The Department of Ecology, Environment and Plant Sciences, Stockholm University, 10691 Stockholm, Sweden.
Swedish Nuclear Fuel and Waste Management Co, (SKB), Box 250, 10124 Stockholm, Sweden.
J Environ Radioact. 2014 Jul;133:48-59. doi: 10.1016/j.jenvrad.2013.05.003. Epub 2013 Jun 13.
This study implements new site-specific data and improved process-based transport model for 26 elements (Ac, Ag, Am, Ca, Cl, Cm, Cs, Ho, I, Nb, Ni, Np, Pa, Pb, Pd, Po, Pu, Ra, Se, Sm, Sn, Sr, Tc, Th, U, Zr), and validates model predictions with site measurements and literature data. The model was applied in the safety assessment of a planned nuclear waste repository in Forsmark, Öregrundsgrepen (Baltic Sea). Radionuclide transport models are central in radiological risk assessments to predict radionuclide concentrations in biota and doses to humans. Usually concentration ratios (CRs), the ratio of the measured radionuclide concentration in an organism to the concentration in water, drive such models. However, CRs vary with space and time and CR estimates for many organisms are lacking. In the model used in this study, radionuclides were assumed to follow the circulation of organic matter in the ecosystem and regulated by radionuclide-specific mechanisms and metabolic rates of the organisms. Most input parameters were represented by log-normally distributed probability density functions (PDFs) to account for parameter uncertainty. Generally, modelled CRs for grazers, benthos, zooplankton and fish for the 26 elements were in good agreement with site-specific measurements. The uncertainty was reduced when the model was parameterized with site data, and modelled CRs were most similar to measured values for particle reactive elements and for primary consumers. This study clearly demonstrated that it is necessary to validate models with more than just a few elements (e.g. Cs, Sr) in order to make them robust. The use of PDFs as input parameters, rather than averages or best estimates, enabled the estimation of the probable range of modelled CR values for the organism groups, an improvement over models that only estimate means. Using a mechanistic model that is constrained by ecological processes enables (i) the evaluation of the relative importance of food and water uptake pathways and processes such as assimilation and excretion, (ii) the possibility to extrapolate within element groups (a common requirement in many risk assessments when initial model parameters are scarce) and (iii) predictions of radionuclide uptake in the ecosystem after changes in ecosystem structure or environmental conditions. These features are important for the longterm (>1000 year) risk assessments that need to be considered for a deep nuclear waste repository.
本研究针对 26 种元素（Ac、Ag、Am、Ca、Cl、Cm、Cs、Ho、I、Nb、Ni、Np、Pa、Pb、Pd、Po、Pu、Ra、Se、Sm、Sn、Sr、Tc、Th、U、Zr）实施了新的特定地点数据和改进的基于过程的传输模型，并通过现场测量和文献数据对模型预测进行了验证。该模型应用于福斯马克（奥雷根德雷肯）计划核废料处置库的安全评估中（波罗的海）。放射性核素迁移模型是放射性风险评估的核心，用于预测生物群中放射性核素的浓度和对人类的剂量。通常，浓度比（CR），即生物体中测量的放射性核素浓度与水中浓度的比值，驱动此类模型。然而，CR 随空间和时间而变化，并且许多生物体的 CR 估计值都缺乏。在本研究中使用的模型中，放射性核素被假设遵循生态系统中有机物的循环，并受放射性核素特异性机制和生物体代谢率的调节。大多数输入参数用对数正态分布概率密度函数（PDF）表示，以考虑参数不确定性。通常，对于 26 种元素的食草动物、底栖动物、浮游动物和鱼类，模型预测的 CR 值与特定地点的测量值吻合良好。当模型用现场数据进行参数化时，不确定性降低，并且对于颗粒反应性元素和初级消费者，模型预测的 CR 值与测量值最相似。本研究清楚地表明，为了使模型稳健，有必要用多种元素（例如 Cs、Sr）进行验证，而不仅仅是用少数几种元素进行验证。使用 PDF 作为输入参数，而不是平均值或最佳估计值，使我们能够估计生物体组中模型预测的 CR 值的可能范围，这比仅估计平均值的模型有所改进。使用受生态过程约束的机制模型可以：（i）评估食物和水摄取途径以及同化和排泄等过程的相对重要性；（ii）在元素组内进行推断的可能性（在许多风险评估中，当初始模型参数稀缺时，这是常见要求）；（iii）在生态系统结构或环境条件发生变化后，预测放射性核素在生态系统中的摄取。这些功能对于需要考虑的深核废料处置库的长期（>1000 年）风险评估非常重要。
