Development of a relationship between physical parameters of tsunami waves and tsunami intensity based on macroscopic effects and its application to the Italian tsunami database

Tsunamis are rare events. However, their impact can be devastating and it may extend to large geographical areas. For low-probability high-impact events like tsunamis, it is crucial to implement all possible actions to mitigate the risk. The tsunami hazard assessment is the result of a scientific process that integrates traditional geological methods, numerical modelling and the analysis of tsunami sources and historical records. For this reason, analysing past events and understanding how they interacted with the land is the only way to inform tsunami source and propagation models, and quantitatively test forecast models like hazard analyses. The primary objective of this thesis is to establish an explicit relationship between the macroscopic intensity, derived from historical descriptions, and the quantitative physical parameters measuring tsunami waves. This is done first by defining an approximate estimation method based on a simplified 1D physical onshore propagation model to convert the available observations into one reference physical metric. Wave height at the coast was chosen as the reference due to its stability and independence of inland effects. This method was then implemented for a set of well-known past events to build a homogeneous dataset with both macroseismic intensity and wave height. By performing an orthogonal regression, a direct and invertible empirical relationship could be established between the two parameters, accounting for their relevant uncertainties. The target relationship is extensively tested and finally applied to the Italian Tsunami Effect Database (ITED), providing a homogeneous estimation of the wave height for all existing tsunami observations in Italy. This provides the opportunity for meaningful comparison for models and simulations, as well as quantitatively testing tsunami hazard models for the Italian coasts and informing tsunami risk management initiatives.

Supported metal nanoparticles for sustainable green catalytic processes

Preformed Au nanoparticles supported on activated carbon and TiO2 were synthesised by sol-immobilisation. Polyethylene glycol, polyvinyl pyrrolidone and polyvinyl alcohol were used as stabilisers for the gold nanoparticles at different polymer/Au wt/wt ratios for each polymer. The effect of polymer/Au wt/wt ratios was investigated on (i) the average nanoparticle size, (ii) catalytic activity for two reactions, 4-nitrophenol reduction and glucose oxidation to glucaric acid. 4-nitrophenol reduction is recognised as a model reaction for nanomaterial catalytic activity tests; glucose oxidation to glucaric acid is a reaction that is traditionally carried out with concentrated nitric acid, for which alternative reaction pathways are looked for in an effort to reduce its environmental impact. The catalysts were characterised from the nanoparticle synthesis by colloidal method by means of UV-vis spectroscopy and DLS analysis, to the immobilisation step by XRD and TEM. The effect of the polymer:Au wt/wt ratio on nanoparticle size depends on the polymer nature, and point out the need to optimise supported nanoparticle synthesis protocols in the future depending on the type of stabiliser. The catalytic tests revealed that the polymers interact with Au nanoparticles through different active sites. Activated carbon (AC) and TiO2 were compared as supports for Au nanoparticles stabilised by PVA at PVA/Au 0,65 wt/wt. AC-supported Au NPs were the most active for glucose oxidation while TiO2-stabilised Au NPs were five times more active in 4-nitrophenol reduction that AC-supported NPs. Hence support and stabiliser are important parameters that should be optimised in order to achieve high catalytic activity for a given reaction.