• Korean Journal of Environment and Ecology
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• v.34 no.4
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• pp.282-293
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• 2020

This study investigated a long-term variation trend of water quality, fish compositions, and ecological health conditions in the Gwanpyeong stream located in the nearby Daejeon metropolitan city to understand the impact of urban development projects on the aquatic ecosystem. The sampling was made in four surveys (2009, 2010, 2016, 2019) before and after urbanization. The urban development was conducted in 2008, resulting in the stream's ecological disturbance, and the stream restoration was conducted in 2012. Thus, stream monitoring was conducted to analyze the ecological trends before and after the restoration. The multi-metric models for Fish Assessment Index(FAI) and necropsy-based Health Assessment Index(HAI) were applied in the fish community and organ-level, respectively, to assess the ecological health of the stream. Minimum turbidity and chlorophyll-a(Chl-a) occurred in the mid-stream(St. 2), and this was probably due to rapid current velocity in the riffle zone. We collected 18 fish species, and the dominant species was Zacco platypus (40.6%). In 2016 immediately after the stream restoration, the relative proportions of sensitive species and insectivore species were the highest along with highest values in the species diversity and species richness index, resulting in the best condition in the ecological health, based on FAI model values. However, the ecological health, based on the FAI, became worse in the latest survey conducted in 2019. The analysis of the HAI model based on the organ-level approach showed skin erosion in the fish of upper stream, kidney defects in downstream, and the liver and gill defects observed in all sites, indicating that the anatomical health was also affected.

• Journal of Soil and Groundwater Environment
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• v.12 no.1
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• pp.53-63
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• 2007

Soil risk assessment models were used to determine the goals of soil remediation and to establish the soil quality standards in developed countries. Recently, Korean Ministry of Environment prepared the guideline for soil risk assessment. Soil risk assessment model applicable to Korean situation will be needed in the near future. In this study, three models for soil risk assessment were extensively compared to suggest the fundamental components that required for the soil risk assessment in Korea. The models considered in this study were CalTOX in the United States, CLEA (Contaminated Land Exposure Assessment) in the United Kingdom, and CSOIL in the Netherlands. The major exposure routes and the intake estimation equations suitable for Korean situation were suggested. The exposure routes suggested were intake of the crops, underground water, indoor outdoor soil ingestion, dust inhalation and a volatile matter inhalation. The equations for intake estimation used in CalTOX and CSOIL seem to be applicable for the calculation of the human intake in Korea.

• Journal of the Korean GEO-environmental Society
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• v.13 no.6
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• pp.83-90
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• 2012

Generally, the effect of the cement deep mixing method on the improvement of clay ground is far greater than the effect of physical improvement. Although it leads to great improvement strength in the initial stage, there are not many constructional precedents in Korea and it is hard to manage quality according to the cement-clay mixing method. In order to figure out the strength characteristics according to the mixing ratio of cement, sand, and clay and the improvement characteristics of weak ground according to the forms of the specimens to be improved, marine clay was used in this study to conduct the uniaxial compression test and soil bin model test. The test piece specimens for the uniaxial compression test were mixed with sand in a fixed ratio with the criterion of the water cement ratio. The cement was mixed with clay in the ratios of 10%, 20%, 30%, and 40% to the clay weight. The moisture content of the soil ground was made in the ratios of 40%, 60%, and 80%. The test piece specimens went through curing by moistening for 7, 14, and 28 days and underwent the uniaxial compression test according to the curing period. For the bearing test, the soil bin models were made and the ground improved in the Mat type was formed. After that, the bearing strength was compared in this study according to the improvement ratio and analyzed the intervening effect between the walls of the improved specimens.

• Journal of Environmental Science International
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• v.28 no.3
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• pp.341-356
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• 2019

In this study, the impacts of local meteorology caused by tidal changes in the West Sea on ozone distributions in the Seoul Metropolitan Area (SMA) were analyzed using a meteorological model (WRF) and an air quality (CMAQ) model. This study was carried out during the day (1200-1800 LST) between August 3 and 9, 2016. The total area of tidal flats along with the tidal changes was calculated to be approximately $912km^2$, based on data provided by the Environmental Geographic Information Service (EGIS) and the Ministry of Oceans and Fisheries (MOF). Modeling was carried out based on three experiments, and the land cover of the tidal flats for each experiment was designed using the coastal wetlands, water bodies (i.e., high tide), and the barren or sparsely vegetated areas (i.e., low tide). The land cover parameters of the coastal wetlands used in this study were improved in the herbaceous wetland of the WRF using updated albedo, roughness length, and soil heat capacity. The results showed that the land cover variation during high tide caused a decrease in temperature (maximum $4.5^{\circ}C$) and planetary boundary layer (PBL) height (maximum 1200 m), and an increase in humidity (maximum 25%) and wind speed (maximum $1.5ms^{-1}$). These meteorological changes increased the ozone concentration (about 5.0 ppb) in the coastal areas including the tidal flats. The increase in the ozone concentration during high tide may be caused by a weak diffusion to the upper layer due to a decrease in the PBL height. The changes in the meteorological variables and ozone concentration during low tide were lesser than those occurring during high tide. This study suggests that the meteorological variations caused by tidal changes have a meaningful effect on the ozone concentration in the SMA.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.1
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• pp.34-45
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• 2021

Weather is one of the important factors in the agricultural industry as it affects the price, production, and quality of crops. Upland crops are directly exposed to the natural environment because they are mainly grown in mountainous areas. Therefore, it is necessary to provide accurate weather for upland crops. This study examined the effectiveness of 12 forest soil factors to interpolate the weather in mountainous areas. The daily temperature and precipitation were collected by the Korea Meteorological Administration between January 2009 and December 2018. The Generalized Additive Model (GAM), Kriging, and Random Forest (RF) were considered to interpolate. For evaluating the interpolation performance, automatic weather stations were used as training data and automated synoptic observing systems were used as test data for cross-validation. Unfortunately, the forest soil factors were not significant to interpolate the weather in the mountainous areas. GAM with only geography aspects showed that it can interpolate well in terms of root mean squared error and mean absolute error. The significance of the factors was tested at the 5% significance level in GAM, and the climate zone code (CLZN_CD) and soil water code B (SIBFLR_LAR) were identified as relatively important factors. It has shown that CLZN_CD could help to interpolate the daily average and minimum daily temperature for upland crops.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.33 no.4
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• pp.148-159
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• 2021

This study estimates the region of freshwater influence (ROFI) by Han River discharge in the Yeomha channel, Gyeonggi Bay. A 3-D numerical model, which is validated for reproducibility of variation in current velocity and salinity, is applied in Gyeonggi Bay. Distance of freshwater influence (DOFI) is defined as the distance from the entrance of Yeomha channel to the point where surface salinity is 28 psu. Model scenarios were constructed by dividing the Han River discharge into 10 categories (200~10,000 m³/s). The relation equation between freshwater discharge and DOFI was calculated based on performing a non-linear regression analysis. ROFI in Yeomha channel expands from the southern sea area of Ganghwa-do to the northern sea area of Yeongheung-do as the intensity of Han River discharge increases. The discharge and DOFI are a proportional relationship, and the increase rate of DOFI gradually decreases as discharge increases. Based on the relation equation calculated in this study, DOFI in the Yeomha channel can be estimated through the monthly mean Han River discharge. Accordingly, it will be possible to respond and predict problems related to damage to water quality and ecology due to rapid freshwater runoff.

• Korean Journal of Environmental Agriculture
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• v.37 no.3
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• pp.189-196
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• 2018

BACKGROUND: Water quality management of river requires quantification of pollutant loads and implementation of measures through monitoring study, but it requires labour and costs. Therefore, many researchers are performing nonpoint source pollution analysis using computer models. However, calibration of model parameters needs observed data. Nitrogen concentration in rainfall is one of the factors to be considered when estimating the pollutant loads through application of the nonpoint source pollution model, but the default value provided by the model is used when there are no observed data. Therefore, this study aims to provide the representative nitrogen concentration of the rainfall for the administrative district ensuring rational modeling and reliable results. METHODS AND RESULTS: In this study, rainfall monitoring data from June 2015 to December 2017 were used to determine the nitrogen concentration in rainfall for each administrative district. Range of the $NO_3{^-}$ and $NH_4{^+}$ concentrations were 0.41~6.05 mg/L, 0.39~2.27 mg/L, respectively, and T-N concentration was 0.80~7.71 mg/L. Furthermore, the national average of T-N concentration in this study was $2.84{\pm}1.42mg/L$, which was similar to the national average of T-N 3.03 mg/L presented by the Ministry of Environment in 2015. Therefore, the nitrogen concentrations suggested in this study can be considered to be resonable values. CONCLUSION: The nitrogen concentrations estimated in this study showed regional differences. Therefore, when estimating the pollutant loads through application of the nonpoint source pollution model, resonable parameter estimation of nitrogen concentration in rainfall is possible by reflecting the regional characteristics.

• Journal of The Korean Society of Agricultural Engineers
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• v.61 no.6
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• pp.111-121
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• 2019

Evapotranspiration (ET) of vegetation is one of the major components of the hydrologic cycle, and its accurate estimation is important for hydrologic water balance, irrigation management, crop yield simulation, and water resources planning and management. For agricultural crops, ET is often calculated in terms of a short or tall crop reference, such as well-watered, clipped grass (reference crop evapotranspiration, $ET_o$). The Penman-Monteith equation recommended by FAO (FAO 56-PM) has been accepted by researchers and practitioners, as the sole $ET_o$ method. However, its accuracy is contingent on high quality measurements of four meteorological variables, and its use has been limited by incomplete and/or inaccurate input data. Therefore, this study evaluated the applicability of Backpropagation Neural Network (BPNN) model for estimating $ET_o$ from less meteorological data than required by the FAO 56-PM. A total of six meteorological inputs, minimum temperature, average temperature, maximum temperature, relative humidity, wind speed and solar radiation, were divided into a series of input groups (a combination of one, two, three, four, five and six variables) and each combination of different meteorological dataset was evaluated for its level of accuracy in estimating $ET_o$. The overall findings of this study indicated that $ET_o$ could be reasonably estimated using less than all six meteorological data using BPNN. In addition, it was shown that the proper choice of neural network architecture could not only minimize the computational error, but also maximize the relationship between dependent and independent variables. The findings of this study would be of use in instances where data availability and/or accuracy are limited.

• Journal of Food Hygiene and Safety
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• v.34 no.6
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• pp.583-590
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• 2019

As the consumption of fresh fruits and vegetables increases, food poisoning caused by foodborne pathogen contamination is not decreasing. To prevent the contamination of produce, a quick and easy, low-cost, environmentally-safe disinfection method that does not affect produce freshness or quality is needed. This study demonstrates a new-concept, circulating-water disinfection system that purifies water by using newly developed 'LED-PS (photosensitizer)-induced ROS generation unit'. Using various types of LED-PS induced ROS generation units, we investigated the conditions for reducing the density of various pathogenic bacteria by more than 3 log CFU / mL in 1 hour. The major operational factors affecting the density reduction of the LED-PS-induced ROS generation unit were analyzed. Depending on bacteria species, the density reduction rate was varied. The effect of the units on reducing the density of Bacillus cereus and Pectobacterium carotovorum subsp. carotovorum was high, but the effect on foodborne bacteria such as Escherichia coli was relatively low. In this circulating water disinfection system, the density reduction effect tended to increase as the flow rate increased and the initial bacterial density decreased. As the amount of PS absorbed beads increased, the density reduction effect increased exponentially in some bacteria. Model 3280, a double cylindrical unit connecting two single cylindrical units, could completely sterilize more than 3 log CFU/mL of B. cereus and P. carotovorum subsp. carotovorum in 30 minutes of LED irradiation.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.4
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• pp.329-339
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• 2021

Soybeans (Glycine max), one of major upland crops, require precise management of environmental conditions, such as temperature, water, and soil, during cultivation since they are sensitive to environmental changes. Application of spectral technologies that measure the physiological state of crops remotely has great potential for improving quality and productivity of the soybean by estimating yields, physiological stresses, and diseases. In this study, we developed and validated a soybean growth prediction model using multispectral imagery. We conducted a linear regression analysis between vegetation indices and soybean growth data (fresh weight and LAI) obtained at Miryang fields. The linear regression model was validated at Goesan fields. It was found that the model based on green ratio vegetation index (GRVI) had the greatest performance in prediction of fresh weight at the calibration stage (R²=0.74, RMSE=246 g/m², RE=34.2%). In the validation stage, RMSE and RE of the model were 392 g/m² and 32%, respectively. The errors of the model differed by cropping system, For example, RMSE and RE of model in single crop fields were 315 g/m² and 26%, respectively. On the other hand, the model had greater values of RMSE (381 g/m²) and RE (31%) in double crop fields. As a result of developing models for predicting a fresh weight into two years (2018+2020) with similar accumulated temperature (AT) in three years and a single year (2019) that was different from that AT, the prediction performance of a single year model was better than a two years model. Consequently, compared with those models divided by AT and a three years model, RMSE of a single crop fields were improved by about 29.1%. However, those of double crop fields decreased by about 19.6%. When environmental factors are used along with, spectral data, the reliability of soybean growth prediction can be achieved various environmental conditions.