Il recupero dei materiali di scarto è un aspetto di grande attualità in campo stradale, così come negli altri ambiti dell’ingegneria civile. L’attenzione della ricerca e degli esperti del settore è rivolta all’affinamento di tecniche di riciclaggio che riducano l’impatto ambientale senza compromettere le prestazioni meccaniche finali. Tali indagini cercano di far corrispondere le necessità di smaltimento dei rifiuti con quelle dell’industria infrastrutturale, legate al reperimento di materiali da costruzione tecnicamente idonei ed economicamente vantaggiosi. Attualmente sono già diversi i tipi di prodotti rigenerati e riutilizzati nella realizzazione delle pavimentazioni stradali e numerosi sono anche quelli di nuova introduzione in fase di sperimentazione. In particolare, accanto ai materiali derivanti dalle operazioni di recupero della rete viaria, è opportuno considerare anche quelli provenienti dall’esercizio delle attività di trasporto, il quale comporta ogni anno il raggiungimento della fine della vita utile per centinaia di migliaia di tonnellate di pneumatici di gomma. L’obiettivo della presente analisi sperimentale è quello di fornire indicazioni e informazioni in merito alla tecnica di riciclaggio a freddo con emulsione bituminosa e cemento, valutando la possibilità di applicazione di tale metodologia in combinazione con il polverino di gomma, ottenuto dal recupero degli pneumatici fuori uso (PFU). La ricerca si distingue per una duplice valenza: la prima è quella di promuovere ulteriormente la tecnica di riciclaggio a freddo, che si sta imponendo per i suoi numerosi vantaggi economici ed ambientali, legati soprattutto alla temperatura d’esercizio; la seconda è quella di sperimentare l’utilizzo del polverino di gomma, nelle due forme di granulazione tradizionale e criogenica, additivato a miscele costituite interamente da materiale proveniente da scarifica di pavimentazioni esistenti e stabilizzate con diverse percentuali di emulsione di bitume e di legante cementizio. / Waste materials reclamation is a subject of great interest in road construction as well as in all other areas of civil engineering. Research and experts attention is focused on the improvement of recycling techniques that can reduce the environmental impact without compromising the final mechanical performances. These investigations try to match the needs of waste disposal with those of infrastructural industry, linked to obtaining building materials technically appropriate and cost effective. Currently there are several types of products already reclaimed and reused in the pavements construction and there are also those newly introduced that are still involved in the testing phase. In particular, in addition to materials resulting from the pavement recycling operations, those derived from the operation of transport activities are to be considered. They include hundreds of thousands of tons of rubber tires that every year reach the end of their life. The goal of this experimental analysis is to provide references and information on the cold recycling technique with bituminous emulsion and cement, studying the possible application of this method in combination with the crumb rubber obtained from end of life tires. The research is characterized by a dual purpose: first is to further promote the technique of cold recycling which is being imposed for its numerous economic and environmental advantages, especially related to the operating temperature; the second is to experiment the use of the crumb rubber, in the two forms obtained from traditional and cryogenic mechanical shredding, added to mixtures entirely consisting of reclaimed asphalt from milling of existing pavements and stabilized with different percentages of bituminous emulsion and cement binder.

The hydrologic risk (and the hydro-geologic one, closely related to it) is, and has always been, a very relevant issue, due to the severe consequences that may be provoked by a flooding or by waters in general in terms of human and economic losses. Floods are natural phenomena, often catastrophic, and cannot be avoided, but their damages can be reduced if they are predicted sufficiently in advance. For this reason, the flood forecasting plays an essential role in the hydro-geological and hydrological risk prevention. Thanks to the development of sophisticated meteorological, hydrologic and hydraulic models, in recent decades the flood forecasting has made a significant progress, nonetheless, models are imperfect, which means that we are still left with a residual uncertainty on what will actually happen. In this thesis, this type of uncertainty is what will be discussed and analyzed. In operational problems, it is possible to affirm that the ultimate aim of forecasting systems is not to reproduce the river behavior, but this is only a means through which reducing the uncertainty associated to what will happen as a consequence of a precipitation event. In other words, the main objective is to assess whether or not preventive interventions should be adopted and which operational strategy may represent the best option. The main problem for a decision maker is to interpret model results and translate them into an effective intervention strategy. To make this possible, it is necessary to clearly define what is meant by uncertainty, since in the literature confusion is often made on this issue. Therefore, the first objective of this thesis is to clarify this concept, starting with a key question: should be the choice of the intervention strategy to adopt based on the evaluation of the model prediction based on its ability to represent the reality or on the evaluation of what actually will happen on the basis of the information given by the model forecast? Once the previous idea is made unambiguous, the other main concern of this work is to develope a tool that can provide an effective decision support, making possible doing objective and realistic risk evaluations. In particular, such tool should be able to provide an uncertainty assessment as accurate as possible. This means primarily three things: it must be able to correctly combine all the available deterministic forecasts, it must assess the probability distribution of the predicted quantity and it must quantify the flooding probability. Furthermore, given that the time to implement prevention strategies is often limited, the flooding probability will have to be linked to the time of occurrence. For this reason, it is necessary to quantify the flooding probability within a horizon time related to that required to implement the intervention strategy and it is also necessary to assess the probability of the flooding time.

Flood disasters are a major cause of fatalities and economic losses, and several studies indicate that global flood risk is currently increasing. In order to reduce and mitigate the impact of river flood disasters, the current trend is to integrate existing structural defences with non structural measures. This calls for a wider application of advanced hydraulic models for flood hazard and risk mapping, engineering design, and flood forecasting systems. Within this framework, two different hydraulic models for large scale analysis of flood events have been developed. The two models, named CA2D and IFD-GGA, adopt an integrated approach based on the diffusive shallow water equations and a simplified finite volume scheme. The models are also designed for massive code parallelization, which has a key importance in reducing run times in large scale and high-detail applications. The two models were first applied to several numerical cases, to test the reliability and accuracy of different model versions. Then, the most effective versions were applied to different real flood events and flood scenarios. The IFD-GGA model showed serious problems that prevented further applications. On the contrary, the CA2D model proved to be fast and robust, and able to reproduce 1D and 2D flow processes in terms of water depth and velocity. In most applications the accuracy of model results was good and adequate to large scale analysis. Where complex flow processes occurred local errors were observed, due to the model approximations. However, they did not compromise the correct representation of overall flow processes. In conclusion, the CA model can be a valuable tool for the simulation of a wide range of flood event types, including lowland and flash flood events.

In order to handle Natural disasters, emergency areas are often individuated over the territory, close to populated centres. In these areas, rescue services are located which respond with resources and materials for population relief. A method of automatic positioning of these centres in case of a flood or an earthquake is presented. The positioning procedure consists of two distinct parts developed by the research group of Prof Michael G. H. Bell of Imperial College, London, refined and applied to real cases at the University of Bologna under the coordination of Prof Ezio Todini. There are certain requirements that need to be observed such as the maximum number of rescue points as well as the number of people involved. Initially, the candidate points are decided according to the ones proposed by the local civil protection services. We then calculate all possible routes from each candidate rescue point to all other points, generally using the concept of the "hyperpath", namely a set of paths each one of which may be optimal. The attributes of the road network are of fundamental importance, both for the calculation of the ideal distance and eventual delays due to the event measured in travel time units. In a second phase, the distances are used to decide the optimum rescue point positions using heuristics. This second part functions by "elimination". In the beginning, all points are considered rescue centres. During every interaction we wish to delete one point and calculate the impact it creates. In each case, we delete the point that creates less impact until we reach the number of rescue centres we wish to keep.

La Comunità Europea, alla luce dei recenti eventi alluvionali occorsi nei Paesi Membri ed al progressivo aumento dei danni economici da essi provocati, ha recentemente emanato una direttiva (Direttiva Europea 2007/60/CE, Flood Directive) per la valutazione e la predisposizione di piani di gestione del rischio idraulico alluvionale. Con riferimento a tale contesto l’attività di ricerca condotta si è concentrata sulla valutazione delle potenzialità offerte dalla modellistica numerico-idraulica mono e bidimensionale quale strumento per l’attuazione della Direttiva 2007/60. Le attività sono state affrontate ponendo particolare attenzione alla valutazione dei termini di incertezza che caratterizzano l’applicazione dei modelli numerico-idraulici, esaminando i possibili effetti di tale incertezza sulla mappatura della pericolosità idraulica. In particolare, lo studio si concentra su diversi tratti fluviali del corso medio inferiore del Fiume Po e si articola in tre parti: 1) analisi dell’incertezza connessa alla definizione delle scale di deflusso in una generica sezione fluviale e valutazione dei suoi effetti sulla calibrazione dei modelli numerici quasi-bidimensionali (quasi-2D); 2) definizione di mappe probabilistiche di allagamento per tratti fluviali arginati in presenza di tre sorgenti di incertezza: incertezza nelle condizioni al contorno di monte, nelle condizioni di valle e nell’identificazione delle eventuali brecce arginali; 3) valutazione dell’applicabilità di un modello quasi-2D per la definizione, a grande scala spaziale, di strategie alternative al tradizionale rialzo dei manufatti arginali per la mitigazione del rischio alluvionale associato a eventi di piena catastrofici. Le analisi condotte, oltre ad aver definito e valutato le potenzialità di metodologie e modelli idraulici a diversa complessità, hanno evidenziato l’entità e l’impatto dei più importanti elementi d’incertezza, sottolineando come la corretta mappatura della pericolosità idraulica debba sempre essere accompagnata da una valutazione della sua incertezza. / In the light of recent catastrophic flood events and the steadily increase of economic losses associated with inundations in Europe, the European Community recently issued the Flood Directive (2007/60/EC), which requires Member States to evaluate and map flood-risk and to develop flood risk management plans. Concerning these issues, the present dissertation focuses on the development and testing of mono and quasi two-dimensional (quasi-2D) numerical hydraulic models for the implementation of Directive 2007/60. The activities are carried out paying particular attention on the evaluation of the main sources of uncertainty that characterize the application of numerical models, examining their possible effect on the flood hazard mapping. The study considers various river branches of the River Po and is structured into three main parts: 1) analysis of rating-curve uncertainty in a given river section and evaluation of its effects on the calibration of roughness coefficients for a quasi-2D, 2) flood hazard mapping for a diked river reach considering three major sources of uncertainties: uncertainties in upstream and downstream boundary conditions and uncertainties in the dike-failure location and breach morphology; 3) development and testing of a quasi-2D hydraulic model to support the large-scale identification of optimal flood-risk mitigation strategies relative to the 500-year flood. The analysis assesses the potential of methodologies and numerical-hydraulic models for flood hazard mapping and highlights the impact of the most important elements of uncertainty, pointing out how a correct flood hazard map should always be accompanied by a throughout uncertainty assessment.

Tradizionalmente, l'obiettivo della calibrazione di un modello afflussi-deflussi è sempre stato quello di ottenere un set di parametri (o una distribuzione di probabilità dei parametri) che massimizzasse l'adattamento dei dati simulati alla realtà osservata, trattando parzialmente le finalità applicative del modello. Nel lavoro di tesi viene proposta una metodologia di calibrazione che trae spunto dell'evidenza che non sempre la corrispondenza tra dati osservati e simulati rappresenti il criterio più appropriato per calibrare un modello idrologico. Ai fini applicativi infatti, può risultare maggiormente utile una miglior rappresentazione di un determinato aspetto dell'idrogramma piuttosto che un altro. Il metodo di calibrazione che viene proposto mira a valutare le prestazioni del modello stimandone l'utilità nell'applicazione prevista. Tramite l'utilizzo di opportune funzioni, ad ogni passo temporale viene valutata l'utilità della simulazione ottenuta. La calibrazione viene quindi eseguita attraverso la massimizzazione di una funzione obiettivo costituita dalla somma delle utilità stimate nei singoli passi temporali. Le analisi mostrano come attraverso l'impiego di tali funzioni obiettivo sia possibile migliorare le prestazioni del modello laddove ritenute di maggior interesse per per le finalità applicative previste. / In the majority of rainfall-runoff modelling applications, the objective function to be minimised in the parameterisation procedure is based on a measure of the goodness-of-fit that maximized the fit of the simulated data to the overall observed data, taking partially into account the specific model applications. The present dissertation focuses on the development and testing of an objective function based on the expected utility of the rainfall-runoff model. The method is based on the evidence that the performances of a hydrological model closely depend on the purpose of the application. For istance, the simulated data caught have different utility in a water resources management system or in a flood forecasting system. In the proposed method, at each time step, the comparison between simulated and observed data is carried out by using an “ad-hoc” utility function. The calibration is performed by maximizing the overall estimated utility of the simulated data. Different utility functions are tested and the results are compared against those obtained with traditional procedure. The results reveal that an adequate utility function allows an improvement of the model performances in the reproduction of the discharges considered most important to the purpose of the modeling application.

A design can be defined as context-sensitive when it achieves effective technical and functional transportation solutions, while preserving and enhancing natural environments and minimizing impacts on local communities. Traffic noise is one of the most critical environmental impacts of transportation infrastructure and it affects both humans and ecosystems. Tire/pavement noise is caused by a set of interactions at the contact patch and it is the predominant source of road noise at the regular traffic speeds. Wearing course characteristics affect tire/pavement noise through various mechanisms. Furthermore, acoustic performance of road pavements varies over time and it is influenced by both aging and temperature. Three experimentations have been carried out to evaluate wearing course characteristics effects on tire/pavement noise. The first study involves the evaluation of skid resistance, surface texture and tire/pavement noise of an innovative application of multipurpose cold-laid microsurfacing. The second one involves the evaluation of the surface and acoustic characteristics of the different pavement sections of the test track of the Centre for Pavement and Transportation Technology (CPATT) at the University of Waterloo. In the third study, a set of highway sections have been selected in Southern Ontario with various types of pavements. Noise measurements were carried out by means of the Statistical Pass-by (SPB) method in the first case study, whereas in the second and in the third one, Close-proximity (CPX) and the On-Board Sound Intensity (OBSI) methods have been performed in parallel. Test results have contributed to understand the effects of pavement materials, temperature and aging on tire/pavement noise. Negligible correlation was found between surface texture and roughness with noise. As a general trend, aged and stiffer materials have shown to provide higher noise levels than newer and less stiff ones. Noise levels were also observed to be higher with temperature increase.

The focus of the Ph.D. dissertation is on the thermal part of the energy planning issue since the space conditioning (heating and cooling – H&C) of buildings represents about 75% of the energy consumed by European residential buildings and only 16% of the heating and cooling consumption is covered by renewable energy sources (RES). At the same time, the increased complexity of the spatial planning process when energy issues are involved has made clear the need for new “energy-aware” tools and methods used in this field. The proposed methodology is GIS (Geographical Information System)-based and performed at regional scale given that the movement of energy planning activities from national to regional and local scale allows a much more detailed analysis of both the energy demand and supply, balancing them more effectively. The integration of the spatial dimension within energy analyses can also provide the decision-makers with a spatially-explicit approach towards the energy transition and the development of sustainable energy plans and strategies. The general aim of the Ph.D. thesis is to develop a Spatial Decision Support System (SDSS) allowing the decision-makers to take into account (during the planning process) both the improvement of the energy production from RES and the energy renovation of the existing building stock. The SDSS aims also to connect the energy planning (supply side) with spatial planning (demand side) by seeking synergies between the two fields. This connection is made taking advantage of the framework of the Strategic Environmental Assessment (SEA). The Ph.D. thesis is partially developed within a European co-financed project included in the Interreg Alpine Space programme. The GRETA project was designed to foster the use of shallow geothermal energy (SGE) in energy plans and strategies along the Alps. SGE is a low-carbon source for H&C of buildings, which exploits the heat stored within the ground, a local source widely available and less dependent from changes in time compared to other RES. Despite this, its exploitation is not yet diffused and its growth is limited mainly by factors such as scarce knowledge, complicated and fragmented legislation, and high installation costs. Considering all these issues, the research questions that shaped the Ph.D. activities are: ➢ How to estimate the thermal energy demand of the residential building stock at the regional scale, as a starting point for developing sustainable energy strategies aimed at the reduction of the thermal energy consumption in the existing buildings. ➢ How to integrate this appraisal in the energy planning of a region in order to elaborate different scenarios for the energy balance between thermal demand and supply, fostering the use of shallow geothermal energy (SGE) that is a renewable source still not well-known and not exploited. ➢ How to encourage the connection between energy planning and spatial planning towards the common goal of sustainable energy transition, helping to fill the gap between the development of plans and strategies and their implementation, thanks to the Strategic Environmental Assessment (SEA) framework. The proposed methodology has been applied in a case study, i.e. Valle d’Aosta, an Italian alpine region. Almost all the data processing is performed with open-source software (GRASS GIS, QGIS, Python, and R) and applying a spatially-explicit approach, for pushing the integration of the spatial dimension in the energy analysis. The spatial units of analysis are the single building and the census tract. The single building has been chosen as the smallest unit available for ensuring a better characterization of the thermal energy demand and of the potential energy production from SGE. Moreover, the scenario analysis for the energy renovation of buildings is better performed at the building level; so, it is particularly suitable for developing an SDSS. Nevertheless, some data processing is done at the census tract level, using aggregated and statistical information to estimate the required values at the building level. The reason for this twofold scale of analysis is that the data availability often changes depending on time, space and data provider. For instance, for the case study area only little data was available at the building level for the whole region. Therefore, the methodology integrates data from different sources to fill this knowledge gap. The methodology applied in the case study is divided into two parts: 1) The first one concerns the data collection and processing for the spatial estimation of the space heating demand of the existing building stock. At the end of it, the technical and economic suitability of SGE (performed within the GRETA project) for covering the energy demand of buildings and replacing some fossil fuels is evaluated. 2) The second one is carried out in the framework of SEA, by defining common objectives and developing scenarios for the integration of SGE in the energy planning process, as the short-term objective, and the coordination of energy and spatial planning goals, as the long-term objective. In the Ph.D. thesis, SEA is intended as a conceptual framework for integrating energy and spatial planning, rather than as an evaluation tool. The main outputs of the Ph.D. thesis are: (i) the spatial evaluation of the space heating demand of each residential building of the case study, without using the “archetypes approach”; (ii) the development of a method for the integration of data from different sources and for its estimation if missing at the building level; (iii) the use of SEA as a framework for connecting energy planning and spatial planning fields, to support strategic decision-making processes. Even though the Ph.D. case study is a typical alpine region, (iv) the developed methodology can be applied at different scales and not only on alpine regions but potentially in every kind of context. Since it strongly depends on the availability of data, the replicability of the methodology is quite high. The main expected impacts of these outputs are: (1) SDSS allows to reach a trade-off between the number of input data and the level of detail often required by decision-makers; (2) SDSS can support the decision-makers allowing them to analyse from various viewpoints different energy scenarios and also to localise where is better to address the energy measures; (3) the results at the building level represent a starting point for defining and developing strategies for the energy transition of settlements at different scales; (4) SEA used as a strategic tool for integrating energy and spatial planning, by coordinating strategic objectives, and linking the thesis outputs to the energy decision-making process.

The research background and motivation of this paper is related with the role of agro-tourism impact on environment. The research background and motivation of this paper is related with the role of agro-tourism impact on environment. Agro-tourism activities impact on the development of rural area represent the reasons for it is strategic support at microeconomic and macroeconomic context. In the process of developing agro-tourism, significant attention is necessary to the environment, representing the raw material of agro-tourism activity. So, the relation among agro-tourism and environment shows a particular significance. A sustainable development and protection of the environment being the required circumstances for its practice. It is necessary realizing vital changes regarding the production and consumption of goods and services. In order to preserve our One Planet while taking into consideration economic and social aspects. Research suggests that agro-tourism sector it is a growing sector. Therefore, the link from agro-tourism and sustainable development are claiming the identification of new models by making the development more sustainable. So, this thesis proposes the approach of the influence of circular economy on the sustainable development of agro-tourism. To introduce the notion of circular economy in agro-tourism it necessary to establish and apply a sustainable development for agro-tourism structures activities. Adopting a new exemplary of management starts up with promoting new intentions related to production, consumption, ethics, etc. Circular economy in agro-tourism can lead to a sustainable use of resources for the present and future generations and accomplish sustainable development in this domain. The present research is a contribution, by questioning present issues and future potentialities, suggest ways in which agro-tourism can embrace a sustainable development with the influence of circular economy. Highlighting to focus agro-tourism structures concerning optimizing the environment by delivering major benefits for local communities and for the economy of Europe.

This dissertation focuses on the assessment of projected changes on water resources by the end of this century (2071-2100), considering an ensemble of high resolution future climate scenarios, the effects of hydrological parameterisation, and the bias of the hydrological model in representing different streamflow magnitudes. Quantification of the impacts of climate change on water resources will depend on the emission scenario, climate model, downscaling technique and impact model used to drive the impact study. In particular, hydrological impact studies involve important decisions (e.g., model structure, parameterisation, input data) whose effects are reflected into the final impacts. As a result, quantification of impacts of climate change have to be seen as a "cascade of uncertainty", in which decisions taken in every step of the assessment process convey uncertainties that are unavoidably propagated to subsequent levels. At the other hand, uncertainties in projections of climate models and those involved in the quantification of their hydrological response limit the understanding of those future impacts and hamper the assessment of mitigation policies. The Soil and Water Assessment Tool (SWAT) hydrological model was set up for daily simulations of the western part of the Ebro River basin (~ 42000 km2) in Spain, during the control period 01/Jan/1961 to 31/Dec/1990, and two subcatchments were selected for testing the methodology proposed in this dissertation. A sensitivity analysis with Latin Hypercube One-factor-At-a-Time (LH-OAT) was carried out in order to identify parameters with a high effect on simulated streamflows. Then, an uncertainty analysis was carried out using the Generalized Likelihood Uncertainty Estimation (GLUE) methodology, in order to select parameter sets that can be considered as acceptable simulators of the system, adopting a re-scaled Nash-Sutcliffe efficiency as "less formal" likelihood, and a cut-off threshold equal to zero to discriminate between behavioural and non-behavioural simulators. Afterwards, a Latin Hypercube (LH) sampling strategy was implemented within GLUE, in order to reduce the number of model runs required to obtain a good exploration of the parameter space. The 95% of the cumulative distribution of each predicted output, weighted by the re-scaled likelihood of each behavioural parameter set, was used to compute the predictive uncertainty bounds, both during the control and future scenarios. Bias-corrected daily time series of precipitation and air temperature, for the future period 2071-2100, were derived from an ensemble of six high-resolution climate change scenarios, selected from the EU FP5 PRUDENCE project. Long-term averages of precipitation and air temperature fields were computed for the control period, and projected anomalies for the future scenarios were computed as well, in an annual, seasonal and monthly basis, including expected changes for different elevation bands within the basin. The same bias-corrected time series were then used to drive daily hydrological simulations during the future period on the two selected catchments. For each climate scenario, a number of simulations equal to the number of behavioural parameter sets obtained during the uncertainty analysis was carried out. Resulting streamflows were used to compute daily flow duration curves (FDCs) to provide a qualitative assessment of the relative importance of uncertainties coming from the choice of the driving RCM and from hydrological parameterisation. In addition, streamflows derived from running each climate scenario with its corresponding behavioural parameter sets, were used to compute empirical cumulative density functions (ECDFs) of three selected percentiles, representing different flow magnitudes, in order to provide a quantitative assessment of the projected changes in streamflows. We observed that the hydrological parametric uncertainty was larger than the uncertainty coming from the driving RCM, during the complete future period and each one of the four seasons, for the two selected catchments. However, this result can not be generalised, because it is conditional to decisions taken during the uncertainty analysis and to the ensemble of RCMs considered. Empirical CDFs computed for projected values of low (Q5), medium (Q50) and high (Q95) flows show that there is a general projected decrease in all the streamflow magnitudes, but bias in the representation of the streamflows during the control period 1961-1990 hamper the assessment of reliable quantitative projections for low and medium flows, whereas projected decreases for high flows range from 0 to 60%, depending on the catchment and the climate scenario considered.