Abstract: In iets meer dan 30 jaar moeten we tot 50% meer eiwit produceren, terwijl onze conventionele lineaire voedselproductieketen reeds de grenzen van duurzaamheid overschrijdt. Microbieel eiwit (MP), de eiwitrijke biomassa van micro-organismen, werd onderzocht als nieuw voeder en voedselingrediënt in een circulaire eiwitproductieketen. MP-productie kan gebaseerd zijn op primaire grondstoffen om zo de inefficiënte stappen in de huidige eiwitproductie over te slaan, of de productie kan gebaseerd zijn op secundaire grondstoffen afkomstig van de verliezen in de conventionele productieketen (bijvoorbeeld afvalwater). Zowel indirecte als directe strategiën voor nutriëntenherwinning kunnen geïdentificeerd worden. Indirecte nutriëntenherwinning werd onderzocht door struviet toe te passen als fosfor- en stikstofbron voor MP-productie. Struviet, een herwinningsproduct in de afvalwaterzuivering, bleek een hoge zuiverheidsgraad te hebben waardoor het een uitstekende selectieve barrière vormt tussen afvalstroom en MP productie. Oplossingssnelheden en MP groei-experimenten toonden aan dat struviet gemakkelijk gedoseerd kan worden in functie van de microbiële nutriëntenbehoeftes, waarnaast problemen vermeden worden gerelateerd aan de turbiditeit van nevenstromen, wat de productie van fototrofe MP mogelijk maakt. Daarnaast werd ook directe nutriëntenherwinning onderzocht. Hierbij werden de voedingswaarde en veiligheid geanalyseerd van biomassa bestaande uit aerobe heterotrofe bacteriën (AHB) afkomstig van effluentzuivering van 25 bedrijven in de voedings- en drankensector. Verder werd ook de temporele variabiliteit in kaart gebracht. Er werd een veelbelovend eiwitgehalte geobserveerd waarvan de variabiliteit aanzienlijke was. Verder werd aangetoond dat het eiwitgehalte positief gecorreleerd was met stikstofbelasting en negatief met slibverblijftijd, wat een indicatie is dat de implementatie van een geoptimaliseerd productieproces, de biomassakwaliteit gevoelig kan verhogen. Bovendien was de veiligheid als veevoeder gegarandeerd op vlak van de meeste contaminanten. In het daarop volgende hoofdstuk werd de variabiliteit in voedingswaarde en veiligheid bestudeerd van commerciële fototrofe MP (de microalgen Chlorella en Spirulina), gekweekt op primaire grondstoffen. De waargenomen variabiliteit in voedingswaarde vereist verdere optimalisatie van het productieproces. Er werd ook waargenomen dat een hoog eiwitgehalte geen hoge totale voedingswaarde impliceert, omdat de verteerbaarheid en de eiwitkwaliteit nog steeds ongunstig kunnen zijn. Op basis van gemeten contaminanten geeft een veilige consumptiedosis aan dat microalgen perfect kunnen worden geconsumeerd als volwaardige eiwitbron in plaats van als supplement, hun huidige hoofdtoepassing. In een laatste experimenteel hoofdstuk werd onderzocht hoe de variabiliteit in biomassakwaliteit van microalgen kan worden gereduceerd en hoe een stabiele, hoogwaardige biomassaproductie kan worden bekomen. De invloed van oogsttijd, operationele modus en fotoperiode werd bepaald op de productiviteit van biomassa, eiwit en essentiële aminozuren en er werden optimale productieparameters geïdentificeerd. Samengevat is MP-productie op basis van indirecte en directe nutriëntenherwinning veelbelovend. Verdere technologische ontwikkelingen en het verhogen van bewustwording en sociale acceptatie, moeten een verdere introductie van MP in de voeder- en voedingsmarkt faciliteren. Hier kan MP een belangrijke oplossing vertegenwoordigen om de exponentieel groeiende wereldbevolking op een duurzame manier te voeden.

Abstract: In the present study depth profiles of light, oxygen, pH and photosynthetic performance in an artificial biofilm of the green alga Halochlorella rubescens in a porous substrate photobioreactor (PSBR) were recorded with microsensors. Biofilms were exposed to different light intensities (50-1,000mol photons m(-2) s(-1)) and CO2 levels (0.04-5% v/v in air). The distribution of photosynthetically active radiation showed almost identical trends for different surface irradiances, namely: a relatively fast drop to a depth of about 250 mu m, (to 5% of the incident), followed by a slower decrease. Light penetrated into the biofilm deeper than the Lambert-Beer Law predicted, which may be attributed to forward scattering of light, thus improving the overall light availability. Oxygen concentration profiles showed maxima at a depth between 50 and 150m, depending on the incident light intensity. A very fast gas exchange was observed at the biofilm surface. The highest oxygen concentration of 3.2mM was measured with 1,000mol photons m(-2) s(-1) and 5% supplementary CO2. Photosynthetic productivity increased with light intensity and/or CO2 concentration and was always highest at the biofilm surface; the stimulating effect of elevated CO2 concentration in the gas phase on photosynthesis was enhanced by higher light intensities. The dissolved inorganic carbon concentration profiles suggest that the availability of the dissolved free CO2 has the strongest impact on photosynthetic productivity. The results suggest that dark respiration could explain previously observed decrease in growth rate over cultivation time in this type of PSBR. Our results represent a basis for understanding the complex dynamics of environmental variables and metabolic processes in artificial phototrophic biofilms exposed to a gas phase and can be used to improve the design and operational parameters of PSBRs. Biotechnol. Bioeng. 2016;113: 1046-1055. (c) 2015 Wiley Periodicals, Inc.

Abstract: Complete removal of estrogens such as estrone (E1), estradiol (E2), estriol (E3) and ethinylestradiol (EE2) in wastewater treatment is essential since their release and accumulation in natural water bodies are giving rise to environment and health issues. To improve our understanding towards the estrogen bioremediation process, a mathematical model was proposed for describing estrogen removal by nitrifying activated sludge. Four pathways were involved in the developed model: i) biosorption by activated sludge flocs; ii) cometabolic biodegradation linked to ammonia oxidizing bacteria (AOB) growth; iii) non growth biodegradation by AOB; and iv) biodegradation by heterotrophic bacteria (HB). The degradation kinetics was implemented into activated sludge model (ASM) framework with consideration of interactions between substrate update and microorganism growth as well as endogenous respiration. The model was calibrated and validated by fitting model predictions against two sets of batch experimental data under different conditions. The model could satisfactorily capture all the dynamics of nitrogen, organic matters (COD), and estrogens. Modeling results suggest that for El, E2 and EE2, AOB-linked biodegradation is dominant over biodegradation by HB at all investigated COD dosing levels. However, for E3, the increase of COD dosage triggers a shift of dominant pathway from AOB biodegradation to HB biodegradation. Adsorption becomes the main contributor to estrogen removal at high biomass concentrations. (C) 2018 Elsevier Ltd. All rights reserved.

Abstract: Hydrogenotrophic denitrification is a novel and sustainable process for nitrogen removal, which utilizes hydrogen as electron donor, and carbon dioxide as carbon source. Recent studies have shown that nitrous oxide (N2O), a highly undesirable intermediate and potent greenhouse gas, can accumulate during this process. In this work, a new mathematical model is developed to describe nitrogen oxides dynamics, especially N2O, during hydrogenotrophic denitrification for the first time. The model describes electron competition among the four steps of hydrogenotrophic denitrification through decoupling hydrogen oxidation and nitrogen reduction processes using electron carriers, in contrast to the existing models that couple these two processes and also do not consider N2O accumulation. The developed model satisfactorily describes experimental data on nitrogen oxides dynamics obtained from two independent hydrogenotrophic denitrifying cultures under various hydrogen and nitrogen oxides supplying conditions, suggesting the validity and applicability of the model. The results indicated that N2O accumulation would not be intensified under hydrogen limiting conditions, due to the higher electron competition capacity of N2O reduction in comparison to nitrate and nitrite reduction during hydrogenotrophic denitrification. The model is expected to enhance our understanding of the process during hydrogenotrophic denitrification and the ability to predict N2O accumulation.

Abstract: Owing to their high surface-to-volume ratio, there has been an increasing research interest in mixed ionic electronic conducting (MIEC) capillary membranes for large-scale high temperature oxygen separation applications. They offer an energy-efficient solution for high temperature combustion processes in oxy-fuel and pre-combustion CO2 capture technologies used in fossil fuel power plants. In order to assess the effectiveness of these membranes in power plant applications, the impact of the geometry of Ba0.5Sr0.5Co0.8Fe0.2O3-delta (BSCF) capillaries on their performance in the three-end and four-end integration modes has been investigated and thoroughly discussed. The model's parameters were derived from four-end mode lab-scale experiments using gas-tight, macrovoid free and sulfur-free BSCF capillary membranes that were prepared by a phase-inversion spinning technique. The results of this modeling study revealed that in the four-end mode higher average oxygen fluxes and smaller total membrane areas can be obtained than in the three-end mode. This is due to the higher pO(2) gradient across the membrane wall. (C) 2012 Elsevier Ltd and Techna Group S.r.l. All rights reserved.

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: Antibiotics such as sulfamethoxazole (SFX) are environmentally hazardous after being released into the aquatic environment and challenges remain in the development of engineered prevention strategies. In this work, a mathematical model was developed to describe and evaluate cometabolic biotransformation of SFX and its transformation products (TPs) in an enriched ammonia oxidizing bacteria (AOB) culture. The growth-linked cometabolic biodegradation by AOB, non-growth transformation by AOB and nongrowth transformation by heterotrophs were considered in the model framework. The production of major TPs comprising 4-Nitro-SFX, Desamino-SFX and N-4-Acetyl-SFX was also specifically modelled. The validity of the model was demonstrated through testing against literature reported data from extensive batch tests, as well as from long-term experiments in a partial nitritation sequencing batch reactor (SBR) and in a combined SBR + membrane aerated biofilm reactor performing nitrification/denitrification. Modelling results revealed that the removal efficiency of SFX increased with the increase of influent ammonium concentration, whereas the influent organic matter, hydraulic retention time and solid retention time exerted a limited effect on SFX biodegradation with the removal efficiencies varying in a narrow range. The variation of influent SFX concentration had no impact on SFX removal efficiency. The established model framework enables interpretation of a range of experimental observations on SFX biodegradation and helps to identify the optimal conditions for efficient removal. (C) 2017 Elsevier Ltd. All rights reserved.

Abstract: BACKGROUND Laccase is an intensively researched enzyme for industrial use. Except for decolorisation measurements, HPLC analysis is the conventional method for monitoring the phenolic removal during laccase enzyme reaction. This paper reports an investigation of the continuous UV absorbance follow-up of the laccase reaction with steam pretreated poplar hydrolysate. RESULTS Vanillin was used as a model substrate and lignocellulose xylose rich fraction (XRF) as a biologically complex substrate for laccase detoxification. The reaction was followed by HPLC-UV as well as by UV spectrometric measurements. Results suggest that the reaction can be successfully monitored by measuring the change of UV absorbance at 280 nm, without previous compound separation. In case of XRF experiments the spectrophotometric follow-up is especially useful, as HPLC analysis takes a long time and provides less information than in case of single substrates. The method seems to be suitable for optimization and process control. CONCLUSION The obtained results can help to construct a fast, easy and straightforward monitoring system for laccase-phenolic substrate reactions.

Abstract: The development of porous metal materials with pore geometries and sizes at the nanoscale offers promising opportunities for the development of smart responsive interfaces for separation and catalytic applications and as building blocks for complex composite materials. Dealloying is an innovative technique based on selective removal of a sacrificial metal from a metal alloy to engineer surface textures and pores across significant thicknesses. Dealloyed structures may be processed over large scales and for a range of source alloys, offering unprecedented manufacturing opportunities. This review presents the operations and challenges of dealloying routes and discusses avenues for process optimizations and improvements, aiming at the development of scalable nanoporous materials. The potential of dealloyed materials for catalytic and sensing applications is expanded and benchmarked against reference materials. Future prospects and applications of dealloyed materials toward surface reactivity control and pore architecture development are highlighted.

Abstract: A new hydrometallurgical method was investigated for selective leaching of chromium from stainless steel slag (SS slag) consisting of temperature controlled extraction with NaOH in the presence of NaOCl, followed by water leaching. After parameter optimization of the NaOCl-NaOH extraction step, a selective Cr leaching of 68% was reached, while dissolution of matrix materials was low (Al 0.3%, Ca 2.0%, Si 0.4%). The optimum conditions for the investigated system are: 105 degrees C, 6 h, SS slag particle size <63 mu m, mass ratio of NaOH to SS slag 0.13, and 3.3 mmol NaOCl to 1 g SS slag. The described oxidative alkaline leaching process by hypochlorite enables selective recovery of Cr at a significantly lower temperature and required amount of alkaline agent than molten salt or alkaline roasting processes. BaCrO4 was precipitated to purify and concentrate Cr from the leachate in which also minor amounts of Mn and V were present. This method allowed for a 99.9% Cr recovery rate. The obtained leaching residue shows no alterations of the SS slag's mineralogy with respect to untreated material. Therefore, a known carbonation treatment of the slag can be applied to prepare novel construction materials with a lowered Cr content. (C) 2016 Elsevier B.V. All rights reserved.

Abstract: Long-term human Space missions depend on regenerative life support systems (RLSS) to produce food, water and oxygen from waste and metabolic products. Microbial biotechnology is efficient for nitrogen conversion, with nitrate or nitrogen gas as desirable products. A prerequisite to bioreactor operation in Space is the feasibility to reactivate cells exposed to microgravity and radiation. In this study, microorganisms capable of essential nitrogen cycle conversions were sent on a 44-days FOTON-M4 flight to Low Earth Orbit (LEO) and exposed to 10(-3)-10(-4) g (gravitational constant) and 687 +/- 170 mu Gy (Gray) d(-1) (20 +/- 4 degrees C), about the double of the radiation prevailing in the International Space Station (ISS). After return to Earth, axenic cultures, defined and reactor communities of ureolytic bacteria, ammonia oxidizing archaea and bacteria, nitrite oxidizing bacteria, denitrifiers and anammox bacteria could all be reactivated. Space exposure generally yielded similar or even higher nitrogen conversion rates as terrestrial preservation at a similar temperature, while terrestrial storage at 4 degrees C mostly resulted in the highest rates. Refrigerated Space exposure is proposed as a strategy to maximize the reactivation potential. For the first time, the combined potential of ureolysis, nitritation, nitratation, denitrification (nitrate reducing activity) and anammox is demonstrated as key enabler for resource recovery in human Space exploration.

Abstract: Combining partial nitrification, granular activated carbon (GAC) filtration, and distillation is a well-studied approach to convert urine into a fertilizer. To evaluate the environmental sustainability of a technology, the operational carbon footprint and therefore nitrous oxide (N2O) emissions should be known, but N2O emissions from urine nitrification have not been assessed yet. Therefore, N2O emissions of a decentralized urine nitrification reactor were monitored for 1 month. During nitrification, 0.4-1.2% of the total nitrogen load was emitted as N2O-N with an average N2O emission factor (EFN2O) of 0.7%. Additional N2O was produced during anoxic storage between nitrification and GAC filtration with an estimated EFN2O of 0.8%, resulting in an EFN2O of 1.5% for the treatment chain. N2O emissions during nitrification can be mitigated by 60% by avoiding low dissolved oxygen or anoxic conditions and nitrite concentrations above 5 mg-N L-1. Minimizing the hydraulic retention time between nitrification and GAC filtration can reduce N2O formation during intermediate storage by 100%. Overall, the N2O emissions accounted for 45% of the operational carbon footprint of 14 kg-CO2,equiv kg-N-1 for urine fertilizer production. Using electricity from renewable sources and applying the proposed N2O mitigation strategies could potentially lower the carbon footprint by 85%.