Suppr超能文献

放射性核素在沿海水生生态系统中的迁移和吸收:三维动态模型与箱式模型的比较。

Radionuclide transport and uptake in coastal aquatic ecosystems: a comparison of a 3D dynamic model and a compartment model.

机构信息

Ecological and Environmental Department, DHI, Agern Allé 5, 2970, Hørsholm, Denmark.

出版信息

Ambio. 2013 May;42(4):464-75. doi: 10.1007/s13280-013-0398-2.

Abstract

In safety assessments of underground radioactive waste repositories, understanding radionuclide fate in ecosystems is necessary to determine the impacts of potential releases. Here, the reliability of two mechanistic models (the compartmental K-model and the 3D dynamic D-model) in describing the fate of radionuclides released into a Baltic Sea bay is tested. Both are based on ecosystem models that simulate the cycling of organic matter (carbon). Radionuclide transfer is linked to adsorption and flows of carbon in food chains. Accumulation of Th-230, Cs-135, and Ni-59 in biological compartments was comparable between the models and site measurements despite differences in temporal resolution, biological state variables, and partition coefficients. Both models provided confidence limits for their modeled concentration ratios, an improvement over models that only estimate means. The D-model enables estimates at high spatio-temporal resolution. The K-model, being coarser but faster, allows estimates centuries ahead. Future developments could integrate the two models to take advantage of their respective strengths.

摘要

在地下放射性废物处置库的安全评估中,了解放射性核素在生态系统中的归宿对于确定潜在释放的影响是必要的。在这里,测试了两种基于模拟有机物(碳)循环的生态系统模型(分区 K 模型和 3D 动态 D 模型)来描述释放到波罗的海海湾的放射性核素的归宿。放射性核素的转移与食物链中碳的吸附和流动有关。尽管在时间分辨率、生物状态变量和分配系数方面存在差异,但模型和现场测量结果在生物区室中 Th-230、Cs-135 和 Ni-59 的积累情况具有可比性。两个模型都为其模型化浓度比提供了置信限,这比仅估计平均值的模型有所改进。D 模型能够以高时空分辨率进行估算。K 模型虽然较粗糙但速度更快,可以预测数百年后的情况。未来的发展可以整合这两个模型,以充分利用它们各自的优势。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c0a5/3636370/44d2180fdd20/13280_2013_398_Fig1_HTML.jpg

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验