A Política Estadual de São Paulo de Mudanças Climática (PEMC) foi lançada em 2009. Esta política voluntária, independente de qualquer acordo nacional ou internacional, foi estabelecida para reduzir a emissão dos gases de efeito estufa em 2020 em 20%, de acordo com os níveis de 2005. Uma vez que a melhoria da eficiência energética está entre as ações de mitigação de emissões de carbono especificadas pela PEMC, este trabalho visa avaliar as emissões diretas e indiretas e o consumo energético das cadeias produtivas na economia do Estado de São Paulo. Conseqüentemente, este estudo combina dados da Matriz Insumo Produto com o Primeiro Inventário de Gases de Efeito Estufa do Estado de São Paulo (2011) e o Balanço Energético (2010). Todos os dados estão baseados nos valores do ano de 2004. O trabalho avalia três simulações. A primeira simulação compara as emissões totais e energia por unidade de demanda final, já a segunda simulação aplica o mesmo método, porém apenas contabiliza as emissões de energia. A terceira simulação é baseada na massa total de emissões diretas e indiretas e foi determinada por meio dos multiplicadores. Além disso, o efeito total de cada setor está relacionado às emissões diretas e indiretas geradas por uma unidade de demanda final. Baseado nos resultados das três simulações foi possível observar que as emissões indiretas representam quase 30% sobre as emissões totais, e que apesar deste número não ser mais representativo, a responsabilidade do setor é maior se as emissões indiretas forem consideradas. Os resultados da Simulação 1, identificam os setores que se destacam devido a altos geradores de emissões e energia: Outros da indústria extrativa e Cimento, de outro modo, se apenas os geradores das emissões fossem considerados Cimento e Pecuária teriam se destacado com aproximadamente 3,5 GgCO2e emitidos direta e indiretamente por 1 milhão de reais de demanda final. Já, de acordo com a Simulação 2, os setores que se destacam são: Cimento e Frabricação de aço e derivadoscom respectivamente 1,4 GgCO2e e 0,5GgCO2e de emissões totais emitidas por 1 milhão de reais de demanda final. Por fim, na Simulação 3, o setor de Transportes se destaca com 23% das emissões diretas, enquanto é responsável por 9% das emissões indiretas, correspondentes às emissões incorporadas pela demanda por serviços e produtos. Por outro lado, o setor Alimentos e bebidas é o que mais se destaca devido a 17% das emissões indiretas apesar de apresentar apenas 2% do total das emissões diretas. / The Sao Paulo State Climate Change Policy (CCP) was established in 2009. This voluntary policy, independent of any domestic and international accord, was established to reduce greenhouse gas emissions in 2020 by 20%, according to 2005\'s emission levels. Once the energy efficiency improvements are among the carbon mitigation actions specified by CCP, this present work aims to evaluate direct and indirect carbon dioxide equivalent emissions and energy consumption of supply chains in the Sao Paulo State\'s economy. Consequently, this study combines data from the Sao Paulo input-output matrix with the First Greenhouse Gas Emissions Inventory of Sao Paulo State (2011) and the Sao Paulo States Energy Balance (2010). All data used are based on 2004 values. Based on the CCP goal to reduce 20% in total emissions, this work assesses three simulations. The first simulation compares total emissions and energy by each final demand unit, whereas the second simulation applies the same method, but accounts for energy related emissions only. The third simulation is based on total direct and indirect emission mass. In addition, the work presents a comparison between all sectors in terms of their direct and indirect emissions, which is conveyed by emission multipliers. In addition, the total effect of each sector which is related to the direct and indirect emissions generated to one final demand unit, was assessed. Based on the results of the 3 simulations it was possible to see that indirect emissions represent almost 30% of the total emissions, and although this number is not more representative, in some cases sector\'s responsibility is greater if indirect emissions are accounted for. Results from Simulation 1 identify the sectors that stand out because of high energy and emission total effects: Other extractive industry and Cement. In comparision, if only total emissions effect are considered Cement and Livestock sectors stand out with approximately 3.5 GgCO2e emitted direct and indirectly for each 1 mi BRL of final demand, for each sector. Then, according to Simulation 2, the sectors that stand out are: Cement and Steel manufacture and products with respectvely 1.4 GgCO2e and 0.5 GgCO2e of total emissions emitted by each 1 mi BRL consumed by sector. Lastly, on Simulation 3, Transport is the sector that stands out with 23% of direct emissions, and 9% of the sum of indirect emissions, due to embodied emissions on services and products demand. Regarding indirect emissions, Food and beverage stands out, encompassing 17% of the indirect emissions and only 2% of total direct emissions.

A Política Estadual de São Paulo de Mudanças Climática (PEMC) foi lançada em 2009. Esta política voluntária, independente de qualquer acordo nacional ou internacional, foi estabelecida para reduzir a emissão dos gases de efeito estufa em 2020 em 20%, de acordo com os níveis de 2005. Uma vez que a melhoria da eficiência energética está entre as ações de mitigação de emissões de carbono especificadas pela PEMC, este trabalho visa avaliar as emissões diretas e indiretas e o consumo energético das cadeias produtivas na economia do Estado de São Paulo. Conseqüentemente, este estudo combina dados da Matriz Insumo Produto com o Primeiro Inventário de Gases de Efeito Estufa do Estado de São Paulo (2011) e o Balanço Energético (2010). Todos os dados estão baseados nos valores do ano de 2004. O trabalho avalia três simulações. A primeira simulação compara as emissões totais e energia por unidade de demanda final, já a segunda simulação aplica o mesmo método, porém apenas contabiliza as emissões de energia. A terceira simulação é baseada na massa total de emissões diretas e indiretas e foi determinada por meio dos multiplicadores. Além disso, o efeito total de cada setor está relacionado às emissões diretas e indiretas geradas por uma unidade de demanda final. Baseado nos resultados das três simulações foi possível observar que as emissões indiretas representam quase 30% sobre as emissões totais, e que apesar deste número não ser mais representativo, a responsabilidade do setor é maior se as emissões indiretas forem consideradas. Os resultados da Simulação 1, identificam os setores que se destacam devido a altos geradores de emissões e energia: Outros da indústria extrativa e Cimento, de outro modo, se apenas os geradores das emissões fossem considerados Cimento e Pecuária teriam se destacado com aproximadamente 3,5 GgCO2e emitidos direta e indiretamente por 1 milhão de reais de demanda final. Já, de acordo com a Simulação 2, os setores que se destacam são: Cimento e Frabricação de aço e derivadoscom respectivamente 1,4 GgCO2e e 0,5GgCO2e de emissões totais emitidas por 1 milhão de reais de demanda final. Por fim, na Simulação 3, o setor de Transportes se destaca com 23% das emissões diretas, enquanto é responsável por 9% das emissões indiretas, correspondentes às emissões incorporadas pela demanda por serviços e produtos. Por outro lado, o setor Alimentos e bebidas é o que mais se destaca devido a 17% das emissões indiretas apesar de apresentar apenas 2% do total das emissões diretas. / The Sao Paulo State Climate Change Policy (CCP) was established in 2009. This voluntary policy, independent of any domestic and international accord, was established to reduce greenhouse gas emissions in 2020 by 20%, according to 2005\'s emission levels. Once the energy efficiency improvements are among the carbon mitigation actions specified by CCP, this present work aims to evaluate direct and indirect carbon dioxide equivalent emissions and energy consumption of supply chains in the Sao Paulo State\'s economy. Consequently, this study combines data from the Sao Paulo input-output matrix with the First Greenhouse Gas Emissions Inventory of Sao Paulo State (2011) and the Sao Paulo States Energy Balance (2010). All data used are based on 2004 values. Based on the CCP goal to reduce 20% in total emissions, this work assesses three simulations. The first simulation compares total emissions and energy by each final demand unit, whereas the second simulation applies the same method, but accounts for energy related emissions only. The third simulation is based on total direct and indirect emission mass. In addition, the work presents a comparison between all sectors in terms of their direct and indirect emissions, which is conveyed by emission multipliers. In addition, the total effect of each sector which is related to the direct and indirect emissions generated to one final demand unit, was assessed. Based on the results of the 3 simulations it was possible to see that indirect emissions represent almost 30% of the total emissions, and although this number is not more representative, in some cases sector\'s responsibility is greater if indirect emissions are accounted for. Results from Simulation 1 identify the sectors that stand out because of high energy and emission total effects: Other extractive industry and Cement. In comparision, if only total emissions effect are considered Cement and Livestock sectors stand out with approximately 3.5 GgCO2e emitted direct and indirectly for each 1 mi BRL of final demand, for each sector. Then, according to Simulation 2, the sectors that stand out are: Cement and Steel manufacture and products with respectvely 1.4 GgCO2e and 0.5 GgCO2e of total emissions emitted by each 1 mi BRL consumed by sector. Lastly, on Simulation 3, Transport is the sector that stands out with 23% of direct emissions, and 9% of the sum of indirect emissions, due to embodied emissions on services and products demand. Regarding indirect emissions, Food and beverage stands out, encompassing 17% of the indirect emissions and only 2% of total direct emissions.

Purpose: The purpose of this study is to identify incentives and discouragements thus providinga better understanding of how metal processing companies could set their Scope 3 boundary. Method: To achieve the purpose of the study, a qualitative case study with an inductive approach was used. The studied company was a global metal processing company that was working towards setting a Scope 3 boundary, and the data consists of semi-structured interviews that were gathered from both internal and external stakeholders. Findings: Firstly, the findings presented, highlight incentives that affected companies in the metal processing industry to pursue setting a Scope 3 boundary, namely incentives that are categorised into 1) Improved corporate environmental reputation, 2) Increased competitive advantage, and 3) Financial gains. The discouragements found were categorised into 1) High uncertainty, 2) Immature industry/technical solutions, and 3) Low influence outside of the organisational boundary. These incentives and discouragements were analysed to show how they affected the Scope 3 boundary. This resulted in an industry-specific guideline on how companies in the metal processing industry could set their Scope 3 boundary. Theoretical contribution: The findings prolong earlier research by defining incentives and discouragements in a Scope 3 context. A theoretical contribution from this study was that regulations might inhibit some of the Scope 3 incentives. The findings indicate that drivers to benchmark against other stakeholders, such as differentiating from competitors and improved corporate sustainable reputation. A non-regulatory market environment is, therefore, fostering these incentives, which could be useful to acknowledge in further studies in a Scope 3 context. Practical implications: This study provides an enhanced understanding of how metal processing companies can set their Scope 3 boundary based on what set of incentives or discouragements that drives them. It is also important for companies to understand incentives and discouragements that may change (e.g., regulations towards Scope 3 emissions) in time, which would result in different Scope 3 boundaries. Also, this understanding of what incentives and discouragementsaffecting the boundary-setting could benefit policymakers in their work improving the Scope 3 discouragements.

To combat climate change multiple initiatives have been launched to steer the financial market towards a more sustainable and resilient path. For example the Montreal Pledge that have committed over 120 investors to measure and disclose their carbon footprints of their portfolios. ISS-Ethix Climate Solution provides climate change related services to investors. In order to evaluate companies’ sustainability ISS-Ethix Climate Solution estimates companies’ direct and indirect greenhouse gas emissions. To simplify these estimations, the emissions from corporations are divided into three scopes, where scope 1 and 2 cover the emissions from the combustion of fuels used in the company and electricity generation. Scope 3 corresponds to all other emissions generated upstream and downstream the companies’ supply chain. The aim of this study was to help ISS-Ethix Climate Solution to develop a model that estimates the indirect scope-3-emission intensity for companies in the automobile sector, fossil fuel sector and utility sector. The first objective was to examine if the variations within the sectors could be explained and categorized. To carry this out each sector was defined and their emission sources identified. The emissions could be explained and categorized for the automobile sector and fossil fuel sector. However, the emissions for the utility sector could only partly be explained and categorized. The second objective was to examine which parameters and subcategories were relevant for estimating the emissions. Two methods were investigated to carry out the second objective; correlation analysis and the average-data method. No correlations could be found between any of the sectors and the selected parameters. The estimated emissions using the average-data method were verified to the companies reported emissions. For the automobile and the fossil fuel companies the estimated emissions followed the same trend as the reported data. However, no trend could be found for the utility companies. Estimating emissions using the average-data method requires a certain corporation structure. The method can be used for corporations with a specific output, but does not suit corporations with a more complex structure. The largest limitation with the models was the information shortages from the corporations. Therefore increased transparency from the companies is a necessity in order to develop the models. / För att minska klimatförändringen har ett flertal initiativ lanserats för att göra finanssektorn mer hållbar. Tillexempel Montreal förbindelsen som har fått över 120 investerare att mäta och publicera klimatutsläppen i sina aktieportföljer. Företaget ISS- Ethix Climate Solution erbjuder klimatrelaterade tjänster för investerare. För att värdera hur hållbart ett företag är estimerar ISS-Ethix deras direkta och indirekta utsläpp av växthusgaser. För att förenkla dessa estimeringar är utsläppen indelade i tre så kallade scopes (områden), där scope 1 och 2 motsvarar emissionerna som genereras av att företaget förbränner fossila bränslen och deras elanvändning. Scope 3 motsvarar alla utsläpp som sker uppströms och nedströms företagens leverantörskedja. Syftet med denna studie var att hjälpa ISS-Ethix Climate Solution att utveckla en modell som estimerade scope 3 utsläppen från företag inom fordonssektorn, fossila- bränslen-sektorn och energisektorn. Det första målet var att undersöka om variationerna inom sektorerna kunde förklaras och kategoriseras. Detta utfördes genom att varje sektor först definierades och utsläppskällorna identifierades. Emissionerna kunde förklaras och kategoriseras för fordonssektorn och fossila-bränslen-sektorn. Däremot kunde utsläppen från energisektorn bara delvis förklaras och kategoriseras. Det andra målet var att undersöka vilka parametrar och sub-kategorier som var viktiga för att estimera sektorernas emissioner. För att göra detta undersöktes två olika metoder; korrelationsanalys och medelvärdesmetoden. Inga korrelationer kunde hittas mellan någon av sektorerna och de undersökta parametrarna. De estimerade emissionerna när medelvärdesmetoden användes, verifierades mot företagens självrapporterade utsläpp. För fordonssektorn och fossila-bränslen-sektorn följde de estimerade och rapporterade utsläppen samma trend. Däremot påträffades ingen trend för energibolagen. Att estimera växthusgasutsläpp med hjälp av en medelvärdesmetod kräver en viss typ av företagsstruktur. Metoden kan användas för företag med en specifik produkt, men är inte lämplig för företag med en mer komplex struktur. Modellernas största begränsning var informationsbristen från företagen. Därför behövs mer transparens från företagen för att kunna utveckla modellerna.