• Wind and Structures
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• v.7 no.3
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• pp.159-172
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• 2004

The study of how buildings affect wind flow is an important part of the research being conducted on urban climate and urban air quality. NJU-UCFM, a standard $k-{\varepsilon}$ turbulence closure model, is presented and is used to simulate how the following affect wind flow characteristics: (1) an isolated building, (2) urban canyons, (3) an irregular shaped building cluster, and (4) a real urban neighborhood. The numerical results are compared with previous researchers' results and with wind tunnel experiment results. It is demonstrated that the geometries and the distribution of urban buildings affect airflow greatly, and some examples of this include a changing of the vortices behind buildings and a "channeling effect". Although the mean air flows are well simulated by the standard $k-{\varepsilon}$ models, it is important to pay attention to certain discrepancies when results from the standard $k-{\varepsilon}$ models are used in design or policy decisions: The standard $k-{\varepsilon}$ model may overestimate the turbulence energy near the frontal side of buildings, may underestimate the range of high turbulence energy in urban areas, and may omit some important information (such as the reverse air flows above the building roofs). In ideal inflow conditions, the effects of the heights of buildings may be underestimated, when compared with field observations.

• Korean Journal of Soil Science and Fertilizer
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• v.48 no.5
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• pp.413-420
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• 2015

Objective of this study was to investigate adsorption characteristics and kinetic models of $NH_4-N$ to biochar produced from rice hull in respective to mitigation of greenhouse gases. $NH_4-N$ concentration was analyzed by UV Spectrophotometer. For the experiment, the soil texture used in this study was sandy loam soil, and application rates of chemical fertilizer and pig compost were $420-200-370kgha^{-1}$ (N-P-K) and $5,500kgha^{-1}$ as recommended amount after soil test for corn cultivation. Biochar treatments were 0.2-5% to soil weight. Its adsorption characteristic was investigated with application of Langmuir isotherm, and pseudo-first order kinetic model and pseudo-second order kinetic model were used as kinetic models. Adsorption amount and removal rates of $NH_4-N$ were $39.3mg^{-1}$ and 28.0% in 0.2% biochar treatment, respectively. The sorption of $NH_4-N$ to biochar was fitted well by Langmiur model because it was observed that dimensionless constant ($R_L$) was 0.48. The maximum adsorption amount ($q_m$) and binding strength constant (b) were calculated as $4.1mgg^{-1}$ and $0.01Lmg^{-1}$ in Langmuir isotherm, respectively. The pseudo-second order kinetic model was more appropriate than pseudo-first order kinetic model for high correlation coefficient ($r^2$) of pseudo-second order kinetic model. Therefore, biochar produced from rice hull could reduce $N_2O$ by adsorbing $NH_4-N$ to biochar cooperated in sandy loam soil.

• Ocean and Polar Research
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• v.30 no.3
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• pp.325-334
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• 2008

A biogeochemical model was used to estimate air-sea $CO_2$ exchange over the East China Sea. Since fresh water discharge from the Changjiang River and relevant chemistry were not considered in the employed model, we were not able to produce accurate results around the Changjiang River mouth. This factor aside, the model showed that the East China Sea, away from the Changjiang River mouth, takes approximately $1.5{\sim}2\;mole\;m^{-2}yr^{-1}$ of $CO_2$ from the atmosphere. The model also showed that biological factors modify the air-sea $CO_2$ flux by only a few percent when we assumed that biological activity increased two-fold. Therefore, we can argue that the biological effect is not strong enough over this area within the framework of the current phosphate-based biological model. Compared to the preindustrial era, in 1995 the East China Sea absorbed $0.4{\sim}0.8\;mole\;m^{-2}yr^{-1}$ more $CO_2$. If warming of the sea surface is considered, in addition to the increase in atmospheric $CO_2$ concentration, by 2045 the East China Sea would absorb $0.2{\sim}0.4\;mole\;m^{-2}yr^{-1}$ less $CO_2$ compared to the non-warming case.

• Korean Journal of Environmental Agriculture
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• v.30 no.4
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• pp.357-366
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• 2011

BACKGROUND: Mathematical model such as GLEAMS have been developed and successfully applied to upland fields to estimate the level of pesticide residues in soil. But, the GLEAMS model rarely applied to the Korean conditions. METHODS AND RESULTS: To evaluate pesticide transport in soil residue using the GLEAMS model from pepper plot, Alachlor, Endosulfan, Cypermethrin and Fenvalerate were applied for standard and double rate. Soil sampling was conducted and decaying patterns of pesticides were investigated. Observed climate data such as temperature and irrigation amount were used for hydrology simulation. The observed pesticide residue data of 2008 were used for parameter calibration, and validation of GLEAMS model was conducted with observed data of 2009. After calibration, the $K_{oc}$ (Organic carbon distribution coefficient) and WSHFRC (Washoff fraction) parameters were identified as key parameters. The simulated concentrations of the pesticides except Fenvalerate were sensitive to $K_{oc}$ parameter. Overall, soil residue concentrations of Alachlor, Cypermethrin and Fenvalerate were fairly simulated compared to those of Endosulfan. The applicability of the GLEAMS model was also confirmed by statistical analysis. CONCLUSION(s): GLEAMS model was eligible for evaluation of pesticide soil residue for Alachlor, Cypermethrin and Fenvalerate.

• Korean Journal of Agricultural Science
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• v.47 no.4
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• pp.1097-1107
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• 2020

Assessment of soil carbon stock is essential for climate change mitigation and soil fertility. The digital soil mapping (DSM) is well known as a general technique to estimate the soil carbon stocks and upgrade previous soil maps. The aim of this study is to calculate the soil carbon stock in the top soil layer (0 to 30 cm) in Jeolla Province of South Korea using the DSM technique. To predict spatial carbon stock, we used Cubist, which a data-mining algorithm model base on tree regression. Soil samples (130 in total) were collected from three depths (0 to 10 cm, 10 to 20 cm, 20 to 30 cm) considering spatial distribution in Jeolla Province. These data were randomly divided into two sets for model calibration (70%) and validation (30%). The results showed that clay content, topographic wetness index (TWI), and digital elevation model (DEM) were the most important environmental covariate predictors of soil carbon stock. The predicted average soil carbon density was 3.88 kg·m-2. The R2 value representing the model's performance was 0.6, which was relatively high compared to a previous study. The total soil carbon stocks at a depth of 0 to 30 cm in Jeolla Province were estimated to be about 81 megatons.

• Journal of Environmental Science International
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• v.23 no.11
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• pp.1827-1833
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• 2014

This study has been carried out to present the valuation system of soil carbon sequestration potentials of soil in accordance with the new climate change scenarios(RCP). For that, by analyzing variation of soil carbon of the each type of agricultural land use, it aims to develop technology to increase the amount of carbon emissions and sequestration. Among the factors which affects the estimation of determining the soil carbon model and influence power after the measurement on soil organic carbon, under the center of a causal relationship between the explanatory variables this study were investigated. Chemical fertilizers (NPK) decreased with increasing the amount of soil organic carbon and as with the first experimental results, when cultivating rice than pepper, the fact that soil organic carbon content increased has been found out. The higher the carbon dioxide concentration, the higher the amount of organic carbon in the soil and this result is reliable under a 10% significance level. On the other hand, soil organic carbon, humus carbon and hot water extractable carbon has been found out that was not affected the soils depth, sames as the result of the first year. The higher concentration of carbon dioxide, the higher carbon content of humus and hot water extractable carbon content. According to IPCC 2006 Guidelines and the new climate change scenario RCP 4.5 and the measurement results of the total amount of soil organic carbon to the crops due to abnormal climate weather, 1% increase in atmospheric carbon dioxide concentration was found to be small when compared to the growing rate of increasing 0.01058% of organic carbon in the soil.

• Journal of the Korean earth science society
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• v.43 no.1
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• pp.60-76
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• 2022

This study presents a software full setup and the following test execution times in a Linux cluster for the United Kingdom Earth System Model (UKESM) and then compares the model results from control and experimental simulations of the UKESM relative to various observations. Despite its low resolution, the latest version of the UKESM can simulate tropospheric chemistry-aerosol processes and the stratospheric ozone chemistry using the United Kingdom Chemistry and Aerosol (UKCA) module. The UKESM with UKCA (UKESM-UKCA) can treat atmospheric chemistryaerosol-cloud-radiation interactions throughout the whole atmosphere. In addition to the control UKESM run with the default CMIP5 SO₂ emission dataset, an experimental run was conducted to evaluate the aerosol effects on meteorology by changing atmospheric SO₂ loading with the newest REAS data over East Asia. The simulation period of the two model runs was 28 years, from January 1, 1982 to December 31, 2009. Spatial distributions of monthly mean aerosol optical depth, 2-m temperature, and precipitation intensity from model simulations and observations over East Asia were compared. The spatial patterns of surface temperature and precipitation from the two model simulations were generally in reasonable agreement with the observations. The simulated ozone concentration and total column ozone also agreed reasonably with the ERA5 reanalyzed one. Comparisons of spatial patterns and linear trends led to the conclusion that the model simulation with the newest SO₂ emission dataset over East Asia showed better temporal changes in temperature and precipitation over the western Pacific and inland China. Our results are in line with previous finding that SO₂ emissions over East Asia are an important factor for the atmospheric environment and climate change. This study confirms that the UKESM can be installed and operated in a Linux cluster-computing environment. Thus, researchers in various fields would have better access to the UKESM, which can handle the carbon cycle and atmospheric environment on Earth with interactions between the atmosphere, ocean, sea ice, and land.

• Journal of Environmental Science International
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• v.22 no.2
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• pp.235-242
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• 2013

The purpose of this article is analyzing the impacts of climate change on winter chinese cabbage yield in Korea, with employing a panel data regression model. Our results show that there is a negative impacts of high temperature and precipitation amount on winter chinese cabbage yields. Especially high temperature and rainfall in September cause serious damage to winter chinese cabbage yield. According to the reduction schedule on greenhouse gas emission(RCP 4.5 scenario.), winter chinese cabbage yield would be 7.7% lower than it is, for reasons of high temperature and rainfall damages by the end of 21st century.

• Journal of Korean Society for Atmospheric Environment
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• v.29 no.6
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• pp.838-848
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• 2013

The Community Multiscale Air Quality (CMAQ) model is capable of providing high quality atmospheric chemistry profiles through the utilization of high-resolution meteorology and emissions data. However, it cannot simulate air quality accurately if input data are not appropriate and reliable. One of the most important inputs required by CMAQ is the air pollutants emissions, which determines air pollutants concentrations during the simulation. For the CMAQ simulation of Korean peninsula, we, in general, use the Korean National Emission Inventory data which are estimated by Clean Air Policy Support System (CAPSS). However, since they are not provided by model-ready emission data, we should convert CAPSS emissions into model-ready data. The SMOKE is the emission model we used in this study to generate CMAQ-ready emissions. Because processing the emissions data is very monotonous and tedious work, we have developed CAPSS2SMOKE program to convert CAPSS emissions into SMOKE-ready data with ease and effective. CAPSS2SMOKE program consists of many codes and routines such as source classification code, $PM_{10}$ to $PM_{2.5}$ ratio code, map projection conversion routine, spatial allocation routine, and so on. To verify the CAPSS2SMOKE program, we have run SMOKE using the CAPSS 2009 emissions and found that the SMOKE results inherits CAPSS emissions quite well.

• Journal of Ecology and Environment
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• v.33 no.4
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• pp.377-389
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• 2010

Understanding the factors relevant to endangerment and the patterns of habitat locations in relation to protected areas is critically important for the conservation of rare species. Although 64 plant species have recently been listed as endangered species in Korea, this information has, until now, not been available, making appropriate management and conservation strategies impossible to devise. Thus, we collected information on potentially threatening factors, as well as information on the locations in which these species were observed. The potentially threatening factors were classified into seven categories. National parks, provincial parks, ecosystem conservation areas, and wetland conservation areas were defined as protected conservation areas. Korean digital elevation model data, along with the maps of all protected areas were combined with the maps of endangered plant species, and analyzed via Geographic Information Systems (GIS). Excluding the category of "small population", endangered plant species in Korea were associated more frequently with extrinsic factors than intrinsic factors. Considering land surface only, all conservation areas in Korea totaled 4.9% of the land, far lower than International Union for Conservation of Nature and Natural Resources (IUCN)'s 10% coverage target. At the species level, 69% of the endangered plant species were detected in conservation areas, mostly in national parks. However, this result demonstrates that 31% of endangered species inhabit areas outside the conservation zones. Furthermore, at the habitat level, a large proportion of endangered species were found to reside in unprotected areas, revealing "gaps" in protected land. In the face of rapid environmental changes such as population increases, urbanization, and climate changes, converting these gap areas to endangered species' habitats, or at least including them in habitat networks, will help to perpetuate the existence of endangered species.