The intersection of fossil fuel industry funding and climate change research is a contentious area, raising significant ethical and practical concerns. Fossil fuel companies have historically played a substantial role in funding research, which has sparked debates about potential biases in climate research due to financial ties. Understanding the extent and impact of this funding is crucial for ensuring unbiased and accurate information that forms the basis of climate policies.

This thesis investigates the terminology and methodology in climate research funded by the fossil fuel industry through a comprehensive scientometric analysis, as compared to general research and a pool of research from universities with ties to fossil fuel industry. The study aims to identify patterns of industry influence on scientific outcomes and the dissemination of climate-related information. Data is collected by extracting research paper abstracts and other relevant information from Scopus database over the period of 2014-2024, divided by subject areas and funding sources, leading to over a 100,000 papers analysed with 80\% relevance score word maps produced in VOSViewer. Thus, employing methodologies such as keyword-based data collection, Natural Language Processing (NLP), and topic modeling, the research identifies significant patterns in studies funded by fossil fuel companies, such as lack of focus on ESG terms, increased focus on carbon capture and hydrogen technologies, and more technical analysis methods. To ensure the robustness of these findings, the study employs validation techniques, including cross-referencing with independent literature and applying advanced statistical methods to control for potential confounding factors via topic modelling. This multifaceted approach enhances the credibility of the results and provides a clearer understanding of the extent and nature of industry-induced biases in climate research.

The analysis spans multiple disciplines, including energy, environmental science, earth and planetary science, and engineering, revealing that industry funded research outcomes are often tied directly to fossil fuel sector sphere of interests, while finding no significant influence patterns in university research. The findings of lack of ESG terms and increased focus on specific climate-mitigation technologies underscore the need for increased ESG interest and diversity in the industry funding of climate research to ensure its integrity and objectivity.

The thesis concludes with a discussion of the implications of these findings for policy and practice. It emphasizes the need for greater transparency in the disclosure of research funding sources and calls for the implementation of stricter guidelines to mitigate bias in scientific research, or for fossil fuel industry to ensure a larger diversity in the research funding. Additionally, it offers recommendations for future research, highlighting the importance of independent funding to preserve the objectivity and integrity of climate science.

By shedding light on the intersection of industry interests and scientific research, this thesis contributes to the ongoing debate about the ethical implications of industry-funded research. It underscores the critical importance of unbiased, evidence-based decision-making in addressing global climate change and supports the development of policies that ensure the reliability of scientific knowledge.

The climate policy domain is critical in addressing the multifaceted challenges posed by environmental degradation, socio-economic factors, and political dynamics. This thesis examines the Stimulering Duurzame Energieproductie (SDE(+)) policy in the Netherlands, evaluating its programmatic, process, and political success using an integrated framework combining dimensions of policy success and criteria for climate policy evaluation. Employing a qualitative research design, the study incorporates structured content analysis, stakeholder interviews, and secondary data analysis to provide a nuanced assessment.

The findings indicate that the policy's success has improved from the transition to and during the SDE+, showing both resilient and conflicted success. While the SDE+ policy has significantly boosted renewable energy production, particularly in solar PV and onshore wind, it has not achieved the 2020 targets and challenges like grid capacity strain and socio-economic inequalities remain. The evaluation highlights the need for a more equitable distribution of burdens and benefits and internalising external costs such as net congestion into the competitive subsidy allocation process.

This comprehensive analysis contributes valuable insights into climate policy effectiveness, supporting the development of more resilient and equitable renewable energy policies in line with international climate targets. Using a new climate-specific evaluation framework, this thesis provides a holistic and nuanced evaluation of the SDE(+) case study, demonstrating its applicability to climate policy. The study underscores the importance of integrating multiple dimensions of policy success to address the complex challenges of climate governance.

To advance the energy transition and prepare for the accompanying increase in electricity demand, the electrical grid of the Netherlands requires rigorous investments for expansion and maintenance. In order to solve and further prevent grid congestion, a lot of projects have to be executed and this demands collaboration of grid operators and local governments. In addition to the technical problems of the transition, there is also a growing part of the population that is suffering from energy poverty and energy injustice which prevents them from benefiting from new innovations, while wealthier households are financially profiting from these. The negative socioeconomic effects are not accounted for in the investment plans of grid operators, even though not addressing these problems will further increase inequality in the population.
In order to research how investments in the electricity grid are related to the socioeconomic status of neighbourhoods and how this affects equality in the province of South-Holland, this thesis is conducted. The study aims to answer the research question: "To what extent can spatial relations between electricity grid infrastructure and socioeconomic characteristics be identified and quantified in the province of South-Holland and what does this relation imply for inequality?"

To answer this question, first a literature study was conducted in order to identify socioeconomic variables related to energy poverty and energy justice to use in the research. Subsequently, data for these selected variables is collected on a neighbourhood level and the electricity infrastructure in the province of South-Holland is mapped. The research focuses on the low and middle voltage grid infrastructure as these grid levels directly influence households and their impact can be assessed on a neighbourhood level.
The collected data was then used in a correlation analysis to discover a possible relationship between the socioeconomic status of a neighbourhood and the amount of low and middle voltage stations located in it. As the electricity demand of wealthier households is higher than the demand of lower income households, it was expected that there would be a positive correlation between prosperity and electricity infrastructure. The found correlations, however, did not result in any definitive conclusions, except for the relation between the amount of inhabitants and the amount of electricity infrastructure, so another analysis was performed that focused more on the spatial correlations. In this hotspot analysis the variables with a strong relation from the correlation analysis were used in a clustering research. This resulted in indications being found that linked areas of socioeconomic prosperity to more investments in electricity infrastructure, as was assumed. This implicates that there is an unbalanced distribution of costs and benefits on the grid as everyone pays the same for the investments, but wealthier neighbourhoods profit more.

In order to learn how this relation came to be and how it affects equality, experts on the topic were interviewed. In total five interviews were conducted with people from main stakeholders in the system, namely: grid operators, municipalities and researchers on energy justice. The interviewees were asked about their thoughts on the results of the analyses, the developments of the electricity grid, its effect on equality and the role of the province of South-Holland in the system. From these interviews it was concluded that the indicated unbalanced distribution of electricity grid investments among different socioeconomic groups in the population is not necessarily a problem for equality on the short term, although it might provide difficulties in the future. The investments follow demand and thus it is a logical consequence that neighbourhoods with a higher electricity usage require more electricity infrastructure.
The problem in the system is that there are socioeconomic groups who have no access to the energy transition and can therefore not benefit from the developments, while others are enriched by it. This unequal balance of costs and benefits causes inequality to grow in the future, so governments will have to ensure lower income households have access to energy transition innovations in order to secure a balanced and sustainable future.

New global climate policies must be deemed just in order to be effective. However, global climate policymaking is complex and subject to normative uncertainties, especially in relation to the distribution of resources, risks, and consequences. These diverging views are dependent on what is distributed and are ultimately based on moral rules and principles that prescribe when a distribution is morally just; distributive justice principles. Enhanced understanding of these distributive preferences is necessary to account for them in both policymaking and modelling. A bottom-up evaluation of stakeholder views in negotiations is a time-consuming but useful method to add to this understanding. This research evaluates the potential of using GPT-4o to perform this task, identifying distributive justice principles in High-Level Segment (HLS) speeches from UNFCCC COP. By identifying distributive justice principles—egalitarianism, utilitarianism, prioritarianism, sufficientarianism, and libertarianism—this research examines the moral foundations of climate policy decisions. Manual annotations of 51 HLS speeches created a ground truth dataset, revealing complexities and class imbalances in principles, with prioritarianism being most dominant. GPT-4o’s performance in identifying relevant sentences and distributive justice principles showed promise but struggled with consistency compared to human annotations. Despite limitations, the model demonstrated efficiency, highlighting its potential for pre-processing and classification tasks. The study underscores the importance of a nuanced, bottom-up understanding of distributive justice in climate negotiations, contributing to climate justice and IAM by offering theoretical insights and practical implications.

Situation
The constant increase in global temperatures is becoming more and more concerning for the future of our planet. The health of the planet is crucial for our existence and for the health of humanity, which is why we need to maintain and care for our environment. The pharmaceutical sector contributes to a lot of greenhouse gas emissions, and the total amount of emissions even exceeds that of the automotive industry. Pharmaceutical companies’ main goal is to improve human health, and therefore, contributing to a healthy environment is also crucial. Pharmaceutical companies have set ambitious climate goals that will need a lot of attention if they are to be fulfilled. More and more collective action initiatives are taking form, such as Energize and projects like Together for Sustainability (TfS). While a lot of progress is being made, collective efforts need to improve, and climate challenges need to be tackled collectively. Johnson & Johnson, as one of the largest pharmaceutical companies in the world, has committed to the SBTi targets and set ambitious goals for itself. They put a lot of emphasis on sustainability and aim to reach their targets across all its 250 subsidiary companies that are spread out over 60 countries.

Problem identification
As the climate impact of the pharmaceutical sector seems to be significantly large, it is important to understand how the climate targets of this sector can be fulfilled. Johnson & Johnson aims to source 100% of their electricity needs from renewable sources by 2025, achieve carbon neutrality for their operations, going beyond their Science-Based Target to reduce absolute Scope 1 and 2 emissions 60% from 2016 levels, and reduce absolute upstream value chain (Scope 3) emissions 20% from 2016 levels by 2030. They are currently on pace to meet their scope 1 and 2 targets. The scope 3 emissions, however, remain significantly larger than the scope 1 and 2 emissions combined. Scope 3 emissions come from other parties that a company works with, which makes influencing them more difficult. Collaboration is needed to stimulate companies across the value chain to contribute to sustainability. Collaboration could be in the form of various projects where companies engage in collective action to achieve certain common goals. Collective action means that multiple parties are engaged in a project that works towards a certain shared goal.
This research aims to explore the current challenges of the pharmaceutical sector with reaching emission targets and how collective action concepts impact the willingness of supplier companies to engage in collective initiatives that focus on reducing emissions. For this study, Johnson & Johnson will be analyzed to get a good understanding of the current state of the pharmaceutical sector...

Amidst the burgeoning challenges of climate change, certain sectors, like the beer industry, find themselves at the forefront due to their dependence on climate-sensitive agricultural inputs. The changing climatic conditions not only influence the flavor profile but also the beer's accessibility, by affecting the quality and yield of essential ingredients such as barley and hops. This research delves into the beer industry's supply chains, which span regions increasingly vulnerable to climatic disruptions, thereby subjecting companies to notable physical risks like water shortages, crop failures, and transportation hindrances.

The pertinence of this study extends beyond the beer industry, revealing broader implications for various business sectors. As supply chains of numerous sectors traverse climate-sensitive zones, they're endangered by hazards like droughts and heatwaves. A prominent challenge exacerbating these threats is poor coordination, evidenced by inconsistent communication, delayed responses to disruptions, supply chain opaqueness, and misaligned adaptive strategies.

To address the overarching research question on effective coordination measures that the beer supply chain can adopt to mitigate vulnerabilities and bolster climate resilience, the study integrates both primary and secondary data. Primary data is sourced through semi-structured interviews, capturing insights from within the beer industry, while secondary data is derived from academic and industry repositories. The combined data offers a comprehensive perspective on the existing challenges and potential solutions for the beer supply chain.

A deep dive into the industry's supply chain relationships elucidates the inherent complexities, informing subsequent analyses on viable coordination mechanisms to combat climate vulnerabilities. Heineken, an industry stalwart, plays a crucial role in this exploration, with the Institutional Analysis and Development (IAD) framework assisting in structuring the problem analysis. This framework is invaluable in scrutinizing institutional setups and their resultant impacts, while Heineken's strategic initiatives are evaluated using action situation analysis.

One of the central themes emerging from the findings is the potential applicability of Elinor Ostrom's design principles. Originally conceived for effective common-pool resource management, these principles, emphasizing clear demarcation, rule-local condition congruence, and responsible governance, could be instrumental for the beer industry. They present a well-structured approach for devising coordination mechanisms, crucial in confronting collective environmental challenges.

In summation, this research underscores the imperative for the beer industry, and by extension, other sectors, to consider Ostrom's principles. Their adoption could pave the way for resilient and sustainable supply chains, proficient in circumventing climate-induced risks. Such proactive measures are not merely pivotal for sustaining business operations but paramount in ushering an era of sustainable, climate-resilient business practices.

As the world's third-largest emitter of greenhouse gases, India stands at a crucial juncture in the global fight against climate change. Recognising the delicate balance India must strike between rapid economic growth and sustainable development, this research employs a Computable General Equilibrium (CGE) model tailored specifically for the nation. By incorporating Greenhouse Gas (GHG) emissions, the model delivers an in-depth analysis of the potential economic impacts of climate mitigation strategies, especially carbon taxation, within the intricate fabric of India's diverse economy. This endeavour fills a significant knowledge gap, offering a tool that policy analysts can use to harmonise India's developmental aspirations with its global climate commitments.
Tapping into the power of quantitative methodologies, the study leverages CGE models known for their proficiency in capturing a country's economic interconnections. For India, this model weaves in GHG emissions to holistically assess the economic ramifications of carbon taxation. Core to this research is data sourced from India's Social Accounting Matrix (SAM) (Pal et al., 2020), complemented by inputs from national databases capturing carbon intensities, labour productivity, and capital stock depreciation.
The application of the CGE model to India's context yielded pivotal insights. A deep dive into sectors revealed that five of them, led prominently by the coal-intensive energy sector, are responsible for over 95% of India's emissions. Notwithstanding the nation's push towards renewables, emissions are dauntingly high. While a modest carbon tax has limited impact, a more aggressive tax rate, although effective, disrupts income distribution, disproportionately affecting India's marginalised populations. The research thus underscores a synergistic approach, merging targeted reinvestments with a robust carbon tax as the linchpin for sustainable decarbonisation in India. While potent in emission reduction, such strategies necessitate protective measures, like subsidies, to prevent deepening India's socio-economic divides.
The study recognises intrinsic limitations that need addressing. The current model's architecture possesses constraints, particularly in its representation of export levels and wage growth. An endogenous presentation in these areas would provide a richer systemic view. While the research touched upon two primary tax rates, a broader exploration of tax rates is warranted to align more accurately with Key Performance Indicators (KPIs). The present pricing mechanism, which leans heavily on consumers bearing the entirety of the carbon tax, hints at a potential imbalance in economic impact and needs reevaluation. Additionally, using placeholder coefficients for decarbonisation offers a limited perspective, potentially glossing over the nuances of carbon reduction dynamics. Notably, the model's exclusion of simulations for extreme weather events is a critical oversight, which could affect its forecasting abilities, especially in climate change.
This research presents actionable policy recommendations, chiefly underscoring the role of targeted reinvestment coupled with a high carbon tax rate. With India's energy sector at the forefront, targeted reinvestments promise to bolster GDP and reduce emissions, providing a roadmap that aligns economic growth with climate mitigation. However, given India's socio-economic fabric, implementing such strategies mandates careful consideration of potential impacts, especially on vulnerable sectors like agriculture and the vast populace of lower-income households.

Sustainable energy transition is the need of the hour, more so, because of the accelerated effects of climate change. This necessitates rapid, continuous, and persuasive political and technological approaches to enable an ecosystem of green alternatives for countries to support their net-zero ambitions. One such emerging technology approach is green hydrogen, which is hydrogen produced from renewable sources. Green hydrogen is considered as a versatile energy carrier to support transitioning of industries, energy systems and transport, towards sustainability. As such, globally, many countries have increasingly considered green hydrogen as a part of their decarbonisation plans. Today, at least 26 countries have adopted hydrogen policy strategies and supporting policy instruments. However, mere adoption is not enough – a test of policy effectiveness is required to evaluate whether policies will be executed in keeping with their stated objectives, whether the various policy instruments/tools introduced to support overall strategies will be collaborative or may conflict with one another, and whether the policies will address issues systematically or ad hoc. It becomes important to understand whether policy strategies and instruments, the underlying processes, and their characteristics - collectively called a policy mix- could actually support policy goals, objectives, and ambitions of various countries.

About 75 percent of CO2 emissions caused by the combustion of fossil fuels stem from cities. Climate policy minimising the amount of emitted carbon can not be evaluated without accurate quantification of CO2 emissions.
Not only the amount of emitted carbon is of interest, but also being able to place emissions in both the spatial as well as the temporal context is necessary. This gives policy makers and scientist the ability to compare the climate impact of neighbourhoods and cities. For doing so, it is necessary to have a rasterised emission estimate with a high resolution.

This study proposes a new method using a Random Forest model trained on the Hestia dataset. The model utilises spatial co-variates, such as population density, night time lights, to estimate emissions in a resolution of 1 X 1 km.
To assess the spatial generalisability of the model, the emission observations of the Hestia dataset are compared against model estimates. The explained variance and R2 is the highest in log transformed form at ∼0.47. The features and hyper-parameters
selected through this method are found to be stable under a variety of model specifications. This provides evidence that the presented model performance generalisability are the that could be achieved given the current data. The relevant covariates for the model are the following, in order of importance: Nightly radiance, intersection density, population, GDP, PM25 and Pedestrian intersections. Inspection of the partial dependence shows that each of these variables, except PM25, have a positive increasing relationship with the emission estimate. This relationship quickly converges for higher values. The highest relative errors mainly occur around the peripheries of cities, for cells with low emission values.

This study lays forward a new scalable approach to estimate emissions and the spatial distribution in urban areas. Currently the study data is limited, but as more data becomes available a Random Forest regression approach could prove to produce accurate insights. Also the findings in model design and evaluation could be used in future studies. For city planners the results can be used to gain a first insight in the spatial distribution of emissions within their city. Pinpointing high emission zones or comparing different urban areas. Knowledge of the spatial distribution of cities can be a pathway of understanding how to develop less carbon intensive cities.

Fossil fuels play an important role as an energy source in the world. The high use of fossil fuels does not come without environmental and climate challenges. The development of renewable energy technology is seen as one of the solutions to tackling these challenges because of its non-carbon-emitting characteristic. Renewable energy technologies required governmental support to grow because of their high costs compared to their fossil fuel counterpart. Countries adopted different renewable policy strategies, resulting in different photovoltaic development trajectories. When observing these photovoltaic development trajectories in countries, a recurring pattern occurs in which development starts and stops. One of several examples of this pattern was when photovoltaic development in Germany began to increase in 2003 with an annual capacity added of 175 MW, then peaking at 8161 MW in 2012 and decreasing to 2633 and 1190 MW, respectively, over the following two years. Another instance was in Spain in 2006. Photovoltaic development started to take off with an annual capacity added of 78 MW, peaking at 2890 MW in 2008 and decreasing to 39 MW the year after. This pattern results in development stagnation and harms the country's markets, jobs, and investor confidence. If the renewable policy strategies adopted by countries result in stop-and-go patterns of development, causing the aforementioned negative impacts, why do countries adopt them? The process of policy-making across countries is believed to be subject to different factors such as the country’s natural resources, culture or beliefs, history, pressure groups, or external events. What could be considered an important reason for one government to adopt or cease a renewable policy may not be important for another country, given the different factors and external events. What are the reasons these different countries adopt these stop-and-go policies? To understand the underlying cause of the stop-and-go policies in different countries, we take a closer look at the photovoltaic development trajectory in several countries. First, we identify the reasons countries started and stopped developing solar PV in the literature. After identifying these reasons, we analyze each country to determine which of these reasons were important for the countries to start or stop developing solar PV. Last but not least, we compare which of these reasons were important for starting or stopping the support of solar PV across countries. Data was collected through literature review and desk research. This thesis analyzed seven countries, nine go events, and four stop events. The countries analyzed in this thesis were France, Germany, Italy, Japan, Spain, the United Kingdom, and the USA. The volume of data analyzed consisted of approximately 277 documents. The analyzed documents were governmental policy documents, peer-reviewed scientific papers, and reports from global organizations such as the IEA, IRENA, REN21, and GWEC. The findings indicated that improving the security of supply and stimulation of the economy were extremely important reasons countries developed solar PV. Countries with abundant domestic fossil fuel resources developed solar PV to stimulate their economies, while countries with scarce domestic fossil fuel resources developed to improve their security of supply. Improving the security of supply as a reason alone was enough in some instances for countries to start developing solar PV. Countries stopped developing solar PV due to an economic crisis or the prioritization of other economic sectors or energy technologies. However, the same economic crisis that caused certain countries to stop developing solar PV was the reason for some countries to stimulate their economy. When countries decided to stop support of PV, some countries took a more aggressive approach to reduce support than others, causing PV capacity added to decrease at a different pace. Nuclear disasters were initially thought to be a reason why countries started developing solar PV though the evidence was limited. However, upon further investigation, it became evident that PV development started before the accident to improve the security of supply and create an industry but was accelerated after the accident. Stop-and-go policies can occur in different countries because the countries can be triggered by the same external events that influence energy policy, for example, the 1970s oil crisis, the 2008 economic crisis, and the reduction of PV costs. Stop-and-go policies also occur due to the election/appointment of new governments that reduce or increase support for solar PV. As a recommendation for policymakers, policymakers should monitor PV capacity added and PV cost trends in the short term to amend PV support policies. PV development increased between 2008-2010 due to falling PV costs and lagging policy amendments leading to explosive growth. This explosive growth happened during an economic crisis. In the context of an economic crisis, the levies on electricity bills for PV support received increasing negative attention. On the other hand, taking a too-aggressive approach to decrease solar PV support may negatively impact investor confidence and the future development of PV in a country. Thus, countries must monitor developments closely and adjust support accordingly. Recommendations for further research on this topic are provided in the conclusion.