• The Korean Journal of Pesticide Science
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• v.18 no.4
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• pp.236-246
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• 2014

Pesticide is used to protect the crops, but also become a cause of polluting the environment. Perform a risk assessment using physical and chemical properties, environmental fate and toxicity data in order to determine the pesticide registration. The aquatic model estimates pesticide concentrations in water bodies that result from pesticide applications to rice paddies and apple orchard. The used models are the PRZM, EXAMS and AGRO shell (PA5), Rice Water Quality Model (RICEWQ) and Screening Concentration In GROund Water (SCI-GROW). The residual concentration of water body was estimated using meteorological data, crop calendar and soil series of Korea. The chosen pesticides were butachlor, carbofuran, iprobenfos and tebuconazole. It has shown the potential that the RICEWQ is possible to predict residue level in water of butachlor and iprobenfos, because the maximum value in water monitoring data is lower than the peak concentration of the model, and the minimum value is lower than the average annual concentration of the model. But RICEWQ was insufficient to predict exposure concentrations in ground water. The estimated exposure concentrations of carbofuran in ground water is very higher than in surface water because of its low soil adsorption coefficient. Although tebuconazole were not detected in the water monitoring that means very low concentration, it is possible that the PA5 can be used to predict residue level in water.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.32 no.4
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• pp.402-413
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• 2022

Objectives: In this study, the scale of exceeding the extreme heat exposure standard at the construction site was estimated using the nationally approved statistical data and wet bulb globe temperature modeling method. By comparing and analyzing the modeling results with the existing work environment monitoring results, the risk of heat exposure at outdoor construction sites was considered. Methods: Using the coordinates of second level administrative districts and meteorological observatories as the key, the automated synoptic observing system data and building permit data for 2021 were matched. The wet-bulb temperature was obtained using Stull's formula, and the globe temperature was obtained using the Tg_KMA2006 model. WBGT was calculated using these. Excess rates were obtained compared to exposure limits for heavy work-continuous work and moderate work-25% rest. It was compared with the results of the work environment monitoring in 2020. Results: As a result, 1,827,536 cases were estimated for 11,052 workplaces in one year. This is much higher than the 5,116 cases of 3818 workplaces of the existing work environment monitoring results. It is confirmed that the exposure limit was exceeded in 10.6~24.0% of the entire period and 70.2~84.1% of the peak period of the heat wave. It is very high compared to 0.9% of the existing work environment monitoring result. Conclusions: It is necessary to improve the system of monitoring and statistics related to extreme heat. Additional considerations are needed regarding WBGT estimation methods, meteorological data, and evaluation time. Various follow-up risk assessment studies for other industries and time series need to be continued.

• Journal of Astronomy and Space Sciences
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• v.26 no.3
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• pp.403-416
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• 2009

COMS (Communication, Ocean and Meteorological Satellite) is a geostationary satellite and developed by KARl for communication, ocean and meteorological observations. It will be tested under vacuum and very low temperature conditions in order to verify thermal design of COMS. The test will be performed by using KARI large thermal vacuum chamber, which was developed by KARI, and the COMS will be the first flight satellite tested in this chamber. The purposes of thermal balance test are to correlate analytical model used for design evaluation and predicting temperatures, and to verify and adjust thermal control concept. KARI has plan to use heating plates to simulate space hot condition especially for radiator panels of satellite such as north and south panels. They will be controlled from 90 K to 273 K by circulating GN2 and LN2 alternatively according to the test phases, while the main shroud of the vacuum chamber will be under constant temperature, 90 K, during all thermal balance test. This paper presents thermal modelling including test chamber, heating plates and the satellite without solar array wing and Ka-band reflectors and discusses temperature prediction during thermal balance test.

• Journal of Korea Water Resources Association
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• v.50 no.7
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• pp.489-502
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• 2017

The objective of this study is to propose and evaluate the BAYES-ESP, which is a dam inflow prediction method based on Ensemble Streamflow Prediction method (ESP) and Bayesian theory. ABCD rainfall-runoff model was used to predict monthly dam inflow. Monthly meteorological data collected from KMA, MOLIT and K-water and dam inflow data collected from K-water were used for the model calibration and verification. To estimate the performance of ABCD model, ESP and BAYES-ESP method, time series analysis and skill score (SS) during 1986~2015 were used. In time series analysis monthly ESP dam inflow prediction values were nearly similar for every years, particularly less accurate in wet and dry years. The proposed BAYES-ESP improved the performance of ESP, especially in wet year. The SS was used for quantitative analysis of monthly mean of observed dam inflows, predicted values from ESP and BAYES-ESP. The results indicated that the SS values of ESP were relatively high in January, February and March but negative values in the other months. It also showed that the BAYES-ESP improved ESP when the values from ESP and observation have a relatively apparent linear relationship. We concluded that the existing ESP method has a limitation to predict dam inflow in Korea due to the seasonality of precipitation pattern and the proposed BAYES-ESP is meaningful for improving dam inflow prediction accuracy of ESP.

• Journal of Internet Computing and Services
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• v.23 no.2
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• pp.29-35
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• 2022

UV rays have beneficial or harmful effects on the human body depending on the degree of exposure. An accurate UV information is required for proper exposure to UV rays per individual. The UV rays' information is provided by the Korea Meteorological Administration as one component of daily weather information in Korea. However, it does not provide an accurate UVI at the user's location based on the region's Ultraviolet index. Some operate measuring instrument to obtain an accurate UVI, but it would be costly and inconvenient. Studies which assumed the UVI through environmental factors such as solar radiation and amount of cloud have been introduced, but those studies also could not provide service to individual. Therefore, this paper proposes a deep learning model to calculate UVI using solar object information and sunlight characteristics to provide an accurate UVI at individual location. After selecting the factors, which were considered as highly correlated with UVI such as location and size and illuminance of sun and which were obtained through the analysis of sky images and solar characteristics data, a data set for DNN model was constructed. A DNN model that calculates the UVI was finally realized by entering the solar object information and sunlight characteristics extracted through Mask R-CNN. In consideration of the domestic UVI recommendation standards, it was possible to accurately calculate UVI within the range of MAE 0.26 compared to the standard equipment in the performance evaluation for days with UVI above and below 8.

• Atmosphere
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• v.28 no.4
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• pp.509-520
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• 2018

The performance of the newly designed Pusan National University Coupled General Circulation Model (PNU CGCM) Ensemble Forecast System which produce 40 ensemble members for 12-month lead prediction is evaluated and analyzed in terms of boreal winter temperature over South Korea (S. Korea). The influence of ensemble size on prediction skill is examined with 40 ensemble members and the result shows that spreads of predictability are larger when the size of ensemble member is smaller. Moreover, it is suggested that more than 20 ensemble members are required for better prediction of statistically significant inter-annual variability of wintertime temperature over S. Korea. As for the ensemble average (ENS), it shows superior forecast skill compared to each ensemble member and has significant temporal correlation with Automated Surface Observing System (ASOS) temperature at 99% confidence level. In addition to forecast skill for inter-annual variability of wintertime temperature over S. Korea, winter climatology around East Asia and synoptic characteristics of warm (above normal) and cold (below normal) winters are reasonably captured by PNU CGCM. For the categorical forecast with $3{\times}3$ contingency table, the deterministic forecast generally shows better performance than probabilistic forecast except for warm winter (hit rate of probabilistic forecast: 71%). It is also found that, in case of concentrated distribution of 40 ensemble members to one category out of the three, the probabilistic forecast tends to have relatively high predictability. Meanwhile, in the case when the ensemble members distribute evenly throughout the categories, the predictability becomes lower in the probabilistic forecast.

• Journal of Korea Water Resources Association
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• v.54 no.9
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• pp.705-718
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• 2021

Climate change has a significant impact on vegetation growth and terrestrial ecosystems. In this study, the possibility of ecological drought was investigated using satellite remote sensing data. First, the Vegetation Health Index was estimated from the Normalized Difference Vegetation Index and Land Surface Temperature provided by MODIS. Then, a joint probability model was constructed to estimate the possibility of vegetation-related drought in various precipitation/evaporation scenarios in forest areas around 60 major ASOS sites of the Meteorological Administration located throughout Korea. The results of this study show the risk pattern of drought related to forest vegetation under conditions of low atmospheric moisture supply or high atmospheric moisture demand. It also identifies the sensitivity of drought risks associated with forest vegetation under various meterological drought conditions. These findings provide insights for decision makers to assess drought risk and develop drought mitigation strategies related to forest vegetation in a warming era.

• Journal of Environmental Science International
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• v.24 no.1
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• pp.133-150
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• 2015

Wind profiler provides vertical profiles of three-dimensional wind vectors with high spatiotemporal resolution. The wind vectors is useful to analyze severe weather phenomena and to validate the various products from numerical weather prediction model. However, the wind measurements are not immune to ground clutter, bird, insect, and aircraft. Therefore, quality of wind vectors from wind profiler must be quantitatively evaluated prior to its application. In this study, wind vectors from UHF wind profiler at Ganwon Regional Meteorological Administration was quantitatively evaluated using 27 radiosonde measurements that were launched every two or three hours according to rainfall intensity during Intensive Observation Period (IOP) from June to July 2013. In comparison between two measurements, wind vectors from wind profiler was relatively underestimated. In addition, the accuracy and quality of wind vectors from wind profiler decrease with increasing beam height. The accuracy and quality of the wind vectors for rainy periods during IOP were higher than for the clear-air measurements. The moderate rainfall intensity lead to multi-peaks in Doppler spectrum. It results in overestimation of vertical air motion, whereas wind vectors from wind profilers shows good agreement with those from radiosonde measurements for light rainfall intensity.

• Journal of Korean Society for Atmospheric Environment
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• v.24 no.4
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• pp.423-438
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• 2008

BEIS2 (Biogenic Emissions Inventory System version 2) and BEIS3.12 (BEIS version 3.12) were used to estimate hourly biogenic emissions over South Korea using a set of vegetation and meteorological data simulated with the MM5 (Mesoscale Model version 5). Two biogenic emission models utilized different emission factors and showed different responses to solar radiations, resulting in about $10{\sim}20%$ difference in the nationwide isoprene emission estimates. Among the 11-vegetation classes, it was found that mixed forest and deciduous forest are the most important vegetation classes producing isoprene emissions over South Korea comprising ${\sim}90%$ of the total. The simulated isoprene concentrations over Seoul metropolitan area show that diurnal and daily variations match relatively well with the PAMS (Photochemical Air Monitoring Station) measurements during the period of June 3${\sim}$June 10, 2004. Compared to BEIS2, BEIS3.12 yielded ${\sim}35%$ higher isoprene concentrations during daytime and presented better matches to the high peaks observed over the Seoul area. This study showed that the importance of vegetation data and emission factors to estimate biogenic emissions. Thus, it is expected to improve domestic vegetation categories and emission factors in order to better represent biogenic emissions over South Korea.

• Spatial Information Research
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• v.17 no.2
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• pp.243-249
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• 2009

Damages from typhoon events have contributed more than 60 percent of total economic and social loss and the size of loss have been increased up to 800 million dollars per year in Korea, It is therefore necessary to make an effort to mitigate the loss of natural disasters. To facilitate the evaluation of damages in advance and to support the decision making to recover the damages, scientific methods have been adopted. With the effort, GIS data can provide various tools. Three components of hazard mapping are estimation of hazard, inventory for vulnerable features, and fragility of each feature. Vulnerability of natural disaster can be obtained by relation between loss and meteorological data such as precipitation and wind speed. Features can be categorized from other GIS data of public facilities and private properties, and then social and economic loss can be estimated. At this point, GIS data conversions for each model are required. In this study, we build a method to estimate typhoon risk based on GIS data such as DEM, land cover and land use map, facilities.