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The movement of people (aka human mobility) impacts several sectors of society such as health, security, economics and politics. Studying specific patterns in mobility such as gender is a complex task because analysing a single dimension requires a rich understanding of the wide range of mechanisms and interactions that can shape the mobility of women and men. In this thesis, we focus on gender groups to broadly understand their mobility patterns, which might reflect (and influence) inequalities from cultural constructs and the labour market. Cultural constructs impose different roles on women and men, translating into how each gender participates in the labour market. Women are usually pressured to participate in jobs related to care and household responsibilities, while men usually take jobs related to leadership and high financial return. In this way, job sectors have an imbalanced participation of each gender, which in turn, reflects in how people move in space and time. This thesis presents the spatio-temporal patterns in the mobility of women and men for four countries: Brazil, Colombia, the United States of America and the United Kingdom. We contribute to the literature with a novel mobility pattern - mobility diversity - that estimates the spatial distribution of mobility across metropolitan areas and unveils differences in the mobility of women and men. Furthermore, we demonstrate the existence of two profiles of cities that share similar mobility patterns that can contribute to the understanding of systematic issues in mobility. Cultural constructs, labour market, and mobility reinforce human behaviours and consequently affects inequalities feeding into the formation of new cultural constructs. To break this cycle, we study idiosyncrasies of the dimension with the most data availability: mobility.

As climate change continues to intensify, growing interest in equitable clean energy transition has emerged to address the environmental and public health impacts of aging energy infrastructure. Of special concern is aging natural gas infrastructure, which serves as a significant source of the potent greenhouse gas (GHG) methane (CH4) and poses risk to the health and safety of the public. The concentration of aging natural gas distribution pipelines in urban centers has motivated this research, examining dynamic interactions among natural gas distribution pipelines, street tree canopies, and local climate action plans. This dissertation approaches the study of urban natural gas systems using an infrastructure ecology framework – a framework to investigate the dynamic relationships among elements of built, natural, and social infrastructure. The results of three studies reported below aim to improve our knowledge of the environmental impacts of aging natural gas infrastructure in urban centers and examine policy opportunities for a clean energy transition. Using a temporal and spatial dataset of street tree condition and soil CH4 and oxygen concentrations across Brookline, MA we were able to model the impact of CH4 on the success of a street tree using the spatial Durbin model. We find that persistent exposure to CH4 and diminished oxygen in the soil pit is correlated with poor tree condition. Next, utilizing a novel virtual data collection application, we tracked the location of leak-prone natural gas distribution infrastructure along the streets of Chelsea, MA. By producing and combining this unique dataset with the comprehensive street tree inventory completed by the municipality, we examined for the first time the relationship between street tree condition and proximity to leak-prone distribution pipe. Results from this analysis were suggestive and demonstrated a need for more comprehensive spatial data collection using virtual tools that can detect dynamic changes in the infrastructure to explain phenomena we are not yet able to interpret. Findings suggest the importance of considering the location of leak-prone pipelines when planting new street trees and protecting existing mature trees. Finally, we introduce the term and conceptual framework ‘infrastructure biome’ to define and describe the interconnected and dependent built, social, and natural infrastructure systems that extend beyond jurisdictional borders. We propose that energy transition policy, specifically a transition off natural gas, would benefit from a regional collaborative policy to achieve the ambitious climate action goals of cities and states throughout the region. Using publicly available natural gas pipeline data, we examine aging and leak-prone natural gas infrastructure for the first time at a regional scale and recommend a collaborative policy to address the shared obstacle of aging natural gas infrastructure to achieve climate action goals.

Globally, there is rising interest in urban food systems. The food system encompasses the linkages between food production and consumption, the institutions who govern them, and the associated multiple sustainability outcomes of environment, economy, equity, human health and well-being (UNEP 2016). Cities thus require tools necessary to evaluate their food system in light of multiple sustainability objectives. This dissertation contributes to the literature by exploring food supply systems to cities from a trans-boundary perspective, linking multiple sustainability outcomes with actions that seek to address health and well-being within the city. We develop spatially disaggregated footprints to assess the multiple environmental impacts of water, GHG, land of both current urban food demand and future scenarios in multiple cities in India and the U.S. Key findings, organized by chapter are described below. The developed methods include five main steps of: 1) quantifying community-wide food demand (across homes, business, and industry); 2) estimating current local production; 3) estimating origins of production serving urban demand by agri-food type, quantifying spatially informed second order impacts (energy/GHG for irrigation); 4) quantifying current in- and trans-boundary environmental impact (energy/GHG, water, and land in Chapter 3). Applied to Delhi India, the analysis finds 10% of food by mass provided by local production. Further, food was the largest contributor to the city water footprint (accounting for both green and blue water) across infrastructure sectors. Food activities also shaped both in-boundary energy and water flows, particularly with the activities of cooking, and urban agriculture respectively. Chapter 3 uses a baseline from Chapter 2 to assess the contribution of city-scale actions to the overall food system’s environmental impacts (expanding to include land, GHG/energy, water). Applied to Delhi, India, the analysis demonstrates that city-scale action can rival typical food policy interventions that occur at larger scales, although no single city-scale action can rival in all three environmental impacts. In particular, ii improved food-waste management within the city (7% system-wide GHG reduction) matches the GHG impact of pre-consumer trans-boundary food waste reduction. The systems approach is particularly useful in illustrating key tradeoffs and co-benefits. For instance, multiple diet shifts that can reduce GHG emissions have trade-offs that increase water and land impacts. Improving the nutrition status for the bottom 50% of the population to the median diet is accompanied by proportionally smaller increases of water, GHG, and land impacts (4%, 9%, and 8%, systemwide): increases that can be offset through simultaneous city-scale actions, e.g., improved food-waste management. Chapter 4 analyses the food systems of 9 different cities within a single country (India). Taking into account differences of unique economies, socio-cultural characteristics and supply chains finds variation across food systems. This work connects urban food demand of consumers and producers incorporating differences of diet and socio- economic data with supply chain data with location of production to inform food miles and environmental impacts across cities. The ratio of consumers to producers largely shapes community-wide food demand, as well as substantial differences in residential diet. Differences of residential diet result in a variation of per capita resource use of 91% (range of 600-1,148; median of 771 m3/capita) for water, 35% for greenhouse gas (GHG) (1st and 2nd order impacts) (range of 0.29-0.45; median of 0.39 t CO2e per capita) and 141% for land (range of 0.12-0.28; median of 0.14 ha per capita). The computation of GHG impacts includes 2nd order impacts (emissions from irrigation), which exhibit even greater variation of 1326% across city per capita consumption (range of 0.02 to 0.29; median of 0.18 t CO2e) accounting for 6-63 % of total combined 1st and 2nd order GHGs. Levels of under-nutrition also vary by city, with the average residential diet of all but two cities (Pondicherry and Delhi) falling below the national recommendations for caloric intake. Three cities (Ahmadabad, Rajkot, Chennai) fall below the recommended protein intake, suggesting an important role for cities in national food security agendas. Food miles vary between cities, with the range of 196 (Pondicherry) to 1,137 (Chennai) km/ton. It is interesting to note, however, that even the highest, (Chennai) is less than U.S. average of >1600 km/t. We also evaluate supply chain risk in terms of the water scarcity of food producing regions that serve cities. The food producing locations on average, are less water scarce than the watersheds local to the urban environments, suggesting the water-intensive large-scale agriculture would be best located at a distance from urban centers, away from competing demands. Chapter 5 further expands the systems framework to the U.S. This work compares the Indian analyses of Pondicherry and Delhi with Minneapolis (Hennepin County) and New York City in the United States, illustrating the wide-spread applicability of these methods, despite differing levels of data availability and substantial differences of food system structure (i.e. differences of diets, levels of local production, processing, etc). This work combines bottom-up and top-down methods to overcome data limitations of the U.S food system, specifically with respect to community-wide flows encompassing homes, businesses, and industries as well as assessing the sensitivity of the supply chain to location of production. The baseline analysis of the four cities finds that 2nd order contribution to GHG impact of per capita food demand is much lower in the U.S. than India due to a higher contribution of meat emissions to total diet and greater energy efficiency of irrigation in the U.S. The scenario analysis provides similar findings across all four cities, with diet change and food waste management as key levers to mitigate environmental impact, though with the distinction of pre-consumer food waste playing a larger role than Indian cities, while post-consumer waste management is more important in U.S cities. Over all, the methods of this dissertation can inform policy in diverse cities despite some data limitations. This provides a timely contribution to cities eager for analysis tools that will help guide progress towards the many objectives of urban food systems.

As the twenty-first century unfolds with newly formed degrees of hypercomplex interactions and reactions amongst space, time, economy, politics, social dynamics, and cultural paradigms, we are observing new typologies of urbanism that are different in kind, rather than degree, from the previous “urban” upon which the vast majority of present theoretical and practical discourse has been based. The techniques, strategies, and methodologies of the twentieth-century no longer serve to adequately represent or to explain the phenomena of today’s incipient mega-cities. A new vocabulary must be developed. A new way of seeing is required in order to understand and therefor to operate within these new conditions. The operational drawing thus becomes a functional methodological alternative. By conceptualizing urban zones of operational conditions within a field of probability, one may understand the hyper-urban space as a series of operational paradigms within a networked matrix, whereby form and special arrangement are no longer the parameters of measurement. In order to de-couple the presumption of a non-real spatio-formal reading of urbanity from the operational patterns of urbanity as real observed phenomena, and moreover to represent and communicate these patterns, a new form of mapping is required. Operational mapping is based upon observed phenomena of social interaction, economic exchange networks, data and communications networks, political territories, infrastructural parasitism, and environmental pressurization as it unfolds in both real and fictive space. Jakarta serves as an Ideal case-study, from which this methodology has been developed. As a very real case of hyper-complexity, and the explosive terrain of new mega-cities, to observe and “map” Jakarta is to observe and map the future of the world itself.

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.

The role of leadership in the resilience of urban systems is poorly understood. Leadership can be thought of as a complex practice, where the functions of leadership emerge from the relationships amongst actors, systems and institutions. There are five theorized functions of Complexity Leadership: Community Building, Information Gathering, Information Using, Generative and Administrative. The purpose of this dissertation was to explore the connection, if any, between Complexity Leadership and the resilience of urban systems.  This was explored in the context of two cases in Asheville, NC: the Residents' Council of Public Housing of Asheville and Rainbow Community School. The Residents' Council is a non profit that represents residents’ interests; Public Housing in Asheville is a typical for a 100k small city. The case documents some of the Residents' Council's attempt to adopt Dynamic Governance, a set of self-organizing governance practices. Rainbow Community School is a private k-8 school, recognized internationally as an Ashoka Change-Maker School for its innovative model of education. Data was collected through a hybrid of traditional ethnographic techniques and distributed ethnography. Data was analyzed inductively, using a combination of qualitative analysis and set theoretic analysis. The research generated findings of three kinds.  First, complexity leadership was necessary but not sufficient to account for the observed resilience qualities. To explain the observed coordination across other functions and capacity to engage with mystery , this research theorizes an additional function of Complexity Leadership—a Spiritual function. Second, individual strategic leadership played a role in fostering resilience through strengthening weak functions of complexity leadership. Third, resilience qualities emerged over time through the process of Panarchy. Spiritual leadership plays a role in fostering Panarchy through creating conditions for cross-scale resonance. The dissertation closes with the contributions of this research to theory, practice, and methods for research in complex urban systems.

Globalization presents challenges to emerging economies, as exports from such countries typically consist of standardized outputs. In response, the new orthodoxy of market liberalization shows mixed technological upgrading results because it fails to account for cross-national, let alone, sub-national variations in institutional capacities. Literature highlights the central role of regional (subnational) economies in driving the global economy through productivity and innovation boosts from agglomerative forces. In emerging countries, the effectiveness of regional agglomerations is hampered by the negative impacts of over-urbanization. This problem is worsened in urban-primate settlement patterns involving very large primary cities and no comparable secondary urban areas. Thus, national reforms may have unequal subnational upgrading impacts because of the inter-regional heterogeneity in agglomerative, urbanization and institutional capacities. In this dissertation consisting of three papers, I explore the above issues through the case of India's manufacturing sector in the post-1991 `delicensing' reforms era (1990 to 2005). In the first paper, I construct and employ a unique indicator of technological sophistication to track regional trends in technological upgrading. I find that technological levels for delicensed industries have converged at the state-level but to lower levels of sophistication. In the second paper, I find evidence that falling technological levels coincide with the dispersion of manufacturing activities from urban centers. Urbanization agglomeration economies (variety) are positively correlated with upgrading in conjunction with capital-intensity and imported inputs into production. However, localization agglomeration economies (own industry concentration) are found to have negative impacts on upgrading across the board, pointing to issues pertaining to limited supply of regional infrastructure. In the third paper, I examine the impact of urbanization on agglomeration economies. I find that urban size thresholds - larger to largest urban areas -- play a positive mediating role on the effectiveness of agglomeration economies on upgrading. Further, very large secondary urban areas influence upgrading by attracting skilled migration. In investigating regional political contexts, I find that the reasons why political majorities and lengthy tenures choose growth in secondary urban areas do not associate with upgrading. This may indicate competing policy priorities to the neglect of the manufacturing sector.

The main purpose of this research was the development and application of Fisher Information (FI) as sustainability metric in the larger goal of building practical concepts of Sustainable Engineering. Thus, FI was studied for measuring and evaluating the sustainability of model and real systems. This work provides details on a numerical and analytical approach to estimate FI based on the identification of changes in the system’s trajectory for determining stable and unstable regimes, which might represent sustainable or unsustainable periods for different systems. Using this approach, FI was computed for: 1) Elementary functions (e.g. linear, quadratic, sinusoidal, and exponential) as a guide for interpreting various cases that include simple model systems such as: 2) A two-species Lotka-Volterra predator-prey model and 3) A wastewater nitrification system. Further, a real system characterized by the US Air Quality was assessed with FI, from 1980 to 2009. Accordingly, the sustainability of the abovementioned system described by the trends of air criteria pollutants including: 4) lead (univariate trajectory) and 5) carbon monoxide, ozone, sulfur dioxide and nitrogen dioxide (multivariate trajectory) was analyzed, as an example of the versatility of this approach. Additionally, the precision of FI computations was also examined, thereby establishing an alternative procedure for considering real systems characterized by noisy and sparse data sets, and a method for finding the proper cycle of a system was proposed. Based on this framework for evaluating and interpreting FI index, the FI-sustainability analysis of several US Metropolitan Statistical Areas was made. Thus, leading social and economic tendencies were identified, from 1970 to 2009, in order to assess local and regional sustainability in Ohio. This study comprises: 6) the cities, suburban areas, and Statistical Metropolitan Areas (MSAs) of Cincinnati, Columbus, and Cleveland, as well as 7): Akron, Cincinnati, Columbus, Cleveland, Dayton, and Toledo MSAs. Therefore, sustainable environmental management can be understood from a retrospective point of view. In this case (6 and 7), FI was computed over 39 years of study in order to identify regime changes and evaluate stable and unstable periods for MSAs in Ohio, and also compare the overall sustainable dynamic for different geographical areas. Future work will provide tools for appropriate environmental, social and economical assessment, which will be used to prevent undesirable trends when possible in these areas of study.