<p>In this study a Multi Regional Input Output model has been developed for the base year 2000, and thereafter extended and hybridized to enable a study of offshore wind power generation in Scandinavia. Foremost the per-unit environmental impact of offshore wind power generation was calculated to an average of 16.5 grams of CO2-eq. per kWh. The MRIO model offers a broad system boundary, covering a complete set of background flows and enables in this way a thorough study of the inter-regional value chains and the corresponding emissions embodied in trade. Scenarios from 2000 to 2030 for future offshore wind power were developed on the basis of GDP projections and projections for future energy demand. One baseline scenario, assuming no further offshore wind power installation, was developed, together with a Medium and a High scenario of future offshore wind power installation. The installed wind power was assumed to replace non-renewable energy sources, primarily domestically and secondly in power importing countries. The Medium and High scenario resulted in a cumulative reduction of 220 Mtons CO2-equivalents and 308 Mtons by 2030, respectively. The Norwegian offshore wind power was by a large exported, while Denmark and Sweden experienced a substantial wind power implementation into their economies, resulting in considerable increase in the percentage share of renewable energy in their electricity mix. This shows that offshore wind power could have a vital role in reaching the European Union’s target of a 20% share of renewable energy by 2020, under the assumption that a substantial capacity of wind power is installed. The results from this study provide important guidance and a broad overview of the effect a large wind power implementation will have on the Scandinavian economy.</p>

<p>The environmental impact of a final product can be regarded as the sum of the impacts of all processes needed to obtain it. The impacts of these processes in all individual layers of production can be quantified using contribution analysis methods. SPA is an advanced method used to identify the chain of production processes linking the most highly emitting process with the final product. This analysis was performed in Matlab, using a specialized algorithm developed by Peters and Hertwich in 1996. In this thesis we test an interdisciplinary approach combining LCA and operational research methods for doing a SPA. A mixed integer program was developed and implemented in Gams. The performance of this generalized algorithm was benchmarked against the specialized algorithm for three test cases performed on three databases of increasing complexity. The results suggest the advantage of this algorithm in performing analysis on sparse data systems compared with the classic method involving Matlab. However, Matlab’s specialized algorithm performs better for dense data systems. Many of the requirements and limitations imposed by the software involved in different steps have proved manageable. This study proves that mathematical programming can be a very useful tool for contribution analysis in general and SPA in particular.</p>

The objective of this study was to develop an approach to integrate LCA of different fuels and energy conversion technologies into the energy planning tool eTransport. Course LCA's for relevant energy commodities, infrastructure and transport services was performed, and the results from these prepared for implementation in eTransport. In the choice of methodology for integration, a lot of aspects needs consideration. These are described throughout the report and emphasized in the choice of methodology. The methodology is illustrated by a case study on Trondheim municipality, followed by a description on how this would be done in eTransport. This project is a groundwork regarding implementation of LCA in eTransport, and will be followed up by further student work, testing the method in practice.

The increasing global demand for energy coupled with decreasing oil-supplies, and increasing risk of adverse climate change due to anthropogenic carbon emissions has created the need for combined economic and environmental assessment. This thesis attempt at devising such a framework based upon Life Cycle Assessment (LCA) and Life Cycle Costing (LCC). These methodologies represent two well established approaches for measuring environmental and economic performance of industrial projects and products. The LCA framework permits introduction of system expansion by interfacing with the greater economy by the hybrid-LCA. This approach also permits the assessment of life-cycle costs within the mathematical structure. The fundamental computations of LCA and LCC are introduced in this text in order to establish the combined assessment framework. This assessment method is applied to two National Renewable Energy Laboratory's studies on bio-ethanol production from lignocellulose. The studies are adapted to Norwegian economic conditions in order to assess the price and emissions of ethanol production from Norwegian wood mass. By combining these performance characteristics, a mitigation price of substituting gasoline with ethanol is established for various plant sizes as well as prices of gasoline.

The goal of this study is to investigate the potential implementation of integrated dimethyl ether (DME) production from by-products of the pulp and paper industry in Fenno-Scandinavia (Finland, Norway and Sweden) and to quantify the consequences of several use scenarios in which fossil fuels were gradually substituted by DME. To that end, two analytical frameworks were jointly used, life cycle assessment (LCA) and environmentally-extended input-output analysis (EEIOA). The first framework was utilised to make an exhaustive inventory of the Chemrec process and its integration in the Finnish, Norwegian and Swedish contexts. The latter framework was employed in order to incorporate this production system into a multi-regional input-output model that has been created for the purpose of the study. For data availability reasons, the stressors that have been examined are anthropogenic carbon dioxide, methane and dinitrogen monoxide, widely regarded as the elements which are responsible for the most serious environmental impacts. Three different story lines (plus a baseline scenario) were taken into account: a resource assessment scenario, in which a total implementation is assumed; a policy-independent approach setting a constant increase in the use of biofuels and a policy-compliance approach, aiming at satisfying European directive goals. It results that 5.21 to 20.6 Mt of DME can be produced, while the range of greenhouse gases emissions that can be saved thanks to a black liquor-based DME production scheme goes from 46.7 (scenario 3) to 70.5 (scenario 2) Mt in 2050, that is, 8.15–12.8% out of the otherwise total emissions in Fenno-Scandinavia. This LCA/IO analysis emphasises that the amount of greenhouse gases emissions embodied in every kg of DME highly depends on each country's background economy and evolves considerably along the decade, unit-level analysis show drastic reductions (-15% to -57% between 2000 and 2050) in DME embodied emissions. A nationwide analysis highlights a very important potential from the Finnish pulp and paper industry. All in all, it shows that such a biofuel production scheme should be implemented in countries that have an remarkable environmental profile to obtain very significant environmental performances. Only a joint effort of all the key sectors (energy, transportation, households) can lead to climate change mitigation and energy security.

To keep process-specificity while extending system boundaries hybrid techniques were developed allowing the micro structure of the important parts of a system to be revealed at the same time the entire economic system in which the system is embedded to be covered. Despite the substantial improvements bestowed by hybrid techniques some downsides still hold. Tiered hybrid LCA first does not model feedbacks whereas the relationship between the process-based system and the input-output based system is interactive and second it may suffer from double counting incidents as a process may be instigated in both the IO and LCI data. Integrated hybrid LCA overcomes those aforementioned pitfalls but only at a price of high labor and data intensity. This work aims to elaborate a new hybridisation method that avoids previously mentioned drawbacks. This technique is designed to not operate anymore at the matrix level as is the case for current hybridisation techniques but at the structural path level, per se the finest level of detail possible for the disaggregation of the Leontief inverse, and as such an ad hoc basis to carry out an hybrid analysis. It is argued that the method presented here constitutes a culmination amongst hybridization techniques. Its operability and capabilities are demonstrated before an interpretation from an input-output vantage point is carried out on a case-study not to be found in the literature, a comparison across the faculties of a university.

In this study a Multi Regional Input Output model has been developed for the base year 2000, and thereafter extended and hybridized to enable a study of offshore wind power generation in Scandinavia. Foremost the per-unit environmental impact of offshore wind power generation was calculated to an average of 16.5 grams of CO2-eq. per kWh. The MRIO model offers a broad system boundary, covering a complete set of background flows and enables in this way a thorough study of the inter-regional value chains and the corresponding emissions embodied in trade. Scenarios from 2000 to 2030 for future offshore wind power were developed on the basis of GDP projections and projections for future energy demand. One baseline scenario, assuming no further offshore wind power installation, was developed, together with a Medium and a High scenario of future offshore wind power installation. The installed wind power was assumed to replace non-renewable energy sources, primarily domestically and secondly in power importing countries. The Medium and High scenario resulted in a cumulative reduction of 220 Mtons CO2-equivalents and 308 Mtons by 2030, respectively. The Norwegian offshore wind power was by a large exported, while Denmark and Sweden experienced a substantial wind power implementation into their economies, resulting in considerable increase in the percentage share of renewable energy in their electricity mix. This shows that offshore wind power could have a vital role in reaching the European Union’s target of a 20% share of renewable energy by 2020, under the assumption that a substantial capacity of wind power is installed. The results from this study provide important guidance and a broad overview of the effect a large wind power implementation will have on the Scandinavian economy.

The environmental impact of a final product can be regarded as the sum of the impacts of all processes needed to obtain it. The impacts of these processes in all individual layers of production can be quantified using contribution analysis methods. SPA is an advanced method used to identify the chain of production processes linking the most highly emitting process with the final product. This analysis was performed in Matlab, using a specialized algorithm developed by Peters and Hertwich in 1996. In this thesis we test an interdisciplinary approach combining LCA and operational research methods for doing a SPA. A mixed integer program was developed and implemented in Gams. The performance of this generalized algorithm was benchmarked against the specialized algorithm for three test cases performed on three databases of increasing complexity. The results suggest the advantage of this algorithm in performing analysis on sparse data systems compared with the classic method involving Matlab. However, Matlab’s specialized algorithm performs better for dense data systems. Many of the requirements and limitations imposed by the software involved in different steps have proved manageable. This study proves that mathematical programming can be a very useful tool for contribution analysis in general and SPA in particular.

Land use refers to the use of land for intensive human activities aiming at exclusive use of land for certain purposes and adapting the properties of land areas in view of these purposes. Environmental problems are, however, generated as a result of these human activities which modify the shape and properties of large land areas according to the requirements of human activities and thereby excluding wild animals and plants from coexisting on such land areas and in their neighbourhoods. Land use also leads to the degradation of the natural environment. Life Cycle Assessment (LCA) methodology is used for evaluating the environmental burdens associated with products or processes while taking their whole life cycle into consideration. LCA is a comprehensive assessment method which considers all aspects of natural environment, human health, and resources. Land use is regarded as an impact category in Life Cycle Assessment and is treated as such. However, the environmental impacts associated with land use and land use change are not being adequately considered in LCA, if considered at all.Life Cycle Impact Assessment is a part of LCA and is aimed at understanding and evaluating the magnitude and significance of the potential environmental impacts of products or processes and this involves developing characterization factors which link an environmental impact to a category indicator. In the assessment of land use impacts, characterization factors are developed so as to weigh the magnitude of environmental interventions such as land occupation and land transformation on the potentially affected attributes of ecosystem quality such as biodiversity, ecological functions and natural resources.The goal of this study is to review the progress of the implementation of land use and land use change as an impact category in LCA with a particular focus on biodiversity, recognize limitations, and indicate future prospects for the development of land use impact assessment methodologies and subsequent integration into LCA. Land use impacts are not being widely integrated into LCA because they are dependent on the regional or local situation which is not well known in LCA and land use as an environmental intervention is very complex. However, the importance of land use cannot be overemphasized when assessing products or processes which make use of raw materials that originate from land extensive activities. Despite this importance, there have been diverse arguments on how to include land use impacts, for example, on biodiversity in LCA so as to provide a common and acceptable methodology for this assessment.This study focuses on how land use impacts can be included in LCA. With a particular focus on land use impacts on biodiversity, the result of this review shows that only a few studies have been carried out. The problem of non-convergence of the methodology for the assessment of land use in LCA still persists because most of the proposed methodologies deal with different aspects of land use impacts and are therefore conflicting.Most of the studies reviewed stress the importance of biodiversity measured in terms of vascular plant species diversity. However, there are other methodologies which consider other impact pathways such as life support functions. The number of studies thereby correlates with an increase in the interest in the research area. However, it is difficult to identify any trend of convergence. Different methods are being proposed which do not actually agree with one another. Some of these methods are not “closely” related to the use of land in the normal usage sense. Most of the methods being proposed are exemplified in different regions and these have not been found to be applicable to global cases. This could be a limiting factor for the applicability of the proposed methodologies in LCA. In order to overcome these shortcomings, more research work would be needed before these methodologies could be incorporated into LCA which is presumed to be a global assessment methodology. This will enhance the credibility of the results provided by an LCA and the subsequent acceptability of the LCA methodology.

The number of household gadgets that use energy, usually electricity, has multiplied in recent decades and energy use in a category that was long called “other” has risen significantly. In the mean time, another concern has arisen: the carbon cost related to the production and disposal of the gadgets. Investigating household electric and electronic equipment (EEE) as a specific household consumption category, the objective of this project is to get more understanding of their consumption and of their carbon footprint over there life-cycle. Space and water heating as well as lighting are excluded. The focus is on Norwegian household carbon footprint considering its specificities both in terms of consumption patterns, external trade and energy mix. First, an economic and statistical analysis of product ownership is conducted. It uses several data sources, such as the recent REMODECE campaign, sales data, lifetime estimation, EE-register data (registration of input and output of Electric and electronic equipment on the Norwegian market) and data from statistical office of Norway. Second, the project aims to record, analyze and compare different sources of information considering production and end-of-life. Both bottom up and top down approaches are investigated, even if a stress is put on bottom-up studies, such as ongoing European EuP study with its Ecoreport tool and EcoInvent database. Third it gives a best estimate of EEEs share in household carbon footprint, found to be 8,1% at 1,5 tons of CO2equivalent per household with production phase as a main contributor. A discussion on uncertainties assessing precision and identifying information gaps is also conducted. In addition to facilitate further research by setting up a framework grouping information sources critically analyzed, this project highlights the increasing importance of EEE products regarding sustainable consumption by putting numbers on the table.