National University of Life and Environment Sciences (NUBiP of Ukraine), Ukraine; Centre for Environmental Radioactivity (CERAD CoE), Faculty of Environmental Sciences and Natural Resource Management, Norwegian University of Life Sciences, P.O. Box 5003, N-1432 Ås, Norway.
National University of Life and Environment Sciences (NUBiP of Ukraine), Ukraine; Centre for Environmental Radioactivity (CERAD CoE), Faculty of Environmental Sciences and Natural Resource Management, Norwegian University of Life Sciences, P.O. Box 5003, N-1432 Ås, Norway.
J Environ Radioact. 2020 Nov;223-224:106387. doi: 10.1016/j.jenvrad.2020.106387. Epub 2020 Aug 28.
The contamination in the near exclusion zone of the Chernobyl nuclear power plant (ChNPP) with Sr, Pu and Am is associated with irradiated nuclear fuel particles. Fit for purpose models enabling long term prediction of mobility and bioavailability of particle-associated radionuclides are crucial for radiation protection of humans and the environment, as well as for planning of remediation measures and future land use. In the present work, a dynamic fuel particle dissolution model developed in 1999-2002 is described and validated using data based on sampling in 2015. The model is based on the characterization of the radionuclide source term of the waste in a shallow sub-surface radioactive waste storage, trench #22, in the Chernobyl Pilot Site (CPS) located in the Red Forest, 2.5 km west of the ChNPP, as well as the description of physical and chemical properties of the fuel particles and subsequent radionuclide leaching into the soil solution. Transformation rate constants of the fuel particle dissolution model related to topsoil, radioactive waste trench and submerged materials, and drained cooling pond sediments, should largely control the mobility and bioavailability of radionuclides (e.g., solubility in the soil, migration to groundwater and transfer to plants). The predicting power of the Chernobyl fuel particle dissolution model with respect to radionuclide leaching dynamics was validated using samples from the same experimental site, showing that predicted particle leaching and subsequent mobility and bioavailability were within 46 ± 3% of the observed data. Therefore, linking source- and release-scenario dependent characteristics of radioactive particles to their potential weathering can provide information that can be implemented in impact assessments models for existing contaminated areas as well as for future events.
切尔诺贝利核电站（ChNPP）近区的 Sr、Pu 和 Am 污染与辐照核燃料颗粒有关。适合目的的模型能够长期预测颗粒相关放射性核素的迁移性和生物可利用性，对于人类和环境的辐射防护、修复措施和未来土地利用规划至关重要。在本工作中，描述了 1999-2002 年开发的动态燃料颗粒溶解模型，并使用基于 2015 年采样的数据进行了验证。该模型基于浅层地下放射性废物储存中废物的放射性核素源项的特征，切尔诺贝利试验场（CPS）位于 ChNPP 以西 2.5 公里的红林，以及燃料颗粒的物理和化学性质的描述以及随后的放射性核素浸出到土壤溶液中。与表土、放射性废物沟和淹没材料以及排水冷却池沉积物相关的燃料颗粒溶解模型的转化速率常数，应在很大程度上控制放射性核素的迁移性和生物可利用性（例如，在土壤中的溶解度、向地下水的迁移和向植物的转移）。使用相同实验场地的样本验证了切尔诺贝利燃料颗粒溶解模型对放射性核素浸出动力学的预测能力，结果表明，预测的颗粒浸出及其随后的迁移性和生物可利用性在观察数据的 46±3%范围内。因此，将放射性颗粒的源和释放情景相关特性与它们的潜在风化联系起来，可以为现有污染区域的影响评估模型以及未来事件提供信息。
