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.

The formerly proposed spectral model of turbulent burning velocity is refined for nonstoichiometric hydrocarbon mixtures. Refinements are made in regard to the following two points : (1) an effect of the diffusivity of deficient reactant on the turbulent burning velocity and (2) consideration of increasing laminar name thickness with a decrease in the laminar burning velocity A comparison between the predicted turbulent velocities and the measured ones is made. The predictions by the refined spectral model agree quantatively well with the experimental results in the regime of practical equivalence ratio, but not in the high and low equivalence ratio regime.

This paper presents a new concept to reduce turbulent frictional drag by injecting micro-bubble into near the buffer layer of turbulent boundary layer on flat plate. The concentrations of micro bubble distribution in the boundary was calculater by eddy viscosity equations in the governing equations. When near region of the buffer layer of turbulent boundary layer is filled with micro-bulle of air and viscous of the region is kept low, the velocity profile in the near region should be changed substantially. Then the Reynolds stress in the region becomes less, which guide to lower velocity gradient there. It results in reduction of velocity gradient at the viscous sublayer, which gives the reduction of shear stress at the wall.

산업사회에 대한 의존도가 커짐에 따라 당면한 사회의 가장 중요한 문제중 하나는 다양한 오염원으로부터의 환경파괴이다. 최근 들어 지구온난화, 환경오염, 이상기후 등의 문제가 심각하게 제기되고 있고 화산활동, 쓰나미 등의 재해 발생 빈도가 증가하고 있다. 이상기후의 진행 속도가 빠르게 진행되어가고 있는 시점에서 컴퓨터의 연산속도 향상으로 이송 및 확산모델에 대한 수치상의 상당한 진전을 보이고 있나 모델간의 특징에 따라서 이송 또는 확산 처리능력에 단편적인 우월성을 발휘할 뿐 두 과정 모두를 효과적으로 다루지 못하고 있다. 성균관대학교 해안환경 연구실에서는 대기 오염물의 확산 특성을 예측하기 위해 국내외 대기 확산 모델과 비교한 Matlab 기반의 Random Walk Method 오염물질 이동 예측 프로그램을 수립하였다. 하지만 Random Walk Method에 의한 라그란쥐적 모델은 이송이 우월한 지역에서 상당히 효과적이지만 확산이 우월한 지역에서는 많은 입자가 동원되어야 정확도를 확보할 수 있다는 문제점을 안고 있다. 본 연구에서는 수치계산이 빠르고 흐름이 우세한 지역에서도 적용 능력이 탁월한 전방입자추적기법의 이송 확산 모델을 수립하여 모델의 검증 및 전방입자 추적법 이송 연산에 의한 확산 모델을 소개하려고 한다. 본 모델에서는 대기 정보를 실시간으로 기류 흐름을 예측할 수 있는 기상수치예보모델(Regional Date Assimilation and Prediction System; RDAPS)을 활용하고 있다. 따라서 기상장 자료로부터 백두산 화산재가 계절풍 시나리오에 대한 한반도 남부로 확장 진출될 가능성 및 화산재의 분포도, 침적범위를 분석하며 본 모형을 통해 앞으로 우리나라의 원전 사고시 대기중으로 방사성 물질이 확산되는 평가에 활용할 수 있을거라 기대된다.

Turbulence greatly influence on atmospheric flow field. In the atmosphere, turbulence is represented as turbulent diffusion coefficients. To estimate turbulent diffusion coefficients in previous studies, it has been used constants or 2-level method which divides surface layer and Ekman layer. In this study, it was introduced Smagorinsky method which estimates turbulent diffusion coefficient not to divide the layer but to continue in vertical direcrtion. We simulated 3-D flow model and TKE equation applied turbulent diffusion coefficients using two methods, respectively. Then we showed the values of TKE and the condition of each term to TKE. The results of Smagorinsky method were reasonable. But the results of 2-level method were not reasonable. Therefor, it had better use Smagorinsky method to estimate turbulent diffusion coefficients. We are expected that if it is developed better TKE equation and model with study of computational method in several turbulent diffusion coefficients for reasonably turbulent diffusion, we will able to predict precise wind field and movements of air pollutants.