• Journal of Korean Society for Atmospheric Environment
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• v.15 no.5
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• pp.613-623
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• 1999

A Lagrangian particle dispersion mode l(LPDM) coupled with the prognostic flow model based on nonequilibrium level 2.5 turbulence closure has been dcveloped to simulate the dispersion from an elevated emission source. The proposed model did not require any empirical formula or data for the turbulent statistics such as velocity variances and Lagrangian time scales since the turbulence properties for LPDM were calculated from results of the flow model. The LPDM was validated by comparing the model results against the wind tunnel tracer experiment and ISCST3 model. The calculated wind profile and turbulent velocity variances were in good agreement with those measured in the wind tunnel. The ground level concentrations along the plume centerline as well as the dispersion codfficients also showed good agreement in comparison with the wind tunnel tracer experiment. There were some discrepancies on the horizontal spread of the plume in comparison with the ISCST3 but the maximum ground level concentrations were in a good confidence range. The results of comparisons suggested that the proposed LPDM with the flow model was an effective tool to simulate the dispersion in the flow situation where the turbulent characteristics were not available in advance.

• Journal of Environmental Science International
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• v.13 no.10
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• pp.891-902
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• 2004

In order to predict air pollution and Yellow-sand dispersion precisely, it is necessary to clarify the sensitivity of meteorological field input interval. Therefore numerical experiment by atmospheric dynamic model(RAMS) and atmospheric dispersion model(PDAS) was performed for evaluating the effect of temporal and spatial resolution of meteorological data on particle dispersion. The results are as follows: 1) Base on the result of RAMS simulation, surface wind direction and speed can either synchronize upper wind or not. If surface wind and upper wind do not synchronize, precise prediction of Yellow-sand dispersion is strongly associated with upwelling process of sand of particle. 2) There is no significant discrepance in distribution of particle under usage of difference temporal resolution of meteorological information at early time of simulation, but the difference of distribution of particles become large as time goes by. 3) There is little difference between calculated particles distributions in dispersion experiments with high temporal resolution of meteorological data. On the other hand, low resolution of meteorological data occur the quantitative difference of particle density and there is strong tendency to the quantitative difference.

• Nuclear Engineering and Technology
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• v.53 no.7
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• pp.2377-2386
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• 2021

To model the atmospheric dispersion of radionuclides released from nuclear accident is very important for nuclear emergency. But the uncertainty of model parameters, such as source term and meteorological data, may significantly affect the prediction accuracy. Data assimilation (DA) is usually used to improve the model prediction with the measurements. The paper proposed a parameter bias transformation method combined with Lagrangian puff model to perform DA. The method uses the transformation of coordinates to approximate the effect of parameters bias. The uncertainty of four model parameters is considered in the paper: release rate, wind speed, wind direction and plume height. And particle swarm optimization is used for searching the optimal parameters. Twin experiment and Kincaid experiment are used to evaluate the performance of the proposed method. The results show that the proposed method can effectively increase the reliability of model prediction and estimate the parameters. It has the advantage of clear concept and simple calculation. It will be useful for improving the result of atmospheric dispersion model at the early stage of nuclear emergency.

• Atmosphere
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• v.23 no.1
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• pp.93-102
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• 2013

Atmospheric transport pathway of an air mass is an important constraint controlling the chemical properties of the air mass observed at a designated location. Such information could be utilized for understanding observed temporal variabilities in atmospheric concentrations of long-lived chemical compounds, of which sinks and/or sources are related particularly with natural and/or anthropogenic processes in the surface, and as well as for performing inversions to constrain the fluxes of such compounds. The Lagrangian particle dispersion model FLEXPART provides a useful tool for estimating detailed particle dispersion during atmospheric transport, a significant improvement over traditional "single-line" trajectory models that have been widely used. However, those without a modeling background seeking to create simple back-trajectory maps may find it challenging to optimize FLEXPART for their needs. In this study, we explain how to set up, operate, and optimize FLEXPART for back-trajectory analysis, and also provide automatization programs based on the open-source R language. Discussions include setting up an "AVAILABLE" file (directory of input meteorological fields stored on the computer), creating C-shell scripts for initiating FLEXPART runs and storing the output in directories designated by date, as wells as processing the FLEXPART output to create figures for a back-trajectory "footprint" (potential emission sensitivity within the boundary layer). Step by step instructions are explained for an example case of calculating back trajectories derived for Anmyeon-do, Korea for January 2011. One application is also demonstrated in interpreting observed variabilities in atmospheric $CO_2$ concentration at Anmyeon-do during this period. Back-trajectory modeling information introduced in this study should facilitate the creation and automation of most common back-trajectory calculation needs in atmospheric research.

• Proceedings of the Korea Air Pollution Research Association Conference
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• 2007.10a
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• pp.459-460
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• 2007

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• Particle and aerosol research
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• v.17 no.3
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• pp.55-69
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• 2021

Chungnam region accounts for the largest SO_X (22.8%) emission with the second-largest NO_X (10.8%) emission in Korea due to the integration of many large industrial sources including a steel mill, coal-fired power plants, and petrochemical complex. Air pollutants emitted by large industrial sources can cause harmful problems to humans and the environment. Thus, it is necessary to understand dispersion patterns of air pollutants from large industrial sources in Chungnam to characterize atmospheric contamination in Chungnam and the surrounding area. In this study, seasonal atmospheric dispersion characteristics for SO_X, NO_X, and PM2.5 from ten major point sources in Chungnam were evaluated using HYSPLIT 4 model, and their contributions to SO₂, NO₂ concentrations in the regions near the source areas were estimated. The predictions of the HYSPLIT 4 model show a seasonal different dispersion pattern, in which air pollutants were dispersed toward the southeast in winter while, northeast in summer. In summer, due to weaker wind speed, air pollutants concentrations were higher than in winter, and they were dispersed to the metropolitan area. The local emissions of air pollutants in Taean area had a greater influence on the ambient SO₂ and NO₂ concentrations at Taean, whereas SO_X and NO_X emissions from large sources located at Seosan showed relatevely little effect on the ambient ambient SO₂ and NO₂ concentrations at Seosan.

• Journal of computational fluids engineering
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• v.3 no.1
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• pp.63-72
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• 1998

The numerical simulations of flowfield and pollutant dispersion over two-dimensional hills of various shapes are described. The Reynolds-averaged Wavier-Stokes equations and concentration diffusion equation based on the gradient diffusion theory have been applied to the atmospheric shear flow over the bell-shaped hills which are basic components of the complex terrain. The flow characteristics such as velocity profiles of the geophysical boundary layer, speed-up phenomena, mean pollutant concentration profiles are compared with experimental data to validate the present numerical procedure and it has been found that the present numerical results agree well with experiments and other numerical data. It has been also found that the distributions of ground level concentration are strongly influenced by the source location and height.

• Journal of Korean Society for Atmospheric Environment
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• v.27 no.1
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• pp.87-96
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• 2011

In this study, the AERMOD dispersion model was used for predicting odor concentrations and back-calculating industrial area source odor emission rate. The studied area was Sihwa industrial complex in Korea. Odor samples were collected during two days over a year period in 2009. The comparison between the predicted and observed concentrations indicates that the AERMOD model could fairly well predict average downwind odor concentrations. The results show odor emission rates of Sihwa industrial complex area source were ranged from 0.204 to 2.320 $OUms^{-1}$ (average 0.476 $OUms^{-1}$). The results also show wind speed and direction are important parameters to the odor dispersion.

• Asian Journal of Atmospheric Environment
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• v.5 no.1
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• pp.1-7
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• 2011

This study assesses the dispersion and emission rates of odor form industrial area source. CALPUFF and AERMOD Gaussian models were used for predicting downwind odor concentration and calculating odor emission rates. The studied region was Seobu industrial complex in Korea. Odor samples were collected five days over a year period in 2006. In-site meteorological data (wind direction and wind speed) were used to predict concentration. The BOOT statistical examination software was used to analyze the data. Comparison between the predicted and field sampled downwind concentration using BOOT analysis indicates that the CALPUFF model prediction is a little better than AERMOD prediction for average downwind odor concentrations. Predicted concentrations of AERMOD model have a little larger scatter than that of CALPUFF model. The results also show odor emission rates of Seobu industrial complex area were an order of 10 smaller than that of beef cattle feed lots.

• Journal of Environmental Science International
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• v.8 no.5
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• pp.555-558
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• 1999

A sea/land breeze circulation system and a regional scale circulation system are formed at a region which has complex terrain around coastal area and affect to the dispersion and advection of air pollutants. Therefore, it is important that atmospheric circulation model should be well designed for the simulation of regional dispersion of air pollutants. For this, Local Circulation Model, LCM which has an ability of high resolution is used. To verify the propriety of a LCM, we compared the simulation result of LCM with an exact solution of a linear theory over a simple topography. Since they presented almost the same value and pattern of a vertical velocity at the level of 1 km, we had a reliance of a LCM. For the prediction of dispersion and advection of air pollutants, the wind filed should be calculated with high accuracy. A numerical simulation using LCM will provide more accurate results over a complex terrain around coastal area.