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: Pretreatment is a critical step in the conversion of lignocellulose into biofuels and biochemicals. During pretreatment, the recalcitrance of lignocellulose is reduced, e.g. by removing lignin, thereby making the carbohydrates more accessible for enzymatic saccharification. Fungal delignification by white-rot fungi is a biotechnological alternative to chemical/physicochemical methods, which is carried out in solid-state fermentation with mild reaction conditions and without the formation of microbial inhibitors. However, fungal pretreatment presents some challenges, such as long pretreatment time, non-selective and low delignification, low enzymatic digestibility and feedstock sterilisation requirement, making its commercial implementation challenging compared to conventional methods. This study investigates the possibility of improving and characterising the solid-state fungal pretreatment of poplar wood by Phanerochaete chrysosporium. The individual and combined effects of MnSO4 and CuSO4 supplements on the delignification of sterilised wood are investigated using response surface methodology to improve the degree and selectivity of fungal delignification. Spore-inoculated solid-state fermentations are carried out for 4 weeks in sterile vented bottles. The mechanism of the concerted action of the metal ions on lignin degradation is then elucidated by relating fungal growth and ligninolytic enzyme activities to lignocellulose degradation as a function of pretreatment time. The optimised metal-supplemented system is then applied to the pretreatment of non-sterilised wood using different inoculation techniques (spores and pre-colonised substrate), nutrients (metal ions with or without glucose and sodium nitrate) and cultivation environments (sterile aerated bottles and open trays). The fermentations are then characterised using infrared spectroscopy, in particular NIR and ATR-FTIR spectroscopy, with the aim of developing rapid lignin quantification methods as an alternative to conventional wet chemical methods. Finally, the feasibility of producing fermentable sugars from sterilised and non-sterilised poplar wood using fungal pretreatment is evaluated through a techno-economic analysis. Supplementing the pretreatment system with 2.01 µmol CuSO4 and 0.77 µmol MnSO4 g-1 wood resulted in 1.9-fold higher lignin degradation, 2.3-fold higher delignification selectivity value and 2.9-fold higher glucose yield. The improved delignification could be explained by the concerted action of Mn2+ and Cu2+ ions, with Mn2+ ions inducing and Cu2+ prolonging manganese peroxidase production responsible for delignification. Fungal pretreatment at non-sterile conditions was obtained using trays in a simple solid-state fermentation set-up without sterile aeration. A 1:3 ratio of pre-colonised and untreated wood was applied for inoculation and only Cu2+, Mn2+ and sodium nitrate as supplements. Remarkably, this technology resulted in a comparably high glucose yield (28.51 ± 0.28%) to the traditional method using sterilised wood, sterile aeration and spores as inoculum, while reducing the amount of wood to be sterilised by 71.2%. Infrared spectroscopy-based methods with high coefficients of determination (R_CV

Abstract: Climate change is causing alterations in precipitation patterns, leading to adverse ecological consequences in many ecosystems. Recently, an increasingly persistent weather pattern has emerged, characterized by lengthening the duration of alternating dry and wet periods, which is more complex than exclusively drought or increasing precipitation. It is currently unclear how soil microbial communities respond to these new regimes in relation to their interactions with plants, especially in precipitation-sensitive ecosystems, such as tropical rainforests and grasslands. In this thesis, we explored responses of soil bacterial and fungal communities to increasing weather persistence in rainforests and grasslands, using high throughput sequencing technology. We firstly investigated the resistance and resilience of microbial communities to prolonged drought in a mature seasonal tropical rainforest which experiences unusually intensive dry seasons in the current century. Through excluding rainfall during and after the dry season, a simulated prolongation of the dry season by five months was compared to the control. Our results indicate that as rain exclusion progressed, the microbial communities increasingly diverged from the control, indicating a moderate resistance to prolonged drought. However, when the drought ceased, the composition and co-occurrence patterns of soil microbial communities immediately recovered to that in the control, implying a high resilience. To further investigate the ecological roles of soil microbial communities in response to increasing weather persistence, we set up grassland mesocosm experiments. In these experiments, precipitation frequency was adjusted along a series, ranging from 1 to 60 consecutive days alternating of dry and wet periods, while keeping the total precipitation constant. Our results show that microbial community assembly tended to be more stochastic processes at intermediate persistence of dry and wet alternations while more deterministic processes dominated at low and high persistence within 120 days regime exposure. Moreover, more persistent precipitation reduced the fungal diversity and network connectivity but barely impacted that of bacterial communities. The prior experiences of persistent weather events for one year caused legacy effects. The soil microbial legacy induced by soil microbial communities subjected to prior persistent weather events was more enduring in subsequent fungal communities than bacterial communities, likely due to slower growth of fungi compared to bacteria. However, a minor effect of soil microbial legacy  was observed on plant performance. In addition, we kept the grassland mesocosm experiment for two growing seasons. The effects of precipitation persistence on soil microbial communities increased in the second year. The dissimilarities of microbial communities between the first and second year were less with more persistent precipitation, potentially resulting in more vulnerable microbial communities, due to some taxa disappearing and a reduction in functional redundancy under more persistent weather. To conclude, our findings provide a comprehensive theoretical understanding of soil microbial communities in response to the current and future climate change, drawing from both natural and experimental systems. It helps in predicting and managing the impacts of future climate change on ecosystems mediated by microbial communities. Additionally, the findings of microbe-mediated legacy effects on grassland ecosystems can provide practical guidance for their application in agriculture, specifically for using an inoculum to mitigate the impacts of climate change.

Abstract: The discovery of antibiotics represented one of the greatest breakthroughs in medicine. Their success combined with an increasing intensive use is apparently bound to be also their undoing. This is due to the development of acquired antibiotic resistance, leading to inefficient antibiotherapy and even to the impossibility of treatment and death. The development and spread of antibiotic resistance are fueled by the widespread presence of trace levels of antibiotics residue, in various media, from environment to aliments. One of the solutions is the rigorous monitoring of the levels of antibiotics, which in term requires an almost constant development of new, more accessible analytical methods, especially screening methods, capable of decentralized analysis. In this direction, the electrochemical detection of antibiotics represents a very viable alternative. In this context, the aim of this thesis was to develop new electrochemical methods for the detection of antibiotics by employing and expanding on several strategies, like biomimetic sensors and electrochemical fingerprinting. Five studies were described in this thesis, that can be roughly divided in three categories, based on the analytical strategy employed. The first group is represented by direct electrochemical methods. The second group focuses on the use of biomimetic elements, molecularly imprinted polymers and aptamers. The hyphenation of electrochemical methods with other analytical methods was explored in the last group. In the last study, included in this group, the singlet oxygen-based photoelectrochemical approach was used for the detection of a phenolic antibiotic, rifampicin. The originality of the thesis consists in the testing and development of new approaches to various strategies used in electrochemical detection, revealing new insights in the field of electrochemical detection of antibiotics. The complex electrochemical fingerprint and the mechanism of the electrochemical oxidation were created and investigated, respectively, for the antibiotic vancomycin. New sensitive nanoplatforms were prepared by employing and combining new protocols. Additionally, important contributions were brought through the study involving the singlet oxygen-based detection of rifampicin. We demonstrated how a photocatalyst can exhibit analyte selectivity by strongly interacting with a complex phenolic compound, rifampicin. Summing up, the studies presented in this thesis will have an important impact in the field of electrochemical detection of antibiotics.

Abstract: Today, illicit drugs are omnipresent in society. Clandestine markets are growing faster than ever before, record amounts of cocaine are seized in seaports and airports, while the associated violence is spiralling out of control. In addition, drug monitoring centres worldwide are warning for the increasing complexity of the drug markets, as the traditionally popular drugs are joined by countless new synthetic variants, while medical drugs are also increasingly being abused. In order to provide services confronted with illicit drug samples (police, customs, forensic scientists, first responders, …) with important information on the identity of an unknown sample, suitable analytical tests are required. While these exist for laboratory environments, on-site applicable tests are important to accelerate the decision-making process. Electrochemical sensors have all the advantages required for such on-site tests: they are fast, portable, easy-to-use and reliable. Furthermore, they are not influenced by colours, which are frequently added to drug samples to deceive the existing tests. Previous work has mainly focussed on the detection of a single drug per analysis. However, many drugs could be encountered due to the diversity of the drug markets. Therefore, this project developed electrochemical strategies for the detection of multiple drugs simultaneously. First, the electrochemical behaviour of the individual drugs was studied in different measuring conditions (assessing the influence of pH, concentration and temperature). Then, all findings and strategies were combined to detect multiple targets simultaneously. An electrochemical sensor was developed for the four most popular drugs at music festivals: cocaine, MDMA, amphetamine and ketamine. This sensor generates a so-called ‘superfingerprint’ of the sample, which is then automatically interpreted by a developed algorithm in order to produce a straightforward output. Finally, a pill analysis sensor was developed in the context of drug checking services, where a consumer can anonymously have a sample chemically analysed to obtain information on the composition, dose and potentially harmful additives. The sensor achieved an outstanding accuracy in identifying the main component and provided the option to quantify, as well as an indication on the presence of other substances in the sample. The project’s findings demonstrate the potential for electrochemistry in illicit drug detection and provide a basis for the development of new sensors, targeting other drug combinations.

Abstract: The low-pressure hollow cathode discharge made of a hollow circular tube and an anode is a type of simple structure discharge system. In particular, under the arc discharge mode, hollow cathodes have high plasma density and energy density with a wide range of adaptability of pressure and current. Low-pressure hollow cathode arc (HCA) discharges have been widely used as plasma sources in various fields such as manufacturing, vacuum welding, and aerospace since the 1960s. Despite the early experimental and applied researches on low-pressure HCA discharges, the basic theoretical study was relatively lagged much behind, resulting in many unanswered questions, such as the optimal discharge operating parameters, the power deposition inside the cathode, the causes of plasma instability, and how to effectively reduce cathode erosion and so on. Due to the special discharge structure of the hollow cathode, it is difficult to make an accurate experimental diagnosis, so a reasonable numerical simulation is an effective study method. However, up to now, there is still a lack of complete and effective numerical models which can evaluate various physical fields in the low-pressure hollow cathode discharges. To address the above problems and difficulties, a comprehensive and self-consistent 2D multi-physical coupling numerical model based on a commercial program of finite element method, the COMSOL Multiphysics, was provided in this paper. The model involves plasma transport, arc flow and heat transfer, and cathode thermal equilibrium, and can consider the effect of an applied magnetic field. The processes of secondary electron emission, thermal-field electron emission, ions and backflow high-energy electrons bombardment, and thermal radiation from the cathode surface are considered in the cathode thermal equilibrium process. Based on the above background, this paper works from the following aspects： In Chapter 1, the basic concepts of low-pressure HCA discharge including the hollow cathode effect, the basic characteristics, and operation modes were introduced firstly; Secondly, the application fields, development history, and overseas and domestic research status of hollow cathode discharge were reviewed; finally, the problems were presented and the research background was explained, and the research purpose of this paper was clarified. In Chapter 2, a complete and self-consistent numerical model of low-pressure hollow cathode discharge was proposed based on the fundamental theory and assumptions, and the set of control equations and boundary conditions in the model were elaborated. In addition, the electron energy distribution function, the collision processes, the solving tools of this model, and calculation schemes were introduced in detail. Finally, a validation example was given to test the rationality and applicability of the numerical model. In Chapter 3, the fundamental plasma properties of low-pressure hollow cathode arcs were investigated. Firstly, the ion Joule heating effect was studied. The results showed that the temperature distributions of the arc and cathode are only able to approach the experimental measurements after considering the ion Joule heating, which shows that the Joule heating of ions is crucial for the heating of the arc plasma. Secondly, by comparing the radial distribution of electron and ion density inside the cathode, the structure of the cathode sheath could be simulated well using this model. Finally, it was shown that the thermal radiation from the cathode surface is an important cooling mechanism of the cathode and only under higher surface emissivity can balance the larger heat flow given by the plasma to the cathode, and the temperature distribution of the cathode shows a non-monotonic increasing trend and is consistent with the profile of experimental measurement so that the so-called active zone is formed. In Chapter 4, the power deposition in the low-pressure HCA was studied in simulation. Two main aspects were considered: the power deposition into particles (both electrons and heavy particles) and the power deposition onto the cathode. It was found that the deposited power into particles increases with the rise of discharge current, but there is no effect on the total power deposition onto the cathode. In high-density plasmas, Coulomb collisions between electrons and ions also become very important, especially since a portion of the deposition energy on heavy particles comes mainly from the energy transfer from electrons to ions. It was also found that regardless of external parameters, half of the power deposition onto the cathode always comes from the particle contribution, while the other half is the net contribution of heat transfer and cathode radiation. The HCA model also allows the simulation of multiple discharge modes for low-pressure HCA discharges over a wide range of gas flow rates. It was also shown that the discharge operating conditions and the external magnetic field can change the distribution of the particle flow on the cathode wall. In Chapter 5, the ion sputtering erosion process on the cathode was simulated by coupling the HCA numerical model with the moving grid technique. The results showed that the ion sputtering erosion on the cathode depends on the ion flux and the plasma potential near the cathode wall and that their distribution and magnitude jointly determine the erosion morphology of the cathode. It was also found that the location of the most severe erosion on the cathode is located in the region of the densest ion flux on the cathode wall, rather than in the longitudinal correspondence with the central region of the internal positive column (IPC). The external magnetic fields can mitigate the cathode erosion and reduce the erosion depth, but stronger magnetic fields lead to a concentration of current density at the cathode tip, which can enhance erosion slightly at the cathode outlet end. Finally, the conclusions and innovation highlights were summarized, and prospects for future work were discussed.

Abstract: Tropical rainforests host an exceptional biodiversity and play a fundamental role in the regulation of global climatic cycles. Soil fungi and bacteria are key players in the transformation and processing of nutrients in terrestrial ecosystems while having an essential role as tree mutualists or antagonists. Still, there are gaps in our understanding of the main variables driving soil microbes on these forests and it is unclear how future climate change scenarios may impact soil microbes and further affect the ecosystem. In this thesis, we first explored the drivers of the microbial community composition in two pristine forests in French Guiana by using amplicon DNA sequencing. The neighboring tree species were found to be a crucial factor influencing the fungal and bacterial community composition at our sites regardless of the season. Additionally, within the environmental factors explored, soil moisture, phosphorus (P) and nitrogen (N) availability were consistently the main soil properties controlling the composition of soil microbial communities. Secondly, as increased nutrient deposition due to anthropogenic activities are expected to affect tropical forests ecosystems N and P availability, a factorial N and P nutrient addition experiment in the same sites was used to assess the effects of changes in the soil nutrient stoichiometry on the soil microbial communities. These results showed that after 3 years of nutrient additions, the bacterial and fungal community composition was affected by both the N and P additions. Besides, the fungal community composition had a stronger response to the nutrient addition, especially when P was added. Moreover, when the nutrient addition effect was assessed in bacteria and fungi with different life strategies, we found different nutrient optima between them. Furthermore, to study the effect of the connection to an existing mycorrhizal mycelium on tree seedlings, I established a mycelium exclusion experiment. Interestingly, we could not detect an effect of the mycorrhizal mycelium exclusion on the seedling N uptake, performance, or fungal community composition in roots after one year. All together this work provides a deeper understanding of the factors influencing the soil microbial communities on these lowland tropical forests, demonstrating that the tree community composition exerts a higher influence on the soil microbial community composition than previously expected. Moreover, our results show that the fungal and bacterial community composition and its relationship with trees in the vicinity is highly dependent on the ecosystem nutrient availability.