Ian Waddington

The paper applies the J-value to the example of a long-term protection system on a notional major-hazard process plant, where a severe accident would otherwise pose a risk of death to the general public either immediately or in the short term. Equations are developed for the improvement in life expectancy produced by averting such an industrial hazard over a prolonged period. The opportunity is taken to review the developments in the J-value that have taken place over the last 12 years.

The policies of population relocation put in train following the severe nuclear reactor accidents at Chernobyl in 1986 and Fukushima Daiichi in 2011 are examined using the Judgement- or J-value. The study concludes that only between 9% and 22% of the 335,000 people finally relocated after Chernobyl were justifiable, based on the J-value and the data available. Similarly, the J-value does not support the relocation of the 160,000 people moved out on a long-term basis after the Fukushima Daiichi… Show more

The policies of population relocation put in train following the severe nuclear reactor accidents at Chernobyl in 1986 and Fukushima Daiichi in 2011 are examined using the Judgement- or J-value. The study concludes that only between 9% and 22% of the 335,000 people finally relocated after Chernobyl were justifiable, based on the J-value and the data available. Similarly, the J-value does not support the relocation of the 160,000 people moved out on a long-term basis after the Fukushima Daiichi nuclear accident. Show less

Actions set in train shortly after the accidents at Chernobyl (1986), and Fukushima Daiichi (2011) had the aim of reducing the more immediate health effects on people living near the plants. The J-value method of risk assessment has been used to judge the cost-effectiveness of a range of agricultural and urban remediation actions. Many remedial measures instituted after the Chernobyl and Fukushima Daiichi accidents have been found to be highly cost-effective.

Following the accident at the Chernobyl Nuclear Power Plant in 1986, the United Kingdom Government imposed restrictions on the consumption of sheep meat that became contaminated by nuclear fallout to ensure it was extremely unlikely that any consumers would receive an unacceptable dose. An analysis using the J-value framework is made of the cost effectiveness of the sheep meat restrictions in force until 2012. The paper shows that the risk to the general population was very low indeed at the… Show more

Following the accident at the Chernobyl Nuclear Power Plant in 1986, the United Kingdom Government imposed restrictions on the consumption of sheep meat that became contaminated by nuclear fallout to ensure it was extremely unlikely that any consumers would receive an unacceptable dose. An analysis using the J-value framework is made of the cost effectiveness of the sheep meat restrictions in force until 2012. The paper shows that the risk to the general population was very low indeed at the time the restrictions were removed in 2012 and could almost certainly have been ended earlier. Show less

A model of human decision making based on the J-value is able to explain the shape of the Preston curve that relates life expectancy at birth and gross domestic product (GDP) per head for all the nations in the world. The model was tested against pan-national data, showing a very good match. Thus the shape of the Preston curve has been explained and, at the same time, validation has been provided for the J-value model.

Utility theory can be used to model the decision process involved in evaluating the cost-effectiveness of systems that protect against a risk to assets. A key variable in the model is the coefficient of relative risk aversion (or simply “risk-aversion”) which reflects the decision maker's reluctance to invest in such safety systems. By considering a full range of accident probabilities, costs of the safety system and potential loss of assets, an average risk-aversion can be calculated from… Show more

Utility theory can be used to model the decision process involved in evaluating the cost-effectiveness of systems that protect against a risk to assets. A key variable in the model is the coefficient of relative risk aversion (or simply “risk-aversion”) which reflects the decision maker's reluctance to invest in such safety systems. By considering a full range of accident probabilities, costs of the safety system and potential loss of assets, an average risk-aversion can be calculated from the model. This paper presents the numerical and computational techniques employed in performing these calculations. Show less