Reusing water is a crucial part of the solution for addressing the growing concern regarding the risk of water scarcity in industrialized and urbanized areas. This study introduces a tool for the design of water networks, focusing on water reuse in industrial parks. Utilizing a mixed-integer nonlinear programming (MINLP) model developed earlier, this tool is the first in water network design models that operates with open-source software, while considering water treatment systems and multiple constituents. A literature study is conducted to discover shortcomings in water network design models and to find a foundational model to use to develop the tool. The developed tool creates a water network based on the optimization of the costs of water obtained from water sources, the costs of treatment systems, and optionally the piping costs. The treatment systems are used to regenerate the water for reuse in industrial plants and to meet environmental discharge limits. The tool develops local optimal solutions as an output. Additionally, this study is the first to integrate a water treatment systems database into a water network design model. However, this database needs to be expanded before it is usable. This study demonstrates the tool through three case studies.

The metaverse is one of the most disruptive technologies to evolve from the digital transformation. While the potential use cases of creating an immersive virtual world are numerous, the vision of an industrial metaverse is only recently emerging as a concept from the technology. In the automotive sector, manufacturers are starting to use simulation, digital twin technology and Building Information Modelling (BIM) to build virtual factories in an industrial metaverse. The benefits of this innovation are believed to significantly boost production flexibility and efficiency, which is why manufacturers set up data-driven digital platforms to enable an industrial metaverse that interconnects multiple actors. How-ever, technical barriers still hamper the implementation of such platforms whose dependence on flawless data grows with the number of use cases for an industrial metaverse. Accordingly, quality insufficiencies of spatial data and the absence of automatic quality assessments to identify these insufficiencies are one of the most decisive barriers to a widespread adoption of industrial metaverse applications. This thesis examines this problem and investigates how data quality insufficiencies in an industrial metaverse en-vironment can be identified and overcome at the example of an automotive manufacturer that uses the Nvidia Omniverse digital platform to create virtual factory models. A design science approach is pursued to create an extension to the Omniverse software that identifies the most critical data quality insufficien-cies, derives key performance indicators (KPIs) and proposes preventive measures to induce a sustained data quality improvement. Thereby, this thesis lays the groundwork for future research emerging around the concept of an industrial metaverse and the remaining obstacles of digital platforms to enable its applications. The pursued DSRM approach to overcome such barriers is capable to serve as guidance for future research projects that pave the way for a gradual enablement of further industrial metaverse use cases in other industries.

A transition from a linear to a Circular Economy is called for. Futures markets in secondary raw materials can support the circular economy through allowing circular businesses to hedge price risk. A blockchain-based architecture is designed using Design Science Research. The architecture can be implemented to facilitate the underlying infrastructure for futures markets: spot markets.

In this research, a few initiatives were completed with practical industrial information and water samples from Heineken®. A Python model was built for an imaginary bottle washer, and tested with difference operational variables under the four testing scenarios. Based on the operational information fromthe Spanish brewery, a second Python model was built for the real-life case study, which was then optimised with several operational variables to reduce either WFP or CFP as caustic soda in five optimisation scenarios. With three water samples from three caustic baths from another bottle washer operated in a Belgian brewery, a composition analysis on significant water parameters was carried out in the Water Lab in TU Delft. This lab analysis gave a basic insight of the compositions of caustic wastewater from bottle washers, and provided possibility to discuss the treatment methods.

Humanity faces the challenge of dealing with resource exhaustion and environmental destruction. The root of these issues lies in the linear economic model established after the industrial revolution. This model relies on two fundamental principles, limitlessness and easily accessible resources and unlimited earth regenerative capacity. The economy thrives by consuming planetary resources to manufacture products and generating wastes by disposing of products in the landfills or incinerating them when they are no longer desirable. However, the growing planet’s population and the limited regenerative earth capacity make this model unsustainable. The circular economy (CE) represents an alternative to the current consumption pattern. It is an economic model aspiring to limit the use of virgin resources in the production systems and eliminate the waste streams by promoting a closed resource loop. The transition to CE is at the top of the agendas of both policymakers and companies (defined as CE auditing actors), which have initiated policy instruments to catalyze it. Such policy instruments could vary from regulations to additional taxes for eco-unfriendly goods. These policy instruments are prone to manipulations when there is a lot at stake. An indicative example is the case, in which plastic waste exported from the Netherlands to Turkey for recycling or reuse was illegally dumped. To prevent such adversities, the CE auditing actors need a monitoring system to control the implementation of their policy instruments and enforce compliance when necessary. Such a system should provide visibility in the flows of raw materials and products in the supply chain and detect frauds. The need for a monitoring system can be addressed by leveraging the research on the data pipeline concept. A data pipeline is an IT infrastructure capturing data at the source. It equips authorities with data shared by the businesses voluntarily and in real-time. This data pertains to the flows of goods from a seller in an exporting country to a buyer in an importing country. Traditionally, data pipelines have been used by customs to access information stored in the traders’ information systems willing to be transparent. The supply chain visibility currently captured by data pipelines is not sufficient to serve CE. They need to be extended to monitor the entire journey of materials and products in the CE context. Furthermore, to unleash the full potential of the shared data, the data recipients need to have trust in the data and its quality. This condition can be satisfied by using blockchain-enabled data pipelines. Blockchain is a technology that exceeds the capabilities of traditional information systems thanks to four characteristics, namely, decentralization, auditability, immutability, and smart contracts. The thesis dives into the research domain of blockchain-based data pipeline solutions by investigating their ability to support the CE transition. For that reason, it develops a framework that evaluates their ability to enforce compliance with CE policy instruments by acting as monitoring systems. The evaluation framework identifies the information requirements needed to be captured by such architectures to monitor the journey of materials and products in a closed-loop supply chain.

The Netherlands is aiming for a circular economy. To transition to a circular economy, eco-industrial parks (EIPs) are needed. The problem is that developing EIPs is not easy. Many industrial parks aiming to become more sustainable and transform into EIPs have failed. In the Netherlands, industrial symbiosis, which is the most important aspect of EIPs, is not common. However, some EIPs in the country have successfully implemented industrial symbiosis and utility sharing activities. Studying what these successful EIPs have done to implement utility sharing and industrial symbiosis activities is relevant to understand what can be done in other EIP developments to increase their likelihood of success. The literature revealed some gaps that need to be addressed regarding EIPs. There is little literature on EIPs in the Netherlands, and most of the existent literature regarding the success factors and barriers to creating synergies in the Netherlands is old. Besides, there is no literature on some EIPs. This study fills the gaps by updating what is happening at three front-running EIPs in the Netherlands and what are the success factors and barriers that played a role in the implementation of synergies. Therefore, the main research question for this study is: What are the main factors that influence the implementation of industrial symbiosis and utility sharing in front-running eco-industrial parks in the Netherlands?Three successful parks in terms of industrial symbiosis and utility sharing were studied using the framework of Eilering & Vermeulen (2004) to answer this question. The selected front-running EIPs were InnoFase in Duiven, Industrial Park Kleefse Waard in Arnhem, and Biopark Terneuzen in Zeeland. A cross-case analysis was made between the three EIPs.In total, nine main factors and 64 sub-factors were found as relevant to implement industrial symbiosis and utility sharing when developing an EIP. With these findings, the framework of Eilering & Vermeulen (2004) was refined.

Technologies for the reduction of the carbon dioxide emissions in the Dutch vegetable oil and fat industry are identified and characterised by their costs and carbon emission reduction potential. The Dutch vegetable oil and fat industry consists of seven companies each producing more than 10 kton CO2 per year, emitting a total of 0.36 Mton CO2 in 2018. In this study, Marginal Abatement Cost (MAC) curves are created to obtain an overview of the most cost-effective decarbonisation options. Both energy efficiency improvement technologies and alternative heating systems are required to achieve full decarbonisation of this industry. The energy consumption for the vegetable oil processing can be reduced by 44%, 45% and 57% for rapeseed oil, soybean oil and palm oil, respectively. The Vertical Ice Condensing technology is the most cost-effective decarbonisation option and a biogas boiler is the most-effective alternative heating system that can supply the energy in all stages of the vegetable oil processes. However, the energy substitution by a biogas boiler is limited by the biomass available from processing residues. Therefore, an electric boiler is required to deliver the residual energy supply to realise zero carbon emissions. The cost-effective decarbonisation options can abate cooperatively 38% and 40% of the total CO2 emissions for 2020 and 2030 respectively.

The global battle to reduce greenhouse gases changes many aspects of how we should think of our energy resources. For a large part, the industry is responsible for worldwide energy consumption. In the Netherlands, this share amounts to 41% of total energy production (Compendium voor de Leefomgeving, 2019). The industry is looking into different methods to lower their energy consumption to reduce carbon emissions. This is generally done by improved technologies, and by reusing existing energy flows. This study is focused on how industrial zones can optimally utilize their available waste heat (WH) in such a way that carbon emissions are minimized. By creating an optimal dispatch for waste heat in an industrial zone, insights into how the network should be operationalized are gained. It can also lead to industrial synergies due to cooperation between companies in the industrial zone. The research has been performed in four phases. (1) An orienting and descriptive phase, (2) a scenario creation and modeling phase, (3) verification, analyzing, and evaluation of the gained insights, and (4) the discussion and conclusion of the research. Sectors with both large scale demand and supply of WH are likely to be interested in participating in an integrated WH market. As a result, establishing large scale connections prevents large amounts of carbon emissions. Additionally, the financial incentive to invest in these solutions increases due to increasing carbon taxation. Key drivers for carbon reduction are the large scale connections, with a demand profile that exceeds the supply pattern by much. Determining the optimal dispatch of an industrial zone will offer a method to account for the volatility of supply and demand. It was expected that flexibility options in the WH market would be interesting, however with the current supply and demand patterns, WH can be utilized almost fully. That means that in the current system flexibility options do not add value. Several considerations remain for the implementation of integrated WH networks. Such as the power-to-heat technology that will likely increase the share of WH supply in industrial zones. Furthermore, a market mechanism has to be established when multiple parties (>2) get involved in the network to increase the feasibility of the deployment of the network.

In the Netherlands 2 million tons organic bio-waste is not fully sorted and ends up burned or landfilled. This process is unnecessarily harming the health of people, animals and our planet every year. With our waste quantities only increasing, this is an important topic on the European agenda.

The creation of user-driven, self-organising, and decentralized networks is supported to make better use of the remaining value in bio-waste. The behaviour of people in these networks is critical for its environmental impact and long-term survival. This research proposes a quantitative set-up to increase the bio-waste separation rate of small and medium-sized enterprises (SMEs). To research the potential environmental benefit in a symbiotic network for bio-waste separation the following research question was posed:

What is the influence of different groups of human behaviour and policy interventions in the development of bio-waste sortation networks for environmental benefit in symbiosis?

The Value-Belief-Norm theory is a social theory that is based on the altruistic intentions that drives people to behave in the interest of the planet, rather than their own benefit. The set-up offers a new approach to combine the Value-Belief-Norm theory with Industrial Symbiosis. This approach is applied in an agent-based simulation model and case study of the NDSM wharf Amsterdam.

The Dutch government has announced that 7 million houses and 1 million buildings in the service sector need to be provided by sustainable heat in 2050 (Klimaatberaad, 2018b). This is an enormous challenge considering that over 90 percent of the houses and service sector buildings in the Netherlands are currently heated by the local combustion of natural gas (Hans Ariëns, 2018). The objective of this policy measure is in line with the European climate targets to mitigate the effect of climate change (Klimaatberaad, 2018a). Moreover, it helps to facilitate the Dutch policy to stop the natural gas extraction from the largest natural gas field in the Netherlands (Klimaatberaad, 2018a). To achieve the enormous objective in 2050, the Dutch government is choosing a gradual approach and formulated a first clear policy target for 2030. The CO2 emissions of the buildings induced by space heating and domestic water heating need to be reduced by 3,4 Mt compared to the 1990 levels (Klimaatberaad, 2018a). Sustainability measures in the service sector should lead to a reduction of 1 Mt and phasing out natural gas in 1.5 million houses in combination with insulation measures should cover the remainder of 2 Mt (Klimaatberaad, 2018a). To adequately meet the demand for space heating and domestic water heating in 2030 and beyond, alternative heating technologies need to be integrated in the energy infrastructures to provide the desired energy demand to the buildings. Natural gas is currently distributed by means of an extensive gas infrastructure. There is a potential to use the existing infrastructure to distribute and store sustainable gasses such as biomethane or hydrogen (Dodds & McDowall, 2013). Alternative energy infrastructures can also replace the natural gas infrastructure in the satisfaction of the energy demand. Possibilities are the electricity infrastructure and a district heating infrastructure. Energy can also be produced locally from renewable energy sources as biomass, geothermal energy, solar energy, and wind energy

Water is an important resource in many industries in the world. Due to emerging regulatory framework, change in consumer’s perspective and increasing costs for water, industries are forced to move towards sustainable water use. Nowadays, improvements in the brewery industry are focussed on increasing the efficiency of the processes or treating the complete wastewater stream on site. Water network optimization models can effectively decrease the fresh water flowrate and wastewater flowrate production. The water pinch is in most cases used to optimize fresh water use and wastewater production in a single industry. This thesis is the first to use the water pinch in a circularity concept of a wider network with a brewery and external user. Circularity is in this thesis defined as the percentage of water from a brewery that can be reused by an external party, after it has been used inside the brewery. Two case breweries in Egypt were used to illustrate the water pinch method, El Obour brewery and Sharkia brewery. For both breweries an orange orchard of 87 ha with a water demand of 9836 m3/month was indicated as the external user. Per brewery, a list of water using processes that produce an effluent was determined. This list contains the CIP processes in the brew house and cellars and includes every process in the packaging department. In addition, the utility department processes cooling towers, boilers and CO2 washers were part of the water network of the breweries. The initial water network of El Obour consisted of 18 brewery processes and one external user, the orange orchard. Sharkia brewery had 17 brewery processes and the orange orchard. Actual process water flowrates were used as well as UBM process water flowrates. For El Obour brewery the initial fresh water flowrate was 9755 m3/month and 8466 m3/month for UBM process water flowrates. The Sharkia brewery initial fresh water flowrate was 15695 m3/month and 14961 m3/month for UBM process water flowrates. COD, Total N and Na+ were identified as key constituents. Per key constituent, a composite curve was constructed and a new, optimized water network designed. For the El Obour brewery the water pinch steps were described in detail to show how the composite curves and the networks could be constructed. The Sharkia brewery was used to validate the method. With the composite curve and pinch point determined, processes could be indicated as source or sink. The orange orchard was always considered as a sink and was satisfied first with every possible source. The water that was flowing from the brewery to the orange orchard identified the circularity potential of the network. COD was the reference constituent for both breweries as the most restrictions occurred in this network. With the COD limiting network as basis, integrated networks were designed that complied with every constituent restriction. The results showed that for El Obour the fresh water consumption decreased with 7% to 7909 m3/month and the wastewater production decreased with 22% to 6607 m3/month. Resulting in an initial circularity potential of the El Obour brewery of 11 – 13% (depending on the used process water flowrates based on actual measurements or UBM). The fresh water consumption and wastewater production savings for Sharkia were respectively 0% and 34%. The Sharkia brewery could be 28 – 34% circular on water in the initial phase without treatment of effluents (depending on the used process water flowrates based on actual measurements or UBM). 100% circularity could not be achieved due to too high Na+ and COD concentrations. Total N caused no restrictions for reuse. The results show that the water pinch can be used to determine to what extend the case breweries can be circular on water with an external user. The water pinch is not only an optimization tool but it can help industrial sites including a brewery to identify collaboration between different users of the local watershed. Hereby increasing the circularity on water.

This research has been performed with the goal to set up a model for the comparison of the environmental impact caused by the production of yachts. This model is created in such a way that it can be implemented in the YETI, Yacht Environmental Transparency Index, which is currently under development. The model that is created is based on a Life Cycle Assessment methodology named Fast Track LCA. This methodology consists of five steps which are further standardized to meet the requirements of the YETI. Choices are made for the functional unit, system boundaries, the quantification of materials, the assessment method, environmental database and LCA software. With a case study, the created model is validated as the results have realistic values. Some other design choices are applied on the case study to check the sensitivity of the model. The sensitivity was enough to show the effect of a different hull material and the use of batteries for the hotel load and peak shaving. It is concluded that the model can be used for the comparison of the environmental impact from production of different yachts. However, it should be noted that due to design choices for the model based on the requirement for comparison, the outcome itself is an underestimation of the environmental impact from yacht production.

At the United Nations Climate Change Conference held in Paris in 2015, ambitious goals for the worldwide CO2 emissions were set. To achieve these goals, a huge reduction in CO2 emissions must be realized. For the energy market, the current aim is to use renewable electricity instead of fossil fuels. However, there are multiple sectors where electricity is not a suitable form of energy, due to storage issues. For example, the chemical industry is heavily based on fossil fuels as a resource to synthesize chemicals. It is therefore useful to investigate the feasibility of renewable synthetic fuels.

The goal of this thesis is to design a process that converts the hydrocarbon fuel combustion products CO2 and H2O into a fuel that is a liquid at atmospheric conditions. Methanol is selected as the liquid fuel because of its basic molecule structure. It requires much more energy to obtain methanol from CO2 and H2O than it does from natural gas. The process is determined to be container-sized to become cost competitive through mass production. The technical feasibility of a mass produced, autonomous, renewable and container-sized methanol production plant is studied in this thesis. The whole process is divided into sub processes. H2O is obtained from desalination of seawater. The H2O is split into H2 and O2 using alkaline electrolysis. The CO2 is adsorbed from the air and recovered using pressure and temperature swing. The required energy is obtained using solar PV and solar thermal. The H2 and CO2 are finally converted to methanol in the methanol synthesis sub process. The intermittent character of solar energy yields a dynamically operated process. The methanol synthesis sub process is studied further because of the small scale and dynamic operation that are new concepts for this technology. The other sub processes are considered as black boxes with fixed in- and outputs. The steady state operation of the whole process is modeled using Aspen Plus™ and the distillation process is modelled in MATLAB®. Using the results from Aspen, pinch analysis is performed for optimal use of the available heat.

From the results of the model, it is found that an autonomous container-sized methanol production plant is technically feasible. 140 kg of methanol can be produced daily with a purity of at least 96.6 %, using a set-up of three 40 feet sea containers, two of which are dedicated to the capture of CO2. 288 kW of electrical power and 24 kW of heat is required for the operation. This is equal to a solar park with an area of 1663 m2 assuming an average 6 hours of solar irradiance. Using the LHV of methanol in the calculation, the total efficiency of the process is estimated at 45 %. The results from the MATLAB® model of the distillation cannot be validated because the used equation of state of REFPROP underestimates the concentration of methanol in each iteration, yielding an invalid mass balance. Fixing this issue results in an invalid energy balance. It is therefore concluded that REFPROP is not suitable for iterative calculations of distillation columns.