Abstract: Adequate removal of pollutants from sewage is important to protect the environment and public health. Today, sewage treatment plants are operational in many parts of the world, and although the used technologies are effective in removing pollutants from wastewater, they are energy- and resource-intensive. Reshaping sewage treatment into a two-stage system, with separated organic carbon and nitrogen removal, facilitates the transformation towards energy-positive sewage treatment. This thesis will focus on resource-efficient nitrogen removal from sewage via partial nitritation/anammox (PN/A), with reduced organic carbon and oxygen consumption compared to conventional techniques. PN/A relies on the teamwork between two microbial groups to convert ammonium into nitrogen gas. Several other groups of microbes however can proliferate in the sludge, competing for substrate with the key players, lowering the nitrogen removal efficiency and increasing the energy demand. To obtain the desired microbial community, control tools should be applied to selectively promote the desired microbes while suppressing the unwanted competitors. In this thesis, multiple control tools were studied to establish a workable framework for successful implementation of PN/A in the main stream of a sewage treatment plant. These tools can be divided into three categories: i) kinetic tools, regulating substrate availability (e.g., oxygen availability control and residual ammonium concentration), ii) physical tools, revolving around sludge retention and selection (e.g., sludge age control and sludge aggregation form), and iii) chemical tools, exposing the sludge to stress conditions for which the unwanted microbes are vulnerable (e.g., sludge treatments with a single stressor such as free ammonia). The first research chapter focussed on oxygen availability control and single-stressor sludge treatments. The following two chapters covered the development of a novel multi-stressor concept combining substrate starvation and exposure to sulphide and free ammonia. In the final research chapter, the previously obtained knowledge was combined into a demonstration study on pilot-scale. The combination of these control tools was found effective in achieving nitrogen removal via PN/A, both on lab- and pilot-scale. Consequently, the obtained results in this thesis can catalyse the implementation of mainstream PN/A by providing a toolbox with multiple control tools and clever reactor design, thus advancing the concept of energy neutrality and resource efficiency in sewage treatment plants.

Abstract: Photocatalysis has been labeled for decades as a promising technique for air purification. The principle seems straightforward and requires a photocatalyst that is immobilized on a substrate, and one or more UV sources to activate the photocatalyst. No waste products are produced, the reactions occur in mild conditions and the supplies are relatively cheap. Yet it seems that the commercialization of photocatalytic systems does not break through on the global market. The aim of this thesis is to identify and tackle the bottlenecks that impede commercialization from an application-oriented approach. The problem of indoor air pollution is enhanced by the fact that people spend more and more time indoors and that ventilation is kept to a minimum as an energy-saving measure. This inevitably leads to an accumulation of volatile organic compounds (VOCs) that are emitted by e.g. building materials, paint and furniture. Human exposure to VOCs is directly related to the sick building syndrome leading to complaints such as headache, fatigue, dizziness and lack of concentration. In addition, exposure to VOCs is related to serious long-term health effects such as cancer or respiratory diseases. Therefore, significant research efforts are focused on advanced indoor air purification methods. Integration or retrofitting of a photocatalytic (PCO) air purifying unit into heating, ventilation and air conditioning (HVAC) equipment has been chosen as an interesting approach. As a starting point of this thesis, the operational conditions of a ventilation system were mapped. These systems are characterized by high flow rates and the necessity of minimal pressure losses. Pressure losses increase the energy demand and can lead to failure of the ventilation fan and thereby undermine the proper functioning of the ventilation system. A suitable substrate must allow the contaminated air to pass through with a minimal pressure drop, allow sufficient contact time between VOC and photocatalyst, have a large surface area available for coating with excellent adhesion, and be transparent to UV light. Therefore, the permeability and the available exposed surface were selected as main selection criteria. After a thorough quantitative analysis of potential substrates, borosilicate glass tubes were selected. Glass tubes can easily be stacked to constitute a transparent monolithic multi-tube reactor, with their length parallel to the air flow in order to minimize the pressure drop. Moreover, borosilicate glass is relatively inexpensive and has excellent UV-A light transmitting properties. Based on a literature study, a sol-gel coating procedure was selected that is extremely suitable for coating glass substrates. The next step was to optimize the amount of P25 (commercial titanium dioxide) in the photocatalytic sol-gel coating for its application. More P25 in the sol-gel coating results in a higher adsorption capacity and consequently a higher photocatalytic activity, but greatly reduces the transparency of the coating. After an in-depth study, the concentration of 10 g L-1 P25 was selected as the most feasible for multi-tube reactors. Since the operation of photocatalytic reactors is based on a complex interaction of physical and chemical processes, mathematical models were developed, supported by experimental data, that include all these phenomena as a tool for reactor design and optimization. By making use of such models, time-consuming and expensive experimental research can be minimized. However, the experimental validation of models is of utmost importance to prove its reliability and accuracy. Intrinsic kinetic parameters provide the fundamentals for these models as they describe the photocatalytic reaction rate, independent of fluid dynamics, reactor geometry and radiation field. In this work they were estimated by means of a Computational Fluid Dynamics (CFD) study, based on FTIR (Fourier-transform infrared spectroscopy) experiments with a lab scale multi-tube reactor. The kinetic parameters were validated by an alternative analytic approach, emphasizing the accuracy and reliability of the simulations. Finally, the aforementioned CFD approach, based on the simultaneously modelling of airflow, mass transfer, UV light irradiation and photocatalytic reactions, was used to obtain insights for the light source configuration in upscaled multi-tube reactors. After taking all these insights and some practical implications into account, a final upscaled multi-tube reactor design was proposed and converted into a first built prototype. Subsequently, it was evaluated according the CEN-EN-16486-1 standard for VOC removal by the external scientific research center ‘CERTECH’. The scientific results, regarding the mineralization of the VOCs and photocatalytic efficiency of the reactor, demonstrated the feasibility for indoor air purification by the upscaled multi-tube reactor and the possible implementation in ventilation systems.

Abstract: Today’s society is increasingly challenged by a range of urgent environmental problems. Air pollution is one of these pressing topics. This thesis will mainly focus on the degradation of volatile organic compounds (VOCs) and particulate matter (PM) – more specifically soot. A second globally urging topic is the quest for sustainable energy production. To simultaneously target both environmental problems, a photoelectrochemical (PEC) cell will be studied in this thesis, combining air purification and sustainable energy production in a single device. Photocatalysis is used at the anode of the PEC cell to drive the air purification process, while the energy contained in the degraded compounds is (partially) recovered at the cathode, either as H2 gas or electricity. The first two experimental chapters focus on the proof of concept of such an unbiased all-gas phase PEC cell targeting VOC degradation, using both TiO2- and WO3-based photocatalysts. In the two following experimental chapters the photocatalytic soot oxidation capacity of these TiO2- and WO3-based photocatalysts was studied. In the final experimental chapter the previously obtained results were combined, striving towards an efficient, sunlight-driven and soot-degrading waste gas-to-energy PEC cell.

Abstract: ​Food production is a cornerstone in contemporary industrial societies. Its production requires land, water and enormous amounts of fertilizers. These precious fertilizers enter the linear food chain and suffer from a cascade of inefficiencies, resulting in detrimental effects to the environment. A radical transforming of the current food production chain is, therefore, essential to guarantee a sustainable future for humanity. ​This thesis has studied the production of microbial protein (i.e. single-cell protein), which is the use of microorganisms such as yeast, fungi, algae and bacteria as protein ingredient for animal feed. The type of microorganisms targeted in this thesis were purple non-sulfur bacteria (PNSB). These bacteria are an extremely heterogenic group that contain photosynthetic pigments and are able to perform anoxygenic photosynthesis. The core focus of the thesis was technology development for the production of PNSB as a source of microbial protein on wastewater and fresh fertilizers. In the final stage of this research, it was the objective to explore the potential of PNSB as a nutritious feed ingredient for shrimp. ​Overall, this work has provided the building blocks to transform the conventional food production chain. The findings show that PNSB production and biomass valorization is within reach. Further pilot implementation and cost reduction will facilitate the introduction of PNSB production in future’s wastewater treatment plants and the valorization of the biomass as nutritious animal feed ingredient.​

Abstract: Exposure to air pollution, such as particulate matter (PM), causes adverse health effects, particularly to the respiratory tract and cardiovascular system. PM is the collective name for all kinds of particles ranging from small particles and liquid droplets, which contain organic compounds, acids and metals, to soil or dust particles. One distinguishes PM10, PM2.5 and PM0.1, which have aerodynamic particle sizes smaller than 10, 2.5 and 0.1 µm, respectively. It is mainly the latter that is the most harmful, as PM0.1 penetrates deep into the respiratory system and carries relatively more toxic substances than the other PM fractions. Over a 15-year period, PM concentrations in European member states have fallen by about 30%. Nevertheless, the World Health Organisation (WHO) air quality guidelines, which became stricter in 2021, are exceeded in most places around the world. Particularly in cities, excessive levels of PM are measured and it is here that PM mitigation should be investigated. For this, the implementation of urban green infrastructure, including trees, shrubs, green roofs and green walls, is being looked at. Plants hinder airflow and remove PM from the air by deposition on their leaves and branches. This process is known as dry deposition. Plants can capture PM very efficiently, due to their complex structure of leaves and branches. Green walls offer significant advantages over other types of urban green infrastructure because they can grow on the huge available wall area and, because they do not hinder air circulation, as we sometimes see with trees. Green walls are believed to have a much greater, untapped potential to reduce PM pollution. However, a literature review showed that we do not know the quantitative impact of green walls and lack the tools and/or general methodology to do so. The objective of this thesis is therefore to develop a method for assessing PM removal by green walls, based on predictive models and based on relevant parameters that are experimentally determined. Computational fluid dynamics (CFD) is a numerical method to simulate airflow in complex environments such as cities. These models can also simulate the vegetation-wind interaction in detail and are interesting tools to assess the effect of green walls on PM concentrations in real environments. It is important to first study the aerodynamic effect of green walls and parameterise it correctly in CFD models. Plants decrease the wind speed and create turbulence through a combination of viscous and form drag, which are determined by the permeability (K) and drag coefficient (Cd), respectively. Wind tunnel experiments were conducted with three commonly found climbers (Hedera helix, Parthenocissus tricuspidata and Parthenocissus quinquefolia) and the variation of leaf area density was investigated for two of them. It was observed that the air resistance depended on plant species, leaf area density and wind speed. The difference between the plant species was assigned to the functional leaf size (FLS), the ratio of the largest circle within the boundaries of the leaf to the total leaf area. FLS is likely associated with other morphological characteristics of plants that, when considered collectively, provide a more comprehensive representation of leaf complexity. The pressure and velocity measurements obtained were used to optimise the permeability and drag coefficient in a CFD model. At wind speeds below 0.6 m s-1, the resistance was mainly determined by viscous drag and a larger leaf size resulted in a higher viscous drag. At wind speeds above 1.5 m s-1, form drag was dominant and the parameterised Cd decreased with increasing wind speed due to the sheltering effect of successive plant elements. The leaf area density had a significant effect on K and Cd and, is therefore an important plant parameters in CFD models. The main conclusion here is that the common practice of using a constant Cd to model the influence of plants on the air flow leads to deviations from reality. Wind tunnels are highly suitable to study the impact of green walls on PM concentration under controlled environmental conditions. For this purpose, a new wind tunnel setup was built and great attention was paid to obtaining a uniform air flow. Thus, based on CFD models, appropriate flow controllers were chosen, consisting of honeycombs and screens with different mesh sizes. New PM generation devices and measuring equipment were installed and set up appropriately. Devices were available for generating and measuring ultrafine dust (<0.1 µm, i.e. PM0.1) and fine dust (<0.3 µm, i.e. PM0.3) consisting of soot particles, and, on the other hand, fine dust with particle sizes smaller than 2.5 (PM2.5) and 10 µm (PM10) consisting of 'Arizona fine test dust'. With the new wind tunnel setup, it was possible to measure the influence of Hedera helix (common ivy), grown in a planter against a climbing aid, on the PM concentration and this was expressed by a collection efficiency, i.e. the difference in concentration in front and behind the plants normalised for the incoming concentration. The collection efficiency of H. helix depended on the particle size of the PM and wind speed. The collection efficiency decreased when the particle size increased from 0.02 to 0.2 µm and increased again for particle sizes above 0.3 µm. The collection efficiency also increased with increasing wind speed, especially for particle sizes > 0.03 µm. On the other hand, relative humidity and the type of PM (soot or dust) did not significantly affect the collection efficiency. The main objective of this study was to obtain an optimised size-resolved deposition model. Dry deposition occurs through several mechanisms, in particular gravity, diffusion, impaction and interception, and the subsequent resuspension of deposited PM back to the environment. The modelling of these mechanisms was described by \citet{Zhang2001} and \citet{Petroff2010}. The data obtained from the wind tunnel experiments allowed validating these deposition models. It was for the first time that deposition of real PM on green walls was studied. The different PM deposition mechanisms were found to be strongly dependent on particle size and wind speed. The models of \citet{Zhang2001} and \citet{Petroff2010} each matched PM concentration measurements for only certain particle sizes. Therefore, a combination of the two models was investigated and the root mean square error was lower by on average 3.5% (PM < 0.03 µm) and 46% (PM > 0.03 µm) compared to the original models at wind speeds greater than 1.5 m s-1. For wind speeds less than 1.5 m s-1, the optimised model did not differ from the original models. The optimised model was able to meet the imposed criteria for air quality models, where a correct model exhibits low deviation from measurements ('normalised mean square error' < 1.5), low bias ('fractional bias' between -0.3 and 0.3) and high R2. In comparison, the R$2$ of the optimised model was 0.57, while that of Zhang et al. (2001) and Petroff et al. (2010) was 0.23 and 0.31, respectively. The optimised model was however characterised by a high scatter, with the fraction of modeled results located within a factor of two of the measurements being lower than 50. A model study with a green façade oriented parallel to the incoming airflow showed that deposition by interception and impaction reduced remarkably, but that the orientation had no effect on deposition by Brownian diffusion. A promising green wall form for PM mitigation is the living wall system (LWS). LWS consist of supporting structures with substrate to grow plants in and can be planted with a variety of plant species. This allows to select plant species with optimal characteristics to achieve PM deposition. These characteristics refer to the macro- and microstructure of the leaves, and research has been conducted mainly on these. On the other hand, the influence of the supporting structure and substrate on PM concentrations has rarely been studied. With the new wind tunnel setup, LWS from different manufacturers were tested for their ability to capture PM. The setups were subjected for three hours to an air flow with a low PM concentration (resuspension phase) and then for three hours to an air flow to which additional PM was added (deposition phase). Some setups were able to decrease the PM concentration during both phases, while others just caused the concentration to increase. Some systems were able to reduce particulate matter concentration during both phases, namely LWS consisting of planters (-2% and -4% for PM0.1 and PM2.5, respectively) and textile cloths (-23% and -5% for PM0.1 and PM2.5, respectively). While other systems actually resulted in an increase in concentration especially LWS existing textile fabrics consisting of geotextiles (+11% for both PM fractions) and with moss as substrate (+2% and +5% for PM0.1 and PM2.5, respectively). This highlights the importance of careful selection of suspension systems to reduce particulate matter concentrations. Further research is therefore needed on the materials used in these systems in relation to their particulate content, as well as on plant development in these systems. In addition to air measurements, measurements were taken of the amount of PM deposited on the leaves and suspension system of LWS. This allowed the difference in PM resuspension and deposition between plant species to be investigated. The amount of deposited particulate matter was determined based on 'saturation isothermal remanent magnetisation' (SIRM), a measure of magnetisable particulate matter. This was possible because the added 'Arizona fine test dust' contained iron oxide. However, no significant difference was observed between the SIRM values measured before the wind tunnel experiment, after resuspension and after deposition. This suggested that the iron oxide content in the Arizona fine test dust was too low to measure a significant difference in the SIRM values on leaves after three hours. The plant species did give rise to different SIRM values ranging between 5 and 260 µ A. In particular, SIRM values above 26 µ A were observed for the plant species that were grouped due to their significantly higher accumulation of PM. 'Specific leaf area' (SLA), specifically the ratio of the one-sided 'fresh' leaf area to its dry mass, was the significant leaf characteristic. SLA correlated with leaf complexity. In particular, plant species with elongated leaves were characterized by low SLA, high FLS and high complexity and showed significantly higher SIRM values. Finally, the optimised size-resolved deposition model was also tested in an urban model to get an idea of the impact of a green wall on PM concentrations in a so-called 'street canyon'. These are narrow streets with high buildings on both sides, making air pollution more persistent. To this end, an ideal scenario was tested in which a green wall was introduced along both sides of the street over a length of about 270 m. The model result showed a decrease in PM2.5 and PM10 of 46 ± 12% and 52 ± 14%. This result is of course for a very optimal scenario where the green wall covers the entire building façades. Since this is not feasible in reality, other ways of promoting contact between green walls and polluted air can be explored. The insights obtained illustrate that the use of climbing plants can be a cost-effective and environmentally friendly solution to reduce PM concentrations. Moreover, the findings showed that models can be used to investigate the impact of green walls on PM levels. These findings fit within the broader context of designing healthy and sustainable urban environments and developing innovative solutions based on solid scientific knowledge.

Abstract: 200 years ago, humanity started the industrial revolution by discovering fossil fuels, which lead to unprecedented technological advancements. However it has become alarmingly clear that the major environmental concerns associated with fossil fuels require a short-term transition from a carbon-based energy economy to a sustainable one based on green electricity. A key step concerning this transition exists in developing electricity-driven alternatives for chemical processes that rely on fossil fuels as a raw material. A technology that is gaining increasing interest to achieve this, is plasma technology. Using plasmas to induce chemical reactions by selectively heating electrons in a gas has already delivered promising results for gas conversion applications like CO2 conversion and N2 fixation, but plasma reactors still require optimization to be considered industrially competitive to existing fossil fuel-based processes and emerging other electricity-based technologies. In this thesis I develop computational models to describe plasma reactors and identify key mechanisms in three different plasma reactors for three different gas conversion applications, i.e. N2 fixation, combined CO2-CH4 conversion and CO2 splitting. I first developed models to describe a new rotating gliding arc (GA) reactor operating in two arc modes, which, as revealed by my model, are characterized by distinct plasma chemistry pathways. Subsequently, my colleague and I study the quenching effect of an effusion nozzle to this rotating GA reactor, reaching the best results to date for N2 fixation into NOx at atmospheric pressure, i.e., NOx concentrations up to 5.9%, at an energy cost down to 2.1 MJ/mol. Afterwards, I investigate the possible improvement of N2 admixtures in plasma-based CO2 and CH4 conversion, as significant amounts of N2 are often found in industrial CO2 waste streams, and gas separations are financially costly. Through combining my models with the experiment from a fellow PhD student, we reveal that moderate amounts of N2 (i.e. around 20%) increase both the electron density and the gas temperature to yield an overall energy cost reduction of 21%. Finally, I model quenching nozzles for plasma-based CO2 conversion in a microwave reactor, to explain the enhancements in CO2 conversion that were demonstrated in experiments. Through computational modelling I reveal that the nozzle introduces fast gas quenching resulting in the suppression of recombination reactions, which have more impact at low flow rates, where recombination is the most limiting factor in the conversion process.

Abstract: The plasma-based dry reforming in a dielectric barrier discharge (DBD) reactor is important to achieve sustainable goals, but many challenges remain. For example, the conversion and energy yield of DBD reactors are relatively low, and the catalysts or packing materials used in existing studies cannot improve them, possibly due to the unsuitable properties and structures of catalysts or packing materials for plasma processes. In order to study the effect of catalyst structure on plasma-based dry reforming, a controllable synthesis of the catalyst supports or templates was explored. In Chapter 2, an initially immiscible synthesis method was proposed to synthesize uniform silica spheres, which can replace the organic solvent-based Stöber method to successfully synthesize silica particles with the same size ranges as the original Stöber process without addition of organic solvents. Using the silica spheres as templates, 3D porous Cu and CuO catalysts with different pore sizes were synthesized in Chapter 3 to study the effect of catalyst pore size on the plasma-catalytic dry reforming. In most cases, the smaller the pore size, the higher the conversion of CH4 and CO2 due to the reaction of radicals and ions formed in the plasma. An exception are the samples synthesized from 1 μm silica, which show better performance due to the electric field enhancement for pore sizes close to the Debye length. Besides the pore size, the particle diameter of the catalyst or packing is also one of the important factors affecting the interaction between plasma and catalyst. In Chapter 4, SiO2 spheres (with or without supported metal) were used to study the effect of different support particle sizes on plasma-based dry reforming. We found that a uniform SiO2 packing improves the conversion of plasma-based dry reforming. The conversion of plasma-based dry reforming first increases and then decreases with increasing particle size, due to the balance between the promoting and hindering effect of the particle filling on the plasma discharge. Chapter 5 is to improve the design of the DBD reactor itself, in order to try to increase its low energy yield. Some stainless steel rings were put over the inner electrode rod of the DBD reactor. The presence of rings increases the local electric field, the displaced charges and the discharge fraction, and also makes the discharge more stable and with more uniform intensity. The placement of the rings improves the performance of the reactor at 30 W supplied power.