Dissertations / Theses on the topic 'Input-Output Analysi'

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.

This thesis studies a theory for the amplification of technological improvement by the production network structure of the economy. The theory is motivated by the idea that, to the extent that inputs and outputs of industries form a chain, improvements are passed down the chain and accumulate multiplicatively. Under a simple model for technological improvement it is possible to compute the overall improvement factor for the general case where the production network has a complicated structure containing cycles. We call this the trophic depth by analogy with ecology. This leads to testable predictions about GDP growth and its variance. We analyse data for 40 countries and 35 industries from 1995 to 2009 and demonstrate that trophic depths are strongly correlated with economic growth. A regression of GDP growth of countries against their trophic depths has a highly statistically significant R-squared equal to 0.38, and when other standard explanatory variables are added to the regression, the trophic depth remains a robust and statistically significant contributor. We perform some statistical analysis to understand the evolution of trophic depths at different stage of the economic development. We identify two growth paths. Along the first growth path, countries are catching up frontier economies while along the second growth path countries are falling behind. This approach allows us to make some forecasts about the evolution of trophic depths and of the wealth of countries. This provides a comprehensive framework to understand the acceleration and deceleration of economic growth. Then, we study another type of technological progress that corresponds to the adoption of new goods in the production chain. This mechanism is related to the dynamic of the production network and for this purpose we perform a link prediction analysis to determine some key factors for new adoptions. Finally, we analyse the relation between stock return comovement and institutional preferences across stocks of various size. A growing literature highlights the role of investors' common asset holdings on market dynamics. While previous studies focused on large stocks we also include small stocks in the sample in order to acknowledge the shift in institutional preferences towards small stocks over the last decades. Moreover, we add the input-output linkages between firms from different industries to our set of explanatory variables.

The aim of the dissertation thesis is to develop a methodology of the compilation of symmetric Time Input-Output tables under the conditions of the Czech Republic. The following aim is to create an input-output model which is based on the compiled symmetric Time Input-Output tables. For the practical applications of this model it is crucial to link the created Input-Output model with the Semi-Dynamic Input-Output model. Semi-Dynamic Input-Output model in the conception of the submitted dissertation thesis takes into account several multiplier effects and presents more comprehensive tool for the use of the Input-Output analyses in this way. The first chapter focuses on the development of the issues linked to the Input-Output tables and analyses on the territory of the Czech Republic and in the world as well. The second chapter which is also theoretical is focused on mapping of different kinds of Input-Output analyses which are done in the world using Physical, Time or Hybrid Input-Output tables. The third chapter is a purely methodological because here it is described the methodology of the compilation of symmetric Time Input-Output tables as well as methodological approach to the various sensitivity analyses. The fourth chapter focuses on the creation Semi-Dynamic Input-Output model and on the formal linking with the Input-Output model based on the Time Input-Output tables. The last fifth chapter is focused analytically. Methods described in the third chapter are applied on the official published data on the Czech economy. The analytical chapter is perceived in the submitted dissertation thesis as a tool for the sensitivity analysis in the sense of validation of the quality of the compiled Time Input-Output tables.

First, the thesis investigates the interrelationships between the forestry sector and other components of the rural economy, through the application of the Generation of Regional Input-Output Tables (GRIT) technique to the estimation of an input-output table for the rural areas of Scotland. This is followed by a forestry-centred multiplier analysis. Second, the thesis considers the implications of alternative forestry development scenarios in Scotland over the next several decades for land use, timber production and processing, agriculture, and rural employment. Six alternative afforestation scenarios ranging from 'no further planting' to 'accelerated expansion' are defined, including 'lowland' and 'green forestry', and a 'most-likely' scenario. This analysis is carried out through a simulation model which is built on a spreadsheet, and consists of base-period data and parameters, followed by successive projected decade blocks. Taking account of labour productivity trends in both forestry and agriculture, scenario-specific calculations produce future values of forest area, wood output, transfer of farmland, displaced agricultural employment, and forest employment created. A distinction is drawn between current (decade-specific) and accumulated (rotation-specific) forest jobs created on transferred agricultural land and existing forest areas. In this way, the future implications of different assumptions as to future forestry policy are produced. Finally, scenario-specific projections for the year 2050 concerning new planting area and total wood production are converted into gross input value estimates for the Forestry Planting and Harvesting sectors. Alternative assumptions which represent extremes of correspondence between the domestic Forestry and Wood Processing sectors yield new levels of gross national (Scottish) output. The adjustment of the national input-output tables is then followed by their regionalisation through the application of GRIT and the estimation of scenario-specific regional direct, indirect and induced output, income and employment effects.

The main focus of the thesis is to derive stability criteria for networked control system (NCS) models featuring imperfections such as time-varying and constant delays, quantization, packet dropouts, and non-uniform sampling intervals. The main method of proof is based on matrix algebra, as opposed to methods using Lyapunov functions or integral quadratic constraints (IQC). This work puts a particular focus on handling systems with a single integrator. This framework is elaborated in different specific directions as motivated by practical realizations of NCSs, as well as through numerical examples. A novel proof of the discrete time multivariate circle criterion and the Tsypkin criterion for systems including a single integrator is presented, as well as a stability criterion for linear systems with a single integrator subject to variable sampling periods and sector-bounded nonlinear feedback. Four stability criteria for different classes of systems subject to packet loss and time-varying delay are given. Stability criteria for a closed loop system switching between a set of linear time-invariant systems (LTIs) are proved. This result is applied to a single-link NCS with feedback subject to packet loss. Finally, necessary and sufficient conditions for delay-independent stability of an LTI system subject to nonlinear feedback are derived.

This thesis involves construction of input-output models measuring the economic impact of a farming innovation organisation (The Birchip Cropping Group) on the Victorian regional economy of Buloke Shire. The input-output modeling undertaken is of two forms; the first being a simple naïve top-down model, and the second a more sophisticated hybrid model. The naïve top-down model is based on input-output coefficients drawn from the Australian national input-output tables, and is regarded as naïve because these input-output coefficients are not adjusted to take account of local economic factors. The hybrid model uses the same national input-output coefficients as a base, and then modifies these coefficients to better reflect industrial conditions in the Shire using a location quotients-adjustment technique, as well as using original survey data collected from entities operating in Buloke Shire. One of the aims of the thesis is to determine whether the simpler naïve top-down approach produces results consistent with the theoretically more accurate hybrid methodology, and thus whether the naïve top-down approach represents a reliable method of conducting regional economic impact analysis. That is, can such studies be undertaken accurately using a naïve top down approach, or is it necessary to adopt the more resource intensive methodology of a hybrid model. The results of the analysis suggest construction of a hybrid model is advisable, as generally the naïve top-down approach produces over-estimates of the economic effects of the Birchip Cropping Group. That is, it appears the economic impact multipliers estimated with the naïve top-down model are too large, suggesting the time and effort involved in constructing the hybrid model was worthwhile. Using the hybrid model, the conclusion is that the Birchip Cropping Group has a significant affect on the regional economy of Buloke Shire, with the economic impact being estimated at close to $600,000 in additional output, $61,000 in additional income, and 3.5 additional jobs per year.

The Duncan Hunter National Defense Authorization Act for Fiscal Year 2009 mandates that the Fully Burdened Cost of Fuel, including the total cost of procuring and transporting fuel, infrastructure operating costs, and the cost of force protection for the logistics tail, be applied in trade-off analyses for all Defense systems that create a demand for energy. Using data from the Defense Logistics Agency Energy, this thesis builds a model of its worldwide supply chain for bulk fuels, and uses the principles of input-output analysis to calculate the total cost to deliver three fuel types to each destination in the supply chain. Although the Defense Logistics Agency Energy charges a standard price to each service for bulk fuels, these results show that they incur very different costs, ranging from less than a penny per gallon to over 70 cents per gallon, to deliver to different locations. Given the appropriate data on services' fuel distribution networks, a Defense-wide extension of the Bulk Fuels Distribution Model could be used to replace the current seven-step Fully Burdened Cost of Fuel process with a single step, allowing for less complex and more accurate Fully Burdened Cost of Fuel calculations.

This thesis examines the existing theories and applications of Multivariate Statistical Process Control, outlines areas of difficulty and proposes a new technique of multivariate process control chart with input-output relationship for optimal process control. The process control techniques developed up to the present time focused on the fast detection of out-of-control signals, and achieved considerable success in that respect. The techniques reported on multivariate process control thus far include extensions of univariate process control charts to their multivariate counterparts, ranging from classical Shewharts charts to modern Cumulative Sum Process Control charts. Alternative approaches in this area include Principal Component Approach, Partial Regression approach, Baysian modelling and sequential tests on detection of change points. Although each method has its own limitation, these new developments have significantly contributed to the achievement of a constant high quality of products and services. The techniques of process control are yet incomplete. They require continuous attention, as production and service technologies are being continuously developed.In particular, the level of automation, re-engineering of production processes and ever demanding economic optimality of technology demand the re-engineering of statistical process control. The CFM chart developed in this thesis would open the door to this area of science and lays a critical foundation for future research
Doctor of Philosophy (PhD)

This diploma thesis discusses utilization of dynamic Input-Output models as a basis for decision-making for policy makers. The first part is focused on theoretical derivation of the basic dynamic models. This part is followed by a practical application of the presented models, which proposes a method of deriving the matrix of capital and it facilitates the construction of data sources. The results show that the dynamic models are usable, but it is necessary to take into consideration their structural constraints and data limits. Data applied for 2009 show that the economic crisis has led to a 6% decline in GVA growth rates.

Accounting for social impacts in supply chain analysis is of increasing importance. Global trade has increased significantly since 1970, as has inequality. As global supply chains have become more prevalent, the need to understand and analyse these supply chains has also grown. Excellent work on quantitative analysis of environmental impacts in supply chains has taken place in the past two decades. However, relatively few methodologies have been applied to quantitative analysis of social impacts in supply chains. This thesis considers how social indicators for supply chain analysis can be developed through the use of socially extended multi-regional input-output analysis. Chapter 1 provides an introduction and context. Chapter 2 considers the history of social accounting. Chapter 3 looks at quantitative accounting for social-economic indicators and the development of national accounts, particularly in reference to standardised collection of data for social-economic indicators and socially-extended input- output analysis. Chapter 4 presents a case study of coltan mining and methodological analysis using deaths in the Democratic Republic of Congo as a social indicator for the electronics supply chain. Chapter 5 analyses the results of the same case study and considers how enumerating social impacts in upstream supply chains can influence environmental and social justice actions in downstream supply chains. Chapter 6 provides a review of input-output analysis used as a tool for analysing consumption since 2010. Chapter 7 proposes the use of a suite of quantitative social indicators for analysis in the form of a social footprint. Chapter 8 provides a conclusion. This thesis tracks the author’s interest in understanding social impacts in global supply chains and proposes a social footprint for supply chain analysis using the multi-regional input output methodology.

Anthropogenic climate change is a major threat to human existence. Policy makers need concrete data and projections on future emissions pathways to make informed decisions on how to mitigate the impacts of climate change. Integrated Assessment Models (IAM) are a class of models prominently used to quantify the impact of climate change on the earth and human systems. The Model for Energy Supply Strategy Alternatives and their General Environmental Impact (MESSAGEix) model is one of the most widely used IAMs. The MESSAGEix model has 4 main components: an energy system model, a macroeconomic model, a land-use model and an atmospheric science model. The energy system model is at the core of MESSAGEix since a large proportion of greenhouse gas emissions causing climate change are from the production and consumption of energy. MESSAGEix covers the direct supply chain impacts, such as emissions and energy use from energy production and transmission sectors. However, by extrapolating historical final energy requirements into the future, MESSAGEix misses the role of indirect energy requirements that play out through supply chains. Most importantly, MESSAGEix’s future final energy trajectories do not reveal anything about the commodities that contribute to future energy demand. I have therefore identified a point of improvement for the MESSAGEix model - to enhance the capability of the model by incorporating an exogenous final energy requirements scenario builder (IO-scenario builder) capable of capturing energy demand associated with an economy’s supply-chain system. In this study, I have successfully developed a method for linking MESSAGEix with an input-output (IO) database. More specifically, I have constructed an Australian national-level model (MESSAGEix-Australia) to empirically demonstrate this linking method. To further demonstrate the capabilities of this iterative linkage, results of an existing hybrid Life-Cycle Assessment (LCA) study on the energy implications of Australia’s future road system are incorporated into MESSAGEix-Australia.

More and more local governments (municipalities and county councils) include the indirect climate impacts of consumption in their environmental work. Life Cycle Assessment (LCA) is an established tool for inventorying both direct and indirect impacts of a product or service, but when the climate impact of an entire organization's consumption of products and services is of interest, the inventory of data can easily become excessive. Through the years, various methods for enabling life cycle inventory on the organizational level have been developed. Hybrid-LCA is one of them where the term "hybrid" comes from that the method combines a so-called bottom up with a top down approach of the data inventory. The practical application of hybrid-LCA and the usefulness of the assessment results for local governments are not self-evident. This study aims to investigate the practical application of hybrid-LCA as a tool for inventorying climate impact for municipalities’ and county councils’ consumption. The purpose includes identifying the challenges associated with the practical procedure when conducting a hybrid-LCA and evaluating the inventory results’ usefulness in municipalities and county councils’ climate work. The results of the study are based on semi-structured interviews, a case study in which hybrid LCA is applied and a workshop where the case study is evaluated. The results show that the hybrid-LCA enables both a holistic approach to the climate impact and a level of detail for selected areas, making it possible to prioritize areas and identify measures to reduce the climate impact from consumption. The main challenges that arise in the practical procedure of the hybrid-LCA are associated with inventory and verification of foreground data and matching purchases of product groups to standardized classifications. To simplify the execution, increase transparency and facilitate monitoring, local governments are recommended to investigate the possibility of coordinating purchasing system and labeling product groups, in accordance with standardized classifications. It is also recommended to request information about a products weight and material content from suppliers. The uncertainties associated with the outcome of a hybrid-LCA are and remain large, therefore it is important that the results are communicated in terms of potential environmental impacts.

This study assesses the effect CCS employment on the global warming impact of the European cement industry using Multi-Regional Input-Output Analysis.For the cement sectors of the 28 European countries studied, technology and cohort distributions were established, thermal efficiency fuel input data were collected, and the capacity turnover and evolution of CO2 emissions from cement production of each country were determined. An economic life cycle inventory of CCS implementation for cement was established, and a cradle-to-gate assessment of the cement production with and without CCS implementation was performed using the EXIOBASE multi-regional input-output model for the years 2013, 2030, and 2050.The results of the analysis show that the implementation of CCS in the European cement industry leads to an increase in the emissions embodied in cement demand for Europe as a whole compared to a scenario where CCS is not used. However, the results of global warming impact due to cement demand vary from country. This illustrates the variations in production technologies of different countries and the importance quantifying emissions embodied in trade flows of goods throughout the world economy when calculating environmental impact.

This thesis examines the existing theories and applications of Multivariate Statistical Process Control, outlines areas of difficulty and proposes a new technique of multivariate process control chart with input-output relationship for optimal process control. The process control techniques developed up to the present time focused on the fast detection of out-of-control signals, and achieved considerable success in that respect. The techniques reported on multivariate process control thus far include extensions of univariate process control charts to their multivariate counterparts, ranging from classical Shewharts charts to modern Cumulative Sum Process Control charts. Alternative approaches in this area include Principal Component Approach, Partial Regression approach, Baysian modelling and sequential tests on detection of change points. Although each method has its own limitation, these new developments have significantly contributed to the achievement of a constant high quality of products and services. The techniques of process control are yet incomplete. They require continuous attention, as production and service technologies are being continuously developed.In particular, the level of automation, re-engineering of production processes and ever demanding economic optimality of technology demand the re-engineering of statistical process control. The CFM chart developed in this thesis would open the door to this area of science and lays a critical foundation for future research

Current human activity is degrading the environment and depleting biotic and abiotic resources at unheard-of rates, inducing global environmental change and jeopardising the development of humankind. The structure of human activity determines which resources are extracted, how they are transformed and where and how they are emitted back to the environment. Thus, the structure of human activity ultimately determines the human-Earth System interaction and human-induced environmental degradation. Several theories and empirical findings suggest that a cyclic structure would lower the resource requirements and emissions of the economic system, decoupling production and consumption from their environmental impacts. However, the cyclic structure has not been fully characterised nor related to the resource requirements or emission generation estimates of environmental impacts as calculated through models representing the physical structure of the economic system. This thesis is interested in developing tools to analyse the physical structure of the economic system and, ultimately, to develop a method to identify its cyclic structure and relate it to the environmental impact induced by economic activity. Using this new knowledge, it might be possible to reduce the environmental impact of the economy by altering its physical structure. In chapter 3, the different methods to calculate the emissions and resources associated to a given final demand of physical input-output tables are reviewed because they gather different results; it is argued that only two are valid. Surprisingly, these two methods reveal different physical structures; these are explored using a backward linkage analysis and their differences explained. It is found that only one method is appropriate to analyse the physical structure of the economic system and this method is in fact a new input-output model capable of tracing by-products as final outputs. Also, since traditional input-output structural analyses provide aggregate measures, a visual representation of input-output tables enabling researchers to perform disaggregated structural analyses and identify intersectoral patterns is developed. In chapter 4, a method to derive the full cyclic structure of the economic system is developed using network analysis within the Input-Output framework; it identifies the intersectoral cycles and the resources and emissions associated to cycling. It is shown that cyclic flows maximise the system throughput but lower the resource efficiency of the system vis-à-vis the system outputs. It is demonstrated that 1) the complete structure is composed of a cyclic-acyclic and a direct-indirect sub-structure, challenging the common understanding of the functioning of the structure, and 2) cycling is composed of pre-consumer cycling, post-consumer cycling, re-cycling and trans-cycling. In chapter 5, a set of indicators are developed to capture the weight and emissions associated to each sub-structure and the sub-structures are related to the economy's resource efficiency and emissions. In chapter 6, it is illustrated how to use the concepts, indicators and methods developed in previous chapters to identify strategies to improve the resource efficiency of the economy by altering its structure. Finally, in chapter 7, it is suggested to refine the definition of recycling to integrate the different systemic effects of pre-consumer and post-consumer cycling and it is argued that the ideal structure of a circular, close-loop economy should minimise its pre-consumer cycling in favour of more efficient acyclic flows while maximising its post-consumer cycling.

Specifications on digital hardware systems typically contain descriptions and requirements expressed in natural language and diagrams of various types. The objective of the research reported here is the automatic detection of common references ("coreferences") to objects in natural language specification statements in order to permit automatic integration of requirements. This thesis describes a prototype system for detecting coreferences. First, the natural language statements are translated into conceptual graphs (semantic nets). Then, these graphs are scanned by a rule-based system to determine whether each concept that is encountered is the definition of a new concept or a reference to a previously defined concept. Tests performed on the system developed indicate a high percentage rate of correct classifications.
Master of Science

Material flow-based indicators play an important role in indicator sets related to green and resource-efficient growth. This paper examines the global flows of materials and the amounts of materials directly and indirectly necessary to satisfy domestic final demand in different countries world-wide. We calculate the indicator Raw Material Consumption (RMC), also referred to as Material Footprint (MF), by applying a global, multi-regional input-output (MRIO) model based on the GTAP database and extended by material extraction data. We examine world-wide patterns of material extraction and materials embodied in trade and consumption, investigating changes between 1997 and 2007. We find that flows of materials related to international trade have increased by almost 60% between 1997 and 2007. We show that the differences in Material Footprints per capita are huge, ranging from up to 100 tonnes in the rich, oil-exporting countries to values as low as 1.5 to 2 tonnes in some developing countries. We also quantify the differences between the indicators Domestic Material Consumption (DMC) and RMC, illustrating that net material exporters generally have a DMC larger than RMC, while the reverse is observed for net importers. Finally, we confirm the fact that most countries with stable or declining DMCs actually show increasing RMCs, indicating the occurrence of leakage effects, which are not fully captured by DMC. This challenges the world-wide use of DMC as a headline indicator for national material consumption and calls for the consideration of upstream material requirements of international trade flows.

This thesis examines the economic impact of two alternative canning plant sizes in Scott County, Virginia. The impacts of a community cannery as well as a commercial cannery are analyzed with respect to changes in output, employment, and income. Several uses for the commercial cannery are considered, such as specialization in different product categories. In both cases, an input-output model is used to evaluate the effects of the operation of the cannery in the county. The results indicate that the impact of the commercial cannery is significantly larger than the community cannery. Specialization of the commercial cannery in the Canned Specialties sector has the largest impact with respect to industry output and labor income while specialization in the Sausages and Other Prepared Meats sector has the largest impact with respect to employment.
Master of Science

Thesis (PhD (Philosophy))-- University of Western Sydney, Nepean, 1998.
"Thesis submitted for the fulfilment of the requirement of Doctor of Philosophy in quantitative methods, School of Quantitative Methods and Business Operations, Faculty of Commerce, University of Western Sydney, Nepean" Bibliography : p 233-257.

Countries face different problems depending on factors such as geographical position, climate, wealth, political regime, and natural resources. Given this diversity, it is important that economic, social, and environmental assessments utilise regionally detailed and comprehensive information. However, when examining a particular type of assessment, studies (in most cases) are usually conducted without any regional or sectoral specificity due to the difficulty of creating an inter-regional modelling framework at sub-national levels. A fundamental tool for identifying specific economic characteristics of regions (either global or within a nation) is a multi-region input-output (MRIO) system. Through the understanding of regional economic distribution, sectoral contribution, and inter-regional supply chain network, input-output (I-O) based assessments are capable of providing a comprehensive picture of regional economic structures. However, the creation of an MRIO system is a time-consuming task that requires skill in handling the complexity of data compilation and reconciliation. To this end, finding an alternative method for creating an MRIO database in the most efficient way is necessary. In this thesis, I developed new MRIO databases that utilised virtual laboratory technology: IndoLab, TaiwanLab, SwedenLab, and USLab , and also took part in developing the JapanLab. I then demonstrated the use of these new facilities for addressing research questions surrounding employment multipliers in Indonesia, economic impacts due to natural disasters in Taiwan, regional consumer emissions in Sweden, and the responsibility for food loss in Japan. In addition, I presented the application of a new dataset in the global MRIO database for assessing the carbon footprints of global tourism sectors.

Background and contextGeneral and far reaching scenarios of possible futures for humanity's social metabolism have been put forth, outlining strikingly contrasting potential environmental prospects. Lifecycle assessment (LCA) and environmentally extended input-output (EEIO) —the dominant methodologies for environmental assessment of production and consumption activities— have been little used to analyse specific activities within these possible futures.Most LCAs and EEIOs are attributional and retrospective; they use past data with a central tendency approach to determine the impact of activities that are already embedded within a production-consumption system. On the other hand, so-called prospective-consequential LCAs analyse perturbations to a system, e.g. the introduction of new technologies or a change in consumption levels, and are therefore targeted at guiding decisions in the present and near-future. For large scale perturbations or more long-term decisions into the future, however, the consequential approach has been criticised as either losing transparency through complex modelling or relying overly much on ceteris paribus assumptions. It has recently been proposed that a prospective attributional approach to lifecycle studies could fill this void. Such an approach involves estimating the environmental impacts that can be attributed to the lifecycle of a future good or service embedded within exogenously defined scenarios of the future economy. Little has been done in this direction so far.Already in retrospective studies, the separate use of process-based LCA and EEIO has been criticised as leading to either truncated or heavily aggregated assessments. The advantages of using hybridizations of these two techniques seems even greater for prospective attributional analyses, considering how the EEIO framework is a robust vehicle for future economic scenarios. There is thus a need for further development in the direction of prospective attributional hybrid EEIO-LCAs.

Nous étudions les conditions historiques et épistémologiques de la formation de l'analyse input-output (AIO). Dans les années 1950 l'AIO connaît un succès exceptionnel: le tableau entrées-sorties et le modèle de Leontief est un outil statistique puissant. Les archives de Wassily Leontief à Harvard font apparaître qu'elle résulte de la coopération entre Leontief (Harvard) et des administrations américaines durant la seconde guerre mondiale. Si d'un côté le succès de l'AIO auprès des administrateurs est celui d'une technologie sociale au service de la puissance, Leontief de son côté ne cherche pas à développer une analyse de la planification. Le discours de Leontief, appuyé sur son projet d'étude des relations interindustrielles, est d'abord un discours sur le statut épistémologique de l'économie: pour Leontief l'économie est une science empirique à fonder sur un critère de vérité opérationnaliste. Nous répondons à la question suivante: comment l'AIO, une technologie sociale, peut-elle servir de plate-forme au discours épistémologique de Leontief sur le statut de la science économique? La réponse reprend les quatre caractéristiques de l'AIO: un outil statistique qui relève de 1 'histoire de la statistique; une technologie sociale qui est le résultat d'une configuration complexe entre le politique, le théorique, la science et l'épistémologie à un moment historique donné; une construction théorique subtile; un positionnement épistémologique particulier. Nous montrons comment l'analyse input-output n'aurait pu se faire et ne peut se comprendre que grâce à l'alchimie complexe entre les préoccupations théoriques et épistémologiques pour une configuration historique donnée.

The supply chain risk management discipline studies how to address daily and extraordinary risks to avoid vulnerability and to guarantee production continuity. In the case of the electricity sector, the economic impact of interrupting the power supply is depicted by an indicator called the deficit cost, measured in monetary unit per electricity consumption unit (for example, in Brazil, R$/MWh). This value is commonly applied to cost-benefit analysis that results in decisions about maintenance and investment in the electricity system in the medium and long term, in addition to composing the short-term energy price. Most countries in the world have a thermal energy matrix, and cases in which interruption problems occur are mainly due to punctual failures in generation or transmission and last a few hours or days until maintenance is concluded. Brazil, however, has been strongly dependent on hydrological conditions ever since the main generation source became hydroelectric. Since restricted energy supply scenarios last longer, from weeks to months, a better measure for the electricity structural deficit impact is the economic loss in the deficit-affected regional production, translated as the GDP (gross domestic product) region. This dissertation estimates the Brazilian GDP marginal loss due to power deficits by applying an input-output (I/O) matrix analysis methodology and concludes that the officially adopted deficit cost is underestimated.
Sem resumo em português.

Our world is beleaguered by environmental and socioeconomic problems, such as natural resources degradation, natural hazards, climate change, unemployment, and inequality. Trade supply chains are recognised as important means to address environmental and socio-economic challenges. The world has benefited from trade in many ways, such as promoting economic growth, opening the global market for all countries, and creating jobs. However, trade is likely to increase environmental externalities at both national and global level. Trade can directly affect local environment through overexploitation of natural resources and substantial pollution. One reason for this is that trade is mainly driven by regions’ differing natural resource endowments. Considering the adverse environmental impact of trade and supply chains, as well as their effects on societal and economic development, domestic and international trade supply chains play a key role in addressing regional and global environmental challenges, and thus contribute to achieving Sustainable Development Goals (SDGs) – a global plan adopted by all United Nations (UN) members for a better and more sustainable future. This thesis applies a quantitative interdisciplinary approach - multiregional input-output (MRIO) analysis to estimate the environmental and socioeconomic impacts of supply chains in three case studies: (i) calculate material footprint in four megacities of China by linking Chinese MRIO to the Global MRIO database Eora, (ii) estimate direct and indirect economic loss and spillovers of desertification in China, as well as the nutrient loss caused by desertification, by applying an improved input-output (IO)-based disaster model, (iii) investigate how Greenhouse Gas (GHG) emissions, land use, and employment will be affected by switching from petroleum-based plastics to bio-based plastics, with an improved IO technique for estimating the substitution effects of bioplastics.

International trade, an important channel and a clear demonstration of globalization, has attracted worldwide attention. The development of international trade has brought tremendous benefit to the entire society in many ways. However, the negative impacts of international trade supply chains cannot be ignored. Compared to the environmental impacts associated with global supply chains that have been substantially researched, the social impacts associated with that trade are an emerging topic in both academic and industrial areas. ‘Social footprint’ is the terminology used to describe the social impacts associated with the entire supply chain activities, and social footprinting is the method to calculate and report social footprints. Social footprinting shares some methodologies with environmental footprinting, and based on cases, includes extra processing steps. This thesis uses Multi-Regional Input-Output analysis (MRIO) to calculate social footprints and analyze social impacts in five case studies. Chapter 1 briefly introduces the background to this research. Chapter 2 describes the process of updating the global Multi-Regional Input-Output Database Eora and incorporating it into the cloud platform Global IELab. Chapter 3 investigates the corruption footprints of 189 countries by weighing the national corruption level with employment data. Chapter 4 further explains the how to combat corruption through international trade. Chapter 5 describes the combination of the MRIO database Eora with a social risk database, the Social Hotspots Database (SHDB), and the application of the combined data to the analysis of a group of Sustainability Development Goal indicators. Chapter 6 looks into occupational airborne disease caused by particulate matters. Chapter 7 provides a case study in the Arab region for employment flow measurement and analysis. Chapter 8 concludes.

The purpose of this research is to help understand the key relationships in an evolving economic structure that are driving resource use and greenhouse gas emissions in Australia. The approach involves looking at the factors and relationships that underpin economic growth in Australia. This research seeks to understand the changes in these factors by taking a historical perspective to the determinants of environmental impact through an investigation of structural changes over a period of 30 years. A detailed model is developed using the macro-economic tool of input-output analysis. This model makes it possible to investigate inter-relationships and intra-relationships between sectors of the environment, the economy and the population at disparate scales.

Doctor of Philosophy (PhD)
The purpose of this research is to help understand the key relationships in an evolving economic structure that are driving resource use and greenhouse gas emissions in Australia. The approach involves looking at the factors and relationships that underpin economic growth in Australia. This research seeks to understand the changes in these factors by taking a historical perspective to the determinants of environmental impact through an investigation of structural changes over a period of 30 years. A detailed model is developed using the macro-economic tool of input-output analysis. This model makes it possible to investigate inter-relationships and intra-relationships between sectors of the environment, the economy and the population at disparate scales.

The purpose of this thesis is to investigate what effect, if any, the social roles between second language learners and their conversational partners have on the types and frequencies of the following discourse categories: (a) input interactional modifications (b) corrections of language learners' linguistic errors by others and (c) language learners' production of comprehensible output. This study also seeks to corroborate previous research findings with regards to negotiation of meaning interactions (Pica, 1988; Pica, Holliday, Lewis & Morgenthaler, 1989) and other-corrections of language learners' linguistic errors (Chun, Day, Chenoweth & Luppescu, 1982).

El objetivo de esta tesis es analizar las relaciones existentes entre las actividades productivas y la generación de emisiones de CO2 en el Ecuador. Sobre la base del enfoque input-output se plantean tres capítulos que permiten comprender de mejor manera esta interrelación. El primer capítulo identifica los sectores clave en las emisiones de CO2 para la economía ecuatoriana al año 2013. Los resultados muestran que 19 de las 71 actividades productivas son las más influyentes en la generación de emisiones de CO2. De las 19 actividades 8 pueden considerarse como sectores clave. Las 8 actividades son responsables del 60% del total de las emisiones generadas por el aparato productivo; además, 4 de ellas pertenecen al sector de los servicios, convirtiéndolo en un sector relevante para el análisis de la generación de emisiones de CO2 en la economía ecuatoriana. El segundo capítulo profundiza el análisis de las emisiones de CO2 generadas por las actividades pertenecientes al sector servicios, para lo cual se utiliza la metodología denominada “subsistemas input-output”. Esta técnica permite obtener varios componentes a través de los cuales se generan las emisiones totales (directas e indirectas) de un sector o grupo de sectores. Los resultados muestran que las emisiones atribuibles al sector servicios de manera directa están fuertemente concentradas en la actividad de transporte y almacenamiento, no obstante existen otras actividades pertenecientes al sector que se caracterizan por tener un fuerte componente de arrastre sobre otras ramas de la economía. Al respecto destacan actividades como el comercio, las telecomunicaciones, los servicios inmobiliarios o la administración del gobierno, las cuales serían relevantes para el diseño de políticas de mitigación. El tercer capítulo analiza los factores que están detrás de la evolución de las emisiones CO2 del sector servicios en el Ecuador entre los años 2007 y 2013. Para ello se combinan el análisis de subsistemas input-output con análisis de descomposición estructural. La desagregación de efectos a los que se llega en este estudio es mayor a la obtenida en aplicaciones similares, debido a la metodología utilizada en el análisis de subsistemas. Esta desagregación permite obtener resultados que facilitan la comprensión de los elementos y las casusas que están detrás de la variación de las emisiones de CO2 de las actividades que conforman el sector servicios. Los resultados muestran que si bien la expansión de la demanda es la principal causa para el incremento de las emisiones, existen importantes asimetrías en el comportamiento de las actividades que conforman el sector servicios y en las causas que las generan. Se observa que algunas actividades presentan mejoras en términos de eficiencia y tecnología que, de alguna manera, compensaron el incremento de las emisiones ocasionadas por el aumento de la demanda. Sin embargo, otras actividades, incrementaron sus emisiones no sólo por un aumento de la demanda sino también por un deterioro en términos de eficiencia y tecnología.
The aim of the present thesis is to analyse the existent relationship between productive activities and CO2 emissions generated in Ecuador. On the basis of the input-output approach, three chapters are developed allowing a better understanding of this relationship. The first chapter identifies the key sectors in CO2 emissions for the Ecuadorian economy by 2013. The results show that 19 of the 71 productive activities are the most influential in the CO2 emissions generation. Of the 19 activities 8 can be considered as key sectors. The 8 activities are responsible for 60% of the total emissions generated by the productive apparatus; and, 4 of them belong to the services sector, making the last a relevant sector for the analysis of the CO2 emissions generation in the Ecuadorian economy. The second chapter deepens the analysis of the CO2 emissions generated by the activities belonging to the services sector, for which the methodology named "input-output subsystems" is used. This technique allows the identification of several components through which the total emissions (direct and indirect) of a sector or group of sectors are generated. The results show that the emissions directly attributable to the services sector are strongly concentrated in the transport and storage activities. However, However, in the case of other service activities, they have strong pull effect on other activities of the economy. In this respect, activities such as trade, telecommunications, real estate services or government administration, which would be relevant to the design of mitigation policies. The third chapter analyses the factors that are behind the evolution of the CO2 emissions of the services sector in Ecuador between 2007 and 2013. For this, the analysis of input-output subsystems is combined with structural decomposition analysis. The disaggregation of effects presented in this study is greater than that obtained in similar applications, due to the methodology used in the analysis of subsystems. This disaggregation shows results that facilitate the understanding of the elements and the causes that are behind the variation of CO2 emissions of the activities belonging to the services sector. The results indicate that although the expansion of demand is the main cause for the increase of the emissions, there are important asymmetries in the behaviour of the activities of the services sector and the causes that generate those emissions. It is evidenced that some activities show improvements in terms of efficiency and technology which, in some way, compensate the increase in emissions caused by the demand effect. However, other activities, increased their emissions not only due to an upsurge in the demand but also given a deterioration in terms of efficiency and technology.

The main target of the thesis is analysing of short-term indirect cross-sectoral impacts of taxation of electricity, solid fuels and natural gas on particular sectors of NACE in the Czech Republic, especially impacts on production prices. The key instrument for the analysis is the short-term price model for the Czech Republic, created as a component of the thesis. A secondary target is focused on the analysis of direct impacts, especially impacts on prices and expenditures of particular sectors of NACE. Within the scope of the main target, there are five different variants of taxation. For each of them the impact of taxation of particular commodities on changes in production prices of particular sectors of NACE is simulated. Than two different variants, both of them including taxation of all commodities, are compared. The thesis includes also two hypotheses, which are going to be confirmed or disproved on the basis of obtained results. For achieving the main target the methodology of Leontief input -- output analysis was chosen (Leontief, 1966). This is the key instrument for creating short-term price model for the Czech Republic. This method is suitable especially for analysing short-term cross-sectoral impacts, however under necessary condition of no changes in current technologies, agreements and cross-sectoral relations. This condition represents strict limitation for the price model created for the thesis. Regarding scientific contribution, the main asset of this thesis is creation of macroeconomic short-term price model for the Czech Republic, which is based on methodology of Leontief input -- output analysis. The additional contribution is calculation of the short-term impacts of new environmental taxation on production prices of particular sectors of NACE. Considering available information, environmental taxes in the Czech Republic have not been analysed by Leontief input - output methodology yet. There is not also sufficient analysis of environmental taxes impacts on particular sectors of NACE in the Czech Republic. The thesis is divided to seven chapters. The first chapter focuses on introduction to environmental tax regulation issue. The second chapter presents theories and concepts of taxation impact analysis. The third chapter focuses on models and empirical research in environmental taxation area. The fourth chapter is dealing with basic practical aspects of introduction of new energy taxation in the Czech republic and presents data useful for the following analysis. The fifth chapter consists of describing of applied methodology and describing of creation of the price model. The sixth chapter summarises results of simulation of direct impact of taxation on average prices for companies and on expenditures of particular sectors of NACE. The seventh chapter presents results of cross-sectoral analysis of indirect macroeconomic impacts for all variants; the chapter includes also testing of hypotheses and comments of final results.

The main target of the thesis is analysing of short-term indirect cross-sectoral impacts of taxation of electricity, solid fuels and natural gas on particular sectors of NACE in the Czech Republic, especially impacts on production prices. The key instrument for the analysis is the short-term price model for the Czech Republic, created as a component of the thesis. A secondary target is focused on the analysis of direct impacts, especially impacts on prices and expenditures of particular sectors of NACE. Within the scope of the main target, there are five different variants of taxation. For each of them the impact of taxation of particular commodities on changes in production prices of particular sectors of NACE is simulated. Than two different variants, both of them including taxation of all commodities, are compared. The thesis includes also two hypotheses, which are going to be confirmed or disproved on the basis of obtained results. For achieving the main target the methodology of Leontief input – output analysis was chosen (Leontief, 1966). This is the key instrument for creating short-term price model for the Czech Republic. This method is suitable especially for analysing short-term cross-sectoral impacts, however under necessary condition of no changes in current technologies, agreements and cross-sectoral relations. This condition represents strict limitation for the price model created for the thesis. Regarding scientific contribution, the main asset of this thesis is creation of macroeconomic short-term price model for the Czech Republic, which is based on methodology of Leontief input – output analysis. The additional contribution is calculation of the short-term impacts of new environmental taxation on production prices of particular sectors of NACE. Considering available information, environmental taxes in the Czech Republic have not been analysed by Leontief input - output methodology yet. There is not also sufficient analysis of environmental taxes impacts on particular sectors of NACE in the Czech Republic. The thesis is divided to seven chapters. The first chapter focuses on introduction to environmental tax regulation issue. The second chapter presents theories and concepts of taxation impact analysis. The third chapter focuses on models and empirical research in environmental taxation area. The fourth chapter is dealing with basic practical aspects of introduction of new energy taxation in the Czech republic and presents data useful for the following analysis. The fifth chapter consists of describing of applied methodology and describing of creation of the price model. The sixth chapter summarises results of simulation of direct impact of taxation on average prices for companies and on expenditures of particular sectors of NACE. The seventh chapter presents results of cross-sectoral analysis of indirect macroeconomic impacts for all variants; the chapter includes also testing of hypotheses and comments of final results.