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Geostatistical Modelling for 134Cs Released from The Fukushima Radioactive Fallout

Year 2018, Volume: 1 Issue: 1, 102 - 110, 06.08.2018

Sevim Bilici , Ahmet Bilici , Fatih Külahcı

Abstract

The distribution of radionuclides
show variability as spatially. For this reason, determining the spatial
distribution is very important. In the study, spatial analysis technique using
as Point Cumulative Semivariogram (PCSV) method is modelled for the radioactive
fallout which had occurred after the Fukushima Dai-Ichi Nuclear Power Plant
accident. The theoretical basis of the Point Cumulative Semivariogram (PCSV)
method is based to variogram analysis. PCSV allow the regionalized behavior of
variables into use. PCSV modelling is applied for 134Cs radionuclide
in soil samples in the accident area. 5 different models are obtained to
determine the transport properties and distribution of 134Cs.


Keywords

Fukushima Radioactive Fallout Spatial Analysis Point Cumulative Semivariogram 134Cs Transport

References

  • [1] N. Yoshida, Y. Takahashi, Land-surface contamination by radionuclides from the Fukushima Daiichi Nuclear Power Plant accident. Elements 8 (2012) 201–206.
  • [2] K. Hirose, 2011 Fukushima Dai-ichi Nuclear Power Plant accident: summary of regional radioactive deposition monitoring results. J Environ Radioact 111 (2012) 13–17.
  • [3] TJ. Yasunari, A. Stohl, RS. Hayano, JF. Burkhart, S. Eckhardt, T. Yasunari, Cesium-137 deposition and contamination of Japanese soils due to the Fukushima nuclear accident. PNAS 108 (2011) 19530–19534.
  • [4] S. Niksarlıoğlu, F. Külahcı, Z. Şen, Spatiotemporal Modeling and Simulation of Chernobyl Radioactive Fallout in Northern Turkey, J Radioanalytical and Nuclear Chemistry 303 (1) (2015)171-186.
  • [5] F. Külahcı, Z. Şen, S. Kazanç, Cesium Concentration Spatial Distribution Modeling by PCSV, WAS Pollution 195 (2008) 151-160.
  • [6] I. H. Harms, Modelling the dispersion of 137Cs and 239Pu released from dumped waste in the Kara Sea. Journal of Marine Systems 13 (1997) 1–19.
  • [7] M. Van der Perk, T. Lev, A.G. Gillett, et al., Spatial modelling of transfer of long-lived radionuclides from soil to agricultural products in the Chernigov region, Ukraine. Ecological Modelling 128 (2000) 35–50.
  • [8] X. Zhang, Y. Long, X. He, J. Fu, Y. Zhang, A simplified 137Cs transport model for estimating erosion rates in undisturbed soil. J Environ Radioact 99 (2008) 1242–1246.
  • [9] J.C. Davis, Statistics and Data Analysis in Geology, New York, (2002) 638.
  • [10] G. Matheron, Random Structures and Mathematical Geology, Revue De L Institut International De Statistique-Review of The International Statistical Institute 38 (1) (1970).
  • [11] I. Clark, Practical geostatistics. Applied Science Publishers, London, 1979.
  • [12] I. Clark Practical geostatistics, Applied Science Publishers, London, 2001.
  • [13] F. Külahcı, Z. Şen, Potential utilization of the absolute point cumulative semivariogram technique for the evaluation of distribution coefficient. J Hazard Mater 168 (2009)1387–1396.
  • [14] Z. Şen, Cumulative semivariogram model of regionalized variables. Math Geol 21 (1989) 891–903.
  • [15] Z. Şen, ZZ. Habib, Point cumulative semivariogram of areal precipitation in mountainous regions. J Hydrol 205 (1998) 81–91.
  • [16] A.D. Şahin, Z. Şen, A new spatial prediction model and its application to wind records. Theoret Appl Climatol 79 (2004) 45–54.
  • [17] A.G. Journel, C.J. Huijbregts, Mining geostatistics. Academic Press, New York, 1978.
  • [18] Z. Şen, Point Cumulative Semivariogram for Identification of Heterogeneities in Regional Seismicity of Turkey. Mathematical Geology 30 (1998) 767-787.
  • [19] J. C. Davis, Statistics and Data Analysis in Geology, John Wiley & Sons Inc. Canada, 1973.

Year 2018, Volume: 1 Issue: 1, 102 - 110, 06.08.2018

Sevim Bilici , Ahmet Bilici , Fatih Külahcı

Abstract

References

  • [1] N. Yoshida, Y. Takahashi, Land-surface contamination by radionuclides from the Fukushima Daiichi Nuclear Power Plant accident. Elements 8 (2012) 201–206.
  • [2] K. Hirose, 2011 Fukushima Dai-ichi Nuclear Power Plant accident: summary of regional radioactive deposition monitoring results. J Environ Radioact 111 (2012) 13–17.
  • [3] TJ. Yasunari, A. Stohl, RS. Hayano, JF. Burkhart, S. Eckhardt, T. Yasunari, Cesium-137 deposition and contamination of Japanese soils due to the Fukushima nuclear accident. PNAS 108 (2011) 19530–19534.
  • [4] S. Niksarlıoğlu, F. Külahcı, Z. Şen, Spatiotemporal Modeling and Simulation of Chernobyl Radioactive Fallout in Northern Turkey, J Radioanalytical and Nuclear Chemistry 303 (1) (2015)171-186.
  • [5] F. Külahcı, Z. Şen, S. Kazanç, Cesium Concentration Spatial Distribution Modeling by PCSV, WAS Pollution 195 (2008) 151-160.
  • [6] I. H. Harms, Modelling the dispersion of 137Cs and 239Pu released from dumped waste in the Kara Sea. Journal of Marine Systems 13 (1997) 1–19.
  • [7] M. Van der Perk, T. Lev, A.G. Gillett, et al., Spatial modelling of transfer of long-lived radionuclides from soil to agricultural products in the Chernigov region, Ukraine. Ecological Modelling 128 (2000) 35–50.
  • [8] X. Zhang, Y. Long, X. He, J. Fu, Y. Zhang, A simplified 137Cs transport model for estimating erosion rates in undisturbed soil. J Environ Radioact 99 (2008) 1242–1246.
  • [9] J.C. Davis, Statistics and Data Analysis in Geology, New York, (2002) 638.
  • [10] G. Matheron, Random Structures and Mathematical Geology, Revue De L Institut International De Statistique-Review of The International Statistical Institute 38 (1) (1970).
  • [11] I. Clark, Practical geostatistics. Applied Science Publishers, London, 1979.
  • [12] I. Clark Practical geostatistics, Applied Science Publishers, London, 2001.
  • [13] F. Külahcı, Z. Şen, Potential utilization of the absolute point cumulative semivariogram technique for the evaluation of distribution coefficient. J Hazard Mater 168 (2009)1387–1396.
  • [14] Z. Şen, Cumulative semivariogram model of regionalized variables. Math Geol 21 (1989) 891–903.
  • [15] Z. Şen, ZZ. Habib, Point cumulative semivariogram of areal precipitation in mountainous regions. J Hydrol 205 (1998) 81–91.
  • [16] A.D. Şahin, Z. Şen, A new spatial prediction model and its application to wind records. Theoret Appl Climatol 79 (2004) 45–54.
  • [17] A.G. Journel, C.J. Huijbregts, Mining geostatistics. Academic Press, New York, 1978.
  • [18] Z. Şen, Point Cumulative Semivariogram for Identification of Heterogeneities in Regional Seismicity of Turkey. Mathematical Geology 30 (1998) 767-787.
  • [19] J. C. Davis, Statistics and Data Analysis in Geology, John Wiley & Sons Inc. Canada, 1973.
There are 19 citations in total.

Details

Primary Language English
Subjects Metrology, Applied and Industrial Physics
Journal Section Articles
Authors

Sevim Bilici

Ahmet Bilici

Fatih Külahcı

Publication Date August 6, 2018
Submission Date July 14, 2018
Acceptance Date July 31, 2018
Published in Issue Year 2018 Volume: 1 Issue: 1

Cite

APA Bilici, S., Bilici, A., & Külahcı, F. (2018). Geostatistical Modelling for 134Cs Released from The Fukushima Radioactive Fallout. Journal of Physical Chemistry and Functional Materials, 1(1), 102-110.
AMA Bilici S, Bilici A, Külahcı F. Geostatistical Modelling for 134Cs Released from The Fukushima Radioactive Fallout. Journal of Physical Chemistry and Functional Materials. August 2018;1(1):102-110.
Chicago Bilici, Sevim, Ahmet Bilici, and Fatih Külahcı. “Geostatistical Modelling for 134Cs Released from The Fukushima Radioactive Fallout”. Journal of Physical Chemistry and Functional Materials 1, no. 1 (August 2018): 102-10.
EndNote Bilici S, Bilici A, Külahcı F (August 1, 2018) Geostatistical Modelling for 134Cs Released from The Fukushima Radioactive Fallout. Journal of Physical Chemistry and Functional Materials 1 1 102–110.
IEEE S. Bilici, A. Bilici, and F. Külahcı, “Geostatistical Modelling for 134Cs Released from The Fukushima Radioactive Fallout”, Journal of Physical Chemistry and Functional Materials, vol. 1, no. 1, pp. 102–110, 2018.
ISNAD Bilici, Sevim et al. “Geostatistical Modelling for 134Cs Released from The Fukushima Radioactive Fallout”. Journal of Physical Chemistry and Functional Materials 1/1 (August 2018), 102-110.
JAMA Bilici S, Bilici A, Külahcı F. Geostatistical Modelling for 134Cs Released from The Fukushima Radioactive Fallout. Journal of Physical Chemistry and Functional Materials. 2018;1:102–110.
MLA Bilici, Sevim et al. “Geostatistical Modelling for 134Cs Released from The Fukushima Radioactive Fallout”. Journal of Physical Chemistry and Functional Materials, vol. 1, no. 1, 2018, pp. 102-10.
Vancouver Bilici S, Bilici A, Külahcı F. Geostatistical Modelling for 134Cs Released from The Fukushima Radioactive Fallout. Journal of Physical Chemistry and Functional Materials. 2018;1(1):102-10.
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