In July 1998, an M w = 6.2 earthquake struck the islands of Faial, Pico and San Jorge (in the Azores Archipelago), registering VIII on the Modified Mercalli Intensity scale and causing major destruction in the northeastern part of Faial. The main shock was located offshore, 8 km North East of the island, and it triggered a seismic sequence that lasted for several weeks. The existing data for this earthquake include both the general tectonic environment of the region and the teleseismic information. This is accompanied by one strong-motion record obtained 15 km from the epicentre, the epicentre location of aftershocks, and a large collection of the damage inflicted to the building stock (as poor rubble masonry, of 2-3 storeys). The present study was carried out in two steps: first, with a finite-fault stochastic simulation method of ground motion at sites throughout the affected islands, for two possible locations of the rupturing fault and for a large number of combinations of rupture mechanisms (as a parametric analysis); secondly, the damage to buildings was modelled using a well-known macroseismic method that considers the building typologies and their associated vulnerabilities. The main intent was to integrate different data (geological, seismological and building features) to produce a scenario model to reproduce and justify the level of damage generated during the Faial earthquake. Finally, through validation of the results provided by these different approaches, we obtained a complete procedure for the parameters of a first model for the production of seismic damage scenarios for the Azores Islands region.

To comply with the need to spread the culture of earthquake disaster reduction, we rely on strategies that involve education. Risk education is a long-term process that passes from knowledge, through understanding, to choices and actions thrusting preparedness and prevention, over recovery. We set up strategies for prevention that encompass child and adult education, as a bottom-up approach, from raising awareness to reducing potential effects of disruption of society. Analysis of compulsory school education in three European countries at high seismic risk, namely Portugal, Iceland and Italy, reveals that generally there are a few State-backed plans. The crucial aspects of risk education concerning natural hazards are starting age, incompleteness of textbooks, and lack of in-depth studies of the pupils upon completion of their compulsory education cycle. Hands-on tools, immersive environments, and learn-by-playing approaches are the most effective ways to raise interest in children, to provide memory imprint as a message towards a culture of safety. A video game, Treme-treme, was prepared to motivate, educate, train and communicate earthquake risk to players/pupils. The game focuses on do's and don'ts for earthquake shaking, and allows children to think about what might be useful in the case of evacuation. Education of the general public was addressed using audio-visual products strongly linked to the social, historical and cultural background of each country. Five videos tackled rising of awareness of seismic hazards in Lisbon, the area surrounding Reykjavik, Naples, and Catania, four urban areas prone to earthquake disasters.

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The analysis of the seismic attenuation is a prominent and problematic component of hazard assessment. Over the last decade it has become increasingly clear that the intrinsic uncertainty of the decay process must be expressed in probabilistic terms. This implies estimating the probability distribution of the intensity at a site I s as the combination of the distribution of the decay ∆I and of the distribution of the intensity I 0 found for the area surrounding that site. We focus here on the estimation of the distribution of ∆I. Previous studies presented in the literature show that the intensity decay in Italian territory varies greatly from one region to another, and depends on many factors, some of them not easily measurable. Assuming that the decay shows a similar behavior in function of the epicenter-site distance when the same geophysical conditions and building vulnerability characterize different macroseismic fields, we have classified some macroseismic fields drawn from the Italian felt report database by applying a clustering algorithm. Earthquakes in the same class constitute the input of a two-step procedure for the Bayesian estimation of the probability distribution of ∆I at any distance from the epicenter, conditioned on I 0 , where ∆I is considered an integer, random variable, following a binomial distribution. The scenario generated by a future earthquake is forecast either by the predictive distribution in each distance bin, or by a binomial distribution whose parameter is a continuous function of the distance. The estimated distributions have been applied to forecast the scenario actually produced by the Colfiorito earthquake on 1997/09/26; for both options the expected and observed intensities have been compared on the basis of some validation criteria. The same procedure has been repeated using the probability distribution of ∆I estimated on the basis of each class of macroseismic fields identified by the clustering algorithm.