Tesis sobre el tema "Regional analysi"

Le deformazioni lente di versante in roccia (DGPV e grandi frane) sono fenomeni diffusi che interessano interi versanti e mobilizzano volumi di roccia anche di miliardi di metri cubi. La loro evoluzione è legata a processi di rottura progressiva sotto forzanti esterne e di accoppiamento idromeccanico, rispecchiate da un complesso processo di creep. Sebbene caratterizzate da bassi tassi di spostamento (fino a pochi cm / anno), queste instabilità di versante danneggiano infrastrutture e ospitano settori potenzialmente soggetti a differenziazione e collasso catastrofico. È quindi necessaria una robusta caratterizzazione del loro stile di attività per determinare il potenziale impatto sugli elementi a rischio e anticipare un eventuale collasso. Tuttavia una metodologia di analisi finalizzata a questo scopo è ancora mancante. In questa prospettiva, abbiamo sviluppato un approccio multiscala che integra dati morfostrutturali, di terreno e tecniche DInSAR, applicandoli allo studio di un inventario di 208 deformazioni lente di versanti mappate in Lombardia. Su questo dataset abbiamo eseguito una mappatura geomorfologica e morfostrutturale di semi dettaglio tramite immagini aeree e DEM. Abbiamo quindi sviluppato un pacchetto di procedure oggettive per lo screening su scala di inventario delle deformazioni lente di versante integrando dati di velocità di spostamento, cinematica e di danneggiamento dell’ammasso roccioso per ogni frana. Utilizzando dataset PS-InSAR e SqueeSAR, abbiamo sviluppato una procedura mirata a identificare in maniera semiautomatica la velocità InSAR rappresentativa, il grado di segmentazione e l'eterogeneità interna di ogni frana mappata identificando la presenza di possibili fenomeni secondari. Utilizzando la tecnica 2DInSAR e tecniche di machine learning, abbiamo inoltre sviluppato un approccio automatico caratterizzare la cinematica di ciascuna frana. I dati così ottenuti sono stati integrati tramite analisi di PCA e K-medoid per identificare gruppi di frane caratterizzati da stili di attività simili. Partendo dai risultati della classificazione su scala regionale, ci siamo poi concentrati su 3 casi di studio emblematici, le DGPV di Corna Rossa, Mt. Mater e Saline, rappresentativi di problematiche tipiche delle grandi frane (segmentazione spaziale, attività eterogenea, sensibilità alle forzanti idrologiche). Applicando un approccio DInSAR mirato abbiamo indagato la risposta del versante a diverse baseline temporali per evidenziare le eterogeneità spaziali e, tramite un nuovo approccio di stacking su basline temporali lunghe abbiamo estrattoi segnali di spostamento permanenti ed evidenziato i settori e le strutture con evoluzione differenziale. Lo stesso approccio DInSAR è stato utilizzato per studiare la sensibilità delle deformazioni lente di versante alle forzanti idrologiche. Il confronto tra i tassi di spostamento stagionale e le serie temporali di precipitazioni e scioglimento neve per il monte. Mater e Saline hanno delineato complessi trend di spostamento stagionale. Queste tendenze, più evidenti per i settori più superficiali, evidenziano una risposta maggiore a periodi prolungati di precipitazione modulati dagli effetti dello scioglimento della neve. Ciò suggerisce che le DGPV, spesso considerate non influenzate dalla forzante climatica a breve termine (pluriennale), sono sensibili a input idrologici, con implicazioni chiave nell'interpretazione del loro fallimento progressivo. I nostri risultati hanno dimostrato l'efficacia della metodologia multi-scala proposta, che sfrutta i prodotti DInSAR e l'analisi mirata per identificare, classificare e caratterizzare l'attività delle deformazioni lente di versante includendo dati geologici in tutte le fasi dell'analisi. Il nostro approccio, è applicabile a diversi contesti e dataset e fornisce gli strumenti per indagare processi chiave in uno studio finalizzato alla definizione del rischio connesso alle deformazioni lente di versante.
Slow rock slope deformations (DSGSDs and large landslides) are widespread, affect entire hillslopes and displace volumes up to billions of cubic meters. They evolve over long time by progressive failure processes, under variable climatic and hydro-mechanical coupling conditions mirrored by a complex creep behaviour. Although characterized by low displacement rates (up to few cm/yr), these slope instabilities damage sensitive structures and host nested sectors potentially undergoing rockslide differentiation and collapse. A robust characterization of the style of activity of slow rock slope deformations is required to predict their interaction with elements at risk and anticipate possible failure, yet a comprehensive methodology to this aim is still lacking. In this perspective, we developed a multi-scale methodology integrating geomorphological mapping, field data and different DInSAR techniques, using an inventory of 208 slow rock slope deformations in Lombardia (Italian Central Alps), for which we performed a geomorphological and morpho-structural mapping on aerial images and DEMs. On the regional scale, we developed an objective workflow for the inventory-scale screening of slow-moving landslides. The approach is based on a refined definition of activity that integrates the displacement rate, kinematics and degree of internal damage for each landslide. Using PS-InSAR and SqueeSAR datasets, we developed an original peak analysis of InSAR displacement rates to characterize the degree of segmentation and heterogeneity of mapped phenomena, highlight the occurrence of sectors with differential activity and derive their characteristic displacement rates. Using 2DInSAR velocity decomposition and machine learning classification, we set up an original automatic approach to characterize the kinematics of each landslides. Then, we sequentially combine PCA and K-medoid cluster analysis to identify groups of landslides characterized by consistent styles of activity, accounting for all the relevant aspects including velocity, kinematics, segmentation, and internal damage. Starting from the results of regional-scale classification, we focused on the Corna Rossa, Mt. Mater and Saline DSGSDs, that are emblematic case studies on which apply DInSAR analysis to investigate typical issues in large landslide studies (spatial segmentation, heterogenous activity, sensitivity to hydrological triggers). We applied a targeted DInSAR technique on multiple temporal baselines to unravel the spatial heterogeneities of complex DSGSDs and through a novel stacking approach on raw long temporal baseline interferograms, we outlined the permanent displacement signals and sectors with differential evolution as well as individual active structures. We then used DInSAR to investigate the possible sensitivity of slow rock slope deformations to hydrological triggers. Comparison between seasonal displacement rates, derived by interferograms with targeted temporal baselines, and time series of precipitation and snowmelt at the Mt. Mater and Saline ridge outlined complex temporally shifted seasonal displacement trends. These trends, more evident for shallower nested sectors, outline dominant controls by prolonged precipitation periods modulated by the effects of snowmelt. This suggests that DSGSDs, often considered insensitive to short-term (pluri-annual) climatic forcing, may respond to hydrological triggering, with key implication in the interpretation of their progressive failure. Our results demonstrated the effectiveness of the proposed multi-scale methodology that exploits DInSAR products and targeted processing to identify, classify and characterize the activity of slow rock slope deformation at different levels of details by including geological data in all the analysis stages. Our approach, readily applicable to different settings and datasets, provides the tools to solve key scientific issues in a geohazard-oriented study of slow rock slope deformations.

Estendendo l’approccio di decomposizione dell’Indice di Malmquist proposto da Fare et al. (1992) secondo cui la variazione della produttività è descritta come variazione della tecnologia e dell’efficienza, Simar e Wilson (1999) hanno fornito per la prima volta un’interpretazione statistica dell’indice e dei suoi componenti, proponendo un algoritmo basato sul bootstrap per stimare gli intervalli di confidenza degli indici sopra definiti. In questa tesi si è, per la prima volta, proposto un nuovo metodo di stima della densità, basato su una selezione più accurata della bandwidth, partendo e adattando i recenti sviluppi introdotti da Simar e Wilson (2007) nel caso univariato al caso bivariato. Inoltre, per la prima volta è stata testata la performance delle procedure per stimare gli indici, attraverso l’implementazione di simulazioni Monte Carlo. Essi hanno mostrato un basso livello di performance del modello proposto da Simar e Wilson nel 1999 rispetto a quello proposto in questo lavoro. In particolare, essi hanno evidenziato che la procedura di stima della densità è molto sensibile alla presenza di valori unitari dell’efficienza, tanto da fornire seri problemi nella valutazione della stima della funzione di densità continua. Inoltre, sono stati applicati e adattati i data driven methods, che hanno evidenziato risultati diversi rispetto alla procedura originale, lasciano ampi spazi a ricerche future. Da un punto di vista empirico, è stata analizzata la crescita delle regioni italiane attraverso la Total Factor Productivity (TFP), nel periodo 1980-2001. Quindi sono stati stimati l’indice di Malmquist e i suoi componenti come pure i loro rispettivi intervalli di confidenza, applicando la procedure migliore, identificata nella fase di ricerca precedente. E’ stato registrato un guadagno complessivo della variazione della produttività, corretta nella bias, del 2.1%, dell’efficienza del 0.5% e della tecnologia del 1.6%. L’analisi di sensibilità, basata su tecniche bootstrap, ha rilevato che per la maggior parte delle regioni italiane l’efficienza e la tecnologia non hanno mostrato cambiamenti statisticamente significativi. Secondo questi risultati, l’approccio inferenziale ha fornito un’analisi più accurata e rigorosa rispetto all’approccio tradizionale, adottato da Leonida et al.(2004 ,Table 1, pg. 2190) nella quale le stime sono state valutate come miglioramenti o recessioni, trascurando sia la correzione della bias che il loro significato statistico.
Improving the Fare et al. (1992) approach on Malmquist index of productivity, which can be decomposed into indices describing changes in technology and changes in efficiency , Simar and Wilson (1999) provided a statistical interpretation to their Malmquist productivity index and its components, and presented a bootstrap algorithm to estimate confidence intervals for the indices. Extending the recent developments introduced by Simar and Wilson (2007) in the bandwidth specification in the univariate case, we propose new methods of density estimation, based on more accurate bandwidth specification. Monte Carlo experiments have been computed for the first time in this context. They have shown a low quality of performance of the Simar and Wilson (1999)'s bootstrap approximations, and high level of quality for the proposed methods. In particular, they have found out as best performer method the procedure based on the density estimation without considering the ones, revealing the severe problem of deteriorating the estimation of the continuous density of the efficiency scores. Moreover, data driven methods have been applied to the Malmquist Index framework and at this stage of research they have shown different results from those provided by Simar and Wilson (1999). From an empirical point of view, Total Factor Productivity (TFP) growth of the Italian regions over the period 1980-2001 has been analyzed. Malmquist Productivity Index (MPI) and its components (namely Efficiency Change and Technical Change) as well as confidence intervals have been estimated by applying the best performed procedure, previously determinated. Including human capital among inputs, we estimated an overall bias-corrected productivity gain of 2.1 percent, an efficiency gain of 0.5 and a technical gain of 1.6 percent. The bootstrap analysis revealed that for most Italian regions efficiency and technical changes did not show a statistically significant change. According to these results, the inferential approach has provided a more rigorous and accurate insights on the Italian regional TFP than the traditional Data Envelopment Analysis (DEA) estimation carried out by Leonida et al.(2004 ,Table 1, pg. 2190) in which all the estimated values are interpreted as progress or regress without taking into account the bias of the estimated values and their statistical significance.

The subjekt of my diploma work is socioeconomic development of region Plzeň, its goals and priorities and areas of development. The work consists of two parts. The subjekt of first part is the characteristic of the region. I'm dealing with the settlement structure, population, economic structure, labour market, transport, tourism , culture and health and social security. The sekond parts is concerning with proposals of developing goals and priorities of the region. I'm comparing apportionable datas with datas for the whole Czech republic. In the SWOT analysis I am summarizing datas that I have found out, In the final part I am suggesting solving problemes, which region has those problemes and wchich region could have them in the future.

Studies on water resources are rarely developed in basins where anthropic impact is negligible; therefore, the flow values are seldom ''natural'' and are often significantly affected by the interference of human works. These alterations of the natural discharges can be due to the presence, along the river network, of interfering hydraulic structures. Interactions between these infrastructures and the natural streamflow are certainly in need of further attention. Two main issues have been studied here in detail: i) the impact on water availability and the variability caused by water abstractions and ii) the flood attenuation effect induced by existing reservoirs, that produces flood hazard mitigation downstream. When working in a regional analysis framework, input data and results should represent the natural conditions. Hence, the alterations due to hydraulics structures embedded into the river network should be removed or introduced carefully. For instance, regional estimates of flood peak discharges do not consider the flood attenuation operated by the existing reservoirs. Nevertheless dams have a significant impact, especially in the nearest areas downstream, that should be accounted for. For the Piemonte and Valle d'Aosta Regions, this flood peak attenuation effect has been studied in detail to provide a correct starting point for further flood hazard studies. On the other hand, to assess the impact of water abstractions on daily discharge data, basic indices of alterations have been defined and an innovative correction model to reconstruct the natural streamflow statistics has been proposed. Non-impacted discharge characteristics are needed to provide a correct regional estimate of water resources availability and, consequently, of the gross hydropower potential. For water use planning purposes or to define the residual hydropower potential, the correction model proposed can also be used backward, adding anthropic effects to non-impacted values of discharge. The relevance of the proposed approach and methods in regional analysis of extreme and average flows is something that can be better recognized only with the effort of systematically characterizing the infrastructures that interfere with the natural hydrology along the river network. The applications made in this work were made possible by a cooperative effort addressed to the realization of a comprehensive Hydrological and Infrastructures Information System for the Regione Piemonte, that constitutes an important laboratory for hydrological simulations in a real world of heavily altered natural processes.

Energy production and consumption contribute to 76% of the European greenhouse gas (GHG) emissions in 2018, and 90% of global GHG emissions with land use, land use change and forestation (LULUCF) in the same year. By applying energy efficiency (EE) and renewable energy (RE) technologies, the GHG emission intensity of the energy sector reduced by 1.3% in 2018 compared to the previous year. The current climate change policy aims at decarbonization, sustainable environment, economic prosperity and social equity. It requires the deep decarbonisation of the economies, meaning that the energy and power systems as well as other emission intensive sectors need to transform into zero-emission ones. It also requires the minimization of the environmental impacts while ensuring the economic development and meeting the need of the population growth. This thesis quantifies and evaluates the life cycle environmental impacts with focus on GHG emissions of the power sector, as consequences of changes in the environmental policy. Specifically, the thesis will answer five research questions: 1. What are climate change and energy/ power development policies in Italy? 2. What are changes in the energy/ power systems as consequences of energy climate policies? 3. What are the methods and approach for quantifying and evaluating life cycle environmental impacts as consequences of changes? 4. What are the life cycle environmental impacts of the Italian energy/ power system, with focus on GHG emissions, as consequences of changes in environmental and power policies? 5. The interactions between the energy climate policies and the environmental impacts/ GHG emissions of the Italian power system? The thesis is structured into six chapters, including two chapters of introduction and conclusion, and four chapters of answering five above-mentioned research questions. Chapter 2 provides the answers for two questions (Question 1 and Question 2) on climate and energy policies and changes in the Italian energy/power system due to climate and energy policies. Climate change and energy/ power development policy in Italy is presented in five main documents: FIT for 55, Integrated national energy and climate plan (NECP), national energy strategy (SEN), national energy efficiency action plan (PAEE), and national renewable energy action plan (NREAP). The four national documents set out the targets for EE and RE. Specifically, the targets of energy savings by 2030 include 43% reduction in primary energy consumption, 0.8% reduction in annually final energy consumption without transportation sector and 10 MTOE final energy consumption reduction. For RE, by 2030, the target is 28% ~ 30% of share of RE in total energy consumption, 55% of RE share in electricity consumption and 21% ~ 22% of RE share in transportation sector. It is expected that the electricity generation technology mix will change in order to meet the requirement on RE and EE targets set out in the Italian energy and climate policies. In this thesis, the energy scenarios called National Trend Italia (NT Italia) will be used. The NT Italia was developed by Terna and Snam, for the horizon years 2025, 2030 and 2040, using modelling tools for electricity demand, gas demand and market simulation. In these scenarios, the installed capacity of electricity by natural gas, which is slightly increased by 2040. The installed capacity of coal-based electricity and other fossil fuels-based electricity reduce from 7GW currently to 2GW by 2025, and will not change then. The scenarios also see a constant growth of electricity by RE, reaching 64 GW for solar and 25 GW for wind power (including 4.2 GW offshore) by 2040, while the installed capacity of hydropower and other renewable electricity will be stable. Chapter 3 and Chapter 4 of this thesis will deal with the research question 3, in which Chapter 3 is about the methodology and Chapter 4 focuses on the applied framework. In Chapter 3, the state of the art of consequential life cycle assessment (C-LCA) in the energy and power sectors has been reviewed. The review was conducted on 43 case studies of C-LCA in energy sector and 31 C-LCA papers in power sector. It was identified that economic models are frequently applied in combination with life cycle assessment (LCA) to conduct a C-LCA study in energy and power sectors. The identified economic models include equilibrium (partial and general equilibrium), input-output, and dynamic (agent based and system dynamic) models. Out of these, the equilibrium model is the most widely used, showing some strengths in availability of data and energy system modelling tools. The input-output model allows for describing both direct and indirect effects due to changes in the energy sector, by using publicly available data. The dynamic model is less frequently applied due to its limitation in availability of data and modelling tools, but has recently attracted more attention due to the ability in modelling quantitative and qualitative indicators of sustainability. The review indicates that the most suitable approach to conduct the study is combining one or several economic models and LCA to assess the consequential life cycle impacts of the power system. As each economic model has their own strengths and limitations, the choice of the applied models in combination with LCA largely depends on the goal of the study, the nature of the changes due to market mechanisms, economic or social origins, and the availability of data. In Chapter 4, a framework of combining Input Output Analysis (IOA) and process-based LCA for conducting the study was proposed. Moreover, this chapter provides detailed information on data collected for the model. There are several weighting points for proposing this framework. Firstly, the goal of the study is to assessing the consequential life cycle impacts of energy/ power systems. It requires the comprehensive overview of all economic sectors, as energy is connected all economic activities. The comprehensiveness will be ensured by applying IOA. At the same time, the process-based LCA will provide the detail of a sector/ a product system, which is normally a limitation of economic-wide tool such as IOA. Secondly, the change in the power system originates from economic activities (supply and demand of energy) as well as the environmental requirement to GHG emission reduction and zero carbon emissions. This change can be well modelled with an economic analysis tool (IOA) in combination with an environmental management tool (processed-based LCA). Finally, data for these tools is publicly available. The IOA depends on the input output tables (IOT), which is published every five years by the Italian Statistics (Istat). Data on energy sector is collected from Energy Balance Table, published annually by Ministry of Economic Development, the data from Terna and Snam, the database of the International Energy Agency (IEA), International Renewable Energy Agency (IRENA) and European Commission. Data on environmental aspects includes the National Accounting Matrix with Environmental Accounts (NAMEA), being collected from Istat. Data for process-based LCA is taken from ecoInvent 3. Some global database for IOA are available such as World Input Output Database (WIOD), EXIOBASE, and ect. Followings is the general framework for combining IOA and processed-based LCA to conduct a C-LCA. Consequential life cycle impact is the subtraction of the life cycle impact ‘after change’ and the life cycle impact ‘before change’. The life cycle impact ‘before change’ is quantified by applying IOA. The life cycle impact ‘after change’ depends on the change of pollutant amount, technological coefficient and the final demand due to the inclusion of renewable energy into the Italian energy system. In this thesis, multiregional input output (MRIO), a variant of IOA is used to cover several regions or countries. The application of hybrid MRIO and process-based LCA (hereinafter being called as H-MRIO) is described as followings: • First, two types of data, including MRIO and hybridization data are collected. MRIO data such as the Italian and multiregional IOTs and air emissions accounts are collected from Istat and EXIOBASE. Hybridization data is collected from Italian power/energy suppliers for power development scenarios, and from the ecoinvent database for direct air emissions of power generation technologies • From MRIO data, the MRIO model with two regions of Italy and Rest of the World (RoW) and 36 economic sectors will be constructed. • In combination with the power development scenarios, the Italian electricity sector is disaggregated into seven power generation technologies, for both intermediate flow matrices and final demand vectors in Italian IOT. Similarly, in the environmental burden matrices, the air emissions of electricity sector are disaggregated into those of seven power generation technologies, with data taken from ecoinvent. At this time, the H-MRIO model composes of 42 sectors (36 economic sectors - 1 electricity sector + 7 power technologies). • The model is calculated with historical data of 2010 and 2017 (reference scenario) and replicated for the future scenarios of 2025, 2030 and 2040. Chapter 5 focuses on applying the proposed H-MRIO framework on the Italian context, to obtained the answers for the last two research questions (Question 4 and 5). The total GHG emissions to meet global final demand in 2017 calculated in the study is at 47.69 GtCO2e, which is slightly higher than the global GHG emissions estimated by Climate Watch, at 47 GtCO2e excluding Land use change and forestation (LUCF). The difference in the obtained results of this model and other models is caused by the difference in scope of air emissions being studied. This model quantified actual anthropogenic emissions of CO2, CH4 and N2O, excluding emissions from LULUCF and biomass burning as a fuel. Meanwhile the Climate Watch’s model takes into account all GHGs (CO2, CH4, N2O, and F-gases such as HFCs, PFCs, and SF6), excluding LUCF. This causes a difference of around 1 GtCO2eq of F-gases and 2.8 Gt CO2eq of CH4. The exclusions of emissions from land use (mostly CH4), biogenic CO2 and F-gases in this model leads to an insignificant difference of around 0.69 GtCO2e (less than 1.5%). In order to look into details of the sources of the change in the air emission, a decomposition analysis has been conducted. With the change in final demand and electricity sector composition of Italy, consumption-based GHG emissions appear to decrease in the period 2010-2040. Specifically, due to changes in production structure, emission coefficients, and final demand, the annual CO2 emission reduction embodied in production activities during the period 2017- 2025 will be up to 7.1 MtCO2, which makes up 57.1 MtCO2 emission reduction in the whole period. The increased final demand of Italy causes an annual increase of 4.8 MtCO2. While the change in production structure, including electricity sector and corresponding change in other economic sectors, helps to reduce 6.1 MtCO2 annually. The change in emission flow coefficients brings an annual reduction credit of about 5.8 MtCO2. During the period of 2025-2030 and 2030-2040, the annual change in emission reduction will be much smaller, at 2.3 MtCO2 and 33.9 ktCO2 respectively. Due to the change in power supply technologies and power consumption, the future air emissions dramatically reduce in electricity sector. Most of the emissions of the domestic electricity production come from fossil fuel based electricity, e.g. electricity by coal and natural gas. A smaller part comes from other renewable electricity, including geothermal and biomass based electricity. The productions of solar and wind power do not generate any air-borne emission, and that of hydropower emits an amount of N2O. The reduction in electricity from fossil fuels such as coal and natural gas help to reduce the emissions of the domestic electricity production nearly four times from 97.5 MtCO2 in 2017 to 25.9 MtCO2 by 2040. Besides, the CO2 emission of final consumption of electricity is 34.9 MtCO2 in 2017, which reduces by more than half, at 13.7 MtCO2 by 2040. The CO2 emission of final electricity consumption is divided among technologies by their production structure. As it can be observed, low-carbon technologies such as solar and wind power technologies contribute to emissions, because of the manufacturing of their infrastructures. The emissions of final electricity consumption are smaller than that of domestic electricity production, as they are shared by other economic sectors as intermediates for production activities. The changes in electricity consumption induce changes in other economic sectors, which are clearly shown in coke and petroleum, pharmaceuticals, water transportation, education, and healthcare, either increase or decrease their emissions. Particularly, electricity sector accounts for 11.6% of the total CO2 emissions in 2017, which reduces to 5.9% by 2040. The CO2 emission shares of some other economic sectors also decrease during the period 2017-2040, such as construction and healthcare (reducing around 1 percent point). Meanwhile, the CO2 emission shares of some sectors increases, such as food and beverage (increasing less than 1 percent point). It should be noted that the CO2 emission contributions of these sectors to the national final consumption emissions do not show the correspondingly absolute increase (or decrease). Instead, they relatively present the changes in the identified ‘hotspot’ sectors over years. The absolute values of the CO2 emissions decrease in all economic sectors between 2017 and 2040. The decrease is clearly presented in economic sectors such as construction, decreasing from 20.99 MtCO2 in 2017 to 13.4 MtCO2 by 2040, at about 0.33 MtCO2 annually; or food and beverage, decreasing from 15 MtCO2 to 12.5 MtCO2, or 0.1 MtCO2 annually; or healthcare, decreasing from 17.7 MtCO2 to 11.43 MtCO2 or 0.27 MtCO2 annually in the same period. Five economic sectors holding larges shares out of total CO2 emission of final consumption includes: wholesale and retail, healthcare, food and beverage, electricity and construction (‘hotspot’ sectors). In 2017, wholesale and retail contribute to more than 12% of the total CO2 emission of the Italian final consumption. The four remaining sectors account for an average CO2 emission, from 6% to 10% of the total CO2 emissions. By 2040, the shares of emissions of these sectors remain in the same range. This emission pattern suggests that between 2017 and 2040, in order to reduce the national CO2 emissions, effort should be focused on these ‘hotspot’ sectors. Besides, the different contributions of domestic and import emissions to the total emissions suggest that Italy should have proper strategies to reduce its emissions in term of geographical effort. CO2 emissions of Italian trade partners for food and beverage, health, construction, and wholesale and retail should be taken into account because their emissions largely depends on import. The effort should be taken either to reduce their trade partners’ emission intensity, or to move away from trade partners that having high emission intensities. Meanwhile equal effort should be shared between local manufacturers and trade partners being relevant to renewable power technologies such as solar, wind and other renewable.
Energy production and consumption contribute to 76% of the European greenhouse gas (GHG) emissions in 2018, and 90% of global GHG emissions with land use, land use change and forestation (LULUCF) in the same year. By applying energy efficiency (EE) and renewable energy (RE) technologies, the GHG emission intensity of the energy sector reduced by 1.3% in 2018 compared to the previous year. The current climate change policy aims at decarbonization, sustainable environment, economic prosperity and social equity. It requires the deep decarbonisation of the economies, meaning that the energy and power systems as well as other emission intensive sectors need to transform into zero-emission ones. It also requires the minimization of the environmental impacts while ensuring the economic development and meeting the need of the population growth. This thesis quantifies and evaluates the life cycle environmental impacts with focus on GHG emissions of the power sector, as consequences of changes in the environmental policy. Specifically, the thesis will answer five research questions: 1. What are climate change and energy/ power development policies in Italy? 2. What are changes in the energy/ power systems as consequences of energy climate policies? 3. What are the methods and approach for quantifying and evaluating life cycle environmental impacts as consequences of changes? 4. What are the life cycle environmental impacts of the Italian energy/ power system, with focus on GHG emissions, as consequences of changes in environmental and power policies? 5. The interactions between the energy climate policies and the environmental impacts/ GHG emissions of the Italian power system? The thesis is structured into six chapters, including two chapters of introduction and conclusion, and four chapters of answering five above-mentioned research questions. Chapter 2 provides the answers for two questions (Question 1 and Question 2) on climate and energy policies and changes in the Italian energy/power system due to climate and energy policies. Climate change and energy/ power development policy in Italy is presented in five main documents: FIT for 55, Integrated national energy and climate plan (NECP), national energy strategy (SEN), national energy efficiency action plan (PAEE), and national renewable energy action plan (NREAP). The four national documents set out the targets for EE and RE. Specifically, the targets of energy savings by 2030 include 43% reduction in primary energy consumption, 0.8% reduction in annually final energy consumption without transportation sector and 10 MTOE final energy consumption reduction. For RE, by 2030, the target is 28% ~ 30% of share of RE in total energy consumption, 55% of RE share in electricity consumption and 21% ~ 22% of RE share in transportation sector. It is expected that the electricity generation technology mix will change in order to meet the requirement on RE and EE targets set out in the Italian energy and climate policies. In this thesis, the energy scenarios called National Trend Italia (NT Italia) will be used. The NT Italia was developed by Terna and Snam, for the horizon years 2025, 2030 and 2040, using modelling tools for electricity demand, gas demand and market simulation. In these scenarios, the installed capacity of electricity by natural gas, which is slightly increased by 2040. The installed capacity of coal-based electricity and other fossil fuels-based electricity reduce from 7GW currently to 2GW by 2025, and will not change then. The scenarios also see a constant growth of electricity by RE, reaching 64 GW for solar and 25 GW for wind power (including 4.2 GW offshore) by 2040, while the installed capacity of hydropower and other renewable electricity will be stable. Chapter 3 and Chapter 4 of this thesis will deal with the research question 3, in which Chapter 3 is about the methodology and Chapter 4 focuses on the applied framework. In Chapter 3, the state of the art of consequential life cycle assessment (C-LCA) in the energy and power sectors has been reviewed. The review was conducted on 43 case studies of C-LCA in energy sector and 31 C-LCA papers in power sector. It was identified that economic models are frequently applied in combination with life cycle assessment (LCA) to conduct a C-LCA study in energy and power sectors. The identified economic models include equilibrium (partial and general equilibrium), input-output, and dynamic (agent based and system dynamic) models. Out of these, the equilibrium model is the most widely used, showing some strengths in availability of data and energy system modelling tools. The input-output model allows for describing both direct and indirect effects due to changes in the energy sector, by using publicly available data. The dynamic model is less frequently applied due to its limitation in availability of data and modelling tools, but has recently attracted more attention due to the ability in modelling quantitative and qualitative indicators of sustainability. The review indicates that the most suitable approach to conduct the study is combining one or several economic models and LCA to assess the consequential life cycle impacts of the power system. As each economic model has their own strengths and limitations, the choice of the applied models in combination with LCA largely depends on the goal of the study, the nature of the changes due to market mechanisms, economic or social origins, and the availability of data. In Chapter 4, a framework of combining Input Output Analysis (IOA) and process-based LCA for conducting the study was proposed. Moreover, this chapter provides detailed information on data collected for the model. There are several weighting points for proposing this framework. Firstly, the goal of the study is to assessing the consequential life cycle impacts of energy/ power systems. It requires the comprehensive overview of all economic sectors, as energy is connected all economic activities. The comprehensiveness will be ensured by applying IOA. At the same time, the process-based LCA will provide the detail of a sector/ a product system, which is normally a limitation of economic-wide tool such as IOA. Secondly, the change in the power system originates from economic activities (supply and demand of energy) as well as the environmental requirement to GHG emission reduction and zero carbon emissions. This change can be well modelled with an economic analysis tool (IOA) in combination with an environmental management tool (processed-based LCA). Finally, data for these tools is publicly available. The IOA depends on the input output tables (IOT), which is published every five years by the Italian Statistics (Istat). Data on energy sector is collected from Energy Balance Table, published annually by Ministry of Economic Development, the data from Terna and Snam, the database of the International Energy Agency (IEA), International Renewable Energy Agency (IRENA) and European Commission. Data on environmental aspects includes the National Accounting Matrix with Environmental Accounts (NAMEA), being collected from Istat. Data for process-based LCA is taken from ecoInvent 3. Some global database for IOA are available such as World Input Output Database (WIOD), EXIOBASE, and ect. Followings is the general framework for combining IOA and processed-based LCA to conduct a C-LCA. Consequential life cycle impact is the subtraction of the life cycle impact ‘after change’ and the life cycle impact ‘before change’. The life cycle impact ‘before change’ is quantified by applying IOA. The life cycle impact ‘after change’ depends on the change of pollutant amount, technological coefficient and the final demand due to the inclusion of renewable energy into the Italian energy system. In this thesis, multiregional input output (MRIO), a variant of IOA is used to cover several regions or countries. The application of hybrid MRIO and process-based LCA (hereinafter being called as H-MRIO) is described as followings: • First, two types of data, including MRIO and hybridization data are collected. MRIO data such as the Italian and multiregional IOTs and air emissions accounts are collected from Istat and EXIOBASE. Hybridization data is collected from Italian power/energy suppliers for power development scenarios, and from the ecoinvent database for direct air emissions of power generation technologies • From MRIO data, the MRIO model with two regions of Italy and Rest of the World (RoW) and 36 economic sectors will be constructed. • In combination with the power development scenarios, the Italian electricity sector is disaggregated into seven power generation technologies, for both intermediate flow matrices and final demand vectors in Italian IOT. Similarly, in the environmental burden matrices, the air emissions of electricity sector are disaggregated into those of seven power generation technologies, with data taken from ecoinvent. At this time, the H-MRIO model composes of 42 sectors (36 economic sectors - 1 electricity sector + 7 power technologies). • The model is calculated with historical data of 2010 and 2017 (reference scenario) and replicated for the future scenarios of 2025, 2030 and 2040. Chapter 5 focuses on applying the proposed H-MRIO framework on the Italian context, to obtained the answers for the last two research questions (Question 4 and 5). The total GHG emissions to meet global final demand in 2017 calculated in the study is at 47.69 GtCO2e, which is slightly higher than the global GHG emissions estimated by Climate Watch, at 47 GtCO2e excluding Land use change and forestation (LUCF). The difference in the obtained results of this model and other models is caused by the difference in scope of air emissions being studied. This model quantified actual anthropogenic emissions of CO2, CH4 and N2O, excluding emissions from LULUCF and biomass burning as a fuel. Meanwhile the Climate Watch’s model takes into account all GHGs (CO2, CH4, N2O, and F-gases such as HFCs, PFCs, and SF6), excluding LUCF. This causes a difference of around 1 GtCO2eq of F-gases and 2.8 Gt CO2eq of CH4. The exclusions of emissions from land use (mostly CH4), biogenic CO2 and F-gases in this model leads to an insignificant difference of around 0.69 GtCO2e (less than 1.5%). In order to look into details of the sources of the change in the air emission, a decomposition analysis has been conducted. With the change in final demand and electricity sector composition of Italy, consumption-based GHG emissions appear to decrease in the period 2010-2040. Specifically, due to changes in production structure, emission coefficients, and final demand, the annual CO2 emission reduction embodied in production activities during the period 2017- 2025 will be up to 7.1 MtCO2, which makes up 57.1 MtCO2 emission reduction in the whole period. The increased final demand of Italy causes an annual increase of 4.8 MtCO2. While the change in production structure, including electricity sector and corresponding change in other economic sectors, helps to reduce 6.1 MtCO2 annually. The change in emission flow coefficients brings an annual reduction credit of about 5.8 MtCO2. During the period of 2025-2030 and 2030-2040, the annual change in emission reduction will be much smaller, at 2.3 MtCO2 and 33.9 ktCO2 respectively. Due to the change in power supply technologies and power consumption, the future air emissions dramatically reduce in electricity sector. Most of the emissions of the domestic electricity production come from fossil fuel based electricity, e.g. electricity by coal and natural gas. A smaller part comes from other renewable electricity, including geothermal and biomass based electricity. The productions of solar and wind power do not generate any air-borne emission, and that of hydropower emits an amount of N2O. The reduction in electricity from fossil fuels such as coal and natural gas help to reduce the emissions of the domestic electricity production nearly four times from 97.5 MtCO2 in 2017 to 25.9 MtCO2 by 2040. Besides, the CO2 emission of final consumption of electricity is 34.9 MtCO2 in 2017, which reduces by more than half, at 13.7 MtCO2 by 2040. The CO2 emission of final electricity consumption is divided among technologies by their production structure. As it can be observed, low-carbon technologies such as solar and wind power technologies contribute to emissions, because of the manufacturing of their infrastructures. The emissions of final electricity consumption are smaller than that of domestic electricity production, as they are shared by other economic sectors as intermediates for production activities. The changes in electricity consumption induce changes in other economic sectors, which are clearly shown in coke and petroleum, pharmaceuticals, water transportation, education, and healthcare, either increase or decrease their emissions. Particularly, electricity sector accounts for 11.6% of the total CO2 emissions in 2017, which reduces to 5.9% by 2040. The CO2 emission shares of some other economic sectors also decrease during the period 2017-2040, such as construction and healthcare (reducing around 1 percent point). Meanwhile, the CO2 emission shares of some sectors increases, such as food and beverage (increasing less than 1 percent point). It should be noted that the CO2 emission contributions of these sectors to the national final consumption emissions do not show the correspondingly absolute increase (or decrease). Instead, they relatively present the changes in the identified ‘hotspot’ sectors over years. The absolute values of the CO2 emissions decrease in all economic sectors between 2017 and 2040. The decrease is clearly presented in economic sectors such as construction, decreasing from 20.99 MtCO2 in 2017 to 13.4 MtCO2 by 2040, at about 0.33 MtCO2 annually; or food and beverage, decreasing from 15 MtCO2 to 12.5 MtCO2, or 0.1 MtCO2 annually; or healthcare, decreasing from 17.7 MtCO2 to 11.43 MtCO2 or 0.27 MtCO2 annually in the same period. Five economic sectors holding larges shares out of total CO2 emission of final consumption includes: wholesale and retail, healthcare, food and beverage, electricity and construction (‘hotspot’ sectors). In 2017, wholesale and retail contribute to more than 12% of the total CO2 emission of the Italian final consumption. The four remaining sectors account for an average CO2 emission, from 6% to 10% of the total CO2 emissions. By 2040, the shares of emissions of these sectors remain in the same range. This emission pattern suggests that between 2017 and 2040, in order to reduce the national CO2 emissions, effort should be focused on these ‘hotspot’ sectors. Besides, the different contributions of domestic and import emissions to the total emissions suggest that Italy should have proper strategies to reduce its emissions in term of geographical effort. CO2 emissions of Italian trade partners for food and beverage, health, construction, and wholesale and retail should be taken into account because their emissions largely depends on import. The effort should be taken either to reduce their trade partners’ emission intensity, or to move away from trade partners that having high emission intensities. Meanwhile equal effort should be shared between local manufacturers and trade partners being relevant to renewable power technologies such as solar, wind and other renewable.

La présente thèse a pour objet d'étudier la contribution de la région dans le développement régional. En s'appuyant sur une argumentation financière et juridique, et en faisant appel à des approches historique, comparative et prospective, cette thèse étudie le développement en tant que fonction principale de la collectivité territoriale régionale. Le rôle peut-être résumé dans la primauté régionale en matière de développement économique, consacrée par le législateur à travers la reconnaissance à la région du rôle de coordination et de chef de file. Ces configurations sont pour autant entravées par un contexte financier qui rend le rôle de la région particulièrement complexe
This thesis is intended to study the contribution of the region to regional development. Based on the financial and legal analysis, referring to historical, comparative and perspective approaches, the thesis examines the development as a major function of administrative territorial structures. The nature of this function can be summarized in the regional primacy in economic development, dedicated by the legislature through the recognition of the role of regional coordination and leadership. In the meantime, these configurations are hampered by a financial context which makes the region's function of a particularly complex nature

This diploma thesis deals with complex evaluation of tourism competitiveness of five Moravian regions. First chapter explains basic definitions related to the tourism and regional competitiveness. Second chapter analyzes in detail natural conditions, economics, transport, people and tourism of the regions. In the third chapter, the competitiveness of Moravian regions in three areas (economics, people and tourism) and as a whole is examined through the method of the economic n-angle.

The paper studies the regional integration as the unique process which depends on the degree of cooperation and interchange among regions. The generalisation of existing approaches for regional integration has been classified by the criterions. The data of the main economic indicators have been analysed. The economic analysis proves the differences in production endowments, the asymmetry in fixed capital investment, the disproportional income, and foreign direct investment distribution in 2001 – 2005 in Ukrainian regions. Econometric modelling depicts the existence of the division for the industrial regions with high urbanisation and backward agrarian regions in the Ukraine, the industrial development disparities among regions; the insufficient infrastructure (telecommunications, roads, hotels, services and etc.), the low labour productivity in industrial sector, and insufficient regional trade.

Syftet med denna uppsats är att analysera fyra statliga offentliga dokument för att se vad problemen är representerade att vara som leder politiken mot en riktning där den kommunala planeringen, i form av den fysiska planeringen och bostadsförsörjningsplaneringen, i större utsträckning ska ordnas i- och ta hänsyn till ett regionalt perspektiv. Syftet med denna uppsats blir således också att analysera villkoren för det kommunala självstyret när en av dess grundbultar, den kommunala planeringen, i ökad utsträckning ska ordnas i- och ta hänsyn till den regionala nivån. Den här uppsatsen teoretiska- och metodologiska ansats bygger på ett vetenskaplig paket av Carol Bacchi. Hennes ansats studerar problemrepresentationer och för att besvara den här uppsatsen övergripande frågeställningar använder jag mig av ett diskursanalysverktyg som är inspirerad utifrån hennes ansats. Den empiriska analysen visar att en av problemrepresentationerna är att det pågår en regionförstoring med växande funktionella regioner. En annan problemrepresenation som framträder i de undersökta dokumenten är att det anses vara betydande av en ökad samordning av den kommunala planeringen. Det kommunala planmonopolet, som är en del av det kommunala självstyret, problematiseras att vara av stor vikt i de undersökta dokumenten, men att det finns brister i tillämpningen m.m. Alla dessa problematiseringar ovan som funnits i de undersökta dokumenten kan spåras till en diskurs där hållbar utveckling, konkurrenskraft och tillväxt är det självklara och eftersträvansvärda. Villkoren för kommunalt självstyre kan förstås på det sättet att en av dess grundbultar, den kommunala planeringen, i större utsträckning ska ordnas i- och ta hänsyn till en nyregional logik som bygger på en viss typ av politik med en konsensustradition.
The purpose of this essay is to analyze four public document published by the Swedish state to see what the problems is represented to be, which makes the politics move to a certain direction where municipal planning, more specifically spatial and social planning and housing planning, should take into account regional perspectives. Also, the purpose of this essay is to analyze the terms of the local self-government in a context where the municipal planning is increasingly to be arranged in a regional perspective. This essays theoretical- and methodological approach contains of a scientific package created by Carol Bacchi. Her theoretical- and methodological approach studies problem representations and to answer this essay overall questions I use a discourse analysis tool inspired of Bacchis approach. The empirical analysis shows that there is a problem representation about an ongoing regional expansion, thus expanding functional regions. Another problem representation is that it is considered necessary to have a greater coordination of the municipal planning. The municipal monopoly, which is a part of the local self-government, is problematized in the examined document to be of great importance, but there are some shortcomings in the application. All of these problem representations and problematisations can be traced to a discourse in which sustainable development, competitiveness and growth is desirable. The terms of the local self-government can be understood in the sense that one of its cornerstones, the municipal planning, greater will be arranged in a new regional logic, which builds upon a certain kind of politics with a consensus tradition

Frequency analysis is a vital tool when nding a well-suited probability distributionin order to predict extreme rainfall. The regional frequency approach have beenused for determination of homogeneous regions, using 11 sites in Skane, Sweden. Todescribe maximum annual daily rainfall, the Generalized Logistic (GLO), GeneralizedExtreme Value (GEV), Generalized Normal (GNO), Pearson Type III (PE3),and Generalized Pareto (GPA) distributions have been considered. The method ofL-moments have been used in order to nd parameter estimates for the candidatedistributions. Heterogeneity measures, goodness-of-t tests, and accuracy measureshave been executed in order to accurately estimate quantiles for 1-, 5-, 10-, 50- and100-year return periods. It was found that the whole province of Skane could beconsidered as homogeneous. The GEV distribution was the most consistent withthe data followed by the GNO distribution and they were both used in order toestimate quantiles for the return periods. The GEV distribution generated the mostprecise estimates with the lowest relative RMSE, hence, it was concluded to be thebest-t distribution for maximum annual daily rainfall in the province.

Der Einfluss von Bildung gewinnt gesellschaftlich und politisch an Bedeutung. Auch im wissenschaftlichen Bereich zeigt sich dies über eine vielseitige Diskussion zum Einfluss von Bildung auf das Einkommen. In dieser Arbeit werden nationale und regionale Disparitäten in der monetären Wertschätzung von allgemeinem Humankapital aufgedeckt und diskutiert. Dafür werden verschiedene Verfahren diskutiert und basierend darauf Intervalle für die mittleren Bildungsrenditen bestimmt. Im ersten Abschnitt wird die Thematik theoretisch über zwei verschiedene Modellansätze fundiert und kritisch diskutiert. Anschließend folgt die Darstellung des aktuellen empirischen Forschungsbestands. Der Hauptteil der Arbeit beginnt mit der Darstellung des verwendeten Datensatzes und seiner kritischen Repräsentativitätsprüfung. Eine nähere Variablenbeschreibung mit deskriptiver Analyse dient zur Erklärung der verwendeten Größen. Darauffolgend werden bestehende Verfahren zur Schätzung von Bildungsrenditen diskutiert. Unter ausschließlicher Berücksichtigung der Erwerbstätigen zeigt das 3SLS-Verfahren die besten Eigenschaften. Bezieht man jedoch alle Erwerbspersonen in die Analyse mit ein, so erweist sich das Heckman-Verfahren als sehr geeignet. Die Analyse - zunächst auf nationaler Ebene - bestätigt weitestgehend die bestehenden Erkenntnisse der Literatur. Eine Separierung des Datensatzes auf verschiedene Alterscluster, Voll- und Teilerwerbstätige sowie Erwerbstätige in der Privatwirtschaft und im öffentlichen Dienst zeigen keine signifikanten Unterschiede in der Höhe der gezahlten durchschnittlichen Bildungsrenditen. Anders verhält es sich bei der regionalen Analyse. Zunächst werden Ost- und Westdeutschland separat betrachtet. Für diese erste Analyse lassen sich über 95 %-Konfidenzintervalle deutliche Unterschiede in der Höhe der Bildungsrenditen ermitteln. Aufbauend auf diese Ergebnisse wird die Analyse vertieft. Eine Separierung auf Bundesländerebene und ein weiterer Vergleich der Konfidenzintervalle folgen. Zur besseren statistischen Vergleichbarkeit der Ergebnisse wird neben dem 3SLS-Verfahren, angewendet auf die separierten Datensätze, auch ein Modell ohne die Notwendigkeit der Separierung gewählt. Hierbei ist die Variation der Regionen über Interaktionsterme berücksichtigt. Dieses Regressionsmodell wird auf das OLS- und das Heckman-Verfahren angewendet. Der Vorteil hierbei ist, dass die Koeffizienten auf Gleichheit getestet werden können. Dabei kristallisieren sich deutlich unterschiedliche Bildungsrenditen für Mecklenburg-Vorpommern, aber auch für Sachsen-Anhalt und Thüringen im Vergleich zu den restlichen Bundesländern Deutschlands heraus. Diese Länder zeichnen sich durch eine besonders hohe jährliche Verzinsung von allgemeinem Humankapital aus. Es folgt eine Diskussion über mögliche Ursachen für die regional verschiedenen Bildungsrenditen. Dabei zeigt sich, dass in den Bundesländern mit hoher Rendite das mittlere Einkommensniveau und auch das durchschnittliche Preisniveau tendenziell geringer sind. Weiterhin wird deutlich, dass bei höheren relativen Abweichungen der durchschnittlichen Einkommen höhere Renditen zu verzeichnen sind. Auch die Wanderungsbewegungen je nach Qualifikation unterscheiden sich. Unter zusätzlicher Berücksichtigung der Arbeitslosenquoten zeigt sich in den Ländern mit hoher Rendite eine tendenziell höhere Arbeitslosigkeit. Im zusammenfassenden Fazit der Arbeit werden abschließend die Erkenntnisse gewürdigt. Dabei ist zu bemerken, dass der Beitrag einen Start in die bundesländerweite Analyse liefert, die eine Fortführung auf beispielsweise eine mehrperiodische Betrachtung anregt.
The impact of education becomes politically and for the society more important. In research area the higher relevance is indicated by a distinctive discussion about, for example, the influence from education to earnings. This thesis shows national and regional disparities with respect to the monetary appreciation to general human capital. Therefore different econometric methods are discussed and based on that, intervals for the returns to education are estimated. The first chapter presents the theoretical fundament using two different models, which are critically discussed in the text. Afterwards the existing empirical literature is shown. The main part starts with a description of the dataset and a discussion about its representativeness. A closer examination to the variables follows using descriptive statistics and verbal explanations. The estimation part starts with a discussion about common methods to measure returns to education. Looking at employees exclusively, 3SLS gives best performance. However, by extension the analysis to the overall manpower Heckman-method is best. The national analysis confirms the results from the existing literature. Within the next step the dataset is separated to have a closer look at different cohorts, full- and part-time worker, as well as public- and private-sector worker. Comparing these groups with each other the estimated returns to education are not statistically different. However, results change by estimating regional returns to education for Germany. First the dataset is splitted into two regions, the eastern- and the western-region. Comparing the estimated 95 %-confidence intervals, differences are significant between both regions in Germany. Hence, it is worth to intensify the regional analysis. The next step is a further separation of the dataset to a federal-state-analysis. Again, the comparisons of the resulting confidence intervals show partially no overlapping confidence intervals. Separating the dataset gives no possibility to compare the coefficients with statistic tests. Because of that a new regression model without the necessity of separation is introduced. For this purpose the variation of the regions are included by interaction terms. This model can be estimated using OLS- and Heckman-method. The advantage of this procedure is that the schooling-coefficients can be tested on statistical equality. Irrespective which method is used, differences in the return to education can be estimated for Mecklenburg-West Pomerania especially and for Saxony-Anhalt and Thuringia. These three states tend to a higher monetary return to general human capital compared to the other federal states. Thereafter a discussion follows about possible causes for the estimated regional heterogeneous returns to education. It is shown that federal states with a high return to education lean towards a lower middle level of income and a lower price level on average. In addition to that, there is a relation between a higher relative deviation from average income and higher returns to education. Looking at migration movements between federal states, it is shown that there are differences in the qualification levels. Moreover, regions with a higher unemployment rate tend to result in higher returns as well. The summarizing conclusion appreciates the scientific findings. For that it has to be said, that this work gives a start for an analysis which should have a closer look to different parts of Germany. It gives an incentive to pursue with, for example, an analysis for more than one year.

Scotland has a set of legislative targets to reduce its greenhouse gas emissions, measured on a territorial basis, introduced by the Climate Change (Scotland) Act 2009. In addition, the Scottish Government have adopted as a 'national outcome' target a reduction in the emissions embodied in Scottish consumption activities. These targets differ in terms of whether the emissions embodied in exports are included (territorial) or whether the emissions embodied in imports are included (consumption) in the emissions total. The first area of work in this thesis is quantifying the different emissions totals that can be calculated under both of these accounting principles using the currently available data for Scotland. Using the input-output framework, we explore the construction, and the implications, of this range of measures. We also identify some wider issues that arise in the adoption of different emissions targets for a region within an interdependent national economy. The second area of work focuses on understanding the sectoral level relationships which underpin national output and CO2 emissions in Scotland. It is often the case that the focus of policy and public debate is on 'the number' (i.e. the emissions total) and changes in it. Underpinning this 'number', however, is a series of complex economic relationships at the sectoral level which we want to better understand. We seek to better understand these relationships in Scotland using the tools of linkage and key sector analysis. The final strand of work in this thesis looks to explore the compatibility of the current focus of economic policy in Scotland on increasing export demand, with the environmental objectives of reducing Scottish territorial and consumption emissions. There is great emphasis placed by the Scottish Government on the economic impacts of investing in 'green' industries, while little is said of the environmental impact of more general growth in export demand, even though this is a clear economic policy priority.Using a CGE model framework, we explore the implications on both the territorial and consumption emissions totals of a general increase in export demand with flow migration and no-migration. These two cases provide interesting insights on both the long-run impact on these emissions totals, as well as on the dynamic adjustment to the long-run total. The analysis in this thesis answers a number of interesting research questions, and uncovers some additional questions which will be the focus of future research. It is clear that the economy and the environment are interdependent. What needs to be better understood is which parts of the economy impact on the environment, how trade influences the impact of our economy on the environment, and how economic and environmental policy objectives are interdependent.

There is a growing debate on the theoretical basis, how it could be conceptualised, as well as the utility and meaning of regional competitiveness. This is associated with various attempts to measure regional competitiveness with the help of composite indices for coming-up with league tables. However the measurement of regional performance has run ahead of the academic debate, such indices receive a lot of media attention, and in some cases are even used by policy-makers to support their arguments. It is therefore instructive to look at such indices in more detail to evaluate their utility from a practical standpoint. This is done by working out the theoretical framework for six indices, deconstructing these and analysing the single indicators. Methodologically, issues such as normalization, standardization and the aggregation into a single number are also included. In addition to this, since many authors claim that their indices can function as a proxy for future growth, a statistical analysis of the predictive quality with respect to economic performance has also been carried out. This thesis, therefore, for the first time, sheds light on the utility of regional competitiveness indices and contributes to the discussion of the meaning of benchmarking regional performance based on the regional competitiveness hegemony that can be observed. The findings suggest that indices of regional competitiveness can be of only limited help for policy-decisions besides although they are a source for a wealth of information on certain regional indicators. This is primarily because of the lack of a theoretical basis for measuring regional competitiveness, and secondly because of the poor performance in functioning as a proxy for future economic performance.

British Columbia is characterized by a relatively hierarchical urban system. This study aims to identify areas of potential for the development of Polycentric Urban Regions (PURs) to provide a counterweight to the dominant urban core and to develop higher functions in peripheral areas to increase their long-term viability. Three methods are employed to assess the spatial-functional and political-institutional dimensions of organizing capacity for the development of PURs: spatial analysis to determine proximity between population centres by driving time and distance; Pareto analysis to measure the existing degree of polycentricity in regional districts; and a survey of regional planners to assess their knowledge, current planning activities and attitudes towards polycentricity. Eleven areas with potential for PUR development were identified, which each have unique spatial and political challenges and opportunities. In general, many areas have good spatial conditions, but differences in the role of the regional district as a planning coordinator will make a common approach to PUR development challenging. In future studies of these regions, it is recommended to focus on the outcomes of PUR development and the benefits that could be realized in each region according to more specific local conditions.

This doctoral thesis investigates the process and problems of central (top-down) budgeting system of Iran and aims at exploring how it can be replaced with a decentralized (Bottom –up) model that may be more in line with the interests and expectations of regions of the country. In chapter 1, the trend of socio-economic planning in last decades (particularly after the Islamic revolution) is studied and the reason why access to the endowment of fossilized energy resources could not accelerate and pass current developing situation is reviewed. Then in chapters 2 and 3 a historical pathology of planning and budgeting system considering various conceptual understandings of planning and budgeting and their underlying effects on development indicators is discussed. To highlight the importance of participatory role of people in process of planning and budgeting, the concepts and characteristics of good governance and its possibility to implement in Iran is critically reviewed in chapter 4. Differences in the conceptual understanding of decentralization has urged the author to resort to questionnaires and face to face interviews with most experienced experts and scholars in the field of planning and budgeting in Iran, which are explained in detail in chapter five. Based on the compilation and classification of viewpoints of the respondents and concentration on the concept of good governance, chapter 6 of the thesis entails reformative guidelines which are presented in line with necessary changes in the basic rules and regulations governing the budgeting system of the country and has provided practical steps towards its realization. This thesis contributes to an initiative document for the adoption of executive policies in Iran's planning and budgeting system which eventually results in the improvement of living conditions and the development indices of the country.

Cette thèse se propose de mettre en perspective l’impact de l’environnement entrepreneurial, afin d'expliquer les raisons de la variation spatiale du niveau de développement régional pour les régions de l’Union Européenne et celles des régions tunisiennes. Cette inégalité régionale s’accompagne par une non-stationnarité spatiale des relations modalisées dans l’espace, ce qui implique que certaines variables peuvent avoir un effet positif dans quelques régions, alors que des effets négatifs sont observables dans d’autres régions. Pour aborder la question des inégalités régionales liées à une contribution entrepreneuriale dans un contexte spatiale, trois chapitres, sous forme d’articles, ont été développés. Le premier chapitre étudie l’hétérogénéité spatiale de l’impact de l’environnement entrepreneurial sur le développement des régions de l’Union Européenne. Le deuxième s’intéresse à la description des répartitions spatiales globales et locales de l’indice de développement régional en Tunisie, ainsi qu'à l’impact de la variation de l’effet de la micro-entreprise sur l’indice de développement des régions (délégations) tunisiennes. Le dernier chapitre explique les facteurs favorisant un environnement entrepreneurial adéquat pour attirer les micro-entreprises dans les régions (délégations) tunisiennes principalement défavorisées mais qui sont cependant dans une phase de développement.En se basant sur un échantillon composé de 246 régions de l’Union Européenne, les résultats du premier chapitre annoncent que l’environnement entrepreneurial contribue à expliquer les inégalités du développement entre les régions. Ce résultat révèle que promouvoir un entrepreneuriat d’opportunité face à un entrepreneuriat de nécessité dans les régions les moins développées de l’Union Européenne est une obligation, notamment dans les pays de l’Europe Centrale et Orientale. Le deuxième chapitre a pour objectif d’examiner l’effet de la micro-entreprise sur l’indice de développement des 262 régions tunisiennes à l’aide d’une analyse exploratoire des données Géo-référencées. Le résultat obtenu montre, sur la base d’un modèle spatial global, que la présence de la micro-entreprise dans une région impacte positivement le niveau de développement régional de celle-ci et de celles des régions voisines. A contrario, pour un modèle spatial local, nous constatons, d’une part que l'impact de la micro-entreprise s’affaiblit en se rapprochant des régions côtières (développées), et d’autre part que l'impact de la micro-entreprise est plus important dans les régions à faible niveau de développement par rapport à celles dotées d’un développement favorable. Les résultats du troisième chapitre affirment que l’entrepreneuriat par nécessité, un contexte social décourageant, la corruption, la faible fiabilité des structures d'appui et le déséquilibre entre la formation universitaire et l’offre d’emplois qualifiés sur le marché sont les facteurs majeurs freinant la survie de la micro-entreprise dans les régions en retard de développement
This thesis proposes to put into perspective the impact of the entrepreneurial environment, in order to explain the reasons for the spatial variation of the level of regional development for the regions of the European Union and those of the Tunisian regions. This regional inequality is accompanied by non-stationary spatial modalized relationships in space, implying that certain variables can have a positive effect in some regions, while negative effects are observable in other regions. To address the issue of regional inequalities in an entrepreneurial contribution in a context space, three chapters, in the form of articles, have been developed. The first chapter sheds light on the spatial heterogeneity of the impact of the environment on the development of the European Union Regions. The second focuses on the description of spatial distributions global and local index to regional development in Tunisia, as well as the impact of the change in the effect of the micro-enterprise on the index of development of the Tunisian regions (delegations).The last chapter explains the factors fostering an entrepreneurial environment to attract micro-enterprises in the (delegations) Tunisian regions primarily disadvantaged but are in a phase of development .Based on a sample composed of 246 regions of the European Union, the results of the first chapter announced that the entrepreneurial environment helps explain inequalities in development between the regions. This result reveals that promote entrepreneurship of opportunity in the face of the necessity entrepreneurship in the regions the least developed in the European Union is an obligation, particularly in countries of Central Europe and Eastern. The second chapter is aimed to consider the effect of the micro-enterprise on the development index of 262 Tunisian regions using an exploratory analysis of Geo-referenced data. The result shows, on the basis of a global spatial model, that the presence of the micro-enterprise or business in a region impacted positively the level of regional development and those of the neighboring regions. Conversely, for a local spatial model, we see, on the one hand that the impact of micro-enterprise weakens while approaching coastal areas (developed), and on the other hand the impact of the micro-enterprise is more important in the regions with low level of development compared to those with a favorable development. The results of the third chapter claim that entrepreneurship by necessity, a discouraging social context, corruption, low reliability of support structures and the imbalance between the academic training and supply of skilled jobs on the market are the major factors slowing down the survival of the micro-enterprise in under developed regions

Regional flood frequency techniques are commonly used to estimate flood quantiles when flood data are unavailable or the record length at an individual gauging station is insufficient for reliable analyses. These methods compensate for limited or unavailable data by pooling data from nearby gauged sites. This requires the delineation of hydrologically homogeneous regions in which the flood regime is sufficiently similar to allow the spatial transfer of information. Therefore, several Regional Flood Frequency Analysis (RFFA) methods are applied to the Ceyhan Basin. Dalyrmple (1960) Method is applied as a common RFFA method used in Turkey. Multivariate statistical techniques which are Stepwise and Nonlinear Regression Analysis are also applied to flood statistics and basin characteristics for gauging stations. Rainfall, Perimeter, Length of Main River, Circularity, Relative Relief, Basin Relief, Hmax, Hmin, Hmean and H&Delta
are the simple additional basin characteristics. Moreover, before the analysis started, stations are clustered according to their basin characteristics by using the combination of Ward&rsquo
s and k-means clustering techniques. At the end of the study, the results are compared considering the Root Mean Squared Errors, Nash-Sutcliffe Efficiency Index and % difference of results. Using additional basin characteristics and making an analysis with multivariate statistical techniques have positive effect for getting accurate results compared to Dalyrmple (1960) Method in Ceyhan Basin. Clustered region data give more accurate results than non-clustered region data. Comparison between clustered region and non-clustered region Q100/Q2.33 reduced variate values for whole region is 3.53, for cluster-2 it is 3.43 and for cluster-3 it is 3.65. This show that clustering has positive effect in the results. Nonlinear Regression Analysis with three clusters give less errors which are 29.54 RMSE and 0.735 Nash-Sutcliffe Index, when compared to other methods in Ceyhan Basin.

There are two objectives of this study. The first objective is to determine the domain of attraction of an extreme value distribution of gust wind speeds, at a selected station, when only limited samples from the site are available. The second objective is to perform a series of homogeneity tests for the selected stations, such that homogenous regions for these extreme gust winds may be identified. After carefully examining the wind data available, it was decided that 133 out of more than 750 stations in the contiguous United States were selected for the study. These selected stations all have confirmed Exposure C environments, with at least 15 years of records. All wind speeds used in this study were adjusted to 10 meters above ground level. On the basis of a S-statistic method, the proper representations of extreme gust winds at the 133 selected weather stations in the contiguous United States are examined. The results indicate that the annual extreme gust wind speeds at 65 out of the 133 stations are Gumbel extreme value distributions (Type I), whereas the other 68 stations' extreme gust wind speeds are reverse Weibull (Type III), distributed. Nine homogeneous regions, for the annual extreme gust winds, were identified by applying a Type I based regional analysis. This analysis was applied to the 65 stations in the contiguous United States whose annual extreme gust winds are Type I distributed.
x, 92 leaves

Parametric methods, currently used in regional flood frequency analysis, have numerous drawbacks and limitations, especially with regard to flood distribution selection and regional relationship form. Alternative approaches involving nonparametric methods are investigated in this thesis on a set of New Brunswick annual maximum floods. Nonparametric methods were employed at the three steps of regional analysis: at-site flood frequency analysis, homogeneous region delineation and regional relationship development. Nonparametric flood frequency analysis indicated that an annual maximum flood data set from New Brunswick contained some unimodal distributions along with many mixed distributions of bimodal and heavy-tailed shapes. A simulation study showed that sampling variability from a unimodal distribution could not account for the bimodality in nonparametric frequency analysis, confirming the existence of mixed distributions. L-moment analysis, a parametric method, confirmed that the entire set of floods from New Brunswick could not be appropriately described by a unimodal distribution. In this study, a new method is proposed for the purpose of homogeneous region delineation which effectively combines geographical considerations and flood data characteristics. The technique is based on the grouping of stations with similar density function shape, which reflect similar flood generating mechanisms. In New Brunswick, flood densities of three different shapes were grouped on a geographical basis to delineate homogeneous regions. Statistical tests based on L-moment analysis confirmed that the stations within a homogeneous bimodal region came from the same distribution. But L-moment analysis would propose either the Generalized Logistic or the Generalized Extreme Value as the regional distribution. Nonparametric frequency analysis revealed, however, that the floods within that region actually came from a mixed distribution. Nonparametric regression was employed for regional relationship development in New Brunswick; however, no significant improvement over the parametric approach of linear regression resulted. Using bootstrapping of pairs, a new method to compute the confidence interval at the center of a nonparametric regression was investigated. A comparison of linear and nonparametric regression confidence intervals can assist in evaluating the appropriateness of a linear model, and thus the need to employ nonparametric regression. Nonparametric regression was shown to be useful in screening irrational relationships that could be developed with the parametric approach. A new regional analysis methodology, involving nonparametric methods at the three steps of regional analysis, is proposed in this study, resulting in improved homogeneous region delineation, in more accurate at-site quantile estimates, and more realistic regional relationships.

Watershed models can play an important role in regional planning. Their ability to consider large, spatially diverse regions and assess the impact of different land use scenarios on water resources can lead to better, more informed decision making. Recent legislation in Ontario has led to the adoption of watershed models as part of drinking water source protection planning processes. In this study, the ability of the SWAT model to simulate the hydrology of the Raisin River watershed, an area of 556km2 located in eastern Ontario, is examined. The model was calibrated using data from 1985 to 1994 and validated using data from 1995 to 2004. Weekly average flow rates were used to evaluate the model, producing a Nash Sutcliffe coefficient of 0.798 for the period of calibration and 0.788 for the validation period. Model error is most significant during the annual snowmelt period, suggesting deficiencies in the way snowmelt is modeled. Baseflow predictions are correct on an annual basis but exhibit more volatility than the observed flow. The Nash Sutcliffe coefficient is a common measure of hydrologic model performance but suffers from being strongly biased to certain times of the year. Specifically, it is insensitive to periods of low flow which are important for source protection planning. The possibility of transforming the observed and predicted flow rates to compensate is discussed. The methodology presented takes advantage of readily available standardised data, permitting a similar modeling exercise to be easily undertaken for a different region. Results and analysis as presented could be used directly in the development of source protection plans. Spatial and temporal variation of water budget components (runoff, recharge and evapotranspiration) throughout the watershed is discussed. The impact of land use and soil type on the water budget is also highlighted.
Les modèles de bassin d'eau peuvent jouer un rôle important dans la planification régionale. Leur capacité de considérer de grandes régions, diverses en espace et évaluer l'impact de scénarios d'utilisation de différentes terres sur des ressources en eau peut mener à des prises de décisions meilleures et plus informées. La récente législation en Ontario a mené à l'adoption de modèles de bassin d'eau faisant partie de processus de planification de protection de source d'eau potable. Dans cette étude, la capacité du modèle SWAT (Outil d'évaluation du sol et de l'eau) pour simuler l'hydrologie du bassin de la Rivière Raisin, un secteur de 556km2 situé à l'est de l'Ontario, est examiné. Le modèle a été calibré au cours de la période de 1985 à 1994 et validé au cours de la période de 1995 à 2004. Des débits hebdomadaires moyens ont été utilisés pour évaluer le modèle, produisant un coefficient Nash Sutcliffe de 0.798 pendant la période de calibrage et 0.788 pendant la période de validation. L'erreur modèle est la plus significative pendant la période de fonte de neige annuelle, suggérant des manques dans la manière que la fonte de neige est modelée. Les prédictions du débit de base sont correctes sur une base annuelle, mais exposent plus de volatilité que le flux observé. Le coefficient Nash Sutcliffe est une mesure commune de performance du modèle hydrologique, mais souffre en étant fortement influencé par certains temps de l'année. Spécifiquement, il est insensible aux périodes de bas débit qui sont importantes pour la planification de la protection de source. La possibilité de transformer les débits observés et prévus pour indemniser est discutée. La méthodologie présentée profite de données standardisées aisément disponibles, permettant à un exercice de modélisation semblable d'être facilement entrepris pour une région différente. Les résultats et l'analyse tel que présentés pourraient$

In recent years, particularly post 1990 and contrary to the expectation and predictions of many economists, there is ample evidence that the informal economy has expanded globally (Schneider et al., 2010). This, in addition to finding out the potential of the informal economy, has sparked renewed interest amongst researchers. Until now, however, most of the ‘empirical’ studies have concentrated on the Asian and Latin American countries (Debrah 2007), and most methodological approaches for studying the concept have remained debatable (Aryeetey, 2010). This thesis seeks to close a gap in the literature by developing two novel research frameworks: the Individual, Firm and State (IFS), and Four Circles (4Cs) to explain the link between theories and methods, as well as the impacts and benefits, of the informal economy. The study also utilises secondary and collected-primary data, modified-MIMIC and Currency approaches, to explore the determinants, characteristics, and regional prevalence of the Nigerian informal economy, as well as the relationships between the Nigerian informal economy and key macroeconomic variables/business enterprises. The results of the study demonstrate that the Nigerian informal economy has 65.4% participation rate, contributes an equivalent of 52-53% of official GDP, and provides cheap and easily accessible goods/services to members of the public, income generation for the government, and job, income and poverty reduction for informal participants. However, participants in the sector are confronted with many challenges: inadequate finances, inconsistent government policies, unfriendly business environment, and inadequate infrastructures. Similarly, the main determinants of the Nigerian informal economy are population growth, corruption, unemployment, and survival factors. Also, the study reports significant regional differences in participants’ income and education levels. Finally, the study finds the informal economy more prevalent in the north-west and south-west regions of Nigeria. Recommendations are proposed on the basis of the IFS; individuals and firms operating in the informal economy are encouraged to build up skills and become membership of relevant-trade unions. The government should implement policies which facilitate the creation of jobs, friendly business environment, entrepreneurial development, financial and training support for participants in the informal economy.

This thesis studies the effect of innovation activities and productivity by using the CDM-model and extend the existing knowledge by using the CIS-dataset in combination with official statistics performing a such detailed regional analysis that have not been done before. By using the different labour market codes interacted with the industry codes I can capture informative deviations between different industries in different regions. The results show a significant variation between the different regions and industries, and that the urban and metropolitan areas are more innovative and more productive than the rural areas. However, the financial sector and health sectors showed a steady innovation input activity across most regions while the metropolitan areas showed to invest less in innovation inputs in the real estate sector compered to rural and urban areas.

Lung function depends on the expansion and contraction of lung tissue during the respiratory cycle. The measurement of regional pulmonary function is of great interest and importance since many lung diseases can cause changes in biomechanical or material properties. It is also significant to study the radiation-induced changes in pulmonary function following radiation therapy. In this thesis, we propose a technique that uses four-dimensional (3D+time) CT imaging (4DCT), 3D non-rigid image registration to estimate regional lung function. Lung images reconstructed at different inflation levels are analyzed for dynamic lung function development during a breath cycle. We demonstrate local pulmonary function can be reproducibly measured using 4DCT in human subjects prior to RT. The image registration accuracy is validated using semi-automatic anatomic landmark picking system. The major contributions of this thesis include: 1) demonstrating the robustness and reproducibility of regional pulmonary function measurement using 4DCT in both sheep and human subjects, 2) developing approaches to improve the measurement reproducibility by dynamic lung volume matching and Jacobian normalization, 3) development and comparison four cubic metrics for reproducibility analysis, 4) research on time-varying lung ventilation in different breathing phases in both sheep and human subjects. Our contributions in this thesis are useful for diagnosis and assessment of lung diseases, useful for qualifying radiation induced changes in pulmonary function in irradiated and non-irradiated lung tissue.

Improving the capacity to make predictions in ungauged basins is one of most difficult challenge for the scientific community (see for example the current initiative Prediction Ungaged Basins (PUB) launched by the International Association of Hydrological Sciences, IAHS). Whatever hydrological models are used, in view of the tremendous spatio-temporal heterogeneity of climatic and landscape properties, extrapolation of information, or knowledge, from gauged to ungauged basins remains fraught with considerable difficulties and uncertainties, especially in the light of the generally poor understanding of where water goes when it rains, what flow path it takes to the stream, and the age of the water that emerges in the channel. The PUB problem is the key concept of this thesis and it is analysed from several point of view. Methodologies able to observe, model and predict the hydrological response at the regional scale are proposed.

Global assessment of myocardial function is widely performed by estimating ejection fraction (EF), but many common cardiac diseases initially affect the myocardium on a regional, rather than global, basis. Computed tomography (CT), most commonly applied to assess the coronary arteries, is a prime candidate for such regional analysis. This doctoral thesis makes steps towards regional CT functional analysis with two clinical and two technical contributions. The first clinical contribution focuses on evaluating the feasibility and utility of functional analysis with currently available CT technology. Our study found that CT strain analysis could identify regional wall motion abnormalities in cardiomyopathy that are not otherwise detected using conventional metrics of myocardial function such as EF. In order for cine CT of the heart to become routine clinical practice, improvements need to be made to the image acquisition protocol. The second clinical contribution focus on making these improvements with results pointing to the possibility of one millisievert range cine CT images with high (>50 milliseconds) temporal resolutions. Moving to technical considerations, a key concern has been how to better characterise the myocardium in CT. To address this, the first technical contribution examines the use of feature-based attribute vectors, which were found to improve image registration towards deriving more reliable motion estimations. The second technical contribution focus on developing a pipeline tailored towards CT strain analysis. Noting that CT naturally provides information in 3D, a 3D hyperelastic biomechanical model fitting method was evaluated. Analysis of an infarction model demonstrated that regional myocardial strain can be estimated in the 3D space and areas of infarction can be detected. By considering both technical and clinical perspectives, these advances will contribute to the the field of regional cardiac functional analysis towards improving patient care.

The Swedish regions are new phenomena, from the start from the new regionalism which started in the 1980´s. The purpose of the thesis is to analyze Region Skåne and Västra Götalandsregionen to come to a conclusion which model of region they are and want to be by using theories of regional identity and identity of politics and see similarities and differences. My research question is: Which of cultural, administrative and functional region are Region Skåne and Västra Götaland striving to construct?    The methods I have used are qualitative text- and content analysis to analyze the regions, by using theories about regional identity and identity of politics. Furthermore, I am using some statistic from SOM-institutet to analyze the regional identity in the regions.    The result show that Region Skåne is constructing a cultural region, because of their strong regional identity and that the politicians are using identity of politics to combine the citizens. The citizens feel a strong fellowship and share a common history and culture.    However Västra Götalandsregionen is an administrative region, there their regional identity is low and do not have a common history and culture. There the politicians’ focus is on administrative things, as research and communication.

This research is concerned with examining market segments and regional variations associated with winery visitors in the state of Virginia. The tourism literature published by the state of Virginia for wineries indicates that there are five wine regions. In this research, data were collected from interviews conducted at wineries in each of the five wine regions. The first phase of analysis sought to create market segments using a factor-cluster approach. Segments were created using cluster analysis and multiple discriminant analysis. Three distinct market segments based on benefits sought by the visitor emerged from these data. Regional variations were examined in the second part of this study. The data were classified into individual regions based on the locations of the wineries examined. Distinct differences in the regional profiles were revealed. Weak significant relationships among the segments and regions were also revealed through analysis indicating a spatial component to the segments. This research proposes the use of three regions for market research purposes, while retaining the five existing regions for promoting an organized structure to visiting wineries in the state.
Master of Science

The concept of Region is one of the elements which has differentiated Regional Economics from other fields of Applied Economics. In spite of this, however, researchers in this field of economic analysis have not paid a great deal of attention to this concept. All too often, Regions have been identified with the politico-administrative units into which nationstates have divided their territory and for which statistical information is widely available. However, a Region can be defined in many different ways. Frameworks which define regions according to analytical/theoretical criteria provide greater scope for applied studies and permit a more complete interpretation of the results contained therein. In this research we have proposed a concept of Region which goes beyond the administrative division of territory. Our regional aggregation has been based on agglomeration economies, one of the fundamental concepts in the fields of Economic Geography and Urban and Regional Economics. In accordance with the work of Polèse et al. (2007), the territory has been classified into analytical regions which take into account the size of the population and the distance from the main urban areas. In doing so, we achieve an aggregation which corresponds with the differences in agglomeration economies across space. However, their robustness in comparison with the administrative units commonly used has - to date - not been evaluated.The objective of the first chapter of this thesis was to prove that the functional regions defined under such economic criteria provide better defined regions - in terms of greater compactness and separation - than the administrative ones commonly used to carry out labour market studies at sub-national level. Using micro data from the last available Spanish Census, the functional and administrative regions are evaluated using the Theil index and the Davies-Bouldin Validation index. Applied to employment (by gender, industry and level of qualification and occupation), both indexes show better results for the analytical regions than for any of the ordinary administrative ones (NUTS I, II or III regions). In other words, the analytical classification generates areas where the distribution of employment is more homogeneous within and more heterogeneous between the regions. Agglomeration economies and distance (to the metropolis) seem to be relevant for understanding the patterns of distribution of employment, either by gender, by industry or by level of qualification and occupation. In practice, this provides a clearer way for identifying local labour markets and explaining their differences and similarities. In light of the results from the first chapter, we suggest the use of this alternative classification -subject, of course, to the availability of data - when carrying out Labour Economics studies that include a spatial dimension. The following chapters have provided two applications of this analytical division of the territory to Labour Economics issues: the factors affecting the probability of being employed (Chapter 2) and the effects that labour mobility and commuting have on the central regions (Chapter 3). In the second chapter, we presented a spatial analysis of employment at local level where, among other factors, the demographic and geographical characteristics can and do affect the outcome. The empirical results support the hypothesis that size - in terms of population - and location - in terms of distance to a metropolis - are explanatory variables for the probability of being employed. In other words, employment depends not only on the personal characteristics of the individuals (level of education, age, sex, etc.) but also on the type of analytical region - as defined in Chapter 1 - where they live. Regarding the importance of location, our results show a significant gap in the chances of being employed between "central" and "peripheral" types of regions, i.e., the closer the region is to the metropolis, the higher the concentration of economic activity and therefore employment. Likewise, the types of regions, i.e., the closer the region is to the metropolis, the higher the concentration of economic activity and therefore employment. Likewise, theexpected negative relationship between employment and the size of the region where the individual lives is confirmed, and this seems to be stronger for non-skilled individuals than for people with university studies. In terms of employability, the largest Spanish metropolitan areas (MA1) seem to be enjoying the full benefits of agglomeration economies while the smaller metropolitan areas (MA2) seem to be suffering their negative effects. Likewise, for urban areas that cannot be considered "metropolitan areas" (UA1 and UA2), size does not seem to be as important as their central-peripheral location. In rural areas (less than 50,000 inhabitants), both size and distance seem to be relevant determinants of employability. In other words, regardless of the level of studies, there are fewer chances of being employed in rural areas as opposed to urban areas and in peripheral rural areas as opposed to central rural areas. Recognizing the importance of these spatially differentiated results should have a significant impact on current policy discussions, shifting the focus from general solutions to more spatially customized ones where size and location are considered. Just as differences in age, gender or industrial structure are taken into account in the design of employment policies (at national or local level), these results suggest that an additional spatial dimension that somehow includes the size and location of the local area where the person lives should be considered. Some important migration policy implications can also be derived when using these alternative functional regions to analyze the direct and indirect effects that the arrival of workers has in the core regions. Spain has experienced over the last two decades an intense arrival of both immigrants and in-migrants to its central regions, and as a consequence (though not exclusively) of these inflows, we can observe internal migrations and/or commuting to some areas that might be more attractive. Using the last available Census, the estimations for Spain of an input-output multi-regional model that includes the possibility of commuting show that the arrival of in- and im-migration to the core generates a set of effects induced by the redistribution of population among other regions. The arrival of workers from the periphery to the core provokes reallocations of residence in all cases (displacement effect).However, the intensity of these reallocations increases with size, which shows the existence of some agglomeration diseconomies associated with big cities. When the possibility of commuting is also considered, the arrival of workers from the periphery to the core generates the reallocation of both jobs (economic activity) and residences. The larger cities are the ones pushing out more residents to other areas, while keeping most of the jobs. In other words, they are becoming attractive areas to work in, but not to live in (due to, among other reasons, high housing costs, congestion or other negative externalities). The oppposite is true for the smaller cities, which are attractive for residing in but for working in. The distributional pattern of residences proves to be different to the distributional pattern of jobs. These results highlight the idea that the effects of the arrival of population are not only felt by the recipient region/city but may generate comparatively far larger effects on other regions in the form of internal migration and commuting flows, something that policy makers should bear in mind. To conclude, surpassing the administrative division of the territory, this classification manages to have explanatory power in spatial Labour Economics topics while including relevant geo-economic characteristics such as location and agglomeration economies. The use of this classification has proved to offer a better understanding of the patterns of distribution of employment (by gender, by industry or by level of qualification and occupation), job opportunities, and of the probabilities of being employed depending on the level of qualification or the degree of attractiveness of a region for working or living purposes. Some other questions spatially related to the performance of regional labour markets remain unanswered. Future lines of research include the application of this classification to the study of labour economic issues such as the determinants of unemployment, inter-industrial labour mobility or the existence of overqualification taking into account spatial factors (i.e. the type of analytical region where the potential worker lives) which are usually ignored.Agglomeration economies and distance play an important role in the location of economic activity, and therefore should affect the labour outcomes once the worker has decided to live in certain type of region. Obviously, such a decision does not have to be permanent, and workers can move in order to improve their labour opportunities. Therefore, a further possible question of relevance is the internal migration decisions between and within analytical regions. That is, can certain regularities be observed? Are people moving from peripheral regions to central or metropolitan areas or the other way round? Are internal migrations better explained in terms of size, i.e. in terms as counter-urbanization or urbanization? Are these movements linked to job opportunity decisions? Can we observe any differences according to their level of qualification? Even more, workers can be employed in a certain type of region but live in another, i.e., we could observe migration on a daily basis (commuting). Is one type of analytical region attracting workers or attracting residents? Do people tend to live and work in the same type of region? Could the analytical division be improved in order to specifically include the commuting criteria used in the local labour markets literature? We believe that these questions provide a fascinating and important future research agenda.

Phosphor (P) ist ein für alles Leben notwendiges essentielles Nährelement. Die heutige globalisierte und intensivierte agrarische Produktion benötigt daher die Anwendung großer Mengen Phosphatgesteins, welches eine endliche Ressource darstellt. Gleichzeitig ist der intensive P Gebrauch mit der Eutrophierung von Gewässern verbunden. Es besteht daher Forschungsbedarf um die landwirtschaftliche Produktion zu erhalten. Ziel dieser Arbeit ist die in der Region Berlin-Brandenburg nach Ansatzpunkten für ein verbessertes P Management zu suchen. Hierfür wurde für 2011 eine Substanzflussanalyse (SFA) für P erstellt und Pflanzenproduktion der Jahre 2005-2012 genauer untersucht. Mit Hilfe einer Briefumfrage wurde Daten von 119 Bauernhöfen ausgewertet und mit dem pflanzenverfügbaren P Gehalt (PVP) der landwirtschaftlichen Nutzfläche abgeglichen (LNF). Im Ergebnis zeigt sich für die Region eine negative P Bilanz der LNF(-3.617 t P) und ein hohes Recyclingpotential in Abfall (933 t P) und Abwasser (3.921 t P). P in mineralischen Düngemitteln belief sich auf 4.447 t. Der Gesamtentzug über die Ernte ohne Stroh betrug 15.283 t P und war vergleichbar zu 2006, das Jahr des geringsten P-Entzugs. P-Entzug durch die Ernte schwankte um 7.069 t P/a von 2005 bis 2013, abhängig vom Ertrag der Hauptfeldfrüchte, welche durch die Wetter- und Bodenbedingungen bestimmt wurde. Hieraus ergeben sich mögliche Konsequenzen für P-Flüsse in Bezug auf den Klimawandel, die an den Wasserhaushalt und die Temperatur gekoppelt sind. Die Analyse der Umfrage ergab, dass die kleinen und mittgroßen Einzelunternehmen höhere PVP Werte in der LNF aufwiesen. Die größeren Unternehmensformen regierten empfindlich auf Faktoren, die niedrige PVP-Werte begünstigten. Pacht, Grünland, extensive Rinderhaltung, und viehlose ökologische Landwirtschaft waren mit niedrigen PVP-Werten assoziiert. Biogasanlagen und intensive Tierhaltung, zum Teil auch in Kombination miteinander standen im Zusammenhang mit hohen PVP-Werten.
Phosphorus (P) is an essential nutrient for all life on earth and it is thus needed in agricultural production. Today’s globalized and intensified agricultural production has led to the dependency on P inputs which are fed by phosphate rock, being a finite resource. In contrast, excessive P is a major driver in eutrophication. To sustain agricultural production, there is a need to address this problem. The aim of this thesis was to identify points at which P management could be improved for the region Berlin-Brandenburg. To analyze the system and screen for improvement, a substance flow analysis (SFA) for P for the year 2011 was compiled and for crop production the years 2005-2012 were analyzed. Also, data from 119 farms was obtained by a letter survey and relations between farm structural factors and soil test P (STP) were drawn. The results showed a negative balance for agricultural soils (-3,617 t P) and a considerable recycling potential in waste (933 t P) and wastewater (3,921 t P). Mineral fertilizer inputs amounted to 4,447 t P. P removal by crops was 15,283 t without straw and residues, being almost as low as in 2006; the year with the lowest removal by main crops. P removal by harvest varied significantly (7,069 t P/yr from 2005 to 2013) and depended on the performance of main crops which in turn is influenced by weather and soil. As a result of this, climate change may interact significantly with P flows in agriculture. Here, important variables are connected to conditions in P uptake and plant growth in general (e.g. water supply and temperature). The analyses of farms in the region showed that individual farms of small to medium size had more land with (very) high STP. Larger partnerships and companies/cooperatives were susceptible to factors causing low STP. Tenancy, grassland, extensive cattle and stockless organic farming had a lowering effect on STP. Biogas plants and intensive (cattle) farming, partly combined, were connected to a rise in STP.

The purpose of this work is to develop a preliminary interior design of a regional aircraft considering ergonomic and cost aspects. The use of virtual humans provides a better interpretation of the aircraft interior environment, making possible to simulate movements and passenger comfort aspects. The importance of this study becomes evident through the necessity of the aircraft manufacturer of predicting human behavior during all the flight phases. This text also aims to present the difficulty to accomplish the design requirements and at same time meet the market expectations without oversizing the aircraft. The dissertation is applied to an aircraft (called "Unique") developed in the context of the EMBRAER Engineering Specialization Program (PEE) and includes different features of the aircraft interior environment as: cross section definition, seat configuration and passenger cabin layout. The ergonomics analysis comprises the living space (distance between seats) and oxygen mask accessibility. The used method was RULA tool (available in the Catia V5 package) that evaluate individuals' exposures to limb disorders like postures, forces and muscle activities that have been shown to contribute to Repetitive Strain Injuries (RSIs). A preliminary cost analysis is also presented by comparing a standard (30 pax at 32" seat pitch) and an advanced (28 pax at 30"/36" seat pitch) aircraft interior configuration.

It is generally acknowledged that economic activity continues apace and at the expense of social and ecological integrity while the course of economic development remains far from any approximation of sustainability. Few would dispute the fact that since 1992 little has been accomplished in practical terms to meet Agenda 21 objectives. Many would agree that Agenda 21-inspired local visions and goals have not translated into actual local change in part because of the complex and the multi-faceted nature of the issues involved. Policy work on ecological modernization and sustainability needs to be explicit on the question of scale and the role of governments. The central challenge for policy makers, action takers, and researchers is to determine the appropriate territorial (physical, social, economic, and political) scale at and through which government power needs to be deployed to effect transition to sustainable modes of regulation. This question is particularly relevant given the current discourse on regionalization / globalization. Adopting a 'post-disciplinary' approach this thesis examines how institutional inter-relations shape the outcome of plans to meet policy objectives on sustainable development at the local (municipality) scale. In-depth analysis of interview and secondary data reveals that numerous factors 'regulate' what occurs at local and other scales in relation to sustainable development. This thesis concludes with exploring the policy and future research implications of the findings.

Il contesto di studio è l’analisi del Piano Socio Sanitario Regionale della Regione del Veneto in seguito alla sua approvazione con la Legge Regionale n. 48 del 28 dicembre 2018. L’elaborato si divide in tre capitoli: nel primo capitolo viene approfondito il Servizio Sanitario Nazionale, dalla struttura alle funzioni, dalle forme di finanziamento all’evoluzione non solo normativa ma anche organizzativa del Servizio Sanitario Regionale del Veneto. Attraverso un percorso logico si informa il lettore del funzionamento del sistema salute in Italia e nel Veneto. Il secondo capitolo tratta il tema principale di questa tesi, l’analisi del Piano Socio Sanitario Regionale del Veneto, in vigore nel prossimo quinquennio. L’analisi che è stata effettuata verterà sugli attori (dal cittadino al personale), sui modelli organizzativi (in particolare il modello di rete e il modello di integrazione sanitaria) e sui contenuti principali del Piano, che riguardano gli obiettivi necessari allo sviluppo dell’assistenza socio sanitaria. Nell’ultimo capitolo si tratta l’utilizzo degli strumenti necessari per raggiungere gli obiettivi prefissati dal Piano, specificando i sistemi informativi e gli sviluppi in ambito ICT che potranno portare ad un miglioramento e all’innovazione del sistema sanitario.