Of Disasters and Dragon Kings: A Statistical Analysis of Nuclear Power Incidents and Accidents

Abstract

We perform a statistical study of risk in nuclear energy systems. This study provides and analyzes a data set that is twice the size of the previous best data set on nuclear incidents and accidents, comparing three measures of severity: the industry standard International Nuclear Event Scale, the Nuclear Accident Magnitude Scale of radiation release, and cost in U.S. dollars. The rate of nuclear accidents with cost above 20 MM 2013 USD, per reactor per year, has decreased from the 1970s until the present time. Along the way, the rate dropped significantly after Chernobyl (April 1986) and is expected to be roughly stable around a level of 0.003, suggesting an average of just over one event per year across the current global fleet. The distribution of costs appears to have changed following the Three Mile Island major accident (March 1979). The median cost became approximately 3.5 times smaller, but an extremely heavy tail emerged, being well described by a Pareto distribution with parameter α = 0.5-0.6. For instance, the cost of the two largest events, Chernobyl and Fukushima (March 2011), is equal to nearly five times the sum of the 173 other events. We also document a significant runaway disaster regime in both radiation release and cost data, which we associate with the "dragon-king" phenomenon. Since the major accident at Fukushima (March 2011) occurred recently, we are unable to quantify an impact of the industry response to this disaster. Excluding such improvements, in terms of costs, our range of models suggests that there is presently a 50% chance that (i) a Fukushima event (or larger) occurs every 60-150 years, and (ii) that a Three Mile Island event (or larger) occurs every 10-20 years. Further-even assuming that it is no longer possible to suffer an event more costly than Chernobyl or Fukushima-the expected annual cost and its standard error bracket the cost of a new plant. This highlights the importance of improvements not only immediately following Fukushima, but also deeper improvements to effectively exclude the possibility of "dragon-king" disasters. Finally, we find that the International Nuclear Event Scale (INES) is inconsistent in terms of both cost and radiation released. To be consistent with cost data, the Chernobyl and Fukushima disasters would need to have between an INES level of 10 and 11, rather than the maximum of 7.

A civil super-Apollo project in nuclear research for a safer and prosperous world

“…This is a Damocles sword hanging over the head of large European populations for many generations. Thus, even in stable society, nuclear risk is still high [8,9]. The official industry and political position is a combination of dangerously underestimating risk, and being disingenuous about it to the public.…”

“…Supposedly impossible scenarios (according to industry-standard Probabilistic Safety Analysis risk estimates) such as Chernobyl and Fukushima [10] can be taken as the basis to imagine others, whose impact would be in the range of tens of trillions (of dollars, euros, Swiss francs, etc.) with lasting consequences in the form of major zones of uninhabitability [8,9]. Think for instance of the real-estate value of New York City, USA or of Zurich, Switzerland, both of which are rather close to an operating NPP and would become uninhabitable in exceptional and extremely unlikely -but possible -scenarios.…”

“…For all, one cannot exclude the possibility of another accident involving a partial meltdown of the reactor of a large NPP, with a significant fraction (say 5-20%) of the reactor contaminating the atmosphere, ocean and/or Earth soil. Our estimates show that just one event has global measurable consequences [8,9]. Supposedly impossible scenarios (according to industry-standard Probabilistic Safety Analysis risk estimates) such as Chernobyl and Fukushima [10] can be taken as the basis to imagine others, whose impact would be in the range of tens of trillions (of dollars, euros, Swiss francs, etc.)…”

Multiple Outlier Detection in Samples with Exponential & Pareto Tails: Redeeming the Inward Approach & Detecting Dragon Kings

“…We consider events (incidents and accidents) occurring at nuclear power plants, studied in [56]. We consider both the property damage (in US Dollars), and a logarithmic measure of the amount of radiation released called the Nuclear Accident Magnitude Scale (NAMS) [47].…”

Much ado about nothing? The rhetoric and reality of the nuclear renaissance

“…What counts is not simply whether or not nuclear power plants can be operated safely and that the nuclear industry can objectively measure and demonstrate this, but whether or not the public believe that nuclear power is safe. While the nuclear industry argues that it has an impressive safety track record when compared with other forms of fossil fuel energy generation, this argument remains contested (see, for example, Wheatley et al, 2015).…”