Although many attempts have been made to solve the atmospheric diffusion equation, there are many limits that prevent both solving it and its application. The causes of these impediments are primarily due to both the partial differentiation term and the turbulence diffusion coefficient. In consideration of this dilemma, this study aims to discuss the methodology and cases of utilizing a passive air sampler to increase the applicability of atmospheric dispersion modeling. Passive air samplers do not require pumps or electric power, allowing us to achieve a high resolution of spatial distribution data at a low cost and with minimal effort. They are also used to validate and calibrate the results of dispersion modeling. Currently, passive air samplers are able to measure air pollutants, including SO2, NO2, O3, dust, asbestos, heavy metals, indoor HCHO, and CO2. Additionally, they can measure odorous substances such as NH3, H2S, and VOCs. In this paper, many cases for application were introduced for several purposes, such as classifying the VOCs’ emission characteristics, surveying spatial distribution, identifying sources of airborne or odorous pollutants, and so on. In conclusion, the validation and calibration cases for modeling results were discussed, which will be very beneficial for increasing the accuracy and reliability of modeling results.
Understanding the dispersion of xenon isotopes following a nuclear test is critical for global security and falls within the remit of both the Comprehensive Nuclear-Test-Ban Treaty (CTBT) and the International Noble Gas Experiment (INGE). This paper aims to show if it is possible to discriminate the source of xenon releases based on the atmospheric dispersion of xenon isotopes using HYSPLIT. Using ORIGEN and SERPENT simulations, four released scenarios are defined with four different fractionation times (i.e., 1 hour, 1 day, 10 days, and 30 days) after a 1kt TNT equivalent 235U explosion event. These time-delayed release scenarios were selected to certify the possibility of mis-determining xenon release source. We use the Lagrangian dispersion model for atmospheric dispersion to predict the concentration distribution of xenon isotopes under each scenario. The model allows us to better understand how these isotopes would distribute over time and space, offering valuable data for real-world detection efforts. To our knowledge, there have been no researches on the analysis of xenon isotopic ratios considering atmospheric dispersion. In this work, we focused on the atmospheric dispersion using HYSPLIT to characterize the xenon isotopic ratios from nuclear tests. In addition, we compared the xenon isotopic ratios obtained from the atmospheric dispersion with those from ORIGEN calculations, which would be helpful to discriminate the source of the xenon releases.
Radioactive materials from nuclear power facilities can be released into the atmosphere through various channels. Recently, the dispersion of radioactive materials has become critical issue in Korea after Kori Unit 1 and Wolsong Unit 1 were permanently shut down. In this study, annual atmospheric dispersion factors were compared based on the continuous release and purge release using the XOQDOQ computer program, a method for calculating atmospheric dispersion factors at commercial nuclear power stations. The meteorological data analyzed in this study was based on the Shin Kori nuclear power meteorological tower which has the largest operating nuclear power plants in Korea, for three years (from 2008 to 2010). The analysis results of the dispersion factor of the radioactive material release obtained using the XOQDOQ program showed that the difference between the continuous release and purge release was within two times. This study will be valuable helpful for revealing the uncertainty of the predictive atmospheric dispersion factor to achieve regulation.
지속적으로 관찰되어 온 백두산 화산폭발 전조 현상들이 사회적 이슈가 되고 있으며 주변국인 일본의 화산활동 또한 활발한 추세이다. 국내와 500km 이상 떨어진 위 화산들은 국내에 직접적인 피해를 주기 어렵지만 화산 분화와 함께 분출되는 화산재의 경우 국내에 직간접적인 피해를 미칠 수 있다. 화산재 확산대응의 일환으로 수치해석 모델이 국내외로 사용되고 있으며 각 수치해석 모델 은 사용된 수치해석 방법에 따라 한계가 있다. 본 논문에서는 라그랑지안 방법을 기반으로 한 PUFF-UAF 모델을 분석하였으며, 초기 입자의 수에 대한 의존성의 문제점과 많은 입자개수를 사용함에도 불구하고 나타나는 화산재 농도 예측의 부정확성에 대한 문제점을 제기하였다. 이에 본 논문 연구를 통하여 라그랑지안 기법의 전산효용성을 이용하고 나타난 문제점을 해결하기 위하여 PUFF-UAF 모 델의 결과에 가우시안 확산 모델을 적용하여 결과를 보완하는 PUFF-Gaussian 모델을 개발하였다. 실제 화산분화로 부터 관측된 결과 와 본 연구로 예측된 결과를 비교한 결과 본 연구에서 제안한 방법의 효용성을 보였다.
Odor dispersion from road emissions were investigated using CFD (Computational Fluid Dynamics). The Shear Stress Transport k-ω model in FLUENT CFD code was used to simulate odor dispersion around the road. The two road configurations used in the study were at-grade and fill road. Experimental data from the wind tunnel obtained in a previous study was used to validate the numerical result of the road dispersion. Five validation metrics are used to obtain an overall and quantitative evaluation of the performance of Shear Stress Transport k-ω models: the fractional bias (FB), the geometric mean bias (MG), the normalized mean square error (NMSE), the geometric variance (VG), and the fraction of predictions within a factor of two of observations (FAC2). The results of the vertical concentration profile for neutral atmospheric show reasonable performance for all five metrics. Six atmospheric stability conditions were used to evaluate the stability effect of road emission dispersion. It was found that the stability category D case of at-grade decreased the non-dimensional surface odor concentration smaller 0.78~0.93 times than those of stability category A case, and that F case decreased 0.39~0.56 times smaller than those of stability category A case. It was also found that stability category D case of filled road decreased 0.84~0.92 times the non-dimensional surface odor concentration of category A case and stability category F case decreased 0.45~0.58 times compared with stability category A case.
해상으로 운송되는 위험유해물질 (HNS, Hazardous and Noxious Substance)은 6,000여종 이상으로 많은 종류를 포함하고 있으므로, 유출시 대응전략 수립을 위한 HNS 거동 및 위험반경 예측을 결정론적으로 제시하기 어렵다. HNS 거동예측에서는 예측의 신속성과 효율성을 고려하여 차이가 미미한 모든 종류의 HNS 특성을 모두 고려하는 대신에 거동에 크게 영향을 미칠 수 있는 특성들에 초점을 맞쳐 대표적인 거동예측 모델을 개발하여 적용할 필요가 있다. 본 연구에서는 HNS를 기체상, 액체상, 고체상 등 크게 3분류로 구분하고, 각각의 분류별 거동특성 모델링을 연구하였다. 물질 특성별 거동특성은 증기압, 용해도, 밀도 등을 고려하였으며, 각각의 변수에 따른 증발, 혼홥, 침강 등의 거동을 모델링하였다. 물질의 거동특성 모델링은 대기 해양 확산모델의 계산에서 대기중 확산, 수중 확산, 해저면 침적 등을 결정하는 과정으로 활용된다.
Atmospheric stability is an important parameter which effects pollutant dispersion in the atmospheric boundary layer.The objective of this paper was to verify the effect of stability conditions on odor dispersion downwind from anarea source using computational fluid dynamic (CFD) modeling. The FLUENT Realizable k-ε model was used tosimulate odor dispersion as released by an odor source. A total of 3 simulations demonstrated the effects of unstable,neutral, and stable atmospheric conditions. Unstable atmospheric stability conditions produced a shorter odor plumelength compared with neutral and stable conditions because of stronger convective effects. Like other studies,unstable atmospheric condition produced higher plume height compared with neutral and stable conditions.
The characteristics of atmospheric dispersion of radioactive material (i.e. 137Cs) related to local wind patterns around the Kori nuclear power plant (KNPP) were studied using WRF/HYSPLIT model. The cluster analysis using observed winds from 28 weather stations during a year (2012) was performed in order to obtain representative local wind patterns. The cluster analysis identified eight local wind patterns (P1, P2, P3, P4-1, P4-2, P4-3, P4-4, P4-5) over the KNPP region. P1, P2 and P3 accounted for 14.5%, 27.0% and 14.5%, respectively. Both P1 and P2 are related to westerly/northwesterly synoptic flows in winter and P3 includes the Changma or typhoons days. The simulations of P1, P2 and P3 with high wind velocities and constant wind directions show that 137Cs emitted from the KNPP during 0900~1400 LST (Local Standard Time) are dispersed to the east sea, southeast sea and southwestern inland, respectively. On the other hands, 5 sub-category of P4 have various local wind distributions under weak synoptic forcing and accounted for less than 10% of all. While the simulated 137Cs for P4-2 is dispersed to southwest inland due to northeasterly flows, 137Cs dispersed northward for the other patterns. The simulated average 137Cs concentrations of each local wind pattern are 564.1~1076.3 Bqm-3. The highest average concentration appeared P4-4 due to dispersion in a narrow zone and weak wind environment. On the other hands, the lowest average concentration appeared P1 and P2 due to rapid dispersion to the sea. The simulated 137Cs concentrations and dispersion locations of each local wind pattern are different according to the local wind conditions.
In order to how well predict ISCST3(Industrial Source Complex Short Term version 3) model dispersion of air pollutant at point source, sensitivity was analysed necessary parameters change. ISCST3 model is Gaussian plume model.
Model calculation was performed with change of the wind speed, atmospheric stability and mixing height while the wind direction and ambient temperature are fixed. Fixed factors are wind direction as the south wind(180˚) and temperature as 298 K(25℃). Model's sensitivity is analyzed as wind speed, atmospheric stability and mixing height change. Data of stack are input by inner diameter of 2m, stack height of 30m, emission temperature of 40℃, outlet velocity of 10m/s.
On the whole, main factor which affects in atmospheric dispersion is wind speed and atmospheric stability at ISCST3 model. However it is effect of atmospheric stability rather than effect of distance downwind. Factor that exert big influence in determining point of maximum concentration is wind speed. Meanwhile, influence of mixing height is a little or almost not.
Recently air quality modeling studies for industrial complex and large cities located in the coastal regions have been carried out. Especially, the representation of atmospheric flow fields within a model domain is very important, because an adequate air quality simulation requires an accurate portrayal of the realistic three- dimensional wind fields. Therefore this study investigated effect of using high resolution terrain height data and FDDA with observational data to reflect local characteristics in numerical simulation. So the experiments were designed according to FDDA and the detail terrain height with 3sec resolution or not. Case 30s was the experiment using the terrain height data of USGS without FDDA and Case 3s was the experiment using the detail terrain height data of Ministry of Environment without FDDA and Case 3sF was experiment using the detail terrain height data of Ministry of Environment with FDDA. The results of experiments were more remarkable. In Case 3s and Case 3sF, temperature indicated similar tendency comparing to observational data predicting maximum temperature during the daytime and wind speed made weakly for difference of terrain height. Also Case 3sF had more adequate tendency than Case 3s at dawn.
The sensitivity analysis of two short-term models (ISCST3, INPUFF2.5) is performed to improve the model accuracy. It appears that the sensitivities on the changes of wind speed, stack height and stack inner diameter in the near distance from source, stability and mixing height in the remote distance from source, are significant. Also, the gas exit velocity, stack inner diameter, gas temperature and air temperature which affect the plume rise have some effects on the concentration values of each model within the downwind distance where final plume rise is determined. And in modeling for the atmospheric dispersion of point pollutant source INPUFF2.5 can calculate amount, trajectory of puff and concentration versus time at each receptors. So, it is compatible to analyze distribution of point pollutants concentration at modeling area.
We will calculate concentration of air pollutants using ISCST3, FDM and AERMOD of models recommended in U. S. EPA which are able to predict concentration of short term for point source, complex like industrial complex, power plant and burn-up institution.
Before executing model, as analyzing computational result of many cases according to selecting of input data, we will increasing predictable ability of model in limit range of model. Especially, we analyzed three cases - case of considering various emission rate according to time scale and not, case considering effect of atmospheric pollution materials removed by physical process.
In our study, after comparing and analyzing results of three model, we choose the atmospheric dispersion model reflected well the characteristic of the area. And we will investigate how large the complex pollutant sources such as industrial complex contribute to atmospheric environment and air quality of the surrounding the area as predicting and estimating chosen model.
For the efficient control of atmospheric quality, it is so important to predict the influence accurately of which the air pollutant emitted into the atmosphere. Atmospheric dispersion model enables to simulate and grasp the atmospheric condition occurred due to the emission of pollutants. The result of model is largely affected by the amount of emission, the characteristics of physical and chemical process, meteorological input data, and the receptor which the concentration is calculated.
The aim of this research, therefore, is to suggest more suitable model in Pusan area than other areas by performing TCM2, CDM2.0 and ISCLT2 models. As the basic work for executing the model, we computed the amount of emission of air pollutants in Pusan at 1992 and analyzed the occurrence frequency of atmospheric stability for recent decade(1985∼1994). CDM2.0 showed the similar result relatively with observed value in the case of full year(1992), fall and winter, and ISCLT2 brought more suitable result in spring for Pusan area.
As the result of this research, in future, it is necessary for us to develop the numerical model considering the topographical characteristics, to select the proper observation site and to increase the observation site for Pusan.