• 한국대기환경학회지
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• 제13권2호
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• pp.137-145
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• 1997

To predict the effects of air pollutant in the coastal region, we have developed the air pollutant model, the reaction model and the deposition of NO, $NO_2, and O_3$. And the numerical model of air pollutant concentration employed the nested technique to calculate with the higher resolution for the area. The nested technique used two grid systems, one for the large scale calculating region with the coarse mesh grid (CMG) and the other for the small scale region with the fine grid (FMG). In other to prove the validity of the simulation model the calculations were conducted for the present situation. The results of them reasonably agree with the observed data and proved the validity of the model.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2021년도 추계학술대회
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• pp.345-347
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• 2021

미세먼지 에측의 정확도 향상을 위해 다양한 연구가 이루어지고 있으나 미세먼지 농도에 따른 다양한 특성으로 인해 딥러닝 모델의 학습이 잘 이루이지지 않는 문제가 있다. 본 논문에서는 미세먼지 농도의 특성을 분해하여 특성을 반영하기 위한 EEMD 기반의 미세먼지 농도 예측 모델을 제안한다. 미세먼지 농도를 EEMD를 통해 분해 후, 각각 도출된 특성에 따른 예측 결과를 앙상블하여 최종 미세먼지 농도 값을 도출한다. 모델의 성능 평가 결과, 91.7%의 미세먼지 농도 예측 정확도를 확인하였다.

• 한국대기환경학회지
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• 제15권5호
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• pp.545-554
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• 1999

We would like to develop a short-term model to predict the time-related concentration of ozone whose reaction mechanism is complex. The paper targets Seoul where an ozone alert system has recently been employed. In order to develop a short-term prediction model for ozone, we suggested the Ozone Peak Indicator(OPI), an equivalent of the potential daily maximum ozone concentration, with precursors being the only limiting factor, and we calculated the Ozone Peak Indicarot as OPI={$rac{(O_3)_{max}cdot(H_{eH})_{max}(Rad)_{max}$ to preclude the influence of mixing height and solar radiation on the daily maximum ozone concentration. The OPI on the day of the prediction is to be calcultated by using the relation between OPI and the initial value of precursors. The basic prediction formula for time-related ozone concentration was established as $O_3(1)={(OPI)cdot Rad(t-2)H_{eH}}$, using the OPI, solar radiation two hours before prediction and mixing height. We developed, along with the basic formula for predicting photochemical oxidants, "SEOM"(Seoul Empirical Oxidants Model), a Fortran program that helps predict solar radiation and mixing height needed in the prediction of ozone pollution. When this model was applied to Seoul and an analysis of the correlation between the observed and the predicted ozone concentrations was made through SEOM, there appeared a very high correlation, with a coefficient of 0.815. SEOM can be described as a short-term prediction model for ozone concentration in large cities that takes into account the initial values of precursors, and changes in solar radiation and mixing height. SEOM can reflect the local characteristics of a particular and region can yield relatively good prediction results by a simple data input process.t process.

• 통합자연과학논문집
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• 제11권1호
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• pp.30-38
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• 2018

CALPUFF is one of the recommended air pollution models by EPA with AERMOD. It has been used to simulate the ambient concentration of critical air pollutants as well as non-critical pollutants such as persistent organic matters and the organic materials causing odor. In this model, the air pollutants go through dispersion, transportation, chemical reaction, and deposition process. These mechanisms are significantly influenced by meteorological condition. This study produces the meteorological field in three different methods for the simulation of $SO_2$ using CALPUFF: 1) CALMET model by using both ground-level and aerological observation, 2) CALMET model by using MM5 results with NCEP/NCAR reanalyzed data, 3) CALMET model by using MM5 results in which FDDA is applied with NCEP/NCAR reanalyzed data as well as the meteorological data of Korea Meteorological Administration. As a result of CALPUFF model, the resolved concentration of $SO_2$ showed different behaviors in three cases. For the first case, the fluctuation of SO2 concentration was frequently observed while the fluctuation is reduced in the second and third cases. In addition, the maximum concentration of $SO_2$ in the first case was about 2~3 times higher than the second case, and about 4~6 times higher than the third case. These results can be caused by the accuracy of the resolved meteorological field. It is inferred that the meteorological field of the first case could be less accurate than other two cases. These results show that the use of correct meteorological data can improve the result of dispersion model. Moreover, the contribution of various sources such as point, line, and area sources on the ambient concentration of air pollutant can be roughly estimated from the sensitivity analysis.

• 한국항행학회논문지
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• 제25권6호
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• pp.576-581
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• 2021

고농도의 경우 저농도와 비교하였을 때, 발생 빈도수의 차이와 발생 환경에 대한 차이로 예측 성능의 한계를 두드러지게 보이고 있다. 이러한 문제를 해결하기 위해 본 논문에서는 인공신경망 알고리즘을 이용하여 저농도와 고농도로 분류하고 구분된 농도별로 특성을 학습시킨 두 가지 예측 모델을 통해 예측을 수행하는 모델을 제안하였다. 저농도와 고농도를 분류하기 위해 DNN 기반의 분류 모델을 설계하고 분류모델을 통해 구분된 저농도와 고농도를 기준으로 농도별 특성을 반영하기 위한 저농도 예측 모델과 고농도 예측 모델을 설계하였다. 농도별 예측 모델의 성능 평가 결과, 저농도 예측 정확도가 90.38%, 고농도 예측 정확도는 96.37% 의 예측 정확도를 보였다.

• Nuclear Engineering and Technology
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• 제51권8호
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• pp.2013-2017
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• 2019

The radon concentrations in soil air were measured before and after a rainfall. ²²⁶Ra concentration, porosity, moisture content and temperature in soil were measured at Kyungpook National University in Daegu. As the results of measurement and analysis, the arithmetic mean of measured ²²²Rn concentration increased from 12100 ± 500 Bq/㎥ to 16200 ± 600 Bq/㎥ after the rainfall. And the measured ²²⁶Ra concentration was 61.4 ± 5.7 Bq/kg and the measured porosity was 0.5 in soil. The estimated values of ²²⁶Ra concentration and porosity using diffusion model of ²²²Rn in soil were 60.3 Bq/kg and 0.509, respectively. The estimated values were similar to the measured values. ²²²Rn concentration in soil increased with depth and moisture content. The estimations were obtained through fitting based on the diffusion model of ²²²Rn using the measurement values. The measured depth profiles of ²²²Rn were similar to the calculated depth profiles of ²²²Rn in soil. We hope that the results of this study will be useful for environmental radiation analysis.

• Nuclear Engineering and Technology
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• 제34권3호
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• pp.242-249
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• 2002

The relationship between the tritium release rate from the nuclear power plant and tritium concentration in the environment around the Kori site was modeled. The tritium concentration in the atmosphere was calculated by multiplying the release rates and $\chi$/Q values, and the d3V deposition rate at each sector according to the direction and the distance was obtained using a dry deposition velocity. The area around Kori site was divided into 6 zones according to the deposition rate. The six zones were divided into 14 compartments for the numerical simulation. Transfer coefficients between the compartments were derived using site characterization data. Source terms were calculated from the dry deposition rates. Tritium concentration in surface soil water and groundwater was calculated based upon a compartment model. The semi-analytical solution of the compartment model was obtained with a computer program, AMBER. The results showed that most of tritium deposited onto the land released into the atmosphere and the sea. Also, the estimated concentration in the top soil agreed well to that measured. Using the model, tritium concentration was predicted in the case that the tritium release rates were doubled.

• 한국지반환경공학회 논문집
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• 제12권6호
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• pp.35-42
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• 2011

본 논문에서는 준설매립투기장에서 발생하는 부유물질의 유출농도를 예측하기 위하여 실내모형실험을 수행하고 실험결과를 기존의 설계방법에서 제시한 결과와 비교 분석하였다. 현장의 펌프준설선에 의한 준설토의 투기 상황을 모사하기 위하여 투기농도와 투기장의 길이를 변화시킨 실내 모형실험을 수행하고, 투기가 진행됨에 따른 부유물질 유출 농도의 시간에 따른 변화를 측정하였다. 컬럼을 사용한 침강압밀 실험결과를 바탕으로 한 미공병단(US Army COE, 1987)에서 제시한 설계방법에 의한 유출농도에 대한 분석결과와 모형실험 결과를 비교한 결과, 상호 유사한 경향을 나타냄을 확인하였다.

• 한국농공학회:학술대회논문집
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• 한국농공학회 2005년도 학술발표논문집
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• pp.673-678
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• 2005

The objective of this paper is to develop the microorganism concentration simulation model for the health related effect analysis while farmers and water managers reuse the wastewater for agricultural irrigation. This model consists of the CE-QUAL-R1 model and the CREAMS-PADDY model. The CE-QUAL-R1 model is the 1-D numerical model to analyze the water quality of the reservoir and the CREAMS-PADDY model is modified from CREAMS model for considering the hydrologic cycles in paddy field. This model was applied to examine the application by the observed data from 2003 in Byoungjum study area. From this research, the average root mean square error (RMSE) for the simulated concentration during the calibration period was 0.51 MPN/100ml and correlation coefficient $(R^2)$ was 0.71. And the RMSE for the simulated concentration during the verification period was 0.46 MPN/100ml and $R^2$ was 0.73. This simulation results show that the coliform inflow concentrations by the wastewater irrigation wield great influence upon the temporal coliform concentrations in paddy field.

• Journal of Radiation Protection and Research
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• 제43권2호
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• pp.39-49
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• 2018

Background: A model to assess the activity concentration of agricultural products and the public ingestion dose as result of a nuclear accident is necessarily required to manage the contaminated agricultural systems by the accident, or to estimate the effects of chronic exposure due to food ingestion at a Level 3 PSA. Materials and Methods: A dynamic compartment model, which is composed of three sub-modules, namely, an agricultural plant contamination assessment model, an animal product contamination assessment model, and an ingestion dose assessment model has been developed based on Korean farming characteristics such as the growth characteristics of rice and stockbreeding. Results and Discussion: The application study showed that the present model can predict well the characteristics of the activity concentration for agricultural products and ingestion dose depending on the deposition date. Conclusion: The present model is very useful to predict the radioactivity concentration of agricultural foodstuffs and public ingestion dose as consequence of a nuclear accident. Consequently, it is expected to be used effectively as a module for the ingestion dose calculation of the Korean agricultural contamination management system as well as the Level 3 PSA code, which is currently being developed.