7 resultados para disaster risk reduction

em AMS Tesi di Dottorato - Alm@DL - Università di Bologna


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Climate-change related impacts, notably coastal erosion, inundation and flooding from sea level rise and storms, will increase in the coming decades enhancing the risks for coastal populations. Further recourse to coastal armoring and other engineered defenses to address risk reduction will exacerbate threats to coastal ecosystems. Alternatively, protection services provided by healthy ecosystems is emerging as a key element in climate adaptation and disaster risk management. I examined two distinct approaches to coastal defense on the base of their ecological and ecosystem conservation values. First, I analyzed the role of coastal ecosystems in providing services for hazard risk reduction. The value in wave attenuation of coral reefs was quantitatively demonstrated using a meta-analysis approach. Results indicate that coral reefs can provide wave attenuation comparable to hard engineering artificial defenses and at lower costs. Conservation and restoration of existing coral reefs are cost-effective management options for disaster risk reduction. Second, I evaluated the possibility to enhance the ecological value of artificial coastal defense structures (CDS) as habitats for marine communities. I documented the suitability of CDS to support native, ecologically relevant, habitat-forming canopy algae exploring the feasibility of enhancing CDS ecological value by promoting the growth of desired species. Juveniles of Cystoseira barbata can be successfully transplanted at both natural and artificial habitats and not affected by lack of surrounding adult algal individuals nor by substratum orientation. Transplantation success was limited by biotic disturbance from macrograzers on CDS compared to natural habitats. Future work should explore the reasons behind the different ecological functioning of artificial and natural habitats unraveling the factors and mechanisms that cause it. The comprehension of the functioning of systems associated with artificial habitats is the key to allow environmental managers to identify proper mitigation options and to forecast the impact of alternative coastal development plans.

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Coastal flooding poses serious threats to coastal areas around the world, billions of dollars in damage to property and infrastructure, and threatens the lives of millions of people. Therefore, disaster management and risk assessment aims at detecting vulnerability and capacities in order to reduce coastal flood disaster risk. In particular, non-specialized researchers, emergency management personnel, and land use planners require an accurate, inexpensive method to determine and map risk associated with storm surge events and long-term sea level rise associated with climate change. This study contributes to the spatially evaluation and mapping of social-economic-environmental vulnerability and risk at sub-national scale through the development of appropriate tools and methods successfully embedded in a Web-GIS Decision Support System. A new set of raster-based models were studied and developed in order to be easily implemented in the Web-GIS framework with the purpose to quickly assess and map flood hazards characteristics, damage and vulnerability in a Multi-criteria approach. The Web-GIS DSS is developed recurring to open source software and programming language and its main peculiarity is to be available and usable by coastal managers and land use planners without requiring high scientific background in hydraulic engineering. The effectiveness of the system in the coastal risk assessment is evaluated trough its application to a real case study.

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La tesi affronta il concetto di esposizione al rischio occupazionale e il suo scopo è quello di indagare l’ambiente di lavoro e il comportamento dei lavoratori, con l'obiettivo di ridurre il tasso di incidenza degli infortuni sul lavoro ed eseguire la riduzione dei rischi. In primo luogo, è proposta una nuova metodologia denominata MIMOSA (Methodology for the Implementation and Monitoring of Occupational SAfety), che quantifica il livello di "salute e sicurezza" di una qualsiasi impresa. Al fine di raggiungere l’obiettivo si è reso necessario un approccio multidisciplinare in cui concetti d’ingegneria e di psicologia sono stati combinati per sviluppare una metodologia di previsione degli incidenti e di miglioramento della sicurezza sul lavoro. I risultati della sperimentazione di MIMOSA hanno spinto all'uso della Logica Fuzzy nel settore della sicurezza occupazionale per migliorare la metodologia stessa e per superare i problemi riscontrati nell’incertezza della raccolta dei dati. La letteratura mostra che i fattori umani, la percezione del rischio e il comportamento dei lavoratori in relazione al rischio percepito, hanno un ruolo molto importante nella comparsa degli incidenti. Questa considerazione ha portato ad un nuovo approccio e ad una seconda metodologia che consiste nella prevenzione di incidenti, non solo sulla base dell'analisi delle loro dinamiche passate. Infatti la metodologia considera la valutazione di un indice basato sui comportamenti proattivi dei lavoratori e sui danni potenziali degli eventi incidentali evitati. L'innovazione consiste nell'applicazione della Logica Fuzzy per tener conto dell’"indeterminatezza" del comportamento umano e del suo linguaggio naturale. In particolare l’applicazione è incentrata sulla proattività dei lavoratori e si prefigge di impedire l'evento "infortunio", grazie alla generazione di una sorta d’indicatore di anticipo. Questa procedura è stata testata su un’azienda petrolchimica italiana.

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This work presents a comprehensive methodology for the reduction of analytical or numerical stochastic models characterized by uncertain input parameters or boundary conditions. The technique, based on the Polynomial Chaos Expansion (PCE) theory, represents a versatile solution to solve direct or inverse problems related to propagation of uncertainty. The potentiality of the methodology is assessed investigating different applicative contexts related to groundwater flow and transport scenarios, such as global sensitivity analysis, risk analysis and model calibration. This is achieved by implementing a numerical code, developed in the MATLAB environment, presented here in its main features and tested with literature examples. The procedure has been conceived under flexibility and efficiency criteria in order to ensure its adaptability to different fields of engineering; it has been applied to different case studies related to flow and transport in porous media. Each application is associated with innovative elements such as (i) new analytical formulations describing motion and displacement of non-Newtonian fluids in porous media, (ii) application of global sensitivity analysis to a high-complexity numerical model inspired by a real case of risk of radionuclide migration in the subsurface environment, and (iii) development of a novel sensitivity-based strategy for parameter calibration and experiment design in laboratory scale tracer transport.

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Background. A sizable group of patients with symptomatic aortic stenosis (AS) can undergo neither surgical aortic valve replacement (AVR) nor transcatheter aortic valve implantation (TAVI) because of clinical contraindications. The aim of this study was to assess the potential role of balloon aortic valvuloplasty (BAV) as a “bridge-to-decision” in selected patients with severe AS and potentially reversible contraindications to definitive treatment. Methods. We retrospectively enrolled 645 patients who underwent first BAV at our Institution between July 2007 and December 2012. Of these, the 202 patients (31.2%) who underwent BAV as bridge-to-decision (BTD) requiring clinical re-evaluation represented our study population. BTD patients were further subdivided in 5 groups: low left ventricular ejection fraction; mitral regurgitation grade ≥3; frailty; hemodynamic instability; comorbidity. The main objective of the study was to evaluate how BAV influenced the final treatment strategy in the whole BTD group and in its single specific subgroups. Results. Mean logistic EuroSCORE was 23.5±15.3%, mean age was 81±7 years. Mean transaortic gradient decreased from 47±17 mmHg to 33±14 mmHg. Of the 193 patients with BTD-BAV who received a second heart team evaluation, 72.5% were finally deemed eligible for definitive treatment (25.4%for AVR; 47.2% for TAVI): respectively, 96.7% of patients with left ventricular ejection fraction recovery; 70.5% of patients with mitral regurgitation reduction; 75.7% of patients who underwent BAV in clinical hemodynamic instability; 69.2% of frail patients and 68% of patients who presented relevant comorbidities. 27.5% of the study population was deemed ineligible for definitive treatment and treated with standard therapy/repeated BAV. In-hospital mortality was 4.5%, cerebrovascular accident occurred in 1% and overall vascular complications were 4% (0.5% major; 3.5% minor). Conclusions. Balloon aortic valvuloplasty should be considered as bridge-to-decision in high-risk patients with severe aortic stenosis who cannot be immediate candidates for definitive percutaneous or surgical treatment.

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This work is focused on the study of saltwater intrusion in coastal aquifers, and in particular on the realization of conceptual schemes to evaluate the risk associated with it. Saltwater intrusion depends on different natural and anthropic factors, both presenting a strong aleatory behaviour, that should be considered for an optimal management of the territory and water resources. Given the uncertainty of problem parameters, the risk associated with salinization needs to be cast in a probabilistic framework. On the basis of a widely adopted sharp interface formulation, key hydrogeological problem parameters are modeled as random variables, and global sensitivity analysis is used to determine their influence on the position of saltwater interface. The analyses presented in this work rely on an efficient model reduction technique, based on Polynomial Chaos Expansion, able to combine the best description of the model without great computational burden. When the assumptions of classical analytical models are not respected, and this occurs several times in the applications to real cases of study, as in the area analyzed in the present work, one can adopt data-driven techniques, based on the analysis of the data characterizing the system under study. It follows that a model can be defined on the basis of connections between the system state variables, with only a limited number of assumptions about the "physical" behaviour of the system.

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Over the last decades the impact of natural disasters to the global environment is becoming more and more severe. The number of disasters has dramatically increased, as well as the cost to the global economy and the number of people affected. Among the natural disaster, flood catastrophes are considered to be the most costly, devastating, broad extent and frequent, because of the tremendous fatalities, injuries, property damage, economic and social disruption they cause to the humankind. In the last thirty years, the World has suffered from severe flooding and the huge impact of floods has caused hundreds of thousands of deaths, destruction of infrastructures, disruption of economic activity and the loss of property for worth billions of dollars. In this context, satellite remote sensing, along with Geographic Information Systems (GIS), has become a key tool in flood risk management analysis. Remote sensing for supporting various aspects of flood risk management was investigated in the present thesis. In particular, the research focused on the use of satellite images for flood mapping and monitoring, damage assessment and risk assessment. The contribution of satellite remote sensing for the delineation of flood prone zones, the identification of damaged areas and the development of hazard maps was explored referring to selected cases of study.