The overall goals of this dissertation are to investigate the sustainability of the built environment, holistically, by assessing its Triple Bottom Line (TBL): environmental, economic, and social impacts, as well as propose cost-effective, socially acceptable, and environmentally benign policies using several decision support models. This research is anticipated to transform life cycle assessment (LCA) of the built environment by using a TBL framework, integrated with economic input-output analysis, simulation, and multicriteria optimization tools. The major objectives of the outlined research are to (1) build a system-based TBL sustainability assessment framework for the sustainable built environment, by (a) advancing a national TBL-LCA model which is not available for the United States of America; (b) extending the integrated sustainability framework through environmental, economic, and social sustainability indicators; and (2) develop a systembased analysis toolbox for sustainable decisions including Monte Carlo simulation and multi-criteria compromise programming. When analyzing the total sustainability impacts by each U.S. construction sector, “Residential Permanent Single and Multi-Family Structures" and "Other Non-residential Structures" are found to have the highest environmental, economic, and social impacts compared to other construction sectors. The analysis results also show that indirect suppliers of construction sectors have the largest sustainability impacts compared to onsite activities. For example, for all U.S. construction sectors, on-site construction processes are found to be responsible for less than 5 % of total water consumption, whereas about 95 iv % of total water use can be attributed to indirect suppliers. In addition, Scope 3 emissions are responsible for the highest carbon emissions compared to Scope 1 and 2. Therefore, using narrowly defined system boundaries by ignoring supply chain-related impacts can result in underestimation of TBL sustainability impacts of the U.S. construction industry. Residential buildings have higher shares in the most of the sustainability impact categories compared to other construction sectors. Analysis results revealed that construction phase, electricity use, and commuting played important role in much of the sustainability impact categories. Natural gas and electricity consumption accounted for 72% and 78% of the total energy consumed in the U.S. residential buildings. Also, the electricity use was the most dominant component of the environmental impacts with more than 50% of greenhouse gases emitted and energy used through all life stages. Furthermore, electricity generation was responsible for 60% of the total water withdrawal of residential buildings, which was even greater than the direct water consumption in residential buildings. In addition, construction phase had the largest share in income category with 60% of the total income generated through residential building’s life cycle. Residential construction sector and its supply chain were responsible for 36% of the import, 40% of the gross operating surplus, and 50% of the gross domestic product. The most sensitive parameters were construction activities and its multiplier in most the sustainability impact categories. v In addition, several emerging pavement types are analyzed using a hybrid TBL-LCA framework. Warm-mix Asphalts (WMAs) did not perform better in terms of environmental impacts compared to Hot-mix Asphalt (HMA). Asphamin® WMA was found to have the highest environmental and socio-economic impacts compared to other pavement types. Material extractions and processing phase had the highest contribution to all environmental impact indicators that shows the importance of cleaner production strategies for pavement materials. Based on stochastic compromise programming results, in a balanced weighting situation, Sasobit® WMA had the highest percentage of allocation (61%), while only socio-economic aspects matter, Asphamin® WMA had the largest share (57%) among the WMA and HMA mixtures. The optimization results also supported the significance of an increased WMA use in the United States for sustainable pavement construction. Consequently, the outcomes of this dissertation will advance the state of the art in built environment sustainability research by investigating novel efficient methodologies capable of offering optimized policy recommendations by taking the TBL impacts of supply chain into account. It is expected that the results of this research would facilitate better sustainability decisions in the adoption of system-based TBL thinking in the construction field.

The Paris Agreement has stipulated global lowering of carbon emission to reach the 1.5°C target by 2030. The Intergovernmental Panel on Climate Change has suggested several scenarios with rapid innovation and downscaling of energy usage. Against this background, this thesis analyzes the productive capacity of Sweden to reach the corresponding carbon emission target. A product-byindustry input-output-model of the economy to study different re-allocations of production is used. The effect of these re-allocations on the output as well as carbon dioxide emissions from domestic production are considered. Linear optimization is used to achieve efficient re-allocations. Two scenarios are considered: one called the “basic case”, and one called the “efficient export case”. The basic case uniformly rescales the output. The efficient export case internalizes the export and allows it to be uniformly rescaled by the optimization up to trade balance as well. The data is from 2016 as it is the latest data with the necessary information. The result for the basic case shows that the 1.5°C target in 2016 can be reached without downscaling the output. The total employment shrinks by 2%, while some sectors of the economy are significantly changed. The result of the efficient export case has a similar result while total employment shrinks by 11%. The basic case releases 2% less than the reported carbon emissions, and the efficient export case 24% less where the efficient export case downscales the gross domestic product with 13%. The dynamics of innovation, negative impacts on production, and population growth are not accounted for in these estimates. Further studies need to internalize more constraints and develop more detailed models to provide more accurate policy guidance.

"The Strengths and Limitations of Input-Output Analysis in Evaluating Fiscal Policy" by Bc. Lenka Liskova Abstract: The thesis addresses the recent debates on suitable macroeconomic policy and calls for an alternative evaluation and forecasting method of economic impact, by assessing the applicability of Leontief's input- output model. We concentrate on providing an insight into the entire process of input-output analysis, which yields computation of simple input-output multipliers - output, gross value added and income multi- pliers. Thanks to the ability to capture linkages in the economy, com- puted multipliers are used as a tool to evaluate the effects of vehicle scrappage schemes and ICT infrastructure investment subsidies applied within a sample of diverse developed countries - Australia, Germany, Japan, UK and USA. We also aim to provide a sufficient explanation of the input-output model and a computation manual based on the example of the Leontief open model and calculation of simple multipli- ers. In our research, we numerically evaluate the effects of fiscal stim- ulus measures in the automobile industry and ICT sector and provide their comparison among 5 countries with different industry structures. Most importantly, the thesis provides a suggestion for policy makers to consider applying input-output...

The main objective of the thesis is to identify appropriate approach to evaluation of impacts of the first phase of the ecological tax reform in the Czech Republic, its consequent adaption and application for the particular purpose. The input-output analysis has been found as the most convenient solution for such a sort of analysis. The analysis has been used for the evaluation of impacts on final production prices of each NACE sector resulting from introduction of new taxes on electricity, solid fuels, natural gas and some other kinds of gases in the Czech Republic. Because of unavailability of information about the final impact of taxes on particular objects in the economy, the analysis is conducted on the basis of five incidence assumptions about the impact of taxes on distributors and customers. While the aforementioned analysis is the essential chapter of the thesis, the work starts with a theoretical introduction related to optimal tax theories and theories about possible positive effects of environmental tax implementation. Additionally, energy tax implementation in the Czech Republic and in the European Union is mentioned. Furthermore, an important starting point in finding the most convenient model was to summarize various approaches to modelling energy tax impacts on the economy. Therefore, theoretical description of particular models is provided when history of the models, type of equations and dependences in the model are described. Moreover database requirements and possibilities to use the model for another purpose are discussed. The thesis also comprises of the analysis of pros and cons and additional important characteristics of relevant models together with the summary for which purpose was the particular model used in the Czech Republic. The introduction of energy tax in the Czech republic on the final production prices was proved to be unimportant and with only exceptions (namely the sector of production and distribution of electricity, natural gas and water) an increase in final production prices does not exceed 0,2 % and for a half of all the sectors the increase does not exceed 0,1 %.

This dissertation studies three classes of estimators for the asymptotic variance parameter of a stationary stochastic process. All estimators are based on the concept of data "re-use" and all transform the output process into functions of an approximate Brownian motion process. The first class of estimators consists folded standardized time series area and Cramér-von Mises (CvM) estimators. Detailed expressions are obtained for their expectation at folding levels 0 and 1; those expressions explain the puzzling increase in small-sample bias as the folding level increases. In addition, we use batching and linear combinations of estimators from different levels to produce estimators with significantly smaller variance. Finally, we obtain very accurate approximations of the limiting distributions of batched folded estimators. These approximations are used to compute confidence intervals for the mean and variance parameter of the underlying stochastic process. The second class --- folded overlapping area estimators --- are computed by averaging folded versions of the standardized time series corresponding to overlapping batches. We establish the limiting distributions of the proposed estimators as the sample size tends to infinity. We obtain statistical properties of these estimators such as bias and variance. Further, we find approximate confidence intervals for the mean and variance parameter of the process by approximating the theoretical distributions of the proposed estimators. In addition, we develop algorithms to compute these estimators with only order-of-sample-size work. The third class --- reflected area and CvM estimators --- are computed from reflections of the original sample path. We obtain the expected values and variance of individual estimators. We show that it is possible to obtain linear combinations of reflected estimators with smaller variance than the variance of each constituent estimator, often at no cost in bias. A quadratic optimization problem is solved to find an optimal linear combination of estimators that minimizes the variance of the linearly combined estimator. For all classes of estimators, we provide Monte Carlo examples to show that the estimators perform as well in practice as advertised by the theory.

A warmer climate is expected to increase the risks of natural disasters globally. China is one of the hotspots of climate impacts since its infrastructures and industries are often hard hit. Yet little is known about the nature and the extent to which they are affected. This thesis builds novel system-of-systems risk assessment methodologies and data for China, representing infrastructures (energy, transport, waste, water and digital communications) as interdependent networks that support spatially distributed users of infrastructure services. A unique national-scale geo-spatial network database containing 64,834 existing infrastructure assets is assembled. For the first time, flood and drought exposure maps of China's key infrastructures are created, highlighting the locations of key urban areas to understand how its infrastructures and population could be exposed to climate impacts. To deepen the understanding of how climate change will affect the Chinese infrastructure system and hence its economy, economic impact modelling is applied. The research combines a detailed firm-level econometric analysis of 162,830 companies with a macroeconomic input-output model to estimate flood impacts on China's manufacturing sector over the period 2003 - 2010. It is estimated that flooding on average reduces firm output by 3.18% - 3.87% per year and their propagating effects on the Chinese macroeconomic system to be a 1.38% - 1.68% annual loss in total direct and indirect output, which amounts to 17,323 - 21,082 RMB billion. Several infrastructure sectors - electricity, the heat production and supply industry, gas production and supply, the water production and supply industry - are indirectly affected owing to the effects of supply chain disruptions. Taking the above analysis one step further, this thesis explores how climate disaster risks may change over the period 2016 - 2055, using flooding as a case study. A global river routing (CaMa-Flood) model at a spatial resolution of 0.25° x 0.25° is applied and downscaled for China, using the daily runoff of 11 Atmospheric and Oceanic General Circulation Models (AOGCMs). Combining the flood analysis with the infrastructure database, this research demonstrates the changing locations of exposed infrastructures and their dependent customers. We find that by 2055, the number of infrastructure assets exposed to increasing probability of flooding under RCP 4.5 are 41, 268, 115, 53, 739, 1098, 432 for airports, dams, data centres, ports, power plants, rail stations, reservoirs respectively - almost 8% of all assets for each sector. The lengths of line assets exposed to increasing flood hazards are 14,376 km, 32,740 km, 102,877 km and 25,310 km oil pipelines, rail tracks, roads and transmission lines respectively. Under RCP 8.4, the numbers increase to 51, 301, 137, 71, 812, 1066, 424 for point assets. Linear assets increase to 19,938 km, 39,859 km, 122,155 km and 30,861 km. Further, we demonstrate that indirect exposure of customers reliant on those infrastructure assets outside the floodplain could also be high. The average number of customers affected by increasing flood probabilities are 54 million, 114 million and 131 million for airports, power plants and stations respectively. However, within this aggregate increase there is large spatial variation, which has implications for spatial planning of adaptation to flood risk to infrastructure. This is a first substantial study of flood impacts to infrastructure both in terms of direct exposure and their indirect implications. Lastly, to shed some light on the potential vulnerability of China's infrastructure system to climate impacts, this thesis develops a framework that identifies the drivers of infrastructure development in China using evidence from policy documents and a unique geospatial dataset for the years 1900 - 2010. Understanding these drivers will provide a useful foundation for future research in terms of developing infrastructure models that could project the locations of future infrastructure assets and networks in China, thereby quantifying how China's infrastructure exposure and vulnerability will change over time. Overall this research provides an integrated system-of-systems perspective of understanding network and economic vulnerabilities and risks to Chinese energy, transport, water, waste and digital communication infrastructures due to climate change. This is crucial in informing the long-term planning and adaptation in China.

Orientador: Mariano Francisco Laplane / Dissertação (mestrado) - Universidade Estadual de Campinas, Instituto de Economia / Made available in DSpace on 2018-08-18T16:22:33Z (GMT). No. of bitstreams: 1 Rocha_IgorLopes_M.pdf: 3022565 bytes, checksum: 9cac3492f05843b98f4a1f753bcefd3f (MD5) Previous issue date: 2011 / Resumo: O desenvolvimento da estrutura produtiva brasileira durante as décadas de 1930 a 1980 e sua importância como eixo dinâmico da economia foram objetos de diversos estudos. Com a crise da dívida externa e a fragilidade fiscal e financeira do Estado, um novo modelo de desenvolvimento passou a ganhar adeptos, ensejando uma reviravolta na estratégia até então adotada. A política econômica empreendida, especialmente a partir da década de 1990, forjou um período de grandes mudanças no ambiente produtivo e competitivo, com reflexos ainda contemporâneos. É com base nessas acepções que o objetivo central deste trabalho se volta à investigação da dinâmica estrutural da economia brasileira, particularmente no que se refere ao seu padrão comercial e produtivo. A fim de consubstanciar a análise histórica e teórica, recorre-se ao referencial de insumo-produto, a partir das matrizes estimadas para os anos de 1995 a 2008. Destaca-se o comportamento dos coeficientes de comércio e de insumos importados, em grande medida associados ao descompasso entre a estrutura de oferta e os ciclos de demanda, assim como a rigidez estrutural da indústria nacional em termos produtivos e comerciais. Observam-se ainda neste processo os componentes dinamizadores do valor adicionado e do emprego na demanda agregada / Abstract: The development of Brazilian productive structure between the 1930?s and 1980?s and its importance as a dynamic hub of the economy were subject of several studies. After the external debt crisis and the fiscal and financial fragility of the State, a new development model began to gain adepts entailing a turnaround in strategy then adopted. The economic policy undertaken, especially from the 1990's onwards, forged a period of great changes in productive and competitive environment, with still contemporary consequences. Based on these references, the aim of this study is to investigate Brazilian structural dynamics, particularly what refers to the commercial and productive pattern. In order to support the historical and theoretical analysis, the input-output approach is used to estimate matrices from 1995 to 2008. It is highlighted the evolution of trade and imported input coefficients, largely associated with the gap between supply structure and demand cycles, as well as the structural rigidity of domestic industry in terms of production and trade. It is also observed in this process the dynamic components of aggregate demand for value-added and employment / Mestrado / Ciências Economicas / Mestre em Ciências Econômicas

This study examines how federal farm policies, specifically crop Insurance, have affected the farm economic structure of North Dakota's agriculture sector. The system of derived input demand equations is estimated to quantify the changes in North Dakota farmers' input use when they purchase crop insurance. Further, the cumulative rolling regression technique is applied to capture the varying effects of the farm policies over time. Empirical results from the system of input demand functions indicate that there is no moral hazard since North Dakota farmers will increase fertilizer and pesticide use in the presence of crop insurance. Results also indicate that farmers in this state will not increase the use of land.

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.

With the current trend in cloud computing and virtualization, more organizations are moving their systems from a physical host to a virtual server. Although this can significantly reduce hardware, power, and administration costs, it can increase the cost of analyzing performance problems. With virtualization, there is an initial performance overhead, and as more virtual machines are added to a physical host the interference increases between various guest machines. When this interference occurs, a virtualized guest application may not perform as expected. There is little or no information to the virtual OS about the interference, and the current performance tools in the guest are unable to show this interference. We examine the interference that has been shown in previous research, and relate that to existing tools and research in root cause analysis. We show that in virtualization there are additional layers which need to be analyzed, and design a framework to determine if degradation is occurring from an external virtualization layer. Additionally, we build a virtualization test suite with Xen and PostgreSQL and run multiple tests to create I/O interference. We show that our method can distinguish between a problem caused by interference from external systems and a problem from within the virtual guest.