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This thesis looks at the urban environment as the centre of human habitation. It governs the comfort of much of the human population and is essential to life itself. In the modern world, it is governed at many levels and this thesis approaches two of them: modelling a building's system and elements of urban city design. Urban climate, in the UK, is being increasingly affected by climate change and urban pollution remains a concern. How cities are maintained and designed is being adjusted to consider these interactions. This thesis looks at the impact of roughness of the cities-scape on wind speed, considered a factor capable of improving air quality . This thesis will looks at urban albedo and the impact it has on air temperature at ground level compared with the general degree of urban density. Uncertainty is a part of complex systems such as cities which contain many elements and in order to address this models are used to describe these system. A modeller will not have access to all information or the time to address every element at a high level of detail. The Gaussian processes used in this thesis have inherent uncertainty quantification, and they make estimates that make allowances for inaccuracies. This means conclusions drawn using this method can be considered more robust to uncertainties in the data. This thesis will examine empirical data using different methodologies to draw conclusions about model fitness of the methods used. The case studies that are used are the problem of emulator construction for the building energy models (BEMs) and two example relationships of urban weather from the Birmingham University Climate Laboratory (BUCL) and the urban fabric. Building energy use, through domestic, office and industrial consumption, is a major part of how we as a society consumes electricity/gas and this consumption is metered. Building systems are modelled using physical principles which requires a large amount of information about constructed systems, user behaviour and the ambient environment which is very costly justifying alternatives such as statistical modelling. This thesis will showcase how they can be used to address the issue of climate change for a building energy use, in cooling.

Energy and environmental building performance simulation techniques have advanced considerably throughout the past half a century. Sophisticated and easy to use simulation engines now exist that can simultaneously simulate heat flow, fluid flow, plant systems, daylighting and radiation exchange and the impacts of building occupants on these systems and the corresponding feedbacks. Meanwhile, mass rural-urban migration has meant that the global population is now predominantly urban - we have become homo urbanus - with the vast majority, more than three quarters, of global resource use being concentrated into urban settlements. With growing concerns over climate change, there is thus a need to identify ways of reducing the negative environmental impacts of urban settlements, whilst ensuring that the quality of urban life is maintained or enhanced. This principle is enshrined in the UN Sustainable Development Goal 11: Sustainable Cities and Communities. In consequence, the last quarter of a century has seen a considerable increase in research activity to develop computational techniques that can efficiently and accurately simulate energy and environmental performance at higher spatial scales, and accounting for increasingly sophisticated building-occupant, building-building and building-system interactions. It is in this urban complexity that this thesis is situated. Specifically, this thesis seeks to develop and apply a computational framework with which energy (using sunlight availability as a corollary), thermal and acoustic comfort can be simulated and optimised in the urban context, through a series of urban district use cases located in China. In the first instance, candidate building and urban morphology parameters are identified through cluster analysis. These parameters are then used to support parametric modelling of the above sunlight, thermal comfort and acoustic comfort performance domains, using dedicated simulation techniques. Hierarchical cluster analysis is also applied to these results to synthesise preliminary design guidelines. These simulation results are also used to train meta-models, developed using an adapted combination of generic regression neural network (GRNN) and grey wolf optimiser (GWO) algorithms. The trained and validated meta-models are then used to define the objective functions employed by a non-dominated sorting genetic algorithm with elitist strategy (NSGAII) optimiser to identify feasible Pareto solution sets of our three performance domains, employing the earlier defined morphology parameters. Finally, a specification for an interactive web-based urban design tool is outlined, with which the trained optimiser could be employed to suggest well performing morphologies as inspiration to urban designers.

Only a small number of the subjects who enter treatment For obesity maintain their target weight. Explanations for this include increased food efficiency and alterations in resting metabolic rate (RMR). The RMR has been shown to be reduced after weight reduction and it is believed that a benefit of exercise training is an adaptive increase in lean body weight (LBW) with a concurrent decrease in excess body fat. Since caloric restriction is essential for weight reduction, an increase or preservation of LBW is desirable. The purpose of this study was to assess the effect of caloric restriction (DO group; n = 6) and caloric restriction plus weight training (DWT group; n = 8} on total weight (TW), percent fat (% fat), lean body weight (LBW), and RMR during an 8 week study. Both groups met 3 days/week for 30-45 min/day to perform a specific exercise or flexibility routine. The DWT group performed three sets of ten lifts on seven resistive exercises, under supervision, while the DO group performed a set routine designed to increase flexibility but result in no appreciable exercise. Subjects met weekly with a Registered Dietitian to provide information regarding nutritional and caloric content of Food, as well as behavior modification techniques. Results revealed non-Significant treatment effects between the groups on the variables RMR, % fat, and LBW. A treatment effect was observed for TW, with the DO group significantly losing more weight. Total weight and % fat significantly decreased in both groups from pre to posttest. A significant difference was noted for the DWT group from 4 weeks - 8 weeks in RMR, although there was no effect from baseline - 8 weeks. Thus, resistive exercise when added to caloric restriction, increases strength, but results in Slower weight loss when compared to diet only subjects while resulting in similar losses in % fat and total weight.