Global warming, associated with elevated levels of greenhouse gases is expected to alter hydrologic regimes, permafrost extent and vegetation composition in the Hudson Bay Lowlands (HBL). Greenhouse gas (respiration, CH4 and N2O; GHG) emissions and soil gas concentrations were determined over the growing seasons of 2005 and 2006 from numerous habitats within three dominate ecosystems within the HBL, a polygonized-peat plateau, northern fringe boreal forest and palsa fen, near Churchill, Manitoba. Nitrous oxide emissions and soil concentrations were near zero however, a trend for very slight production of N2O was observed at dry aerobic sample positions while very slight consumption occurred at very wet sample locations. “Hot-spots” of intense CH4 emissions and soil concentrations occurred in the sedge-dominated areas of high moisture and plant productivity, whereas areas of low moisture and plant productivity resulted in slight CH4 consumption. Of all the ecosystems studied, the palsa fen had the greatest CH4 production, with carbon losses from CH4 occurring at rates of approximately 50 g C m-2 during the growing season. A peat plateau ecosystem site was also used to compare GHG emissions using a similar vegetation type (Cladina stellaris) and under differing soil conditions. Based on the results, slight gradients in soil conditions such as moisture content, peat accumulation and active layer depths altered respiration emissions but did not significantly affect CH4 and N2O fluxes. The differences in GHG emissions were not as great as those between different plant community types, which suggest plant community types could be used to predict GHG emissions in similar environments.

Global warming, associated with elevated levels of greenhouse gases is expected to alter hydrologic regimes, permafrost extent and vegetation composition in the Hudson Bay Lowlands (HBL). Greenhouse gas (respiration, CH4 and N2O; GHG) emissions and soil gas concentrations were determined over the growing seasons of 2005 and 2006 from numerous habitats within three dominate ecosystems within the HBL, a polygonized-peat plateau, northern fringe boreal forest and palsa fen, near Churchill, Manitoba. Nitrous oxide emissions and soil concentrations were near zero however, a trend for very slight production of N2O was observed at dry aerobic sample positions while very slight consumption occurred at very wet sample locations. “Hot-spots” of intense CH4 emissions and soil concentrations occurred in the sedge-dominated areas of high moisture and plant productivity, whereas areas of low moisture and plant productivity resulted in slight CH4 consumption. Of all the ecosystems studied, the palsa fen had the greatest CH4 production, with carbon losses from CH4 occurring at rates of approximately 50 g C m-2 during the growing season. A peat plateau ecosystem site was also used to compare GHG emissions using a similar vegetation type (Cladina stellaris) and under differing soil conditions. Based on the results, slight gradients in soil conditions such as moisture content, peat accumulation and active layer depths altered respiration emissions but did not significantly affect CH4 and N2O fluxes. The differences in GHG emissions were not as great as those between different plant community types, which suggest plant community types could be used to predict GHG emissions in similar environments.

Climate change is arguably the most important global societal challenge. Developing ‘low-carbon societies’, i.e. reducing greenhouse gas (GHG) emissions and adapting to a changing climate, is becoming a policy goal across the globe. Agriculture plays an important role in this transformation. The sector is highly vulnerable to climate variability, and is a significant source of emissions. At the same time, it has potential for reducing GHG emissions and also provides opportunity for carbon sequestration in soils and crop biomass. Policy support for mitigating GHG emissions is being informed by scientific evidence on the effectiveness and costs of mitigation opportunities. This information is frequently depicted in marginal abatement cost curves (MACCs), an assessment tool which can help to visualise the hierarchy of technical measures and their cumulative level of abatement. Similarly to other assessment tools, MACCs’ suitability to provide information has certain limitations. Furthermore, different derivations of MACCs are appropriate to answer different questions. In order to draw both informative and reliable conclusions for policy decisions, the characteristics of the MACCs and the resulting limitations have to be presented clearly. This dissertation seeks to answer the general question whether the agricultural MACCs can be improved so that they provide more comprehensive and tailored information to policy makers. In particular five limitations of the MACCs are discussed: the lack of representation of wider effects, the issue of cost-effectiveness of policy instruments and the inclusion of transaction costs, the uncertainty in the MACCs, the boundaries and the heterogeneity of the analysis. Theoretical frameworks are developed and case study examples are provided for these limitations, and the frameworks are assessed in terms whether they achieve the goal of providing more comprehensive information to policy makers than a conventional MACC. Furthermore, the dissertation summarises the available methodologies and applications in agriculture to enhance the MACCs and provides guidelines for researchers and policy makers about the choice of methods and the communication of the results in order to improve the use of MACCs in the policy process.

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We are currently experiencing a climate crisis. The planet’s temperature is rising considerably due to the emission of greenhouse gases generated by human activities. This situation poses a challenge for everyone, including companies. Private sector actors are taking actions to mitigate the consequences of climate change, such as global warming. Some of these measures are imposed by national regulations, and others are motivated by the firms' own will. The latter include Science Based Target initiative (SBTi), a voluntary initiative that supports companies in setting climate targets to reduce emissions in line with climate science and the Paris Agreement. The number of companies taking action through participation in it is growing. However, SBTis a young initiative that should be further explored, as more research is needed on its effects. This master’s thesis responds to this gap by studying the impact of joining the SBTi on the financial performance of companies measured through stock returns, volatility and financial risk. For this purpose, the Difference-in-Differences (DiD) statistical technique has been applied through a linear regression model to a sample of 4869 companies. It includes both SBTi member and non-members. At the same time, this research also addresses a second objective, to estimate the determinants to join SBTi, since this is a voluntary action, through a Probit model. It has been found that there is a negative relationship when the financial variable is stock return. While when volatility and financial risk are measured, there is no statistically significant effect. These findings show that being a member of SBTi could reduce investor returns, but does not influence the other two financial indicators. This suggests that investors are not attracted to these companies and may indicate that they see the initiative as a costly distraction. Also, as investors manage their portfolios to reduce market downturns, investing in firms that are part of the initiative will not be something they will consider in terms of their votality. Although the initiative's objectives and commitments help to mitigate climate risks by encouraging the reduction of carbon dioxide emissions, they do not generate significant impacts on the level of financial risk, according to the observations. Regarding the results on the likelihood of joining SBTi, it was found that companies that produce lower returns to investors, have lower stock price fluctuations, have higher financial risk and pollute less, are more likely to be members. This suggests that the initiative should drive its efforts towards companies with these characteristics. This study is innovative in its field in that it addresses a topic of current interest but that has been little explored, the SBTi. It applies two methodologies, regression analysis through DiD and Probit model, but with global panel data, which makes it more challenging. This master’s thesis contributes to the research community in three ways. First, it fills a gap providing new insights into SBTi from a financial perspective. Second, it informs the initiative itself of the implications of its activity and makes it easier to identify potential members and attract them. Third, it can be useful for investors who want to be part of the fight against climate change and include these companies in their portfolios, but want to know the financial consequences of doing so. / Vi upplever för närvarande en klimatkris. Planetens temperatur stiger avsevärt på grund av utsläppen av växthusgaser som genereras av mänsklig verksamhet. Denna situation utgör en utmaning för alla, inklusive företag. Privata aktörer vidtar åtgärder för att mildra konsekvenserna av klimatförändringar, såsom global uppvärmning. Vissa av dessa åtgärder föreskrivs av nationella regleringar, medan andra motiveras av företagens egna vilja. Det senare inkluderar SBTi, en frivillig initiativ som stödjer företag i att fastställa klimatmål för att minska utsläppen i linje med klimatvetenskapen och Parisavtalet. Antalet företag som vidtar åtgärder genom deltagande i initiativet ökar. Dock är SBTi en ung initiativ som bör undersökas mer, eftersom merforskning behövs om dess effek. Denna avhandling fyller detta gap genom att studera effekten av att delta i SBTi på företagens finansiella prestationer, mätt genom aktieavkastning, volatilitet och finansiell risk. För detta ändamål har den statistiska tekniken DiD tillämpats genom en linjär regressionsmodell på ett urval av 4869 företag. Det omfattar både medlemmar och icke-medlemmar av SBTi. Samtidigt behandlar denna forskning även ett andra mål, att uppskatta faktorer som påverkar beslutet att delta i SBTi, eftersom detta är en frivillig åtgärd, genom en Probit-modell. Det har konstaterats att det finns ett negativt samband när den finansiella variabeln är aktieavkastning. När volatilitet och finansiell risk mäts finns det däremot ingen statistiskt signifikant effekt. Dessa resultat visar att att vara medlem i SBTi kan minska avkastningen för investerare, men påverkar inte de andra två finansiella indikatorerna. Detta tyder på att investerare inte lockas av dessa företag och kan indikera att de ser initiativet som en kostsam distraktion. Dessutom, eftersom investerare hanterar sina portföljer för att minska marknadsnedgångar, kommer investeringar i företag som är en del av initiativet inte vara något de överväger med avseende på volatilitet. Även om initiativets mål och åtaganden bidrar till att mildra klimatrisker genom att främja minskning av koldioxidutsläppen, genererar de inte signifikanta effekter på finansiell risknivå enligt observationerna. Vad gäller resultaten angående sannolikheten att delta i SBTi, visade det sig att företag som ger lägre avkastning till investerare, har lägre aktieprisfluktuationer, har högre finansiell risk och förorenar mindre, har större sannolikhet att vara medlemmar. Detta tyder på att initiativet bör rikta sina ansträngningar mot företag med dessa egenskaper. Denna studie är nyskapande inom sitt område genom att den behandlar ett ämne av aktuellt intresse men som är relativt outforskat, nämligen SBTi. Den tillämpar två metoder, regressionsanalys med DiD och en Probit-modell, men med globala paneldata, vilket gör det mer utmanande. Denna avhandling bidrar till forskarsamhället på tre sätt. För det första fyller den en lucka genom att ge nya insikter om SBTi ur ett finansiellt perspektiv. För det andra informerar den själva initiativet om konsekvenserna av dess verksamhet och underlättar identifieringen av potentiella medlemmar och att locka dem. För det tredje kan den vara användbar för investerare som vill vara en del av kampen mot klimatförändringar och inkludera dessa företag i sina portföljer, men som vill känna till de finansiella konsekvenserna av att göra det.

Research report, presented to the SBL Unisa, Midrand. / The current and future anticipated changes in the earth’s climate are a concern that has captured business’s and governments’ global attention. Climate change and its potential impacts cannot be ignored as there is ample evidence that global warming is indeed the result of anthropogenic greenhouse gas emissions. The mobile operator in Africa and the Middle East (ME) operates on continents and in parts of the world, predicted by scientists as the most vulnerable to the effects of climate change. The mobile operator in Africa and the Middle East is moreover an emitter of significant amounts of CO2 and this exacerbates the serious environmental climate change problem that humankind faces. This research paper addresses the Corporate Social Responsibility of African and Middle East (ME) mobile operators, and its Carbon Footprint. The main objectives of the research are to identify strategic risks and opportunities and the implications for the mobile operator and to determine its Greenhouse Gas emissions. The performance against targets and plans to reduce GHG emissions are also reviewed. The research is based on the questionnaire of the Carbon Disclosure Project (CDP) initiative. A shortened and modified version of the CDP was designed and emailed to two major mobile telecom operators both operating in Africa and the Middle East. It is postulated that the telecommunications industry is at an inflection point where significant changes must take place in the way energy requirements are managed. This in turn could have a positive effect on reducing its carbon footprint, benefit corporate reputation and at the same time earn “green miles” in the subscriber’s minds. The research reached the main conclusion that the mobile operators’ investigated do not yet have strategies, systems and reporting in place to be counted as “good corporate citizens” concerning their environmental responsibility. The research further concluded that a proactive strategic intent is a necessity to achieve this goal. In short: The Corporate Social Responsibility of African and Middle East mobile operators indeed has a positive effect on its Carbon Footprint.

The UK is required to reduce its greenhouse gas emissions by 80 per cent from 1990 levels, by 2050. Greenhouse gas emissions attributed to the UK higher education sector have increased by 34.5 per cent from 1990 to 2005. Higher education institutions have a unique role in the UK greenhouse gas emissions inventory, beyond management of their own estates and compliance with policy and legislation, higher education institutions have responsibilities as innovators and educators, inspiring students and employees through example and best practice. This study sought to understand acceptability of greenhouse gas emissions reduction policies among employees of a higher education institution. The value-belief-norm theory was used in a questionnaire to understand individual attitudinal factors thought to influence policy acceptability (N=405). Recognising that an employee's attitudinal factors may be influenced by their work colleagues, this study used social network analysis to understand the social context within which individual attitudinal factors sit. Support was found for higher education institutions to reduce their greenhouse gas emissions. Employees found policies that encouraged desired behaviours, such as assistance with train travel costs and working from home, to be more acceptable than policies that discouraged undesired behaviours, such as doubling the price of a car-parking permit. Support was found for the structure and content of the value-belief-norm theory, but logistic regression suggested that it provided a weak explanation of employee policy acceptability, indicating that other factors may have a greater role. Analysis of workplace social networks suggested that employees have small social groups (x̄=8) and do not select to be close to colleagues that reflect their own perspectives. Practitioners and policymakers should seek to address this void in environmental social norms through recruitment of more environmental champions to deliver strong and persuasive pro-environmental messages.

Reducing anthropogenic GHG emissions globally is a key driver for the development of renewable energy sources. A key route towards achieving this is to replace fossil-based fuels with renewable and low carbon energy technologies such as biofuels from energy crops. Cereals and oil-seed crops such as corn, wheat, and soybean are the main feedstocks primarily used for biofuels production and the key characteristics of these crops are high biomass and energy yield per ha. However, there are concerns about the availability and sustainability of these crops for biofuels production in the face of a changing climate since crop productivity is inherently sensitive to climate. Therefore, an understanding of the impacts of climate change on energy crops production as feedstocks for biofuels production and their potential for life cycle GHG emissions reductions is crucial for making decisions on future biofuels production. This thesis examined potential climate change impacts on the productivity of two major biofuel crops: corn (Zea mays L.) and soybean (Glycine max) in Gainesville, USA and one major biofuel crop: wheat (Triticum spp.) in Rothamsted, UK. The overall objective was to calculate the potential impacts of combined changes in climate variables: surface air temperature (T), precipitation (P), and atmospheric concentration of CO2 ([CO2]) on life cycle GHG emissions savings of biofuels from corn, soybean, and wheat. The methodology was underpinned by life cycle thinking. Life cycle assessment (LCA) models linked to cropping system models (CSM) were used in the analysis. In assessing the impact of climate change on corn, wheat, and soybean crops yields, two applications of the CERES (Crop-Environment Resource Synthesis) model: CERES-Wheat (for wheat) and CERES-Maize (for corn), and CROPGRO (Crop Growth) model application: CROPGRO-Soybean of the Decision Support System for Agrotechnology Transfer (DSSAT-CSM) v4.0.2.0 model were used using observed weather data from the baseline (1981-1990) period for each study site. These models describe, based on daily data, the basic biophysical processes taking place at the soil-plant-atmosphere interface as a response to the variability of different processes such as: photosynthesis, specific phenological phases, evapotranspiration, and water dynamics in soil. Compared with the baseline, T was projected to increase by +1.5, +2, +2.5, +3, +3.5, +4, +4.5, and +5 oC, P was projected to change by ±5, ±10, ±15, and ±20%, and [CO2] was projected to increase by +70, +140, +210, +280, and + 350 ppm for Gainesville, USA. For Rothamsted, UK, T was projected to increase by +0.5, +1.5, +2.5, +3.5, and +4.5 oC, P was projected to change by ±10, and ±20%, and [CO2] was projected to increase by +70, +210, and + 350 ppm. Simulated yields output (grain/seeds and biomass) from the CSM models were used as inputs into the LCA models. Potential life cycle GHG emissions savings were calculated for corn-based biofuels: corn bioethanol (CBE), corn integrated biomethanol (CIBM), and corn integrated bioelectricity (CIBE); soybean-based biofuels: soybean biodiesel (SBD), soybean integrated biomethanol (SIBM), and soybean integrated bioelectricity (SIBE); wheat-based biofuels: wheat bioethanol (WBE), wheat integrated biomethanol (WIBM), and wheat integrated bioelectricity (WIBE). Results indicated that under the baseline (1981-1990) scenario, production and use of CBE, CIBM, CIBE, SBD, SIBM, SIBE, WBE, WIBM, and WIBE could save -4743.32 kg CO2-equiv. ha-1, -8573.31 kg CO2-equiv. ha-1, and -10996.7 kg CO2-equiv. ha-1, -2655.41 kg CO2-equiv. ha-1, -3441.1 kg CO2-equiv. ha-1, and -1350.04 kg CO2-equiv ha-1, -2776.1 kg CO2-equiv. ha-1, -500.87 kg CO2-equiv. ha-1 and -4648.93 kg CO2-equiv. ha-1 respectively, of the total life cycle GHG emissions of CO2, CH4, and N2O for the production and utilization of an energetically equivalent amount of fossil-based fuel counterpart, which they displaced. However, model predictions of future life cycle GHG emissions savings for both crops showed that the responses of corn, soybean, and wheat to simultaneous changes in T, P, and [CO2] were different under different climate change scenarios. In the future period life cycle GHG emissions savings of corn-based biofuels was predicted to decline in all cases ranging from -4.2% to -46.1%, -2.6% to -37.7%, and -1.6% to -33.4% for CBE, CIBM, and CIBE, respectively compared with the baseline (1981-1990) period. In contrast, model predictions showed that life cycle GHG emissions savings of wheat-based biofuels would increase under all climate change scenarios ranging from +2.5% to +33.5%, +0.1% to +37.8%, and +1.0% to +34.4% for WBE, WIBM, and WIBE, respectively. On the other hand, the life cycle GHG emissions savings of soybean-based biofuels was predicted to increase by +0.22% to +27%, +0.1% to 28%, and +0.1% to +31.6% for SBD, SIBM, and SIBE, respectively under some climate change scenarios (e.g., [CO2] = 680; P = +20%; and T = +1.5 oC scenario) and also decline by -0.7% to -60.8%, -0.1% to -44.6%, and -0.1% to -82.6% for SBD, SIBM, and SIBE, respectively under some climate change scenarios (e.g., [CO2] = 400; P = -20%; and T = +5 oC scenario). These results revealed that the potential impacts of climate change on energy crops productivity and net life cycle GHG emissions savings could be very large and diverse, and that the anticipated life cycle GHG emissions reductions of biofuels would not be the same in the future.

Inland waters such as streams and lakes have recently been found to be supersaturated with both carbon dioxide (CO2) and methane (CH4) – the high concentrations resulting in significant natural emissions of greenhouse gases (GHGs). Previous studies have shown that streams emit particularly large amounts of GHGs per area covered, but the spatial variability is very high and has rarely been studied in detail. This study focuses on the variability of aquatic CO2 and CH4 concentrations with high spatial resolution in a hemi-boreal stream. The study area is a 7 km2 catchment in Skogaryd in southwest Sweden. 131 samples were collected and the stream was divided into groups depending on slope gradient and geographical placement. The results show that the concentrations had high spatial variability, especially regarding CH4, and that the concentrations are higher and more variable at lower slope gradients, which possibly indicates an increased gas exchange at higher slopes. The results also showed that concentrations can increase or decrease sharply over short distances in relation to changing slope gradient. This shows that frequent spatial sampling is needed to more accurately represent streams than what is often the case in many studies. A general distance between sampling locations could not be found due to the high variability of concentrations. Instead, the authors suggest that future studies of CO2 and CH4 concentrations in streams use a stratified random sampling strategy based on slope gradients.