Environmental Technologies Branch, Canadian Nuclear Laboratories, Chalk River Laboratories, Chalk River, ON, K0J 1J0, Canada.
Ambio. 2018 Sep;47(5):585-594. doi: 10.1007/s13280-017-0995-6. Epub 2017 Nov 29.
Several cesium and strontium bioaccumulation models are used widely in national and international guidance for ecological and human health risk assessments for radiocesium (Cs and Cs) and radiostrontium (Sr), but have not been used to make predictions of radiological risk from nuclear accidents under variable environmental conditions on broad geographical scales. In this paper, we first present models for predicting the bioaccumulation of cesium and strontium by aquatic biota based on ambient concentrations of dissolved potassium and calcium, respectively, and then test these models using independent data from aquatic ecosystems at Canadian nuclear sites. Secondly, models yielding the best predictions across a wide range of input parameters were selected to estimate bioaccumulation factors (BAFs) for cesium and strontium in aquatic ecosystems across Canada, using trophic level of organisms and dissolved potassium for cesium and calcium concentrations for strontium as predictor variables, and presented as contour maps of radiological risk. The models show that risk from bioaccumulation of cesium and strontium can vary by several orders of magnitude depending on site-specific environmental conditions and trophic ecology. Overall, our results suggest that single-parameter approaches taken by regulatory standards may either over- or under-predict radiological risk at many locations, and are thus not readily suitable to inform siting decisions for new nuclear developments.
几种铯和锶的生物积累模型被广泛应用于放射性铯（Cs 和 Cs）和放射性锶（Sr）的生态和人类健康风险评估的国家和国际指南中，但尚未用于预测在广泛地理范围内的不同环境条件下核事故的放射性风险。在本文中，我们首先提出了基于环境中溶解钾和钙浓度的预测水生生物体内铯和锶生物积累的模型，然后使用来自加拿大核设施的水生生态系统的独立数据来测试这些模型。其次，选择能够在广泛输入参数范围内进行最佳预测的模型，使用生物的营养级和铯的溶解钾以及锶的钙浓度作为预测变量，来估算加拿大水生生态系统中铯和锶的生物积累因子（BAFs），并以放射性风险的等高线图形式呈现。这些模型表明，由于特定地点的环境条件和营养生态的不同，铯和锶的生物积累所带来的风险可能会有几个数量级的差异。总体而言，我们的研究结果表明，监管标准中采用的单参数方法可能会高估或低估许多地点的放射性风险，因此不太适合为新的核发展提供选址决策的依据。
