Atmospheric dispersion calculation of radiological releases can be done for different purposes such as deterministic or probabilistic safety analysis, environmental impact assessment, emergency preparedness and response. The characteristics of the weather conditions used in such assessments have a significant effect on the results, thus it is vital to select appropriate meteorological data for the calculation. In this paper, we conduct a study on deterministic safety analysis of radiological releases and investigate the effects of using different subsets of a meteorological database for such assessments.

We demonstrate that conducting deterministic dose assessment with a large site specific dataset of meteorological measurements and the use of a dose percentile is more beneficial than using one set of meteorological parameters. This is because variations in the meteorological condition have considerable effect on the dose results when using one set of meteorological parameters (e.g. worst case scenario) and less when a large meteorological database is used. We show that there can be a significant difference in the maximum dose computed with a large (at least annual with hourly resolution) meteorological database when there is a lack of data points or conversion of the parameters is needed, thus the 100th dose percentile is not optimal for verification of safety criteria fulfillment. It is better to use a relatively high percentile (e.g. from 80th to 99th), partly because it behaves more robustly and also because the use of the maximum dose (100th percentile) would be overly conservative. In case of meteorological data not being available for a sufficient temporal domain (e.g. data available for only one year or less), a multiplication factor – determined based on conservative assumptions and extensive studies on the possible spread of meteorological conditions and their effect at a given location – can be used for the comparison of a selected dose percentile with the safety limit.

A 5-years long meteorological database provided by a meteorological measurement system was used in this study as an example to demonstrate and calibrate the methodology on a real database. The methods presented in this work are universal, they can be used in deterministic safety analysis of other nuclear facilities, and the results can facilitate the development of optimal meteorological databases.

可以出于不同目的进行放射性释放的大气扩散计算，例如确定性或概率安全性分析，环境影响评估，应急准备和响应。在这种评估中使用的天气条件的特征对结果有重大影响，因此选择合适的气象数据进行计算至关重要。在本文中，我们对放射性释放的确定性安全性分析进行了研究，并研究了使用气象数据库的不同子集进行此类评估的影响。

我们证明与大型站点特定的气象测量数据集进行确定性剂量评估以及使用剂量百分位数比使用一组气象参数更有利。这是因为使用一组气象参数（例如最坏的情况）时，气象条件的变化对剂量结果有相当大的影响，而使用大型气象数据库时，变化较小。我们显示，当缺少数据点或需要参数转换时，大型（至少每年一次，以小时分辨率）气象数据库计算出的最大剂量可能存在显着差异，因此不需要百分位剂量最适合验证安全性标准的实现。最好使用相对较高的百分位数（例如 （从80到99）），部分是因为其性能更强壮，还因为使用最大剂量（第100个百分位数）过于保守。如果无法在足够的时域内获得气象数据（例如，只有一年或更短的时间才能获得数据），则乘数–根据保守的假设和对气象条件可能扩散及其在给定条件下的影响的广泛研究确定位置–可用于比较选定的剂量百分位数与安全极限。

在这项研究中，使用了由气象测量系统提供的长达5年的气象数据库作为示例，以在真实的数据库上演示和校准该方法。这项工作中介绍的方法是通用的，可用于其他核设施的确定性安全分析，其结果可促进最佳气象数据库的开发。