Long-term prediction of 137Cs in Lake Onuma on Mt. Akagi after the Fukushima accident using fractional diffusion model
The Fukushima Daiichi Nuclear Power Plant accident also contaminates lakes in Japan. Especially in closed lakes, there is a problem of prolonged low-level 137 Cs contamination because the activity concentration of 137 Cs declines sharply immediately after the accident, but then begins to decrease sl...
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description | The Fukushima Daiichi Nuclear Power Plant accident also contaminates lakes in Japan. Especially in closed lakes, there is a problem of prolonged low-level
137
Cs contamination because the activity concentration of
137
Cs declines sharply immediately after the accident, but then begins to decrease slowly. In this paper, we derived a long-term prediction formula based on the fractional diffusion model (FDM) for the temporal variation in
137
Cs activity concentrations of the water in Lake Onuma on Mt. Akagi, one of the closed lakes, and of pond smelt (Hypomesus nipponensis), a typical fish species inhabiting in the lake. The formula reproduced well the measured
137
Cs activity concentration of the lake water and pond smelt for 5.4 years after the accident. Next, we performed long-term prediction for 10,000 days using this formula and compared it with the prediction results of the two-component decay function model (TDM), which is the most common model. The results suggest that the FDM prediction will lead to a longer period of contamination with low-level
137
Cs than the TDM prediction. |
doi_str_mv | 10.1038/s41598-021-99667-1 |
format | Article |
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137
Cs contamination because the activity concentration of
137
Cs declines sharply immediately after the accident, but then begins to decrease slowly. In this paper, we derived a long-term prediction formula based on the fractional diffusion model (FDM) for the temporal variation in
137
Cs activity concentrations of the water in Lake Onuma on Mt. Akagi, one of the closed lakes, and of pond smelt (Hypomesus nipponensis), a typical fish species inhabiting in the lake. The formula reproduced well the measured
137
Cs activity concentration of the lake water and pond smelt for 5.4 years after the accident. Next, we performed long-term prediction for 10,000 days using this formula and compared it with the prediction results of the two-component decay function model (TDM), which is the most common model. The results suggest that the FDM prediction will lead to a longer period of contamination with low-level
137
Cs than the TDM prediction.</description><identifier>EISSN: 2045-2322</identifier><identifier>DOI: 10.1038/s41598-021-99667-1</identifier><language>eng</language><publisher>London: Nature Publishing Group UK</publisher><subject>639/705/1041 ; 704/172 ; 704/286 ; Cesium radioisotopes ; Closed lakes ; Contamination ; Diffusion models ; Humanities and Social Sciences ; Hypomesus olidus ; Lakes ; multidisciplinary ; Nuclear accidents & safety ; Nuclear power plants ; Ponds ; Predictions ; Science ; Science (multidisciplinary) ; Temporal variations</subject><ispartof>Scientific reports, 2021-10, Vol.11 (1)</ispartof><rights>The Author(s) 2021</rights><rights>The Author(s) 2021. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-p721-313f12a18a043f3bdce18285f630fd7bac9da84d20cc8622b9908612b3f9f9393</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1038/s41598-021-99667-1$$EPDF$$P50$$Gspringer$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://doi.org/10.1038/s41598-021-99667-1$$EHTML$$P50$$Gspringer$$Hfree_for_read</linktohtml><link.rule.ids>314,776,780,860,27901,27902,41096,42165,51551</link.rule.ids></links><search><creatorcontrib>Suetomi, Eiichi</creatorcontrib><creatorcontrib>Hatano, Yuko</creatorcontrib><creatorcontrib>Fujita, Masakiyo</creatorcontrib><creatorcontrib>Okada, Yukiko</creatorcontrib><creatorcontrib>Suzuki, Kyuma</creatorcontrib><creatorcontrib>Watanabe, Shun</creatorcontrib><title>Long-term prediction of 137Cs in Lake Onuma on Mt. Akagi after the Fukushima accident using fractional diffusion model</title><title>Scientific reports</title><addtitle>Sci Rep</addtitle><description>The Fukushima Daiichi Nuclear Power Plant accident also contaminates lakes in Japan. Especially in closed lakes, there is a problem of prolonged low-level
137
Cs contamination because the activity concentration of
137
Cs declines sharply immediately after the accident, but then begins to decrease slowly. In this paper, we derived a long-term prediction formula based on the fractional diffusion model (FDM) for the temporal variation in
137
Cs activity concentrations of the water in Lake Onuma on Mt. Akagi, one of the closed lakes, and of pond smelt (Hypomesus nipponensis), a typical fish species inhabiting in the lake. The formula reproduced well the measured
137
Cs activity concentration of the lake water and pond smelt for 5.4 years after the accident. Next, we performed long-term prediction for 10,000 days using this formula and compared it with the prediction results of the two-component decay function model (TDM), which is the most common model. The results suggest that the FDM prediction will lead to a longer period of contamination with low-level
137
Cs than the TDM prediction.</description><subject>639/705/1041</subject><subject>704/172</subject><subject>704/286</subject><subject>Cesium radioisotopes</subject><subject>Closed lakes</subject><subject>Contamination</subject><subject>Diffusion models</subject><subject>Humanities and Social Sciences</subject><subject>Hypomesus olidus</subject><subject>Lakes</subject><subject>multidisciplinary</subject><subject>Nuclear accidents & safety</subject><subject>Nuclear power plants</subject><subject>Ponds</subject><subject>Predictions</subject><subject>Science</subject><subject>Science (multidisciplinary)</subject><subject>Temporal variations</subject><issn>2045-2322</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>C6C</sourceid><sourceid>BENPR</sourceid><recordid>eNpFkMtqwzAQRUWh0JDmB7oSdO1Uo_FDWobQtAWXbLIXsh6J8rBdy-73V00Knc3AzJ3LnUPIE7AlMBQvMYdCioxxyKQsyyqDOzLjLC8yjpw_kEWMR5aq4DIHOSPfddfus9ENF9oPzgYzhq6lnaeA1TrS0NJanxzdttNF07T5HJd0ddL7QLVPV3Q8OLqZTlM8hCTQxgTr2pFOMbR76gd99dNnaoP3aZgcLp1150dy7_U5usVfn5Pd5nW3fs_q7dvHelVnfZU-QEAPXIPQLEePjTUOBBeFL5F5WzXaSKtFbjkzRpScN1IyUQJv0EsvUeKcPN9s-6H7mlwc1bGbhpQnKl4IKEEiiqTCmyr2Q4rthn8VMPWLVd2wqoRVXbEqwB8P4Gw8</recordid><startdate>20211013</startdate><enddate>20211013</enddate><creator>Suetomi, Eiichi</creator><creator>Hatano, Yuko</creator><creator>Fujita, Masakiyo</creator><creator>Okada, Yukiko</creator><creator>Suzuki, Kyuma</creator><creator>Watanabe, Shun</creator><general>Nature Publishing Group UK</general><general>Nature Publishing Group</general><scope>C6C</scope><scope>3V.</scope><scope>7X7</scope><scope>7XB</scope><scope>88A</scope><scope>88E</scope><scope>88I</scope><scope>8FE</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>LK8</scope><scope>M0S</scope><scope>M1P</scope><scope>M2P</scope><scope>M7P</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>Q9U</scope></search><sort><creationdate>20211013</creationdate><title>Long-term prediction of 137Cs in Lake Onuma on Mt. Akagi after the Fukushima accident using fractional diffusion model</title><author>Suetomi, Eiichi ; Hatano, Yuko ; Fujita, Masakiyo ; Okada, Yukiko ; Suzuki, Kyuma ; Watanabe, Shun</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-p721-313f12a18a043f3bdce18285f630fd7bac9da84d20cc8622b9908612b3f9f9393</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>639/705/1041</topic><topic>704/172</topic><topic>704/286</topic><topic>Cesium radioisotopes</topic><topic>Closed lakes</topic><topic>Contamination</topic><topic>Diffusion models</topic><topic>Humanities and Social Sciences</topic><topic>Hypomesus olidus</topic><topic>Lakes</topic><topic>multidisciplinary</topic><topic>Nuclear accidents & safety</topic><topic>Nuclear power plants</topic><topic>Ponds</topic><topic>Predictions</topic><topic>Science</topic><topic>Science (multidisciplinary)</topic><topic>Temporal variations</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Suetomi, Eiichi</creatorcontrib><creatorcontrib>Hatano, Yuko</creatorcontrib><creatorcontrib>Fujita, Masakiyo</creatorcontrib><creatorcontrib>Okada, Yukiko</creatorcontrib><creatorcontrib>Suzuki, Kyuma</creatorcontrib><creatorcontrib>Watanabe, Shun</creatorcontrib><collection>Springer Nature OA Free Journals</collection><collection>ProQuest Central (Corporate)</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Biology Database (Alumni Edition)</collection><collection>Medical Database (Alumni Edition)</collection><collection>Science Database (Alumni Edition)</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest One Sustainability</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>Natural Science Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>ProQuest Biological Science Collection</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Science Database</collection><collection>Biological Science Database</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>ProQuest Central Basic</collection><jtitle>Scientific reports</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Suetomi, Eiichi</au><au>Hatano, Yuko</au><au>Fujita, Masakiyo</au><au>Okada, Yukiko</au><au>Suzuki, Kyuma</au><au>Watanabe, Shun</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Long-term prediction of 137Cs in Lake Onuma on Mt. Akagi after the Fukushima accident using fractional diffusion model</atitle><jtitle>Scientific reports</jtitle><stitle>Sci Rep</stitle><date>2021-10-13</date><risdate>2021</risdate><volume>11</volume><issue>1</issue><eissn>2045-2322</eissn><abstract>The Fukushima Daiichi Nuclear Power Plant accident also contaminates lakes in Japan. Especially in closed lakes, there is a problem of prolonged low-level
137
Cs contamination because the activity concentration of
137
Cs declines sharply immediately after the accident, but then begins to decrease slowly. In this paper, we derived a long-term prediction formula based on the fractional diffusion model (FDM) for the temporal variation in
137
Cs activity concentrations of the water in Lake Onuma on Mt. Akagi, one of the closed lakes, and of pond smelt (Hypomesus nipponensis), a typical fish species inhabiting in the lake. The formula reproduced well the measured
137
Cs activity concentration of the lake water and pond smelt for 5.4 years after the accident. Next, we performed long-term prediction for 10,000 days using this formula and compared it with the prediction results of the two-component decay function model (TDM), which is the most common model. The results suggest that the FDM prediction will lead to a longer period of contamination with low-level
137
Cs than the TDM prediction.</abstract><cop>London</cop><pub>Nature Publishing Group UK</pub><doi>10.1038/s41598-021-99667-1</doi><oa>free_for_read</oa></addata></record> |
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subjects | 639/705/1041 704/172 704/286 Cesium radioisotopes Closed lakes Contamination Diffusion models Humanities and Social Sciences Hypomesus olidus Lakes multidisciplinary Nuclear accidents & safety Nuclear power plants Ponds Predictions Science Science (multidisciplinary) Temporal variations |
title | Long-term prediction of 137Cs in Lake Onuma on Mt. Akagi after the Fukushima accident using fractional diffusion model |
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