No description available.

Pollution is one of humanity's most pressing problems. Although there are many types of pollution, air pollution is one of the main causes of global warming. Therefore, simultaneously improving environmental quality and economic growth, and studying the variables that affect this relationship, has been one of the key issues for researchers and policymakers in recent years, especially in the wake of the United Nations 2030 Agenda for Sustainable Development.This paper aims to estimate the relationship between carbon emissions, GDP per capita, renewable energy and non-renewable energy sources as well environmental taxes in G10 industrialized countries over the period 1972-2020. Regression analysis and panel data were used to answer the questions. Previous studies of the Ecological Kuznets Curve (EKC) for CO2 emissions, with most samples based on G10 member countries, have had mixed results. The environmental Kuznets curve shows that economic development initially leads to environmental degradation, but once economic growth reaches a certain level, the relationship between society and the environment begins to improve and the degree of environmental degradation decreases. From a very simple perspective, this might suggest that economic growth is good for the environment. Critics, however, argue that economic growth is not guaranteed to lead to environmental improvements, which can often backfire. At the very least, it requires very targeted policies and attitudes to ensure that economic growth goes hand in hand with environmental improvement. / <p> Tre helt olika miljö-/BNP-kurvor</p><p>Studien undersöker etablerade teorier för att beskriva sambandet mellan miljöskador och ekonomisk aktivitet, inklusive Environmental Kuznets Curve (EKC), Brundtland Curve Hypothesis (BCH) och Environmental Daly Curve (EDC).</p>

Flying can constitute as much as a third of an academic institution’s total emissions and there’s a growing concern among researchers around their academic travel contributing to global warming. This paper is part of KTH FLIGHT, a research project for decreased CO2-emissions in flight-intensive organizations through creation and testing of practical tools. It is a Research through Design work that provides new knowledge about a previously largely unexplored implementation area of emission trading systems like Cap and Trade. These have previously helped reduce emissions at lower costs than tax based systems in various settings but little research exists in terms of design and important factors for a university to promote more sustainable travel patterns. This paper reveals challenges and opportunities regarding implementation and shows current feasibility in implementing in a Swedish university (KTH), and provides suggestions for choosing suitable users and direction of future research. / Flygresor kan utgöra upp till en tredjedel av en akademisk institutions totala utsläpp och det finns en växande oro bland forskare kring att deras resande bidrar till den globala uppvärmningen. Denna rapport är en del av KTH FLIGHT, ett forskningsprojekt med syfte att minska CO2 -utsläpp i flygintensiva organisationer genom att skapa och testa praktiska verktyg. Detta är ett Research through Design-arbete som bidrar med ny kunskap om ett tidigare till stor del outforskat område för implementeringar av utsläppshandelssystem såsom Cap and Trade. Dessa har i olika sammanhang tidigare bidragit till minskade utsläpp med lägre kostnader än skattebaserade system. Men i dagsläget finns det lite forskning gällande dess design och viktiga faktorer för att främja mer hållbara resvanor på ett universitet. Denna uppsats visar på utmaningar och möjligheter vid en implementering och visar aktuell genomförbarhet i ett svenskt universitet (KTH), samt ger förslag på val av lämpliga användare samt inriktning för framtida forskning.

No description available.

Copper processing plants involved in smelting, electro-refining and electro-winning are heat-intensive undertakings that provide extensive challenges for attainment of high energy efficiency. Literature has shown that most of these plants, especially smelters, operate at low overall energy efficiency due to the seemingly complex energy scenario where heat and electricity as forms of energy are treated distinctively from each other. Many copper processing plants have not yet explored both available and emerging waste heat recovery technologies hence remain operating at lower energy efficiencies. In the copper processing plants under study in particular the Nchanga tailings leach plant (TLP), plant operators hinted that some of the processes that ought to operate in heated environments operate at ambient temperatures because of lack of a heating mechanism. The project discusses possible heating mechanisms from available local resources and applicable technologies. As the competing options for providing the required heat at the Nchanga TLP present different carbon emission scenarios, the carbon emissions associated to the recommended installations shall be quantified against a suitable baseline. Flue gas waste heat from the nearby Nchanga smelter has been taken as the available local energy source on which the applicable heating scenarios at TLP are analyzed. The project analyzed waste heat scenarios for three furnaces at Nchanga smelter where it has been established that flue gases from the furnaces contain 37.31 MW of waste heat. Analysis for channeling the waste heat into heat recovery steam generators gave the steam turbine power generation potential of 7.06 MW. The project also demonstrated how energy efficiency undertakings can be used as a driver for carbon emission reduction measures and for participation to the available carbon trading mechanisms such as CDM. Selection of suitable baseline scenarios revealed a lot of potential for carbon finance undertakings in the three case study plants. At the Nchanga smelter, the 7.06 MW power generation capacity has an associated potential of 61,820 tCO2/year emission reductions that can be monetized through the available carbon trading markets. The research established that Nchanga TLP has a heating demand of 10.87MW. If this heating demand was to be met by using the smelter waste heat, the undertaking can be taken as CDM activity or other carbon trading platform with an associated potential of 95,183 tCO2/year.

台灣為海島型國家，因自有能源貧乏，99%以上的能源仰賴國外進口。為確保能源供給之穩定與安全，除發展再生能源之外，提高能源終端使用效率為重要之解決手段。熱泵系統因其獨特之節能減碳效果，在歐美先進國家備受重視，極力推廣。基此，考量台灣氣候類型及居住型態，評估熱泵熱水系統的適用性及成本效益分析，爰為本研究之動機與目的。 為了彰顯應用熱泵系統在不同地區氣候條件與能源價格之差異，本研究將台灣劃分為12個地區，並且以電能、LPG桶裝瓦斯、NG管線瓦斯三種現有之住宅用熱水系統作為可供替代之選項，利用迴避成本(Avoided Cost)推估台灣各地區住宅部門改採熱泵熱水系統之成本效益。此外，參考歐美先進國家熱泵系統補助政策，以及台灣現有「太陽能熱水系統推廣獎勵措施」之政府政策補助方案，設定各相關參數，俾模擬政府補貼方案情境下之成本效益分析。 分析結果以淨現值(Net Present Value)、益本比(Benefit-Cost Ratio)及折現回收期(Discounted Payback Period )呈現，結論可從兩個觀點之檢定加以評估。其一、以「參與者檢定」評估是否有足夠的經濟誘因，促使住宅用戶裝設熱泵熱水系統。其二、以「總資源成本檢定」，評估推廣熱泵系統對於整體社會是否具有淨效益。 本研究中全台12個地區，若以熱泵系統取代電能熱水系統、LPG瓦斯熱水系統、NG瓦斯熱水系統三種既有設備，交叉比對之33個替代方案，由「參與者檢定」之結果顯示，所有替代方案之益本比均大於1.1；折現回收期最長達11.3年，最短僅3.2年。若模擬政府補助18,000名用戶採用熱泵系統，則「總資源成本檢定」之結果中，所有替代方案之益本比介乎1至1.73之間；折現回收期最長達14.9年，最短僅5.4年；住宅部門以熱泵替代現有電能、LPG瓦斯、NG瓦斯熱水系統至少可降低碳排放量每年2,707公噸。三種替代類別中以電能熱水系統替代方案益本比最高(介乎1.55至1.73)；LPG瓦斯替代方案之益本比居次(介乎1.19至1.28)；NG瓦斯替代方案益本比最低(介乎1.0至1.06)。全台12個地區考量環境溫度差異之影響以南投分區改採熱泵系統的益本比最高(電能替代1.73、LPG瓦斯替代1.28、NG瓦斯替代1.06)，屏東分區的益本比為最低(電能替代1.55、LPG瓦斯替代1.19、NG瓦斯替代1.0)。 若考量熱泵系統市場滲透率，以熱泵取代NG瓦斯熱水系統之市佔率達5%、20%、50%時，台灣整體社會的淨現值分別為251百萬元、1,006百萬元與2,514百萬元，且每年可減少碳排放量27,169公噸、108,675公噸以及271,687公噸。 / As an island country, 99% energy supply in Taiwan depends on importation due to the very limited endogenous energy. In order to maintain both energy security and stability, improving energy efficiency of consumer end-use is an important government policy. Heat pump systems have been widely applied and strongly promoted in Europe and United State for its uniquely energy saving and CO2 reducing capability. Therefore, the motivation of this study is to access the regional applicability of heat pump water heating system for Taiwan’s climate and residential building types by cost-benefit analysis method. To demonstrate the regional difference of climatic conditions and energy prices heat pump application, Taiwan is divided in twelve regions with three kinds of alternative residential water heating systems (i.e. electric heating, LPG tank heating, and NG pipe heating). Under these conditions, we utilize the avoided cost method to access itemized costs and benefits of heat pump water heating systems in various regional families in Taiwan. In addition, referring to heat pump incentive scheme in advanced European countries and North America while considering solar water heating systems incentive policy in Taiwan, we also simulate variation of parameters (such as cash rebate subside, total residential heat pump user numbers )of heat pump system subsidy program. The outcome of cost-benefit analysis is presented in a form as net present value (NPV), benefit-cost ratio (BCR), and discounted payback period (DP). The results could be analyzed by test from two different perspectives including Participant Test (PCT) from participant perspective and Total Resource Cost Test (TRC) from overall sociality perspective. All of the 33 alternative programs constituted by 12 regions with electric , LPG and NG systems, for PCT, BCR, all 33 alternative programs are greater than 1.1; DP are between 3.2 to 11.3 years. For TRC, BCR, all 33 alternative programs are greater than 1 but less than 1.73; DP are between 5.4 to 14.9 years. Residential building adopting heat pump could reduce 2,707 tons carbon emissions annually. For the three types of alternative system, BCR of electric heating alternative program is the largest and NG alternative program being the least. For all of the 12 regions, BCR of Nantou region is the largest for adopting heat pump while BCR of Pingtung region is the smallest. NPV of overall Taiwan with market penetration reaching 5%, 20% and 50% substitution rate from heat pump system to NG water heating system are 251 million NT$, 1,006 million NT$, and 2,514 million NT$ respectively. Carbon emissions reduce 27,169 tons, 108,675 tons and 271,687 tons annually.

都市CO2的過量排放，是造成全球氣候暖化與環境變異的主因之一。低碳都市的發展成為目前永續發展的核心議題，亦是抑制氣候暖化的關鍵。低碳都市的概念，包括空間和非空間維度。空間維度探討了都市型態、土地利用與運輸系統，非空間維度則著眼於經濟、能源使用和節能產品。然而過去低碳方面的研究，多聚焦於非空間維度之探討上，甚少關注空間維度面向，但面對全球氣候暖化與低碳發展，都市不僅可落實低碳發展政策，其規劃更在低碳都市的建設與發展過程中扮演關鍵角色。因此，本研究依循「全球考量，在地行動」之概念及方式，以低碳都市為主軸，並以空間規劃及環境經濟之角度切入，針對低碳都市衡量指標建構及分析、縣市低碳效率評估及低碳政策影響效果之探討、都市發展及空間結構與碳量間關係之探討等三項研究主題，進行實證分析與探討，企圖補強低碳都市在空間維度之論述，使都市的低碳化有所依循，亦使都市能藉此更達低碳與永續之目標。 在「低碳都市衡量指標系統之建構及探討」主題上，以台灣為實證案例，根據低碳都市的內涵、理念與目標，研撰適宜之衡量指標系統，透過因子分析定權法進行衡量指標的擇取，藉此評估台灣各縣市的低碳發展狀態。根據實證結果，顯示台灣的低碳都市評估指標系統，包括「環境品質及資源消耗」、「經濟及建設」、「財政及資源循環」、「社會狀態」等4構面，共22個指標；而台灣各縣市在低碳發展的綜合表現上，以台北市的狀態最佳，而以彰化縣表現最差。 而在「縣市低碳發展效率評估及低碳政策影響效果之探討」主題上，以台灣各縣市作為實證案例，在考量非意欲產出下(碳排放威脅、環境污染衝擊)，透過DEA中的不良產出模型(Bad Outputs Model)評估縣市低碳發展效率，並藉由Tobit模型，釐清低碳政策對縣市低碳發展效率之影響效果。依據不良產出模型之效率評估結果，顯示臺北市、新竹市、臺東縣、花蓮縣在低碳發展效率上相對具有效率，且已達最適規模水準；而高雄縣是目前亟待改善的首要縣市。此外，藉由Tobit模式的實證分析，其結果顯示工廠家數、資源回收量、市區公車系統路線總長、具綠建築標章的建物數、綠地面積等變數，對縣市低碳發展效率有顯著影響，其中，除工廠家數對縣市低碳發展效率有負向影響外，其餘變數皆呈正向影響效果。而由此亦得知產業結構、資源循環利用、低碳運輸、低碳建築、碳匯規劃等低碳政策，對於縣市低碳發展效率是顯著有效的。 在「都市發展及空間結構與碳量關係之探討」主題上，以台灣各縣市作為實證案例，透過偏最小平方法的分析，實證都市發展及空間結構對碳量之影響關係與影響程度，並找出低碳都市發展中關鍵的空間規劃要素。而根據偏最小平方法的實證結果，顯示都市混合度、都市發展強度及密度與都市綠化對碳淨存量產生負向影響，亦即都市混合度、都市緊密度及綠化程度愈高，愈能減少碳淨存量；而都市工業機能、都市交通狀態對碳淨存量有正向影響，亦即都市工業機能與都市交通狀態愈高，愈會增加碳淨存量，其中又以都市交通狀態的影響效果最大。 綜合上述，本研究之研究成果包括：「釐清低碳都市模糊且紛雜的概念及內涵」、「建構適宜台灣本土的低碳都市衡量指標系統」、「評估台灣各縣市低碳發展之整體狀態」、「評估台灣各縣市之低碳發展效率」、「檢視台灣現行低碳政策對於縣市低碳發展效率之影響效果」及「找出低碳都市發展中關鍵的空間規劃要素」，期待此些成果，能作為地方政府或規劃單位於低碳目標下，進行低碳都市發展及規劃開發時之參考。 / Excessive CO2 emission is one of the main causes of causing global warming and climate change. Therefore, low-carbon urban development is currently the core issue in sustainable development, and it is also the key to curb climate warming. The concept of the low-carbon city includes spatial dimension and non-spatial dimension. The former contains the issues of urban form, transportation system, and land use planning, the latter contains the issues of economy, energy consuming, and energy saving product. The spatial dimension plays the important role in the construction and development of the low-carbon city, but only the few studies focused on. Therefore, this paper takes the spatial dimension of the low-carbon city as the main scope, and discusses the topics of “research on low-carbon city indicator system”, “evaluating the low-carbon efficiency of city and analyzing its influential policies”, and “the effects of urban development and spatial structure on carbon emissions”. In the topics of “research on low-carbon city indicator system”, this paper takes cities and counties of Taiwan as the empirical cases, and uses factor analysis to establish the appropriate low-carbon city indicator system for Taiwan. Furthermore, this paper evaluates the cities'/counties' status of low-carbon developments by this low-carbon city indicator system. According to the empirical results, there are four evaluating aspects of the low-carbon city: 1) environmental quality and resource consumption, 2) economy and construction, 3) finance and resource recycling and 4) social status. Based on the comprehensive performance of the low-carbon city indicator system, Taipei City shows the best performance, whereas Changhua County shows the worst performance. In the topics of “evaluating the low-carbon efficiency of the city and analyzing its influential policies”, this paper takes cities and counties of Taiwan as the empirical cases, and assesses low-carbon efficiency of the city by Bad Outputs Model. Moreover, this paper uses Tobit Model to analyze the influence of low-carbon policies on the low-carbon efficiency of the city. According to the result of Bad Outputs Model, Taipei City, Hsinchu City, Taitung County, and Hualien County are efficiency, and achieve the optimal scale level. Moreover, Kaohsiung County is the county in the most urgent need of improvement. Another result of Tobit model indicates that the industrial unit has the negative impact on the low-carbon efficiency of the city. Moreover, resource recovery, the total length of the urban bus route, the number of green buildings, and green area all have the positive impact on the low-carbon efficiency of the city. In the topics of “the effects of urban development and spatial structure on carbon emissions”, this paper takes cities and counties of Taiwan as the empirical cases, and uses partial least squares method (PLS) to identify the impact of urban development and spatial structure on carbon emissions. The empirical results show that the mixed land use, urban intensity and density, and urban greening all have the negative impact on carbon emissions. Moreover, industrial function and urban transportation all have a positive impact on carbon emissions. Finally, these results can be used as reference for future low-carbon urban planning and policy.

Outdoor air pollution is a major contributor to adverse health effects of citizens, in particular those living in urban environments. Air quality monitoring networks are set up to measure air quality in different environments in compliance with national and European legislation. Generally, only a few fixed monitoring sites are located within a city and thus cannot represent air pollutant concentrations in urban areas accurately enough to allow for a detailed human exposure assessment. Other approaches to derive detailed urban air pollutant concentration estimates exist, such as dispersion models and land-use regression (LUR) models. Low-cost portable air quality monitors are also emerging, which have the potential to add value to existing monitoring networks by providing measurements at greater spatial resolution and also to provide individual-level exposure assessment. The aim of this thesis is to demonstrate how measurements and modelling in combination allow detailed investigations of the variability of air pollutants in space and time in urban area, and in turn improve on the current exposure assessment methods. Three types of low-cost portable monitors measuring NO2, O3 (Aeroqual monitors) and PM2.5 (microPEM monitor) were evaluated against their respective reference instruments. The Aeroqual O3 monitor showed very good correlation (r2 > 0.9) with the respective reference instruments, but biases in the slope and intercept coefficients indicated that calibration of Aeroqual O3 monitor was needed. The Aeroqual NO2 monitor was subject to cross-sensitivity from O3, which, as demonstrated, can be effectively corrected by making O3 and NO2 measurements in tandem. Correlation between the microPEM monitor and its reference instrument was poor (r2 < 0.1) when PM2.5 concentrations were low (< 10 μg m-3), but significantly improved (r2 > 0.69) during periods with elevated PM2.5 concentrations. Relative humidity was not found to affect the raw results of PM2.5 measurements in a consistent manner. All three types of monitors cannot be used as equivalent or indicative methods instead of reference methods in studies that require quantification of absolute pollutant concentrations. However, the generally good correlations with reference instruments reassure their application in studies of relative trends of air pollution. Concentrations of PM2.5, ultrafine particles (UFP) and black carbon (BC) were quantified using portable monitors through a combination of mobile and static measurements in the city of Edinburgh, UK. The spatial variability of UFP and BC was large, of similar magnitude and about 3 times higher than the spatial variability of PM2.5. Elevated concentrations of UFP and BC were observed along streets with high traffic volumes whereas PM2.5 showed less variation between streets and a footpath without road traffic. Both BC and UFP significantly correlated with traffic counts, while no significant correlation between PM2.5 and traffic counts was observed. The relationships between UFP, NO2 and inorganic components of PM2.5 were further investigated through long-term measurements at roadside, urban background and rural sites. UFP moderately correlated with NOx (NO2 + NO) and showed varying relationships with NOx depending on the particle size distribution. Principal component analysis and air-mass back trajectory analysis revealed that PM2.5 concentrations were dominated by long-range transport of secondary inorganic aerosols, whereas UFP were mainly related to varying local emissions and meteorological conditions. These findings imply the need for different policies for managing human exposure to these different particle components: control of much BC and UFP appears to be manageable at local scale by restricting traffic emissions; however, abatement of PM2.5 requires a more strategic approach, in cooperation with other regions and countries on emissions control to curb long-range transport of PM2.5 precursors. A dispersion model (ADMS-Urban) was used to simulate high resolution NO2 and O3 concentrations in Edinburgh. The effects of different emission and meteorological input datasets on the resulting modelled NO2 concentrations were investigated. The modelled NO2 and O3 concentrations using the optimal model setup were validated against reference instrument and diffusion tube measurements. Temporal variability of NO2 was predicted well at locations that were not heavily influenced by local effects, such as road junctions and bus stops. Temporal variability of O3 was predicted better than for NO2. Long-term spatial variability of NO2 was found to correlate well with diffusion tube measurements, while modelled spatial variability of O3 in ADMS-Urban compared poorly with diffusion tube measurements. However, it was found that the O3 diffusion tube measurements may be subject to some unidentified biases affecting their accuracy. Land-use regression (LUR) models are widely used to estimate exposure to air pollution in urban areas. An appropriately sized and designed monitoring network is an important component for the development of a robust LUR model. Concentrations of NO2 were simulated by ADMS-Urban at ‘virtual’ monitoring sites in 54 different network designs of varying numbers and types of site, using a 25 km2 area including much of the Edinburgh city area. Separate LUR models were developed for each network. These LUR models were then used to estimate ambient NO2 concentrations at all residential addresses, which were evaluated against the ADMS-Urban modelled concentration at these addresses. The improvement in predictive capability of the LUR models was insignificant above ~30 monitoring sites, although more sites tended to yield more precise LUR models. Monitoring networks containing sites located within highly populated areas better estimated NO2 concentrations across all residential locations. LUR models constructed from networks containing more roadside sites better characterised the high end of residential NO2 concentrations but had increased errors when considering the whole range of concentrations. No particular composition of monitoring network resulted in good estimation simultaneously across all residential NO2 concentration and of the highest NO2 levels implying a lack of spatial contrast in LUR-modelled pollution surface compared with the dispersion model. Finally, the results from the measurement and modelling studies presented in thesis are synthesised in the context of current exposure assessment studies. Low-cost air-quality monitors currently do not possess and are unlikely in the near future to provide the robustness and accuracy to replace the existing routine monitoring network. Development of the low-cost air-quality should be aiming at upgrading them as the indicative method as defined in the data quality objective in the EU directive. The monitoring sites used to build LUR models should capture well the population distribution in the study area as opposed to capturing the greatest pollution contrast. The traditional methods of evaluating LUR models are also ineffective in characterising the models’ capability at estimating pollutant concentration at residential address. Given that the dispersion models are also subject to the availability and uncertainties in the input data, future air quality model development should endeavour to incorporate both dispersion and land-use regression models, where the uncertainty in the input data can be reduced by using LUR models built on actual measurements, and the limitation in the statistical modelling can be replaced by adopting the deterministic approach used in the dispersion model.

Internprissättning av koldioxid (ICP) är ett verktyg som företag frivilligt kan tillämpa för att sätta ett ekonomiskt värde på sina utsläpp. Det kan i sin tur underlätta företags styrning mot lägre koldioxidutsläpp. Flera organisationer rekommenderar företag att arbeta med ICP, däribland Finansinspektionen och EU-kommissionen. Det finns inget facit på hur företag bör arbeta med ICP och det finns lite forskning inom området, i synnerhet svensk forskning. Enligt den forskning som finns är det tre ICP-metoder som är vanligast förekommande; Intern koldioxidavgift, skuggprissättning och intern handel med utsläppsrätter. Utifrån detta är syftet med denna studie att öka förståelsen för arbetet med ICP och undersöka om ICP kan effektivisera företags hållbarhetsarbete. Studien har genomförts med hjälp av forskningsintervjuer, där respondenter från tre företag intervjuats. Intervjuerna har strävat efter att svara på frågorna var, när, hur och varför företag tillämpar ICP. Utgångsläget för studien har varit en kvalitativ forskningsmetod med teoretisk bas som ansats. Vidare har en tematisk analys genomförts utifrån den teoretiska basen som består av en redogörelse för ekonomistyrningslitteratur, kontextuella teorier, tidigare forskning om ICP samt en praktisk ICP-guide. Studien har påvisat att ICP används vid beslutsfattande och att det kan användas både på operativ och strategisk nivå. Vidare kan studien konstatera att skuggprissättning är den vanligaste metoden i de studerade företagen. Motivet till ICP-arbetet varierar men ett generellt motiv som studien identifierat är att ICP används för att styra beslut i rätt strategisk riktning. Även riskhantering är ett motiv som är ständigt återkommande i studiens empiri och ICP används då för att förbereda verksamheten mot framtida eventuella koldioxidregler. Slutligen konstaterar studien att ICP i viss utsträckning kan effektivisera företags hållbarhetsarbete. / Internal Carbon Pricing (ICP) is a self-regulation tool that companies voluntarily can apply to add an economic value on their GHG emissions. ICP can facilitate controlling and steering towards lower GHG emissions. Several organizations recommend companies to work with ICP, including the Swedish Financial Supervisory Authority and the European Commission. There is not one solution on how companies should work with ICP and there is little research in the area, especially Swedish research. According to the available research, however, three ICP methods are the most common; Internal carbon fee, shadow pricing and internal emissions trading. Based on this, this study aims to increase the understanding of the work with ICP and whether ICP can improve companies' sustainability work. The study was conducted with the help of research interviews, where respondents from three companies were interviewed. The interviews have sought to answer the questions of where, when, how and why companies apply ICP. The starting point for the study has been a qualitative research method with a theoretical base. A thematic analysis has been carried out on the basis of literature review, on the basis of previous research on ICP and on the basis of previous examples on how companies work with ICP. The study has concluded that ICP is used in decision-making and that it can be used in decisions made at both operational and strategic levels. Furthermore, the study can state that shadow pricing is the most common method in the cases studied. The motive behind the ICP work varies, but a general motive that the study has identified is that ICP is used to steer decisions in the right strategic direction. Risk management is also a motive that is constantly recurring in the study's empirical data, where ICP is used to prepare the business for future possible carbon regulations. Finally, the study states that ICP to a certain extent can improve companies' sustainability work.

The purpose of this master thesis is to develop a model to estimate the carbon intensity, i.e the carbon emission relative to economic activity, of publicly traded companies which do not report their carbon emissions. By using statistical and machine learning models, the core of this thesis is to develop and compare different methods and models with regard to accuracy, robustness, and explanatory value when estimating carbon intensity. Both discrete variables, such as the region and sector the company is operating in, and continuous variables, such as revenue and capital expenditures, are used in the estimation. Six methods were compared, two statistically derived and four machine learning methods. The thesis consists of three parts: data preparation, model implementation, and model comparison. The comparison indicates that boosted decision tree is both the most accurate and robust model. Lastly, the strengths and weaknesses of the methodology is discussed, as well as the suitability and legitimacy of the boosted decision tree when estimating carbon intensity. / Syftet med denna masteruppsats är att utveckla en modell som uppskattar koldioxidsintensiteten, det vill säga koldioxidutsläppen i förhållande till ekonomisk aktivitet, hos publika bolag som inte rapporterar sina koldioxidutsläpp. Med hjälp av statistiska och maskininlärningsmodeller kommer stommen i uppsatsen vara att utveckla och jämföra olika metoder och modeller utifrån träffsäkerhet, robusthet och förklaringsvärde vid uppskattning av koldioxidintensitet. Både diskreta och kontinuerliga variabler används vid uppskattningen, till exempel region och sektor som företaget är verksam i, samt omsättning och kapitalinvesteringar. Sex stycken metoder jämfördes, två statistiskt härledda och fyra maskininlärningsmetoder. Arbetet består av tre delar; förberedelse av data, modellutveckling och modelljämförelse, där jämförelsen indikerar att boosted decision tree är den modell som är både mest träffsäker och robust. Slutligen diskuteras styrkor och svagheter med metodiken, samt lämpligheten och tillförlitligheten med att använda ett boosted decision tree för att uppskatta koldioxidintensitet.