The Fukushima Daiichi Nuclear Disaster

Author(s):  
Noriko Hikosaka Behling ◽  
Thomas G. Behling ◽  
Mark C. Williams ◽  
Shunsuke Managi
2012 ◽  
Vol 27 (2) ◽  
pp. 213-215 ◽  
Author(s):  
Takashi Nagata ◽  
Yoshinari Kimura ◽  
Masami Ishii

AbstractThe Great East Japan Earthquake occurred on March 11, 2011. In the first 10 days after the event, information about radiation risks from the Fukushima Daiichi nuclear plant was unavailable, and the disaster response, including deployment of disaster teams, was delayed. Beginning on March 17, 2011, the Japan Medical Association used a geographic information system (GIS) to visualize the risk of radiation exposure in Fukushima. This information facilitated the decision to deploy disaster medical response teams on March 18, 2011.Nagata T, Kimura Y, Ishii M. Use of a geographic information system (GIS) in the medical response to the Fukushima nuclear disaster in Japan. Prehosp Disaster Med. 2012;27(2):1-3.


2014 ◽  
Vol 304 (1) ◽  
pp. 27-31 ◽  
Author(s):  
Yoshikazu Kikawada ◽  
Masaaki Hirose ◽  
Atsushi Tsukamoto ◽  
Ko Nakamachi ◽  
Takao Oi ◽  
...  

Author(s):  
Tsukasa Sugita ◽  
Haruo Miyadera ◽  
Kenichi Yoshioka ◽  
Naoto Kume

A method to measure an amount of nuclear materials in fuel debris by using muon tomography has being developed for proceeding with decommissioning of Fukushima Daiichi nuclear power plant. As a result of the Fukushima Daiichi nuclear disaster, the molten fuels were mixed with reactor structures and accumulated as fuel debris in the reactor buildings. There is still a large amount of fuel debris remained in each reactor. Fuel debris removal is planned in the near future and the debris will be taken out in this process. The debris need to be inspected from a viewpoint of nuclear material control. Since the debris is a mixture of fuel and other structures, it is hard to quantitate nuclear materials in debris by existing measurement method. Muons are cosmic-ray particles which have high energies, therefore, they are highly penetrative. This feature makes muon tomography sensitive to find heavy materials such as uranium or plutonium. We conducted a simulation study of applying muon tomography to measure fuel debris by using a Monte-Carlo method. A simulation model which includes muon detectors, shielding container and fuel debris was constructed to reproduce a measurement situation at the site. In conclusion, muon tomography quantitate the nuclear materials, therefore, this method should be useful for the fuel debris removal of Fukushima Daiichi reactors.


2019 ◽  
Vol 44 (2-4) ◽  
pp. 94-118
Author(s):  
Thierry Ribault

This article is a contribution to the political economy of consent based on the analysis of speeches, declarations, initiatives, and policies implemented in the name of resilience in the context of the Fukushima nuclear disaster. It argues that, in practice as much as in theory, resilience fuels peoples’ submission to an existing reality—in the case of Fukushima, the submission to radioactive contamination—in an attempt to deny this reality as well as its consequences. The political economy of consent to the nuclear, of which resilience is one of the technologies, can be grasped at four interrelated analytical levels adapted to understanding how resilience is encoded in key texts and programs in the wake of the Fukushima Daiichi accident. The first level is technological: consent through and to the nuclear technology. The second level is sociometabolic: consent to nuisance. The third level is political: consent to participation. The fourth level is epistemological: consent to ignorance. A fifth cognitivo-experimental transversal level can also be identified: consent to experimentation, learning and training. We first analyze two key symptoms of the despotism of resilience: its incantatory feature and the way it supports mutilated life within a contaminated area and turns disaster into a cure. Then, we show how, in the reenchanted world of resilience, loss opens doors, that is, it paves the way to new “forms of life”: first through ignorance-based disempowerment; second through submission to protection. Finally, we examine the ideological mechanisms of resilience and how it fosters a government through the fear of fear. We approach resilience as a technology of consent mobilizing emotionalism and conditioning on one side, contingency and equivalence on the other.


2017 ◽  
Vol 12 (4) ◽  
pp. 460-463 ◽  
Author(s):  
Sho Takahashi ◽  
Jun Shigemura ◽  
Yoshitomo Takahashi ◽  
Soichiro Nomura ◽  
Aihide Yoshino ◽  
...  

AbstractObjectiveThe 2011 Fukushima Daiichi nuclear accident was the worst nuclear disaster since Chernobyl. The Daiichi workers faced multiple stressors (workplace trauma, victim experiences, and public criticism deriving from their company’s post-disaster management). Literatures suggest the importance of workplace interpersonal support (WIS) in enhancing psychological health among disaster workers. We sought to elucidate the role of their demographics, disaster-related experiences, and post-traumatic stress symptoms on perceived WIS.MethodsWe analyzed self-report questionnaires of 885 workers 2-3 months post-disaster. We used sociodemographic and disaster exposure-related variables and post-traumatic stress symptoms (measured by the Impact of Event Scale-Revised) as independent variables. We asked whether WIS from colleagues, supervisors, or subordinates was perceived as helpful, and used yes or no responses as a dependent variable. Logistic regression analyses were performed to assess correlates of WIS.ResultsOf the participants, one-third (34.7%) reported WIS. WIS was associated with younger age (20-28 years [vs 49-], adjusted odds ratio [aOR]: 3.25, 95% CI: 1.99-5.32), supervisory work status (aOR: 2.30, 95% CI: 1.35-3.92), and discrimination or slur experience (aOR: 1.65, 95% CI: 1.08-2.53).ConclusionsEducational programs focusing on WIS might be beneficial to promote psychological well-being among nuclear disaster workers, especially younger workers, supervisors, and workers with discrimination experiences. (Disaster Med Public Health Preparedness. 2018;12:460–463)


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