Cities occupy 2% of the earth's surface, and yet consume 75% of the world's resources. As a major contributor to rapidly growing global energy expenditures, urban buildings are often designed and operated inefficiently despite their significant contributions to carbon emissions, triggering environmental deterioration locally and worldwide. Moreover, ongoing industrialization and urbanization pose challenges for achieving a more sustained and resilient built environment. The goal of this PhD research is to advance our understanding of urban building networks' thermal-energy dynamics in order to achieve sustainable energy conservation in the built environment. Considering buildings as networks rather than as stand-alone entities highlights the inextricably linked and interwoven relationship between urban micro-climates and buildings. With this approach, I strive to explore, mitigate, and optimize the mutual influences of the Inter-Building Effect (IBE) in dense urban settings through numerical and empirical analyses. My research also draws inspiration for investigating solutions to complex engineering problems from nature, as I seek to understand synergies between building and biological systems to discover innovative connections and integrate biology to transform buildings through sustainable building network designs. This dissertation contains three interdependent projects to explore, mitigate and optimize the IBE, respectively. I first developed a systematic approach to separately assess the complex interactions that constitute the IBE in dense urban settings and conducted cross-regional analyses in a dynamic simulation environment. Having disaggregated, quantified and understood the effects of mutual shading and mutual reflection within a network of buildings, I then, in the second project, examined different measures to mitigate the negative IBE impact under certain circumstances (e.g. directional reflective optical properties of building facades and thermal storage technologies). These two projects extended prior work that examined the potential for a biological system retroreflective surface to reduce IBE in urban building networks. Therefore, in my third project, I introduced a broad framework that draws parallels between natural and built environment systems through a levels-of-organization perspective leading to the search for an optimal status of the IBE. Inspired from a self-regulating phenomenon of plant density, I presented and discussed an approach to determine optimal urban building network density as an example for how this framework can support cross-level assessment. The findings expand and deepen our understanding of the IBE and provide insights on the strategies to mitigate the negative mutual impact within dense urban building networks. This research contributes a unique and holistic perspective on the interdependencies in the urban building network system. To design density-optimal building networks will become increasingly important to sustainable urban development and smart growth as clusters of dense urban settings continue to grow due to rapid urbanization and population migration in the next few decades. / Ph. D.

La pollution atmosphérique en milieu urbain a été identifiée comme une cause importante d’impacts sanitaires, y compris de décès prématurés. En particulier, les concentrations ambiantes de polluants gazeux tels que le dioxyde d’azote (NO2) et de particules (PM10 et PM2,5) sont réglementées, ce qui implique que des stratégies de réductions d’émissions doivent être mises en place pour diminuer ces concentrations dans les lieux où la réglementation correspondante n’est pas respectée. Par ailleurs, la pollution atmosphérique peut contribuer à la contamination d’autres milieux, par exemple à travers la contribution des dépôts atmosphériques à la contamination des eaux de ruissellement.Les aspects multifactoriels et multiéchelle de la pollution en ville rendent l’identification des sources difficile. En effet, le milieu urbain est un espace hétérogène caractérisé par des structures architecturales complexes (bâti ancien côtoyant un bâti plus moderne, zones résidentielles, commerciales, industrielles, axes routiers…), des émissions de polluants atmosphériques non uniformes et par conséquent une exposition de la population à la pollution qui est variable dans l’espace et le temps.La modélisation de la pollution atmosphérique urbaine a pour vocation de comprendre l’origine des polluants, leur étendue spatiale et leur niveau de concentrations/dépôt. Certains polluants ont des temps de résidence long et peuvent séjourner plusieurs semaines dans l’atmosphère (PM2,5) et donc être transportés sur de longues distances, d’autres au contraire, sont plus locaux (NOx en proximité du trafic). La répartition spatiale d’un polluant dépendra alors de plusieurs facteurs et notamment des surfaces rencontrées. La qualité de l’air, elle, dépend fortement des conditions météorologiques, du bâti (rue-canyon) et des émissions.L’objectif de cette thèse est de traiter certains de ces aspects en modélisant : (1) la pollution urbaine de fond avec un modèle de chimie-transport (Polyphemus/POLAIR3D), qui permet d’estimer les dépôts de polluants atmosphériques par type de surfaces urbaines (toits, murs et chaussées), (2) la pollution à l’échelle de la rue en intégrant explicitement les effets du bâti de manière tridimensionnelle avec d’une part un modèle multiéchelle de chimie-transport (SinG) et d’autre part un modèle de mécanique des fluides (Code_Saturne) et (3) un processus de micro-échelle qui est la réémission des particules présentes sur la chaussée par le trafic routier avec trois formulations différentes (déterministe, semi-empirique et empirique). L’intérêt de cette thèse est de pouvoir comparer et évaluer l’opérabilité et la performance de plusieurs modèles de qualité de l’air à plusieurs échelles (région, quartier et rue) afin de mieux appréhender la caractérisation de la qualité de l’air en milieu urbain / Urban air pollution has been identified as an important cause of health impacts, including premature deaths. In particular, ambient concentrations of gaseous pollutants such as nitrogen dioxide (NO2) and particulate matter (PM10 and PM2.5) are regulated, which means that emission reduction strategies must be put in place to reduce these concentrations in places where the corresponding regulations are not respected. Besides, air pollution can contribute to the contamination of other media, for example through the contribution of atmospheric deposition to runoff contamination.The multifactorial and multiscale aspects of urban make the pollution sources difficult to identify. Indeed, the urban environment is a heterogeneous space characterized by complex architectural structures (old buildings alongside a more modern building, residential, commercial, industrial zones, roads, etc.), non-uniform atmospheric pollutant emissions and therefore the population exposure to pollution is variable in space and time.The modeling of urban air pollution aims to understand the origin of pollutants, their spatial extent and their concentration/deposition levels. Some pollutants have long residence times and can stay several weeks in the atmosphere (PM2.5) and therefore be transported over long distances, while others are more local (NOx in the vicinity of traffic). The spatial distribution of a pollutant will therefore depend on several factors, and in particular on the surfaces encountered. Air quality depends strongly on weather, buildings (canyon-street) and emissions.The aim of this thesis is to address some of these aspects by modeling: (1) urban background pollution with a transport-chemical model (Polyphemus / POLAIR3D), which makes it possible to estimate atmospheric pollutants by type of urban surfaces (roofs, walls and roadways), (2) street-level pollution by explicitly integrating the effects of the building in a three-dimensional way with a multi-scale model of transport chemistry (SinG) and (3) a microscale process which is the traffic-related resuspension of the particles present on the road surface with three different formulations (deterministic, semi-empirical and empirical).The interest of this thesis is to compare and evaluate the operability and performance of several air quality models at different scales (region, neighborhood and street) in order to better understand the characterization of air quality in an urban environment