These integrated maps of radiation dose rates has started being used in the local
governments and agencies to plan the return of residents [12]. These maps can be
used to provide additional important measures with the estimates of upper and
lower bounds such as the expected cost and waste amount from decontamination.
Having the confidence intervals or the upper/lower bounds of those measures will
be helpful for planning the decontamination in more robust manner and also
preparing for the worst-case scenarios. In addition, the detailed map and its confidence interval are critical to inform the public of the contamination level as well as
the progress of decontamination for better decision-making.
References
1. K. Saito, Y. Onda. Outline of the national mapping projects implemented after the Fukushima
accident. J. Environ. Radioactivity 139(C), 240–249 (2015). doi:10.1016/j.jenvrad.2014.10.
009
2. S. Mikami, T. Maeyama, Y. Hoshide, R. Sakamoto, S. Sato, N. Okuda et al. The air dose rate
around the Fukushima Dai-ichi Nuclear Power Plant: its spatial characteristics and temporal
changes until December 2012. J. Environ. Radioactivity 139(C), 250–259. (2015). doi:10.
1016/j.jenvrad.2014.08.020
3. K. Saito, I. Tanihata, M. Fujiwara, T. Saito, S. Shimoura, T. Otsuka et al, Detailed deposition
density maps constructed by large-scale soil sampling for gamma-ray emitting radioactive
nuclides from the Fukushima Dai-ichi nuclear power plant accident. J. Environ. Radioactivity
139(C), 308–319. (2015). doi:10.1016/j.jenvrad.2014.02.014
4. Japan Atomic Energy Agency, Establishing the methodology to understand the long-term
impact of radionuclides released during the Fukushima Daiichi nuclear power plant accident,
JAEA Report (2012), http://fukushima.jaea.go.jp/initiatives/cat03/entry05.html. (in Japanese)
5. S. Tsuda, T. Yoshida, M. Tsutsumi, K. Saito, Characteristics and verification of a car-borne
survey system for dose rates in air: KURAMA-II. J. Environ. Radioactivity, 139(C), 260–265
(2015). doi:10.1016/j.jenvrad.2014.02.028
6. T. Torii, Y. Sanada, T. Sugita, A. Kondo, Y. Shikaze, Y. Urabe, Investigation of radionuclide
distribution using aircraft for surrounding environmental survey from Fukushima Daiichi
nuclear power plant. JAEA-Technology 2012-036, (2012) (in Japanese)
7. C.K. Wikle, R.F. Milliff, D. Nychka, L.M. Berliner, Spatiotemporal hierarchical Bayesian
modeling: tropical ocean surface winds. J. Am. Stat. Assoc. 96(454), 382–397 (2001)
8. H.M. Wainwright, D. Sassen, J. Chen, S.S. Hubbard, Bayesian hierarchical approach for
estimation of reactive facies over plume-scales using geophysical datasets. Water Resour.
Res. (2014)
9. Y. Zhou, A.M. Michalak, Characterizing attribute distributions in water sediments by
geostatistical downscaling. Environ. Sci. Technol. 43(24), 9267–9273 (2009)
10. P. Diggle, P.J. Ribeiro, Model-Based Geostatistics. Springer Science & Business Media
(2007)
11. H.M. Wainwright, J. Chen, A. Seki, K. Saito, A multiscale Bayesian data integration
approach for mapping radionuclide contamination in the regional scale. J Environ Radioact.
167, 62–69 (2017a)
12. H.M. Wainwright, A. Seki, J. Chen, K. Saito, A multiscale Bayesian data integration
approach for mapping air dose rates around the Fukushima Daiichi Nuclear Power Plant.
Proceeding of WM2017 Conference, March 5–9, 2017, Poenix, Arisona, USA (2017b)
64
H.M. Wainwright et al.
governments and agencies to plan the return of residents [12]. These maps can be
used to provide additional important measures with the estimates of upper and
lower bounds such as the expected cost and waste amount from decontamination.
Having the confidence intervals or the upper/lower bounds of those measures will
be helpful for planning the decontamination in more robust manner and also
preparing for the worst-case scenarios. In addition, the detailed map and its confidence interval are critical to inform the public of the contamination level as well as
the progress of decontamination for better decision-making.
References
1. K. Saito, Y. Onda. Outline of the national mapping projects implemented after the Fukushima
accident. J. Environ. Radioactivity 139(C), 240–249 (2015). doi:10.1016/j.jenvrad.2014.10.
009
2. S. Mikami, T. Maeyama, Y. Hoshide, R. Sakamoto, S. Sato, N. Okuda et al. The air dose rate
around the Fukushima Dai-ichi Nuclear Power Plant: its spatial characteristics and temporal
changes until December 2012. J. Environ. Radioactivity 139(C), 250–259. (2015). doi:10.
1016/j.jenvrad.2014.08.020
3. K. Saito, I. Tanihata, M. Fujiwara, T. Saito, S. Shimoura, T. Otsuka et al, Detailed deposition
density maps constructed by large-scale soil sampling for gamma-ray emitting radioactive
nuclides from the Fukushima Dai-ichi nuclear power plant accident. J. Environ. Radioactivity
139(C), 308–319. (2015). doi:10.1016/j.jenvrad.2014.02.014
4. Japan Atomic Energy Agency, Establishing the methodology to understand the long-term
impact of radionuclides released during the Fukushima Daiichi nuclear power plant accident,
JAEA Report (2012), http://fukushima.jaea.go.jp/initiatives/cat03/entry05.html. (in Japanese)
5. S. Tsuda, T. Yoshida, M. Tsutsumi, K. Saito, Characteristics and verification of a car-borne
survey system for dose rates in air: KURAMA-II. J. Environ. Radioactivity, 139(C), 260–265
(2015). doi:10.1016/j.jenvrad.2014.02.028
6. T. Torii, Y. Sanada, T. Sugita, A. Kondo, Y. Shikaze, Y. Urabe, Investigation of radionuclide
distribution using aircraft for surrounding environmental survey from Fukushima Daiichi
nuclear power plant. JAEA-Technology 2012-036, (2012) (in Japanese)
7. C.K. Wikle, R.F. Milliff, D. Nychka, L.M. Berliner, Spatiotemporal hierarchical Bayesian
modeling: tropical ocean surface winds. J. Am. Stat. Assoc. 96(454), 382–397 (2001)
8. H.M. Wainwright, D. Sassen, J. Chen, S.S. Hubbard, Bayesian hierarchical approach for
estimation of reactive facies over plume-scales using geophysical datasets. Water Resour.
Res. (2014)
9. Y. Zhou, A.M. Michalak, Characterizing attribute distributions in water sediments by
geostatistical downscaling. Environ. Sci. Technol. 43(24), 9267–9273 (2009)
10. P. Diggle, P.J. Ribeiro, Model-Based Geostatistics. Springer Science & Business Media
(2007)
11. H.M. Wainwright, J. Chen, A. Seki, K. Saito, A multiscale Bayesian data integration
approach for mapping radionuclide contamination in the regional scale. J Environ Radioact.
167, 62–69 (2017a)
12. H.M. Wainwright, A. Seki, J. Chen, K. Saito, A multiscale Bayesian data integration
approach for mapping air dose rates around the Fukushima Daiichi Nuclear Power Plant.
Proceeding of WM2017 Conference, March 5–9, 2017, Poenix, Arisona, USA (2017b)
64
H.M. Wainwright et al.