To prepare for an urban influx of 2.5 billion people by 2050, it is critical to create cities that are lowcarbon, resilient, and livable. Cities not only contribute to global climate change by emitting the majority of anthropogenic greenhouse gases but also are particularly vulnerable to the effects of climate change and extreme weather. We explore options for establishing sustainable energy systems by reducing energy consumption, particularly in the buildings and transportation sectors, and providing robust, decentralized, and renewable energy sources. Through technical advancements in power density, city-integrated renewable energy will be better suited to satisfy the high-energy demands of growing urban areas. Several economic, technical, behavioral, and political challenges need to be overcome for innovation to improve urban sustainability.S ince 2007, a greater percentage of the global population has been living in urban areas than in rural areas. Increased urbanization is expected to continue, with two-thirds of the world's population projected to live in urban areas by 2050, a net urban influx of 2.5 billion people (1). Cities today are generally not equipped to address dramatic urban growth and strain on existing infrastructure in a sustainable way, especially with respect to their energy systems.To be sustainable, cities must themselves, or in the resources that they command, become lowcarbon, resilient, and livable (2). Although there can be considerable variation in methods for evaluating the emissions footprint of cities (3), with 54% of the population living in urban areas, it is estimated that cities are currently responsible for 60 to 70% of anthropogenic greenhouse gas emissions (4). The two main strategies for transitioning to a low-carbon city are to shift from fossil fuels to cleaner energy sources and to reduce urban energy consumption levels. The low-carbon transition can be accomplished through energyefficiency measures, behavioral interventions, and incorporating carbon sinks such as urban parks. Cities and their energy systems should also be resilient to natural and human-made threats (2). The energy systems of cities are increasingly vulnerable to the effects of climate change and extreme weather, including storms, flooding, and sea-level rise, and also to natural and humaninduced disasters. In addition, urban energy systems directly affect the well-being and happiness of urban inhabitants. Health conditions, economic competitiveness, cultural appeal, and social, gender, and racial equality are influenced by high-energy sectors such as transportation, food production, and water quality.Here we evaluate some of the more promising recent technological advancements that could help urban areas become sustainable cities. Many opportunities exist, but focusing on city-integrated renewable energy-defined as distributed, nonfossil fuel energy generated locally in urban areas-has the potential to help cities meet several sustainability needs. Many of these renewable sources increase regional ener...

The rooftop solar industry in the United States   has experienced dramatic growth-roughly 50% per year since 2012, along with steadily falling prices. Although the opportunities this affords for clean, reliable power are transformative, the benefits might not accrue to all individuals and communities. Combining the location of existing and potential sites for rooftop photovoltaics (PV) from Google's Project Sunroof and demographic information from the American Community Survey, the relative adoption of rooftop PV is compared across census tracts grouped by racial and ethnic majority. Black-and Hispanic-majority census tracts show on average significantly less rooftop PV installed. This disparity is often attributed to racial and ethnic differences in household income and home ownership. In this study, significant racial disparity remains even after we account for these differences. For the same median household income, black-and Hispanic-majority census tracts have installed less rooftop PV compared with no-majority tracts by 69 and 30%, respectively, while white-majority census tracts have installed 21% more. When correcting for home ownership, black-and Hispanic-majority census tracts have installed less rooftop PV compared with no-majority tracts by 61 and 45%, respectively, while white-majority census tracts have installed 37% more.

Distributed photovoltaics (PV) have played a critical role in the deployment of solar energy, currently making up roughly half of the global PV installed capacity. However, there remains significant unused economically beneficial potential. Estimates of the total technical potential for rooftop PV systems in the United States calculate a generation comparable to approximately 40% of the 2016 total national electric-sector sales. To best take advantage of the rooftop PV potential, effective analytic tools that support deployment strategies and aggressive local, state, and national policies to reduce the soft cost of solar energy are vital. A key step is the low-cost automation of data analysis and business case presentation for structure-integrated solar energy. In this paper, the scalability and resolution of various methods to assess the urban rooftop PV potential are compared, concluding with suggestions for future work in bridging methodologies to better assist policy makers.

The electric power grid is a critical societal resource connecting multiple infrastructural domains such as agriculture, transportation, and manufacturing. The electrical grid as an infrastructure is shaped by human activity and public policy in terms of demand and supply requirements. Further, the grid is subject to changes and stresses due to diverse factors including solar weather, climate, hydrology, and ecology. The emerging interconnected and complex network dependencies make such interactions increasingly dynamic, posing novel risks, and presenting new challenges to manage the coupled human-natural system. This paper provides a survey of models and methods that seek to explore the significant interconnected impact of the electric power grid and interdependent domains. We also provide relevant critical risk indicators (CRIs) across diverse domains that may be used to assess risks to electric grid reliability, including climate, ecology, hydrology, finance, space weather, and agriculture. We discuss the convergence of indicators from individual domains to explore possible systemic risk, i.e., holistic risk arising from cross-domain interconnections. Further, we propose a compositional approach to risk assessment that incorporates diverse domain expertise and information, data science, and computer science to identify domain-specific CRIs and their union in systemic risk indicators. Our study provides an important first step towards datadriven analysis and predictive modeling of risks in interconnected human-natural systems.

Abstract-The technically recoverable global wave energy resource is estimated to be between 2 PWh/year and 5.5PWh/year, approximately 12% and 32% of global electricity consumption. Despite wave energy's vast global potential, there has been relatively little commercial deployment to date. There is large variation in both the current estimated and future expected electricity generation costs associated with wave technologies. This paper quantifies a forecasted levelized cost of electricity (LCOE) for wave energy by performing a two-stage Monte Carlo simulation, considering both the variability in current LCOE estimates and uncertainty in the one-factor learning rate. We compare the forecasted LCOE to wave energy targets of the European Union and U.S. Department of Energy and show the criticality of support mechanisms to achieve learning rates that lead to economic competitiveness in the utility-scale markets.

Recent studies suggest that small scale (5–10kW) distributed solar Rankine combined heat and power could be a viable renewable energy strategy for displacing fossil fuel use in residential buildings, small commercial buildings, or developing rural communities. One of the primary obstacles of scaling down solar Rankine technology to this level is finding an appropriate expander design. This paper considers the radial-inflow turbine for such an application. Although well-tested methodologies exist for design analysis of radial inflow turbines, existing analysis tools are generally focused on machines using a combustion gases in a Brayton cycle. Use of Rankine cycle working fluids under conditions optimal for small scale Rankine solar systems result in turbine operating conditions that can be dramatically different from those in combustion-based Brayton cycle power systems. This investigation explored how analysis tools developed by NASA and others for conventional Brayton cycle power systems can be adapted to analyze and design radial inflow expanders for small scale Rankine solar combined heat and power systems. Using a 1D model derived from analysis methodologies used by NASA for conventional aerospace gas turbine power applications, the effect of reduced power output on performance is explored. Since the model contains several non-dimensional variables, a variety of geometries are surveyed, and performance sensitivity to various geometric parameters is observed. The interplay between radial inflow turbine performance and cycle efficiency for the system is examined in detail. Several fluids are compared to access how critical temperature and the shape of the saturation dome affect thermodynamic performance of the cycle and efficiency of the turbine. Conclusions regarding optimal fluids and geometric parameters for the radial-inflow turbine are discussed.

Over half the world's population lives in urban settings, and transportation within these regions is responsible for a substantial portion of global pollution and energy expenditures. The electrification of urban transportation offers several benefits including improved urban air quality, reduced noise, and decreased dependence on fuel imports and volatile fuel prices. Additionally, electrification programs centered in urban regions present an opportunity to provide a high degree of mobility at reduced environmental impact. However, the global environmental benefit of electrifying urban transportation will largely depend on using electricity generation sources that produce minimal emissions, such as photovoltaics. In this paper, we studied the feasibility of satisfying all urban transportation energy needs with city-integrated photovoltaics for 87 cities from 43 countries with highly varied solar resources. Of the cities studied, 11 were able to satisfy their transportation needs by covering less than 5% of the city land area with photovoltaics. Nearly half of the cities (40 cities) were able to meet their needs with less than 10% covered and the majority of cities (84%) could do so with less than 15% covered. As one would expect, cities with greater annual solar insolation generally required less photovoltaic coverage. However, annual solar insolation was not the most significant factor. Data mining with an extra-trees regressor was performed to determine the relative importance of over 200 city attributes. These attributes included factors related to urban form, existing transportation infrastructure and investment, behavioral patterns, time and energy efficiency of a variety of modes of transportation, and transportation pricing and fines. Based on relative attribute importance, policy recommendations are offered for both existing and emerging cities.

Animal-related outages (AROs) are a prevalent form of outages in electrical distribution systems. Animal-infrastructure interactions vary across species and regions, underlining the need to study the animal-outage relationship in more species and diverse systems. Animal activity has been an indicator of reliability in the electrical grid system by describing temporal patterns in AROs. However, these ARO models have been limited by a lack of available species activity data, instead approximating activity based on seasonal patterns and weather dependency in ARO records and characteristics of broad taxonomic groups, e.g., squirrels. We highlight available resources to fill the ecological data gap limiting joint analyses between ecology and energy sectors. Species distribution modeling (SDM), a common technique to model the distribution of a species across geographic space and time, paired with community science data, provided us with species-specific estimates of activity to analyze alongside spatio-temporal patterns of ARO severity. We use SDM estimates of activity for multiple outage-prone bird species to examine whether diverse animal activity patterns were important predictors of ARO severity by capturing existing variation within animal-outage relationships. Low dimensional representation and single patterns of bird activity were important predictors of ARO severity in Massachusetts. However, both patterns of summer migrants and overwintering species showed some degree of importance, indicating that multiple biological patterns could be considered in future models of grid reliability. Making the best available resources from quantitative ecology known to outside disciplines can allow for more interdisciplinary data analyses between ecological and non-ecological systems. This can result in further opportunities to examine and validate the relationships between animal activity and grid reliability in diverse systems.