth of 30 cm after 400 years range from 50.3 to 55.8 Mg C $ha^{-1}$, corresponding to 98.1 to 108.9% of the C stock at present. The soil C stock under the scenarios with residue retention was 2.5-11.0% higher than that under scenarios with residue collection. However, there was no significant impact of harvest interval and intensity on the soil C stock. The soil C dynamics depended on the dead organic matter dynamics derived from the amount of dead organic matter and growth pattern after harvest.