• Journal of Radiation Protection and Research
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• v.28 no.4
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• pp.311-319
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• 2003

We developed a grid-based Gaussian plume model to evaluate tracer release data measured at Young Gwang nuclear site in 1996. Downwind distance was divided into every 10m from 0.1km to 20km, and crosswind distance was divided into every 10m centering released point from -5km to 5km. We determined dispersion factors, ${\sigma}_y\;and\;{\sigma}_z$ using Pasquill-Gifford method computed by atmospheric stability. Forecasting ability of the grid-based Gaussian plume model was better at the 3km away from the source than 8km. We confirmed that dispersion band must be modified if receptor is far away from the source, otherwise P-G method is not appropriate to compute diffusion distance and diffusion strength in case of growing distance. So, we developed an empirical equation using linear programming. An objective function was designed to minimize sum of the absolute value between observed and computed values. As a result of application of the modified dispersion equation, prediction ability was improved rather than P-G method.

• Proceedings of the Korea Air Pollution Research Association Conference
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• 1999.10a
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• pp.183-185
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• 1999

가우시안 모델의 부정확성의 중요한 요인중의 하나는 수평확산폭($\sigma$$_{y}$)과 연직확산폭($\sigma$$_{z}$)이다. (이와김,1992) 가우시안 모델에서 사용되는 확산폭 산출방법인 Pasquill-Gifford Scheme은 미국 Nebraska 주 O'neill 부근 풀로 덮힌 평탄한 지형에서 확산 실험을 수행한 Prairie grass project의 결과로 연기의 확산폭은 각 안정도 계급(A-F)별로 거리의 함수로 나타낸 식을 이용하고 있다.(중략)략)

• 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.