Abstract: Green walls (GW) can diminish building's surface temperature through shading, insulation, and evapotranspiration mechanisms. These can be analyzed by computer models that account for heat and mass transfer phenomena. However, most previous models were one-dimensional thermal simulations in which boundary conditions (BC), like convective moisture transport, were not or only partly considered. The present work proposes a more comprehensive way to predict GW's hygrothermal behavior by integrating a 3D multiphysics model that couples heat and moisture transport in Comsol Multiphysics®. The air cavity that usually separates the GW from the building was also considered. Heat sink terms were added to represent plants' transpiration and substrates' evaporation, considering the leaf area density (LAD) and substrate's water saturation (Sr). The model was validated against experiments where four green wall-test panels (GW-TPs) were evaluated in a climate chamber under steady-state conditions. This provides a much sounder approach for validation than what currently exists (r = 0.97; RMSE = 0.33 °C). The four GW-TPs decreased the masonry's surface temperature in the range of 0.89–1.14 °C (0.97 ± 0.11 SD °C). The average contribution of the evapotranspiration effect was 30%, whereas the contribution of the air cavity was 60.7 ± 0.09%. The temperature at the substrate's rear was reduced on average by 0.57 ± 0.15 SD °C. When solar radiation was considered as a BC, the GW-TPs decreased the building's surface temperature by 10 °C. Lastly, high values of LAD and Sr translated into increased temperature reduction values.

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: Nanomaterials are materials that have at least one dimension in the nanometer length scale, which corresponds to a billionth of a meter. When three dimensions are confined to the nanometer scale, these materials are referred to as nanoparticles. These materials are of great interest since they exhibit unique physical and chemical properties that cannot be observed for bulk systems. Due to their unique and often superior properties, nanomaterials have become central in the field of electronics, catalysis, and medicine. Moreover, they are expected to be one of the most promising systems to tackle many challenges that our society is facing, such as reducing the emission of greenhouse gases and finding effective treatments for cancer. The unique properties of nanomaterials are linked to their size, shape, structure, and composition. If one is able to measure the positions of the atoms, their chemical nature, and the bonding between them, it becomes possible to predict the physicochemical properties of nanomaterials. In this manner, the development of novel nanostructures can be triggered. However, the morphology and structure of nanomaterials are highly sensitive to the conditions for relevant applications, such as elevated temperatures or intense light illumination. Furthermore, any small change in the local structure at higher temperatures or pressures may significantly modify their performance. Hence, three-dimensional (3D) characterization of nanomaterials under application-relevant conditions is important in designing them with desired functional properties for specific applications. Among different structural characterization approaches, transmission electron microscopy (TEM) is one of the most efficient and versatile tools to investigate the structure and composition of nanomaterials since it can provide atomically resolved images, which are sensitive to the local 3D structure of the investigated sample. However, TEM only provides two-dimensional (2D) images of the 3D nanoparticle, which may lead to an incomplete understanding of their structure-property relationship. The most known and powerful technique for the 3D characterization of nanomaterials is electron tomography, where the images of a nanostructured material taken from different directions are mathematically combined to retrieve its 3D structure. Although these experiments are already state-of-the-art, 3D characterization by TEM is typically performed under ultra-high vacuum conditions and at room temperature. Such conditions are unfortunately not sufficient to understand transformations during synthesis or applications of nanomaterials. This limitation can be overcome by in situ TEM where external stimuli, such as heat, gas, and liquids, can be controllably introduced inside the TEM using specialized holders. However, there are some technical limitations to successful perform 3D in situ electron tomography experiments. For example, the long acquisition time required to collect a tilt series limits this technique when one wants to observe 3D dynamic changes with atomic resolution. A solution for this problem is the estimation of the 3D structure of nanomaterials from 2D projection images acquired along a single viewing direction. For this purpose, annular dark field scanning TEM (ADF STEM) imaging mode provides a valuable tool for quantitative structural investigation of nanomaterials from single 2D images due to its thickness and mass sensitivity. For quantitative analysis, an ADF STEM image is considered as a 2D array of pixels where relative variation of pixel intensity values is proportional to the total number of atoms and the atomic number of the elements in the sample. By applying advanced statistical approaches to these images, structural information, such as the number or types of atoms, can be retrieved with high accuracy and precision. The outcome can then be used to build a 3D starting model for energy minimization by atomistic simulations, for example, molecular dynamics simulations or the Monte Carlo method. However, this methodology needs to be further evaluated for in situ experiments. This thesis is devoted to presenting robust approaches to accurately define the 3D atomic structure of nanoparticles under application-relevant conditions and understand the mechanism behind the atomic-scale dynamics in nanoparticles in response to environmental stimuli.

Abstract: The growing demand for tools to generate chemical information in decentralized settings is creating a vast range of opportunities for potentiometric sensors, since their combination of robustness, simplicity of operation and cost can hardly be rivalled by any other technique. In previous works, we have shown that the mixed potential of a Pt electrode can be controlled with analytical purposes using a coating of Nafion, thus providing a way to develop a potentiometric biosensor for glucose. Unfortunately, the linear range of this device did not match the relevant clinical range for glucose in blood. This work presents a novel strategy to control the mixed potential that allows the development of a potentiometric biosensor for the direct detection of glucose in whole, undiluted blood without any sample pretreatment. By changing the ionomer, the analytical response can be tuned, shifting the linear range while keeping the sensitivity. Aquivion, a polyelectrolyte from the same family as Nafion, is used to stabilize the mixed potential of a platinized paper-based electrode, to entrap the enzyme and to reduce the interference from negatively charged species. Factors affecting the generation of the signal and the principle of detection are discussed. Optimization of the biosensor composition was achieved with particular focus on the characterization of the linear range and sensitivity. The accurate measurement of blood sugar levels in a single drop of whole blood with excellent recovery is presented.

Abstract: Laser Microprobe Mass Spectrometry (LAMMA) is used to examine micrometric particles of calcium oxyanion salts (CaCO3, CaSO4, CaSO4·2H2O) and calcium oxide, in both the positive and negative ion mode. The major molecular ions, appearing in the positive mass spectrum, can be divided into three series, namely CamOm-1+, (CaO)m+ and (CaO)mH+ (m = 1-4). In the case of the former two series the relative intensities of the mass peaks as a function of the fragment valence K = (1 + 2n)/m, for CamOn+, can be fitted to a Gaussian distribution curve, as was earlier demonstrated for secondary ion mass spectrometry. The high stability of the (CaO)mH+ series can be explained by the favourable fragment valence of +2 corresponding to the usual oxidation state of calcium.

Abstract: In present work, we have performed the Grand Canonical Monte Carlo (GCMC) simulations to quantify CO2 capture inside porous silica at high operating temperatures of 673.15 K and 873.15 K; and over a operating pressure range of 500 kPa – 4000 kPa that are methane steam reforming process parameters. Related chemical potential values at these thermodynamic conditions are obtained from the bulk phase simulations in the Canonical ensemble in conjunction with Widom’s insertion technique, where the CO2 has been accurately represented by TraPPE force field. Present structure of the porous silica is a single slit pore geometry of various heights (H = 20 Å, 31.6 Å, 63.2 Å and 126.5 Å), dimensions in which possible vapour-liquid equilibria for generic square well fluids has been reported in literature. Estimation of the pore-fluid interactions show a higher interaction between silica pore and adsorbed CO2 compared to the reported pore-fluid interactions between homogeneous carbon slit pore and adsorbed CO2; thus resulting in an enhancement of adsorption inside silica pores of H = 20 Å and H = 126.5 Å, which are respectively 3.5 times and 1.5 times higher than that in homogeneous carbon slit pores of same dimensions and at 673.15 K and 500 kPa. Estimated local density plots indicate the presence of structured layers due to more molecular packing, which confirms possible liquid-like and vapour-like phase coexistence of the supercritical bulk phase CO2 under confinement.

Abstract: Nitrogen dioxide (NO2) concentrations were used to evaluate the air quality before and after the infrastructural change of an important traffic artery in Mortsel, Antwerp (Belgium). During the reconstruction works two pairs of traffic lanes were reduced to one in each direction. Two sampling campaigns were conducted: the first one before the works in 2003 and the second one in 2005, after the road works were finished. Sampling was performed on a weekly base with the use of passive diffusion tubes on the streets, and also indoors in nearby houses. The samples were analyzed by ion chromatography, from which data the NO2 concentrations in air could be calculated. These results were compared with NO2 values from the air monitoring station 42R801 of the Flemish Environment Agency in Borgerhout, Antwerp. On the base of different NO2 concentrations, correlated well with the traffic density, sampling locations were classified into three groups as follows: 1) heavily polluted (heavy traffic); 2) moderately polluted (medium traffic); or 3) less polluted (low traffic density). Sampling sites located further from the road works, enclosed to the group less polluted, showedthe lowestNO2 concentrations. The highestNO2 levelwas found for the locations close to reconstructionworks, which belonged to the group heavily polluted. The contribution of NO2 was at the samelevel before and after the roadworks. During the first campaign it ranged from30±7 µg/m3 to 71±11 µg/m3 and during the second sampling itwas between 36±17 µg/m3 and 73±17 µg/m3. These modernizationworks had no impact on preventing the traffic-related pollutant as NO2 and as a consequence no significant effect on the air quality in the studied region. It has been proven that the impact of traffic on the air quality is unmistakably high and simply reduction of the number of the traffic lanes, intended to discourage the traffic flow, had apparently no environmentally advantageous effect

Abstract: Two sampling campaigns in suburban places in the north zone of Santa Clara city, Cuba, have been carried out on a weekly base with the use of Radiello passive diffusion tubes in order to monitor the tropospheric ozone (O3) levels in 2010. The first campaign was scheduled from February to April (cold season) and the second one in August and October (warm season), both of them at two sampling sites, i.e., Farm and School of Art Instructors. After aqueous extraction, the samples were analyzed by UVVIS spectrophotometry. A seasonal trend was observed with the maximum O3 concentrations in the cold season and the minimum levels in the warm season. Samples collected during the cold season showed the highest O3 levels. Higher levels were reached at the Farm site with average values of about 58 ± 12 μg/m3, which exceeded the limit of the Cuban Standard 99:1999. In the warm season, the O3 concentrations were similar for both sites, but lower than those observed in the cold season. The overall, seasonal average value was found to be 24 μg/m3. Despite the higher weekly average temperatures in August, the O3 concentrations during this month showed the lowest values of the whole sampling period, which finding is in agreement with that reported by the Meteorological Institute of Cuba. Mathematical models, based on the Cochrane-Orcutt algorithm, were fitted to the acquired data set to explain the change in the tropospheric ozone concentrations under various meteorological conditions during the two campaigns. The correlation coefficients for both the cold and the warm seasons demonstrated a strong correlation, i.e., 0.779 and 0.951, respectively. The high correlation of wind speed in the model from the first sampling campaign explains the sharp decrease in O3 concentrations at the SAI sampling site from the sixth week of sampling.

Abstract: A Monte Carlo simulation has been developed to describe the incoherent and coherent scatter processes for the complex geometry of a secondary target energy-dispersive x-ray fluorescence system. Photons are followed from the x-ray tube anode until the detection of scattered secondary target photons in the active Si layer of the detector. The program quantitatively shows the broadening of the incoherent scatter peak with increasing atomic number, and it models the incoherent peak shape adequately. The incoherent-to-coherent scatter intensity ratios obtained differ by 1030% from the theoretical values, while their dependence on the sample atomic number corresponds to that expected from theory.