• Journal of Animal Environmental Science
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• v.20 no.2
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• pp.41-48
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• 2014

This study was conducted to investigate the dispersion prediction of odor from swine farms in Korea. Gaussian Plume model used in considering of farm size, wind velocity, atmospheric stability and threshold odor unit to prediction of odor dispersion based on the survey on current state of odor emission and control from 48 site of swine farms. Farm size, wind velocity and atmospheric stability were affected the distance of odor dispersion, showed longer distance in cases of large farm, low wind velocity and stable atmospheric condition. We will suggestion the adjusted distance of odor dispersion according to farm size was estimated to 180 m in small farm and 320 m in large farm when apply the 3 OU, 5 m/s wind velocity and stable atmospheric condition.

• Journal of Korean Society for Atmospheric Environment
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• v.14 no.5
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• pp.411-420
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• 1998

To estimate the dispersion coefficients in a coastal area with complex topography, several schemes using empirical equations expressed with and in lateral and vertical directions, respectively have been examined. Estimation results using these equations and meteorological data obtained from SODAR system were compared' with previously measured dispersion coefficients in other coastal areas. Validations of estimation results have been performed by comparing the measured concentrations with predicted ones empolying in Boryung coastal area. Important conclusions were drawn as follows; (1) Variations of lateral and vertical wind direction revealed different height dependency in upper and lower mixed boundary layer. (2) Because of turbulent constraint effect by large water body in a coastal region, the lateral and the vertical dispersion coefficients were smaller than those of P-G system. (3) As a result of examining the performance measure of these schemes through checking of coincidence between measured and predicted concentrations, vertical dispersion coefficients were smaller than those of P-G system, and the Cramer scheme was found to be more appropriate rather than others in the coastal area surrounding Boryung power plant.

• Journal of Korean Society for Atmospheric Environment
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• v.19 no.3
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• pp.249-261
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• 2003

A three-dimensional mesoscale atmospheric dispersion modeling system consisting of the Lagrangian particle dispersion model (LPDM) and the meteorological mesoscale model (MM5) was employed to simulate the transport and dispersion of non-reactive pollutant during the nuclear spill event occurred from Sep. 31 to Oct. 3, 1999 in Tokaimura city, Japan. For the comparative analysis of numerical experiment, two more sets of foreign mesoscale modeling system; NCEP (National Centers for Environmental Prediction) and DWD (Deutscher Wetter Dienst) were also applied to address the applicability of air pollution dispersion predictions. We noticed that the simulated results of horizontal wind direction and wind velocity from three meteorological modeling showed remarkably different spatial variations, mainly due to the different horizontal resolutions. How-ever, the dispersion process by LPDM was well characterized by meteorological wind fields, and the time-dependent dilution factors ($\chi$/Q) were found to be qualitatively simulated in accordance with each mesocale meteorogical wind field, suggesting that LPDM has the potential for the use of the real time control at optimization of the urban air pollution provided detailed meteorological wind fields. This paper mainly pertains to the mesoscale modeling approaches, but the results imply that the resolution of meteorological model and the implementation of the relevant scale of air quality model lead to better prediction capabilities in local or urban scale air pollution modeling.

• Journal of Radiation Protection and Research
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• v.38 no.2
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• pp.60-67
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• 2013

A diffusion coefficient is an important parameter in the prediction of atmospheric dispersion using a Gaussian plume model, and its modelling approach varies. In this study, dispersion coefficients recommended by the U. S. Nuclear Regulatory Commission's (U. S. NRC's) regulatory guide and the Canadian Nuclear Safety Commission's (CNSC's) regulatory guide, and used in probabilistic accident consequence analysis codes MACCS and MACCS2 have been investigated. Based on the atmospheric dispersion model for a hypothetical accidental release recommended by the U. S. NRC, its influence to atmospheric dispersion factor was discussed. It was found that diffusion coefficients are basically predicted from a Pasquill- Gifford curve, but various curve fitting equations are recommended or used. A lateral dispersion coefficient is corrected with consideration for the additional spread due to plume meandering in all models, however its modelling approach showed a distinctive difference. Moreover, a vertical dispersion coefficient is corrected with consideration for the additional plume spread due to surface roughness in all models, except for the U. S. NRC's recommendation. For a specified surface roughness, the atmospheric dispersion factors showed differences up to approximately 4 times depending on the modelling approach of a dispersion coefficient. For the same model, the atmospheric dispersion factors showed differences by 2 to 3 times depending on surface roughness.

• Journal of Radiation Protection and Research
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• v.22 no.4
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• pp.273-288
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• 1997

A three dimensional sea-land breeze model and Lagrangian particle dispersion model have been employed for the study on the mesoscale atmospheric dispersion of radioactive materials released from Wolsung NPPs. In this study, atmospheric dispersion simulations are carried out under two synoptic weather conditions : the geostrophic flow is a weak northerly wind(CASE 1) and a strong northerly wind(CASE 2) on a clear day in spring. The results show that atmospheric dispersion is affected by sea-land breeze and the recirculation of particles by the change of wind direction between sea breeze and land breeze plays an important role in atmospheric concentration distribution of radoactive materials.

• Journal of Korean Society for Atmospheric Environment
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• v.31 no.6
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• pp.573-584
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• 2015

In this study, the atmospheric dispersion of radioactive material ($^{137}Cs$) was simulated with regard to its impact within a 50-km radius from the Kori Nuclear Power Plant (NKPP) based on two different types of models (the non-steady-state puff model CALPUFF and the lagrangian model HYSPLIT) during the spring of 2012 (May 2012). The dispersion distribution of $^{137}Cs$ calculated in the CALPUFF model was similar to that of the HYSPLIT model, but the magnitudes of differences in its spatio-temporal concentrations between the two models were different. The $^{137}Cs$ concentrations simulated by the CALPUFF were significantly lower than those of the HYSPLIT due to a limitation of puff models (e.g. puff size growth over time). The CALPUFF had the advantage of determining the dispersion of radioactive materials and their impacts on the surrounding regions, compared with the HYSPLIT that had high concentrations of $^{137}Cs$ in only small local areas with the movement of air masses along the local winds.

• Nuclear Engineering and Technology
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• v.55 no.6
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• pp.2305-2314
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• 2023

The governing equations of atmospheric dispersion most often taking the form of a second-order partial differential equation (PDE). Currently, typical computational codes for predicting atmospheric dispersion use the Gaussian plume model that is an analytic solution. A Gaussian model is simple and enables rapid simulations, but it can be difficult to apply to situations with complex model parameters. Recently, a method of solving PDEs using artificial neural networks called physics-informed neural network (PINN) has been proposed. The PINN assumes the latent (hidden) solution of a PDE as an arbitrary neural network model and approximates the solution by optimizing the model. Unlike a Gaussian model, the PINN is intuitive in that it does not require special assumptions and uses the original equation without modifications. In this paper, we describe an approach to atmospheric dispersion modeling using the PINN and show its applicability through simple case studies. The results are compared with analytic and fundamental numerical methods to assess the accuracy and other features. The proposed PINN approximates the solution with reasonable accuracy. Considering that its procedure is divided into training and prediction steps, the PINN also offers the advantage of rapid simulations once the training is over.

• Journal of Environmental Science International
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• v.5 no.3
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• pp.277-284
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• 1996

The Characteristics of atmospheric flow and dispersion of air pollutants in the mountainous coastal area were studied using two-dimensional model by the combination of land-sea breezes and transport. The pollutants emitted into the simulated wind field in considering with the mesoscale local circulations. The typical effects of land-sea breezes and tophography of coastal area on the dispersion are discussed in detail, and the model is proved as an useful tool to pridict real time pollutant transport by the results of application studies in Pusan, Korea where the urbanized coastal area with mountainous topography. It was found that sulfur dioxide ($SO_2$) are differently transported and concentrated as going inland by the influence of the sea breeze with topographic changes. Key words : land-sea breezes, sulfur dioxide, dispersion, coastal area.

• Environmental Sciences Bulletin of The Korean Environmental Sciences Society
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• v.1 no.1
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• pp.35-43
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• 1997

Handling the emergency problems such as Chemobyl accident require real time prediction of pollutants dispersion. One-point real time sounding at pollutant source and simple model including turbulent-radiation process are very important to predict dispersion at real time. The stability categories obtained by one-dimensional numerical model (including PBL dynamics and radiative process) are good agreement with observational data (Golder, 1972). Therefore, the meteorological parameters (thermal, moisture and momentum fluxes; sensible and latent heat; Monin-Obukhov length and bulk Richardson number; vertical diffusion coefficient and TKE; mixing height) calculated by this model will be useful to understand the structure of stable boundary layer and to handling the emergency problems such as dangerous gasses accident. Especially, this simple model has strong merit for practical dispersion models which require turbulence process but does not takes long time to real predictions. According to the results of this model, the urban area has stronger vertical dispersion and weaker horizontal dispersion than rural area during daytime in summer season. The maximum stability class of urban area and rural area are 'A' and 'B' at 14 LST, respectively. After 20 LST, both urban and rural area have weak vertical dispersion, but they have strong horizontal dispersion. Generally, the urban area have larger radius of horizontal dispersion than rural area. Considering the resolution and time consuming problems of three dimensional grid model, one-dimensional model with one-point real sounding have strong merit for practical dispersion model.

• Journal of Korean Society for Atmospheric Environment
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• v.21 no.5
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• pp.537-545
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• 2005

A new dispersion model for dense gas is constructed in the Lagrangian framework. Prediction of concentration by the proposed model is compared with measure data obtained in the experiment conducted in Thorney Island in 1984. Two major effects of dense gas dispersion, gravity slumping and stratification effect, are successfully incorporated into LDM (Lagrangian dense gas model). Entrainment effect is naturally modelled by introducing stochastic dispersion model with the effect of turbulence suppression by stratification. Not only various releasing conditions but also complex terrain can be extended to, although proposed model is appropriate for flat terrain.