Attention for the aviation industry's impact on climate change has increased significantly in recent years, as it is one of the fastest growing industries worldwide. Aviation contributes around 2.4% to the global emissions of CO₂ and an average of 3.5% to climate change because of fossil fuel consumption. If aviation continues its current trajectory of increasing traffic volumes, the sector will increasingly conflict with global decarbonization targets. Although aviation's emissions targets align with the overall goals of the Paris Agreement, it is unlikely that the sector will meet these goals. While efficiency measures are being implemented, concerns are growing over the short-term feasibility of current development scenarios. Given that radical engine innovations and large-scale deployment of Sustainable Aviation Fuels (SAF) are unlikely to become technically and commercially viable before 2040, improving fuel efficiency remains the most immediate and effective strategy for reducing emissions. The key short-term measures available to airlines under the four-pillar strategy proposed by the International Air Transport Association (IATA) can be summarized as follows:

- Invest in new generation, more fuel-efficient aircraft to increase average fuel efficiency;
- Implement strategies to increase passenger load factors;
- Optimize flight operations such as route planning to reduce flight distances.

As advancements in operational and aircraft fuel efficiency also enhance cost-effectiveness, airlines have the potential to significantly reduce fuel costs and pass these savings on to consumers, leading to lower ticket fares. This could further stimulate passenger demand, amplifying the existing upward trend in air travel. This feedback might result in a fuel efficiency rebound effect, partially or fully offsetting the intended emission reductions. Projections for future demand, fuel efficiency and the associated emission reduction in the literature often overlook the fuel efficiency rebound effect, leading to systematic overestimation of actual emission reductions. 

The research addresses this critical knowledge gap by conceptualizing and quantifying how future fuel efficiency rebound effects may affect projected emission reductions in passenger aviation. Previous research identified rebound effects in aviation of 49%* between 1986 and 1999, and 18.8% between 2000 and 2013, based on retrospective analysis of empirical data. A forward-looking analysis of how fuel efficiency rebound effects may influence future emission projections is currently missing. The research estimates the fuel efficiency rebound effect over a 15-year time horizon, up to 2040. Indirect rebound effects fall outside the scope of this analysis. With the aim of contributing to the integration of rebound dynamics into policy evaluation models and supporting robust policy design, the research adopts an exploratory approach by combining quantitative System Dynamics (SD) modeling with Scenario Analysis. 

The research contributes to future predictive studies on rebound effects and broader emission reduction efforts in aviation. First, it conceptualizes the key drivers and feedback mechanisms of the rebound effect using a systems thinking approach. Second, it captures these dynamics in a compact System Dynamics model, that operates without relying on extensive empirical data. Third, it estimates the rebound effect and its implications within a reference scenario, and explores a range of plausible scenario outcomes. Fourth, it analyzes these outcomes to identify influential combinations of market-specific uncertain parameters. Finally, the research highlights critical market-specific empirical data gaps that must be addressed to narrow the plausible range of model results.

The model results indicate an emission reduction potential of 14% compared to a scenario without any efficiency improvements. Within a reference scenario, a rebound effect of 91.3% was estimated over the 2025-2040 period, offsetting the majority of this potential and resulting in an actual net reduction of only 1.3%. The magnitude of the rebound and its impact on emissions is influenced by market-specific uncertainties, including airline pricing strategies, fare elasticity of demand, and the market shares of different haul segments. To capture a range of plausible outcomes, 1000 scenario runs were conducted, incorporating varying combinations of these uncertainties. The findings suggest that in the majority of scenarios, the rebound effect approaches or exceeds 100%.

Using the Patient Rule Induction Method (PRIM) algorithm, outcomes of interest were evaluated based on a rebound effect threshold, defined as any scenario in which a larger share of the emission reduction potential is offset relative to the reference scenario. The extent to which fuel cost savings are passed on to consumers appeared to be less influential, as the analysis revealed that even at its minimum value, a substantial rebound effect can occur. However, a higher average pass-through rate remains undesirable, as it is associated with an even greater magnitude of the rebound effect. The magnitude of the rebound effect exceeds the 91.3% observed in the reference scenario, under the following conditions:

- Consumers exhibit a high sensitivity to fare price reductions per passenger-kilometer;
- Relatively high market shares of longer haul segments compared to that of short-haul segments;
- Airlines can fully capitalize on demand growth, i.e. the potential amount of flights is unrestricted.

The rebound effect estimated in the research is significantly higher than the rebound effects of 49% and 18.8% reported in previous research. This discrepancy can be attributed to key methodological differences, including the use of a ceteris paribus approach that isolates behavioral feedback effects, and the exclusive focus on passenger aviation, whereas previous research also included cargo operations. The results indicate that the rebound effect in passenger aviation can offset a substantial portion of the emission reduction potential in the reference scenario. In most other scenarios, the effect is even more pronounced, with projected outcomes showing a complete offset or even an additional increase in emissions. These findings highlight a significant risk that the sector's contribution to global emission reduction targets is being overestimated, as the effectiveness of the key short-term measures under the four-pillar strategy proposed by the IATA is substantially diminished by the rebound effect.

*The rebound effect is typically expressed as the ratio of the lost savings to the expected savings, representing the share of the emission reduction potential offset by the rebound of efficiency improvements. 

The water and subsurface sector faces numerous urgent challenges related to climate adaptation and sustainable infrastructure. It is the responsibility of Rijkswaterstaat (RWS) to establish objectives and collaborate with partners in the sector to address these challenges. Innovations are crucial for effectively addressing these issues, and therefore, RWS has developed an innovation strategy focused on the tactical level, which provides essential information for its employees and partners. This study examines RWS’s current innovation strategy and its development, evaluates the strategy’s influence on innovation processes within the water and subsurface sector, and offers recommendations for enhancing the strategy. Specifically, the study investigates the influence of RWS’s innovation strategy on resource allocation, the development and diffusion of innovations, and both internal and external collaboration. The findings indicate that the influence of RWS’s innovation strategy is most evident in resource allocation, where its focal points serve as guiding principles for innovation and as accountability mechanisms. Furthermore, the influence of the strategy on the development and diffusion of innovations, as well as on both internal and external collaboration, is becoming increasingly apparent in practice; however, it requires additional time for further visibility. Positive developments include the adoption of specific tools designed to stimulate the innovation process and the implementation of innovative collaborative approaches, such as learning spaces. To enhance RWS’s innovation strategy and its influence in the water and subsurface sector, this study recommends maintaining continuity, improving visibility and clarity, and stimulating sector-wide collaboration and alignment.

The future of the Dutch delta is challenged by the wicked problem of climate change characterized by sea level rise and extreme weather changes as well as land subsidence and the uncertainty pertaining to these processes. This makes well-considered policy decisions a sought-after endeavor. To provide a long-term view of how the Dutch delta behaves under future conditions and how this may be influenced by solutions from different domains, Deltares initiated an exploration into the need for a ”Deltaverkenner”, a national-scale decision support tool to collect, integrate, improve, and visualize insights from disciplinary research. Decision support tools (DSTs) are developed to support decision-makers in decision-making processes by providing frameworks and models to assist in making informed decisions. The benefits of DSTs can be plentiful. However, for information to successfully transfer the boundaries between science and policy it needs to be salient, credible and legitimate.

Therefore, this thesis aims to explore, synthesize and evaluate co-produced designs for a decision-making support tool for water governance contributing to climate change adaptation in the Netherlands that best fits the needs of the stakeholders involved. Consequently, this thesis aims to answer the following research question:
“What do stakeholders perceive as a fit for purpose design for a water governance decision support tool contributing to climate change adaptation in the Netherlands?”

To do so, it takes an informed, iterative co-production approach, meaning possible designs for the DST are co-designed based on stakeholders’ needs in collaboration with stakeholders and experts. Subsequently, the potential designs are evaluated by the stakeholders. This process is informed by lessons learned from the application of previous decision support tools at the water governance science-policy interface. Additionally, the findings are analyzed in comparison to a literature-based theoretical framework regarding the requirements for successful DSTs and the trade-offs to consider at the science-policy interface.

The findings show that there is consensus on the need for a quick and aggregated tool, preferably a conceptual model like a system dynamics model or a reservoir model. This tool should be able to provide insight into the impacts (both water engineering related and societal impacts such as nature, agriculture and economics) of strategies like the ’voorkeursstrategiën’ for the Delta program. It is also clear there is no desire for a computationally detailed model. There seems to be enough information available; the challenge is to find a way to aggregate this into a quick, easy to use, informative tool that offers significant interaction opportunities in the form of dialogue between different users, as well as feedback between users and the tool based on system knowledge.

The findings were analyzed using a theoretical framework that identifies important considerations for a successful decision support tool that capable of bridging the science-policy interface. Most of the findings of this thesis align with the framework especially regarding the content and use elements for a DST. Regarding the goal and process elements, the findings and the framework are also in agreement, however more research is needed to further specify the needs from stakeholders.
While the findings offer interesting insights into the perception of stakeholders on fit for purpose designs of the ’Deltaverkenner’, they also highlight several areas where more research is necessary to further ii iii concretize the need and offer a starting point for potentially developing an approach for the ’Deltaverkenner’. Specifically the 5 W’s have to be elaborated and specified. Who should the ’Deltaverkenner’ be for, why the need for a ’Deltaverkenner’, what should it be able to do and where and when (timing, resources, process) should it be developed.

To further concretize the need for a ’Deltaverkenner’ and to ensure all elements of the theoretical framework are considered for successful decision support tools at the science-policy interface, the recommendation is to develop a meta model detailing the design of the process for developing the ’Deltaverkenner’. This framework should include criteria derived from co-production, boundary object, and decision support systems design processes. Additionally, the literature on impact pathways can inform the types of knowledge, types of research orientations, types of interactions, and the beneficiaries to ensure an effective impact on the decision making process.

This study takes initial steps to understand why 47% of companies creating Radically New Technological Innovations fail before reaching large scale diffusion and how to prevent such failures. This was achieved by integrating Ortt’s (2010) evolution model—which states that an innovation passes through a development and adaptation phase before reaching large-scale diffusion—with the Technological Innovation System framework, which emphasizes that an innovation encompasses more than just its technical features. These combined theories were then analyzed using the System Dynamics Modelling approach. The main question in this process was: “How can we develop a System Dynamics Model that accurately portrays the interactions among elements within the Technical Innovation System, shedding
light on the system’s behavior across different phases and identifying factors hindering the progression of the adaptation into the diffusion phase?"

To answer this question, we developed a method, a model depicting the interactions between the TIS-factors, a theory on transitions between phases, and a simulation model demonstrating the influence of certain factors on these transitions. The developed method is based on synthesis, in which theories on the factors within the TIS, namely customers, price, performance, production, networks, institutions, and complementary products and services, are combined into one coherent framework. This framework acts as a hypothesis, outlining the variables that make up the factors and defining their interrelations. From this hypothesis, a conceptual and a simulation model can be built which can be validated using expert interviews and experimentation. Using this method, we built a conceptual model that maps the variables and their relationships, while also clearly stating its assumptions. Through evaluating this model, we identified customers, production, networks, and complementary products and services as potential drivers in the system.

Additionally, we found that growth in legitimacy and R&D can have both positive and negative influences on the system, depending on how other factors develop. To understand how the TIS is first adapted and then reaches large scale diffusion, a theory on market transitions was designed. Here we hypothesized that the adaptation and diffusion phases are really a series of heterogeneous markets that are characterized by different demand preferences. Initially, during the adaptation phase, these are niche markets, while in the diffusion phase, the innovation can enter larger and more demanding main markets. Additionally, we proposed three pathways for an innovation to transition from one market to another: first, by evolving its TIS to align with the market’s demand preferences, which is often essential in main markets; second, when demand preferences shift to match with the TIS, typically seen in smaller niche markets; and third, when both demand and the TIS evolve to better align.

Lastly, our goal was to begin to identify which elements are crucial in market transitions. To achieve this, we constructed a simulation model that illustrated the interaction between standardization and potential shifts in demand preferences. The variable Standardization is grounded in the assumption derived from the conceptual model that, given enough time, all TISs will produce a standardized product. Our findings indicate that when entering a market, having a high level of standardization is essential to achieve high-level diffusion, particularly in markets focused on a developed TIS. Conversely, to prevent low diffusion levels, it is important to enter the market only when the product is favored by consumers, especially in markets determined by external demand preferences; additionally, low standardization should also be avoided.

In conclusion, the synthesis method created here can be used to indicate what elements are essential in enabling or hindering the progression from the adaptation to the diffusion phase. Initial conclusions indicate that there are several drivers and potential hindrances within the system and that both standardization and shifting demand preferences can greatly impact possible transitions, depending on the specific characteristics of the market.
As these are the first steps in a long line of research, there is so much more to be done. For this it might seem obvious to only look to the future and aim to design more specialized conceptual models, or a simulation model that encompasses all elements. However, I also want to invite you to look to the past and see how this study can be used to clarify the theories and methods that form its foundation.

Digisation and the continuous advancement of Artificial Intelligence (AI) incites projections about automation altering occupations over many sectors and countries. With increasing availability of digital infrastructure, many parts of emerging economies will open their doors and become subject to digitisation, robots and AI simultaneously (Messina 2016, Das and Hilgenstock 2018), which for advanced economies have appeared slower, with less established power structures and at different times. With high uncertainty around and little literature on the subject, the societal implications of automation in emerging economies are ambiguous, with potentials of automation boosting economies and leveling the playing field of development one one hand, but also leading to exploitative dynamics, in which companies with intellectual property rights and know-how on automation technologies inflict harm on labour markets, economies and thus many societal layers of emerging economies. While a multitude of indicators on job transformation through digitisation, robots or AI and their respective implications on employment emerged and were discussed within the literature for advanced economies, lack of abundant data causes ongoing uncertainty for emerging economies.

This thesis addresses the scientific gap of who is at risk of automation in emerging economies. The literature review entails an overview on the field of labour automation, the social effects of automation, and the (projected) case for emerging economies. The quantitative analysis entails the calculation of two automation indicators, Routine Task Intensity for automation through digitisation and robots, and Suitability for Machine Learning (SML) for automation through AI for emerging economies. SML and RTI are compared among occupations and socio-demographic groups as well as their relationship towards each other. To identify patterns to susceptible socio-demographic groups within the labour markets of emerging economies, a cluster analysis is performed on the most pertinent and yet orthogonal demographic parameters. The attained insights on socio-demographic clusters and their susceptibility towards automation are discussed to develop are broader picture on how automation affects emerging economies in order to educate policymakers and aid in rethinking policy approaches in response to changes in skill demands.

This thesis finds ground for concern that emerging economies will be subject to a not just broader but also likely more sudden wave of digital automation than advanced economies, potentially magnified through historic power imbalances and global market dynamics. Our results demonstrate that also for the task compositions of emerging economies, it can be expected that with the advent of AI a substantively larger share of tasks, occupations and socio-demographic groups is susceptible to automation as compared to automation through digitisation and robots. Workers with low and high education show higher automation susceptibilities than mid-educated workers, although through different technologies. The finding that also high-educated workers are susceptible motivates the conclusion that education systems might see their traditional societal role of enablers of social mobility endangered. Finally, this thesis finds that women are systematically more susceptible to AI-enabled automation and the observation that men are more susceptible to automation through digitisation and robots in advanced economies does not hold true for emerging economies. This thesis concludes by calling for particular consideration of emerging economies in the field of automation in labour markets, the merging of more granular data for emerging economies and an institutional model of automation.

Nature-based solutions (NbS) are increasingly being used around the globe as a climate action tool. In the Global South, which faces significant climate risks, higher urbanisation rates emphasise the importance of climate justice. While social valuations and interactions with nature-based solutions have been well researched, the relationships between nature-based solutions and social vulnerability to climate change remain difficult to capture. Furthermore, there exist little support for decision-makers to integrate social vulnerability into NbS planning. In this thesis, a social vulnerability framework to determine ecosystem service demand is presented using principal component analysis (PCA), and used with an NbS matching model to determine the types and locations of NbS to be prioritised, applied to a case study of Cape Town, South Africa. The presented framework allows for leveraging openly available quantitative data sets and incorporating different risk factors, while depending on expert interviews to contextualise the model and emphasize its limitations. Three potential policy considerations are recommended for the city of Cape Town to facilitate climate just NbS implementation: cooperation with conservation, potential for climate adaptation and justice, and the importance of community involvement. Using this method of prioritisation and selection, decision-makers of the city of Cape Town can incorporate climate justice into its urban planning for NbS, while taking consideration of the framework limitations and restrictions.

For most countries, the targets set in the sustainable development goals for 2030 are far from being met. The main cause is a lack of financing, due to the relatively high risks and low rewards associated with sustainable projects. This has caused a financing gap in developing countries of upwards of 2.5 trillion US$ annually, equal to 3% of global GDP. These unattractive aspects of sustainable investment projects result in a lack of private investment, leaving public investment as the main source of funding for these projects. A vital area within the financing gap is the lack of financing for SMEs in developing countries, which are important for economic growth and job creation. The issues faced by these countries and especially SMEs have been compounded by the COVID 19 pandemic, which has claimed countless lives, but also countless jobs in developing countries and has caused extensive economic damage. In this light, achieving impact on SDG 8: ‘Decent Work and Economic Growth’ was deemed critical for the whole of sustainable development.

Recently, blended finance, an investment type utilizing public and philanthropic capital to accelerate private investments, has become more popular. However, effective practices of using blended finance to foster job creation in developing countries through SME financing are lacking. Furthermore, there is little to no literature on investment decisions that goes into selecting projects for blended finance. In this light, this research aims to answer the following question: “What are effective practices and key investment decisions in using blended finance to fund SMEs in developing countries, focusing on impact towards achieving SDG8?

To answer this question, a literature review of the concept of sustainable development, sustainable financing methods and the role of SMEs in the developing countries was conducted. This highlighted the potential of blended finance when compared to other sustainable financing methods in being able to aid these SMEs and impact SDG 8. Afterwards, a data analysis of the performance of recent SME financing projects in developing countries, as well as a case study consisting of interviews with blended finance investment experts was conducted, in order to find effective practices of financing SMEs in developing countries to facilitate the targets set by in SDG8 and highlight how investment decisions are (to be) taken when considering blended finance projects.

It was found that even though the projects in lower-income countries within the could have stronger performance, a balance has to be struck between projects in these countries and those in slightly less low-income countries, in order to achieve consistent results. Furthermore, the use of public loan guarantees seems like a promising method but is currently suffering from a lack of willingness by banks to engage in blended finance transactions, due to solvency issues and general lower risk appetite and unfamiliarity with the methodology.

Furthermore, key investment decisions from an investor perspective lie in the specific business case of the project and whether the investment is ‘additional’ to the market. Furthermore, the attitude and capabilities of the entrepreneur behind the project are essential, as investors prefer projects in which the entrepreneur has enough skin in the game and is open to collaboration with a multitude of investors, such that one investor does not have to bear all the risks. Furthermore, it is important for investors to balance impact with financial performance, as only achieving impact through risky projects is not a sustainable business practice. More investment decisions could be made in the future if more and different blended finance methodologies would become more readily available. However, many of these, such as higher-leverage loan guarantees and first loss guarantees, are hampered by a lack of willingness again of private credit suppliers to engage in these transactions with public blended finance institutions. Furthermore, larger fund sizes would help investor diversity more, and thereby reach a wider range of projects and achieve more universal impact.

Therefore, it is recommended that if blended finance investments globally were to be expanded, that policy makers such as the UN, local governments, and the World Bank find ways to increase awareness of private credit suppliers and for them engage in more blended finance transactions. Furthermore, concrete law and regulation changes should be considered to the use of collateral, both physical and non-physical, by SMEs in developing countries, as to ensure SMEs will become more capable of engaging in loans with banks, which could then be supported by public investors in various blended finance arrangements. It is finally recommended that further research is done on this topic, especially at a larger scale and perhaps slightly into the future, when more projects will have been completed and therefore results will have become clearer. This could further explore the effectiveness of blended finance compared to other investment methods, and if found to be more effective, convey this to private parties. If these measures are to be taken and the knowledge on blended finance is expanded, it stands to reason that blended finance could be one of the tools to reduce the investment gap in sustainable development and aid in the creation of jobs in developing countries, where people need these most.

The gap between planning and budgeting is a problem for improving health systems. In decentralisation health care services, authority, resources, and responsibilities are moved from central actors (i.e. national government) to peripheral actors (i.e. municipalities). Adding the risk of creating silos within sub-national governments, creating the need for collaboration in some form. Data analytical forecasting, like prognosis tools, may facilitate planning for health care service implementation. When operating on the interface between actors, as a boundary object, they may mitigate the risk of fragmentation and isolation associated to decentralisation, by enabling collaboration.

In the case of decentralised Assisted Living in the Netherlands ("Beschermd Wonen") citizens dealing with psycho-social problems, receive guidance to participate in society. Newly responsible sub-regions have limited facilities and funds for their own citizens.

Newly responsible sub-regions having limited facilities and funds, may face incurring costs and inaccessible care when citizens seek to other areas due to uncoordinated implementation and elimination of facilities. To plan these, a prognosis tool was designed and developed for the three sub-regions.

A literature review was conducted on decentralisation of health care services globally. The prognosis tool’s technical design and development, and observations during, were studied. Analysed Interviews with actors involved in the prognosis tool, assessed if and how collaborating was enabled.

Lack of research on the implementation of decentralisation for health services, the use of prognosis tools for this purpose, the risk fragmentation resulting from independent processes and lack of system focus and the need for collaboration were highlighted in the literature, justifying building and testing a tool.

The design of the tool was therefore intentional: colour codes stimulated usability, the three sub-regions sub-files were stored in one place promoting transparency, and standardisation was stimulated by representing all sub-regions’ demands and resources into a general fitting categorisation and identical calculations from input to results for all sub-regions.

The tool and outcome is usable for agreements with care suppliers (procurement) or housing and enables organisation through agreements between sub-regions.

The meta-analysis of the interviews revealed that from the prognosis tool’s design and development, shared understanding emerged through shared language and extensive problem demarcation.
An independent expert mediated the needs of sub-regions, staying close to the task. This combined with the factual outcome led to insight and clarity in the content of subregions’ own and other’s task.

Inducing trust and confidence in the relation and in achieving own and shared goals. Leading to tranquility and comfort, setting the atmosphere for collaboration. By clarifying the uncertainties and interdependencies, where or why collaboration is needed (the identified risk) has stimulated collaborative action.

This prognosis tool has enabled collaboration for decentralised health services by addressing both socio-technical aspects. The latter integrate the effected sub-systems, ensuring the outcome can be used for organising future steps (such as procurement). The former, extensive problem demarcation and shared language emerged a shared understanding of the system. In combination with the factual outcome (prognosis), insight and clarity was created into the actual need and to enable trust and comfort, enabling collaboration.

Implemented in river landscapes, Nature-based Solutions (NbS) have the potential to reduce flood risk, while also playing an important role in restoring many of the ecosystem services that are lost as result of human interventions and global warming. A barrier to succesfull implementation of NbS is the lack of a global and common framework with guidelines for its implementation and evaluation. In response, the IUCN Global Standard for NbS was published. Even though the IUCN Standard has been designed to be applicable to NbS in all sectors and over the entire globe, knowledge on its applicability and usefulness for specific sectors remains limited at present. Therefore, this study aims to identify the challenges that occur in ex-post application of the IUCN Standard to river restoration projects with a focus on flood risk mitigation, and the added value that this application may provide.

At first, a literature study is conducted in which the content of the IUCN Standard is related to twenty-two other assessment frameworks for NbS and compared in-depth to the three most relevant frameworks. These comparisons indicate that that the IUCN Standard has a broad scope of application, provides limited flexibility in assessment to its users and is descriptive. Furthermore, the comparisons reveal that the IUCN Standard can be used as a tool to evaluate the extent to which the essential processes of a NbS, established by the IUCN, have been incorporated in the project (i.e., process-oriented framework). The standard can, however, not be used to evaluate project results, including biophysical and social results.

In the next part of the research, the IUCN Standard is applied to three case studies of river restoration projects with a focus on flood risk mitigation, of which at least two differ significantly in the surface area, position in the catchment, kinetic energy of the river, data accessibility, resources and the type of riverine NbS measures that were implemented. The selected case studies are the Eddleston Water Project, the “Room for the River” Deventer Project and the Missouri River Levee Setback Project. Despite facing challenges in the interpretation of indicators, data accessibility, a relatively coarse scale for evaluation, and tensions between the project objectives and the use of the IUCN Standard, the standard is successfully applied to all case studies. The case study results consist of (1) a total percentage match to the IUCN Standard and a statement on being in adherence to the standard, which may provide credibility to the project processes, (2) the strenghts and weaknesses of a project, which may be used to guide projects and strengthen (future) projects, and (3) a radar chart, which may provide possibilities to compare to and learn from other projects. Based on these results, it can be concluded that, despite of a few challenges, the IUCN Standard is applicable to river restoration projects with a focus on flood risk mitigation, and that application of the standard may provide added value in various ways, although restricted by the limited evaluation of flood risk mitigation.

The IPCC report of August 2021 calls for an immediately reduction in greenhouse gas emissions. Without changing the world’s diets, even if we stop all fossil fuel emissions today, we would still not be able to maintain global warming below 1.5°C. The EU has set out their strategy for reducing agricultural emissions in the Farm to Fork Strategy, as part of the European Green Deal. This strategy, however, falls short of addressing meat consumption. Individual meat consumption is shaped by a range of factors, including social norms. The influence of these norms is investigated in this thesis, which addresses the research question: “how do social norms influence meat consumption and to what extent can European policy influence these to reduce meat consumption?”. This thesis takes the Netherlands as case study, and constructs an explorative agent-based model, based on the Theory of Planned Behaviour, where social norms spread through social networks. Individual meat consumption is broken into beef, pork, poultry, processed and substitute meat consumption. The factors of influence are analysed in this research through a correlation analysis of various surveys, and the likelihood to eat specific meat types is calculated through a least-squares multiple regression analysis. This research finds that social norms play a tangible role in shaping consumption, and targeting these can emissions from meat consumption by 0.4-4%. Fiscal policies are a more effective policy measure for the EU to follow, as a 20% tax on all meat can reduce emissions by 10%. A tax on beef was found to redistribute consumption in such a way that overall emissions do not decrease. The findings from this research are discussed in the political, policy and socio-economic contexts regarding meat consumption.

This dissertation aims to contribute towards the research on just transitions by providing insight into the extent of the employment impacts caused by a potential energy transition in South Africa. South Africa is in the process of transforming its electricity mix. The majority of electricity is currently sourced from coal-fired power plants. The transition maybe towards an electricity mix that includes more renewable sources of electricity generation, particularly from wind and solar technologies. The degree to which this transition will create and displace jobs is presently unclear. Furthermore, the extent to which these new jobs will be demanded locally or abroad and the implications that this transition will have on decent work is uncertain.The main research question posed at the outset of this dissertation was: What are the possible net employment effects of South Africa’s transition from coal to wind and solar forms of electricity generation? A quantitative method was employed to address this question: an Input-Output Analysis. The I-JEDI input-output model was used, updated with more recent data for South Africa that has more industrial detail. Additionally, a coal displacement vector was created to calculate the jobs displaced due to lack of demand for coal-fired power plants. Hence, the net employment effects were calculated. This quantitative method was supplemented with findings from a series of semi-structured interviews and a workshop with union members to ground the results in some of the realities of South Africa’s socio-political landscape. Two exploratory scenarios were createdthat were simulated in the model, each with their own narrative about South Africa’s future electricity prospects: Integrated Resource Plan (IRP) 2019 scenario and the Ambitious Solar and Wind (ASW) scenario. The IRP 2019 scenario was aligned with the recent government plans to transform the electricity mix. The ASW scenario included higher levels of local manufacturing of solar and wind technologies than currently employed. The results of this research are exploratory, aiming to provide insight into the boundary of what is possible. The main findings suggest that solar and wind may employ significantly more people than currently employed in the coal-fired power plant supply chain considering both operations and maintenance (O&M) and construction activities. O&M jobs numbers for coal-fired power plants are larger than wind and solar under the IRP2019 scenario but are comparable for the ASW scenario. While the results from the model showed promising prospects for employment, it was revealed through the stakeholder interactions and literature that there are several challenges to achieving a just energy transition. In particular, there is the challenge of garnering the support of labour unions and ensuring decent work. It was found that the overall skill levels in terms of education for the different sources of electricity were similar, but there are many other skill considerations required for people to change vocation from the old jobs in coal to new jobs in solar and wind.

Economic activity generates carbon emissions that accelerate climate change. Rising temperatures will eventually lead to climate damages that deteriorate our economic system, putting the livelihood of millions at risk. The purpose of our analysis is to assess how this feedbacking dynamic develops until the end of the century. To do so, we have used a macroeconomic stock-flow consistent model of the global economy called DEFINE, which is based on post-Keynesian and ecological economics principles. DEFINE explicitly includes an ecosystem with finite natural resources, an extensive macroeconomy featuring five main actor clusters (households, firms, banks, government and central banks), and a financial system. Furthermore, we have operationalised the economic policies of the European Green Deal and used them as an input to the model. Using environmental and macroeconomic performance indicators, we have assessed the effectiveness of these policies in achieving sustainable growth and keeping global temperature change within 2ºC by 2100. In our analysis, the European Green Deal fosters the decarbonisation of the economy, but in its current form is not sufficient to keep global warming within the 2ºC target.

To protect the coastal system, nourishment of the coast is nowadays being applied more frequently. Within these coastal systems new elements are often implemented to add value to the design without compromising on the function of the design of the nourishment. One of these possible purposes is the creation of an artificial lagoon. However, to be effectively applied a deeper understanding of the behaviour of these lagoons is required. In 2015 the Hondsbosse Dunes (HD) were realized at the Dutch coast at the former “Hondsbosse en Pettermer Zeewering” near Camperduin, and an artificial lagoon was created for nature and recreation purposes within this design. The lagoon provides a boost for both the beach itself as well as the surrounding region. However, the lagoon’s inlet is not stable and continuous maintenance is needed. The objective of this study is to explore the behaviour and longevity of this artificial lagoon, considering the frequency and moments of closure of the lagoon’s inlet. This is achieved by assessing and studying offshore hydrodynamic conditions, satellite imagery, geographical measurements, dredging activity, and water level measurements inside the lagoon. Whether the lagoon is stable or not depends on the inlet stability. Key factors that affect the inlet stability are the tidal prism and the annual littoral drift. The lagoon at the HD can be characterized as an intermittently closed estuary, which is a water body that become isolated from the open coast for a period of time. This system can be divided in a perched or a non-perched system. A perched system has a high berm that closes of the system, where a non-perched system does not necessarily have a berm but has a lack of channel surface area. To get a better understanding on how local hydrodynamic conditions can cause the lagoon’s closure, the hydrodynamic conditions and available data were analysed. The significant wave height for storm events and the total water level at the shore, which includes the tide, the surge and the runup, are considered for the hydrodynamic conditions. Geographical measurements, satellite imagery and dredging moments are used to achieve a better insight of the system. The lagoon surface area is examined above 2.03 m NAP, to establish the behaviour of the lagoon basin and its inlet in time. The result of the data analysis performed in this thesis suggest that the lagoon surface area does not move spatially in time. However, due to the lack of bathymetric measurements the lagoon could not be studied in further detail. Closure of the system occurs due to its highly dynamic channel, which is supported by an analysis of the cross-sections of the channel area in combinations with satellite imagery. A detailed view on the water level inside the lagoon and the exchange between the open coast resulted in four stages that were indicated visually: 1.Closed stage, resulting in a closed channel. The water level can only increase when the water level at the open coast overflows the berm. It leads to a stepwise increasement of the water level, referred to as a perched system. .Open stage. The channel is open and water exchange is possible with the open coast. The effect of the tide can be observed clearly in the water level of the lagoon. 3.Dredging stage. The water level decreases rapidly from a level above high tide at the open coast, to a value near or below high tide level. Afterwards water exchange with the open coast may occur, but this is not always the case. 4.Episodic event. The water level fluctuates, for which the cause cannot be stated beforehand. It depends among others on the type of system, hydrodynamic conditions and on the shape of the channel. The system is called non-perched when a high-water level overwashes the berm in the channel. It seems that the system is open, but water exchange does not occur and the water level in the lagoon increases Analysis of these stages indicates that the system is closed almost 70% of the time. The system is most often closed between October and April, when the channel is dredged again leading to an open system. An open system occurs after dredging in spring, where the results shows that the water level inside the lagoon follows the tide. The data indicate that the system is open for 10-17% of the time. Storm events highly influence closure of the channel. Although storm events on the North Sea are indicated by a significant wave height larger than 400 cm, the results demonstrate that storm events with a significant wave height of 300 cm provoke closure of the channel. This is the result of the small catchment of the lagoon. These storm events increase in winter periods, whereas summer storms appear two to three times a year. The impression that storm events lead to closure of the channel is therefore confirmed. The results show that the lagoon remains the same over a timespan of three years, which suggests that the frequency of closure and opening is not time dependent. This leads to different dredging strategies that are possible for the near future. To create an open lagoon all year round, dredging frequency needs to increase, as it is implied that storm events lead to closure. This increases the dredging costs. If the preference lies in low dredging costs, the system will be closed during certain periods of the year. Since the lagoon is created for recreation purposes closure during the winter season and dredging during the recreation season is proposed as a strategy. These findings correspond to the currently considered strategy for the HD. The data suggest that artificial lagoons, like the investigated case at the Hondsbosse Dunes, never stay open or open without human intervention. This indicates that active management is needed to keep these lagoons open.