Ensuring accessibility to large-scale housing sites in the Netherlands is crucial due to the housing crisis, limited space and financial constraints. Poor transport- and spatial planning decisions can lead to congestion and restricted access, issues often overlooked in fragmented policy-making. To address this, policy integration is needed. However, integration between transport and spatial planning remains unimplemented, creating a gap. In a qualitative way, this research tried to answer the question: How can the relationship between transport planning and spatial planning in the Netherlands be strengthened?. Here, a new policy integration concept of manageability is found alongside the concepts of coordination, coherence, and cooperation found in literature. Regional decision-makers should prioritize coherence and manageability at the start of decision-making processes, with coordination and cooperation as foundational elements. Recommendations include exploring policy integration in related domains in the Netherlands, exploring specific policy integration concepts, or dual relationships within the four established policy integration models of this research.

To achieve climate neutrality, the Netherlands is phasing out fossil fuels and expanding renewable energy, with offshore wind playing a key role. The European Commission aims to increase offshore renewable energy capacity to 300 GW by 2050. As wind farms are built further offshore, high-voltage direct current (HVDC) technology is becoming essential for efficient grid connection. TenneT's 2GW program supports this transition by standardizing offshore platforms, enabling faster deployment and scaling of offshore wind energy to meet climate targets efficiently.

A critical component of these platforms is gas-insulated switchgear (GIS), which ensures safe and reliable operation by controlling the connection of wind turbines to the grid. Traditionally, GIS relies on sulfur hexafluoride (SF₆), a potent greenhouse gas with a global warming potential (GWP) of 24,300. In response to environmental concerns, Regulation (EU) 2024/573 mandates a phase-out of SF₆ in switchgear up to and including 145 kV by 2028, necessitating the transition to alternative technologies.

This study evaluates SF₆-free alternatives for high-voltage GIS in offshore converter stations, considering environmental impact, economic feasibility, long-term reliability, safety, technical performance, and regulatory compliance. A multi-criteria decision analysis (MCDA) is conducted, assessing 42 alternative gases and insulation technologies based on GWP, ozone depletion potential, flammability, toxicity, boiling point, and dielectric strength. Two viable alternatives emerge: a gas mixture of C₄F₇N, CO₂, and O₂ (GWP 301–614) and vacuum GIS insulated with clean air (GWP 0).

To determine the feasibility of both technologies for next-generation converter stations, expert interviews are conducted to identify key challenges and drivers. Challenges include its current voltage limit of 145 kV, larger space requirements, and limited supplier availability. A major driver is the transition from 66 kV to 132 kV inter-array cables, reducing the number of required switchgear installations from 40 to 24. This mitigates space constraints and makes vacuum GIS a viable long-term solution. Additionally, ongoing developments in vacuum switchgear technology reduce dependency on a single manufacturer.

A comparative life-cycle assessment (LCA) of SF₆, C₄F₇N, and vacuum GIS focuses on manufacturing and use phase emissions, as these contribute most to greenhouse gas emissions and exhibit the most significant differences among technologies. Results show that C₄F₇N technology has the lowest total emissions in these phases, as vacuum GIS production requires more aluminum, leading to higher manufacturing emissions. While sustainable aluminum sourcing could mitigate this, no regulatory or economic incentives currently exist.

This study concludes that vacuum GIS is the most viable alternative to SF₆ for offshore converter stations, aligning with future platform developments and regulatory compliance. TenneT is advised to prepare for a transition to vacuum GIS, supported by 132 kV inter-array cables, enabling a more sustainable and scalable offshore grid. Future research should focus on a comprehensive life-cycle assessment to fully evaluate the long-term environmental impact of alternative technologies.

Green hydrogen has the potential to contribute in decarbonization efforts and achieving a net-zero emission economy by 2050. This report investigates the potential for production of green hydrogen offshore, using a Floating Production Storage and Offloading (FPSO) vessel. The aim is to determine a techno-economically feasible strategy for deploying this Green FPSO (GFPSO) and in turn its holistic hydrogen supply chain. State of the art literature is reviewed to define the knowledge gap to address and delineate the scope of the research. This is encapsulated by the main research question: "What strategy could be used to deploy a GFPSO supply chain and ensure techno-economically feasible outcomes?". To answer this question, a methodology is devised involving the breakdown of the strategy into key decisions, the outline of the criteria by which the strategy can be scored against, and the formulation of an MILP model. The model encapsulates the supply chain from energy generation, hydrogen production, storage, and transport to destination. Technical and economic parameters are implemented in a North Sea business case context, assuming 4 scenarios which represent how each implemnentation strategy varies. This comes down to the configuration of energy vector of gaseous hydrogen (GH2), liquid hydrogen (LH2), and ammonia (NH3), as well as the transport mode of either shipping vessels or a pipiline, used to deliver the medium from production to demand location. Based on the MILP model result, the optimal locations in the discretized region for energy generation within each scenario, as well as comparison across scenarios using the calculated levelised cost of hydrogen (LCOH) in [€/kg].

The results of the study reveal LCOH values of 4.05-6.52[€/kg] for the time period of 2020-2050. The lowest cost was observed in the GH2 pipeline configuration, followed by NH3 shipping. The pipeline configuration required implementation closer to shore, while the shipping configuration correlates with the location of highest energy availability in the weather data. The greatest portion of the overall costs in all scenarios originated from wind turbines used for energy generation. Conversion process costs formed another significant component of the total costs in the scenarios involving NH3 and LH2. Sufficient reduction of these conversion costs could enable a more competitive performance from the corresponding configurations. Based on the criteria framework, the strategy utilizing GH2 pipeline supply chain configuration performs best in terms of LCOH, CO2 emissions, and access, while NH3 shipping performs better in Commercial Readiness Index (CRI), Technological Readiness Index (TRL), Ease of Implementation (EoI), and in existing regulations. The significance of these strengths and weaknesses will vary depending on the weight attributed to the importance of the criterion by the decision making entity.

Effective waste management is critical for urban sustainability, yet decision-making in this domain is often divided due to diverse stakeholder interests. This study applies the Multi-Actor Multi-Criteria Analysis (MAMCA) to evaluate waste collection alternatives for the redevelopment of the Dreven, Gaarden, and Zichten neighborhoods in The Hague. Stakeholders—including the Municipality of The Hague, Staedion (housing corporation), Haagse Milieu Service (waste collection service), and Heijmans (developer)—were engaged to define key evaluation criteria: cost, space usage, ease of use, sustainability, and implementation feasibility. Five alternatives were assessed: (1) the existing Underground Residual Waste Containers (ORACs) as a baseline, (2) Indoor Roll Containers, (3) Indoor Press Containers, (4) Press Underground Containers (ORACs with compaction), and (5) an Underground Waste Transport System (OAT). The results indicate that press underground containers (ORACs) are the most supported alternative across stakeholders, offering a balance between cost efficiency, operational feasibility, and sustainability. In contrast, indoor roll containers received the lowest evaluation due to high operational costs and inefficiencies. Despite this, indoor roll containers are currently being implemented in the first newly constructed buildings in the redevelopment area. This underscores the necessity of using MAMCA in waste management decision-making, as it enables a structured, multi-stakeholder approach that can lead to more broadly supported and efficient solutions. The study demonstrates MAMCA’s potential as a decision-support tool, integrating stakeholder preferences and structuring complex multi-criteria evaluations. The findings provide a foundation for the data-driven, phased implementation of press underground containers and emphasize the importance of stakeholder collaboration in waste management decision-making.

Autonomous Driving Systems (ADS) are an innovative solution to urban mobility problems and have the potential to transform the Dutch roads radically. However, before these systems can be widely adopted, they must undergo a rigorous certification process to meet safety and reliability standards. Regulatory authorities are currently grappling with the challenge of certifying ADS responsibly. Despite significant technological progress, there is still limited understanding of the root causes behind these certification challenges. Without a clear understanding of these obstacles, finding effective solutions remains difficult. Therefore, this research aims to explore the barriers to responsible ADS certification and provide insights into how these challenges can be overcome.

Summary
Cities worldwide face the dual challenge of increasing density while developing sustainably. These pressures strain transportation systems, necessitating optimal performance. In the Netherlands, transport policy focuses on three main objectives: accessibility, liveability, and safety. This thesis addresses accessibility and liveability.
Liveability concerns the fit between residents and their living environment. This fit is an ecological relationship involving interactions with the built, natural, and social environments. The thesis explores two approaches to operationalising this ecological fit: static and dynamic. The static approach, exemplified by tools like the Leefbaarometer, views liveability as a measurable outcome. It considers the valuation of the environment as a proxy for fit, obtained through surveys or hedonic pricing methods. This approach is widely used in current transport policy evaluation but is limited in its ability to do ex-ante analysis.
On the other hand, the dynamic approach views liveability as an ongoing process. It considers fit the difference between what a resident expects to observe and experiences. This approach uses generative modelling, which involves causal probabilistic relationships. The manner in which these generative models are updated is unique, attempting to capture the dynamics of the reciprocal relationship between the resident and the living environment. The resident embodies the generative model, containing both internal and external states. The generative model is definitive of a resident's niche. Construction of the niche is afforded by accessibility.

Objective
The thesis aims to work towards future operationalisation of the dynamic approach to liveability. While full implementation is far beyond the scope, the objective is to understand the role of representations in defining and operationalising liveability. In the context of transport systems, representations can be understood as simplified and compressed digital twins of complicated urban environments. These representations can be used for decision-making in infrastructure planning and policy formulation.
The dynamic approach to liveability relies on the action-perception loop as its generative model. This loop means that perception is anticipated, an action in itself. Selecting optimal actions is a matter of maximising epistemic and pragmatic value. Writing a thesis is an action; hence, we follow the formal decomposition of action selection:
• Epistemic component: develop a theoretical framework, exploring the action-perception loop in liveability and the role of representations within this loop. Bridging cognitive science and transport modelling enables novel machine learning applications.

• Pragmatic component: automate the operationalisation of liveability by applying urban representation learning techniques to the province of South Holland. Our novel contribution is the developed mathematical model based on spatial convolutions. The study uses various data sources relevant to transport planning, including road networks, public transport schedules, aerial and street view images, and points of interest.

Modelling Study
Addressing the pragmatic component, we develop a novel urban representation learning technique using the H3 hierarchical hexagonal discrete global grid system (DGGS). Neural networks are used to extract representations such that each discrete hexagon is assigned a coordinate in the metric representation space. Features from different data sources are extracted using individual encoder networks. These features are then combined using a late-fusion network to obtain the final representations. We develop Ring Aggregation, a mathematical model to fuse multiple features while accounting for spatial context through sampling heuristics and spatial convolutions. The methodology considers insights from the dynamic approach to liveability, like landscapes of affordances, analogous to location-based accessibility. No operationalisation of the dynamic approach is developed in this study. Instead, this study applies the static approach and evaluates urban representations using multiple univariate linear regressions with Leefbaarometer scores as targets.

Key Epistemic Observations
• The action-perception loop is central to the dynamic approach to liveability but absent in the static approach.
• Representations play an instrumental role in the action-perception loop, informing action selection.

Key Pragmatic Observations
• Regarding sampling heuristics used to train the late-fusion network, Euclidean distance and location-based accessibility perform similarly, better preserving urban area integrity.
• The configuration of Ring Aggregation significantly impacts urban representation quality, showing heterogeneity between Leefbaarometer scores. Socially oriented scores can perform just as well with smaller receptive fields and steeper weighted average functions like exponential.
• Different data sources excel in predicting various aspects of liveability, suggesting the importance of integrated data approaches in transport policy.
• Compared to urban2vec and M3G studies, Ring Aggregation outperforms them in predicting Leefbaarometer scores across the board.

Looking Forward
By reframing the roles of indicators, perception and preferences, this thesis concludes that static and dynamic approaches to liveability are complementary. Complementarity implies that the static approach to liveability can be used to bootstrap the development of the dynamic approach. While 'living' digital twins operationalising the dynamic approach do not yet exist, this study provides building blocks towards their development. Future directions for research and application in transport policy centre on the hypothesis that hierarchical active inference models are already transport models, just waiting to be used.

The introduction of Highly Automated Vehicles (HAVs) presents challenges for everyday transport, particularly impacting cyclists, who are part of what is called vulnerable road users. While HAVs promise to optimise traffic flow and enhance safety, concerns about their safety remain. This research addresses the gap in understanding cyclists' expectations and perceptions of social driving behaviour in The Netherlands. By developing a conceptual framework and a questionnaire, the study explores the interactions between cyclists and HAVs, focusing on trust, perceived safety and perceived social behaviour of cyclists in urban settings like The Hague. Findings reveal that cyclists' comfortability with sharing the roads with HAVs and their belief that HAVs are more likely to follow the rules influence their opinions. Additionally, the use of electronic Human-Machine Interface (eHMI) in HAVs, seems to positively affect cyclists’ trust, perceived safety and perceived social behaviour. Notably, it is found that demographic factors have little influence on cyclists' attitudes towards HAVs. The study underscores the importance of predictability in fostering higher safety ratings and demonstrates how the characteristics and driving behaviour of HAVs affect cyclist perceptions. These insights can guide policymakers and developers in devising solutions that enhance the safety and well-being of all road users, ensuring the effective integration of HAV technology while minimising potential drawbacks.

The construction of the Grand Ethiopian Renaissance Dam (GERD), a massive hydroelectric project on the Blue Nile, is part of the broader Nile River basin, which spans across 11 countries in northeastern Africa, including Ethiopia, Sudan, and Egypt. The GERD is designed to be the largest dam in Africa, with the primary purpose of generating electricity to power Ethiopia’s development and provide energy to neighbouring countries. However, its construction has ignited significant debate, particularly due to concerns from downstream countries, Sudan and Egypt, which rely heavily on the Nile's waters for agriculture, drinking water, and energy production. The dam's operation and management have far-reaching implications for the entire Nile basin region. Adding to this complexity is the uncertainty of future climate conditions, which could drastically change water availability in the region. To navigate these challenges, it is essential to develop robust reservoir management strategies—policies that are resilient and adaptable to various future scenarios. This thesis explores a broader and more detailed approach to evaluating the robustness of water management policies, focusing on the case of the Nile River. Instead of relying on a single metric, we use multiple robustness metrics; Percentile-based Skewness, Mean-Variance, Undesirable Deviations, and Minimax Regret to see how they might lead to different conclusions about the best strategies.

To evaluate the resilience of these policies against future uncertainties, a series of steps are involved. First, policies are generated using optimization techniques designed to identify the best strategies that could foster cooperation among the countries, while also addressing their individual objectives. These strategies are then tested for their effectiveness under various future scenarios, which is done by applying robustness metrics. A robustness metric is a quantitative measure used to assess the resilience and stability of a system or process in the face of uncertainties, disturbances, or perturbations. It provides a way to quantify how well a system can maintain its performance or functionality under varying conditions. These metrics can range from assessing absolute performance or regret prioritizing risk-aversion, maximizing performance, or minimizing variance, depending on the specific uncertainties and the decision-maker's risk tolerance. However, many previous studies done on robustness of reservoir control rely on the 90th Percentile Regret metric which looks at how much worse a given strategy performs compared to the best possible outcome. While useful and practical, this approach doesn’t fully capture the range of different ways to test against future scenarios.
This research reveals that the choice of robustness metric can greatly affect the evaluation of different policies. Using four different metrics, we were able to conclude different “most robust” policies. Using minimax regret metric, Compromise Policie(s) are the most robust. However, using Undesirable Deviations metric, Best Egypt Irrigation Policy is the most robust. Using Percentile-Based Skewness yields Compromise: Percentile and Best Sudan Irrigation Policy as the most robust, and using Mean-Variance metric, only Best Sudan Irrigation policy emerged as the most robust. This variation occurs because different robustness metric prioritizes different aspects of policy performance under uncertainty. While the regret metric focuses on minimizing the worst-case scenario outcomes, other metrics like Percentile-Based Skewness emphasize the consistency of outcomes across a range of scenarios.

These findings emphasize the importance of using a diverse set of robustness metrics in policy evaluation. A diverse set of metrics allows for a more comprehensive assessment of policies by capturing different aspects of performance and risk under uncertainty. Depending on which metric is used, different strategies may be recommended, leading to potentially different outcomes for the countries involved. While strategies may seem mutually exclusive, a more nuanced approach can involve balancing the trade-offs highlighted by the various metrics, leading to a more informed and robust decision-making process.

The European Union Emissions Trading System (EU ETS) and the Carbon Border Adjustment Mechanism (CBAM) are important mechanisms to the EU’s climate strategy. They aim to reduce greenhouse gas emissions and prevent carbon leakage, where production shifts to regions with looser emission constraints. Established in 2005, the EU ETS operates on a cap-and-trade principle. It raises production costs for EU industries compared to international markets, leading to losses in market shares. To address this, the CBAM places a tax on imports based on their carbon content. This aligns foreign producers with EU carbon pricing and targets emission-intensive goods primarily in the manufacturing sector. This approach discourages the relocation of carbon-intensive production. It also incentivizes non-EU countries to adopt similar measures. By integrating CBAM with the EU ETS, the EU aims to maintain industrial competitiveness and promote global decarbonization efforts.

This thesis quantitatively assesses the impact of the CBAM on the price competitiveness of emission-intensive and trade-exposed industries in Germany. Germany is the EU's largest economy and a key player in manufacturing and exports. By developing a Leontief input-output price model and using data from Eurostat's FIGARO database, the study examines the effects of CBAM on production costs, export competitiveness, and domestic market competitiveness. The main research question is: "To what extent does the CBAM change the price competitiveness of carbon-intensive industries in Germany?" This price-centric analysis provides industry stakeholders with insights into the immediate cost impacts of CBAM on their sectors.

The analysis reveals that Germany’s manufacturing sector sees a minimal average production cost increase of 0.8% with the CBAM. Sub-sectors like basic metals, non-metallic mineral products, and refined petroleum face cost increases up to 3%. The CBAM effectively mitigates domestic market competitiveness deterioration by raising import prices from non-EU countries more than domestic production costs. However, it negatively impacts export competitiveness, necessitating additional measures such as subsidies, tax credits, export rebates, and “contracts for difference.” The CBAM also presents opportunities for revenue recycling into green infrastructure and technologies. The study underscores the need for supportive export-oriented policies to maintain Germany’s industrial competitiveness under stringent climate regulations. Despite some export market losses, gains in domestic markets are more pronounced. This understanding of the CBAM's economic implications is important for the EU’s climate strategy and economic integration. The results of this thesis have several limitations due to modelling simplifications. These include assumptions of no behavioral changes by companies, fixed production inputs, and linear technology, which may not reflect real-world adaptability and substitution capabilities. Additionally, the model assumes non-EU countries face the full CBAM tax without considering their emissions trading systems or free allowances within the EU, potentially overestimating cost impacts.

This thesis contributes to the existing literature by offering a targeted, sector-specific analysis of the CBAM's impact on Germany's manufacturing economy. Prior studies have largely overlooked this, focusing instead on aggregated country-level impacts or external trade partners. Emphasizing price impacts and using a detailed input-output model, the research provides actionable insights for policymakers to refine the CBAM and support vulnerable sectors. It adds to the policy debate on balancing environmental goals and industrial decarbonization by identifying the most affected manufacturing sub-sectors. The comparative analysis between Germany and the EU highlights the differential impacts of the CBAM and shows Germany's specific vulnerabilities and strengths, such as the mitigating effect of high value-added in the chemical industry. The study also demonstrates the integrated effects of the CBAM and the EU ETS, providing insights into their interplay. Using the novel FIGARO database, the research sets a precedent for future studies to use similar data sources. Finally, it offers policy design considerations to mitigate negative CBAM impacts, providing a scientific foundation for policy adjustments.

Future work should focus on sector-specific studies in carbon-intensive industries like steel, cement, aluminum, and chemicals. These studies should explore the sectoral impacts of CBAM and consider revenue recycling models. Research should also integrate varying substitution rates and price elasticities in input-output models, using detailed data collection on compliance costs to improve accuracy. Combining input-output with agent-based modeling can provide further insights. Improved data-sharing practices between the EU and trade partners are essential. Standardized protocols ensuring consistency and reliability, potentially via international data spaces, will lead to more precise insights.

The heavy-duty road transport sector is critical to European trade and socio-economic development, moving millions of tons of goods within and to neighboring countries, and this depends on fleets of diesel trucks. The path to decarbonization in Europe will require joint efforts from multiple stakeholders and significant investments in technological development, infrastructure and fuel production. This study assesses the available drivetrains to meet the European Union’s carbon reduction targets, and provides insight into the future market segmentation from the perspective of the transport companies. It quantifies selection criteria by setting a mixed-integer linear programming problem to optimize the total cost of ownership of transport, while complying with carbon reduction targets set by the European Union, and discusses underlying factors that may play a significant role. The results show that there will be significant segmentation and diversification in drivetrain technology in the short to medium term, including zero-emission, low-emission and conventional fossil technologies, as economics and carbon reduction targets play a major role in determining the composition of future truck fleets. Ultimately, fossil-based vehicles could be entirely phased out in favor of zero-emission trucks, where the market share is split between battery electric and fuel cell electric vehicles. Key factors influencing this segmentation are the price of fuel, availability of bio-based fuels and the role of emission regulation, in particular the scope and severity of future carbon reduction targets. Furthermore, underlying implications may also have important consequences, including customer perspective towards new technologies, renewable energy intermittency, security of supply, critical material supply chains, and the significant infrastructure upgrade and development costs. The degree to which these issues will affect the future transport market is unknown.

In the last years, the effects of the climate crisis on the environment and living species have become increasingly tangible. Emissions and release of chemicals are damaging ecosystems and substantially increasing the rate of respiratory and infectious diseases, which have never been present previously in some of those regions. This has led to a careful reconsideration of the environmental impact of human activities which highlighted the significant footprint of the healthcare sector, arising a paradox: although it is providing cures and assistance to the population, at the same time this sector is increasing the demand for it by substantially contributing to the total environmental footprint.
Looking at the Netherlands, the healthcare sector is responsible for approximately 7 percent of the national environmental impact in terms of CO2 emission equivalent, 4 percent of the total waste, and 13 percent of the consumption of raw materials. These considerations underpin the necessity to consider this impact in evaluating new interventions in this sector. However, the lack of guidelines, agreement on methodology, and practical examples still represent a substantial barrier to the actual inclusion of sustainability criteria in the economic evaluation
of healthcare interventions.
From this fragmented scenario, two research questions stem: How is it possible to evaluate the environmental footprint of care pathways? And once it has been quantified, how can it be included in the current economic evaluation of the healthcare interventions? In this thesis, answers to these research questions are provided by conducting a case study. It is centered on a chronic disease whose long-term management represents a burden for the Dutch healthcare system both in terms of natural and human resources: Chronic Kidney Disease (CKD). In fact, in the Netherlands, with a prevalence of 8.9 percent, it requires a significant number of healthcare professionals (GP, nephrologist, specialized nurse) and requires extensive natural resources (water, electricity). Therefore, the environmental impact of the care activities involved in the treatment of CKD has been evaluated. In doing
so, a framework has been created to address the first research questions. Following the Sustainable Healthcare Coalition (SHC) guidelines, the entire care pathway has been disassembled into modules, tailored with experts’ help on medical practices followed in the Netherlands. Therefore, next to providing relevant insights into the most environmentally impactful activities in the CKD care pathway, this work contributes to the general knowledge concerning the environmental analysis of the care pathway by providing (for the first time according to the knowledge of this author and the experts involved) a framework applicable, with the necessary modifications of the specific cases, to every chronic disease in the Netherlands. Additionally, to provide an example of how to include environmental impact in the economic evaluation of healthcare intervention, a medicine prescribed to
CKD patients has been chosen: Forxiga.
So far, the few attempts to take into account the environmental footprint of treatment in their economic evaluations have been made by incorporating it as a cost. In this thesis for the first time, next to the inclusion as a cost,
the environmental impact of a medicine has been translated into actual health benefits and incorporated in its economic evaluation. Additionally, an overview of the existing environmental metrics and analyses is presented to provide the reader with a full picture of the current practices.
This study is particularly relevant for several stakeholders. In the first place, its insights concerning the most polluting segments of the care pathway may be very valuable to steering policymakers’ future strategies to reduce emissions and to emit guidelines in this field. Next to that, the information presented in this work may create a competitive advantage for (bio)pharmaceutical companies which can make their production and distribution processes more sustainable thereby addressing the general public’s concerns about the footprint of the sector. Additional beneficiaries of this study are health insurance providers and other healthcare payers who can utilize its results in the negotiation process with (bio)pharmaceutical companies.
This study shows that carrying out an LCA (which is not a common healthcare practice yet) for care pathways is feasible and valuable. In addition, it shows the added value of including the environmental impact of medicines in their economic evaluation so to provide a more comprehensive assessment. However, despite the relevance and the added value, some limitations have been identified. Carrying out an LCA is a resource-intensive and time-consuming activity that many companies often cannot afford. It is a data-driven analysis that is severely hindered by the lack of knowledge-sharing within the healthcare sector. In the absence of data, this analysis requires several assumptions and involves many proxies that undermine the reliability of its results.

On railway lines with scarce infrastructure capacity, allocation methods allow for the assessment of the capacity requests from railway undertakings. The European Commission introduced a regulation to ensure a uniform approach to capacity allocation across all member states through socioeconomic and environmental criteria. However, relevant experiences and methods related to such criteria are hard to come by across Europe, meaning that such criteria' impact on capacity allocation is unknown. In this paper, we provide a method that applies the European criteria and can give insight into the possible impact of this new way of allocating capacity. The railway line Deventer – Bad Bentheim case study allows for the application of the method and defines its possible impacts. Compared to the current Dutch approach of distributing capacity scarcity, open-access train services have higher chances of receiving capacity access. The result shows how railway undertakings will behave more beneficially to society during capacity allocation procedures following the implementation of the method. Recommendations to improve the method are to reduce the number of assumptions, provide an inflation correction across all monetary parameters and consider using minimal frequencies.

In Dutch policy-making, there is a growing emphasis on embracing a broad definition of welfare, transcending traditional economic metrics and encompassing all facets valued for a good life, both presently and for future generations, as well as on a global scale. This perspective, called brede welvaart in Dutch, is referred to as broad prosperity in this research. Despite the widespread belief in the importance of policy integration for fostering considerations of broad prosperity in mobility policy, the governance of this integration remains ambiguous. This thesis aims to address how governance structures can effectively ensure that broad prosperity principles are utilised in mobility policy-making, particularly through integration with urban development policy-making.
Adopting a qualitative multiple-case study approach, this research systematically investigates the intricate interplay between policy integration in mobility and urban development, broad prosperity considerations, and the resulting policy-making process. Literature review and expert interviews are combined to formulate a conceptual framework for distinguishing broad prosperity policy-making from conventional policy-making and measuring policy integration. A thorough analysis of the decision-making process in mobility plans for the cases Zeeburgereiland, Binckhorst, Valkenhorst, and Merwedekanaalzone is executed through document analysis and stakeholder interviews. This information together with results from focus groups in which workable governance approaches are discussed, provide an answer to the main research question: How should the governance of mobility and urban development be organised to enable a broad assessment of welfare in policy-making?...

The aviation sector, responsible for approximately 2% of global anthropogenic greenhouse gas emissions, is projected to grow 4-6 times by 2050, conflicting with the European Union’s Green Deal target of achieving net-zero emissions by the same year. While aircraft electrification offers a promising solution, its application is largely limited to short-haul flights due to range and weight limitations. Sustainable Aviation Fuel (SAF) emerges as a compelling alternative for long-haul operations, as it is compatible with both existing infrastructure and can be blended with fossil fuels. Currently, Hydroprocessed Esters and Fatty Acids (HEFA) is the predominant pathway for producing SAF. There remains a significant supply gap for SAF, emphasising the need to scale up production and explore alternative technologies. This thesis evaluates the potential of hydrothermal liquefaction (HTL) and fast pyrolysis (FP) to address this supply gap.

The research objective is to compare HTL and FP with HEFA. A literature review identified three main knowledge gaps: (1) a lack of studies on the social impacts of HTL and FP, (2) the absence of stakeholder involvement in evaluating these technologies, and (3) the need for updated data integration to effectively compare HTL and FP with established SAF technologies like HEFA. This study addresses these gaps using a multi-criteria analysis (MCA) to provide a holistic evaluation across a multi-temporal timescale while considering diverse stakeholder perspectives.

The study employed a four-phase methodology. The first phase began with the identification of stakeholders through desk research. The second phase involved establishing the criteria for the MCA via a literature review focusing on four main dimensions: environmental (Global Warming Potential and use of by-products), economic (capital expenditure, operating expenditure, and feedstock price), technical (technology readiness level and efficiency), and social (safety and social impacts related to feedstock use). The stakeholders assigned the weightings of each criterion relative to the others during structured interviews using the Best-Worst Method (BWM). In the third phase, each technology was assessed against the established criteria through detailed analysis using specific methods. Based on the findings of the analysis, SAF experts assigned performance scores to each technology per criterion. Finally, in the fourth phase, the criteria and their weightings, along with the performance scores, were integrated to calculate a final weighted MCA score for each technology. This resulted in a final ranking of the technologies based on their overall MCA scores for each stakeholder.

HTL and FP are potential alternatives to the HEFA pathway to produce SAF, each with different advantages and disadvantages. Technically and economically, HEFA currently outperforms due to its maturity and lower costs. At the same time, HTL and FP offer potential environmental and social benefits, particularly in terms of the kind of feedstocks used and the possibilities of by-product valorisation. The preference for each technology varies between stakeholders, indicating the need for a balanced approach that integrates multiple perspectives in SAF implementation decision-making. This research provides actionable insights for advancing SAF technologies and supports the broader goal of achieving sustainable aviation.

Private cars are inefficient in terms of land allocation. Car-free neighbourhoods offer a solution to this inefficiency by enforcing less car-centric urban design, expensive parking fees, and prioritising more sustainable and space-efficient modes of transportation. Carsharing services emerge as an alternative to private car ownership by providing vehicles available for short-term use. Notably, not much is known regarding carsharing services as an alternative mobility solution in car-free neighbourhoods. The present thesis investigates pricing strategies that could be implemented for business-to-consumer carsharing services in car-free residential neighbourhoods to align with the diverse needs and preferences of potential users. To this end, this thesis employs a case study of the car-free neighbourhood Merwede. Specifically, a cost-benefit analysis is conducted to estimate the potential value of carsharing in a car-free context. Emphasis is put on policies that may stimulate carsharing adoption and on determining equitable service pricing strategies.  To predict the modal split of future Merwede residents, datasets – containing mobility information for Utrecht residents clustered by income group – are used. To determine the influence of a service price change on carsharing demand, per-income-group price elasticities are estimated. This resulted in the following values for low-, middle-low-, middle-high-, and high-income groups, respectively: -0.8, -0.5, 0.4, and -0.1. Three stakeholders are considered in the analysis: carsharing service operators, users, and the Municipality of Utrecht. Results indicate that subsidies for lower-income residents in the form of a trip credit incentive (of 50 or 100 euros per month per user) yield positive total net present values and higher carsharing adoption rates. This thesis concludes by stating that while the generalisability of these findings may be limited, the CBA model synthesised for Merwede provides a case study from which future car-free neighbourhoods – aiming to implement carsharing – may learn.

This thesis investigates sustainable renovation alternatives for campus buildings at TU Delft, aiming to contribute to the university's sustainability goals and promote energy-efficient building renovation solutions. The study uses a Multi-Actor Multi Criteria Analysis (MAMCA) framework to evaluate two main alternatives: the implementation of a green roof and an energy efficiency upgrade (EER) project. Stakeholder engagement and analysis is an important aspect of the research, with input gathered from a variety of campus users, including academics, students and Campus Real Estate & Facility Management (CREFM). The criteria considered in the evaluation include environmental, social, economic and technical dimensions, reflecting the multifaceted nature of sustainability. Subsequently, sensitivity analysis are conducted to assess the impact of different stakeholders' preferences on the ranking of alternatives, thus exploring possible trade-offs and aligned views. The results show that green roofs perform favorably on most criteria, particularly in promoting biodiversity, preserving habitats and producing sustainable energy. Despite the challenges posed by limited data availability and stakeholder response rates, this research introduced an effective decision-making framework based on the inclusion of stakeholders and concluded that the multiple interests of different stakeholders can significantly influence the decision making process in sustainable renovations.

This research aims to enhance the understanding and quantification of logistics in the Netherlands by identifying factors influencing freight activities in urban areas. Using a linear regression model developed from BasGoed freight tour data, CBS location data, and Dutch zonal plan data, the study integrates 26 variables to predict freight trip generation and freight generation. The main explaining factors include the surface area of distribution centers, employment in various sectors, the presence of rail or inland waterway terminals, urban density, and the surface area of business spaces. The model, validated through statistical tests and literature comparisons, provides reliable predictions, with employment influencing freight production and surface area affecting freight attraction.

A case study in the Utrecht A12 zone demonstrated the practical relevance of the model, offering insights for policymakers to design logistics-friendly urban environments. Limitations include simplified statistical procedures and reduced accuracy in seaport and transhipment areas. Despite these constraints, the model delivers valuable predictions for various spatial scenarios.

Future research should explore model performance using CBS XML-microdata, consider non-linear relationships, and examine variables for shipment size and vehicle type. Addressing causality and endogeneity with instrumental variables is also recommended. This study contributes significantly to both scientific and societal domains, providing a robust model for freight trip generation and freight generation, and guiding municipalities in effective spatial planning and decision-making for sustainable urban development.