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The mixed layer modified radionuclide atmospheric diffusion based on Gaussian model.
Li, Ting; Zheng, Xiaolei; Yu, Shengpeng; Wang, Jin; Cheng, Jie; Liu, Jie.
Affiliation
  • Li T; Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei, Anhui, China.
  • Zheng X; University of Science and Technology of China, Hefei, Anhui, China.
  • Yu S; International Academy of Neutron Science, Qingdao, Shandong, China.
  • Wang J; International Academy of Neutron Science, Qingdao, Shandong, China.
  • Cheng J; International Academy of Neutron Science, Qingdao, Shandong, China.
  • Liu J; China Three Gorges University, Yichang, Hubei, China.
Front Public Health ; 10: 1097643, 2022.
Article in En | MEDLINE | ID: mdl-36684942
Background: Atmospheric diffusion is often accompanied by complex meteorological conditions of inversion temperature. Methods: In response to the emergency needs for rapid consequence assessment of nuclear accidents under these complex meteorological conditions, a Gaussian diffusion-based model of radionuclide is developed with mixed layer modification. The inhibition effect of the inversion temperature on the diffusion of radionuclides is modified in the vertical direction. The intensity of the radionuclide source is modified by the decay constant. Results: The results indicate that the enhancement effect of the mixed layer on the concentration of radionuclides is reflected. The shorter the half-life of the radionuclide, the greater the effect of reducing the diffusion concentration. The Kincaid dataset validation in the Model Validation Kit (MVK) shows that, compared to the non-modified model, predictions of the modified model have an enhancement effect beyond 5 km, modulating the prediction values to be closer to the observation values. Conclusions: This development is consistent with the modification effects of the mixed layer. The statistical indicators show that the criteria of the modified model meet the criteria of the recommended model.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Radioisotopes Type of study: Prognostic_studies Language: En Journal: Front Public Health Year: 2022 Document type: Article Affiliation country: Country of publication:

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Radioisotopes Type of study: Prognostic_studies Language: En Journal: Front Public Health Year: 2022 Document type: Article Affiliation country: Country of publication: