Regional groundwater vulnerability maps that indicate the impact of leaching uncertainties, should be accompanied by maps expressing the probability of surpassing that index value. This case study presents first steps in a methodology for developing such an index and the probability of its value. Regionalization of piezometric data provided an estimate of the lacking water table depth at soil profiles. Monte‐Carlo simulations of pesticide fate on these soil profiles produced local distributions of a groundwater vulnerability index. Soil hydraulic properties were randomly generated using pedotransfer functions and experimental probability density functions of particle‐ size distribution and organic matter content. Medians of locally simulated distributions were then mapped to show the spatial distribution of groundwater vulnerability. It appeared that the resulting groundwater vulnerability map might be significantly affected by soil spatial variability, although soils are quite similar throughout the area. Deciles of the locally simulated distributions seem to show intrinsic coregionalization. This property could be used to build, over the whole area, an estimated groundwater vulnerability index distribution.

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A global dataset of refinery accidents for the years 1990-2016 was analyzed to evaluate the capacity of 16 attributes to differentiate between accidents that cause or not fatalities. For this purpose a Dominance-based Rough Set Approach (DRSA) analysis was carried out. The quality of approximation and accuracy measures confirmed that the established information table is able to distinguish outcome levels in terms of fatalities. Furthermore, the suitability of the extracted rules to describe hidden relationships in the accident dataset was demonstrated. Although, the predictive capacity of the decision rules was not satisfactory, the rules still proved to be useful to identify the attributes that contribute most to assign an accident to the correct outcome class. In summary, this study provided a number of new and substantial insights on worldwide refinery accidents, which complement and extend previous findings for accident frequencies and associated trends as well as different types of consequences. period (Otway and Pahner, 1976). In 1975, the US Reactor Safety Study (WASH-1400) marked a major milestone in probabilistic risk assessment (US NRC, 1975), and subsequently spread to other disciplines and countries (Rasmussen, 1981). The need for systematic and consistent, comparative risk assessment of energy technologies has been recognized since the 1980s (Fritzsche, 1989, Inhaber, 1979). Since then, it became a central element both in the comprehensive evaluation of the risk performance of energy technologies (Burgherr and Hirschberg, 2014), and in the broader context of sustainability assessment (Cinelli et al., 2014, Hirschberg and Burgherr, 2015, Santoyo-Castelazo and Azapagic, 2014). Recently, an increased interest can be observed to assess the frequencies and consequences of accidents overtime , and to compare them among energy chains, chain stages, activities and