• Journal of the Korean earth science society
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• v.35 no.1
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• pp.1-18
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• 2014

The purpose of this study was to analyze the sensitivity of meteorological fields and the variation of concentration of particulate matters (PMs) due to aerosol schemes and dust options within the WRF-Chem model to estimate Asian dusts affected on 29 May 2008 in the Korean peninsula. The anthropogenic emissions within the model were adopted by the $0.5^{\circ}{\pm}0.5^{\circ}$ RETRO of the global emissions, and the photolysis option was by Fast-J photolysis. Also, three scenarios such as the RADM2 chemical mechanism and MADE/SORGAM aerosol, the MOSAIC 8 section aerosol, and the GOCART dust erosion were simulated for calculating Asian dust emissions. As a result, the scenario of the RADM2 chemical mechanism & MADE/SORGAM aerosol depicted higher concentration than the others' in both Asian dusts and the background concentration of PMs. By comparing of the daily mean of PM10 measured at each air quality monitoring site in Seoul with the scenario results, the correlation coefficient was 0.67, and the root mean square error was $44{\mu}gm^{-3}$. In addition, the air temperature, the wind speed, the planetary boundary layer height, and the outgoing long-wave radiation were simulated under conditions of no chemical option with these three scenarios within the WRF or WRF-Chem model. Both the spatial distributions of the PBL height and the wind speed of u component among the meteorological factors were similar to those of the Asia dusts in range of 1,800-3,000 m and $2-16ms^{-1}$, respectively. And, it was shown that both scenarios of the RADM2 chemical mechanism and MADE/SORGAM aerosol and the GOCART dust erosion were interacted on-line between meteorological factors and Asian dusts or aerosols within the model because the outgoing long-wave radiation was changed to lower than the others.

• Economic and Environmental Geology
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• v.34 no.4
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• pp.375-383
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• 2001

We extracted sea surface heights(SSH) from the TopexJPoseidon(T/P) radar altimeter data to compare with fhe SSH estimated from in-situ lide gauges(T/G) at Ulleungdo, Pohang, and SockcholMucko sites. Selection criteria such as wet/dry troposphere, ionosphere, and ocean tide were used to estimate accurate SSH. For time series analysis, the one-hour interval tide gauge SSHs were resampled al lO-day interval of the satellite SSHs. The ocean tide model applied in the altimeter data processing showed periodic aliasings of 175.5 day, 87.8 day, 62J day, 58.5 day, 49.5 day and 46.0 day, and, hence, the ZOO-day filtering was applied to reduce these spectral noises. Wavenumber correlation analysis was also applied to extract common components between the two SSHs, resulting in enhancing the correlation coefficient(CC) dramatically. The original CCs between the satenite and tide gauge SSHs are 0.46. 0.26, and 0.]5, respectively. Ulleungdo shows the largest cc bec;luase the site is far from the coast resulting in the minimun error in the satellite observations. The CCs were then increased to 0.59, 030, and 0.30, respectively, after 200.day filtering, and to 0.69, 0.63. and 0.59 after removing inversely correlative components using wavenumber correlation analysis. The CCs were greatly increased by 87, 227, and 460% when the wavenumber correlation analysis was followed by 2oo-day filtering, resulting in the final CCs of 0.86, 0.85, 0.84, respectively. It was found that the best SSHs were estimated when the two methods were applied to the original data. The low-pass filtered TIP SSHs were found to be well correlated with the TIG SSHs from tide gauges, and the best correlation results were found when we applied both low-pass filtering and spectral correlation analysis to the original SSHs.

• Economic and Environmental Geology
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• v.51 no.2
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• pp.99-111
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• 2018

In this study three target radionuclides ($^{60}Co$, $^{137}Cs$, and $^{125}Sb$) were reacted with solid samples collected from the nuclear facility sites to investigate their sorption and mobility behaviors for preparing unexpected nuclear accidents. The highest sorption distribution coefficients ($K_{ds}$) of target radionuclides ($^{60}Co=947mL/g$, $^{137}Cs=2105mL/g$, $^{125}Sb=81.3mL/g$) were found in topsoil layer under groundwater condition, and the $K_d$ values of three radionuclides decreased in the order of fractured rock and bedrock samples under the same groundwater condition. High $K_d$ values of $^{60}Co$ in topsoil layer and fracture rock resulted from the clay minerals present, and the $K_d$ values decreased 58-69 % under seawater condition due to high ionic strength. $^{137}Cs$ sorption was controlled by the ion exchange reaction with $K^+$ on flayed edge sites (FES) of mica. The $^{137}Cs$ sorption was the most affected by seawater (89-97 % decrease), while $^{125}Sb$ sorption was not much affected by seawater. As the results of column and batch experiments, the retardation factors (R) of $^{137}Cs$, $^{60}Co$, and $^{125}Sb$ were determined about 5400-7400, 2000-2500, and 250-415, respectively, indicating no significant transport for these radionuclides even in fractured zone with groundwater. These results suggest that even in the case of severe nuclear accident at the nuclear facilities the mobility of released radionuclides ($^{60}Co$, $^{137}Cs$, and $^{125}Sb$) can be significantly retarded by the topsoil layer and fractured rock. In addition, the results of this study will be used for the safety and environmental performance assessment of nuclear facilities.

• Korean Journal of Agricultural and Forest Meteorology
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• v.9 no.3
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• pp.188-194
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• 2007

The relationships between pine mushroom emergence and meteorological factors were analyzed with three years (from 2003 to 2005) of measurement data at Yangyang site, in order to evaluate the effect of micrometeorological environment on pine mushroom production. fine mushroom was daily monitored and collected in the survey area during the its producing period (approximately one month). Pine mushroom production was highest in 2005 with the meteorological conditions of high temperature and frequent rainfalls in October. The production was lowest in 2004 due to dry conditions from mid September to late October, The meterological factors related to humidity (i.e., relative humidity, soil water content, and precipitation) were better correlated than those related to temperature (i.e., air and soil temperature, soil heat flux and solar radiation) with pine mushroom production. However, all of the correlation coefficients were statistically insignificant with values ranging from 0.15 to 0.46. Such poor correlations may be attributed to various other environmental conditions (e.g., topography, soil, vegetation, other fungi, the relationship between pine mushroom and pine forest) affecting pine mushroom production. We found that a mycelium requires a stimulation of low temperature (of three-day moving average) below $19.5^{\circ}C$, in order to farm a mushroom primordium which grows to pine mushroom after 16 days from the stimulation. We also found that the pine mushroom production ended when the soil temperature (of three-day moving average) fell below $14.0^{\circ}C$.

• Journal of Korean Society of Environmental Engineers
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• v.31 no.11
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• pp.947-956
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• 2009

Residual petroleum hydrocarbons after an oil spill may accumulate in the marine benthic ecosystem due to their high hydrophobicity. A lot of monitoring data are required for the estimation of ecosystem exposure to residual petrochemicals in an ecological risk assessment in the affected region. To save time and cost, the environmental exposure to them in the affected ecosystem can also be assessed using a simple food-web bioaccumulation model. In this study, we evaluated residual concentrations of four selected polycyclic aromatic hydrocarbons (phenanthrene, anthracene, pyrene, and benzo[a]pyrene) in a hypothetic benthic ecosystem composed of six species under two exposure scenarios. Body-residue concentration ranged 5~250 mg/kg body depending on trophic positions in an extreme scenario in which the aqueous concentrations of PAHs were assumed to be one-tenth of their aqueous solubility. In addition, bioconcentration factors (BCFs) and bioaccumulation factors (BAFs) were evaluated for model species. The logarithm of bioconcentration factor (log BCF) linearly increased with increasing the logarithm of 1-octanol-water partition coefficient (log $K_{OW}$) until log $K_{OW}$ of 7.0, followed by a gradual decrease with further increase in log $K_{OW}$ without metabolic degradation. Biomagnification became significant when log $K_{OW}$ of a pollutant exceeded 5.0 in the model ecosystem, indicating that investigation of food-web structure should be critical to predict biomagnifications in the affected ecosystem because log $K_{OW}$ values of many petrochemicals are higher than 5.0. Although further research is required for better site-specific evaluation of exposure, the model simulation can be used to estimate the level of the ecosystem exposure to residual oil contaminants at the screening level.

• Journal of the Korean Society of Groundwater Environment
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• v.1 no.1
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• pp.23-32
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• 1994

To determine the apparent equilibrium constants, K$_{ad,app}$, for the adsorption reactions of trace metals on amorphous iron oxyhydroxide (AIO) in the Taebag coal mine area, time-adsorption and pH-adsorption experiments were performed for a selected bottom sediment mainly comprised of AIO from the study area. The results from the adsorption experiments indicate that most of the trace metals, except Pb, achieve equilibrium states with AIO and thus, the calculated K$_{ad,app}$ may represent the true apparent equilibrium constants. K$_{ad,app}$ and the stoichiometric coefficients of proton, x, of the adsorption reactions between the trace metals and AIO were respectively calculated from the intercepts and slopes of the regression lines of log($\Gamma$/ ［M］$_{aq}$)against pH provided by pH-adsorption experiments. The calculated K$_{ad,app}$ this study has the values of the range from 10$^{－4.5}$ to 10$^{2.75}$ , which is much different from the reported values by other investigators for simple experimental systems. K$_{ad,app}$ of this study is more or less close but not exactly pertinent to the estimated values for the other natural systems. It indicates that K$_{ad,app}$ for the adsorption reactions in the aquatic system in the study area is unique and thus should be determined befor the adsorption modelling. The calculated x of this study has the values of the range from -0.3 to 0.7, which is also much different from what most geochemists generally accept. The discrepancy in x may be due to the competition among different kinds of ionic species on the adsorption site or simulataneous occurrence of different kinds of adsorption reactions. The results from this study should help construct an appropriate adsorption model for the aquatic systems polluted by the coal mine drainage in the Taebag area. With the constructed model, one can describe the concentration variations of trace metals due to the adsorption in the system, which is an essential part of the investigation on the water quality affected by coal mine drainage in the Taebag coal field.

• Korean Journal of Occupational Health Nursing
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• v.11 no.1
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• pp.13-30
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• 2002

Industrial shift workers feels suffer mental stresses which are caused by unfamiliar day sleep, noisy environment, sleeping disorder by bright light, unusual contacts with family, difficulty in meeting with friends or having formal social meetings and other social limitations such as the use of transportation. Such stresses influence health of the workers negatively. Thus the health promotion policy for shift workers should be made considering the workers' ways of living and shift work specially. This study attempted to provide basic information for development of the health promotion program for industrial shift workers by examining predictive factors influencing health promotion behaviors of those workers. In designing the study, three power generation plants located in Pusan and south Kyungsang province were randomly selected and therefrom 280 workers at central control, boiler and turbine rooms and environmental chemistry parts whose processes require shift works were sampled as subjects of the study. Data were collected two times from September 17 to October 8, 1999 using questionnaires with helps of safety and health managers of the plants. The questionnaires were distributed through mails or direct visits. Means for the study included the measurement tool of health promotion behavior provided by Park(1995), the tool of self-efficacy measurement by Suh(1995), the tool of internal locus of control measurement by Oh(1987), the measurement tool of perceived health state by Park(1995) and the tool of social support measurement by Paek(1995). The collected data were analyzed using SPSS program. Controlling factors of the subjects were evaluated in terms of frequency and percentage ratio Perceived factors and health promotion behaviors of the subjects were done so in terms of mean and standard deviation, and average mark and standard deviation, respectively. Relations between controlling and perceived factors were analyzed using t-test and ANOVA and those between perceived factors and the performance of health promotion behaviors, using Pearson's Correlation Coefficient. The performance of health promotion behaviors was tested using t-test, ANOVA and post multi-comparison (Scheffe test). Predictive factors of health promotion behavior were examined through the Stepwise Multiple Regression Analysis. Results of the study are summarized as follows. 1. The performance of health promotion behaviors by the subjects was evaluated as having the value of mean, $161.27{\pm}26.73$ points(min.:60, max.:240) and average mark, $2.68{\pm}0.44$ points(min.:1, max.:4). When the performance was analyzed according to related aspects, it showed the highest level in harmonious relation with average mark, $3.15{\pm}.56$ points, followed by hygienic life($3.03{\pm}.55$), self-realization ($2.84{\pm}.55$), emotional support($2.73{\pm}.61$), regular meals($2.71{\pm}.76$), self-control($2.62{\pm}.63$), health diet($2.62{\pm}.56$), rest and sleep($2.60{\pm}.59$), exercise and activity($2.53{\pm}.57$), diet control($2.52{\pm}.56$) and special health management($2.06{\pm}.65$). 2. In relations between perceived factors of the subjects(self-efficacy, internal locus of control, perceived health state) and the performance of health promotion behaviors, the performance was found having significantly pure relations with self-efficacy (r=.524, P=.000), internal locus of control (r=.225, P=.000) and perceived health state(r=.244, P=.000). The higher each evaluated point of the three factors was, the higher the performance was in level. 3. When relations between the controlling factors(demography-based social, health-related, job-related and human relations characteristics) and the performance of health promotion behaviors were analyzed, the performance showed significant differences according to marital status (t=2.09, P= .03), religion(F=3.93, P= .00) and participation in religious activities (F=8.10, P= .00) out of demography-based characteristics, medical examination results (F=7.20, P= .00) and methods of the collection of health knowledge and information(F=3.41, P= .01) and methods of desired health education(F=3.41, P= .01) out of health-related characteristics, detrimental factors perception(F=4.49, P= .01) and job satisfaction(F=8.41, P= .00) out of job-related characteristics and social support(F=14.69, P= .00) out of human relations characteristics. 4. The factor which is a variable predicting best the performance of health promotion behaviors by the subjects was the self-efficacy accounting for 27.4% of the prediction, followed by participation in religious activities, social support, job satisfaction, received health state and internal locus of control in order all of which totally account for 41.0%. In conclusion, the predictive factor which most influence the performance of health promotion behaviors by shift workers was self-efficacy. To promote the sense, therefore, it is necessary to develop the nursing intervention program considering predictive factors as variables identified in this study. Further industrial nurses should play their roles actively to help shift workers increase their capability of self-management of health.

• Nuclear Medicine and Molecular Imaging
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• v.43 no.1
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• pp.72-78
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• 2009

Purpose: Bone mineral density (BMD) measurements need to be precise enough to be capable of detecting small changes in bone mass of rats. Using a regular dual-energy X-ray absorptiometry (DXA), we measured many BMD of various skeletal sites in rats to examine precision of DXA in relation to the repositioning on the bones of rats. Materials and Methods: Using DXA and small animal software, scans were performed 4 times in all 12 male rats without repositioning (Group 1a). Another four scans for 6 of 12 rats were done with repositioning between scans (Group 2). Customized regions of interest (ROIs), encapsulate the right hind limb, L1-4, skull and pelvic bones were drawn at each measurement. The precision of the measurements was evaluated by measuring the coefficient of variation (CV) of four measurements of BMD at each skeletal site of all rats with or without repositioning. Significance of differences between group 1b (six rats out of group 1a, which were come under group 2) and group2 were evaluated with Wilcoxon Signed Rank Sum Test. Results: CVs obtained at different skeletal sites of all measurements in Group 1b and 2. It was $3.51{\pm}1.20$, $ 2.62{\pm}1.20$ for the hindlimb (p=0.173), $3.83{\pm}2.02$, $4.59{\pm}2.02$ for L1-4 (p=0.600), $3.73{\pm}1.87$, $1.53{\pm}0.89$ for skull (p=0.046), and $2.92{\pm}0.60$, $1.45{\pm}0.60$ for pelvic bones (p=0.075). Conclusion: Our study demonstrates that the DXA technique has the precision necessary when used to assess BMD for various skeletal sites in rats regardless of repositioning.

• The Korean Journal of Nuclear Medicine Technology
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• v.14 no.1
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• pp.122-126
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• 2010

Purpose: F-18-FPCIT that shows strong familiarity with DAT located at a neural terminal site offers diagnostic information about DAT density state in the region of the striatum especially Parkinson's disease. In this study, we altered the iteration and subset and measured SUV${\pm}$SD and Contrasts from phantom images which set up to specific iteration and subset. So, we are going to suggest the appropriate range of the iteration and subset. Materials and Methods: This study has been performed with 10 normal volunteers who don't have any history of Parkinson's disease or cerebral disease and Flangeless Esser PET Phantom from Data Spectrum Corporation. $5.3{\pm}0.2$ mCi of F-18-FPCIT was injected to the normal group and PET Phantom was assembled by ACR PET Phantom Instructions and it's actual ratio between hot spheres and background was 2.35 to 1. Brain and Phantom images were acquired after 3 hours from the time of the injection and images were acquired for ten minutes. Basically, SIEMENS Bio graph 40 True-point was used and True-X method was applied for image reconstruction method. The iteration and Subset were set to 2 iterations, 8 subsets, 3 iterations, 16 subsets, 6 iterations, 16 subsets, 8 iterations, 16 subsets and 8 iterations, 21 subsets respectively. To measure SUVs on the brain images, ROIs were drawn on the right Putamen. Also, Coefficient of variance (CV) was calculated to indicate the uniformity at each iteration and subset combinations. On the phantom study, we measured the actual ratio between hot spheres and back ground at each combinations. Same size's ROIs were drawn on the same slide and location. Results: Mean SUVs were 10.60, 12.83, 13.87, 13.98 and 13.5 at each combination. The range of fluctuation by sets were 22.36%, 10.34%, 1.1%, and 4.8% respectively. The range of fluctuation of mean SUV was lowest between 6 iterations 16 subsets and 8 iterations 16 subsets. CV showed 9.07%, 11.46%, 13.56%, 14.91% and 19.47% respectively. This means that the numerical value of the iteration and subset gets higher the image's uniformity gets worse. The range of fluctuation of CV by sets were 2.39, 2.1, 1.35, and 4.56. The range of fluctuation of uniformity was lowest between 6 iterations, 16 subsets and 8 iterations, 16 subsets. In the contrast test, it showed 1.92:1, 2.12:1, 2.10:1, 2.13:1 and 2.11:1 at each iteration and subset combinations. A Setting of 8 iterations and 16 subsets reappeared most close ratio between hot spheres and background. Conclusion: Findings on this study, SUVs and uniformity might be calculated differently caused by variable reconstruction parameters like filter or FWHM. Mean SUV and uniformity showed the lowest range of fluctuation at 6 iterations 16 subsets and 8 iterations 16 subsets. Also, 8 iterations 16 subsets showed the nearest hot sphere to background ratio compared with others. But it can not be concluded that only 6 iterations 16 subsets and 8 iterations 16 subsets can make right images for the clinical diagnosis. There might be more factors that can make better images. For more exact clinical diagnosis through the quantitative analysis of DAT density in the region of striatum we need to secure healthy people's quantitative values.

• Korean Journal of Agricultural and Forest Meteorology
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• v.22 no.3
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• pp.215-231
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• 2020

Forest landscape models (FLMs) can be used to investigate the complex interactions of various ecological processes and patterns, which makes them useful tools to evaluate how environmental and anthropogenic variables can influence forest ecosystems. However, due to the large spatio-temporal scales in FLMs studies, parameterization and validation can be extremely challenging when applying to new study areas. To address this issue, we focused on the parameterization and application of a spatially explicit forest landscape model, LANDIS-II, to Mt. Gyebang, South Korea, with the use of the National Forest Inventory (NFI) and long-term ecological research (LTER) site data. In this study, we present the followings for the biomass succession extension of LANDIS-II: 1) species-specific and spatial parameters estimation for the biomass succession extension of LANDIS-II, 2) calibration, and 3) application and validation for Mt. Gyebang. For the biomass succession extension, we selected 14 tree species, and parameterized ecoregion map, initial community map, species growth characteristics. We produced ecoregion map using elevation, aspect, and topographic wetness index based on digital elevation model. Initial community map was produced based on NFI and sub-alpine survey data. Tree species growth parameters, such as aboveground net primary production and maximum aboveground biomass, were estimated from PnET-II model based on species physiological factors and environmental variables. Literature data were used to estimate species physiological factors, such as FolN, SLWmax, HalfSat, growing temperature, and shade tolerance. For calibration and validation purposes, we compared species-specific aboveground biomass of model outputs and NFI and sub-alpine survey data and calculated coefficient of determination (R²) and root mean square error (RMSE). The final model performed very well, with 0. 98 R² and 8. 9 RMSE. This study can serve as a foundation for the use of FLMs to other applications such as comparing alternative forest management scenarios and natural disturbance effects.