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累积普通克里金插值模型预测放射性沉降物及其在切尔诺贝利和福岛评估中的应用:一种新方法和综述。

Cumulative Ordinary Kriging interpolation model to forecast radioactive fallout, and its application to Chernobyl and Fukushima assessment: a new method and mini review.

机构信息

Faculty of Science, Department of Physics, Nuclear Physics Division, Fırat University, Harput, TR, 23119, Elazig, Türkiye.

Engineering Natural Sciences Faculty, Istanbul Medipol University, Kavacık, Istanbul, Türkiye.

出版信息

Environ Sci Pollut Res Int. 2022 Sep;29(43):64298-64311. doi: 10.1007/s11356-022-21921-4. Epub 2022 Jul 16.

Abstract

The Cumulative Ordinary Kriging (COK) interpolation method has been proposed for the spatial prediction of atmospheric radioactive fallout in any given region. COK is built on the Ordinary Kriging and Cumulative Semivariogram methods and combines all their advantages to achieve statistically significant results. It is verified in this paper the reliability of the results from COK with other well-known Modified Shepard's Method (MSM), Inverse Distance Square (INDSQ), Polynomial Regression (PR), Natural Neighbour (NN), Radial Basis (RB), and Kriging Method interpolation methods. The model is tested in detail and in every possible way in two and three dimensions and applied to real-time Cs-134 and Cs-137 radioactive fallout data from the Chernobyl and Fukushima reactor accidents by combining both experimental and theoretical results. The results obtained from the applications for all interpolation methods are included in the supplementary materials section at the end of the article for the benefit of the readers. COK can also be used for spatial modelling of any particle at micro or macro scale. It can contribute significantly to environmental quality, ecological, and human health.

摘要

累积普通克里金(COK)插值方法已被提出用于任何给定区域大气放射性沉降物的空间预测。COK 建立在普通克里金和累积半变异函数方法的基础上,并结合了它们所有的优点,以获得具有统计学意义的结果。本文验证了 COK 与其他著名的修正谢泼德法(MSM)、倒数平方(INDSQ)、多项式回归(PR)、自然邻接法(NN)、径向基(RB)和克里金法插值方法的结果的可靠性。该模型在二维和三维空间中进行了详细和全面的测试,并通过结合实验和理论结果,应用于切尔诺贝利和福岛反应堆事故的实时 Cs-134 和 Cs-137 放射性沉降物数据。所有插值方法的应用结果都包含在文章末尾的补充材料部分,供读者参考。COK 还可用于微观或宏观尺度任何粒子的空间建模。它可以为环境质量、生态和人类健康做出重大贡献。

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