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Titania has been the focus of attention for several decades owing to its chemical stability, non-toxicity, inexpensiveness and robust surface chemistry. Its technological applications include use in diverse areas such as photocatalytic reactors, antibacterial coatings, dye sensitive solar cells (DSSC) and more recently the perovskite solar cells to name a few. All of these applications are based on the ability to inject or generate electronhole pairs in titania and transport them to a suitable interface at which they are ejected to either engender a reaction as in photocatalysis or drive a load as in photovoltaics. From a technological perspective it is also important that such science be achieved and controlled in supported titania structures. The research reported in this thesis, thus, started with the development of a process for obtaining adherent titania films by oxidation of sputtered Ti films on stainless steel, a very commonly used substrate. Challenges that had to be overcome included the need to oxidize titanium to obtain the right phase mixture while preventing film cracking or delamination due to compressive stresses generated during anodic oxidation of Ti. During this process of obtaining nanostructured TiO2 through anodization, it was serendipitously discovered that planar TiO2 films obtained by oxidation of sputtered Ti films did significantly better than anodized nanoporous titania in bactericidal studies. This was then replicated in organic dye degradation studies. Analysis of the material showed that this improved performance was due to the unintentional contamination during sputtering by Cu, Zn, Mo possibly due to arcing across brass contacts. This quaternary system was then systematically explored and it was shown that an optimal metastable composition in the Ti- Cu-Mo oxide ternary system performs the best. DFT studies showed that this was due to introduction of shallow and deep states in the band gap that, depending on the level of dopants, either enhances carrier lifetimes or leads to ...

India’s recently concluded second National Communications Project, co-ordinated by the MoEF involved participation of about 130 institutions spread over the country. A summary of these reports are expected to be prepared soon to be communicated to the UNFCC. In the meantime, Ministry of Environment and Forests (MoEF) has come out recently with an Indian National Network for Climate Change Assessment (INCCA)1

While transport is inevitable in our economy and daily lives, it also engenders many negative effects - on the economy, society, and environment. Though a large share of the external costs associated with climate change is attributable to transport, this is only partly carried by it. The transport sector still lags behind with regard to emitted greenhouse gases and faces difficulties in achieving the emission reduction goals. In line with the ‘polluter pays’ principle, an instrument for internalizing the external costs of transport is a road pricing scheme. Not only would it stimulate the use of more environmentally friendly vehicles, this concept could also prove its use in pursuing a level playing field across different transport modes. Implementation of a pricing system should be well thought of, as perverse effects can easily arise. Road pricing will also incentivize the switch to zero-emission vehicles. A pricing scheme should be implemented coherently on a European level to avoid additional kilometres due to detour and related externalities.

For more than 3000 years, windmills have been used to harvest energy from the wind. Over the past 30 years, electrical generators and advanced aerodynamics have turned them into the wind turbines we know. From hereon, how can the coming 30 years see them transition from outsider to key player of the energy system to help reach carbon neutrality? Increasing rotor diameters is a possible answer, clustering turbines into wind farms is another. Yet, with both options come new challenges, as the sensitivity of components to fatigue increases with the size of rotors and the wake phenomenon is responsible for power losses in wind farms. This thesis falls within the context of using control strategies to tackle these challenges. More specifically, this work relies on high fidelity simulations to investigate control approaches numerically. When it comes to reducing fatigue loads, individually controlling the pitch of each blade has proven to be efficient. This thesis introduces a novel controller architecture that relies on a neural network trained with reinforcement learning. This work demonstrates that a neural network can learn how to alleviate loads in simple wind conditions and that it is also capable of transferring that knowledge to realistic ones, such as turbulence and wakes. Regarding the question of wake mitigation, dynamically controlling wind turbines is gaining interest. While some strategies enhance the lateral displacement of the wake, others periodically modify its intensity. This work provides some insights into the mechanisms relating dynamic actuation of the blades to power gains in the wake. To do so, the effects of dynamic flow control on the wake destabilization and recovery processes are investigated. Attention is also paid to quantifying the impacts of such strategies on both power production and loads at the scale of a pair of turbines. (FSA - Sciences de l'ingénieur) -- UCL, 2022

Cellulose and hemicelluloses are the most abundant structural polysaccharide in nature. Their optimal valorization in lignocellulose-based biorefineries requires a good knowledge of the contents available in various biomasses, and of their molecular composition. The composition and more specifically the monosaccharidic content (cellulosic glucan, xylan, arabinan, mannan, galactan and hemicellulosic glucan) were analyzed in several lignocellulosic grass crops: switchgrass (Panicum virgatum L.), tall fescue (Festuca arundinacea Schreb.), cocksfoot-alfalfa association (Dactylis glomerata L.-Medicago sativa L.). Cellulose and hemicelluloses contents were in the range 20.8-33.3 and 14.5-32.6 g (100gDM)-1, respectively, with lignin, total soluble sugars, proteins, and ash contents around 2.9-7.8, 2.0-21.7, 5.7-17.2 and 4.3-16.3 g (100gDM)-1, respectively. The main hemicellulosic components were, by order of decreasing importance, xylan 8.3-23.2 g (100gDM)-1, arabinan 2.12-4.10 g (100gDM)-1, hemicellulosic glucan 1.36-3.42 g (100gDM)-1, galactan 0.63-2.31 g (100gDM)-1 and mannan 0.27-1.08 g (100gDM)-1. Plant species and harvest cycle has the most significant influence on the structural polysaccharide composition, while the influences of cultivar and nitrogen fertilization were only rarely significant.

At high latitudes, a significant part of the oceans is covered by sea ice that forms when seawater freezes. Sea ice is a major player in the global climate system. It is also a primary indicator of climate change, as it responds rapidly to variations in surface air temperatures and wind regimes. Since years now, scientists have developed numerical models to assist them in better understanding the sea ice system. These models simulate the evolution of the main sea ice characteristics at high spatial resolution and temporal frequency, which makes them valuable tools to enlarge the picture given by incomplete observations. In addition, models are used for their predictive skills, from seasonal to centennial horizons. However, in spite of their increasing complexity, substantial uncertainties still persist in model reconstructions and predictions of Arctic and Antarctic sea ice. In this doctoral thesis, we have developed the tools to properly identify the possible sources of these uncertainties. We have highlighted the important role of model physics and initial conditions for the climate simulations of Arctic sea ice. We have also implemented statistical methods to optimally constrain the models given measurements, a field of research known as data assimilation. In the framework of sea ice data assimilation, we have been able to propose a multi-decadal reconstruction of Antarctic sea ice thickness, which is not possible from observational data only. Sea ice models become more comprehensive. At the same time, more and more observations are available to evaluate, constrain and improve them. To address the sensible questions about the future of sea ice and of climate in general, an optimal use of these two sources of information will be required. This thesis illustrates some steps to move forward in this direction. (SC - Sciences) -- UCL, 2014

This paper describes a methodology for determining the optimal envelope shape that minimizes the solar array area of a high altitude airship to be deployed at a specified geographical location. It identifies the critical day of the year and the optimal altitude of deployment on that day, and determines the smallest area of solar array that is just sufficient to meet all the operating requirements. This ensures that the airship can be deployed round the clock throughout the year at that specific geographical location, without any power shortfall. The methodology involves eleven design variables whose values are affected by parameters stemming from four disciplines, viz., Environment, Geometry, Aerodynamics, and Energy. Candidate envelope profiles are generated using a standard shape generation algorithm, and their volumetric drag coefficient is estimated using a surrogate based aerodynamic model. Envelope shapes corresponding to minimum solar area obtained by coupling the methodology to an optimizer based on Genetic Algorithms. To study the effect of the season of deployment, optimal envelope shapes were obtained for deployment on three specific days of the year (viz., Winter solstice, Summer solstice and Equinox) for an assumed altitude of deployment. It was seen that area of solar arrays needed for the airship were 4-9% lower than that for the baseline airship envelope. However, when the altitude of deployment and day of operation were allowed to vary, the optimal envelope shapes obtained had 35% lower solar area.

Simultaneous with the growing demand for sustainable food, statistics in all EU member states report consumption patterns that are characterized by too much fat, overdoses of sugar and a lack of fruits and vegetables. The streams of literature that investigate the factors influencing sustainable food consumption and healthy food consumption are largely separated. However, the question whether there is a positive relationship between consumer behaviour towards sustainable food and consumer behaviour towards healthy food remains largely unanswered. The purpose of this paper is to examine the relationship between the consumption of different types of sustainable food on the one hand, and healthy food patterns on the other. The study is based on a sample of 2595 respondents in Belgium. The research shows a significant relationship between a healthy diet and sustainable food choices. Analyses applied to identify gender- or age-specific tendencies demonstrate that the association is particularly pronounced for consumers between 26 and 40 years old. For younger consumers (<26 years) and older consumers (>65 years), the relationship between sustainable food behavior and the choice for healthy food is weak. These findings can be extremely useful in the communication and promotion of different types of sustainable food.