Almahayni Talal, Beresford Nicholas A, Crout Neil M J, Sweeck Lieve
Biosphere Impact Studies Unit, The Belgian Nuclear Research Centre, Boeretang 200, Mol, Belgium.
NERC Centre for Ecology and Hydrology, CEH Lancaster, Lancaster Environment Centre, Library Av., Bailrigg, Lancaster, LA1 4AP, UK.
J Environ Radioact. 2019 May;201:58-66. doi: 10.1016/j.jenvrad.2019.01.006. Epub 2019 Feb 15.
Numerous radioecological models have been developed to predict radionuclides transfer from contaminated soils to the food chain, which is an essential step in preparing and responding to nuclear emergencies. However, the lessons learned from applying these models to predict radiocaesium (RCs) soil-to-plant transfer following the Fukushima accident in 2011 renewed interest in RCs transfer modelling. To help guide and prioritise further research in relation to modelling RCs transfer in terrestrial environments, we reviewed existing models focussing on transfer to food crops and animal fodders. To facilitate the review process, we categorised existing RCs soil-to-plant transfer models into empirical, semi-mechanistic and mechanistic, though several models cross the boundaries between these categories. The empirical approach predicts RCs transfer to plants based on total RCs concentration in soil and an empirical transfer factor. The semi-mechanistic approach takes into account the influence of soil characteristics such as clay and exchangeable potassium content on RCs transfer. It also uses 'bioavailable' rather than total RCs in soil. The mechanistic approach considers the physical and chemical processes that control RCs distribution and uptake in soil-plant systems including transport in the root zone and root absorption kinetics. Each of these modelling approaches has its advantages and disadvantages. The empirical approach is simple and requires two inputs, but it is often associated with considerably uncertainty due to the large variability in the transfer factor. The semi-mechanistic approach factorises more soil and plant parameters than the empirical approach; therefore, it is applicable to a wider range of environmental conditions. The mechanistic approach is instrumental in understanding RCs mobility and transfer in soil-plant systems; it also helps to identify influential soil and plant parameters. However, the comlexity and the large amount of specific parameters make this approach impractical for nuclear emergency preparedness and response purposes. We propose that the semi-mechanistic approach is sufficiently robust and practical, hence more fit for the purpose of planning and responding to nuclear emergencies compared with the empirical and mechanistic approaches. We recommend further work to extend the applicability of the semi-mechanistic approach to a wide range of plants and soils.
已经开发了许多放射生态模型来预测放射性核素从受污染土壤向食物链的转移，这是核应急准备和应对中的关键步骤。然而，2011年福岛事故后应用这些模型预测放射性铯（RCs）从土壤到植物的转移所吸取的教训，重新引发了对RCs转移建模的兴趣。为了指导和确定陆地环境中RCs转移建模的进一步研究重点，我们回顾了现有的侧重于向粮食作物和动物饲料转移的模型。为便于审查过程，我们将现有的RCs从土壤到植物的转移模型分为经验模型、半机理模型和机理模型，不过有几个模型跨越了这些类别之间的界限。经验方法基于土壤中总RCs浓度和经验转移因子来预测RCs向植物的转移。半机理方法考虑了土壤特性（如粘土和可交换钾含量）对RCs转移的影响。它还使用土壤中“生物可利用”的RCs而非总RCs。机理方法考虑了控制土壤-植物系统中RCs分布和吸收的物理和化学过程，包括根区运输和根系吸收动力学。这些建模方法各有优缺点。经验方法简单，只需两个输入，但由于转移因子变化很大，往往存在相当大的不确定性。半机理方法比经验方法考虑了更多的土壤和植物参数；因此，它适用于更广泛的环境条件。机理方法有助于理解RCs在土壤-植物系统中的迁移和转移；它还有助于识别有影响的土壤和植物参数。然而，其复杂性和大量特定参数使得这种方法对于核应急准备和应对目的不切实际。我们认为半机理方法足够稳健和实用，因此与经验方法和机理方法相比，更适合核应急规划和应对目的。我们建议进一步开展工作，将半机理方法的适用性扩展到广泛的植物和土壤。
