各类放射性核素具有不同的大气扩散特性,如轻气体和重颗粒的浮力和重力沉积现象,分别。高斯羽流模型被广泛用于描述放射性流出物的大气扩散行为,特别是用于工程环境影响评估或核应急支持的目的。尽管如此,浮力和重力沉积在以前的工作中很少报道,特别是氚,这可能会导致对公众评估近地表浓度分布和辐射剂量的偏差。基于多种形式的氚案例,我们对浮力和重力沉积现象进行了定量描述,并讨论了建立改进的高斯羽流模型来预测近地表浓度分布的可行性。首先,通过使用计算流体动力学方法(CFD)和标准高斯羽流模型来预测表面附近的tri浓度分布,以达到一致性,而无需考虑浮力和重力沉积效应。其次,通过气态tri的物种迁移模型和液滴tri的离散相模型,结合气态tri的密度变化引起的浮力和足够大小的液滴tri的重力,确定了浮力和重力沉积的影响。第三,获得了浮力和重力沉积校正因子,以修改标准高斯羽流模型。最后,将改进高斯羽流模型的预测结果与CFD方法进行了比较。事实证明,改进的校正方法可以更准确地预测具有密度变化的气态污染物或具有重力沉积特性的颗粒的大气浓度分布。
Various types of radionuclides have different atmospheric dispersion characteristics, such as
buoyancy and gravitational deposition phenomenon of light gas and heavy particles, respectively. Gaussian plume model was widely used to describe atmospheric dispersion behaviors of radioactive effluents, particularly for the purpose of engineering environmental impact assessment or nuclear emergency support. Nonetheless,
buoyancy and gravitational deposition were rarely reported in previous work for tritium in particular, which might cause a deviation in evaluating near-surface concentration distribution and radiation dose to the public. Based on the multi-form tritium
case, we made a quantitative description for the
buoyancy and gravitational deposition phenomenon and discussed the feasibility of developing an improved Gaussian plume model to predict near-surface concentration distribution. Firstly, tritium concentration distribution near to the surface was predicted by using computational fluid dynamics method (CFD) and standard Gaussian plume model to reach consistency without consideration of buoyancy and gravitational deposition effects. Secondly, effects of
buoyancy and gravitational deposition were identified by species transport model for gaseous tritium and discrete phase model for droplet tritium with integrating the
buoyancy force caused by density variation of gaseous tritium and gravitational force of droplet tritium with enough size. Thirdly, buoyancy and gravitational deposition correction factors were obtained to modify the standard Gaussian plume model. Lastly, predictive results by improved Gaussian plume model were compared with CFD method. It was proved the improved correction method enables higher accuracy in predicting the atmospheric concentration distribution of gaseous pollutants with density variation or particles with gravitational deposition properties.