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<p>In the U.S, more than 5.6 million commercial buildings are in operation and some include offices, schools, and childcare centers. These large buildings have complex indoor plumbing and often drinking water chemical and microbiological safety hazards can go undocumented. Generally, the larger the building’s square footage, the greater number of building occupants potentially exposed to the drinking water and greater amount and complexity of indoor cold and hot water piping and appurtenances. Because commercial buildings routinely undergo periods of low to no water use (e.g., holidays, weekends) cold and hot water can stagnate in the plumbing. This stagnation can allow for chemical and biological drinking water quality safety to deteriorate. This thesis work was designed to examine water safety challenges in school, childcare center, and office buildings to address existing knowledge-gaps.<br></p><p><br></p><p>The study described in Chapter 1 was conducted to better understand the risks of elevated copper levels at U.S. schools and childcare centers. Study goals were to: (1) understand occurrences of copper in school and childcare center drinking water systems, (2) review acute and chronic health impacts associated with the ingestion of copper contaminated water, and (3) examine the effectiveness of remedial actions to address copper in drinking water. Of the more than 130,000 schools and 856,000 childcare centers in the U.S., only about 1.7% of all those facilities had copper drinking water testing data recorded in a federal Safe Drinking Water database since the database was created in 1992. Of these facilities that were designated public water systems, about 13% (2,332) had reported a copper drinking water exceedance. Over a period of 30 years, very few studies have been conducted to document copper levels in schools and childcare centers. Available studies reported widely different sampling protocols and remedial actions. Flushing copper contaminated water from plumbing was the most evaluated remedial action, but flushing sometimes needed to be repeated indefinitely because copper exceeded safe limits within hours after flushing stopped. In-building water treatment with ion exchange systems and orthophosphate corrosion inhibitor addition have been used. At present, there is limited data from testing for copper in schools and childcare centers as well as studies to aid building managers in identifying and remediating copper occurrences. <br></p><p><br></p><p>The study described in Chapter 2 was designed to better understand chemical and microbiological quality in a green office building due to weekend stagnation events (~60 hours per event). Specific goals were (1) to investigate characterize disinfectant, pH, as well as heavy metal and microbial contaminant levels at the building point-of-entry and fixtures throughout the building, (2) understand how water quality varied spatially and by fixture use frequency, and (3) investigate the effectiveness of remedial actions on removing the water quality problems identified. As-built plumbing drawings were used to create a sampling plan and flushing plan. The total chlorine concentration decreased during stagnation (p < 0.05) and was highest at the building entry point (max 0.8 mg/L), and lower throughout the building (max 0.28 mg/L). Total cell counts were greater on Mondays compared to Fridays (p < 0.05). Legionella spp. was highest at the fixture with zero water use recorded during the study. Copper and lead levels throughout the building increase over the weekend (p < 0.05). Copper exceeded the U.S. federal health-based drinking water limit (1.3 mg/L) at 4 of the 12 tested locations. These locations all branched off the same riser. Manual fixture flushing temporarily reduced copper levels, but copper rebounded quickly prompting the need to flush fixtures every 19 hours. Results showed that drinking water testing should be required for building water systems before occupancy permits are issued, and after an extended stagnation period to understand worst case conditions. Testing should include disinfectant level, copper, lead, and legionella. <br></p><p><br></p><p>This thesis research found that a general lack of water testing data for existing office, school, and childcare center buildings inhibited a wider understanding of water safety risks. It is recommended that building officials adopt water testing as a requirement for building occupancy certificates. Testing should also be conducted periodically during the life of the buildings especially after unusually long stagnation periods (e.g., shutdowns or holiday breaks), and in buildings where children or other sensitive populations (e.g., elderly or people with underlying conditions) are occupants. Testing should include disinfectant level, copper, lead, and legionella at the point of entry and multiple locations throughout the building, depending on fixture use and building occupants. Without water testing, occupants may continue to be exposed to water that does not meet federal safe drinking water limits and go undetected. If contamination is found, building managers should review the flushing plan and potentially consider point of use water treatment to address short- and long-term water safety problems. <br></p>

<div>Bike sharing system (BSS) is growing worldwide. Although bike sharing is viewed as a sustainable transportation mode, it still has environmental footprints from its operation (e.g., bike rebalancing using automobiles) and upstream impacts (e.g., bike and docking station manufacturing). Thus, evaluating the environmental impacts of a BSS from the life cycle perspective is vital to inform decision making for the system design and operation. In this study, we conducted a comparative life cycle assessment (LCA) of station-based and dock-less BSS in the U.S. The results show that dock-less BSS has a greenhouse gas (GHG) emissions factor of 118 g CO2-eq/bike-km in the base scenario, which is 82% higher than the station-based system. Bike rebalancing is the main source of GHG emissions, accounting for 36% and 73% of the station-based and dock-less systems, respectively. However, station-based BSS has 54% higher total normalized environmental impacts (TNEI), compared to dock-less BSS. The dock manufacturing dominants the TNEI (61%) of station-based BSS and the bike manufacturing contributes 52% of TNEI in dock-less BSS. BSS can also bring environmental benefits through substituting different transportation modes. Car trip replacement rate is the most important factor. The results suggest four key approaches to improve BSS environmental performance: 1) optimizing the bike distribution and rebalancing route or repositioning bikes using more sustainable approaches, 2) incentivizing more private car users to switch to using BSSs, 3) prolonging lifespans of docking infrastructure to significantly reduce the TNEI of station-based systems, and 4) increasing the bike utilization efficiency to improve the environmental performance of dock-less systems.</div><div>To improve the design of current BSS from the life cycle perspective, we first proposed a simulation framework to find the minimal fleet size and their layout of the system. Then we did a tradeoff analysis between bike fleet size and the rebalancing frequency to investigate the GHG emission if we rebalance once, twice and three times a day. The optimal BSS design and operation strategies that can minimize system GHG emission are identified for a dock-less system in Xiamen, China. The results show that at most 15% and 13% of the existing fleet size is required to serve all the trip demand on weekday and weekend, if we have a well-designed bike layout. The tradeoff analysis shows that the GHG emission may increase if we continue to reduce the fleet size through more frequent rebalancing work. Rebalancing once a day during the night is the optimal strategy in the base scenario. We also tested the impacts of other key factors (e.g., rebalancing vehicle fleet size, vehicle capacity and multiple depots) on results. The analysis results showed that using fewer vehicles with larger capacity could help to further reduce the GHG emission of rebalancing work. Besides, setting 3 depots in the system can help to reduce 30% of the GHG emission compared with 1-depot case, which benefits from the decrease of the commuting trip distance between depot and the serve region.</div>

<div> <p>People spend most of their time indoors. Because people’s health and productivity are highly dependent on the quality of the indoor thermal environment, it is important to provide occupants with healthy, comfortable and productive indoor thermal environment. However, inappropriate thermostat temperature setpoint settings not only wasted large amount of energy but also make occupants less comfortable. This study intended to develop a new control strategy for HVAC systems to adjust the thermostat setpoint automatically and accordingly to provide a more comfortable and satisfactory thermal environment.</p> <p>This study first trained an image classification model based on CNN to classify occupants’ amount of clothing insulation (clothing level). Because clothing level was related to human thermal comfort, having this information was helpful when determining the temperature setpoint. By using this method, this study performed experimental study to collect comfortable air temperature for different clothing levels. This study collected 450 data points from college student. By using the data points, this study developed an empirical curve which could be used to calculate comfortable air temperature for specific clothing level. The results obtained by using this curve could provide environments that had small average dissatisfaction and average thermal sensation closed to neutral.</p> <p>To adjust the setpoint temperature according to occupants’ thermal comfort, this study used mean facial skin temperature as an indicator to determine the thermal comfort. Because when human feel hot, their body temperature would rise and vice versa. To determine the correlation, we used a long wave infrared (LWIR) camera to non-invasively obtain occupant’s facial thermal map. By processing the thermal map with Haar-cascade face detection program, occupant’s mean facial skin temperature was calculated. By using this method, this study performed experimental study to collect occupant’s mean facial skin temperature under different thermal environment. This study collected 225 data points from college students. By using the data points, this study discovered different intervals of mean facial skin temperature under different thermal environment. </p> <p>Lastly, this study used the data collected from previous two investigations and developed a control platform as well as the control logic for a single occupant office to achieve the objective. The measured clothing level using image classification was used to determine the temperature setpoint. According to the measured mean facial skin temperature, the setpoint could be further adjusted automatically to make occupant more comfortable. This study performed 22 test sessions to validate the new control strategy. The results showed 91% of the tested subjects felt neutral in the office</p> </div> <br>

<p> According to the World Health Organization, long-term exposures to heavy metal toxicants such as arsenic (As) and lead (Pb), even at the parts per billion (ppb, μg/L) level, can cause severe health problems such as cancer, skin lesions, and cardiovascular diseases. Therefore, an accurate and rapid heavy metal toxicant monitoring technique is needed. This research investigated the proof-of-the concept of a portable sensor for detecting As and Pb in water. The sensor system utilized a Quartz Crystal Microbalance - QCM (openQCM w-i2) system interfaced with a computer as the sensing platform. It was further integrated with a peristaltic pump and required tubing to create the integrated sensing system. It used a 10 MHz AT-cut quartz crystal gold electrode as the sensing substrate. For the determination of As in water, dithiothreitol (DTT) was used as the ligand to be deposited on the gold electrode using the Self-assembly-monolayer method (SAM). For the determination of Pb, a combination of ligands (Chitosan, Glutaraldehyde, and lead ionophore II - CGL) was used and deposited on the gold electrode using the spin-coating method. The system was tested for As in water with specific concentrations (0, 50, 100, and 200 ppb) under laboratory conditions. Similarly, the system was tested for Pb in water with different concentrations (0, 10, 25, 50, and 100 ppb) under laboratory conditions. The resulted change of frequency (with respect to time, in seconds) of the QCM system to different concentrations of the individual analyte was recorded. Subsequently, the recorded data were analyzed to determine the correlation model and coefficient of determination, R2. The maximum R2 values for detecting As and Pb were 0.963 and 0.991, respectively. Thus, this proof-of-the-concept study using the developed QCM-based sensing system for detecting As and Pb in water was successful.</p>

<div>Machine tools are an important piece of manufacturing equipment that are widely used throughout many industries. Machine tools shape and form raw materials into desired products through processes such as grinding, cutting, bending, and forming, and when they perform these operations, they consume large amounts of energy. Due to the significant energy consumption, machine tools have a large environmental footprint. Addressing the environmental footprint of machine tools through energy reduction is important to addressing manufacturing and industry’s footprint. One strategy with great potential to reduce machine tool energy consumption is lightweighting. Lightweighting is a design strategy that reduces the mass of moving components with a goal of reducing energy consumption. This strategy is effective since a greater mass requires more energy to move. Lightweighting has had great success in the transportation sector where lightweight materials and lightweight design strategies have been implemented. There has been some work to explore the potential benefits of lightweighting machine tools, however an in-depth study relating mass to energy consumption in machine tools along with exploring other potential concerns, i.e., impact on dynamics and cost, is required.</div><div>To explore the lightweighting of machine tools, a lightweighting application along with models are proposed to investigate the connection between mass and energy in machine tools and potential concerns associated with lightweighting, i.e., decreased dynamic performance and increased machine tool cost. First, a method to reduce the mass of a vertical milling machine tool table is proposed. This method will include the implementation of a sandwich panel for the table while optimizing the structure of the table to maximize its strength and minimize its mass. Following, to link mass to energy consumption, an energy model is proposed to quantify the energy required to drive the table throughout the use of the machine, including cutting and non-cutting moves. In addition to modeling energy, this model will explore the role of motor sizing in the energy consumption of the drive system. To address dynamic concerns resulting from lightweighting, a dynamic model is proposed. This model will provide insight into the dynamic performance of the table and explore the impact of lightweighting on machine tool performance. Finally, a cost model of machine tools is proposed to study the impact of lightweighting on cost. Machine tool cost drivers will be explored along with the role that design complexity has on purchase price.</div><div>This dissertation provided a proof of concept for a lightweighting application through the sandwich panel design of the slide table. The energy model built considering the lightweight table provided a link between the mass and energy consumption in the machine tool. It was shown that more than 30% of the drive system energy could be saved by lightweighting the table. A 30% savings is substantial, especially if applied to multiple systems throughout the machine tool. The static and dynamic models showed that designing lightweight components can be accomplished without sacrificing performance. Various design tools, e.g., finite element analysis, can be used to address static and dynamic concerns. The cost model showed how lightweighting will not increase the cost of the machine tool and therefore will not discourage machine builders from implementing lightweighting to reduce energy consumption.</div><div>The contributions of this research are summarized as follows:</div><div>1.A shape optimization method to design the sandwich panel table, accomplished through a genetic algorithm. This provides a lower-cost lightweighting application.</div><div>2.A mechanistic model linking mass to energy consumption. This provides insight into design considerations required to implement lightweighting</div><div>3.Static and dynamic models of the milling machine slide table. These provide understanding of how lightweighting affects the performance machine tools</div><div>4.A cost model of milling machines. This provides insight into how lightweighting affects the machine tool cost</div><div><br></div>

<p>Additive manufacturing (AM) can be an advantageous substitute to various traditional manufacturing techniques. Due to the ability to rapidly create products, AM has been traditionally used to prototype more efficiently. As the industry has progressed, however, use cases have gone beyond prototyping into production of complex parts with unique geometries. Amongst the most popular of AM processes is fused deposition modeling (FDM). FDM fabricates products through an extrusion technique where plastic filament is heated to the glass transition temperature and extruded layer by layer onto a build platform to construct the desired part. The purpose of this research is to elaborate on the potential of this technology, while considering environmental impact as it becomes more widespread throughout industry, research, and academia.</p> <p>Although AM consumes resources more conservatively than traditional methodologies, it is not free from having environmental impacts. Several studies have shown that additive manufacturing can affect human and environmental health by emitting particles of a dynamic size range into the surrounding environment during a print. To begin this study, chapters investigate emission profiles and characterization of emissions from FDM 3D printers with the intention of developing a better understanding of the impact from such devices. Background work is done to confirm the occurrence of particle emission from FDM using acrylonitrile butadiene styrene (ABS) plastic filament. An aluminum bodied 3D printer is enclosed in a chamber and placed in a Class 1 cleanroom where measurements are conducted using high temporal resolution electrical low-pressure impactor (ELPI), scanning mobility particle sizer (SMPS), and optical particle sizer (OPS), which combined measure particles of a size range 6-500nm. Tests were done using the NIST standard test part and a honeycomb infill cube. Results from this study show that particle emissions are closely related to filament residence time in the extruder while less related to extruding speed. An initial spike of particle concentration is observed immediately after printing, which is likely a result of the long time required to heat the extruder and bed to the desired temperature. Upon conclusion of this study, it is theorized that particles may be formed through vapor condensation and coagulation after being released into the surrounding environment.</p> <p>With confirmation of FDM ultrafine particle emission at notable concentrations, an effort was consequently placed on diagnosing the primary cause of emission and energy consumption based on developed hypotheses. Experimental data suggests that particle emission is mainly the result of condensing and agglomerating semi-volatile organic compounds. The initial emission spike occurs when there is dripping of semi-liquid filament from the heated nozzle and/or residue left in the nozzle between prints; this supports the previously stated hypothesis regarding residence time. However, the study shows that while printing speed and material flow influence particle emission rate, the effects from these factors are relatively insignificant. Power profile analysis indicates that print bed heating and component temperature maintaining are the leading contributors to energy consumption for FDM printers, making time the primary variable driving energy input.</p> <p>To better understand the severity of FDM emissions, further investigation is necessary to diligence the makeup of the process output flows. By collecting exhaust discharge from a Makerbot Replicator 2x printing ABS filament and diffusing it through a type 1 water solution, we are able to investigate the chemical makeup of these compounds. Additional exploration is done by performing a filament wash to investigate emissions that may already be present before extrusion. Using solid phase micro-extraction, contaminants are studied using gas chromatography mass spectrometry (GCMS) thermal desorption. Characterization of the collected emission offers more comprehensive knowledge of the environmental and human health impacts of this AM process.</p> <p>Classification of the environmental performance of various manufacturing technologies can be achieved by analyzing their input and output material, as well as energy flows. The unit process life cycle inventory (UPLCI) is a proficient approach to developing reusable models capable of calculating these flows. The UPLCI models can be connected to estimate the total material and energy consumption of, and emissions from, product manufacturing based on a process plan. The final chapter focuses on using the knowledge gained from this work in developing UPLCI model methodology for FDM, and applying it further to the second most widely used AM process: stereolithography (SLA). The model created for the FDM study considers material input/output flows from ABS plastic filament. Energy input/output flows come from the running printer, step motors, heated build plate, and heated extruder. SLA also fabricates parts layer by layer, but by the use of a photosensitive liquid resin which solidifies when cured under the exposure of ultraviolet light. Model material input/output flows are sourced from the photosensitive liquid resin, while energy input/output flows are generated from (i) the projector used as the ultraviolet light source and (ii) the step motors. As shown in this work, energy flow is mostly time dependent; material flows, on the other hand, rely more on the nature of the fabrication process. While a focus on FDM is asserted throughout this study, the developed UPLCI models show how conclusions drawn from this work can be applied to different forms of AM processes in future work.</p>

<div>Accurate prediction of electricity demand is a critical step in balancing the grid. Many factors influence electricity demand. Among these factors, climate variability has been the most pressing one in recent times, challenging the resilient operation of the grid, especially during climatic extremes. In this dissertation, fundamental challenges related to accurate characterization of the climate-energy nexus are presented in Chapters 2--4, as described below. </div><div><br></div><div>Chapter 2 explores the cost of neglecting the role of humidity in predicting summer-time residential electricity consumption. Analysis of electricity demand in the CONUS region demonstrates that even though surface temperature---the most widely used metric for characterising heat stress---is an important factor, it is not sufficient for accurately characterizing cooling demand. The chapter proceeds to show significant underestimations of the climate sensitivity of demand, both in the observational space as well as under climate change. Specifically, the analysis reveals underestimations as high as 10-15% across CONUS, especially in high energy consuming states such as California and Texas. </div><div><br></div><div>Chapter 3 takes a critical look at one of the most widely used metrics, namely, the Cooling Degree Days (CDD), often calculated with an arbitrary set point temperature of 65F or 18.3C, ignoring possible variations due to different patterns of electricity consumption across different regions and climate zones. In this chapter, updated values are derived based on historical electricity consumption data across the country at the state level. Chapter 3 analysis demonstrates significant variation, as high as +-25%, between derived set point variables and the conventional value of 65F. Moreover, the CDD calculation is extended to account for the role of humidity, in the light of lessons learnt in the previous chapter. Our results reveal that under climate change scenarios, the air-temperature based CDD underestimates thermal comfort by as much as ~22%.</div><div><br></div><div>The predictive analytics conducted in Chapter 2 and Chapter 3 revealed a significant challenge in characterizing the climate-demand nexuses: the ability to capture the variability at the upper tails. Chapter 4 explores this specific challenge, with the specific goal of developing an algorithm to increase prediction accuracy at the higher quantiles of the demand distributions. Specifically, Chapter 4 presents a data-centric approach at the utility level (as opposed to the state-level analyses in the previous chapters), focusing on high-energy consuming states of California and Texas. The developed algorithm shows a general improvement of 7% in the mean prediction accuracy and an improvement of 15% for the 90th quantile predictions.</div>

<div>The security, resilience and sustainability of water supply in urban areas are of major concern in cities around the world. Their dynamics and long-term trajectories result from external change processes, as well as adaptive and maladaptive management practices aiming to secure urban livelihoods. This dissertation examines the dynamics of urban water systems from a social-ecological-technical systems perspective, in which infrastructure and institutions mediate the human-water-ecosystem relationship. </div><div><br></div><div>The three concepts of security, resilience and sustainability are often used interchangeably, making the achievement of goals addressing such challenges somewhat elusive. This becomes evident in the international policy arena, with the UN Sustainable Development Goals being the most prominent example, in which aspirations for achieving the different goals for different sectors lead to conflicting objectives. Similarly, the scientific literature remains inconclusive on characterizations and quantifiable metrics. These and other urban water challenges facing the global urban community are discussed, and research questions and objectives are introduced in Section 1. </div><div><br></div><div>In Section 2, I suggest distinct definitions of urban water security, resilience and sustainability: Security refers to the state of system functioning regarding water services; resilience refers to ability to absorb shocks, to adapt and transform, and therefore describes the dynamic, short- to medium-term system behavior in response to shocks and disturbances; sustainability aims to balance the needs in terms of ecology and society (humans and the economic systems they build) of today without compromising the ability to meet the needs of future generations. Therefore, sustainability refers to current and long-term impacts on nature and society of maintaining system functions, and therefore affects system trajectories. I suggest that sustainability should include not only local effects, but consider impacts across scales and sectors. I propose methods for the quantification of urban water security, resilience and sustainability, an approach for modeling dynamic water system behavior, as well as an integrated framework combining the three dimensions for a holistic assessment of urban water supply systems. The framework integrates natural, human and engineered system components (“Capital Portfolio Approach”) and is applied to a range of case study cities selected from a broad range of hydro-climatic and socio-economic regions on four continents. Data on urban water infrastructure and services were collected from utilities in two cities (Amman, Jordan; Ulaanbaatar, Mongolia), key stakeholder interviews and a household survey conducted in Amman. Publicly available, empirical utility data and globally accessible datasets were used to support these and additional case studies. </div><div><br></div><div>The data show that community adaptation significantly contributes to urban water security and resilience, but the ability to adapt is highly heterogeneous across and within cities, leading to large inequality of water security. In cities with high levels of water security and resilience, adaptive capacity remains latent (inactive), while water-insecure cities rely on community adaptation for the self-provision of services. The framework is applied for assessing individual urban water systems, as well as for cross-city comparison for different types of cities. Results show that cities fall along a continuous gradient, ranging from water insecure and non-resilient cities with inadequate service provision prone to failure in response to extant shock regimes, to water secure and resilient systems with high levels of services and immediate recovery after shocks. Although limited by diverse constraints, the analyses show that urban water security and resilience tend to co-evolve, whereas sustainability, which considers local and global sustainable management, shows highly variable results across cities. I propose that the management of urban water systems should maintain a balance of security, resilience and sustainability.</div><div><br></div><div>The focus in Section 3 is on intra-city patterns and mechanisms, which contribute to urban water security, resilience and sustainability. In spite of engineering design and planning, and against common expectations, intra-city patterns emerge from self-organizing processes similar to those found in nature. These are related to growth processes following the principle of preferential attachment and functional efficiency considerations, which lead to Pareto power-law probability distributions characteristic of scale-free-like structures. Results presented here show that such structures are also present in urban water distribution and sanitary sewer networks, and how deviation from such specific patterns can result in vulnerability towards cascading failures. In addition, unbounded growth, unmanaged demand and unregulated water markets can lead to large inequality, which increases failure vulnerability. </div><div><br></div><div>The introduction of infrastructure and institutions for providing urban water services intercedes and mediates the human-water relationship. Complexity of infrastructural and institutional setups, growth patterns, management strategies and practices result in different levels of disconnects between citizens and the ecosystems providing freshwater resources. “Invisibility” of services to citizens results from maximized water system performance. It can lead to a lack of awareness about the effort and underlying infrastructure and institutions that operate for delivering services. Data for the seven cities illustrate different portfolios of complexity, invisibility and disconnection. Empirical data gathered in a household survey and key stakeholder interviews in Amman reveals that a misalignment of stakeholder perceptions resulting from the lack of information flow between citizens and urban managers can be misguiding and can constrain the decision-making space. Unsustainable practices are fostered by invisibility and disconnection and exacerbate the threats to urban water security and resilience. Such challenges are investigated in the context of urban water system traps: the poverty and the rigidity trap. Results indicate that urban water poverty is associated with local unsustainability, while rigidity traps combined with urban demand growth gravitate towards global unsustainability. </div><div><br></div><div>Returning to the city-level in Section 4, I investigate urban water system evolution. The question how the trajectories of urban water security, resilience and sustainability can be managed is examined using insights from hydrological and social-ecological systems research. I propose an “Urban Budyko Landscape”, which compares urban water supply systems to hydrological catchments and highlights the different roles of supply- and demand-management of water and water-related urban services. A global assessment of 38 cities around the world puts the seven case studies in perspective, emphasizing the relevance of the proposed framework and the representative, archetypal character of the selected case studies. </div><div><br></div><div>Furthermore, I examine how managing for the different dimensions of the CPA (capital availability, robustness, risk and sustainable management) determines the trajectories of urban water systems. This is done by integrating the CPA with the components of social-ecological system resilience, which explain how control of the different components determines the movement of systems through states of security and resilience in a stability landscape. Finally, potential feedbacks resulting from the global environment are investigated with respect to the role that globally sustainable local and regional water management can play in determining the trajectories of urban water systems. These assessments demonstrate how the impact of supply-oriented strategies reach beyond local, regional and into global boundaries for meeting a growing urban demand, and come at the cost of global sustainability and communities elsewhere.</div><div><br></div><div>Despite stark differences between individual cities and large heterogeneities within cities, convergent trends and patterns emerge across systems and are revealed through application of the proposed concepts and frameworks. The implications of these findings are discussed in Section 5, and are summarized here as follows: </div><div>1) The management of urban water systems needs to move beyond the security and resilience paradigms, which focus on current system functioning and short-term behavior. Sustaining a growing global, urban population will require addressing the long-term, cross-scale and inter-sector impacts of achieving and maintaining urban water security and resilience. </div><div>2) Emergent spatial patterns are driven by optimization for the objective functions. Avoiding traps, cascading failure, extreme inequality and maintaining global urban livability requires a balance of supply- and demand-management, consideration of system complexity, size and reach (i.e., footprint), as well as internal structures and management strategies (connectedness and modularity).</div><div>3) Urban water security and resilience are threatened by long-term decline, which necessitates the transformation to urban sustainability. The key to sustainability lies in experimentation, modularization and the incorporation of interdependencies across scales, systems and sectors.</div><div><br></div>