Abstract: Inelastic excitation as exploited in Electron Energy Loss Spectroscopy (EELS) contains a rich source of information that is revealed in the scattering process. To accurately quantify core-loss EELS, it is common practice to fit the observed spectrum with scattering cross-sections calculated using experimental parameters and a Generalized Oscillator Strength (GOS) database [1].   The GOS is computed using Fermi’s Golden Rule and orbitals of bound and excited states. Previously, the GOS was based on Hartree-Fock solutions [2], but more recently Density Functional Theory (DFT) has been used [3]. In this work, we have chosen to use the Dirac equation to incorporate relativistic effects and have performed calculations using Flexible Atomic Code (FAC) [4]. This repository contains a tabulated GOS database based on Dirac solutions for computing double differential cross-sections under experimental conditions.   We hope the Dirac-based GOS database can benefit the EELS community for both academic use and industry integration.   Database Details: – Covers all elements (Z: 1-108) and all edges – Large energy range: 0.01 – 4000 eV – Large momentum range: 0.05 -50 Å-1 – Fine log sampling: 128 points for energy and 256 points for momentum – Data format: GOSH [3]   Calculation Details: – Single atoms only; solid-state effects are not considered – Unoccupied states before continuum states of ionization are not considered; no fine structure – Plane Wave Born Approximation – Frozen Core Approximation is employed; electrostatic potential remains unchanged for orthogonal states when – core-shell electron is excited – Self-consistent Dirac–Fock–Slater iteration is used for Dirac calculations; Local Density Approximation is assumed for electron exchange interactions; continuum states are normalized against asymptotic form at large distances – Both large and small component contributions of Dirac solutions are included in GOS – Final state contributions are included until the contribution of the previous three states falls below 0.1%. A convergence log is provided for reference.   Version 1.1 release note: – Update to be consistent with GOSH data format [3], all the edges are now within a single hdf5 file. A notable change in particular, the sampling in momentum is in 1/m, instead of previously in 1/Å. Great thanks to Gulio Guzzinati for his suggestions and sending conversion script.  Version 1.2 release note: – Add “File Type / File version” information [1] Verbeeck, J., and S. Van Aert. Ultramicroscopy 101.2-4 (2004): 207-224. [2] Leapman, R. D., P. Rez, and D. F. Mayers. The Journal of Chemical Physics 72.2 (1980): 1232-1243. [3] Segger, L, Guzzinati, G, & Kohl, H. Zenodo (2023). doi:10.5281/zenodo.7645765 [4] Gu, M. F. Canadian Journal of Physics 86(5) (2008): 675-689.

Abstract: Supplementary information for the article “In-situ Plasma Studies using a Direct Current Microplasma in a Scanning Electron Microscope” containing the videos of in-situ SEM imaging (mp4 files), raw data/images, and Jupyter notebooks (ipynb files) for data treatment and plots. Link to the preprint: https://doi.org/10.48550/arXiv.2308.15123 Explanation of the data files can be found in the Information.pdf file. The Videos folder contains the in-situ SEM image series mentioned in the paper. If there are any questions/bugs, feel free to contact me at lukas.grunewaldatuantwerpen.be

Abstract: As natural gas prices proved to be very volatile, sustainable alternatives are highly needed. Water-derived H2 was revealed as a promising substitute, allowing to produce a green energy carrier with a minimum of harmful emissions. Direct splitting of earth-abundant seawater provides an eco-friendly route for the production of clean H2, but is hampered by selectivity and stability issues due to the presence of salts.Photocatalytic seawater splitting is particularly promising for this purpose, as it seems less affected by adversary seawater effects and might rely on free and renewable solar power. Unfortunately, the benchmark photocatalyst, TiO2, still suffers from its low solar light activity. It is only actived upon illumination with energetic ultraviolet light (<5% of the sunlight). In order to broaden the activity window to the visible light, the concept of the 'plasmonic rainbow' was explored. Here, TiO2 is modified with various gold-silver composites that possess the unique optical phenomenon of Surface Plasmon Resonance (SPR). This phenomenon enables the absorption of light at very specific wavelengths, depending on the metal type, size, shape and dielectric environment. The light energy might then be converted into hot carriers, strong local electromagnetic fields and/or heat. By combining multiple composites with various sizes and compositions, a broadband absorption could be obtained, resulting in significantly enhanced activity in photocatalytic model reactions under simulated sunlight. The major disadvantage of these plasmonic nanoparticles is their tendency to oxidize and deactivate. To overcome this, polymer shell stabilization strategies were found to be effective to protect the metal cores. Both conductive and non-conductive polymers were studied. For the former, a mix-and-wait strategy generating polyaniline shells of 2-5 nm was used, whille the latter was based on a Layer-by-Layer approach, allowing (sub) nanometer thickness control. For the actual H2 production experiments, the plasmonic loading was optimized in a pure water:methanol scavenger (7:1) mixture and initially the stabilization strategies proofed to be effective for simulated seawater (0.5M NaCl), even after 2 years. However, in real seawater, the activity decreased drastically due to aggregation of the photocatalyst in the presence of multivalent cations. Finally, facile immobilization strategies using 3D printing showed to be able to yield stable, solar active photocatalyst for real seawater splitting.

Abstract: During the past decades, metallic nanoparticles (NPs) have attracted great attention in materials science due to their specific optical properties based on surface plasmon resonances. Because of these phenomena, plasmonic NPs (or nanoplasmonics) are very promising for application in biosensing, photocatalysts, medicine, data storage, solar energy conversion, etc. Currently, colloidal synthesis techniques enable scientists to routinely produce mono and bimetallic NPs of various shapes, sizes, composition, and elemental distribution, with superior properties for plasmonic applications. Two primary directions for further advancing nanoplasmonic-based technologies include synthesizing novel morphologies, such as highly asymmetric chiral NPs, and gaining deeper insights into the factors affecting the stability of produced nanoplasmonics. With the increasing complexity of nanoplasmonics morphologies and higher stability requirements, there is a pressing need for thorough investigations into their 3D structures and their evolution under different conditions, with high resolution. Electron tomography (ET) emerges as an ideal tool to retrieve shape and element-sensitive information about individual nanoparticles in 3D, achieving resolutions down to the atomic level. Moreover, ET techniques can be combined with in situ holders, enabling detailed studies of processes mimicking real applications of nanoplasmonic-based devices. The first part of this thesis will focus on detailed studies of chiral Au NPs, promising for spectroscopy techniques based on the differential absorption of left- and right-handed circularly polarized light. Specifically, I will discuss the primary strategies for wet-colloidal growth of the various types of intrinsically chiral Au NPs. Advanced ET methods will be demonstrated as powerful tools for characterizing the final helical morphologies of the produced Au NPs and for studying the chiral growth mechanisms by examining intermediate structures obtained during chiral growth. The second part will focus on the heat-induced stability of various Au@Ag core-shell NPs. Operating in real conditions, such as elevated temperatures, may cause particle reshaping and redistribution of metals between the core and shell, gradually altering nanoplasmonics properties. Hence, a thorough understanding of the influence of size, shape, and defects on these processes is crucial for further developments. Recently developed techniques, combining fast ET with in-situ heating holders, have allowed me to evaluate the influence of various parameters (size, shape, defect structure) on heat-induced elemental redistribution in Au@Ag core-shell nanoparticles qualitatively and quantitatively. Additionally, I will discuss the prospects of high-resolution ET for visualizing the diffusion of individual atoms within complex nanostructures.

Abstract: Plasma is considered one of the promising technologies to solve greenhouse gas problems, as it can activate CO2 and CH4 at relatively low temperatures. Among the various types of plasmas, the gliding arc plasmatron (GAP) is promising, as it has a high level of non-equilibrium and high electron density. Nevertheless, the conversion of CO2 and CH4 in the GAP reactor is limited. Therefore, combining the GAP reactor with catalysts and making use of the heat produced by the plasma to provide thermal energy to the catalyst, forming a post-plasma catalytic (PPC) system, is hypothesized to improve its performance. Therefore, in this PhD research, we investigate important aspects of the PPC concept towards the use of the heat produced by GAP plasma to heat the plasma bed, without additional energy input. Aiming at this, based on a literature study (chapter 1), Ni-loaded layered double hydroxide (LDH) derived catalyst with good thermal catalytic DRM performance were chosen as the catalyst material. Before applying the LDH as a support material, the rehydration property of calcined LDH in moist and liquid environment was studied as part of chapter 2. The data indicated that after high temperatures calcination (600-900 C), the obtained layered double oxides (LDOs) can rehydrate into LDH, although, the rehydrated LDH were different from the original LDH. In chapter 3, different operating conditions, such as gas flow rate, gas compositions (e.g. CH4/CO2 ratio and nitrogen dilution), and addition of H2O were studied to investigate optimal conditions for PPC DRM, identifying possible differences in temperature profiles and exhaust gas compositions that might influence the catalytic performance. Subsequently, the impact of different PPC configurations, making use of the heat and exhaust gas composition produced by the GAP plasma, is shown in Chapter 4. Experiments studying the impact of adjusting the catalyst bed distance to the post-plasma, the catalyst amount, the influence of external heating (below 250 C) and the addition of H2O are discussed. As only limited improvement in the performance was achieved, a new type of catalyst bed was designed and utilized, as described in chapter 5. This improved configuration can realize better heat and mass transfer by directly connecting to the GAP device. The performance was improved and became comparable to the traditional thermal catalytic DRM results obtained at 800 C, although obtained by a fully electrically driven plasma.

Abstract: Generalized Möbius-Listing surfaces and bodies generalize Möbius bands, and this research was motivated originally by solutions of boundary value problems. Analogous to cutting of the original Möbius band, for this class of surfaces and bodies, results have been obtained when cutting such bodies or surfaces. In general, cutting leads to interlinked and intertwined different surfaces or bodies, resulting in very complex systems. However, under certain conditions, the result of cutting can be a single surface or body, which reduces complexity considerably. These conditions are based on congruence and rotational symmetry of the resulting cross sections after cutting, and on the knife cutting the origin

Abstract: Carbon dioxide electrochemical reduction (CO2ER) has attracted considerable attention as a technology to recycle CO2 into raw materials for chemicals using renewable energies. We recently found that Zn-Al layered double hydroxides (Zn-Al LDH) have the CO-forming CO2ER activity. However, the activity was only evaluated by using the liquid-phase CO2ER. In this study, Ni-Al and Ni-Fe LDHs as well as Zn-Al LDH were synthesized using a facile coprecipitation process and the gas-phase CO2ER with the LDH-loaded gas-diffusion electrode (GDE) was examined. The products were characterized by XRD, STEM-EDX, BF-TEM and ATR-IR spectroscopy. In the ATR-IR results, the interaction of CO2 with Zn-Al LDH showed a different carbonates evolution with respect to other LDHs, suggesting a different electrocatalytic activity. The LDH-loaded GDE was prepared by simple drop-casting of a catalyst ink onto carbon paper. For gas-phase CO2ER, only Zn-Al LDH exhibited the CO2ER activity for carbon monoxide (CO) formation. By using different potassium salt electrolytes affording neutral to strongly basic conditions, such as KCl, KHCO3 and KOH, the gas-phase CO2ER with Zn-Al LDH-loaded GDE showed 1.3 to 2.1 times higher partial current density for CO formation than the liquid-phase CO2ER.

Abstract: Electrons, X-rays and neutrons that pass through a thin crystalline sample will be diffracted. Diffraction patterns of crystalline materials contain Bragg reflections (sharp discrete intensity maxima) and diffuse scattering (a weak continuous background). The Bragg reflections contain information about the average crystal structure (the type of atoms and the average atomic positions), whereas the diffuse scattering contains information about the short-range order (deviations from the average crystal structure that are ordered on a local scale). Because the properties of many materials depend on the short-range order, refining short-range order parameters is essential for understanding and optimizing material properties. The refinement of short-range order parameters has previously been applied to the diffuse scattering in single-crystal X-ray and single-crystal neutron diffraction data but not yet to the diffuse scattering in single-crystal electron diffraction data. In this work, we will verify the possibility to refine short-range order parameters from the diffuse scattering in single-crystal electron diffraction data. Electron diffraction allows to acquire data on submicron-sized crystals, which are too small to be investigated with single-crystal X-ray and single-crystal neutron diffraction. In the first part of this work, we will refine short-range order parameters from the one-dimensional diffuse scattering in electron diffraction data acquired on the lithium-ion battery cathode material Li1.2Ni0.13Mn0.54Co0.13O2. The number of stacking faults and the twin percentages will be refined from the diffuse scattering using a Monte Carlo refinement. We will also describe a method to determine the spinel/layered phase ratio from the intensities of the Bragg reflections in electron diffraction data. In the second part of this work, we will refine short-range order parameters from the three-dimensional diffuse scattering in both single-crystal electron and single-crystal X-ray diffraction data acquired on Nb0.84CoSb. The correlations between neighbouring vacancies and the displacements of Sb and Co atoms will be refined from the diffuse scattering using a Monte Carlo refinement and a three-dimensional difference pair distribution function refinement. The effect of different experimental parameters on the spatial resolution of the observed diffuse scattering will also be investigated. Finally, the model of the short-range Nb-vacancy order in Nb0.84CoSb will also be applied to LiNi0.5Sn0.3Co0.2O2.

Abstract: The foodborne pathogens and microorganisms have played a prevalent role in the ebb and flow of the economy worldwide. The increasing population has strained the food processing industry to produce food in large quantity, which in turn has affected the quality of food. To curb this issue, there is immense pressure to produce and maintain quality food within a short time frame. Hence, high throughput technology is used to determine and timely assess the safety and hygiene of food. Further, the revolution of the food industry has also seen an upsurge of new pathogens and microorganisms, thereby increasing the risk of exposure towards rarest diseases to a larger population. This chapter sheds light on the different types of foodborne pathogens affecting the food industry and its social impact. It further emphasizes the safety measures to be taken on the prevention of the disease from the farm to the processing industries and in turn to the household.

Abstract: Climate change is an ever-increasing threat to our planet, with the urbanisation of previously open spaces exacerbating the issue. The loss of open space leads to a decrease in ecosystem services, which negatively impacts the liveability in urbanised environments, and beyond. The incorporation of green infrastructure (GI) into the built environment is acknowledged as an effective and multi-functional measure to make our living environment resilient and future-proof. Notwithstanding that the local level is essential for effective GI implementation, research into local decision making is very limited. This thesis therefore aims to address two significant gaps in the implementation of GI. The first objective is to bridge the science-policy gap by integrating scientific knowledge on ES and GI into local decision-making processes. In this context, the policy dimension within this thesis involves the process of translating overarching policy objectives into practical actions within local decision-making practices, abstracting from the intricacies of higher-level policymaking itself. The second objective focuses on the people-policy gap, which involves understanding stakeholders' perspectives and priorities regarding GI and its associated ecosystem services. Through stated preference valuation techniques (discrete choice experiments and a best-worst scaling experiment), multi-stakeholder GI perceptions are gathered. Finally, a novel tool to GI valuation is developed, acknowledging the different stakeholder views and building on the insights of collaborative tool development and design. By gaining insights into the demand, prioritisation, and provision of GI from the two most important stakeholder groups at the local level (residents and local decision-makers), this research aims to foster effective communication and alignment between public preferences and policy implementation. Ultimately, addressing these gaps will contribute to more informed planning and decision-making practices related to green infrastructure. The overall goal of this thesis is to enhance the uptake of GI knowledge in the local decision-making context, proposing pathways to facilitate and optimise investments in public GI.

Abstract: It is standard practice in virtual reality applications to synthesize binaural audio based on a discrete set of directionally-dependent head-related impulse responses (HRIRs). This set of HRIRs is often time-aligned in a pre-processing step, to allow for high-fidelity interpolation between HRIRs corresponding with neighbouring directions. The fidelity of this operation depends on the similarity of neighbouring aligned HRIRs. The pairwise quality of similarity makes it a difficult criterion to optimize globally and consequently one often resorts to alignment methods based on a specific feature that can be extracted for each HRIR separately, e.g., the first-onset of the peak or the group delay. However, such proxies for similarity are very sensitive to noise and therefore require a high signal-to-noise ratio, which makes them less suitable for processing HRIRs acquired outside an anechoic room. In this paper, we advance a novel alignment method, which maximizes the similarity – defined as the correlation between the full-length HRIRs – between neighbouring aligned HRIRs for all directions at once. We show that this correlation-based alignment procedure outperforms the first-onset alignment with regards to the fidelity of the spherical harmonics representation of both the spectral and interaural time difference (ITD) information, when tested on the KEMAR HRIR and six human HRIRs. Finally, we show that the correlation-based alignment is more robust to noise.

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: Grafting organophosphonic acids modification (PAs) on metal oxides has shown to be a flexible technology to tune the surface properties of metal oxides for various applications. Nevertheless, there are still puzzles that need to be addressed, such as the correlations between metal oxides properties (types of surface reactive sites) and the modification (modification degree), the correlations between metal oxides properties and the properties of modified surfaces. Moreover, the currently used liquid-phase method for the grafting has associated impeding effects of solvent on tailoring the modification degrees, and also causes the formation of metal phosphonate side products. The solid-phase method can induce the unwanted changes in crystal phase of supports. Based on these questions, the three titania supports with divergent surface properties were selected as the metal oxides supports investigated, propylphosphonic acid (3PA) modification was carried out under the same synthesis conditions: four different concentrations, two solvents (water or toluene), and one reaction time (4 h) and temperature (90 ). MeOH chemisorption was introduced to probe the surface (un)reactive sites for 3PA modification. On the other hand, MeOH chemisorption and inverse gas chromatography (IGC) were combined to characterize the changes in surface polarity and acidic properties induced by the modification. Next, a solid-phase method, manual grinding, was proposed to graft 3PA on titania, avoiding the impeding effects of solvent on improving modification degree and the formation of the titania phosphonate side products, as well as preserving the crystal phase. The results indicate that methanol chemisorption can qualitatively analyze the surface active sites that are consumed by 3PA modification, its chemisorption capacity shows the consistent trend with the maximum modification degree, hereby revealing the kinds of interactions that are important in controlling surface coverage. Titania supports is found to play an important role in changes in surface polarity and acidic properties by charactering the three modified titania samples at a similar modification degree using the methanol chemisorption coupled with in-situ infrared and thermogravimetric-mass spectrometer, and the IGC. Moreover, IGC provides additional information about the changes in binding modes. Furthermore, grafting 3PA modification on titania was achieved by manual grinding. Compared to the liquid-phase method, the maximum modification degree obtained by the manual grinding is 25 % higher while using 83.3 % or 75.0% lower amounts of expensive 3PA and limiting the formation of titania phosphonate side products. Compared to the reactive milling method, the proposed manual grinding method preserves the crystal phase(s) of titania.