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Using a chain of models to predict health and environmental impacts in Norway from a hypothetical nuclear accident at the Sellafield site.
Journal of Environmental Radioactivity ( IF 1.9 ) Pub Date : 2020-01-23 , DOI: 10.1016/j.jenvrad.2020.106159
A Liland 1 , O C Lind 2 , J Bartnicki 3 , J E Brown 1 , J E Dyve 1 , M Iosjpe 1 , H Klein 3 , Y Lin 4 , M Simonsen 3 , P Strand 1 , H Thørring 1 , M A Ytre-Eide 1 , B Salbu 2
Affiliation  

When a nuclear accident occurs, decision makers in the affected country/countries would need to act promptly to protect people, the environment and societal interests from harmful impacts of radioactive fallout. The decisions are usually based on a combination of model prognoses, measurements, and expert judgements within in an emergency decision support system (DSS). Large scale nuclear accidents would need predictive models for the atmospheric, terrestrial, freshwater, and marine ecosystems, for the connections between these in terms of radionuclide fluxes, and for the various exposure pathways to both humans and biota. Our study showed that eight different models and DSS modules could be linked to assess the total human and environmental consequences in Norway from a hypothetical nuclear accident, here chosen to be the Sellafield nuclear reprocessing plant. Activity concentrations and dose rates from 137Cs for both humans and the environment via various exposure routes were successfully modelled. The study showed that a release of 1% of the total inventory of 137Cs in the Highly Active Liquor Tanks at Sellafield Ltd is predicted to severely impact humans and the environment in Norway if strong winds are blowing towards the country at the time of an accidental atmospheric release. Furthermore, since the models did not have built-in uncertainty ranges when this Sellafield study was performed, investigations were conducted to identify the key factors contributing to uncertainty in various models and prioritise the ones to focus on in future research.

中文翻译:

使用一系列模型来预测塞拉菲尔德工厂发生的核事故对挪威的健康和环境的影响。

当发生核事故时,受灾国家/地区的决策者需要迅速采取行动,保护人员,环境和社会利益免受放射性尘埃的有害影响。决策通常基于紧急决策支持系统(DSS)中模型预测,度量和专家判断的组合。大规模核事故将需要针对大气,陆地,淡水和海洋生态系统的预测模型,以及就放射性核素通量而言两者之间的联系以及对人类和生物群的各种暴露途径的预测模型。我们的研究表明,可以将八个不同的模型和DSS模块关联起来,以评估假设的核事故在挪威对人类和环境造成的总体后果,这里被选为塞拉菲尔德核后处理厂。通过各种暴露途径成功地模拟了人类和环境在137Cs下的活动浓度和剂量率。该研究表明,如果在意外的大气中正向该国吹来大风,挪威Sellafield公司的高活性白酒储罐中137Cs总量的1%释放将严重影响挪威的人类和环境。释放。此外,由于在进行Sellafield研究时这些模型没有内置的不确定性范围,因此进行了调查以找出导致各种模型中的不确定性的关键因素,并对这些因素进行了优先排序,以便将来进行研究。通过各种暴露途径成功地模拟了人类和环境在137Cs下的活动浓度和剂量率。该研究表明,如果在意外的大气中正向该国吹来大风,挪威Sellafield公司的高活性白酒储罐中137Cs总量的1%释放将严重影响挪威的人类和环境。释放。此外,由于在进行Sellafield研究时这些模型没有内置的不确定性范围,因此进行了调查以找出导致各种模型中的不确定性的关键因素,并对这些因素进行了优先排序,以便将来进行研究。通过各种暴露途径成功地模拟了人类和环境在137Cs下的活动浓度和剂量率。该研究表明,如果在意外的大气中正向该国吹来大风,挪威Sellafield公司的高活性白酒储罐中137Cs总量的1%释放将严重影响挪威的人类和环境。释放。此外,由于在进行Sellafield研究时这些模型没有内置的不确定性范围,因此进行了调查以找出导致各种模型中的不确定性的关键因素,并对这些因素进行了优先排序,以便将来进行研究。该研究表明,如果在意外的大气中正向该国吹来大风,挪威Sellafield公司的高活性白酒储罐中137Cs总量的1%释放将严重影响挪威的人类和环境。释放。此外,由于在进行Sellafield研究时这些模型没有内置的不确定性范围,因此进行了调查以找出导致各种模型中的不确定性的关键因素,并对这些因素进行了优先排序,以便将来进行研究。该研究表明,如果在意外的大气中正向该国吹来大风,挪威Sellafield公司的高活性白酒储罐中137Cs总量的1%释放将严重影响挪威的人类和环境。释放。此外,由于在进行Sellafield研究时这些模型没有内置的不确定性范围,因此进行了调查以找出导致各种模型中的不确定性的关键因素,并对这些因素进行了优先排序,以便将来进行研究。
更新日期:2020-01-23
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