Satellite and in situ data integrated analysis to study the upper ocean an coastal environment of the Italian seas

The thesis objectives are to develop new methodologies for study of the space and time variability of Italian upper ocean ecosystem through the combined use of multi-sensors satellite data and in situ observations and to identify the capability and limits of remote sensing observations to monitor the marine state at short and long time scales. Three oceanographic basins have been selected and subjected to different types of analyses. The first region is the Tyrrhenian Sea where a comparative analysis of altimetry and lagrangian measurements was carried out to study the surface circulation. The results allowed to deepen the knowledge of the Tyrrhenian Sea surface dynamics and its variability and to defined the limitations of satellite altimetry measurements to detect small scale marine circulation features. Channel of Sicily study aimed to identify the spatial-temporal variability of phytoplankton biomass and to understand the impact of the upper ocean circulation on the marine ecosystem. An combined analysis of the satellite of long term time series of chlorophyll, Sea Surface Temperature and Sea Level field data was applied. The results allowed to identify the key role of the Atlantic water inflow in modulating the seasonal variability of the phytoplankton biomass in the region. Finally, Italian coastal marine system was studied with the objective to explore the potential capability of Ocean Color data in detecting chlorophyll trend in coastal areas. The most appropriated methodology to detect long term environmental changes was defined through intercomparison of chlorophyll trends detected by in situ and satellite. Then, Italian coastal areas subject to eutrophication problems were identified. This work has demonstrated that satellites data constitute an unique opportunity to define the features and forcing influencing the upper ocean ecosystems dynamics and can be used also to monitor environmental variables capable of influencing phytoplankton productivity.

Assessing Household Food Waste in Italy: A Methodology for Detecting Drivers and Quantities

It has been estimated that one third of edible food destined for human consumption is lost or wasted along the food supply chain globally. Much of the waste comes from Global North, where consumers are considered as the bigger contributors. Different studies tried to analyze and estimate the Household Food Waste (HFW), especially in UK and Northern Europe. The result is that accurate studies at national level exist only in UK, Finland and Norway while no such studies are available in Italy, except for survey- based researches. Though, there is a widespread awareness that such methods might be not able to estimate Food Waste. Results emerging from literature clearly suggest that survey estimate inferior amounts of Food Waste as a result, if compared to waste sorting and weighting analysis or to diary studies. The hypothesis that household food waste is under-estimated when gathered through questionnaires has been enquired into. First, a literature review of behavioral economics and heuristics has been proposed; then, a literature review of the sector listing the existing methodologies to gather national data on Household Food Waste has been illustrated. Finally, a pilot experiment to test a mixed methodology is proposed. While literature suggests that four specific cognitive biases might be able to affect the reliability of answers in questionnaires, results of the present experiment clearly indicate that there is a relevant difference between how much the individual thinks to waste and he/she actually does. The result is a mixed methodology based on questionnaire, diary and waste sorting, able to overcome the cons of each single method.

Early Warning For Large Earthquakes: Observations, Models and Real-Time Data Analysis

This thesis is a collection of works focused on the topic of Earthquake Early Warning, with a special attention to large magnitude events. The topic is addressed from different points of view and the structure of the thesis reflects the variety of the aspects which have been analyzed. The first part is dedicated to the giant, 2011 Tohoku-Oki earthquake. The main features of the rupture process are first discussed. The earthquake is then used as a case study to test the feasibility Early Warning methodologies for very large events. Limitations of the standard approaches for large events arise in this chapter. The difficulties are related to the real-time magnitude estimate from the first few seconds of recorded signal. An evolutionary strategy for the real-time magnitude estimate is proposed and applied to the single Tohoku-Oki earthquake. In the second part of the thesis a larger number of earthquakes is analyzed, including small, moderate and large events. Starting from the measurement of two Early Warning parameters, the behavior of small and large earthquakes in the initial portion of recorded signals is investigated. The aim is to understand whether small and large earthquakes can be distinguished from the initial stage of their rupture process. A physical model and a plausible interpretation to justify the observations are proposed. The third part of the thesis is focused on practical, real-time approaches for the rapid identification of the potentially damaged zone during a seismic event. Two different approaches for the rapid prediction of the damage area are proposed and tested. The first one is a threshold-based method which uses traditional seismic data. Then an innovative approach using continuous, GPS data is explored. Both strategies improve the prediction of large scale effects of strong earthquakes.