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首页> 外文期刊>Health Physics: Official Journal of the Health Physics Society >An estimate of spatial uncertainty of mean concentrations predicted by Gaussian dispersion models.
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An estimate of spatial uncertainty of mean concentrations predicted by Gaussian dispersion models.

机译:高斯离散模型预测的平均浓度的空间不确定性估计。

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摘要

Atmospheric dispersion models based on statistical theory predict the stochastic mean concentration at fixed points downwind. The uncertainty in the computed concentration, often expressed as a peak-to-mean ratio, is known to vary between two and five for Gaussian dispersion models. This paper shows that this can be correlated to uncertainty in the predicted location of a fixed concentration, and that in the centerline of the plume it is related to sigma(theta), the standard deviation of the observed horizontal wind direction. Practical formulae and methods are given that may be applied in the post-dispersion calculation phase of the risk assessment to ascertain the likely hazard zones.
机译:基于统计理论的大气弥散模型可预测顺风向定点处的随机平均浓度。对于高斯色散模型,通常以峰均比表示的计算浓度的不确定性在2到5之间变化。本文表明,这可能与固定浓度的预测位置的不确定性有关,并且在羽流的中心线中与观测到的水平风向的标准差sigma(theta)有关。给出了可用于风险评估的分散后计算阶段的实用公式和方法,以确定可能的危险区域。

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