• Journal of the Korean Society for Marine Environment & Energy
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• v.18 no.2
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• pp.94-101
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• 2015

To mitigate the greenhouse gas emission, many carbon capture and storage projects are underway all over the world. In Korea, many studies focus on the storage of $CO_2$ in the offshore sediment. Assurance of safety is one of the most important issues in the geological storage of $CO_2$. Especially, the assessment of possibility of leakage and amount of leaked $CO_2$ is very crucial to analyze the safety of marine geological storage of $CO_2$. In this study, the leakage of injected $CO_2$ through fault was numerically studied. TOUGH2-MP ECO2N was used to simulate the subsurface behavior of injected $CO_2$. The storage site was 150 m thick saline aquifer located 825 m under the continental shelf. It was assumed that $CO_2$ leak was happened through the fault located 1,000 m away from the injection well. The injected $CO_2$ could migrate through the aquifer by both pressure difference driven by injection and buoyancy force. The enough pressure differences made it possible the $CO_2$ to migrate to the bottom of the fault. The $CO_2$ could be leaked to seabed through the fault due to the buoyancy force. Prior to leakage of the injected $CO_2$, the formation water leaked to seabed. When $CO_2$ reached the seabed, leakage of formation water stopped but the same amount of sea water starts to flow into the underground as the amount of leaked $CO_2$. To analyze the effect of injection rate on the leakage behavior, the injection rate of $CO_2$ was varied as 0.5, 0.75, and $1MtCO_2/year$. The starting times of leakage at 1, 0.75 and $0.5MtCO_2/year$ injection rates are 11.3, 15.6 and 23.2 years after the injection, respectively. The leakage of $CO_2$ to the seabed continued for a period time after the end of $CO_2$ injection. The ratios of total leaked $CO_2$ to total injected $CO_2$ at 1, 0.75 and $0.5MtCO_2/year$ injection rates are 19.5%, 11.5% and 2.8%, respectively.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.42 no.5
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• pp.579-596
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• 1997

A simulation study was carried out to delineate potential effects of the lake-induced climate change on crop productivity around Lake Imha which was formed after a multi-purpose dam construction in Andong, Korea. Twenty seven cropping zones were identified within the 30 km by 25 km study area. Five automated weather stations were installed within the study area and operated for five years after the lake formation. A geostatistical method was used to calculate the monthly climatological normals of daily maximum and minimum temperature, solar radiation and precipitation for each cropping zone before and after the dam construction. Daily weather data sets for 30 years were generated for each cropping zone from the monthly normals data representing "No lake" and "After lake" climatic scenarios, respectively. They were fed into crop models (ORYZA1 for rice, SOYGRO for soybean, CERES-maize for corn) to simulate the yield potential of each cropping zone. Calculated daily maximum temperature was higher after the dam construction for the period of October through March and lower for the remaining months except June and July. Decrease in daily minimum temperature was predicted for the period of April through August. Monthly total radiation was predicted to decrease after the lake formation in all the months except February, June, and September and the largest drop was found in winter. But there was no consistent pattern in precipitation change. According to the model calculation, the number of cropping zones which showed a decreased yield potential was 2 for soybean and 6 for corn out of 27 zones with a 10 to 17% yield drop. Little change in yield potential was found at most cropping zones in the case of paddy rice, but interannual variation was predicted to increase after the lake formation. the lake formation.

• Korean Journal of Environmental Agriculture
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• v.25 no.4
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• pp.306-315
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• 2006

Two different experiments, adsorption/desorption and runoff by rainfall simulation of four pesticides, such as alachlor, ethalfluralin, ethoprophos and pendimethalin were undertaken their runoff and erosion losses from sloped land and to assess the influence of their properties and environmental factors on them. The mobility of four pesticides and which phase they were transported by were examined in adsorption study, and the influence of rainfall pattern and sloping degree on the pesticide losses were evaluated in simulated rainfall study. Freundlich adsorption parameters (K) by the adsorption and desorption methods were 1.2 and 2.2 for ethoprophos, 1.5 and 2.6 for alachlor, respectively. And adsorption distribution coefficients (Kd) by the adsorption and desorption methods were 56 and 94 for ethalfluralin, and 104 and 189 for pendimethalin, respectively. K or Kd values of pesticides by the desorption method which were desorbed from the soil after thoroughly mixing, were higher than these ones by the adsorption method which pesticides dissolved in water were adsorbed to the soil. Another parameter (1/n), representing the linearity of adsorption, in Freundlich equation for the pesticides tested ranged from 0.96 to 1.02 by the desorption method and from 0.87 to 1.02 by the adsorption method. Therefore, the desorption method was more independent from pesticide concentration in soil solution than the adsorption method. By Soil Survey and Land Research Center (SSLRC)'s classification for pesticide mobility, alachlor and ethoprophos were classified into moderately mobile $(75{\leq}Koc<500)$, and ethalfluralin and pendimethalin were included to non-mobile class (Koc > 4000). Runoff and erosion loss of pesticides by three rainfall scenarios were from 1.0 to 6.4% and from 0.3 to 1.2% for alachlor, from 1.0 to 2.5% and from 1.7 to 10.1% for ethalfluralin, from 1.3 to 2.9% and from 3.9 to 10.8% for pendimethalin, and from 0.6 to 2.7% and from 0.1 % 0.3% for ethoprophos, respectively. Distribution of pesticides in soil profile were investigated after the simulated rainfall study. Alachlor and ethoprophos were leached to from 10 to 15 cm of soil layer, but ethalfluralin and pendimethalin were mostly remained at the top 5 cm of soil profile. The losses of the pesticides at 30% of sloping degree were from 0.2 to 1.9 times higher than those at 10%. The difference of their runoff loss was related with their concentration in runoff water while the difference of their erosion loss must be closely related with the quantity of soil eroded.

• Korean Chemical Engineering Research
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• v.57 no.1
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• pp.90-104
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• 2019

In this study, CALPUFF modeling was performed, using a real surface and upper air meterological data to predict trustworthy modeling-results. Pollutant-releases from windscreen chambers of enclosed poultry farms, P1 and P2, and from a open poultry farm, P3, and their diffusing behavior were modeled by CALPUFF modeling with volume sources as well as by finally-adjusted CALPUFF modeling where a linear velocity of upward-exit gas averaged with the weight of each directional-emitting area was applied as a model-linear velocity ($u^M_y$) at a stack, with point sources. In addition, based upon the scenario of poultry farm-releasing odor and particulate matter (PM) removal efficiencies of 0, 20, 50 and 80% or their corresponding emission rates of 100, 80, 50 and 20%, respectively, CALPUFF modeling was performed and concentrations of odor and PM were predicted at the region as a discrete receptor where civil complaints had been frequently filed. The predicted concentrations of ammonia, hydrogen sulfide, $PM_{2.5}$ and $PM_{10}$ were compared with those required to meet according to the offensive odor control law or the atmospheric environmental law. Subsequently their required removal efficiencies at poultry farms of P1, P2 and P3 were estimated. As a result, a priori assumption that pollutant concentrations at their discrete receptors are reduced by the same fraction as pollutant concentrations at P1, P2 and P3 as volume source or point source, were controlled and reduced, was proven applicable in this study. In case of volume source-adopted CALPUFF modeling, its required removal efficiencies of P1 compared with those of point source-adopted CALPUFF modeling, were predicted similar each other. However, In case of volume source-adopted CALPUFF modeling, its required removal efficiencies of both ammonia and $PM_{10}$ at not only P2 but also P3 were predicted higher than those of point source-adopted CALPUFF modeling. Nonetheless, the volume source-adopted CALPUFF modeling was preferred as a safe approach to resolve civil complaints. Accordingly, the required degrees of pollution prevention against ammonia, hydrogen sulfide, $PM_{2.5}$ and $PM_{10}$ at P1 and P2, were estimated in a proper manner.

• Korean Journal of Environment and Ecology
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• v.36 no.3
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• pp.303-317
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• 2022

Climate change caused by increased greenhouse gas emissions can alter the natural ecosystem, including the pollination ecosystem and agricultural ecology, which are ecological interactions between potted insects and plants. Many studies have reported that populations of wild bees, including bees and wasps (BW), which are the key pollinators, have gradually declined due to climate change, leading to adverse impacts on overall biodiversity, ultimately with agribusinesses and the life cycle of flowering plants. Therefore, we could infer that the rising temperature in Korean Peninsula (South Korea) due to global warming has led to climate change and influenced the wild bee's ecosystem. In this study, we surveyed the distributional pattern of BW (Superfamily: Apoidea, Vespoidea, and Chrysidoidea) at 51 sites from 2017 (37 sites) to 2018 (14 sites) to examine the effects of climatic factors on the nationwide distribution of BW in South Korea. Previous literature has confirmed that their distribution according to forest climate zones is significantly correlated with mean and accumulative temperatures. Based on the result, we predicted the effects of future climate changes on the BW distribution that appeared throughout South Korea and the species that appeared in specific climate zones using Shared Socioeconomic Pathways (SSPs). The distributions of wild BW predicted by the SSP scenarios 2-4.5 and 5-8.5 according to the BIOMOD species distribution model revealed that common and endemic species will shift northward from the current habitat distribution by 2050 and 2100, respectively. Our study implies that climate change and its detrimental effect on the ecosystem is ongoing as the BW distribution in South Korea can change, causing the change in the ecosystem in the Korean Peninsula. Therefore, immediate efforts to mitigate greenhouse gas emissions are warranted. We hope the findings of this study can inspire further research on the effects of climate change on pollination services and serve as the reference for making agricultural policy and BW conservation strategy

• Korean Journal of Environmental Biology
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• v.39 no.4
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• pp.526-535
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• 2021

Spatial sampling design plays an important role in GIS-based modeling studies because it increases modeling efficiency while reducing the cost of sampling. In the field of agricultural systems, research demand for high-resolution spatial databased modeling to predict and evaluate climate change impacts is growing rapidly. Accordingly, the need and importance of spatial sampling design are increasing. The purpose of this study was to design spatial sampling of paddy fields (11,386 grids with 1 km spatial resolution) in Korea for use in agricultural spatial modeling. A stratified random sampling design was developed and applied in 2030s, 2050s, and 2080s under two RCP scenarios of 4.5 and 8.5. Twenty-five weather and four soil characteristics were used as stratification variables. Stratification and sample allocation were optimized to ensure minimum sample size under given precision constraints for 16 target variables such as crop yield, greenhouse gas emission, and pest distribution. Precision and accuracy of the sampling were evaluated through sampling simulations based on coefficient of variation (CV) and relative bias, respectively. As a result, the paddy field could be optimized in the range of 5 to 21 strata and 46 to 69 samples. Evaluation results showed that target variables were within precision constraints (CV<0.05 except for crop yield) with low bias values (below 3%). These results can contribute to reducing sampling cost and computation time while having high predictive power. It is expected to be widely used as a representative sample grid in various agriculture spatial modeling studies.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.191-207
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• 2021

Up to this day, mobile communications have evolved rapidly over the decades, mainly focusing on speed-up to meet the growing data demands of 2G to 5G. And with the start of the 5G era, efforts are being made to provide such various services to customers, as IoT, V2X, robots, artificial intelligence, augmented virtual reality, and smart cities, which are expected to change the environment of our lives and industries as a whole. In a bid to provide those services, on top of high speed data, reduced latency and reliability are critical for real-time services. Thus, 5G has paved the way for service delivery through maximum speed of 20Gbps, a delay of 1ms, and a connecting device of 106/㎢ In particular, in intelligent traffic control systems and services using various vehicle-based Vehicle to X (V2X), such as traffic control, in addition to high-speed data speed, reduction of delay and reliability for real-time services are very important. 5G communication uses high frequencies of 3.5Ghz and 28Ghz. These high-frequency waves can go with high-speed thanks to their straightness while their short wavelength and small diffraction angle limit their reach to distance and prevent them from penetrating walls, causing restrictions on their use indoors. Therefore, under existing networks it's difficult to overcome these constraints. The underlying centralized SDN also has a limited capability in offering delay-sensitive services because communication with many nodes creates overload in its processing. Basically, SDN, which means a structure that separates signals from the control plane from packets in the data plane, requires control of the delay-related tree structure available in the event of an emergency during autonomous driving. In these scenarios, the network architecture that handles in-vehicle information is a major variable of delay. Since SDNs in general centralized structures are difficult to meet the desired delay level, studies on the optimal size of SDNs for information processing should be conducted. Thus, SDNs need to be separated on a certain scale and construct a new type of network, which can efficiently respond to dynamically changing traffic and provide high-quality, flexible services. Moreover, the structure of these networks is closely related to ultra-low latency, high confidence, and hyper-connectivity and should be based on a new form of split SDN rather than an existing centralized SDN structure, even in the case of the worst condition. And in these SDN structural networks, where automobiles pass through small 5G cells very quickly, the information change cycle, round trip delay (RTD), and the data processing time of SDN are highly correlated with the delay. Of these, RDT is not a significant factor because it has sufficient speed and less than 1 ms of delay, but the information change cycle and data processing time of SDN are factors that greatly affect the delay. Especially, in an emergency of self-driving environment linked to an ITS(Intelligent Traffic System) that requires low latency and high reliability, information should be transmitted and processed very quickly. That is a case in point where delay plays a very sensitive role. In this paper, we study the SDN architecture in emergencies during autonomous driving and conduct analysis through simulation of the correlation with the cell layer in which the vehicle should request relevant information according to the information flow. For simulation: As the Data Rate of 5G is high enough, we can assume the information for neighbor vehicle support to the car without errors. Furthermore, we assumed 5G small cells within 50 ~ 250 m in cell radius, and the maximum speed of the vehicle was considered as a 30km ~ 200 km/hour in order to examine the network architecture to minimize the delay.

• Korean Journal of Agricultural and Forest Meteorology
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• v.14 no.3
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• pp.132-141
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• 2012

Climate change impact assessment of cereal crop production in South Korea was performed using land attributes and daily weather data at a farm scale as inputs to crop models. Farmlands in South Korea were grouped into 68 crop-simulation zone units (CZU) based on major mountains and rivers as well as existing land use information. Daily weather data at a 1-km grid spacing under the A1B- and RCP8.5 scenarios were generated stochastically to obtain decadal mean of daily data. These data were registered to the farmland grid cells and spatially averaged to represent climate conditions in each CZU. Monthly climate data for each decade in 2001~2100 were transformed to 30 sets of daily weather data for each CZU by using a stochastic weather generator. Soil data and crop management information for 68 CZU were used as inputs to the CERES-rice, CERE-barley and CROPGRO-soybean models calibrated to represent the genetic features of major domestic cultivars in South Korea. Results from the models suggested that the heading or flowering of rice, winter barley and soybean could be accelerated in the future. The grain-fill period of winter barley could be extended, resulting in much higher yield of winter barley in most CZUs than that of rice. Among the three major cereal grain crops in Korea, rice seems most vulnerable to negative impact of climate change, while little impact of climate change is expected on soybeans. Because a positive effect of climate change is projected for winter barley, policy in agricultural production should pay more attention to facilitate winter barley production as an adaptation strategy for the national food security.

• Journal of Bio-Environment Control
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• v.30 no.4
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• pp.312-319
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• 2021

This study was conducted to investigate the effect of elevated carbon dioxide on the growth and physiological responses of peach 'Mihong' (Prunus persica). We simulated three different carbon dioxide conditions based on climate change scenarios RCP 8.5 in the sunlight phytotron rooms from April 22 to July 6, 2020; 400 µmol·mol^-1(present condition), 700 µmol·mol^-1 treatment(expecting carbon dioxide concentrations in mid-21st century), 940 µmol·mol^-1 treatment (expecting carbon dioxide concentrations in late 21st century). The average of maximum photosynthesis rate at 700 µmol·mol^-1(16.06 µmol·CO₂·m^-2·s^-1) was higher than those at 400 µmol·mol^-1(14.45 µmol·CO₂·m^-2·s^-1) and 940 µmol·mol^-1(15.96 µmol·CO₂·m^-2·s^-1) from May 22 to July 2. However, stomatal conductances at 700 µmol·mol^-1 and 940 µmol·mol^-1 were lower than those at the control. Also, the carbon dioxide saturation point in all treatments was reduced from 1,200 µmol·mol^-1 in the early stage of growth to 600-800 µmol·mol^-1 in the late stage of growth. The stomatal densities were decreased as carbon dioxide increased. The shoot lengths were decreased while the carbon dioxide was increased, but the increase of trunk diameter and leaf areas, shoot numbers were not statistically different. The fruit weight at 700 µmol·mol^-1(152.5 g) was higher than those at the control(141.8 g) and 940 µmol·mol^-1(147.4 g). The soluble solids were higher at 700 µmol·mol^-1, 940 µmol·mol^-1 compared to the control. These results suggest that a carbon dioxide elevated to 700 µmol·mol^-1 in the future may give a positive effect on the yield and fruit quality of peach 'Mihong' while a carbon dioxide elevated above 940 µmol·mol^-1 may affect negatively such as early senescence and loss of fruit set.

• Journal of Korean Society of Forest Science
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• v.111 no.4
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• pp.461-472
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• 2022

Natural and anthropogenic factors cause forest types to continuously change. Since the ratio of forest area by forest type is important information for identifying the characteristics of national forest resources, an accurate understanding of the prospect of forest type change is required. The study aim was to use National Forest Inventory (NFI) time-series data to understand the characteristics of forest type change and to estimate future prospects of nationwide forest type change. We used forest type change information from the fifth and seventh NFI datasets, climate, topography, forest stand, and disturbance variables related to forest type change to analyze trends and characteristics of forest type change. The results showed that the forests in Korea are changing in the direction of decreasing coniferous forests and increasing mixed and broadleaf forests. The forest sites that were changing from coniferous to mixed forests or from mixed to broadleaf forests were mainly located in wet topographic environments and climatic conditions. The forest type changes occurred more frequently in sites with high disturbance potential (high temperature, young or sparse forest stands, and non-forest areas). We used a climate change scenario (RCP 8.5) to establish a forest type change model (SVM) to predict future changes. During the 40-year period from 2015 to 2055, the SVM predicted that coniferous forests will decrease from 38.1% to 28.5%, broadleaf forests will increase from 34.2% to 38.8%, and mixed forests will increase from 27.7% to 32.7%. These results can be used as basic data for establishing future forest management strategies.