• Journal of Environmental Impact Assessment
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• v.16 no.1
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• pp.89-98
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• 2007

In order to conduct the environmental assessment of long range transboundary air pollutants over East Asia, the moving pathways of air pollutants are of great importance, which are depending upon the meteorological weather patterns. Therefore regional scale modeling study requires the identified geopotential height distribution patterns to deal with behaviors of long range transport air pollutants for the effective long term atmospheric environmental assessment. In this study the synoptic meteorological classification using cluster analysis technique over Northeast Asia, and its previous applications of the regional scale air pollutant modeling studies were reviewed and summarized in detail. Other synoptic meteorological characteristics over Korean peninsula are also discussed.

• Nuclear Engineering and Technology
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• v.50 no.1
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• pp.68-79
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• 2018

The Ki-Jang research reactor (KJRR), a new research reactor in Korea, is being planned to fulfill multiple purposes. In this study, as an assessment of the environmental radiological impact, we characterized the atmospheric dispersion and deposition of radioactive materials released by an unexpected incident at KJRR using the weather research and forecasting-mesoscale model interface program-California Puff (WRF-MMIF-CALPUFF) model system. Based on the reproduced three-dimensional gridded meteorological data obtained during a 1-year period using WRF, the overall meteorological data predicted by WRF were in agreement with the observed data, while the predicted wind speed data were slightly overestimated at all stations. Based on the CALPUFF simulation of atmospheric dispersion (${\chi}/Q$) and deposition (D/Q) factors, relatively heavier contamination in the vicinity of KJRR was observed, and the prevailing land breeze wind in the study area resulted in relatively higher concentration and deposition in the off-shore area sectors. We also compared the dispersion characteristics between the PAVAN (atmospheric dispersion of radioactive release from nuclear power plants) and CALPUFF models. Finally, the meteorological conditions and possibility of high doses of radiation for relatively higher hourly ${\chi}/Q$ cases were examined at specific discrete receptors.

• Atmosphere
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• v.20 no.3
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• pp.343-353
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• 2010

A regional wind network with complex surface conditions must be designed with sufficient space and time resolution to resolve the local circulations. In this study, the spatial variations of the wind field observed in the Seoul and Jeju regional networks were evaluated in terms of annual, seasons, and months to assess the spatial homogeneity of wind fields within the regional networks. The coherency of the wind field as a function of separation distance between stations indicated that significant coherency was sometimes not captured by the network, as inferred by low correlations between adjacent stations. A meso-velocity scale was defined in terms of the spatial variability of the wind within the network. This problem is predictably most significant with weak winds, dull prevailing wind, clear skies and significant topography. The relatively small correlations between stations imply that the wind at a given point cannot be estimated by interpolating winds from the nearest stations. For the Seoul and Jeju regional network, the meso-velocity scale has typically a same order of magnitude as the speed of the network averaged wind, revealing the large spatial variability of the Jeju network station imply topography and weather. Significant scatter in the relationship between spatial variability of the wind field and the wind speed is thought to be related to thermally-generated flows. The magnitude of the mesovelocity scale was significantly different along separation distance between stations, wind speed, intensity of prevailing wind, clear and cloudy conditions, topography. Resultant wind vectors indicate much different flow patterns along condition of contributing factors. As a result, the careful considerations on contributing factors such as prevailing wind in season, weather, and complex surface conditions with topography and land/sea contrast are required to assess the spatial variations of wind field on a regional network. The results in the spatial variation from the mesovelocity scale are useful to represent the characteristics of regional wind speed including lower surface conditions over the grid scale of large scale atmospheric model.

• International Journal of Safety
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• v.9 no.1
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• pp.35-42
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• 2010

We measured the concentrations of air pollutants at several residential sites, roadside sites and industrial sites in Iwate Prefecture, Japan. And the concentration distributions of air pollutants were estimated by atmospheric dispersion model using air emissions data. Based on those results, we calculated environmental risk of air pollutants emitted in Iwate Prefecture. As a result, it was found that the surround of factories with high emissions and highly toxic chemicals and the roadsides were high risk area, benzo(a)pyrene, formaldehyde and ozone exceeded the $10^{-5}$ risk level. Moreover, we tried to use "Loss of life expectancy: LLE" for an index to explain those risk to general public intelligibly. The total LLE of the carcinogenic chemicals was about 8.6 hours. Moreover, LLE of ozone was about 9.2 hours. Ozone has a big influence compared with the carcinogenic chemicals.

• Journal of Korean Society for Atmospheric Environment
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• v.22 no.1
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• pp.135-143
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• 2006

The objective of this study is to develop PSCF (potential source contribution function) program and determine the optimal values of control parameters to enhance the prediction of PSCF modeling. This study provides an important information and methodologies that can be used to get better results of locating influencing sources, especially unknown and fugitive sources. To determine proper values of control parameters in PSCF model, the diagnostic assessment on the results obtained by the various input conditions was carried out. PSCF model has created and improved from version 1.0 to version 7.0 since 200 I and the measured data (at least > 100) of receptor, and the values of control input parameters should be arranged and determined to obtain reliable results in PSCF modeling. The size of modeling domain must be determined to include enough trajectories to get reliable results. And the size of grid is recommended to be 2.5 $\sim$ 5 degrees for global scale, 0.2 $\sim$ 1 degrees for regional scale and 0.05 degree for local scale.

• Journal of Korean Society for Atmospheric Environment
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• v.26 no.2
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• pp.177-189
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• 2010

In order to incorporate correctly the large or local scale circulation in an atmospheric model, a nudging term is introduced into the equation of motion. The MM5 model was used to assess the meteorological values differences in each case, during ozone episode days in Gwangyang bay. The main objective of this study is to investigate the effect of horizontal and vertical flow fields according to the surface and vertical observation data assimilation by upper wind conditions. Therefore, we carried out several numerical experiments with various parameterization methods for nudging coefficient considering the upper wind conditions (synoptic or asynoptic condition). Nudging considering the synoptic and asynoptic nudging coefficient does have a clear advantage over dynamic initialization, therefore appropriate limitation of these nudging coefficient values on its upper wind conditions is necessary before making an assessment. Obviously, under the weak synoptic wind, there was apparent advantage associated with nudging coefficient by the regional difference. The accuracy for the prediction of the meteorological values has been improved by applying the appropriate PBL (Planetary Boundary Layer) limitation of circulation.

• Journal of Environmental Science International
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• v.25 no.7
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• pp.1029-1042
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• 2016

The initial and boundary conditions are important factors in regional chemical transport modeling systems. The method of generating the chemical boundary conditions for regional air quality models tends to be different from the dynamically varying boundary conditions in global chemical transport models. In this study, the impact of real time Copernicus atmosphere monitoring service (CAMS) re-analysis data from the modeling atmospheric composition and climate project interim implementation (MACC) on the regional air quality in the Korean Peninsula was carried out using the community multi-scale air quality modeling system (CMAQ). A comparison between conventional global data and CAMS for numerical assessments was also conducted. Although the horizontal resolution of the CAMS re-analysis data is not higher than the conventionally provided data, the simulated particulate matter (PM) concentrations with boundary conditions for CAMS re-analysis is more reasonable than any other data, and the estimation accuracy over the entire Korean peninsula, including the Seoul and Daegu metropolitan areas, was improved. Although an inland area such as the Daegu metropolitan area often has large uncertainty in PM prediction, the level of improvement in the prediction for the Daegu metropolitan area is higher than in the coastal area of the western part of the Korean peninsula.

• Korean Journal of Agricultural and Forest Meteorology
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• v.24 no.4
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• pp.201-217
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• 2022

The United States is one of the largest producers of major crops such as wheat, maize, and soybeans, and is a major exporter of these crops. Therefore, it is important to estimate the crop production of the country in advance based on reliable long- term weather forecast information for stable crops supply and demand in Korea. The purpose of this study is to improve the seasonal predictability of the agro-climatic indices over the United States by using regional-scale daily temperature. For long-term numerical weather prediction, a dynamical downscaling is performed using Weather Research and Forecasting (WRF) model, a regional climate model. As the initial and lateral boundary conditions of WRF, the global hourly prediction data obtained from the Pusan National University Coupled General Circulation Model (PNU CGCM) are used. The integration of WRF is performed for 22 years (2000-2021) for period from June to December of each year. The empirical quantile mapping, one of the bias correction methods, is applied to the timeseries of downscaled daily mean, minimum, and maximum temperature to correct the model biases. The uncorrected and corrected datasets are referred WRF_UC and WRF_C, respectively in this study. The daily minimum (maximum) temperature obtained from WRF_UC presents warm (cold) biases over most of the United States, which can be attributed to the underestimated the low (high) temperature range. The results show that WRF_C simulates closer to the observed temperature than WRF_UC, which lead to improve the long- term predictability of the temperature- based agro-climatic indices.