**4. Conclusions**

The protection of Critical Infrastructures against extreme natural hazards by evaluating and improving their resilience is one of the main goals for many countries or groups of countries (like the EU). For this reason, methodologies able to quantify the possible criticalities of these infrastructures are needed to better plan and implement actions, countermeasures and investments allowing to limit or avoid the negative energy, social and economic consequences deriving from natural hazards impacts.

With respect to other studies available in the scientific literature, the approach proposed in this paper focuses on energy corridors and aims at defining a criticality index, which is a function of the spatial position along the analysed corridor, and so it is useful to quantify the criticality level for each section of the considered infrastructure. This index is able to take into account a large variety of parameters (related to the natural event, to the corridor, to the availability of alternative sources and to the involved users) and their interdependencies. The developed methodology can be an effective supporting tool for decision makers and public administrations, for companies that have to manage crucial infrastructures for energy commodities transport and for the civil protection, as it allows – through a simple mathematical formulation – to identify the sections of an energy corridor that are critical with respect to a specific natural hazard or that are close to a criticality status, thus defining priority areas of intervention, preventive investments, mitigation actions and *ad hoc* countermeasures.

The introduced criticality index assesses in a numerical way the socio-economic damage (measured in monetary units) due to the effects of an extreme natural event on the selected infrastructure and can be used to evaluate the maximum acceptable frequency and the corresponding intensity of the event itself, allowing a comparison with the design condition of the corridor.

Furthermore, the possibility to evaluate the criticality index also for negative damage values (i.e. for not critical configurations) permits to measure the distance from the criticality, allowing to pay preventive attention to those sections that are closer to critical situations.

In general, the described approach gives the opportunity of ranking the single branches of a corridor according to their criticality and for all the different natural hazards, and, as a consequence, it gives the authorities in charge of protecting critical infrastructures the opportunity of prioritising the interventions.

The implementation of this methodology on real cases requires specialists from different fields and complex information. This can be deduced also from the application to a simplified case study (considering one corridor and two extreme events). However, the case study has underlined the advantages of the procedure, especially if a reassessment of risk acceptability limit is introduced, because it puts into evidence the safety margin with respect to the design conditions or the need for performing structural tests, quantifying the infrastructure resilience.

Additional aspects should be deeply analysed in the case of an extensive application of the proposed methodology, including – in particular – the availability of complete and homogenous technological and environmental databases and the proper definition of the system boundaries that could be not trivial in the case of meshed networks like the natural gas distribution ones.

*Resilience of Critical Infrastructures: A Risk Assessment Methodology for Energy Corridors DOI: http://dx.doi.org/10.5772/intechopen.94755*

Further studies could also be devoted to the analysis of multi-risk scenarios, i.e. to the concurrent occurrence of two or more extreme natural events, defining suitable strategies to allocate the acceptable risk (for instance by taking into account the safety margins of the infrastructure, if they are present), in order to test the infrastructure resilience in the worst (and low-frequency) conceivable conditions.
