Air pollution dispersion from rooftop emissions around hexahedron buildings was investigated using computational fluid dynamics (referred to hereafter as CFD). The Shear Stress Transport (referred to hereafter as SST) k-ω model in FLUENT CFD code was used to simulate the flow and pollution dispersion around the hexahedron buildings. The two buildings used in the study had the dimensions of H: L: W (where H = height, L = length, and W = width) with the ratios of 1:1:1 and 1:1:2. Experimental data from the wind tunnel obtained by a previous study was used to validate the numerical result of the hexahedron building. Five validation metrics are used to obtain an overall and quantitative evaluation of the performance of SST k-ω models: the fractional bias (FB), the geometric mean bias (MG), the normalized mean square errors (NMSE), the geometric variance (VG), and the factor of 2 of the observations (FAC2). The results of vertical concentration profile and longitudinal surface concentration of the 1:1:2 building illustrate the reasonable performance for all five metrics. However, the lateral concentration profile at X = 3H (where X is the distance from the source) shows poor performance for all of the metrics with the exception of NMSE, and the lateral concentration profile at X = 10H shows poor performance for FB and MG.

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.

구제역 바이러스는 소나 돼지 등의 우제류 가축에 경구 또는 흡입 노출 등의 다양한 노출 경로를 통해 심각한 감염성을 유발하는 생물학적 유해인자로 국내 축산업 운영에 있어 막대한 경제적 손실을 초래하는 병원균들 중 하나다. 구제역 발병에 대한 사전적 예방 관리를 도모할 수 있는 조치 방안 중 하나는 공기를 통해 전파되는 구제역 바이러스 확산에 대해 수학적 모델 적용을 통해 예측된 분석 결과에 따라 설정될 수 있다. 대기 확산 모델들은 일반적으로 구제역 바이러스의 주요 전파 경로인 경구 및 접촉 감염의 노출 시나리오를 예측할 수는 없으나, 상대적으로 예측도가 높은 대기 확산 모델의 경우 공기 전파에 대한 구제역 바이러스의 위해성 관리 방안을 결정하는 데 주요 역할을 담당할 수 있는 유용가능한 수단으로 여러 나라에서 활용되어 왔다. 구제역 바이러스 전파를 억제하기 위한 엄격한 관리 방안 중 다량의 가축 살처분 방법은 축산 농가들에게 심각한 경제적 손실을 초래하여 심각한 경우 새로운 자립의 여건마저도 상실시킬 수도 있다. 반면 낮은 수준의 대응 방안은 향후 구제역 발생에 따른 추가적 피해를 근원적으로 억제할 수 없는 역학적 한계에 봉착할 수 있다. 본 연구는 구제역 바이러스의 기본 특성 및 발생 모델 적용에 따른 공기 중 전파의 감염 위험성 평가 관련 선행 문헌들을 고찰하였다. 또한 1970년대 이후 구제역 바이러스의 공기 전파 경로를 예측하기 위해 여러 나라에서 실제 활용된 다양한 대기 확산 모델들의 적용 사례 및 장/단점을 비교 분석하였다.

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.

The air pollutant emission is mainly caused by line sources in urban area. For example, the annually totaled air pollutant emission is known to consist of about 80% of line sources in Daegu. Hence, the appropriate assessment on the air pollutants of line sources is very important for the atmospheric environmental management in urban area. In this study, we made a comparative study to evaluate suitable dispersion model for estimating the air pollution from line sources. Two air pollution dispersion models, ISCST3 and CALINE4 were the subject of this study. The results were as follows; In the assessment of air pollution model, ISCST3 was found to have 4 times higher concentration than CALINE4. In addition, actual data obtained by measurement and estimated values by CALINE4 were generally identical. The air pollution assessment based on ISC3 model produced significantly lower values than actual data. The air pollution levels estimated by ISCST3 were very low in comparison with the observational values.

The numerical modeling and comparison with observations are performed to find out the detailed structure of meteorology and the characteristic of related dispersion phenomena of the non-reactive air pollutant at Kyoungin region, South Korea, where several industrial complex including Siwha, Banwol and Namdong is located. MM5 (Fifth Generation NCAR/Penn State Mesoscale Model), 3-D Land/Sea breeze model and 3-D diagnostic meteorological model have been utilized for the meteorological simulation for September, 2002 with each different spatial resolution, while 3-D Eulerian air dispersion model for the air quality study. We can see the simulated wind field shows the very local circulation quitely well compared with in-site observations in shoreline area with complex terrains, at which the circulation of Land/Sea breeze has developed and merged with the mountain and valley breeze eventually. Also it is shown in the result of the dispersion model that the diurnal variation and absolute value of daily mean SO2 concentrations have good agreement with observations, even though the instant concentration of SO2 simulated overestimates around 1.5 times rather than that of observation due to neglecting the deposition process and roughly estimated emission rate. This results may indicate that it is important for the air quality study at shoreline region with the complex terrain to implement the high resolution meteorological model which is able to handle with the complicate local circulation.

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.

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.